Liquid Biopsy For Early Cancer Detection Research Landscape

Generated: August 7, 2026

Report Type: Research Intelligence

Data Sources: NIH RePORTER, ClinicalTrials.gov, USPTO, PubMed

How to Use This Report

NIH funding patterns validate research direction. Knowing who is funded in your space - with what methods, in what collaborations, and at what scale - calibrates where your work fits relative to the field's momentum and reveals gaps worth pursuing.

The intelligence in this report comes primarily from our semantic analysis across the linked data, not from any single source. NIH RePORTER, ClinicalTrials.gov, USPTO, and PubMed are all publicly searchable - anyone can look up individual records. Our value is in:

• Identifying conceptually-related projects via AI semantic search rather than brittle keyword matching
• Cross-linking each project to its associated patents, clinical trials, and publications
• Synthesizing across the analyzed sample to surface patterns no single record reveals - methodological trends, collaboration networks, gap analysis, and positioning signals

The Market Context section adds external color sourced via live web search. It is supplementary to the core analysis above.

What This Report Does Not Cover

A short, upfront note on the boundaries of this analysis. We surface this so you can read everything below with the right calibration.

• Companies are in this data - non-NIH-funded internal R&D is not. SBIR/STTR grantees, academic-industry partnerships, and commercial entities receiving NIH funding do appear and carry real commercial weight. What's invisible is privately-funded R&D inside companies that doesn't intersect with an NIH grant.
• International activity is largely outside the sample. NIH RePORTER captures US grantees and their direct collaborators. Major work in Europe, China, Japan, and elsewhere is not reflected unless tied to a US-funded project.
• Linked outputs require an NIH grant acknowledgment. A clinical trial, patent, or publication only appears here if it was filed with an NIH project number. Industry-led trials, non-USPTO patents, and papers without NIH funding acks are missing - even when central to the field.
• Recent quarter activity may be incomplete. NIH RePORTER updates with a lag of several weeks; some current-fiscal-year awards may not yet be visible.
• Umbrella institutional grants are not credited to topic funding. Some trials and patents in this report are hosted under broad institutional support awards (P30 cancer centers, CTSA hubs, training grants) whose parent grant covers many programs beyond this topic. Those records appear in the trials and patents sections, but the host grants' dollars are deliberately excluded from Total Committed Funding to keep the headline number topically attributable. Real topic activity at those institutions is therefore likely higher than the funding figures alone suggest.
• Market context is web-sourced, not exhaustive - see the Sources subsection in Market Context for what was retrieved.
• Project categorization is automated. A single primary category is assigned per project by AI classification, with confidence scores. Some boundary cases (especially infrastructure vs. biotools) may be misassigned.

This is depth-over-breadth analysis - high signal on what NIH funds and produces, including its commercial recipients. For a complete literature view, supplement with broader PubMed/Web of Science searches and conference proceedings.

Executive Summary

Of 117 projects totaling $103.0M across 64 organizations, the diagnostics funding category dominates at 58.1% of projects (68 of 117) and $63.0M, with the biotools funding category second at 17.1% (20 of 117) and $14.9M. Trial activity spans 58 trials in progress, planned, or completed vs 16 terminated/suspended/withdrawn (74 total), with the terminated and withdrawn portion worth monitoring as a signal on assay-to-clinic translation friction. NIH funding was $39.7M in FY2024 and $51.2M in FY2025, though two data points do not establish a trend; FY2026 YTD stands at $10.1M and reflects a partial year through August 2026.

Within the sample, two methodological clusters dominate: cfDNA methylation analysis (multi-cancer detection and tissue-of-origin localization) and ctDNA fragment-based approaches, each pursued by multiple well-funded academic nodes. A secondary cluster around extracellular vesicles and exosomes is present but thinner relative to cfDNA, with exosome work concentrated at a small number of institutions. Multi-analyte approaches combining cfDNA with proteomics, radiomics, or microbiome signals appear in roughly a dozen projects and represent a positioning differentiation relative to single-analyte platforms. Non-plasma biofluids - urine, saliva, cerebrospinal fluid, surgical drain fluid - represent a low share of sample projects relative to their biological rationale for organ-specific cancers; whether this reflects true deprioritization or NIH-linked scope is not resolvable from this dataset. Commercial programs like GRAIL's Galleri (NHS-Galleri missed its Stage III/IV aggregate primary endpoint, while PATHFINDER 2 showed increased detection over standard of care) illustrate the gap between analytical performance and population-level endpoints that now sets the evidentiary bar for the sample's academic programs.

For researchers, the concentration of MCED work in a small number of well-funded nodes means differentiation likely requires either a novel analyte layer (e.g., fragmentomics integrated with methylation, or non-plasma biofluid validation) or a mechanistic angle on cfDNA biogenesis that the sample's 3 basic research funding category projects (2.6% of 117) leave largely open. The 4 patents in the sample - focused on mutation detection chemistry and nucleic acid assessment methods - suggest IP density is low relative to project volume, creating freedom-to-operate considerations worth examining before assay development commitments. Collaboration opportunities exist between biotools-category developers (20 of 117 projects) and diagnostics-category clinical validators, particularly where point-of-care or low-cost multiplexed platforms intersect with MCED biomarker panels targeting the reimbursement window the Miller-Meeks legislation may open around 2029.

What Surprised Us

Non-obvious findings detected algorithmically from the data, then interpreted. These are flagged hypotheses, not verified conclusions - patterns worth investigating rather than facts to act on directly. Broader NIH ratios are directional at low topic-sample counts and could reflect real gaps OR taxonomy artifacts; treat individual findings as starting points for deeper diligence.

1. A subset of highly-funded organizations publishes actively but shows no linked patents or trials in the NIH-linked sample

Four organizations collectively received $22.5M in NIH funding and produced 145 linked publications, yet show zero linked patents and zero linked trials within the scope of this analysis - a pattern that signals a potential gap between discovery output and downstream translation milestones visible through NIH acknowledgment. This matters to investors and founders because it may identify research communities generating substantial scientific output that has not yet crossed into IP protection or clinical validation as captured here, representing either a pipeline lagging behind publication pace or work that is commercializing through channels not captured in this sample to this dataset, such as commercial patents, international filings, or industry-sponsored trials. Readers scoping partnership or licensing opportunities should treat this as a starting hypothesis and investigate whether downstream activity exists outside NIH-linked records before drawing conclusions about true translation readiness. Confidence: Medium - Evidence: 4 organizations, 18 projects, $22.5M NIH funding, 145 linked publications, 0 linked trials, 0 linked patents in analyzed sample.

2. A subset of top-funded PIs hold their entire NIH-linked funding on a single project with no adjacent follow-on visible in the sample

Five PIs in the top-funded tier collectively hold $13.7M concentrated in single-project awards, with no adjacent NIH-linked follow-on projects visible in the sample - a pattern that raises questions about portfolio continuity and whether this work has a funded path forward through NIH mechanisms. For researchers and investors, concentrated single-project funding can indicate either a focused bet on a high-conviction approach or a dependency risk if the project concludes without successor funding, and the absence of follow-on in this sample does not rule out industry transitions, non-NIH renewals, or privately funded continuation that would be invisible here. This finding is worth tracking longitudinally, as the expiration of these awards without visible NIH follow-on could signal either natural project completion or a gap in sustained public investment in these research threads. Confidence: Low - Evidence: 5 PIs among top-funded slice, $13.7M combined on single-project awards, no adjacent NIH-linked follow-on visible in the sample.

Field Maturity Assessment

Note: This assessment is based on NIH-linked clinical trials, patents, and publications. It reflects patterns in the analyzed sample and may not represent the full global research landscape.

Technology Readiness: TRL 5-6

Overall Assessment: Maturing - Technology validation underway

Historical Reference Point: TRL 5-6 is comparable to where circulating tumor DNA (ctDNA) monitoring in established oncology treatment settings sat approximately in 2016-2018, when assay platforms were validated in clinic-adjacent studies but multi-site pivotal trials confirming clinical utility in unselected populations were still limited.

Based on the linked trials and publications, liquid biopsy for early cancer detection appears to sit at TRL 5-6: past proof-of-concept and into technology demonstration, with accumulating clinical evidence but no late-stage (Phase 3/4) trial activity observed in the sample. The 792 linked publications with a low 5% preprint ratio suggest a field producing predominantly peer-reviewed, consolidated science rather than speculative early-stage work, and the presence of Phase 2 activity among 19 interventional trials (of which 8 carry a phase label - a subset of the 19 interventional trials in the sample) indicates that candidate assays are being evaluated in structured clinical settings, though the absence of Phase 3/4 trials in the sample means regulatory-grade efficacy validation has not yet been captured here. The dominance of observational designs (53 of 74 total linked trials) is consistent with a field still characterizing biomarker performance across populations before committing to large-scale interventional confirmation.

Confidence: High - Evidence: 792 publications, 5% preprint ratio, 74 total linked trials including Phase 1 and Phase 2 activity, no Phase 3/4 observed, 53 observational vs. 19 interventional trials, $103.0M NIH-linked funding across 117 projects

Supporting Evidence

• Publication Maturity: With 792 linked publications, the 5% preprint ratio (39 preprints) rests on a sufficiently large denominator to be directionally interpretable: a low preprint share suggests the field is producing predominantly peer-reviewed output, consistent with a maturing literature base rather than a rapidly speculative early-stage field.

Confidence: Medium - Evidence: 792 total linked publications, 39 preprints (5% of total); preprint ratio is directionally readable at this denominator but publication-database scope limits field-level generalization

• Clinical Progression: The phase distribution across 74 linked trials - with 63 N/A-phase, 3 unknown-phase, 2 Phase 1, and 6 Phase 2 trials, and no Phase 3/4 activity observed - places the field in mid-stage clinical evaluation: structured interventional testing is underway but large-scale regulatory trials have not yet appeared in the linked sample.

Confidence: High - Evidence: 74 total linked trials, 19 interventional (8 carrying a phase label), 53 observational, Phase 2 present, Phase 3/4 absent

• IP Activity: With only 4 linked patents and 0 filed in the last two years, recency ratios are not interpretable as trend signals at this sample size; the patent signal is too thin to draw conclusions about commercial IP momentum in either direction, and the small count likely reflects NIH-linked data scope rather than a field-level IP characterization.

Confidence: Low - Evidence: 4 total linked patents, 0 recent (last 2 years); sample size precludes trend inference

Strategic Implications

For a researcher entering this space, the Phase 2 presence among 19 interventional trials (8 carrying a phase label) and the dominance of observational designs (53 of 74 trials) signal that proposals focused on biomarker validation methodology, multi-cohort harmonization, or analytical standardization are well-positioned to fill work that the current sample reflects as active but incomplete - R01 and U01 mechanisms supporting multi-site observational or early interventional studies are plausible fits given the NIH-linked funding concentration in diagnostics. NIH-linked funding across 117 projects totaled $39.7M in FY2024 and $51.2M in FY2025 (with FY2026 at $10.1M YTD through August, not comparable as a full year), though two data points do not establish a trend; researchers should not assume continued growth when sizing proposals or planning multi-year timelines. Collaborations bridging clinical oncology and assay development (bioinformatics, cfDNA biology, or multi-analyte integration) are likely to strengthen proposals, given that the field appears to be in the translational validation phase where cross-disciplinary teams have historically been competitive.

Confidence: Medium - Evidence: 74 linked trials (53 observational, 19 interventional, 8 phase-labeled), $103.0M total NIH-linked funding across 117 projects, FY2024-FY2025 funding figures from two consecutive years only

Competitive Topology

Note: Key players listed below are derived from NIH-funded project data and represent academic/research institutions. Commercial entities may not appear. The 5 clusters below are the methodological groupings the synthesis identified as most distinct in the analyzed abstracts - clusters are cross-cutting (a single project can belong to more than one), and a different cut of the data could resolve at 3 or 6 clusters rather than 5.

Among the funded projects analyzed, the competitive topology is dominated by two highly active and overlapping cfDNA-centric approaches - methylation profiling and fragmentomics/WGS - which together account for roughly 28-32 of 117 sampled projects and share infrastructure at several institutions, making them the densest and most translationally advanced zones of this research space.

