Featured Publications
A clonal expression biomarker associates with lung cancer mortality
Biswas D, Birkbak N, Rosenthal R, Hiley C, Lim E, Papp K, Boeing S, Krzystanek M, Djureinovic D, La Fleur L, Greco M, Döme B, Fillinger J, Brunnström H, Wu Y, Moore D, Skrzypski M, Abbosh C, Litchfield K, Al Bakir M, Watkins T, Veeriah S, Wilson G, Jamal-Hanjani M, Moldvay J, Botling J, Chinnaiyan A, Micke P, Hackshaw A, Bartek J, Csabai I, Szallasi Z, Herrero J, McGranahan N, Swanton C. A clonal expression biomarker associates with lung cancer mortality. Nature Medicine 2019, 25: 1540-1548. PMID: 31591602, PMCID: PMC6984959, DOI: 10.1038/s41591-019-0595-z.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerClinicopathological risk factorsCell lung cancerLung cancer mortalityPrognostic gene expression signaturesCancer cell proliferationGene expression signaturesCancer mortalityLung cancerRisk factorsExpression-based biomarkersCopy number gainsDisease subtypesClinical descriptorsTranscriptomic biomarkersIndividual tumorsCancer typesDiagnostic precisionMolecular biomarkersExpression signaturesCell proliferationDNA copy number gainsBiomarkersPatientsIntratumor heterogeneityA local human Vδ1 T cell population is associated with survival in nonsmall-cell lung cancer
Wu Y, Biswas D, Usaite I, Angelova M, Boeing S, Karasaki T, Veeriah S, Czyzewska-Khan J, Morton C, Joseph M, Hessey S, Reading J, Georgiou A, Al-Bakir M, McGranahan N, Jamal-Hanjani M, Hackshaw A, Quezada S, Hayday A, Swanton C. A local human Vδ1 T cell population is associated with survival in nonsmall-cell lung cancer. Nature Cancer 2022, 3: 696-709. PMID: 35637401, PMCID: PMC9236901, DOI: 10.1038/s43018-022-00376-z.Peer-Reviewed Original ResearchConceptsT cell populationsT cellsLung tissueLung cancerCD8+ T cellsNonsmall-cell lung cancerNonsmall cell lung cancerEffector memory phenotypeT cell compartmentCell lung cancerAssociated with survivalNonmalignant lung tissuesStem-like featuresNontumor lung tissuesT cell biologyHuman lung tissueImmunotherapeutic strategiesMemory phenotypeNatural killerLung tumorsTissue-residentPost-surgeryResident memoryMurine tissuesTumorRace- and Ethnicity-Related Differences in Heart Failure With Preserved Ejection Fraction Using Natural Language Processing
Brown S, Biswas D, Wu J, Ryan M, Bernstein B, Fairhurst N, Kaye G, Baral R, Cannata A, Searle T, Melikian N, Sado D, Lüscher T, Teo J, Dobson R, Bromage D, McDonagh T, Vazir A, Shah A, O’Gallagher K. Race- and Ethnicity-Related Differences in Heart Failure With Preserved Ejection Fraction Using Natural Language Processing. JACC Advances 2024, 3: 101064. PMID: 39050815, PMCID: PMC11268103, DOI: 10.1016/j.jacadv.2024.101064.Peer-Reviewed Original ResearchBlack patientsPro-B-type natriuretic peptide levelsN-terminal pro-B-type natriuretic peptide levelsEuropean Society of Cardiology criteriaDiagnosis of HFpEFNatriuretic peptide levelsHeterogeneous clinical syndromeEuropean SocietyCardiology criteriaHFpEF diagnosisClinical presentationFPEF scoreAsian patientsPatient demographicsEthnicity-related differencesMetabolic comorbiditiesAtrial fibrillationHeart failureHFpEFDiagnostic performancePeptide levelsWhite patientsClinical syndromePatientsQuantify health inequalitiesThe future of liquid biopsy
Biswas D, Ganeshalingam J, Wan J. The future of liquid biopsy. The Lancet Oncology 2020, 21: e550. PMID: 33271107, DOI: 10.1016/s1470-2045(20)30687-2.Peer-Reviewed Original Research
