2024
The analytical and clinical validity of AI algorithms to score TILs in TNBC: can we use different machine learning models interchangeably?
Vidal J, Tsiknakis N, Staaf J, Bosch A, Ehinger A, Nimeus E, Salgado R, Bai Y, Rimm D, Hartman J, Acs B. The analytical and clinical validity of AI algorithms to score TILs in TNBC: can we use different machine learning models interchangeably? EClinicalMedicine 2024, 78: 102928. DOI: 10.1016/j.eclinm.2024.102928.Peer-Reviewed Original ResearchTriple-negative breast cancerTumor-infiltrating lymphocytesBreast Cancer Research FoundationPrognostic validityMetastatic triple-negative breast cancerDisease-free survival endpointsHazard ratioHost anti-tumor immunityScored tumor infiltrating lymphocytesTumor-infiltrating lymphocyte scoresTriple-negative breast cancer patientsYears median follow-upTumour-infiltrating lymphocyte assessmentAnti-tumor immunityMedian follow-upIndependent prospective cohortTNBC tumorsPrognostic potentialProspective cohortBreast cancerPrognostic performanceAnalytic cohortFollow-upSchool of MedicineSwedish Society for Medical ResearchCorrelation of eTILs with recurrence free survival (RFS) in stage IIB-IIIA melanoma and use as biomarker for stratification for clinical trials.
Aung T, Zhang C, Espinoza G, Leung L, Moon J, Horst B, Ferringer T, Nastiuk K, Rimm D, Saenger Y. Correlation of eTILs with recurrence free survival (RFS) in stage IIB-IIIA melanoma and use as biomarker for stratification for clinical trials. Journal Of Clinical Oncology 2024, 42: 9567-9567. DOI: 10.1200/jco.2024.42.16_suppl.9567.Peer-Reviewed Original ResearchTumor-infiltrating lymphocytesRecurrence free survivalAmerican Joint Committee on CancerFree survivalInfiltrating lymphocytesRetrospective cohortClinical trialsQuantify tumor-infiltrating lymphocytesStage II-III melanomaTumor-infiltrating lymphocytes groupDiagnostic slidesIIb-IIIaRoswell Park Comprehensive Cancer CenterEarly-stage melanoma patientsCox modelStage IIB-IIICAdjuvant clinical trialsKaplan-Meier curvesMultivariate Cox modelUnivariate Cox modelCox proportional hazards modelsClinical pathological featuresGeisinger Medical CenterProportional hazards modelClinical trial designAn algorithm for standardization of tumor Infiltrating lymphocyte evaluation in head and neck cancers
Xirou V, Moutafi M, Bai Y, Nwe Aung T, Burela S, Liu M, Kimple R, Shabbir Ahmed F, Schultz B, Flieder D, Connolly D, Psyrri A, Burtness B, Rimm D. An algorithm for standardization of tumor Infiltrating lymphocyte evaluation in head and neck cancers. Oral Oncology 2024, 152: 106750. PMID: 38547779, PMCID: PMC11060915, DOI: 10.1016/j.oraloncology.2024.106750.Peer-Reviewed Original ResearchConceptsTumor-infiltrating lymphocytesHead and neck cancerTILs evaluationHPV-positiveNeck cancerPrognostic valueHead and neck squamous cell cancer casesTIL variablesAssociated with favorable prognosisHPV-negative headHPV-negative populationHematoxylin-eosin-stained sectionsCox regression analysisPotential clinical implicationsInter-observer variabilityInfiltrating lymphocytesClinicopathological factorsFavorable prognosisValidation cohortTumor cellsCancer casesProspective settingQuPath softwareRetrospective collectionPredictive significance
2023
Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases
Chatziioannou E, Roßner J, Aung T, Rimm D, Niessner H, Keim U, Serna-Higuita L, Bonzheim I, Cuellar L, Westphal D, Steininger J, Meier F, Pop O, Forchhammer S, Flatz L, Eigentler T, Garbe C, Röcken M, Amaral T, Sinnberg T. Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases. EBioMedicine 2023, 93: 104644. PMID: 37295047, PMCID: PMC10363450, DOI: 10.1016/j.ebiom.2023.104644.Peer-Reviewed Original ResearchConceptsTumor-infiltrating lymphocytesMultiple Cox regressionMelanoma-specific survivalCox regressionTumor thicknessCutaneous melanomaPrimary melanomaAssessment of TILsPD-1 checkpoint inhibitionSignificant unfavourable prognostic factorLonger progression-free survivalDistant metastasis-free survivalSimple Cox regressionUnfavourable survival outcomeFirst-line therapyProgression-free survivalUnfavourable prognostic factorCutaneous melanoma patientsMetastasis-free survivalPresence of ulcerationPrimary cutaneous melanomaCox regression modelPrimary melanoma samplesPrimary tissuesOverall survivalDeep computational image analysis of immune cell niches reveals treatment-specific outcome associations in lung cancer
Barrera C, Corredor G, Viswanathan V, Ding R, Toro P, Fu P, Buzzy C, Lu C, Velu P, Zens P, Berezowska S, Belete M, Balli D, Chang H, Baxi V, Syrigos K, Rimm D, Velcheti V, Schalper K, Romero E, Madabhushi A. Deep computational image analysis of immune cell niches reveals treatment-specific outcome associations in lung cancer. Npj Precision Oncology 2023, 7: 52. PMID: 37264091, PMCID: PMC10235089, DOI: 10.1038/s41698-023-00403-x.Peer-Reviewed Original ResearchNon-small cell lung cancerTumor-infiltrating lymphocytesLung cancerEffective adaptive immune responseImmune checkpoint blockersCell lung cancerLung cancer patientsTumor immune microenvironmentAdaptive immune responsesImmune-related biomarkersTreatment-specific outcomesCheckMate 057Histology variantsImmunotherapy resistanceCheckpoint blockersRegulatory cellsTumor rejectionTumor-immune interactionsClinical outcomesImmunosuppressive signalsClinical benefitInfluence prognosisImmune microenvironmentCancer patientsPatient outcomes
2021
The tale of TILs in breast cancer: A report from The International Immuno-Oncology Biomarker Working Group
El Bairi K, Haynes HR, Blackley E, Fineberg S, Shear J, Turner S, de Freitas JR, Sur D, Amendola LC, Gharib M, Kallala A, Arun I, Azmoudeh-Ardalan F, Fujimoto L, Sua LF, Liu SW, Lien HC, Kirtani P, Balancin M, El Attar H, Guleria P, Yang W, Shash E, Chen IC, Bautista V, Do Prado Moura JF, Rapoport BL, Castaneda C, Spengler E, Acosta-Haab G, Frahm I, Sanchez J, Castillo M, Bouchmaa N, Md Zin RR, Shui R, Onyuma T, Yang W, Husain Z, Willard-Gallo K, Coosemans A, Perez EA, Provenzano E, Ericsson PG, Richardet E, Mehrotra R, Sarancone S, Ehinger A, Rimm DL, Bartlett JMS, Viale G, Denkert C, Hida AI, Sotiriou C, Loibl S, Hewitt SM, Badve S, Symmans WF, Kim RS, Pruneri G, Goel S, Francis PA, Inurrigarro G, Yamaguchi R, Garcia-Rivello H, Horlings H, Afqir S, Salgado R, Adams S, Kok M, Dieci MV, Michiels S, Demaria S, Loi S. The tale of TILs in breast cancer: A report from The International Immuno-Oncology Biomarker Working Group. Npj Breast Cancer 2021, 7: 150. PMID: 34853355, PMCID: PMC8636568, DOI: 10.1038/s41523-021-00346-1.Peer-Reviewed Original ResearchTumor-infiltrating lymphocytesImmune checkpoint inhibitorsInternational Immuno-Oncology Biomarker Working GroupBiomarker Working GroupBreast cancerTriple-negative breast cancerSubgroup of womenDeath-1Middle-income countriesPD-L1TIL analysisCytotoxic treatmentCancer settingPrognostic biomarkerClinical utilityClinical validityPatient advocatesWorking GroupClinical utilizationModern oncologyPatientsLymphocytesCancerFuture approachesImmunotherapyMultiplex Quantitative Analysis of Tumor-Infiltrating Lymphocytes, Cancer-Associated Fibroblasts, and CD200 in Pancreatic Cancer