Confidence: High - Evidence: approximately 30 projects collectively across these two clusters, with cross-cutting institutional activity at UCLA, Johns Hopkins, Stanford, and Fred Hutch, plus multiple clinical trials and patents.

Extracellular vesicle platforms represent a substantively distinct and active second tier (approximately 11-13 projects) with differentiated analyte biology but heterogeneous methods that have yet to converge on a standardized commercial pathway, while alternative biofluid approaches (approximately 12-14 projects) are notable for their breadth of cancer type coverage and non-plasma biofluid diversity, particularly for organ-proximal applications.

Confidence: High - Evidence: counts as noted above across City of Hope, Cornell, MGH, and alternative-biofluid institutions.

CRISPR-based and isothermal amplification biosensor platforms represent the smallest funded cluster in the sample (approximately 4-5 projects) but occupy a technically distinct niche focused on point-of-care sensitivity that has limited overlap with the dominant methylation and fragmentomics approaches.

Confidence: Medium - Evidence: 4-5 projects, no patents or trials identified in the sample.

Methodological Clusters

Confidence: High - Evidence: approximately 18-20 projects across UCLA, Johns Hopkins, Stanford, City of Hope, Moffitt, Pitt, Cedars-Sinai, USC, Fred Hutch, and Binary Genomics, with 2 companion patents from Johns Hopkins and at least 5 linked clinical trials including multi-cancer detection cohort and colorectal cancer detection studies.

Confidence: High - Evidence: approximately 11-13 projects across City of Hope, Cornell, MGH, University of Houston, SUNY Binghamton, University of Florida, UC Davis, Tulane, UIUC, Harvard Medical School, and Oregon Health and Science University, with 1 companion patent from Cornell University.

Confidence: High - Evidence: approximately 10-12 projects across Johns Hopkins, Broad Institute, Sloan-Kettering, Wisconsin, Vanderbilt, Stanford, Fred Hutch, Tufts, Dana-Farber, and UCLA, with 1 companion Dana-Farber patent and at least 3 linked clinical trials including the Broad's metastatic breast cancer prospective study and Johns Hopkins lung cancer cohort.

Confidence: Medium - Evidence: approximately 4-5 projects across UIUC, Duke, UConn, Alelopharma, and Darwin Biosciences, no companion patents or clinical trials identified in the sample.

Confidence: High - Evidence: approximately 12-14 projects across Johns Hopkins, Indiana University, Stanford, Ohio State, USC, Nord Bio, MGH, University of Utah, UCSF, Belay Diagnostics, NYU, and University of Minnesota, with 1 linked clinical trial for bladder cancer detection at Cedars-Sinai and mention of CLIA-certified test development in the Johns Hopkins CSF/saliva abstract.

Strategic Implications

For a researcher evaluating where to position a new lab or grant application, cfDNA methylation profiling is the highest-competition cluster to enter: it concentrates the most NIH investment, multiple large U01 and R01 mechanisms, and several groups already in clinical trial phases, meaning differentiation requires either a novel cancer type niche, a pre-diagnostic longitudinal design, or a methodological improvement in cost or throughput. Differentiation opportunities are stronger in CRISPR-based isothermal biosensor development and nanoplasmonic single-molecule detection, both of which have thinner NIH-linked activity in the sample and suit R33 developmental stage or SBIR/STTR mechanisms that reward sensitivity engineering and point-of-care translation. The alternative biofluid and multi-analyte cluster is well-suited to R21 exploratory mechanisms for researchers with access to specialized specimen types (urine from bladder cancer cohorts, CSF from neuro-oncology programs, saliva from head-and-neck clinics), where proximity-to-tumor enrichment provides a biological rationale that is distinct from blood-only approaches. Researchers with computational or statistical expertise should note that machine-learning integration for fragmentomics and whole-genome cfDNA analysis is an active grant target across R01 and K-award mechanisms, with several funded projects explicitly combining WGS error suppression and ML, suggesting this methodological pairing is competitive but not yet saturated.

Confidence: Medium - Evidence: approximately 5 projects explicitly combining ML with cfDNA sequencing or fragmentomics across the sample, with K08 and R01 mechanisms both represented.

White Space Analysis

This section maps what NIH-funded research covers vs. what's underrepresented within the topic scope. Private R&D, international research, and non-NIH federal funding (DoD, DARPA, industry) are not captured here. Broader-NIH counts are filtered to liquid biopsy cancer detection scope so comparisons are topically apples-to-apples. Sample counts match against title AND abstract for the analyzed project set; broader-NIH counts match against title ONLY (abstracts aren't full-text-indexed at query time), so broader counts are directional lower bounds.

Base rate for "Broader NIH" columns: every broader-NIH cell below is drawn from 2,464 NIH projects matching the liquid biopsy cancer detection scope filter - not the full ~154K RePORTER universe. Read broader-NIH counts as shares of that 2,464-project scope, not of all NIH funding.

How to read this section. Each of the 5 dimensions below is a different axis (e.g., Production Platform, Therapeutic Target). For each project we check whether its title or abstract mentions any keyword in any of that dimension's categories. If yes, the project is matched on that axis. If no, it's unclassified on that axis - usually because the project doesn't foreground that particular axis (a "cell-free antibody discovery for HIV" project foregrounds Engineering and Therapeutic Target but rarely names a specific Antibody Format, so it lands unclassified on Format). A project can be matched on some axes and unclassified on others. High unclassified rates on an axis typically mean the sample doesn't foreground that axis - not that the projects are broken or the taxonomy is wrong.

Overview

Across 117 NIH-funded projects totaling $103.0M, liquid biopsy for early cancer detection shows pronounced concentration along several dimensions: lung cancer dominates the Cancer Type dimension with 26 projects (22.2%), circulating tumor DNA and cell-free DNA anchors the Analyte Class dimension with 47 projects (40.2%), and early detection and screening leads the Clinical Application dimension with 45 projects (38.5%). Coverage thins markedly in detection methodology - only 27 of 117 projects were classifiable, leaving 90 unclassified - and in non-plasma biofluids, where categories such as cerebrospinal fluid, urine, and stool each appear in 4 or fewer projects. These counts reflect NIH RePORTER-searchable federal funding, the largest publicly visible portion of US non-dilutive biomedical research grants, but exclude private industry R&D, international programs, and non-NIH federal agencies, so the picture is a floor estimate of total activity rather than a census.

Confidence: High - Evidence: 117 projects across 5 dimensions, 100% on-topic sample, detection methodology dimension has high unclassified rate (90/117) which limits interpretation of that axis.

Coverage by Cancer Type

Primary cancer type or organ site targeted by the liquid biopsy study

Rows are non-exclusive: a project can appear in more than one category, so the sum of the Projects column can exceed 85 classified projects.

Keywords per category (what was counted):

• Lung Cancer: lung cancer, nsclc, sclc, non-small cell lung, small cell lung, lung adenocarcinoma, lung carcinoma, lung tumor, pulmonary carcinoma, alk+ lung
• Breast Cancer: breast cancer, breast carcinoma, breast tumor, mammary carcinoma, her2, triple negative breast, tnbc, breast adenocarcinoma, metastatic breast
• Colorectal Cancer: colorectal cancer, colorectal carcinoma, colon cancer, rectal cancer, colon adenocarcinoma, colorectal adenocarcinoma, colorectal tumor, colonic neoplasm
• Pancreatic Cancer: pancreatic cancer, pdac, pancreatic ductal adenocarcinoma, pancreatic carcinoma, pancreatic tumor, pancreatic adenocarcinoma, pancreatic neoplasm
• Prostate Cancer: prostate cancer, prostate carcinoma, prostate tumor, prostatic neoplasm, prostate adenocarcinoma, castration resistant prostate, crpc
• Ovarian Cancer: ovarian cancer, ovarian carcinoma, epithelial ovarian, ovarian tumor, ovarian neoplasm, fallopian tube cancer, peritoneal carcinoma, high-grade serous
• Liver and Hepatocellular Cancer: hepatocellular carcinoma, hcc, liver cancer, hepatoma, liver tumor, hepatocellular cancer, cholangiocarcinoma, bile duct cancer, liver neoplasm
• Gastrointestinal Cancer: gastrointestinal cancer, gastric cancer, stomach cancer, esophageal cancer, gi cancer, gastroesophageal, gi tumor, gastrointestinal neoplasm
• Glioma and Brain Cancer: glioma, glioblastoma, gbm, brain tumor, brain cancer, astrocytoma, medulloblastoma, cns tumor, brain neoplasm, intracranial tumor
• Leukemia and Hematologic Malignancies: leukemia, lymphoma, myeloma, hematologic malignancy, aml, cll, all, multiple myeloma, diffuse large b cell, blood cancer
• Bladder and Urologic Cancer: bladder cancer, urothelial carcinoma, bladder carcinoma, bladder tumor, renal cell carcinoma, kidney cancer, rcc, urologic cancer, upper tract urothelial
• Multi-Cancer Early Detection: multi-cancer, multi-cancer early detection, mced, pan-cancer, multiple cancer types, cancer agnostic, tissue of origin, cancer type classification

In the Cancer Type dimension, lung cancer is the single largest focus with 26 projects (22.2% of the sample) and $30.7M in funding, a share roughly double that of the next-largest category, breast cancer, at 12 projects (10.3%). Leukemia and hematologic malignancies (11 projects, 9.4%) and ovarian cancer (9 projects, 7.7%) form meaningful secondary clusters, while liver and hepatocellular cancer (3 projects, 2.6%) and gastrointestinal cancer (2 projects, 1.7%) are sparsely represented within this sample. Multi-cancer early detection, a category of growing clinical interest, appears in only 4 projects (3.4%) despite a broader NIH title-match count of 12, suggesting the topic is early-stage across the funding ecosystem.

Confidence: High - Evidence: 85 of 117 projects classified, top category at 22.2% concentration, 32 projects unclassified.

Coverage by Analyte Class

The molecular analyte or biomarker class being detected or analyzed in the liquid biopsy

[†] Rows marked with a dagger are broader-NIH outliers - either their broader count is much higher than the dimension median (>=5x) or the category name contains a generic biomedical term ("machine learning", "biomarker", "methylation") that over-matches within the topic scope. These counts likely reflect generic keyword prevalence within the scope-filtered universe rather than topic-specific activity. Treat as directional only; do not anchor coverage inferences on daggered cells.

Rows are non-exclusive: a project can appear in more than one category, so the sum of the Projects column can exceed 82 classified projects.