2024
Cancer cell – Fibroblast crosstalk via HB-EGF, EGFR, and MAPK signaling promotes the expression of macrophage chemo-attractants in squamous cell carcinoma
Giangreco G, Rullan A, Naito Y, Biswas D, Liu Y, Hooper S, Nenclares P, Bhide S, Chon U Cheang M, Chakravarty P, Hirata E, Swanton C, Melcher A, Harrington K, Sahai E. Cancer cell – Fibroblast crosstalk via HB-EGF, EGFR, and MAPK signaling promotes the expression of macrophage chemo-attractants in squamous cell carcinoma. IScience 2024, 27: 110635. PMID: 39262776, PMCID: PMC11387794, DOI: 10.1016/j.isci.2024.110635.Peer-Reviewed Original ResearchTumor microenvironmentSquamous cell carcinoma cohortCancer cellsMacrophage chemo-attractantsSquamous cell carcinomaTumor-stroma crosstalkRecruitment of macrophagesExpression of CSF2Prognostic significanceCarcinoma cohortCell carcinomaPatient prognosisHB-EGFStromal fibroblastsCancer outcomesCancer progressionCancerMAPK signalingIndicator of signalingChemo-attractantsCellsFibroblastsCarcinomaExpressionEGFR134 Race and ethnicity-related differences in the diagnosis of heart failure with preserved ejection fraction using natural language processing
Brown S, Biswas D, Wu H, Ryan M, Bernstein B, Fairhurst N, Kaye G, Baral R, Cannata A, Searle T, Melikian N, Sado D, Lüscher T, Teo J, Dobson R, Bromage D, McDonagh T, Vazir A, Shah A, O’Gallagher K. 134 Race and ethnicity-related differences in the diagnosis of heart failure with preserved ejection fraction using natural language processing. 2024, a140-a141. DOI: 10.1136/heartjnl-2024-bcs.132.Peer-Reviewed Original ResearchArtificial intelligence methods for improved detection of undiagnosed heart failure with preserved ejection fraction
Wu J, Biswas D, Ryan M, Bernstein B, Rizvi M, Fairhurst N, Kaye G, Baral R, Searle T, Melikian N, Sado D, Lüscher T, Grocott‐Mason R, Carr‐White G, Teo J, Dobson R, Bromage D, McDonagh T, Shah A, O'Gallagher K. Artificial intelligence methods for improved detection of undiagnosed heart failure with preserved ejection fraction. European Journal Of Heart Failure 2024, 26: 302-310. PMID: 38152863, DOI: 10.1002/ejhf.3115.Peer-Reviewed Original ResearchConceptsLeft ventricular ejection fractionDiagnosis of HFpEFEuropean Society of CardiologyHeart failureNatural language processingElectronic health recordsEuropean Society of Cardiology criteriaClinical diagnosis of HFEuropean Society of Cardiology diagnostic criteriaDiagnostic criteriaVentricular ejection fractionRetrospective cohort studyDiagnosis of HFSociety of CardiologyClinician-assigned diagnosisConsecutive patientsHFpEF patientsEjection fractionElectronic health record dataAcute cardiovascular eventsExpert clinical reviewNatural language processing methodsNatural language processing pipelineHFpEFCardiovascular eventsPD-1 defines a distinct, functional, tissue-adapted state in Vδ1+ T cells with implications for cancer immunotherapy
Davies D, Kamdar S, Woolf R, Zlatareva I, Iannitto M, Morton C, Haque Y, Martin H, Biswas D, Ndagire S, Munonyara M, Gillett C, O’Neill O, Nussbaumer O, Hayday A, Wu Y. PD-1 defines a distinct, functional, tissue-adapted state in Vδ1+ T cells with implications for cancer immunotherapy. Nature Cancer 2024, 5: 420-432. PMID: 38172341, PMCID: PMC10965442, DOI: 10.1038/s43018-023-00690-0.Peer-Reviewed Original ResearchConceptsCheckpoint inhibitionPD-1T cellsProgrammed cell death protein 1Cell death protein 1PD-1 expressionResponse to TCR signalingPD-1 engagementT cell recognitionCancer immunotherapyTCR signalingTranscriptomic programsProtein 1CancerFunctional relevanceCellsImmunotherapyNeoantigensMelanomaPatientsOncology