MacNeil T, Vathiotis IA, Shafi S, Aung TN, Zugazagoitia J, Gruver AM, Driscoll K, Rimm DL. Multiplex Quantitative Analysis of Tumor-Infiltrating Lymphocytes, Cancer-Associated Fibroblasts, and CD200 in Pancreatic Cancer. Cancers 2021, 13: 5501. PMID: 34771664, PMCID: PMC8583434, DOI: 10.3390/cancers13215501.Peer-Reviewed Original ResearchTumor-infiltrating lymphocytesPancreatic ductal adenocarcinomaCancer-associated fibroblastsImmune checkpoint blockadePancreatic cancerCheckpoint blockadePDAC patientsTumor microenvironmentQuantitative immunofluorescenceExpression levelsProgression-free survivalLarge retrospective cohortMajority of patientsPotential prognostic valueLow tumor immunogenicityPotential clinical utilityDesmoplastic tumor microenvironmentImmunoinhibitory proteinOverall survivalRetrospective cohortIndependent predictorsImmunotherapy drugsPrognostic significancePrognostic valueTumor expressionNeoadjuvant durvalumab plus weekly nab-paclitaxel and dose-dense doxorubicin/cyclophosphamide in triple-negative breast cancer
Foldi J, Silber A, Reisenbichler E, Singh K, Fischbach N, Persico J, Adelson K, Katoch A, Horowitz N, Lannin D, Chagpar A, Park T, Marczyk M, Frederick C, Burrello T, Ibrahim E, Qing T, Bai Y, Blenman K, Rimm DL, Pusztai L. Neoadjuvant durvalumab plus weekly nab-paclitaxel and dose-dense doxorubicin/cyclophosphamide in triple-negative breast cancer. Npj Breast Cancer 2021, 7: 9. PMID: 33558513, PMCID: PMC7870853, DOI: 10.1038/s41523-021-00219-7.Peer-Reviewed Original ResearchStromal tumor-infiltrating lymphocytesWeekly nab-paclitaxelTriple-negative breast cancerPD-L1Nab-paclitaxelAdverse eventsBreast cancerGrade 3/4 treatment-related adverse eventsPhase I/II trialGrade 3/4 adverse eventsTreatment-related adverse eventsDoxorubicin/cyclophosphamidePhase II studyGuillain-Barre syndromeMononuclear inflammatory cellsPathologic complete responseTumor-infiltrating lymphocytesTumor cell stainingEvaluable patientsNeoadjuvant durvalumabSP263 antibodyII trialNeoadjuvant chemotherapyNeoadjuvant therapyPrimary endpointAutomated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma
Moore MR, Friesner ID, Rizk EM, Fullerton BT, Mondal M, Trager MH, Mendelson K, Chikeka I, Kurc T, Gupta R, Rohr BR, Robinson EJ, Acs B, Chang R, Kluger H, Taback B, Geskin LJ, Horst B, Gardner K, Niedt G, Celebi JT, Gartrell-Corrado RD, Messina J, Ferringer T, Rimm DL, Saltz J, Wang J, Vanguri R, Saenger YM. Automated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma. Scientific Reports 2021, 11: 2809. PMID: 33531581, PMCID: PMC7854647, DOI: 10.1038/s41598-021-82305-1.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiopsyChemotherapy, AdjuvantClinical Decision-MakingDeep LearningFemaleFollow-Up StudiesHumansImage Processing, Computer-AssistedKaplan-Meier EstimateLymphocytes, Tumor-InfiltratingMaleMelanomaMiddle AgedNeoplasm StagingPatient SelectionPrognosisRetrospective StudiesRisk AssessmentROC CurveSkinSkin NeoplasmsYoung AdultConceptsTumor-infiltrating lymphocytesDisease-specific survivalEarly-stage melanomaOpen-source deep learningCutoff valueMultivariable Cox proportional hazards analysisCox proportional hazards analysisDeep learningLow-risk patientsProportional hazards analysisKaplan-Meier analysisAccurate prognostic biomarkersEosin imagesAccuracy of predictionAdjuvant therapyRisk patientsSpecific survivalPrognostic valueValidation cohortReceiver operating curvesTraining cohortTIL analysisClinical trialsPrimary melanomaPrognostic biomarker
2020
Immunological Differences Between Immune-Rich Estrogen Receptor–Positive and Immune-Rich Triple-Negative Breast Cancers