Keywords per category (what was counted):

• Circulating Tumor DNA and Cell-Free DNA: circulating tumor dna, ctdna, cell-free dna, cfdna, cfdna, circulating dna, cell free dna, circulating cell-free dna, plasma dna, serum dna
• DNA Methylation Biomarkers: dna methylation, methylome, methylation signature, 5-methylcytosine, 5mc, 5-hydroxymethylcytosine, 5hmc, methylation pattern, epigenetic biomarker, bisulfite, methylation-based detection
• Cell-Free RNA and Transcriptomics: cell-free rna, cfrna, circulating rna, cell-free mrna, transcriptome, rna biomarker, long noncoding rna, lncrna, cell free transcriptome
• MicroRNA and Small Non-Coding RNA: microrna, mirna, mir-, small non-coding rna, circulating mirna, plasma mirna, serum mirna, non-coding rna, sncrna
• Extracellular Vesicles and Exosomes: extracellular vesicle, exosome, microvesicle, vesicle-based, evs, ev-based, exosomal, vesicle cargo, tumor-derived vesicle, vesicle biomarker, particle-borne
• Circulating Tumor Cells: circulating tumor cell, ctc, circulating cancer cell, tumor cell isolation, rare cell detection, ctc capture, epithelial cell adhesion, epcam, ctc enrichment
• Circulating Proteins and Proteomics: circulating protein, plasma protein, proteomics, protein biomarker, serum protein, 4d proteomics, proteomic profiling, tumor antigen, cancer antigen
• Ultra-Short and Fragmentomics cfDNA: ultra-short cfdna, fragmentomics, dna fragment, fragment size, nucleosome positioning, cfdna fragmentation, end motif, fragment length, sub-nucleosomal, short cell-free dna
• Tumor Microbiome and Microbial Biomarkers: tumor microbiome, blood microbiome, plasma microbiome, microbial biomarker, microbial dna, bacterial dna, circulating microbial, microbiome liquid biopsy
• Multi-Analyte and Integrated Biomarker Panels: multi-analyte, multi-marker, integrated biomarker, combined analyte, multimodal biomarker, protein plus dna, methylation plus protein, analyte panel, multi-omics liquid biopsy
• Autoantibodies and Immune Response Biomarkers: autoantibody, tumor-derived neoepitope, anti-tumor antibody, humoral immune response, immunoglobulin biomarker, cancer autoantibody, immune checkpoint biomarker, neoantigen antibody
• Circulating Immune and Inflammatory Cells: circulating hybrid cell, myeloid derived suppressor cell, mdsc, immune cell liquid biopsy, inflammatory cell biomarker, disseminated tumor cell, urothelial cell, rare cell immunophenotype

The Analyte Class dimension is heavily weighted toward circulating tumor DNA and cell-free DNA, which appears in 47 projects (40.2% of the sample) with $37.2M in funding, while extracellular vesicles and exosomes is the second-largest category at 15 projects (12.8%). The broader NIH title-match count for extracellular vesicles and exosomes is 443 - more than 4x any other category in this dimension and roughly 40x the median of peer categories - which is almost certainly a keyword-matching artifact reflecting the broad use of 'exosome' across cancer biology writ large rather than liquid biopsy-specific activity; that figure should be treated as directional only. Emerging analyte classes such as cell-free RNA and transcriptomics (5 projects, 4.3%), ultra-short and fragmentomics cfDNA (3 projects, 2.6%), circulating proteins and proteomics (2 projects, 1.7%), and multi-analyte integrated panels (2 projects, 1.7%) each remain thinly funded within this sample.

Confidence: Medium - Evidence: 82 of 117 projects classified, 35 unclassified, EV broader-NIH count flagged as likely artifact.

Coverage by Biofluid and Sample Source

The biological fluid or sample type used as the source for liquid biopsy analytes

[†] Rows marked with a dagger are broader-NIH outliers - either their broader count is much higher than the dimension median (>=5x) or the category name contains a generic biomedical term ("machine learning", "biomarker", "methylation") that over-matches within the topic scope. These counts likely reflect generic keyword prevalence within the scope-filtered universe rather than topic-specific activity. Treat as directional only; do not anchor coverage inferences on daggered cells.

Rows are non-exclusive: a project can appear in more than one category, so the sum of the Projects column can exceed 73 classified projects.

Keywords per category (what was counted):

• Blood Plasma: blood plasma, plasma sample, plasma-based, plasma ctdna, plasma cfdna, cell-free plasma, venipuncture, plasma liquid biopsy, plasma biomarker
• Blood Serum: blood serum, serum sample, serum-based, serum ctdna, serum cfdna, serum biomarker, serum dna, serum protein
• Saliva and Oral Fluid: saliva, salivary, oral fluid, oral biomarker, saliva-based, salivary dna, saliva biopsy, electric field-induced release, efirm, oral cavity fluid
• Urine: urine, urinary, urine-based, urine biomarker, urinary cfdna, urinary ctdna, urine liquid biopsy, voided urine, urinary sediment
• Cerebrospinal Fluid: cerebrospinal fluid, csf, spinal fluid, csf ctdna, csf cfdna, intrathecal, lumbar puncture, csf biomarker
• Bronchoalveolar Lavage and Sputum: bronchoalveolar lavage, bal, sputum, bronchial lavage, airway fluid, bronchoscopy sample, respiratory fluid
• Pleural and Ascitic Fluid: pleural fluid, ascites, ascitic fluid, peritoneal fluid, pleural effusion, body cavity fluid, malignant ascites
• Stool and Fecal: stool dna, fecal dna, stool-based, fecal biomarker, stool liquid biopsy, fecal occult, colorectal stool, fecal sample
• Leukapheresis and Peripheral Blood Mononuclear Cells: leukapheresis, pbmc, peripheral blood mononuclear, buffy coat, whole blood, blood cell fraction, leukocyte
• Multi-Fluid Panel Studies: non-plasma biofluid, multiple biofluids, cross-fluid, biofluid comparison, multi-fluid, non-plasma liquid biopsy, saliva versus plasma, urine versus plasma, biofluid panel
• Blood Plasma or Whole Blood (Cell-free DNA and ctDNA): cell-free dna, cfdna, circulating tumor dna, ctdna, liquid biopsy blood, plasma cfdna, whole blood liquid biopsy, circulating dna
• Extracellular Vesicles and Exosomes: extracellular vesicle, exosome, tumor exosome, vesicle-based biopsy, exosomal biomarker, nanoparticle vesicle, circulating exosome, ev-based liquid biopsy

In the Biofluid and Sample Source dimension, blood plasma or whole blood (cell-free DNA and ctDNA) dominates with 45 projects (38.5% of the sample) and $36.9M, and extracellular vesicles and exosomes as a sample source appears in 16 projects (13.7%) - noting again that its broader NIH count of 443 is anomalous relative to peer biofluid categories in this dimension and likely reflects generic keyword prevalence. Non-plasma biofluids are sparsely represented: saliva and oral fluid accounts for 6 projects (5.1%), urine for 4 projects (3.4%), cerebrospinal fluid for 2 projects (1.7%), stool and fecal for 1 project (0.9%), and bronchoalveolar lavage and sputum for 1 project (0.9%), while blood serum, pleural and ascitic fluid, and multi-fluid panel studies each appear in 0 projects within this sample. The high unclassified count (44 of 117 projects) in this dimension means these shares likely understate total activity across biofluid types.

Confidence: Medium - Evidence: 73 of 117 projects classified, 44 unclassified, EV broader-NIH count flagged as artifact.

Coverage by Detection and Analytical Methodology

The assay platform, sequencing approach, or analytical method used to detect and quantify liquid biopsy analytes

[†] Rows marked with a dagger are broader-NIH outliers - either their broader count is much higher than the dimension median (>=5x) or the category name contains a generic biomedical term ("machine learning", "biomarker", "methylation") that over-matches within the topic scope. These counts likely reflect generic keyword prevalence within the scope-filtered universe rather than topic-specific activity. Treat as directional only; do not anchor coverage inferences on daggered cells.

Rows are non-exclusive: a project can appear in more than one category, so the sum of the Projects column can exceed 27 classified projects.

Keywords per category (what was counted):

• Whole Genome Sequencing and Shallow WGS: whole genome sequencing, wgs, shallow whole genome, low-pass sequencing, genome-wide sequencing, copy number variation, tumor fraction, shallow wgs, low coverage sequencing
• Targeted Panel Sequencing: targeted sequencing, gene panel, hotspot panel, targeted deep sequencing, amplicon sequencing, targeted mutation, cancer gene panel, hybrid capture, targeted next-generation sequencing
• Whole Genome Bisulfite and Methylome Sequencing: bisulfite sequencing, wgbs, methylome sequencing, methylation sequencing, reduced representation bisulfite, rrbs, genome-wide methylation, epigenome sequencing, cell-free dna methylome
• Digital Droplet PCR and BEAMing: digital droplet pcr, ddpcr, digital pcr, beaming, droplet digital, digital quantification, rare mutation detection, digital multiplexed, dpcr
• High Resolution Melt and Methylation-Specific PCR: high resolution melt, hrm, digital hrm, methylation-specific pcr, msp, methylation pcr, melt curve analysis, methylation detection pcr, high-resolution melting
• Nanopore Sequencing: nanopore sequencing, nanopore-based, oxford nanopore, single-molecule nanopore, nanopore methylation, long-read nanopore, nanopore detection, nanopore platform
• Microfluidics and Lab-on-Chip: microfluidic, lab-on-chip, microfluidics, on-chip sorting, droplet microfluidic, microchannel, microfluidic sorting, microfluidic capture, micro-scale assay
• Single-Molecule Sequencing and Counting: single molecule sequencing, single-molecule detection, single molecule counting, single molecule analysis, molecular counting, single-molecule, smrt sequencing, stochastic sensing
• Machine Learning and Computational Analysis: machine learning, deep learning, artificial intelligence, classifier, neural network, random forest, computational model, bioinformatics pipeline, algorithmic detection, signal classification
• Proteomics and Mass Spectrometry: mass spectrometry, proteomics, 4d proteomics, super-resolution microscopy, protein profiling, lc-ms, tandem mass, proteomic discovery, mass spec
• Electrochemical and Biosensor Platforms: electrochemical sensor, biosensor, electrochemical detection, impedance, efirm, electric field-induced release, electrochemical biosensor, field-effect transistor, label-free detection
• Fragment Size and Nucleosome Footprint Analysis: fragmentomics, fragment size, nucleosome positioning, cfdna fragmentation, delfi, nucleosome footprint, fragment length, end motif analysis

The Detection and Analytical Methodology dimension has the lowest classification rate of any dimension, with only 27 of 117 projects assigned to a category and 90 left unclassified, which substantially limits interpretive confidence. Among classified projects, machine learning and computational analysis leads with 6 projects (5.1% of the sample) and $7.3M, followed by microfluidics and lab-on-chip at 5 projects (4.3%), while whole genome sequencing, whole genome bisulfite and methylome sequencing, and fragment size and nucleosome footprint analysis each appear in 3 projects (2.6%). Targeted panel sequencing, digital droplet PCR and BEAMing, single-molecule sequencing, proteomics and mass spectrometry, and electrochemical and biosensor platforms each appear in only 2 projects (1.7%), and nanopore sequencing and high resolution melt methods each appear in 1 project (0.9%) - but given the low overall match rate, these counts should be understood as a partial view rather than a complete inventory of methodological activity in the sample.

Confidence: Low - Evidence: only 27 of 117 projects classified in this dimension (23.1%), high unclassified rate limits conclusions.

Coverage by Clinical Application and Translational Stage

The intended clinical use case and the stage of translational development of the liquid biopsy approach

[†] Rows marked with a dagger are broader-NIH outliers - either their broader count is much higher than the dimension median (>=5x) or the category name contains a generic biomedical term ("machine learning", "biomarker", "methylation") that over-matches within the topic scope. These counts likely reflect generic keyword prevalence within the scope-filtered universe rather than topic-specific activity. Treat as directional only; do not anchor coverage inferences on daggered cells.

Rows are non-exclusive: a project can appear in more than one category, so the sum of the Projects column can exceed 86 classified projects.

