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 microenvironment, precision medicine, digital pathology, and whole-genome sequencing dominate the Class of 2026 cohort. Whole-genome sequencing, precision medicine, and colorectal cancer rose sharply versus Class of 2025, while tumor evolution, NSCLC, liquid biopsy, circulating tumor DNA, and prognosis-focused studies declined most.

See details ↓

Updated July 12, 2026

At a glance

Field
Cancer Genomics and Diagnostics
Cohort label
Class of 2026 (2024 publications)
Papers analyzed
10,203
Papers ranked
20
Top topics in ranked papers
Tumor microenvironment, precision medicine, digital pathology, whole-genome sequencing
Publication window
Jan 1, 2024 – Dec 31, 2024
Eligibility
Research articles; reviews excluded
Citation window
18 months post-publication
18m citation range
88–418
Data source
OpenAlex · Retrieved Jul 2026
License
CC BY 4.0

Rankings

20 papers ranked by 18-month citation count

#1 of 10,203
41818m citations

Genomic data in the All of Us Research Program

The All of Us Research Program Genomics Investigators et al.Nature202410.1038/s41586-023-06957-x

CorrespondingAlexander G. BickInstitutionVanderbilt University Medical Center, United States

All of Us Research ProgramWhole-genome sequencingclinical-grade genome sequencesGenomic variantscoding variantspreviously unreported genetic variantshuman disease genetic basislongitudinal cohort studyDiverse populationselectronic health record linkagegenotype-phenotype associationsgenome-wide association studyreplication of genetic associationsEuropean ancestryAfrican ancestryhealth disparities in genomicsbiobankgenomic medicinedata passport modelAll of Us Researcher Workbenchindividual-level genomic data accesssummary-level datapopulation diversity in biomedical researchvariant discoverypolygenic riskgenomic data sharinghuman geneticsbiomedical research infrastructurelongitudinal health dataancestry-stratified analysisrare variantscommon variants
#2 of 10,203
27218m 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

CorrespondingSiqi Liu, Thomas J. FuchsInstitutionPaige, United States

Foundation modelDigital pathologyartificial intelligenceclinical decision supportPrecision medicineVirchowpan-cancer detectionrare cancers detectionbiomarker predictionCell type annotationarea under the receiver operating characteristic curveSpecimen-level classificationcommon cancersrare cancer variantstissue-specific modelsself-supervised learninglabeled training datatransfer learningCancer diagnosisclinical-grade modelslarge-scale pretraining
#3 of 10,203
23018m citations

Recommendations for the use of next-generation sequencing (NGS) for patients with advanced cancer in 2024: a report from the ESMO Precision Medicine Working Group

M.F. Mosele et al.Annals of Oncology202410.1016/j.annonc.2024.04.005

CorrespondingFabrice AndréInstitutionGustave Roussy, France

next-generation sequencingPrecision medicineAdvanced cancertumour NGSESMO Scale for Clinical Actionability of molecular Targets (ESCAT)ESMO Precision Medicine Working Groupclinical actionabilityMolecular targettreatment decision-makingcost-effectivenessaccessibilityNon-small cell lung cancerprostate cancerColorectal cancercholangiocarcinomaovarian cancerbreast cancergastrointestinal stromal tumourssarcomathyroid cancercancer of unknown primaryrare tumoursMetastasistumour-agnostic alterationstumour-agnostic therapiesmatched therapiesclinical research centresroutine clinical practiceGenomic profilingmolecular profilingbiomarker-driven therapySomatic mutationsGenomic alterations
#4 of 10,203
21418m citations

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

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

CorrespondingWilliam M GradyInstitutionMassachusetts General Hospital and Harvard Medical School, Canada

