Topics and Trends in Most Cited Cancer Genomics and Diagnostics Papers

Ranked by citations 18 months after publication

Class of 2026 (Papers Published in 2024)

What topics and trends defined most-cited Cancer Genomics and Diagnostics research in the Class of 2026?

Among early-high-impact cancer genomics and diagnostics papers, tumor heterogeneity, tumor microenvironment, copy number variation, and immune cell infiltration dominate the Class of 2026 cohort. Spatial transcriptomics, copy number variation, and immune cell infiltration rose sharply versus Class of 2025, while circulating tumor DNA, cell-free DNA, and liquid biopsy-focused studies declined most.

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Updated July 19, 2026

At a glance

Field
Cancer Genomics and Diagnostics
Cohort label
Class of 2026 (2024 publications)
Papers analyzed
10,175
Papers ranked
20
Top topics in ranked papers
Tumor heterogeneity, tumor microenvironment, copy number variation, immune cell infiltration
Publication window
Jan 1, 2024 – Dec 31, 2024
Eligibility
Research articles; reviews excluded
Citation window
18 months post-publication
18m citation range
81–412
Data source
OpenAlex · Retrieved Jul 2026
License
CC BY 4.0

Rankings

20 papers ranked by 18-month citation count

#1 of 10,175
41218m citations

Genomic data in the All of Us Research Program

All of Us Research Program Genomics InvestigatorsNature202410.1038/s41586-023-06957-x

Alexander G. BickVanderbilt University Medical Center, United States

All of Us Research Programclinical-grade genome sequencesunder-represented populations in biomedical researchracial and ethnic minoritiesgenetic variant discoverycoding variantsLongitudinal clinical datadisease-associated genetic variantsEuropean ancestryAfrican ancestryreplication ratesAll of Us Researcher Workbenchdata passport modelgenomic medicinediverse cohort studysummary-level dataindividual-level data access
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#2 of 10,175
27118m citations

A foundation model for clinical-grade computational pathology and rare cancers detection

Eugene Vorontsov, Alican Bozkurt, Adam Casson, George Shaikovski, Michal Zelechowski, Kristen Severson et al.Nature Medicine202410.1038/s41591-024-03141-0

Siqi LiuPaige, United States

Virchowfoundation modelcomputational pathologyHistopathology imagespan-cancer detectionRare cancersBiomarker predictioncell identificationspecimen-level area under the curvetissue-specific clinical-grade modelslimited labeled training dataClinical decision supportPrecision medicine
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#3 of 10,175
21318m citations

A Cell-free DNA Blood-Based Test for Colorectal Cancer Screening

Daniel C Chung et al.New England Journal of Medicine202410.1056/nejmoa2304714

Daniel C ChungMassachusetts General Hospital, United States

Cell-free DNABlood-based testcolorectal cancer screeningscreening colonoscopyAdvanced neoplasiasensitivity for colorectal cancerspecificity for advanced neoplasiastage I, II, III colorectal canceraverage-risk screening populationECLIPSE trialEarly cancer detectionscreening adherencenonadvanced precancerous lesionsclinical validation cohort
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#5 of 10,175
14418m citations

ctDNA-based molecular residual disease and survival in resectable colorectal cancer

Yoshiaki Nakamura, Jun Watanabe et al.Nature Medicine202410.1038/s41591-024-03254-6

Takayuki Yoshino, Eiji OkiNational Cancer Center Hospital East, Japan

Circulating tumor DNAMinimal residual diseaseCIRCULATE-Japan GALAXY studyResectable colorectal cancerstage II-III colon cancerstage IV CRCadjuvant chemotherapydisease-free survivaloverall survivalMRD windowctDNA dynamicstransient clearancespontaneous clearancepost-resection monitoringRisk stratificationactionable biomarker subsets
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#6 of 10,175
13518m citations

Origins and impact of extrachromosomal DNA

Chris Bailey, Oriol Pich et al.Nature202410.1038/s41586-024-08107-3

Paul S. Mischel, Mariam Jamal‐Hanjani, Charles SwantonThe Francis Crick Institute, United Kingdom