O’Meara T, Marczyk M, Qing T, Yaghoobi V, Blenman K, Cole K, Pelekanou V, Rimm DL, Pusztai L. Immunological Differences Between Immune-Rich Estrogen Receptor–Positive and Immune-Rich Triple-Negative Breast Cancers. JCO Precision Oncology 2020, 4: po.19.00350. PMID: 32923897, PMCID: PMC7446500, DOI: 10.1200/po.19.00350.Peer-Reviewed Original ResearchER-positive breast cancerTriple-negative BCM2-like macrophagesTumor-infiltrating lymphocytesBreast cancerImmune-related genesEstrogen receptor-positive breast cancerImmuno-oncology therapeutic targetsRegulatory T cell markersReceptor-positive breast cancerTriple-negative breast cancerImmune activation markersT-cell markersImmune cell markersM1-like macrophagesDifferent immunotherapy strategiesBreast Cancer International ConsortiumNegative breast cancerImmuno-oncology trialsTGF-β pathwayAntitumor immunityCancer Genome AtlasImmunotherapy strategiesActivation markersImmune microenvironmentPitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer
Kos Z, Roblin E, Kim RS, Michiels S, Gallas BD, Chen W, van de Vijver KK, Goel S, Adams S, Demaria S, Viale G, Nielsen TO, Badve SS, Symmans WF, Sotiriou C, Rimm DL, Hewitt S, Denkert C, Loibl S, Luen SJ, Bartlett JMS, Savas P, Pruneri G, Dillon DA, Cheang MCU, Tutt A, Hall JA, Kok M, Horlings HM, Madabhushi A, van der Laak J, Ciompi F, Laenkholm AV, Bellolio E, Gruosso T, Fox SB, Araya JC, Floris G, Hudeček J, Voorwerk L, Beck AH, Kerner J, Larsimont D, Declercq S, Van den Eynden G, Pusztai L, Ehinger A, Yang W, AbdulJabbar K, Yuan Y, Singh R, Hiley C, Bakir MA, Lazar AJ, Naber S, Wienert S, Castillo M, Curigliano G, Dieci MV, André F, Swanton C, Reis-Filho J, Sparano J, Balslev E, Chen IC, Stovgaard EIS, Pogue-Geile K, Blenman KRM, Penault-Llorca F, Schnitt S, Lakhani SR, Vincent-Salomon A, Rojo F, Braybrooke JP, Hanna MG, Soler-Monsó MT, Bethmann D, Castaneda CA, Willard-Gallo K, Sharma A, Lien HC, Fineberg S, Thagaard J, Comerma L, Gonzalez-Ericsson P, Brogi E, Loi S, Saltz J, Klaushen F, Cooper L, Amgad M, Moore DA, Salgado R. Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer. Npj Breast Cancer 2020, 6: 17. PMID: 32411819, PMCID: PMC7217863, DOI: 10.1038/s41523-020-0156-0.Peer-Reviewed Original ResearchStromal tumor-infiltrating lymphocytesEarly TNBCBreast cancerHER2-positive breast cancerTumor-infiltrating lymphocytesLymphocyte distributionStromal tumorsInflammatory cellsPredictive biomarkersTreatment selectionPrognostic toolClinical practiceOutcome estimatesLymphocytesReproducible assessmentTNBCTumorsCancerScoring guidelinesMultiple areasTumor boundariesRisk estimationImpact of discrepanciesRing studiesAssessmentReport on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group
Amgad M, Stovgaard ES, Balslev E, Thagaard J, Chen W, Dudgeon S, Sharma A, Kerner JK, Denkert C, Yuan Y, AbdulJabbar K, Wienert S, Savas P, Voorwerk L, Beck AH, Madabhushi A, Hartman J, Sebastian MM, Horlings HM, Hudeček J, Ciompi F, Moore DA, Singh R, Roblin E, Balancin ML, Mathieu MC, Lennerz JK, Kirtani P, Chen IC, Braybrooke JP, Pruneri G, Demaria S, Adams S, Schnitt SJ, Lakhani SR, Rojo F, Comerma L, Badve SS, Khojasteh M, Symmans WF, Sotiriou C, Gonzalez-Ericsson P, Pogue-Geile KL, Kim RS, Rimm DL, Viale G, Hewitt SM, Bartlett JMS, Penault-Llorca F, Goel S, Lien HC, Loibl S, Kos Z, Loi S, Hanna MG, Michiels S, Kok M, Nielsen TO, Lazar AJ, Bago-Horvath Z, Kooreman LFS, van der Laak JAWM, Saltz J, Gallas BD, Kurkure U, Barnes M, Salgado R, Cooper LAD. Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group. Npj Breast Cancer 2020, 6: 16. PMID: 32411818, PMCID: PMC7217824, DOI: 10.1038/s41523-020-0154-2.Peer-Reviewed Original ResearchTumor-infiltrating lymphocytesComputer-aided diagnosticsPotential of machineAssessment of algorithmsInternational Immuno-Oncology Biomarker Working GroupHER2-positive breast cancerBiomarker Working GroupComputational workflowPrognostic workflowsVisual guidelinesTIL assessmentInfiltrating lymphocytesBreast cancerPredictive featuresSolid tumorsInter-reader variabilityWorkflowClinical validationComputational assessmentRipe opportunityComputational methodsReporting guidelinesLymphocytesVisual scoringClinical translationApplication of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials
Hudeček J, Voorwerk L, van Seijen M, Nederlof I, de Maaker M, van den Berg J, van de Vijver KK, Sikorska K, Adams S, Demaria S, Viale G, Nielsen TO, Badve SS, Michiels S, Symmans WF, Sotiriou C, Rimm DL, Hewitt SM, Denkert C, Loibl S, Loi S, Bartlett JMS, Pruneri G, Dillon DA, Cheang MCU, Tutt A, Hall JA, Kos Z, Salgado R, Kok M, Horlings HM. Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials. Npj Breast Cancer 2020, 6: 15. PMID: 32436923, PMCID: PMC7217941, DOI: 10.1038/s41523-020-0155-1.Peer-Reviewed Original ResearchStromal tumor-infiltrating lymphocytesTriple-negative breast cancerMetastatic triple-negative breast cancerTumor-infiltrating lymphocytesClinical trialsBiomarker-driven clinical trialsPotential predictive biomarkersPotential risk factorsImmunotherapy trialsImmunotherapy responsePredictive biomarkersRisk factorsBreast cancerStratification factorsSpecific trialsIntegral biomarkerTrialsLymphocytesBiomarkersReliable assessmentReviewCancerThe path to a better biomarker: application of a risk management framework for the implementation of PD‐L1 and TILs as immuno‐oncology biomarkers in breast cancer clinical trials and daily practice
Gonzalez‐Ericsson P, Stovgaard ES, Sua LF, Reisenbichler E, Kos Z, Carter JM, Michiels S, Le Quesne J, Nielsen TO, Lænkholm A, Fox SB, Adam J, Bartlett JM, Rimm DL, Quinn C, Peeters D, Dieci MV, Vincent‐Salomon A, Cree I, Hida AI, Balko JM, Haynes HR, Frahm I, Acosta‐Haab G, Balancin M, Bellolio E, Yang W, Kirtani P, Sugie T, Ehinger A, Castaneda CA, Kok M, McArthur H, Siziopikou K, Badve S, Fineberg S, Gown A, Viale G, Schnitt SJ, Pruneri G, Penault‐Llorca F, Hewitt S, Thompson EA, Allison KH, Symmans WF, Bellizzi AM, Brogi E, Moore DA, Larsimont D, Dillon DA, Lazar A, Lien H, Goetz MP, Broeckx G, Bairi K, Harbeck N, Cimino‐Mathews A, Sotiriou C, Adams S, Liu S, Loibl S, Chen I, Lakhani SR, Juco JW, Denkert C, Blackley EF, Demaria S, Leon‐Ferre R, Gluz O, Zardavas D, Emancipator K, Ely S, Loi S, Salgado R, Sanders M, Group I. The path to a better biomarker: application of a risk management framework for the implementation of PD‐L1 and TILs as immuno‐oncology biomarkers in breast cancer clinical trials and daily practice. The Journal Of Pathology 2020, 250: 667-684. PMID: 32129476, DOI: 10.1002/path.5406.Peer-Reviewed Original ResearchConceptsTriple-negative breast cancerTumor-infiltrating lymphocytesPD-L1Breast cancerPatient selectionInter-reader reproducibilityEarly-stage triple-negative breast cancerPD-1/PD-L1 inhibitorsStage triple-negative breast cancerAdvanced triple-negative breast cancerPD-1/PD-L1High tumor-infiltrating lymphocytesImmune checkpoint inhibitor therapyAddition of atezolizumabPD-L1 assessmentSuboptimal patient selectionCheckpoint inhibitor therapyOptimal patient selectionPD-L1 expressionPD-L1 inhibitorsDaily practiceStandard of careImmuno-therapeutic approachesNegative breast cancerEosin-stained slides
2019
Expression Analysis and Significance of PD-1, LAG-3, and TIM-3 in Human Non–Small Cell Lung Cancer Using Spatially Resolved and Multiparametric Single-Cell Analysis