Keywords per category (what was counted):

• Early Cancer Detection and Screening: early cancer detection, cancer screening, early detection, early-stage detection, population screening, asymptomatic detection, pre-symptomatic, cancer risk screening, liquid biopsy screening
• Minimal Residual Disease and Recurrence Monitoring: minimal residual disease, mrd, residual disease, disease recurrence, recurrence monitoring, ctdna surveillance, molecular residual disease, post-treatment monitoring, relapse detection
• Treatment Response Monitoring: treatment response, treatment monitoring, therapy response, response assessment, treatment efficacy, on-treatment monitoring, chemotherapy response, immunotherapy response, real-time monitoring
• Therapy Selection and Companion Diagnostics: companion diagnostic, therapy selection, treatment selection, predictive biomarker, targetable mutation, drug selection, precision oncology, actionable mutation, theranostic
• Biomarker Discovery and Validation: biomarker discovery, biomarker validation, biomarker development, novel biomarker, biomarker identification, assay validation, analytical validation, clinical validation, biomarker characterization
• cfDNA Biogenesis and Biological Mechanisms: cfdna biogenesis, cell-free dna biogenesis, cfdna biology, dna release mechanism, apoptosis dna release, necrosis dna release, cfdna origin, molecular mediator, cfdna generation, nucleosome occupancy
• Clinical Trial and Prospective Cohort: clinical trial, prospective cohort, prospective study, randomized trial, clinical study, patient cohort, longitudinal study, biobank, multi-site study
• Assay Development and Technology Platform: assay development, platform development, technology development, assay optimization, low-cost assay, point-of-care, rapid assay, multiplexed assay, diagnostic platform, clinical assay
• Tissue of Origin and Cancer Type Classification: tissue of origin, cancer type classification, tumor origin, cancer localization, tissue-specific methylation, origin prediction, cancer classifier, organ of origin
• Priming and Sample Enrichment Strategies: priming agent, sample enrichment, tumor priming, ctdna enrichment, circulating tumor cell enrichment, exosome enrichment, vesicle capture, pre-analytical enrichment, signal enhancement
• Alternative Biofluid and Non-Plasma Liquid Biopsy: urine, saliva, oral rinse, cerebrospinal fluid, csf, effusion, bronchoalveolar, non-plasma biofluid
• Multimodal and Integrative Diagnostic Panel: multi-analyte, multimodal, radiomics, imaging biomarker, multi-omic, combined diagnostic, integrative liquid biopsy, blood and imaging

Early cancer detection and screening dominates the Clinical Application and Translational Stage dimension at 45 projects (38.5% of the sample) and $44.2M, consistent with the core focus of the analyzed topic. Minimal residual disease and recurrence monitoring, treatment response monitoring, and alternative biofluid and non-plasma liquid biopsy each account for 12 projects (10.3%), while multimodal and integrative diagnostic panels represent 10 projects (8.5%) with the second-highest funding at $13.2M, suggesting that integrative approaches attract above-average investment per project. Mechanistically foundational work - cfDNA biogenesis and biological mechanisms (1 project, 0.9%), tissue of origin and cancer type classification (1 project, 0.9%), and priming and sample enrichment strategies (1 project, 0.9%) - is sparse within this sample, though 31 of 117 projects were unclassified in this dimension.

Confidence: High - Evidence: 86 of 117 projects classified, top category at 38.5% concentration, 31 unclassified.

Strategic Implications

The analyzed sample does not surface strong quantitative gap signals that meet the threshold for ranked white space opportunities, meaning the data as structured does not yield high-confidence differentiation targets for grant strategy framing. For a researcher evaluating where to position an R01 or R21, the most defensible observation from the coverage data is that detection and analytical methodology is the least-classified dimension (only 27 of 117 projects resolved), which may reflect heterogeneity in methods language rather than absence of activity - proposals that foreground a specific platform with a well-defined analytic novelty claim may face less crowding in reviewer perception, but this inference is speculative given the data quality in that dimension. The high concentration of funding in ctDNA/cfDNA analytes (47 projects, 40.2% of the sample in the Analyte Class dimension) and blood-based biofluids (45 projects, 38.5% in the Biofluid dimension) means that proposals anchored in those mainstream modalities will need a strong differentiation argument on another axis - cancer type, clinical application stage, or methodology - to stand out in review.

Confidence: Low - Evidence: no categories met the ranked opportunity threshold; strategic implications derived from distributional patterns in 117 projects rather than confirmed gap signals.

Research Positioning

Competitive Positioning

Among the funded projects, DNA methylation analysis of cell-free DNA represents the most densely occupied technical territory, appearing across at least 15 projects at UCLA, Johns Hopkins, Stanford, City of Hope, Moffitt, and elsewhere, with multi-cancer early detection (MCED) framing now common enough that it is effectively a default positioning for cfDNA work.

Confidence: High - Evidence: Projects including 5U01CA285010-03 (UCLA methylome), 5U01CA230691-08 (Johns Hopkins multi-analyte), 5U2CCA271885-04 (Pittsburgh methylation optimization), 5U01CA282212-02 (Stanford nanopore methylome), 1U01CA296639-01A1 (City of Hope 5mC/5hmC), 7R01CA252042-05 (Moffitt CRC methylation), R37CA300232 (Cedars-Sinai ctDNA methylation), and others across 15+ funded nodes.

A new entrant seeking differentiation within this sample would find less competition in analyte-expansion directions: microbiome-plasma integration (P20GM130423), synthetic biomarker approaches (5U01CA265711-05), and non-plasma biofluid primaries such as urine (5R37CA262238-05, 5R01CA244526-05), urothelial cell enrichment (5K08CA276704-03), uterine lavage and cervical swab (5U2CCA271871-03), and saliva (R43CA285075, 5U01CA230691-08 head and neck arm) each appear in only one to three projects in the sample.

Confidence: Medium - Evidence: Biofluid-alternative projects number roughly 8-10 across the 117-project sample, compared to 15+ methylation-centric cfDNA projects; single-organ or rare-biofluid approaches are individually sparse, though collectively they occupy a meaningful minority of the portfolio.

Multi-Method Concentration Patterns

Massachusetts General Hospital holds nine projects in the sample spanning at least four distinct methodological categories: microfluidic CTC isolation (5R01CA260304-05), ctDNA-based residual disease monitoring (5K08CA273688-04), imaging-liquid biopsy integration for glioma (R01CA239078), nanoplasmonic extracellular vesicle detection (5U01CA284982-03), uterine lavage proteomics and genomics (5U2CCA271871-03), basic cfDNA in-vivo enrichment (5K08EB036081-02), sepsis organ-damage detection (1R21AI188227-01), and proteomic/genomic longitudinal ovarian biomarker work (5U01CA152990-10) - a concentration of methodological breadth not matched by any other single institution in the sample.

Confidence: High - Evidence: 9 projects, $7.5M, spanning microfluidics, EV detection, ctDNA, proteomics, and imaging integration across the MGH-listed entries in the Full Project List.

Johns Hopkins University holds six projects covering DNA methylation platform development (5R33CA272321-03), multi-analyte non-plasma biofluids (5U01CA230691-08), DELFI fragmentomics for lung (U01CA271896), bladder cancer urothelial DNA flow cytometry (5K08CA276704-03), point-of-care CRC cartridge development (5R01CA278816-03), and automated breast cancer assay development (5R01CA269237-04), indicating a pattern where assay-engineering and clinical translation coexist with analyte discovery work within the same institutional portfolio.

Confidence: High - Evidence: 6 projects, $7.2M, spanning biotools, diagnostics, and infrastructure categories across the JHU-listed entries.

UCLA's five projects concentrate specifically on cfDNA analyte development and MCED test validation (4U01CA233370-08, 5R21CA283665-02, 4R01CA264864-04, 5U01CA285010-03, 5U01CA230705-08), a narrower methodological spread than MGH or JHU but with notably higher average funding per project.

Confidence: Medium - Evidence: 5 projects, $8.6M, all classified under diagnostics, with average per-project funding of approximately $1.7M versus $0.83M for MGH.

Methodological Trends

Fragmentomics - analyzing the size distribution and end-motif patterns of cfDNA fragments rather than relying solely on mutation or methylation signals - appears as a funded direction in at least two projects in the sample (U01CA271896, the DELFI lung cancer project at Johns Hopkins; and 5R01CA240299-05, the Harvard statistical methods project explicitly addressing cfDNA fragment analysis), representing a methodologically distinct layer on top of sequencing infrastructure that is newer in the funding record than mutation-based ctDNA.

Confidence: Medium - Evidence: 2-3 projects directly foregrounding fragmentomics; the approach also appears implicitly in multi-analyte projects at Johns Hopkins (5U01CA230691-08) that list fragmentomics as one analyte dimension.

Machine learning and AI-assisted signal extraction is present across at least six projects spanning nanoplasmonic spectroscopy (R01CA273253), advanced ML for liquid biopsy in melanoma and NSCLC (K08CA263301), neural-network nanoplasmonic platforms (R01CA273253), AI-assisted tumor cell morphology isolation (5R01CA292019-02), machine learning combined with nanofluidics for pancreatic cancer (5R33CA278551-03), and metasurface-enhanced spectroscopy (R21EB034411), suggesting that computational signal-extraction is now treated as an engineering component embedded within assay development rather than a standalone analytical deliverable.

Confidence: Medium - Evidence: 6 projects explicitly incorporating ML/AI as a named methodological component across the Full Project List.

Extracellular vesicle (EV) and exosome-based analytes constitute a stable but distinct minority within the sample - at least 10 projects address EVs or exosomes as the primary analyte (5R01CA218513-08, 5U01CA214254-08, 5R01CA271443-03, U01CA299594, 5R01EB030623-05, 5R01CA253860-05, 5R01CA255319-05, 5R37CA255948-05, 5U01CA284982-03, R01CA241666) - indicating sustained but not dominant NIH investment in this analyte class relative to cfDNA-methylation work.

Confidence: High - Evidence: 10+ EV/exosome projects identified across the Full Project List spanning pancreatic, hepatocellular, ovarian, lung, and multi-cancer applications.

NIH Funding Landscape

Among the examined projects, our analysis reveals that cell-free DNA (cfDNA) methylation profiling and circulating tumor DNA (ctDNA) detection dominate the funded research agenda, appearing across projects at UCLA, Stanford, Johns Hopkins, and multiple NCI-intramural efforts. The sample shows a strong emphasis on multi-cancer early detection paradigms - projects from Mayo Clinic, UCLA, and the University of Chicago are each pursuing blood-based tests capable of simultaneously detecting multiple cancer types from a single draw, reflecting a convergence around the clinical utility of pan-cancer screening. Biofluid diversification is a secondary but notable priority: among the analyzed projects, researchers at Johns Hopkins, UCLA, and NORD BIO are exploring saliva, urine, cerebrospinal fluid, and surgical drain fluid as alternative or complementary matrices to blood plasma, particularly for cancers anatomically proximate to those biofluids. Extracellular vesicle biology - including exosome-derived microRNA, proteomic cargo, and surface markers - represents a substantive funding thread running through projects at Beckman/City of Hope, Cornell, and Massachusetts General Hospital, suggesting that non-cfDNA analytes are viewed as potentially additive to mutation- and methylation-based approaches rather than as replacements.

Funding Summary

Funding figures sum award amounts across all budget periods for each project. Each fiscal year reflects actual spend in that year, not the most recent budget period only. Totals only include projects that meet the topic-relevance threshold - umbrella support grants (e.g., P30 cancer centers) that host a relevant trial but cover many unrelated programs are intentionally excluded so the headline number stays topically attributable.

Funding by Year

The Projects column counts each project in every year it received funding, so per-year counts sum to more than the 117-project sample total. Funding amounts are actual per-year spend from NIH RePORTER budget-period rows.

Through August 2026; FY2026 ends Sep 30, 2026. The YTD figure should not be compared directly to fully-reported prior years.

Top Funding Categories

Key Research Projects

Top Funded Projects

Funding is the sum of award totals across all budget periods for each project. Latest activity is the most recent fiscal year the project received an award. Category is auto-assigned by AI classification and may occasionally misassign monitoring-oriented diagnostic projects as therapeutics - the abstract is the ground truth for what the project actually does.

1. EFIRM Liquid Biopsy Research Laboratory: Early Lung Cancer Assessment

• PI: WONG, DAVID T, University of California Los Angeles
• Funding: $3.6M (latest activity FY2025)
• Category: Diagnostics

Insight: This project advances a saliva-based electrochemical platform - Electric Field-Induced Release and Measurement (EFIRM) - for direct cfDNA detection from a droplet of blood, targeting early lung cancer without the sample processing requirements of standard plasma sequencing workflows. The combination of hardware miniaturization with a parallel biomarker discovery arm positions the work at the intersection of the biotools and diagnostics categories, a pairing that is relatively sparse within the analyzed sample. Its non-plasma-adjacent sample handling approach also connects to the broader observation that non-standard biofluid formats represent a low share of sample projects relative to their organ-specific biological rationale.

This application, Phase 2 of the EFIRM-Liquid Biopsy Research Laboratory is to advance liquid biopsy for early lung cancer detection by: 1) advance the EFIRM Liquid Biopsy (eLB) technology towards ultra-sensitive detection of cancer-associated cfDNA directly in a droplet of blood while 2) a new land...