Extrachromosomal DNA100,000 Genomes ProjectDriver mutationimmunomodulatory gene amplificationlymphocyte-mediated immunityImmune cell infiltrationenhancer-only ecDNApromoter-only ecDNAlncRNA elementstrans interactions between ecDNAsTobacco-induced mutagenesisHomologous recombination deficiencytissue-context-based selectionecDNA in metastasespost-treatment ecDNA prevalenceecDNA and overall survivalinflammatory gene amplificationecDNA formation mechanismsecDNA progression mechanismscombinatorial ecDNA effects
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#7 of 10,175
12718m citations

Tumour evolution and microenvironment interactions in 2D and 3D space

Chia-Kuei Mo, Jingxian Liu et al.Nature202410.1038/s41586-024-08087-4

William E. Gillanders, Ryan C. Fields, Benjamin J. Raphael, Feng Chen, Li DingWashington University in St Louis, United States

Visium spatial transcriptomicstumour microregionsspatial subclonesSingle-nucleus RNA sequencingCODEXCopy number variationOncogenic activationImmune cell infiltrationmacrophage localization3D tumour reconstructionserial section co-registrationimmune hot neighbourhoodsimmune cold neighbourhoodsimmune exhaustion markersantigen presentationmetabolic activitytumour-stromal interactionssubclonal heterogeneityunsupervised deep-learningTumor microenvironment
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#8 of 10,175
11618m citations

A pan-cancer analysis of the microbiome in metastatic cancer

Thomas W Battaglia et al.Cell202410.1016/j.cell.2024.03.021

Emile E. VoestNetherlands Cancer Institute, Netherlands

Metastasistumor microbiomemetagenomicsorgan-specific microbial tropismanaerobic bacteriaHypoxiamicrobial diversityImmune cell infiltrationFusobacteriumImmunotherapy resistancelung cancerlongitudinal tumor samplingtemporal microbial evolutionpan-cancer analysismetastatic tumor biopsiesassembly-based metagenomicshost immune modulationanticancer therapy response
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#9 of 10,175
11618m citations

The genomic landscape of 2,023 colorectal cancers

Alex J Cornish, Andreas J Gruber, Ben Kinnersley, Daniel Chubb, Anna Frangou, Giulio Caravagna, Boris Noyvert, Eszter Lakatos, Henry M Wood, Steve Thorn, Richard Culliford et al.Nature202410.1038/s41586-024-07747-9

Ian TomlinsonInstitute of Cancer Research, United Kingdom

Colorectal cancerWhole-genome sequencing100,000 Genomes ProjectCRC driver genesDriver mutationmicrosatellite-stable CRCmicrosatellite instabilityGenomic instabilityMutational signaturesEscherichia coli pks+ colibactinSBS93 signatureimmune-escape mutationsHLA copy number changeshypermutant tumoursBRCA1IDH1Molecular subtypingprognostic associationsmutational profiles across colorectum
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#10 of 10,175
11518m citations

ClinVar: updates to support classifications of both germline and somatic variants

Melissa J Landrum et al.Nucleic Acids Research202410.1093/nar/gkae1090

Melissa J LandrumNational Institutes of Health, United States

ClinVargermline variantsSomatic alterationoncogenicity classificationclinical impact classificationvariant classification aggregationClinVar XML formatClinVar VCF filessubmission APIbatch file submissionVCV pagesclinical testing laboratoriescancer genomicsVariant annotationgenomic testing transparency
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#11 of 10,175
10918m citations

Transient loss of Polycomb components induces an epigenetic cancer fate

V Parreno, V Loubiere et al.Nature202410.1038/s41586-024-07328-w

Anne‐Marie Martinez, Giacomo CavalliCNRS, France

Polycomb group proteinsepigenetic cancer fatetranscriptional silencingnon-genetic tumorigenesisDrosophilaJAK-STAT signaling pathwayzfh1ZEB1 oncogeneirreversible gene derepressiontransient Polycomb perturbationEpigenomic alterationsinheritance of altered cell fatescancer initiation without driver mutationsMalignant transformation
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#12 of 10,175
10418m citations

Insights for precision oncology from the integration of genomic and clinical data of 13,880 tumors from the 100,000 Genomes Cancer Programme

Alona Sosinsky, John Ambrose, William Cross, Mark Caulfield, Nirupa Murugaesu et al.Nature Medicine202410.1038/s41591-023-02682-0

Mark J. Caulfield, Nirupa MurugaesuGenomics England, United Kingdom

100,000 Genomes ProjectWhole-genome sequencingprecision cancer care13,880 solid tumors33 cancer typesReal-world dataSomatic alterationCopy number variationactionable structural variantsGlioblastomasarcomaHomologous recombination deficiencyHigh-grade serous ovarian carcinomapathogenic germline variantscombined somatic and germline analysispangenomic markersLongitudinal clinical datasurvival analysisprognostic cancer genes
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#13 of 10,175
10318m citations