2023
Using natural language processing to generate a large-scale database of aortic stenosis with long-term follow-up: the CASPER (cogstack aortic stenosis patient electronic registry) database
Wu J, Biswas D, Seale T, Bean D, Fairhurst N, Kaye G, Dobson R, Chowienczyk P, Shah A, O'gallagher K. Using natural language processing to generate a large-scale database of aortic stenosis with long-term follow-up: the CASPER (cogstack aortic stenosis patient electronic registry) database. European Heart Journal 2023, 44: ehad655.2952. DOI: 10.1093/eurheartj/ehad655.2952.Peer-Reviewed Original ResearchNatural language processingElectronic heath recordsLanguage processingData pipelineNatural language processing toolkitRetrieval systemProcessing toolkitSNOMED termsClinical notesAutomated detectionRandomised controlled trialsManual validationLong-term mortality dataCohort of AS patientsMortality dataData sourcesSocial deprivationPatient trajectoriesInfluence of ethnicityControlled trialsPatient demographic dataRandomised trialsExtract dataDatabaseDemographic dataAbstract 18205: Ethnicity and Aortic Stenosis: Presentation, Management and Outcomes
Biswas D, Wu J, Bharucha A, Fairhurst N, Kaye G, Baghai M, Dworakowski R, Byrne J, MacCarthy P, Shah A, Eskandari M, O'Gallagher K. Abstract 18205: Ethnicity and Aortic Stenosis: Presentation, Management and Outcomes. Circulation 2023, 148: a18205-a18205. DOI: 10.1161/circ.148.suppl_1.18205.Peer-Reviewed Original ResearchAortic valve replacementTranscatheter aortic valve implantationAsian patientsWhite patientsBlack patientsSevere ASAortic stenosisBenefit of transcatheter aortic valve implantationSurgical aortic valve replacementManagement of aortic stenosisCox multivariate analysisSocial deprivationManagement of ASAortic valve implantationTAVI interventionKing's College HospitalEthnicity-based differencesValve replacementCardiac symptomsCollege HospitalElectronic health recordsMortality benefitValve implantationMultivariate analysisAS diagnosisQuantifying the impact of immunotherapy on RNA dynamics in cancer
Usaite I, Biswas D, Dijkstra K, Watkins T, Pich O, Puttick C, Angelova M, Thakkar K, Hiley C, Birkbak N, Kok M, Zaccaria S, Wu Y, Litchfield K, Swanton C, Kanu N. Quantifying the impact of immunotherapy on RNA dynamics in cancer. Journal For ImmunoTherapy Of Cancer 2023, 11: e007870. PMID: 37914385, PMCID: PMC10626770, DOI: 10.1136/jitc-2023-007870.Peer-Reviewed Original ResearchConceptsCheckpoint inhibitorsCheckpoint inhibitor treatmentBreast cancerOn-therapyImmune microenvironmentPre-therapyCancer typesPatients treated with checkpoint inhibitorsCheckpoint inhibitor therapyImpact of immunotherapyCancer immune microenvironmentSolid tumor typesMechanism of sensitizationClinical responseCombination therapyTumor typesIO targetsResponse ratePatientsBreastCancerImmunotherapyMelanomaMeta-analysesTherapyTCT-766 Ethnicity and Aortic Stenosis: Presentation, Management, and Outcomes