Colorectal cancerCirculating tumor DNABlood-based biomarkersColorectal cancer screeningearly detectionAdvanced neoplasiasensitivityspecificityclinical validityaverage-risk screening populationstage I colorectal cancerstage II colorectal cancerstage III colorectal cancernonadvanced precancerous lesionsscreening adherencecolorectal cancer-related mortalityLiquid biopsyECLIPSE trialGuardant HealthCancer biomarkerDNA methylationnoninvasive cancer screeningcoprimary outcomespositive predictive valuenegative predictive value
#5 of 10,203
19718m citations

Precision treatment in advanced hepatocellular carcinoma

Xupeng Yang, Chen Yang, Shu Zhang et al.Cancer Cell202410.1016/j.ccell.2024.01.007

CorrespondingJia Fan, Cun Wang, Qiang GaoInstitutionFudan University, China

Liver canceradvanced hepatocellular carcinomaPrecision cancer carePrecision medicineTargeted therapyBiomarkerMolecular targetsorafeniblenvatinibregorafenibcabozantinibramucirumabImmune checkpoint inhibitionatezolizumabbevacizumabnivolumabpembrolizumabtremelimumabdurvalumabVEGF pathwayPD-1/PD-L1 pathwayCTLA-4Tumor microenvironmentGenomic profilingnext-generation sequencingTumor mutational burdenmicrosatellite instabilityTERT promoter mutationsTP53 mutationsCTNNB1 mutationARID1AMET amplificationFGF19 amplificationFGFR inhibitionHER2 amplificationRAS/MAPK pathwayWnt/β-catenin pathwayPI3K/AKT/mTOR pathwayalpha-fetoproteinBarcelona Clinic Liver Cancer stagingCirrhosishepatitis B virushepatitis C virussystemic therapycombination immunotherapyBiomarker-driven clinical trialpatient selectionAcquired drug resistancetranscriptomic subtypesmulti-kinase inhibitorsangiogenesis inhibition
#6 of 10,203
17018m citations

Renal cell carcinoma: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up

T. Powles et al.Annals of Oncology202410.1016/j.annonc.2024.05.537

CorrespondingT. PowlesInstitutionQueen Mary University of London, United Kingdom

Renal cell carcinomaESMO Clinical Practice Guidelinediagnosistreatmentfollow-upincidencemalignancyclear cell renal cell carcinomanon-clear cell renal cell carcinomapapillary renal cell carcinomachromophobe renal cell carcinomasarcomatoid differentiationVHL genemTOR pathwayVEGF pathwaytyrosine kinase inhibitorsImmune checkpoint inhibitionPD-1PD-L1CTLA-4sunitinibpazopanibnivolumabipilimumabpembrolizumabaxitinibcabozantiniblenvatinibeverolimustemsirolimusbevacizumabcombination immunotherapynephrectomycytoreductive nephrectomypartial nephrectomymetastasectomyablative therapiesstereotactic body radiotherapyTargeted therapyfirst-line treatmentsecond-line therapyprognostic risk groupsIMDC risk scoreMSKCC risk scoreBiomarkerstagingTNM classificationmetastatic renal cell carcinomalocalized renal cell carcinomaAdjuvant therapysurveillancehereditary renal cell carcinomavon Hippel-Lindau diseaseangiogenesisTumor microenvironmentclinical trialOverall survivalprogression-free survivalObjective response rate
#7 of 10,203
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

CorrespondingTakayuki Yoshino, Eiji OkiInstitutionNational Cancer Center Hospital East, Japan

Circulating tumor DNAMinimal residual diseaseColorectal cancerresectable colorectal cancerCIRCULATE-Japan GALAXY studyObservational studyadjuvant chemotherapy (ACT)disease-free survivalOverall survivalCancer recurrencectDNA positivityctDNA clearancepost-resection monitoringstage II colon cancerstage III colon cancerstage IV colorectal cancerMRD windowprognostic biomarkeractionable biomarker subsetshazard ratioRisk stratificationadjuvant therapy guidanceLiquid biopsyTumor recurrencemortality riskctDNA monitoringMRD detection
#8 of 10,203
13718m citations