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2. DNA evaluation of fragments for early interception (DELFI) of Lung cancer

• PI: VELCULESCU, VICTOR E., Johns Hopkins University
• Funding: $3.1M (latest activity FY2026)
• Category: Diagnostics

Insight: The DELFI fragmentomics program applies genome-wide cfDNA fragmentation pattern analysis to pre-neoplastic lung lesions, targeting not just binary cancer detection but lesion progression prediction - a distinction that addresses one of the more persistent clinical limitations of LDCT screening, which flags many indeterminate nodules without reliable progression risk data. Working in a prospective lung screening population allows the approach to be tested against real-world screening dynamics rather than case-control cohorts alone, which is methodologically important for sensitivity and specificity estimation at realistic prevalence. Within the analyzed sample, this represents one of the more developed fragmentomics programs, and the focus on pre-neoplastic biology adds a mechanistic dimension that most ctDNA detection projects in the sample do not pursue.

Molecular based blood tests provide an accessible and affordable option for screening high risk populations for many common cancers, leading to early detection with better outcomes. We propose to study the origins and molecular characteristics of cell-free DNA fragments in pre-neoplastic lung lesion...

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3. Multi-modal Liquid Biopsy Early Assessment of Breast Cancer, Pancreatic Cancer, and Multiple Myeloma

• PI: KUHN, PETER, University of Southern California
• Funding: $2.8M (latest activity FY2025)
• Category: Diagnostics

Insight: This project pursues a multi-cancer, multi-analyte liquid biopsy strategy across three disease contexts - breast cancer, pancreatic cancer, and multiple myeloma - using a biologically informed platform developed in academic-industry partnership with Epic Sciences, incorporating rare cell and multi-omic blood analysis. The pancreatic cancer arm is particularly notable for its inclusion of portal vein blood alongside peripheral blood, a sampling approach that attempts to exploit the anatomical proximity of pancreatic drainage to improve signal yield for a cancer type where peripheral cfDNA fractions are typically low at early stages. The myeloma arm, using liquid biopsy as a substitute for bone marrow aspirate to detect precursor-to-malignancy transitions, represents a clinical utility framing - replacing an invasive procedure - that is distinct from the screening framing dominant in the rest of the analyzed sample.

This Liquid Biopsy Research Laboratory (LBRL) partnership team, led by PI Peter Kuhn (academic) and Co-I Rick Wenstrup (industry) of Epic Sciences, is advancing biologically informed liquid biopsy (LBx) technology to fill gaps in current clinical practice of early cancer assessment. The three scenar...

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4. Clinical Utility of a Combined Biomarker Approach to Diagnose Lung Cancer

• PI: GROGAN, ERIC L, Vanderbilt University Medical Center
• Funding: $2.7M (latest activity FY2025)
• Category: Therapeutics

Insight: This project at Vanderbilt enrolls patients with suspicious lung lesions into a prospective trial combining blood-based biomarkers with radiomics-derived imaging features, aiming to validate a combined diagnostic approach at the point of clinical indetermination rather than population screening. The lesion-level focus - patients already flagged by imaging - positions the work as a triage or rule-in tool complementary to LDCT rather than a standalone screening replacement, which is a clinically pragmatic entry point given current reimbursement and workflow realities. Its categorization as therapeutics rather than diagnostics in the dataset is worth noting, as the primary aim is diagnostic validation, reflecting category assignment ambiguity that appears in a small share of sample projects.

Doctors continue to struggle to diagnose lung cancer early when it is most curable. Lung cancer screening along with breakthroughs in blood tests and sophisticated computerized imaging may help solve this problem. We propose to enroll patients with suspicious lung lesions in a trial to test these ne...

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5. Liquid biopsy and radiomics for liver cancer surveillance

• PI: TAOULI, BACHIR, Icahn School of Medicine at Mount Sinai
• Funding: $2.6M (latest activity FY2025)
• Category: Diagnostics

Insight: This project focuses specifically on hepatocellular carcinoma (HCC) surveillance, combining liquid biopsy detection of circulating tumor components with MRI-based radiomics in a multiracial, multi-institutional cohort - a disease-specific and imaging-integrated design that is relatively rare within the analyzed sample's predominantly plasma-only diagnostic projects. HCC is a high-unmet-need target for liquid biopsy given the limitations of current AFP-based surveillance and the high false-positive burden of imaging alone in cirrhotic populations, and the multi-institutional, multiracial cohort design directly addresses generalizability concerns that limit single-site biomarker studies. The radiomics integration mirrors the multi-analyte positioning described in the report context as a differentiation strategy relative to single-analyte platforms.

It is imperative to develop new noninvasive tools for the detection of curable hepatocellular carcinoma, as this improves survival in these patients. We propose a rigorous and systematic evaluation of liquid biopsy (detection of tumor components released to the bloodstream) and magnetic resonance im...

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6. Improving risk stratification for lung cancer screening using peripheral blood leukocyte DNA methylation: an investigation in the National Lung Screening Trial (NLST)

• PI: MICHAUD, DOMINIQUE S., Tufts University Boston
• Funding: $2.1M (latest activity FY2026)
• Category: Diagnostics

Insight: This project takes an epidemiologically grounded approach by leveraging archived blood samples from the National Lung Screening Trial - one of the largest and most rigorously characterized lung cancer screening cohorts available - to evaluate whether peripheral blood leukocyte DNA methylation markers can improve risk stratification for LDCT screening selection. The leukocyte methylation angle is mechanistically distinct from plasma cfDNA or ctDNA approaches that dominate the analyzed sample, instead using immune cell epigenetic signatures as a systemic cancer risk indicator, which sidesteps some of the low-signal challenges of early-stage ctDNA detection. Using a pre-existing, well-annotated trial cohort rather than de novo prospective enrollment is a resource-efficient validation strategy that also enables analysis at the pre-diagnosis timepoint, a window that prospective studies rarely capture at scale.

Lung cancer is the leading cause of cancer death in the US, and while annual screening with low-dose CT (LDCT) is recommended for high-risk individuals, the high false-positive rates remain a major challenge. We propose to use existing blood samples collected during the National Lung Screening Trial...

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7. A miniaturized neural network enabled nanoplasmonic spectroscopy platform for label-free cancer detection in biofluids

• PI: GOMEZ DIAZ, JUAN SEBASTIAN, University of California at Davis
• Funding: $2.0M (latest activity FY2026)
• Category: Diagnostics

Insight: This project develops a portable, neural network-enabled nanoplasmonic spectroscopy platform designed for label-free cancer detection across multiple biofluid types - saliva, blood plasma, and sweat - with an initial focus on head and neck cancer, a disease context where salivary biomarker access has direct anatomical logic. The platform's point-of-care orientation and multi-biofluid capability place it in the biotools-adjacent space where hardware development intersects with diagnostics validation, and its label-free detection mechanism bypasses the sequencing library preparation steps that add cost and complexity to cfDNA-based assays. Within the analyzed sample, saliva-based and sweat-based platforms represent a low share of projects, making this one of the few efforts explicitly targeting non-plasma biofluid matrices at the instrumentation level.

State of the art methods for the early detection and monitoring of cancer are either invasive, time-consuming, expensive, or frequently inaccurate, which hinders the routine screening of at risk-patients to improve survival rates. Here, we propose a portable neural network enabled spectroscopy platf...

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8. Monitoring Immunotherapy Response via Gene Silencing Landscapes in Cell-Free DNA

• PI: BARRETT, MICHAEL T, Binary Genomics, Inc.
• Funding: $2.0M (latest activity FY2025)
• Category: Therapeutics

Insight: This project from Binary Genomics develops a cfDNA-based blood test that maps gene silencing landscapes - epigenetic suppression patterns detectable in cell-free DNA - to monitor tumor burden changes during lung cancer immunotherapy, aiming to distinguish responders from non-responders longitudinally. The gene silencing or methylation-based tumor burden readout is applied here to a treatment monitoring rather than early detection context, which reflects a therapeutic categorization in the dataset and a somewhat different clinical question than screening-oriented projects in the sample. The monitoring application nonetheless advances liquid biopsy sensitivity and specificity requirements that are directly relevant to early detection, since the analytical challenges of detecting low tumor-fraction signal in post-treatment samples parallel those encountered in early-stage disease.

Some lung cancer patients have robust and durable tumor responses to immunotherapy, whereas others derive no benefit from such treatment. A blood test that monitors for changes in the amount of tumor DNA in the circulation could help to distinguish responders from non-responders, thereby improving c...

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9. Genome-wide mutational integration for ultra-sensitive plasma tumor burden monitoring in immunotherapy

• PI: LANDAU, DAN, Weill Medical Coll of Cornell Univ
• Funding: $1.9M (latest activity FY2026)
• Category: Diagnostics

Insight: The MRDetect platform applies genome-wide mutational integration with machine learning to detect extremely low tumor burden in plasma, targeting the post-treatment minimal residual disease window where standard sequencing-based liquid biopsy approaches lose sensitivity due to low ctDNA fractions. The computational architecture - using AI to aggregate weak signals across the full genome rather than relying on high-depth coverage of a targeted panel - represents a technical approach to the sensitivity floor problem that is distinct from the methylation and fragmentomics clusters dominant in the analyzed sample. This ultra-low-burden detection capability, if validated, has implications beyond monitoring: the same sensitivity headroom could be applied to early-stage detection where tumor-derived fractions in plasma are similarly low.

The ability to detect low levels of cancer is crucial for cancer diagnosis and treatment; however, even state-of- the-art techniques such as imaging and ‘liquid biopsy’ through deep sequencing fail to detect cancer when the tumor burden is extremely low, as can occur after treatment or surgery when ...

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10. Lung Cancer Early Detection and Immunotherapy Response Prediction and Monitoring with an Exo-PROS Liquid Biopsy Assay

• PI: WU, YUN, State University of New York at Buffalo
• Funding: $1.9M (latest activity FY2025)
• Category: Therapeutics

Insight: This project develops the Exo-PROS assay, targeting tumor-derived exosomes as the analyte class rather than cell-free DNA, and proposes simultaneous multi-biomarker readout from exosomal content for both lung cancer early detection and immunotherapy response monitoring in a single platform. The exosome focus places this project in the secondary analyte cluster noted in the report context as thinner relative to cfDNA, and the dual indication - screening and monitoring - within one assay is an efficiency argument relevant to clinical adoption and reimbursement justification. The emphasis on user-friendliness and cost-effectiveness signals an orientation toward decentralized or lower-resource clinical settings, a positioning angle that fewer than a handful of projects in the analyzed sample explicitly pursue.

Current screening and diagnostic tests for lung cancer such as low dose CT and tissue biopsy are limited by high false positive rate, radiation exposure and invasive procedure. Liquid biopsy detects tumor-derived biomarkers in blood, allows sequential sampling, complements medical imaging and risk f...

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Market Context

Market Overview

Market context below is synthesized from current web search results. See sources at the end of this section. NIH funding patterns are integrated to bridge public research and commercial activity.

Liquid biopsy for early cancer detection - encompassing multi-cancer early detection (MCED) blood tests, ctDNA-based single-cancer screening, and MRD monitoring - has emerged as one of the most active and rapidly evolving segments in oncology diagnostics. The field is driven by the growing global cancer burden, a strong clinical preference for non-invasive, repeatable diagnostics, and accelerating convergence of next-generation sequencing (NGS), AI-powered methylation analysis, and cfDNA biomarker science. North America dominates the commercial landscape, accounting for roughly half of global revenues, supported by a dense ecosystem of specialized companies, favorable regulatory frameworks, and expanding (though still incomplete) reimbursement pathways. A landmark legislative development in early 2026 - the Miller-Meeks Bill signed into law - established that FDA-approved MCED tests will be eligible for Medicare coverage at approximately $500 per test starting in 2029 for ages 50-65, providing a long-awaited reimbursement signal that is reshaping commercial planning across the industry.