Prognostic genome and transcriptome signatures in colorectal cancers

Luís Nunes, Fuqiang Li, Meizhen Wu, Tian Luo et al.Nature202410.1038/s41586-024-07769-3

Kui Wu, Bengt Glimelius, Cong Lin, Tobias SjöblomUppsala University, Sweden

Whole-genome sequencingTranscriptomic profilingColorectal cancerDriver mutationWNT pathwayEGFR pathwayTGFβ pathwaymitochondrial CYB geneCopy number variationCOSMIC SBS44 signaturemicrosatellite instabilityMolecular subtypingmutation timing analysisMutational signaturesCo-mutationsHypoxiaImmune cell infiltrationPrognostic biomarkerMulti-omics integration
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#14 of 10,175
10018m citations

Single-cell and spatial transcriptomics analysis of non-small cell lung cancer

Marco De Zuani, Haoliang Xue et al.Nature Communications202410.1038/s41467-024-48700-8

Ana CvejicWellcome Sanger Institute, United Kingdom

Non-small cell lung canceradenocarcinomaSquamous cell carcinomaSingle-cell RNA sequencingSpatial transcriptomicsTumor-associated macrophagesanti-inflammatory macrophagesNK cellsT cellsNK cell cytotoxicityImmune checkpoint blockademacrophage reprogrammingcholesterol exportfoetal-like transcriptional signatureiron effluxTumor microenvironmentMyeloid cells
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#15 of 10,175
9418m citations

Priming agents transiently reduce the clearance of cell-free DNA to improve liquid biopsies

Carmen Martin-Alonso, Shervin Tabrizi, Kan Xiong et al.Science202410.1126/science.adf2341

Carmen Martin-Alonso, Shervin Tabrizi, Kan Xiong, J. Christopher Love, Sangeeta N. Bhatia, Viktor A. AdalsteinssonKoch Institute for Integrative Cancer Research, United States

Liquid biopsyCell-free DNACirculating tumor DNAcfDNA clearancepriming agentsintravenous administrationnanoparticlesDNA-binding antibodiestumor-bearing miceEarly cancer detectionblood draw timingin vivo manipulationanalyte recoverysensitivity enhancement
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#16 of 10,175
8918m citations

A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics

Danh-Tai Hoang et al.Nature Cancer202410.1038/s43018-024-00793-2

Danh-Tai Hoang, Eric A. Stone, Eytan RuppinAustralian National University, Australia

deep learningcancer treatment response predictionHistopathology imagestranscriptomics imputationGene expression prediction from histologySpatial transcriptomicsConvolutional neural networktreatment outcome predictiondigital pathologyMulti-modal learningcomputational pathologytherapy response biomarkersprecision oncology
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#18 of 10,175
8318m citations

Mime: A flexible machine-learning framework to construct and visualize models for clinical characteristics prediction and feature selection

Hongwei Liu et al.Computational and Structural Biotechnology Journal202410.1016/j.csbj.2024.06.035

Siyi Wanggou, Xuejun LiCentral South University, China

Mimemachine-learning frameworktranscriptional dataclinical characteristics predictionfeature selectionPIEZO1-associated signaturesprognosis predictionimmunotherapy response predictionSDC1gliomaNext-generation sequencingTumor heterogeneityR packageintegration modelGene signaturepatient outcome prediction
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#19 of 10,175
8218m citations

Enhancing transcription–replication conflict targets ecDNA-positive cancers

Jun Tang, Natasha E Weiser, Guiping Wang et al.Nature202410.1038/s41586-024-07802-5

Christian A. Hassig, Paul S. Mischel, Howard Y. ChangStanford University, United States

Extrachromosomal DNAtranscription-replication conflictsingle-stranded DNAReplication stresspRPA2-S33DNA double strand breaksCHK1CHK1 inhibitionBBI-2779FGFR2 amplificationinfigratinibpan-FGFR inhibitorgastric cancersynthetic lethalityAcquired resistanceS-phase checkpointnucleotide incorporationecDNA-directed therapy
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#20 of 10,175
8118m citations

Integrative single-cell analysis of human colorectal cancer reveals patient stratification with distinct immune evasion mechanisms