Emerging trends and hot topics in the application of multi-omics in drug discovery: A bibliometric and visualized study

Ziheng Wang et al.Current Pharmaceutical Analysis202410.1016/j.cpan.2024.12.001

CorrespondingLin ZhangInstitutionMonash Health, Australia

Multi-omics analysisdrug discoverybibliometric analysiscancer researchPrecision medicinegut microbiotaartificial intelligenceAcquired drug resistancedrug sensitivity predictionGenomic profilingTranscriptomicsproteomicsmetabolomicsepigenomicsCiteSpaceVOSviewerWeb of Science Core Collectionkeyword co-occurrence analysiscitation analysisResearch trendsInternational research collaborationdata integrationdisease treatmentpatient survivalbioinformaticsvisualization analysispublication analysisR software
#9 of 10,203
13418m citations

Origins and impact of extrachromosomal DNA

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

CorrespondingPaul S. Mischel, Mariam Jamal‐Hanjani, Charles SwantonInstitutionThe Francis Crick Institute, United States

Extrachromosomal DNAcancerGene amplificationDriver genesimmunomodulatory genesinflammatory geneslymphocyte-mediated immunityimmune effector processesImmune cell infiltrationtissue-context-based selectionenhancerspromoterslncRNAecDNA interactions in transMutational processesTobacco exposurehomologous recombination deficiencytumour stageTargeted therapycytotoxic treatmentMetastasisOverall survivaltranscriptional landscapeImmunosuppressiontumour growth signals100,000 Genomes ProjectWhole-genome sequencingecDNA formationecDNA detectionTumor heterogeneityGenomic instabilitySomatic mutationsPan-cancer analysisTumor microenvironmentstructural variantscircular DNACancer genomics
#10 of 10,203
12918m citations

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

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

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

Tumor evolutionTumor microenvironmentSpatial transcriptomicsVisium spatial transcriptomicsSingle-nucleus RNA sequencingCODEX (co-detection by indexing)tumour microregionsspatial subclonesIntratumour heterogeneityCopy number variationSomatic mutationsoncogenic activitymetabolic activityantigen presentationImmune cell infiltrationmacrophagestumour boundariesimmune hot neighbourhoodsimmune cold neighbourhoodsimmune exhaustion3D tumour reconstructionserial section co-registrationstromal componentscancer cell clustersSubclonal expansionspatial tumour heterogeneityunsupervised deep-learning algorithmmultimodal data integrationMetastasistumour spatial organizationleading edge biologytumour habitatsClonal evolution
#11 of 10,203
11818m citations

The genomic landscape of 2,023 colorectal cancers

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

CorrespondingIan TomlinsonInstitutionInstitute of Cancer Research, United Kingdom

Colorectal cancerWhole-genome sequencingMutational landscapeDriver genesmicrosatellite-stable CRCmicrosatellite instabilitychromosomal instability100,000 Genomes Projectmolecular subgroupsprognostic associationsEscherichia coli pks+colibactinrectal cancersSBS93 mutational signaturediet as risk factorSmokingimmune-escape driver mutationsHypermutationHLA copy number changesBRCA1IDH1actionable mutationsNon-coding genome mutationsmolecular pathways in CRCGenomic landscapeCopy number variationMutational signaturescolorectum anatomical spectrumrare molecular subgroupspatient care optimizationSomatic mutationstumor genomicsCancer genomicsAPCKRASTP53mismatch repair deficiencyimmune evasionstructural variantsindel signaturescancer aetiologyIntegrative genomic analysis
#12 of 10,203
11718m citations

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

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

CorrespondingMelissa LandrumInstitutionNational Institutes of Health, United States

ClinVarGermline variantsSomatic mutationsVariant annotationoncogenicity classificationclinical impact classificationhuman genetic variantsdisease-variant relationshipspublic databasegenomic databasebatch submissionsubmission APIonline submission formsClinVar XML filesClinVar VCF filestab-delimited filesvariant aggregationClinVar VCV pagesclinical testing laboratoriesCancer genomicsgenomic testingtransparency in genomic testingpatient careNCBIvariant curationsomatic variant interpretationgermline variant interpretation
#13 of 10,203
11618m citations