Clinical evidence generation remains the central competitive battleground. GRAIL's Galleri test - currently sold in the U.S. as a laboratory-developed test since 2021 and the subject of the only large-scale randomized controlled MCED trial - submitted its final FDA PMA module in January 2026. The accompanying NHS-Galleri RCT (142,000 participants) reported mixed results: the trial demonstrated a substantial reduction in Stage IV diagnoses of 12 prespecified cancers and a four-fold higher cancer detection rate, but did not meet its primary endpoint of a statistically significant reduction in Stage III/IV cancers in aggregate - a result that prompted a shareholder class action lawsuit and illustrated the difficulty of translating test performance into population-level endpoints. PATHFINDER 2, the U.S.-based registrational study with over 35,000 participants, reported increased cancer detection over standard-of-care, with results presented at ASCO 2026. Payers, health technology assessors, and regulators continue to weigh these mixed signals as they decide on coverage and approval. Positive predictive value in average-risk screening populations - where cancer prevalence is low - remains a key challenge for all MCED platforms, as real-world PPV is expected to underperform relative to PPV observed in enriched clinical trial populations, a concern that applies across GRAIL, Guardant, Exact Sciences/Abbott, Freenome, and Caris Life Sciences alike.

The competitive and M&A environment has intensified sharply. Abbott's $21 billion acquisition of Exact Sciences, announced in November 2025 and closed March 23, 2026, created a new commercial-scale incumbent combining Cologuard, Oncotype DX, MRD testing, and the Cancerguard MCED blood test (launched September 2025, covering more than 50 cancer types as an LDT) under one global distribution network. Freenome entered a strategic collaboration with Roche granting Roche exclusive ex-U.S. rights to commercialize Freenome's cancer screening technology, though Freenome's platform, like all MCED platforms, faces the shared challenge that real-world PPV in average-risk populations is expected to underperform trial settings, and reimbursement coverage has not yet been established. Natera's Signatera CDx received FDA approval in May 2026 as a companion diagnostic for blood-based treatment-informed MRD testing in muscle-invasive bladder cancer, establishing a novel regulatory endpoint for solid tumor de-escalation, though broader reimbursement coverage for MRD-guided treatment decisions remains unsettled across payers. Caris Life Sciences launched Caris Detect in June 2026, pairing whole-genome and whole-transcriptome sequencing with AI models built on over 1 million molecular profiling cases, adding another well-resourced entrant to the MCED market.

Market Sizing: Direct sizing for liquid biopsy specifically for early cancer detection (MCED applications) is not separately tracked by all major research firms. The closest directly reported estimate comes from DataM Intelligence: $2.48 billion in 2025, projected to $7.85 billion by 2035 at a 12.1% CAGR (DataM Intelligence, 2026). The broader liquid biopsy market (all applications including MRD, companion diagnostics, and treatment monitoring) is estimated at $7.05 billion in 2025, projected to $22.69 billion by 2034 at a 13.91% CAGR (Precedence Research, 2025). Note: market sizing estimates across third-party research firms vary materially - figures range from roughly $2.5 billion to $13.6 billion for 2025 depending on scope definition - and should be treated as directional rather than precise.

Key Players

These players are identified from market reports and trade press, and may differ from the NIH-funded organizations analyzed elsewhere in this report.

• GRAIL (Nasdaq: GRAL) - Galleri MCED test, FDA PMA pending
• Guardant Health - Shield (FDA-approved CRC screening, 2024), Guardant360 Liquid CDx
• Abbott / Exact Sciences (acquired March 2026) - Cancerguard MCED, Cologuard, Oncotype DX
• Natera - Signatera CDx (FDA-approved MRD, 2026)
• Freenome - blood-based MCED platform (Roche ex-U.S. partnership)
• Caris Life Sciences - Caris Detect MCED (launched June 2026)
• Roche / Foundation Medicine - FoundationOne Liquid CDx companion diagnostics
• Illumina - NGS platform provider, Illumina Ventures investor in liquid biopsy ecosystem
• Thermo Fisher Scientific - NGS instruments and reagents
• Myriad Genetics - MyChoice CDx, Precise MRD test
• NeoGenomics - PanTracer LBx
• QIAGEN - liquid biopsy sample preparation and assay kits
• Bio-Rad Laboratories - ddPCR platforms
• Personalis - NeXT Personal tumor-informed MRD

Recent Developments

• 2025-09-01: Exact Sciences launched Cancerguard, a blood-based MCED LDT targeting more than 50 cancer types, entering direct competition with GRAIL's Galleri
• 2025-11-20: Abbott announced a definitive agreement to acquire Exact Sciences for approximately $21 billion, combining Cologuard, Oncotype DX, Cancerguard, and MRD testing under Abbott's global distribution network
• 2025-11-01: BillionToOne raised $314 million in an upsized IPO on Nasdaq (ticker: BLLN), planning to scale noninvasive prenatal and cancer DNA testing businesses
• 2026-01-29: GRAIL submitted the final module of its FDA Premarket Approval (PMA) application for the Galleri MCED test, citing data from 25,490 PATHFINDER 2 participants and first-year NHS-Galleri RCT data; Galleri holds FDA Breakthrough Device designation since 2018
• 2026-01-01: The Miller-Meeks Bill was signed into law, establishing Medicare coverage eligibility for FDA-approved MCED tests at approximately $500 reimbursement starting in 2029 for ages 50-65
• 2026-01-01: Natera submitted the Signatera CDx PMA for identifying benefit from atezolizumab in muscle-invasive bladder cancer
• 2026-01-01: Freenome announced an expanded AI collaboration with NVIDIA to accelerate fragment-level cfDNA AI model training and advance a foundation model for methylation analysis
• 2026-02-19: GRAIL announced topline NHS-Galleri RCT results (142,000 participants): the trial demonstrated a reduction in Stage IV diagnoses of 12 prespecified cancers and a four-fold higher cancer detection rate, but did not meet its primary endpoint of statistically significant aggregate Stage III-IV reduction
• 2026-03-23: Abbott finalized its $21 billion acquisition of Exact Sciences, closing the largest M&A deal in liquid biopsy history
• 2026-03-01: Guardant Health announced a strategic collaboration with Quest Diagnostics to broaden access to the Shield CRC screening test across Quest's nationwide network
• 2026-05-01: GRAIL presented full PATHFINDER 2 results at ASCO 2026 (35,000+ participants), showing Galleri substantially increased cancer detection over standard-of-care including new Stage I and II detections; real-world PPV in average-risk populations remains a disclosed limitation
• 2026-05-01: FDA approved Natera's Signatera CDx for use with adjuvant atezolizumab in muscle-invasive bladder cancer - the first-ever companion diagnostic approval for blood-based treatment-informed MRD testing
• 2026-05-01: FDA approved Guardant360 Liquid CDx as the largest FDA-approved liquid biopsy panel, covering a 100x wider genomic footprint than the prior Guardant360 CDx
• 2026-05-01: NHS England introduced liquid biopsy-based DNA testing as a first-line diagnostic option for patients with suspected lung and advanced breast cancers
• 2026-06-01: Caris Life Sciences launched Caris Detect, a whole-genome and whole-transcriptome sequencing MCED blood test built on AI models trained on over 1 million molecular profiling cases
• 2026-06-01: GRAIL shareholders filed a securities class action lawsuit alleging misleading statements about the likelihood of the NHS-Galleri trial achieving its primary endpoint
• 2026-06-01: Guardant Health lost its bid to overturn an $83 million patent verdict in a TwinStrand Biosciences sequencing patent suit, with a federal judge ordering an ongoing 6% royalty to TwinStrand
• 2026-06-01: Mammogen closed a Series A of up to $30 million to advance clinical validation of its RNA-based breast cancer detection platform

Competitive Landscape

The liquid biopsy early cancer detection market is consolidating around a small number of well-capitalized commercial-stage platforms while simultaneously seeing a new wave of entrants with differentiated modalities. The Abbott/Exact Sciences close in March 2026 created the field's most formidable commercial entity by pairing Cancerguard and a growing MRD portfolio with Abbott's global primary care salesforce and diagnostics distribution. GRAIL remains the most clinically validated standalone MCED company with a PMA under active FDA review, but faces material headwinds: the NHS-Galleri primary endpoint miss, an ongoing shareholder lawsuit, and a post-spin-off valuation reset following its separation from Illumina. Guardant Health holds the only FDA-approved blood-based colorectal cancer screening test (Shield, 2024) and recently received FDA approval for the Guardant360 Liquid CDx as the largest-panel liquid biopsy companion diagnostic, though it is also managing an $83 million patent judgment payable to TwinStrand and the broader PPV and coverage challenges that affect all liquid biopsy screening platforms. Natera's Signatera CDx received FDA approval in May 2026 as a companion diagnostic for blood-based treatment-informed MRD testing in bladder cancer, a regulatory template that other MRD players are now racing to replicate, though broader payer coverage for MRD-guided treatment decisions remains unsettled. Freenome's ex-U.S. partnership with Roche signals that large in-vitro diagnostics incumbents are pursuing asset-light entry into the MCED space rather than building organically, though Freenome's platform, like all MCED platforms, has not yet established reimbursement coverage and faces the shared real-world PPV challenge in average-risk populations. Caris Life Sciences entered MCED directly in June 2026 with a differentiated whole-genome and whole-transcriptome approach backed by a large proprietary molecular database. Across the field, positive predictive value in true average-risk screening populations - where cancer prevalence may be 0.5-1% - remains a shared scientific and commercial challenge; trial PPVs do not automatically translate to real-world settings, and payer coverage decisions are expected to hinge heavily on health-economic modeling and post-market evidence requirements. Reimbursement risk, therefore, is a competitive factor that could reshape positioning across all players equally, regardless of current clinical differentiation.

Sources

Live web sources retrieved during report generation. Click to verify.

• www.openpr.com/news/4580098/united-states-liquid-biopsy-early-cancer-detection-market
• www.gminsights.com/industry-analysis/liquid-biopsy-market
• www.grandviewresearch.com/industry-analysis/liquid-biopsy-market
• www.openpr.com/news/4485588/liquid-biopsy-early-cancer-detection-market-set-for-strong
• www.globenewswire.com/news-release/2025/09/16/3150822/0/en/Liquid-Biopsy-Market-Size-Worth-USD-22-69-Billion-by-2034-Amid-Rising-Demand-for-Minimally-Invasive-Cancer-Testing.html
• www.precedenceresearch.com/liquid-biopsy-market
• www.rootsanalysis.com/reports/liquid-biopsy-and-nicd-market/279.html
• www.towardshealthcare.com/insights/us-liquid-biopsy-market-sizing
• www.biospace.com/press-releases/liquid-biopsy-market-size-to-surpass-usd-22-69-billion-by-2034-driven-by-early-cancer-detection-and-precision-diagnostics
• www.openpr.com/news/4463704/liquid-biopsy-market-2033-growth-drivers-technological

Clinical Validation Status

Note: This analysis includes only clinical trials linked to NIH-funded projects. Industry-sponsored and international trials may exist outside this sample.

The associated clinical trial sample spans a wide range of conditions - lung, colorectal, pancreatic, breast, ovarian, bladder, and head-and-neck cancers are the most frequently targeted - with the largest single enrollment figure being the NCI-sponsored Vanguard study at 24,000 participants, a pan-cancer observational effort that reflects the field's push toward population-scale validation. The majority of trials in the sample are observational or biomarker-validation studies rather than interventional Phase 2 or Phase 3 designs, consistent with a field still establishing analytical and clinical validity before pivoting to therapeutic utility endpoints. The status distribution across the sample is mixed: a substantial share are active or recruiting, alongside completed studies, but the sample also contains terminated, withdrawn, and suspended trials, indicating that execution challenges - including enrollment shortfalls and feasibility barriers - are real features of this development environment, not exceptions. Minimal residual disease monitoring and tissue-of-origin localization appear as emerging clinical use cases alongside primary early detection, with several trials explicitly evaluating ctDNA or cfDNA to guide post-surgical surveillance decisions.

Trial Summary

By Phase

Of the 74 linked trials, 53 are observational studies (72% - biomarker validation, cohort studies, biobank studies), 19 are interventional, and 2 carry another study_type designation (Expanded Access, Other, or unlabeled). Observational trials don't carry Phase 1-4 by design - ClinicalTrials.gov marks them N/A. The phase-labeled trials above are the phased subset of the 19 interventional trials; the remaining 11 interventional trials carry no phase label. This shape is expected for topics centered on diagnostics or biomarker discovery; a therapeutics-focused topic would typically show a phase-dominant distribution.