Biswas D, Wu J, Bharucha A, Fairhurst N, Kaye G, Baghai M, Pareek N, Webb I, Melikian N, Dworakowski R, Byrne J, MacCarthy P, Shah A, Eskandari M, O'Gallagher K. TCT-766 Ethnicity and Aortic Stenosis: Presentation, Management, and Outcomes. Journal Of The American College Of Cardiology 2023, 82: b308. DOI: 10.1016/j.jacc.2023.09.778.Peer-Reviewed Original ResearchAbstract LB237: Functional characterisation of TRACERx reveals mechanisms of NSCLC evolution
Lu W, Zalmas L, Bailey C, Pich O, Ruiz C, Black J, Stavrou G, Biswas D, Gimeno-Valiente F, Litchfield K, Bartek J, McGranahan N, Kanu N, Swanton C. Abstract LB237: Functional characterisation of TRACERx reveals mechanisms of NSCLC evolution. Cancer Research 2023, 83: lb237-lb237. DOI: 10.1158/1538-7445.am2023-lb237.Peer-Reviewed Original ResearchNon-small cell lung cancerElevated chromosomal instabilityWhole-genome doublingChromosomal instabilityIntratumoral heterogeneityHomologous recombination repairDNA damage responseAmerican Association for Cancer Research annual meetingsPC9 cellsRates of acquired resistanceIncreased intratumoral heterogeneityCell lung cancerIncreased CINDrug-resistant tumorsGenome doublingFunctional characterisationStructural chromosome instabilityWhole-genome doubling eventsFAT1 mutationsHomologous recombination repair pathwayBRCA1 foci formationChromosomal gainsMitotic error rateTargeted therapySolid tumorsTracking early lung cancer metastatic dissemination in TRACERx using ctDNA
Abbosh C, Frankell A, Harrison T, Kisistok J, Garnett A, Johnson L, Veeriah S, Moreau M, Chesh A, Chaunzwa T, Weiss J, Schroeder M, Ward S, Grigoriadis K, Shahpurwalla A, Litchfield K, Puttick C, Biswas D, Karasaki T, Black J, Martínez-Ruiz C, Bakir M, Pich O, Watkins T, Lim E, Huebner A, Moore D, Godin-Heymann N, L’Hernault A, Bye H, Odell A, Roberts P, Gomes F, Patel A, Manzano E, Hiley C, Carey N, Riley J, Cook D, Hodgson D, Stetson D, Barrett J, Kortlever R, Evan G, Hackshaw A, Daber R, Shaw J, Aerts H, Licon A, Stahl J, Jamal-Hanjani M, Birkbak N, McGranahan N, Swanton C. Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA. Nature 2023, 616: 553-562. PMID: 37055640, PMCID: PMC7614605, DOI: 10.1038/s41586-023-05776-4.Peer-Reviewed Original ResearchConceptsCirculating tumor DNANon-small-cell lung cancerMetastatic disseminationClinical outcomesPlasma samplesEarly-stage non-small-cell lung cancerCirculating tumor DNA levelsCirculating tumor DNA detectionCytotoxic adjuvant therapyPreoperative ctDNA detectionResidual tumor cellsLongitudinal plasma samplesCancer cell fractionBiomarker of relapseProcess of metastatic disseminationAnalysis of plasma samplesClinical relapseDisease relapseAdjuvant therapyTumor DNAPreoperative plasmaRadiological surveillanceCtDNA detectionPatient cohortTumor cellsEvolutionary characterization of lung adenocarcinoma morphology in TRACERx
Karasaki T, Moore D, Veeriah S, Naceur-Lombardelli C, Toncheva A, Magno N, Ward S, Bakir M, Watkins T, Grigoriadis K, Huebner A, Hill M, Frankell A, Abbosh C, Puttick C, Zhai H, Gimeno-Valiente F, Saghafinia S, Kanu N, Dietzen M, Pich O, Lim E, Martínez-Ruiz C, Black J, Biswas D, Campbell B, Lee C, Colliver E, Enfield K, Hessey S, Hiley C, Zaccaria S, Litchfield K, Birkbak N, Cadieux E, Demeulemeester J, Van Loo P, Adusumilli P, Tan K, Cheema W, Sanchez-Vega F, Jones D, Rekhtman N, Travis W, Hackshaw A, Marafioti T, Salgado R, Le Quesne J, Nicholson A, McGranahan