A pan-cancer analysis of the microbiome in metastatic cancer

Thomas Battaglia, Iris Mimpen et al.Cell202410.1016/j.cell.2024.03.021

CorrespondingEmile E. Voest, Joris van de Haar, Lodewyk F.A. WesselsInstitutionThe Netherlands Cancer Institute, Netherlands

Pan-cancer analysisMicrobiomeMetastasisTumor microbiomeprimary tumorsmetagenomicsmapping-based metagenomicsassembly-based metagenomicsGenomic profilingTranscriptomicsclinical dataTumor biopsyorgan-specific tropismsanaerobic bacteriahypoxic tumorstumor hypoxiamicrobial diversitytumor-infiltrating neutrophilsFusobacteriumImmune checkpoint inhibitionICB resistanceLung cancerLongitudinal tumor profilingtemporal evolutionbacteria depletionhost immune systemanticancer therapy responsepan-cancer resourceTreatment strategiesmicrobial enrichment
#15 of 10,203
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 C. Ambrose, William Cross, Mark J. Caulfield, Nirupa Murugaesu et al.Nature Medicine202410.1038/s41591-023-02682-0

CorrespondingMark J. Caulfield, Nirupa MurugaesuInstitutionUniversity of Westminster, United Kingdom

Precision medicineWhole-genome sequencing100,000 Genomes ProjectCancer ProgrammeSolid tumorsSomatic mutationsCopy number variationstructural variantsGermline variantshomologous recombination deficiencyHigh-grade serous ovarian carcinomaGlioblastomasarcomaactionable mutationsstandard-of-care testingpangenomic markerssurvival analysisCancer genomicsReal-world datalongitudinal clinical datatreatment outcomesRisk stratificationsomatic and germline analysispathogenic germline variantscancer genesPrognosisNHS EnglandGenomics Englandsecure Research Environmentsmall variantsPrecision cancer caregenomic data integrationreal-world evidence33 cancer typeslife course data
#16 of 10,203
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

CorrespondingKui Wu, Bengt Glimelius, Cong Lin, Tobias SjöblomInstitutionUppsala University, China

Colorectal cancerSomatic mutationsWhole-genome sequencingTranscriptomicsDriver genesPopulation-based studylong-term follow-uppathway co-mutationsmutation timing analysisMutational processesMutational signaturesWnt/β-catenin pathwayEGFR pathwayTGFβ pathwayCYB genemitochondrial gene mutationsregulatory elementsCopy number variationCOSMIC SBS44 signaturesurvival analysisgene expression classificationprognostic subtypesmicrosatellite instabilityhypoxiaImmune cell infiltrationstromal cell infiltrationIntegrative genomic analysisPrognosisPersonalized cancer therapyprimary colorectal tumorscancer-causing mutationsGenomic alterationsClinical outcomeexpression subtypesTumor microenvironment
#17 of 10,203
10218m 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

CorrespondingAna CvejicInstitutionWellcome Sanger Institute, Denmark

Non-small cell lung canceradenocarcinomasquamous-cell carcinomaLung cancerSingle-cell RNA sequencingSpatial transcriptomicsTumor microenvironmenttumour ecosystemmyeloid cellsTumor-associated macrophagesM2 macrophage polarizationNK cellsT cellsNK cell cytotoxicityImmune checkpoint inhibitionmacrophage reprogrammingcholesterol exportfoetal-like transcriptional signatureiron effluximmune cell compositionco-expression analysistreatment-naive patientsMulti-omics analysiscell type compositiontranscriptional reprogrammingcancer-related mortalityimmune evasiontumour-promoting inflammation
#18 of 10,203
9418m citations