By Status

Active Trials

Multi-Cancer Detection Observational Cohort Study

• NCT ID: NCT06962995
• Phase: Not specified
• Status: RECRUITING
• Sponsor: Not specified
• Conditions: Not specified
• Enrollment: Not specified

Identification of Biomarkers for Early Detection of Pancreatic Cancer

• NCT ID: NCT00897494
• Phase: Not specified
• Status: COMPLETED
• Sponsor: Barbara Ann Karmanos Cancer Institute
• Conditions: Pancreatic Cancer
• Enrollment: 75 participants

Blood Markers of Early Pancreas Cancer

• NCT ID: NCT03568630
• Phase: Not specified
• Status: RECRUITING
• Sponsor: University of Nebraska
• Conditions: Diabetes Mellitus, Type 2, PreDiabetes, Pancreas Cyst, Chronic Pancreatitis, Genetic Predisposition to Disease, Inherited Disease
• Enrollment: 1,250 participants

Fluid Biopsy for the Diagnosis of Lung Cancer

• NCT ID: NCT04162678
• Phase: Not specified
• Status: TERMINATED
• Sponsor: University of Southern California
• Conditions: Lung Carcinoma
• Enrollment: 51 participants

Development of a New Early Detection Test to Reduce Racial Disparities in Endometrial Cancer (EC) Death Rates

• NCT ID: NCT04474184
• Phase: PHASE1
• Status: RECRUITING
• Sponsor: Mayo Clinic
• Conditions: Endometrial Carcinoma
• Enrollment: 33 participants

Detection of Plasma DNA Methylation in Peripheral Blood From Patients With Resectable Liver Cancer

• NCT ID: NCT04856046
• Phase: Not specified
• Status: RECRUITING
• Sponsor: Mayo Clinic
• Conditions: Resectable Hepatocellular Carcinoma
• Enrollment: 36 participants

Study of Healthy Cohort for Early Detection of Cancer

• NCT ID: NCT05193305
• Phase: Not specified
• Status: RECRUITING
• Sponsor: Johns Hopkins University
• Conditions: Healthy
• Enrollment: 10,000 participants

Collecting Blood Samples From Patients With and Without Cancer to Evaluate Tests for Early Cancer Detection

• NCT ID: NCT05334069
• Phase: Not specified
• Status: RECRUITING
• Sponsor: Alliance for Clinical Trials in Oncology
• Conditions: Acute Lymphoblastic Leukemia, Acute Myeloid Leukemia, Ann Arbor Stage I Lymphoma, Ann Arbor Stage II Lymphoma, Ann Arbor Stage III Lymphoma, Ann Arbor Stage IV Lymphoma, Chronic Lymphocytic Leukemia, Chronic Myeloid Leukemia, Gastroesophageal Junction Adenocarcinoma, Head and Neck Carcinoma, Hematopoietic and Lymphoid Cell Neoplasm, Invasive Breast Carcinoma, Kidney Carcinoma, Malignant Hepatobiliary Neoplasm, Malignant Solid Neoplasm, Melanoma, Muscle-Invasive Bladder Carcinoma, RISS Stage I Plasma Cell Myeloma, RISS Stage II Plasma Cell Myeloma, RISS Stage III Plasma Cell Myeloma, Sarcoma, Stage I Bladder Cancer AJCC v6 and v7, Stage I Breast Cancer AJCC v7, Stage I Colorectal Cancer AJCC v6 and v7, Stage I Esophageal Cancer AJCC V7, Stage I Gastric Cancer AJCC V7, Stage I Lung Cancer AJCC v7, Stage I Ovarian Cancer AJCC v6 and v7, Stage I Pancreatic Cancer AJCC v6 and v7, Stage I Prostate Cancer AJCC v7, Stage I Uterine Corpus Cancer AJCC v7, Stage II Bladder Cancer AJCC v6 and v7, Stage II Breast Cancer AJCC v6 and v7, Stage II Colorectal Cancer AJCC v7, Stage II Esophageal Cancer AJCC v7, Stage II Gastric Cancer AJCC v7, Stage II Lung Cancer AJCC v7, Stage II Ovarian Cancer AJCC v6 and v7, Stage II Pancreatic Cancer AJCC v6 and v7, Stage II Prostate Cancer AJCC v7, Stage II Uterine Corpus Cancer AJCC v7, Stage III Bladder Cancer AJCC v6 and v7, Stage III Breast Cancer AJCC v7, Stage III Colorectal Cancer AJCC v7, Stage III Esophageal Cancer AJCC v7, Stage III Gastric Cancer AJCC v7, Stage III Lung Cancer AJCC v7, Stage III Ovarian Cancer AJCC v6 and v7, Stage III Pancreatic Cancer AJCC v6 and v7, Stage III Prostate Cancer AJCC v7, Stage III Uterine Corpus Cancer AJCC v7, Stage IV Bladder Cancer AJCC v7, Stage IV Breast Cancer AJCC v6 and v7, Stage IV Colorectal Cancer AJCC v7, Stage IV Esophageal Cancer AJCC v7, Stage IV Gastric Cancer AJCC v7, Stage IV Lung Cancer AJCC v7, Stage IV Ovarian Cancer AJCC v6 and v7, Stage IV Pancreatic Cancer AJCC v6 and v7, Stage IV Prostate Cancer AJCC v7, Stage IV Uterine Corpus Cancer AJCC v7, Thyroid Gland Carcinoma
• Enrollment: 2,000 participants

A Diagnostic for the Early Detection of Bladder Cancer

• NCT ID: NCT05347342
• Phase: Not specified
• Status: ACTIVE, NOT RECRUITING
• Sponsor: Cedars-Sinai Medical Center
• Conditions: Bladder Cancer
• Enrollment: 173 participants

Feasibility of Cell-Free DNA Liquid Biopsy in Screening High-Risk Patients for Lung Cancer

• NCT ID: NCT05384769
• Phase: Not specified
• Status: RECRUITING
• Sponsor: City of Hope Medical Center
• Conditions: Lung Carcinoma
• Enrollment: 108 participants

Collecting Blood and Stool Samples to Detect Colorectal Cancer or Advanced Neoplasia in Lynch Syndrome Patients, CORAL Study

• NCT ID: NCT05410977
• Phase: Not specified
• Status: NOT YET RECRUITING
• Sponsor: Mayo Clinic
• Conditions: Colorectal Carcinoma, Lynch Syndrome
• Enrollment: 750 participants

Liquid Biopsy for Early Non-small Lung Cancer Detection

• NCT ID: NCT05462795
• Phase: Not specified
• Status: COMPLETED
• Sponsor: University of Arizona
• Conditions: Non Small-cell Lung Cancer
• Enrollment: 171 participants

Analysis of Whole Body Magnetic Resonance Imaging and Liquid Biopsy for Early Detection of Cancer in Patients With a Strong Family History of Cancer

• NCT ID: NCT05868486
• Phase: EARLY_PHASE1
• Status: ACTIVE, NOT RECRUITING
• Sponsor: City of Hope Medical Center
• Conditions: Hematopoietic and Lymphoid System Neoplasm, Malignant Solid Neoplasm
• Enrollment: 100 participants

Pre-analytical Factors Affecting ctDNA Analysis in Early and Locally Advanced Breast Cancer

• NCT ID: NCT05945290
• Phase: Not specified
• Status: COMPLETED
• Sponsor: Mayo Clinic
• Conditions: Anatomic Stage I Breast Cancer AJCC v8, Anatomic Stage II Breast Cancer AJCC v8, Anatomic Stage III Breast Cancer AJCC v8, Early Stage Breast Carcinoma, Locally Advanced Breast Carcinoma
• Enrollment: 114 participants

MAGESTIC Trial: MiRNA in Detecting Active Germ Cell Tumors in Early Suspected and MetastaTIC Disease Trial

• NCT ID: NCT06060873
• Phase: Not specified
• Status: RECRUITING
• Sponsor: University of Southern California
• Conditions: Malignant Testicular Germ Cell Tumor
• Enrollment: 418 participants

Patent Activity

Note: This analysis includes only patents linked to NIH-funded projects. Commercial patents and international filings may exist outside this sample. USPTO filing timelines also lag commercial activity by roughly 18-24 months, so very recent private R&D may not yet appear in patent data.

IP Landscape (this sample): Insufficient sample to characterize (4 grant-linked patents - a landscape label like "concentrated" or "fragmented" requires at least 10 patents to be meaningful; the shape below is descriptive of this specific sample, not the broader IP landscape)

Patent Holders in Sample: JOHNS HOPKINS UNIVERSITY, DANA-FARBER CANCER INST, CORNELL UNIVERSITY

Recent Activity: None of the 4 linked patents were filed or published within the last 2 years, suggesting no recent acceleration in NIH-linked patenting activity within this sample - though this may reflect NIH reporting lag or a shift of active commercial patenting to non-NIH-linked channels rather than a true slowdown in the field.

Confidence: Low - Evidence: 0 of 4 linked patents date to the last 2 years.

Freedom to Operate Assessment

Among the NIH-linked patents, the 4 linked patents span 3 assignees across the following technical areas: denaturation-enhanced mutation testing (Dana-Farber), nanoparticle and exosome subset-based cancer detection (Cornell), and nucleic acid assessment methods (Johns Hopkins, 2 patents). A new entrant working in nucleic acid-based liquid biopsy methods should note that Johns Hopkins holds 2 patents in this area within the sample, suggesting claim-level review of those nucleic acid assessment methods is warranted before proceeding - though commercial and international patents outside this NIH-linked sample may introduce additional FTO considerations not visible here.

Confidence: Low - Evidence: 4 linked patents from 3 assignees; with a small linked sample, the true commercial IP landscape is likely much larger and this FTO assessment should be treated as a preliminary signal only.

The 4 NIH-linked patents in this sample are held by 3 academic institutions - Johns Hopkins University (2 patents), Dana-Farber Cancer Institute (1 patent), and Cornell University (1 patent) - covering technical approaches that include nucleic acid methods, mutation detection under denaturing conditions, and exosome/nanoparticle-based detection. This pattern is consistent with early-stage foundational research originating in academic settings, which in this field often precedes commercial development by companies whose patents would not appear in an NIH-linked sample.

Confidence: Low - Evidence: 4 linked patents across 3 academic assignees; commercial IP from entities such as diagnostics companies is likely present in USPTO and PATENTSCOPE records outside this sample.

Strategic Implications

For a researcher working in or adjacent to liquid biopsy for early cancer detection, the most actionable step is to run a full USPTO, Google Patents, and PATENTSCOPE search before committing to a specific technical direction - the 4 NIH-linked patents here cover nucleic acid assessment, denaturing mutation detection, and exosome-based methods, but they represent only a slice of what is likely a much larger patent estate held by commercial diagnostics developers. Within this sample, the presence of 2 Johns Hopkins patents covering nucleic acid assessment methods is worth noting: if your research addresses nucleic acid preparation, extraction, or analysis in the liquid biopsy context, claim-level prior-art review against those specific methods - not the assignees as licensing targets, but the technical claims themselves - is a reasonable step in your IP due diligence. Academic researchers considering IP protection for novel methods should also note that the 3 assignees on record are all academic institutions, which is consistent with university-originated foundational IP being licensable through standard technology transfer channels, though whether any of these patents are available for licensing would require direct inquiry through those institutions' technology transfer offices.

Confidence: Low - Evidence: 4 linked patents from 3 assignees, 0 in the last 2 years; with a linked sample this small, field-level conclusions are not supportable and findings should be treated as a preliminary map pending a full patent database search.