Xiaojing Chu, Xiangjie Li, Yu Zhang et al.Nature Cancer202410.1038/s43018-024-00807-z

Zemin Zhang, Sijin ChengChangping Laboratory, China

Single-cell RNA sequencingColorectal cancerTumor microenvironmentImmune evasionRisk stratificationT cell exhaustionCancer-associated fibroblastsMyeloid cellsImmune cell infiltrationimmune checkpoint expressioncellular heterogeneityCancer cellsimmunosuppressive pathwaysPrognostic biomarkerMulti-omics integration
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Dominant research themes and year-over-year shifts in Cancer Genomics and Diagnostics

What Topics Define the Class of 2026?

The word cloud of canonical topics across the 50 highest 18-month-cited papers in cancer genomics and diagnostics reveals a field oriented toward integrative, clinically actionable molecular characterization rather than single-modality assays. Tumor heterogeneity stands out as the most frequently mentioned canonical topic, appearing in 10 of 50 papers (normalized frequency 0.20), reflecting growing emphasis on tumor evolution and subclonal diversity. Tumor microenvironment (9 mentions), copy number variation (7), immune cell infiltration (7), and single-cell RNA sequencing (7) form a second tier of dominant themes, signaling convergence between tissue genomics, spatial profiling, and immune contexture. Larger type further highlights spatial transcriptomics, circulating tumor DNA, colorectal cancer, driver mutation, and KRAS mutation—topics that cluster around comprehensive profiling pipelines and targeted therapy selection. Smaller but visible terms—including molecular subtyping, multi-omics integration, and extrachromosomal DNA—suggest that influential 2024 publications increasingly frame cancer diagnostics as multi-layered data integration problems spanning DNA, RNA, imaging, and clinical outcome endpoints.

Leading research themes
Leading research themes

How Did Topics Shift from the Class of 2025 to the Class of 2026?

Comparing normalized concept frequencies between the Class of 2025 (2023 publications) and Class of 2026 (2024 publications) cohorts shows a clear reorientation of early-high-impact research priorities. Immune cell infiltration and copy number variation exhibited the largest gains (+0.10 normalized frequency; 2 versus 7 papers), followed by spatial transcriptomics (+0.10; 1 versus 6), and driver mutation (+0.08; 1 versus 5). The topic evolution card underscores that Class of 2026 bars extend furthest for tumor heterogeneity, tumor microenvironment, copy number variation, and immune cell infiltration—topics aligned with single-cell sequencing, spatial genomics, and precision oncology infrastructure. Conversely, several themes prominent in the Class of 2025 cohort receded: circulating tumor DNA (−0.12), cell-free DNA (-0.06), liquid biopsy (-0.04), and immune checkpoint blockade (-0.04). Together, these shifts suggest that the most-cited 2024 papers emphasize comprehensive spatial and single-cell platforms, tumor–immune biology, and disease-specific large-cohort studies, while some earlier liquid biopsy and prognostic framing lost ground among early-high-impact work.

How topics shifted year over year
How topics shifted year over year
Methodology

PRI identifies high-impact research using a transparent, topic-agnostic framework applied consistently across scientific domains. Bibliographic records are drawn from OpenAlex, including publication dates, citation relationships, and document types.

This ranking covers the Class of 2026 cohort: journal articles published in 2024. Reviews and other non-article document types are excluded to ensure comparability.

Research impact is quantified with an 18-month post-publication citation window—the number of citing works published within 18 months of each paper's publication date. This metric captures early impact while controlling for publication age.

An LLM-based relevance classifier then reviews each candidate's title and abstract to confirm substantive alignment with the target domain. Only papers classified as relevant appear in the final ranking.

Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459

Full methodologyGitHubbioRxiv preprint

Cite this ranking

Pepkio Research Index (PRI). Topics and Trends in Most Cited Cancer Genomics and Diagnostics Papers, Class of 2026. https://pri.pepkio.com/top-papers/cancer-genomics-and-diagnostics/2026. Accessed 2026-08-20.

Methodology
Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459

Source data

The full ranking corpus and analysis files are openly available on an external repository. Please cite the dataset below when reusing this data.

View source dataset →

Pepkio Research Index (2026). Cancer Genomics and Diagnostics Top Papers, Class of 2026 [Data set]. Figshare. https://doi.org/10.6084/m9.figshare.32869871