MYC targeting by OMO-103 in solid tumors: a phase 1 trial

Elena Garralda, Marie-Ève Beaulieu et al.Nature Medicine202410.1038/s41591-024-02805-1

CorrespondingLaura SoucekInstitutionVall d’Hebron Institute of Oncology, Spain

MYC oncogeneMYC inhibitorOMO-103miniproteinSolid tumorsphase 1 clinical trialdose escalation3+3 designdose-limiting toxicitypharmacokineticsrecommended phase 2 doseInfusion reactionsadverse eventsstable diseaseResponse evaluation criteria in solid tumorsTumor regressionTranscriptomicstarget engagementTumor biopsypharmacodynamic markerspredictive response markerssoluble factorsnonlinear pharmacokineticstissue saturationterminal half-lifeintravenous administrationsingle-agent therapyadvanced solid tumorsoncogene targetingUndruggable targetstranscriptional programsCancer progressiontumor maintenanceantitumor activitycomputed tomographysafety and tolerability
#19 of 10,203
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

CorrespondingShervin Tabrizi, J. Christopher Love, Sangeeta N. Bhatia, Viktor A. AdalsteinssonInstitutionMassachusetts Institute of Technology, United States

Liquid biopsycell-free DNACirculating tumor DNAcfDNA clearancepriming agentsearly cancer detectionDisease monitoringsensitivity enhancementnanoparticlesDNA-binding antibodiesintravenous administrationcfDNA recoverytumor-bearing micesmall tumor detectionin vivo augmentationblood drawSequencinganalyte scarcitycfDNA-clearing cells
#20 of 10,203
8818m 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

CorrespondingDanh-Tai Hoang, Eric A. Stone, Eytan RuppinInstitutionAustralian National University, Australia

deep learningDrug response predictionDigital pathologyTranscriptomics imputationGene expressionTreatment responsecancerNeural networksmulti-modal learningBiomarker discoveryTumor microenvironmentimage-based transcriptomicsPredictive modelingGenomic profilingpathology-transcriptomics integration

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 microenvironment biology stands out as the most frequently mentioned canonical topic, appearing in 17 of 50 papers (normalized frequency 0.34), reflecting growing emphasis on immune contexture, stromal interactions, and spatially resolved profiling alongside genomic readouts. Digital pathology (15 mentions), precision medicine (14), circulating tumor DNA (14), and copy number variation (13) form a second tier of dominant themes, signaling convergence between tissue genomics, liquid biopsy, and image-based diagnostics. Larger type further highlights whole-genome sequencing, liquid biopsy, somatic mutations, colorectal cancer, transcriptomics, and immune checkpoint inhibition—topics that cluster around comprehensive profiling pipelines and therapy selection. Smaller but visible terms—including spatial transcriptomics, multi-omics analysis, microsatellite instability, and genomic profiling—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. Whole-genome sequencing exhibited the largest gain (+0.12 normalized frequency; 4 versus 10 papers), followed by precision medicine (+0.10; 6 versus 11), with additional increases for tumor microenvironment, copy number variation, colorectal cancer, and microsatellite instability. The topic evolution card underscores that Class of 2026 bars extend furthest for tumor microenvironment, precision medicine, whole-genome sequencing, and colorectal cancer—topics aligned with population-scale sequencing, multi-cohort genomics, and precision oncology infrastructure. Conversely, several themes prominent in the Class of 2025 cohort receded: tumor evolution (−0.16), non-small cell lung cancer (−0.14), liquid biopsy (−0.14), cancer progression (−0.12), circulating tumor DNA (−0.10), and prognosis (−0.08). Somatic mutations, transcriptomics, and biomarker mentions remained prevalent but showed modest relative declines versus newer risers. Together, these shifts suggest that the most-cited 2024 papers emphasize comprehensive genomic platforms, tumor–immune biology, and disease-specific large-cohort studies, while lung-cancer-focused 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 2026-07-13.

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