Patent Analysis

Among the 4 linked patents in this sample, the covered technical areas span: digital PCR efficiency and absolute quantification of nucleic acid targets from limited specimens (Dana-Farber Cancer Institute); exosome and exomere subtype characterization by size fractionation for multi-analyte cancer detection including proteins, glycans, lipids, and nucleic acids (Cornell University); and dual-strand barcoding with PCR-based enrichment for sequencing library preparation and mutation identification, covered by 2 separate filings (Johns Hopkins University). The presence of method-level IP covering both upstream sample preparation and downstream analyte quantification suggests that translational efforts are focused on workflow standardization and error-reduction steps that are prerequisite to clinical-grade assay deployment. The assignee set - 3 academic medical institutions across 4 filings - is consistent with early-stage IP emanating from NIH-funded discovery work, where commercialization pathways typically involve licensing to diagnostic developers rather than direct product launch. Given the small number of linked patents, this sample is insufficient to characterize the broader IP environment for liquid biopsy, and readers should treat these filings as illustrative of technical focal points rather than as a representative survey.

Patent Summary

Key Patents

DENATURATION-ENHANCED DNA MUTATION TESTING FOR LIMITED BIOLOGICAL SPECIMENS

• Patent #: 11884970
• Assignee: DANA-FARBER CANCER INST

Disclosed herein are methods to improve the efficiency of absolute quantification of nucleic acid targets such as digital PCR and digital isothermal amplification, and/or reduce the amount of nucleic ...

Nanoparticles and Distinct Exosome Subsets for Detection and Treatment of Cancer

• Patent #: 12259389
• Assignee: CORNELL UNIVERSITY

The present invention is directed to methods of diagnosing, prognosing, and managing treatment of cancer in a subject. These methods involve selecting a subject having cancer and obtaining, from the s...

METHODS AND MATERIALS FOR ASSESSING NUCLEIC ACIDS

• Patent #: 12442038
• Assignee: JOHNS HOPKINS UNIVERSITY

Provided herein are systems, kits, compositions and methods for sequencing library preparation and sequencing workflow (e.g., for the identification of mutations). In certain embodiments, provides her...

METHODS AND MATERIALS FOR ASSESSING NUCLEIC ACIDS

• Patent #: 12553082
• Assignee: JOHNS HOPKINS UNIVERSITY

Provided herein are systems, kits, compositions and methods for sequencing library preparation and sequencing workflow (e.g., for the identification of mutations). In certain embodiments, provides her...

Key Publications

Note: This analysis includes only publications linked to NIH-funded projects and may not represent the complete body of literature in this field. PubMed indexing typically lags publication date by 1-3 months for peer-reviewed articles; preprints appear faster but are not peer-reviewed.

The publication record associated with this sample addresses several interlinked scientific questions: the comparative sensitivity of cfDNA methylation versus mutation-based detection for early-stage cancers, the utility of alternative analytes such as circular RNA and exosome-associated microRNA for pancreatic cancer detection, and the integration of machine learning with fragmentomics or Alu element profiling to extract cancer signal from whole-genome sequencing data. Methodological advances appearing in the literature include MAESTRO-Pool for highly parallel tumor-informed MRD detection at sub-parts-per-million allele fractions in melanoma, A-PLUS for machine-learning-based aneuploidy and Alu pattern analysis across 7,600-plus plasma samples, and True2 sequencing for ultralow-frequency somatic mutation detection in peritumoral glioma tissue. Publication venues in the sample include Clinical Cancer Research, Cancer Cell, Nature, and Gastroenterology, alongside high preprint volume on bioRxiv, suggesting the field spans both rapid-iteration computational work and peer-reviewed clinical translation. A recurring theme across the literature is the recognition that single-analyte approaches face sensitivity-specificity tradeoffs at early cancer stages, driving published work toward multi-marker panels and algorithmic integration of imaging, protein biomarkers, and nucleic acid signals.

Must-Read Publications

1. A Circulating Panel of circRNA Biomarkers for the Noninvasive and Early Detection of Pancreatic Ductal Adenocarcinoma.

• PMID: 37839499

Why it matters: Among the linked publications, this paper stands out as a direct methodological contribution to early cancer detection via liquid biopsy. It demonstrates that a circular RNA panel can detect pancreatic ductal adenocarcinoma at early stages noninvasively, addressing one of the hardest diagnostic problems in oncology.

Key finding: A five-circRNA plasma panel achieved an AUC of 0.94 for PDAC detection when combined with CA19-9, including in CA19-9-negative patients.

2. Tumor- and circulating-free DNA methylation identifies clinically relevant small cell lung cancer subtypes.

• PMID: 38278149

Why it matters: Among the linked publications, this study shows that DNA methylation patterns in cell-free DNA can classify small cell lung cancer subtypes and track phenotypic evolution longitudinally, offering a noninvasive approach to subtype-guided precision therapy in a cancer where tissue access is often limited.

Key finding: A cfDNA methylation classifier distinguished SCLC subtypes from plasma and revealed that SCLC phenotypes can evolve during disease progression.

3. MAESTRO-Pool Enables Highly Parallel and Specific Mutation-Enrichment Sequencing for Minimal Residual Disease Detection in Cohort Studies.

• PMID: 38069911

Why it matters: Among the linked publications, MAESTRO-Pool addresses a core technical barrier in tumor-informed MRD detection by enabling massively parallel bespoke testing across many patients simultaneously, while achieving sensitivity down to 0.78 parts per million with built-in specificity benchmarking.

Key finding: MAESTRO-Pool detected MRD down to 0.78 parts per million with only one false positive across 784 patient-unmatched tests.

Publication Summary

• Total linked publications: 792
• Unique journals: 323
• Publications with year metadata: 790 (the remaining 2 have no parsable year on the PubMed record and are not shown in the year distribution below)

Top Journals:

• bioRxiv : the Preprint Server for Biology (25)
• Clinical Cancer Research : an Official Journal of the American Association for Cancer Research (22)
• Nature Communications (18)
• Cancers (17)
• Npj Precision Oncology (14)

Key Organizations

Top 15 of 64 funded organizations, ranked by NIH funding within the analyzed sample.

Trials, patents, and publications counted here are those where an NIH grant belonging to this org was acknowledged. Patent assignee, trial sponsor, and publication first-author affiliation may differ from the org named on the underlying NIH grant. See the Patent Activity section for a separate view by assignee.

Key Researchers

Next Steps

Concrete actions the report suggests based on what's above. Not exhaustive - use these as a starting checklist you can extend.

• [ ] Map your methodological position against the funded project cluster. Review the Key Research Projects table to identify which analyte types (ctDNA, exosomes, CTCs, cfRNA, methylation) and cancer types are most densely funded within the $103.0M NIH portfolio. Determine whether your own methodology sits in a crowded cluster or a thinner area, keeping in mind that apparent gaps may reflect taxonomy artifacts rather than true whitespace - cross-check adjacent NIH portfolios (metabolomics, epigenomics, single-cell genomics) in NIH RePORTER before drawing conclusions.

• [ ] Audit the funded abstracts in your methodological category before writing your next proposal. Pull the project abstracts in the Key Research Projects table that share your analyte or detection approach. Read the funded abstracts and associated publications for those projects directly - this surfaces the framing language, specific aims structures, and outcome metrics that study sections have already rewarded, without relying on secondhand characterization of any individual researcher's program.

• [ ] Run a full patent search to characterize the IP landscape yourself. The report links only 4 patents to NIH grants in this sample, which is too small to draw any conclusions about how filed IP is distributed or where whitespace exists. Search USPTO, Google Patents, and PATENTSCOPE using assignee, inventor, and keyword filters (circulating tumor DNA, liquid biopsy, cell-free nucleic acid, early detection) to build a full picture of filed IP before deciding whether a given technical approach is encumbered or open.

• [ ] Target the right grant mechanism to your project's maturity and risk profile. The $103.0M portfolio spans multiple mechanisms - use NIH RePORTER to filter the 117 projects in this sample by mechanism (R01, R21, U01, P01, SBIR/STTR) and note which mechanisms cluster around which analyte types or cancer indications. If your work is early-stage or pivoting to a less-studied analyte, an R21 exploratory grant or an SBIR Phase I may be more appropriate entry points than a full R01; verify current funding opportunity announcements at NCI's Cancer Biomarkers Research Group and the Early Detection Research Network (EDRN) program pages.

• [ ] Investigate the low clinical-translation signal before assuming it is a gap. The sample contains 74 trials post-filter, but trial counts only reflect studies acknowledging an NIH grant - commercially funded and industry-sponsored trials are not captured in this sample in this dataset. Before framing a proposal around an underserved cancer type or analyte with few linked trials, search ClinicalTrials.gov independently by intervention type and biomarker category to determine whether the apparent underrepresentation reflects real unmet need or simply non-NIH funding channels.

• [ ] Review the Key Organizations table to map institutional activity in your specific approach. Rather than relying on overall funding totals, filter the 64 funded organizations by the methodological category closest to your own work. This lets you self-direct a landscape read - seeing which institutions are active in, for example, methylation-based detection versus protein biomarker panels - so you can frame your own proposal's novelty argument accurately and identify where published collaborative infrastructure already exists in the literature.

• [ ] Check the top-funded PI portfolios for aim-level framing cues. The top 5 PIs collectively hold 10 projects (see Key Researchers table). Without targeting any individual, search NIH RePORTER for the project numbers associated with those grants and read the public-facing project abstracts. Note the specific aims language, the cancer types selected, and the validation endpoints described - these are direct signals about what the relevant study sections consider fundable scope and rigor in this domain.

• [ ] Reassess the white-space signals finding before building a proposal around a perceived gap. The report returns no top white-space signals for this portfolio. This means the analysis did not surface high-confidence underrepresented areas relative to broader NIH funding ratios - treat this as a data-quality flag, not a confirmation that the field is fully saturated. Broader-NIH ratios are directional at low topic-sample counts (117 projects). Run your own RePORTER search filtered by NCI program codes and disease site to test whether specific analyte-cancer type combinations are underrepresented, and validate any candidate gap against published systematic reviews before committing proposal resources.

About This Report

Methodology

This report analyzes a curated subset of NIH-funded research projects most relevant to liquid biopsy for early cancer detection. Projects were identified using semantic search (AI-based conceptual matching) and filtered by match quality.

Search Interpretation Used: Standard - "liquid biopsy and circulating tumor DNA for early cancer detection and screening"

Note on Funding Figures: Per-project funding amounts shown in this report are the sum of award totals across all budget periods for each project (not just the most recent year). Funding-by-year figures show actual spend per fiscal year drawn from the underlying NIH RePORTER budget-period rows, so a multi-year project contributes to each year it received funding. The current NIH fiscal year (Oct 1 - Sep 30) is partial when this report is generated; that year is labeled "(YTD)" in tables and charts and should not be compared directly to fully-reported prior years.

Note on Funding Attribution: Clinical trials are surfaced through two paths - direct linkage to topically-relevant projects, and semantic similarity between the trial's own title and the topic (using the same vector-embedding mechanism that powers project search, gated by a dedicated trial-inclusion threshold). The second path catches trials that sit under broad institutional umbrella awards (e.g., P30 cancer center support grants, CTSA hubs) whose underlying parent grant covers many unrelated programs. Those trials are reported because their titles are clearly about the topic, but their umbrella grants' funding is not rolled into Total Committed Funding - only projects whose own abstracts clear the project-relevance threshold contribute to funding totals. This keeps the headline funding number topically attributable rather than inflated by institutional overhead grants that happen to host one relevant program among many.

Match Quality Tiers:

Sample Composition:

Sample Interpretation:

• All 117 matches are Precise (similarity ≥50%). This is not a tuned threshold - it reflects the topic mapping to a tightly-bounded research area where most relevant NIH grants land above the 50% similarity cutoff. Broader topics with less coherent literature produce mixed Precise + Balanced splits (typically 60/40 to 80/20). Note that "Precise" measures semantic similarity to the query, not perfect topical fit - a project can score above the threshold and still touch adjacent research areas (e.g., a project whose main focus is diagnostic biomarkers but whose abstract mentions sepsis biomarkers as comparator work). Treat this signal as "the field's vocabulary aligns well with our query," not as "every project is a pure topic match."

Linked Data:

Limitations

This analysis focuses on depth over breadth, capturing publicly-funded academic research. It does not include privately-funded industry R&D or international research outside NIH grants.

Data current as of August 7, 2026.