N, Swanton C, Jamal-Hanjani M. Evolutionary characterization of lung adenocarcinoma morphology in TRACERx. Nature Medicine 2023, 29: 833-845. PMID: 37045996, PMCID: PMC7614478, DOI: 10.1038/s41591-023-02230-w.Peer-Reviewed Original ResearchConceptsPrimary tumor regionLung adenocarcinomaPresence of micropapillary patternLoss of chromosome 3pSolid pattern tumorsHigh-grade patternsClonal evolution analysisSomatic copy number alterationsTumor regionLoss of heterozygosityWhole-exome sequencing dataCopy number alterationsAdenocarcinoma morphologyIntrathoracic recurrenceLepidic tumorsRNA sequencing dataMicropapillary patternRelapse riskGene alterationsMetastatic samplesHistological spectrumMicropapillary tumorsChromosome 3pHigh-gradeHistopathological analysisThe evolution of lung cancer and impact of subclonal selection in TRACERx
Frankell A, Dietzen M, Al Bakir M, Lim E, Karasaki T, Ward S, Veeriah S, Colliver E, Huebner A, Bunkum A, Hill M, Grigoriadis K, Moore D, Black J, Liu W, Thol K, Pich O, Watkins T, Naceur-Lombardelli C, Cook D, Salgado R, Wilson G, Bailey C, Angelova M, Bentham R, Martínez-Ruiz C, Abbosh C, Nicholson A, Le Quesne J, Biswas D, Rosenthal R, Puttick C, Hessey S, Lee C, Prymas P, Toncheva A, Smith J, Xing W, Nicod J, Price G, Kerr K, Naidu B, Middleton G, Blyth K, Fennell D, Forster M, Lee S, Falzon M, Hewish M, Shackcloth M, Lim E, Benafif S, Russell P, Boleti E, Krebs M, Lester J, Papadatos-Pastos D, Ahmad T, Thakrar R, Lawrence D, Navani N, Janes S, Dive C, Blackhall F, Summers Y, Cave J, Marafioti T, Herrero J, Quezada S, Peggs K, Schwarz R, Van Loo P, Miedema D, Birkbak N, Hiley C, Hackshaw A, Zaccaria S, Jamal-Hanjani M, McGranahan N, Swanton C. The evolution of lung cancer and impact of subclonal selection in TRACERx. Nature 2023, 616: 525-533. PMID: 37046096, PMCID: PMC10115649, DOI: 10.1038/s41586-023-05783-5.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerDisease-free survivalCell lung cancerWhole-genome doublingLung cancerLung adenocarcinomaAssociated with shorter disease-free survivalShorter disease-free survivalEvolution of lung cancerPattern of relapseSubclonal selectionPrimary study endpointHistory of smokingSubclonal expansionsCopy number instabilityEGFR mutationsCancer-associated mortalityCopy number heterogeneityClinical outcomesStudy endpointIntratumour heterogeneityNever-smokersClonal expansionFollow-upOncogenic isoform
2022
RAS oncogenic activity predicts response to chemotherapy and outcome in lung adenocarcinoma
East P, Kelly G, Biswas D, Marani M, Hancock D, Creasy T, Sachsenmeier K, Swanton C, Downward J, de Carné Trécesson S. RAS oncogenic activity predicts response to chemotherapy and outcome in lung adenocarcinoma. Nature Communications 2022, 13: 5632. PMID: 36163168, PMCID: PMC9512813, DOI: 10.1038/s41467-022-33290-0.Peer-Reviewed Original ResearchConceptsResponse to chemotherapyLung adenocarcinomaRas oncogene activationOncogenic activityKRAS wild-type tumorsReduced response to chemotherapyWild-type tumorsKRAS mutant tumorsResistance to therapyCohort of patientsAdverse clinical outcomesResponse to treatmentRAS pathway activationActive patient groupAggressive diseaseMutant tumorsKRAS mutationsClinical outcomesPreclinical studiesActivating mutationsClinical decision-makingGenetic alterationsPatient stratificationPatient groupKRASAbstract 5636: V-delta-1 T cells are resident in the human lung and associate with survival in patients with non-small cell lung cancer in the TRACERx Study
Wu Y, Biswas D, Usaite I, Mihaela A, Boeing S, Karasaki T, Veeriah S, Czyzewska-Khan J, Reading J, Georgiou A, Al-Bakir M, McGranahan N, Jamal-Hanjani M, Hackshaw A, Consortium T, Quezada S, Hayday A, Swanton C. Abstract 5636: V-delta-1 T cells are resident in the human lung and associate with survival in patients with non-small cell lung cancer in the TRACERx Study. Cancer Research 2022, 82: 5636-5636. DOI: 10.1158/1538-7445.am2022-5636.Peer-Reviewed Original ResearchNon-small cell lung cancerCell lung cancerT cell compartmentV delta 1T cellsAssociated with survivalLung cancerTRACERx studyLung tissueAmerican Association for Cancer Research annual meetingsStage I-III non-small cell lung cancerT cell knockout miceCD8+ T cellsMurine tissuesFirst-in-human clinical trialIL-17-producingNon-malignant lung tissueT-cell immunotherapyT-cell receptor sequencingT cell clonesIL-17 productionT helper 1Acute myeloid leukemiaSusceptibility to carcinogenesisHuman lungAbstract 645: Heterogeneity of immunotherapy biomarkers in the TRACERx non-small cell lung cancer multi-region lung cancer cohort study
Hiley C, Litchfield K, Pich O, Moore D, Naceur-Lombardelli C, Veeriah S, Bakir M, Summan S, Grigoriadis K, Ruiz C, Puttick C, Enfield K, Ward S, Frankell A, Biswas D, Rosenthal R, Birkbak N, Jamal-Hanjani M, McGranahan N, Swanton C, Consortium T. Abstract 645: Heterogeneity of immunotherapy biomarkers in the TRACERx non-small cell lung cancer multi-region lung cancer cohort study. Cancer Research 2022, 82: 645-645. DOI: 10.1158/1538-7445.am2022-645.Peer-Reviewed Original ResearchNon-small cell lung cancerTumor mutational burdenIntra-tumor heterogeneityIntratumoral heterogeneityCancer Cohort StudyImmunotherapy biomarkersTumor regionAmerican Association for Cancer Research annual meetingsPredictors of response to immunotherapyCohort studyPrediction of immunotherapy responseTumor purityNeo-adjuvant settingResponse to immunotherapyFirst-line therapyImpact of intratumoral heterogeneityCell lung cancerMisclassification of patientsWhole-exome sequencingHeterogeneity of expressionMetastatic settingPDL1 immunohistochemistryPrimary tumorImmunotherapy responseMutational burdenAbstract LB064: B cells synergize with T cell regulation at immune hotspots in lung squamous cell carcinoma
Zhang H, AbdulJabbar K, Moore D, Akarca A, Enfield K, Jamal-Hanjani M, Raza S, Veeriah S, Biswas D, Salgado R, McGranahan N, Quesne J, Swanton C, Marafioti T, Yuan Y. Abstract LB064: B cells synergize with T cell regulation at immune hotspots in lung squamous cell carcinoma. Cancer Research 2022, 82: lb064-lb064. DOI: 10.1158/1538-7445.am2022-lb064.Peer-Reviewed Original ResearchTertiary lymphoid structuresSquamous cell carcinomaLung squamous cell carcinomaCD8+ T cellsCell carcinomaT cell regulationB cellsT cellsTumor nestsAmerican Association for Cancer Research annual meetingsLymphoid aggregatesTumor-infiltrating CD8+ T cellsPresence of tertiary lymphoid structuresCD4+Foxp3+ T cellsAssociated with poor overall survivalSubpopulation of T cellsHeterogeneous immune infiltrationT regulatory cellsRobust prognostic markersImmune cell aggregatesT cell subtypesT cytotoxic cellsTherapeutic targetImmune cell subpopulationsPoor overall survival