Datar I, Sanmamed MF, Wang J, Henick BS, Choi J, Badri T, Dong W, Mani N, Toki M, Mejías L, Lozano MD, Perez-Gracia JL, Velcheti V, Hellmann MD, Gainor JF, McEachern K, Jenkins D, Syrigos K, Politi K, Gettinger S, Rimm DL, Herbst RS, Melero I, Chen L, Schalper KA. Expression Analysis and Significance of PD-1, LAG-3, and TIM-3 in Human Non–Small Cell Lung Cancer Using Spatially Resolved and Multiparametric Single-Cell Analysis. Clinical Cancer Research 2019, 25: 4663-4673. PMID: 31053602, PMCID: PMC7444693, DOI: 10.1158/1078-0432.ccr-18-4142.Peer-Reviewed Original ResearchMeSH KeywordsAntigens, CDBiomarkers, TumorCarcinoma, Non-Small-Cell LungGene Expression Regulation, NeoplasticHepatitis A Virus Cellular Receptor 2HumansLung NeoplasmsLymphocyte ActivationLymphocyte Activation Gene 3 ProteinLymphocytes, Tumor-InfiltratingPrognosisProgrammed Cell Death 1 ReceptorRetrospective StudiesSingle-Cell AnalysisSurvival RateConceptsNon-small cell lung cancerHuman non-small cell lung cancerTumor-infiltrating lymphocytesAdvanced non-small cell lung cancerTim-3PD-1Cell lung cancerLAG-3Lung cancerPD-1 axis blockadeShorter progression-free survivalBaseline samplesTim-3 protein expressionMajor clinicopathologic variablesMultiplexed quantitative immunofluorescencePD-1 expressionProgression-free survivalTim-3 expressionLAG-3 expressionT-cell phenotypeTumor mutational burdenImmune inhibitory receptorsImmune evasion pathwaysTIM-3 proteinMass cytometry analysisPhenotyping tumor infiltrating lymphocytes (PhenoTIL) on H&E tissue images: predicting recurrence in lung cancer
Barrera C, Corredor G, Wang X, Schalper K, Rimm D, Velcheti V, Madabhushi A, Castro E. Phenotyping tumor infiltrating lymphocytes (PhenoTIL) on H&E tissue images: predicting recurrence in lung cancer. Progress In Biomedical Optics And Imaging 2019, 10956: 1095607-1095607-8. DOI: 10.1117/12.2513048.Peer-Reviewed Original ResearchTumor-infiltrating lymphocytesTIL densityLung cancerEarly stage non-small cell lung cancer patientsNon-small cell lung cancer patientsCell lung cancer patientsEarly-stage lung cancerKaplan-Meier analysisLung cancer patientsStage lung cancerLikelihood of recurrenceBetter prognosisLate recurrenceCancer patientsDifferent cancer typesDisease outcomeRecurrenceDifferent subtypesCancer typesLymphocytesCancerPatientsPrognosisIndependent validationSpatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non–Small Cell Lung Cancer
Corredor G, Wang X, Zhou Y, Lu C, Fu P, Syrigos K, Rimm DL, Yang M, Romero E, Schalper KA, Velcheti V, Madabhushi A. Spatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non–Small Cell Lung Cancer. Clinical Cancer Research 2019, 25: 1526-1534. PMID: 30201760, PMCID: PMC6397708, DOI: 10.1158/1078-0432.ccr-18-2013.Peer-Reviewed Original Research
2018
Prognostic implications of residual disease (RD) tumor-infiltrating lymphocytes (TIL) in triple negative breast cancer (TNBC) after neo-adjuvant chemotherapy (NAC).
Luen S, Salgado R, Dieci M, Vingiani A, Curigliano G, Hubbard R, Castaneda Altamirano C, Sanchez J, D'Alfonso T, Cheng E, Castillo Garcia M, Adams S, Ahmed F, Rimm D, Demaria S, Symmans W, Michiels S, Loi S. Prognostic implications of residual disease (RD) tumor-infiltrating lymphocytes (TIL) in triple negative breast cancer (TNBC) after neo-adjuvant chemotherapy (NAC). Journal Of Clinical Oncology 2018, 36: 571-571. DOI: 10.1200/jco.2018.36.15_suppl.571.Peer-Reviewed Original Research
2017
Assessing Tumor-Infiltrating Lymphocytes in Solid Tumors
Hendry S, Salgado R, Gevaert T, Russell PA, John T, Thapa B, Christie M, van de Vijver K, Estrada MV, Gonzalez-Ericsson PI, Sanders M, Solomon B, Solinas C, Van den Eynden GGGM, Allory Y, Preusser M, Hainfellner J, Pruneri G, Vingiani A, Demaria S, Symmans F, Nuciforo P, Comerma L, Thompson EA, Lakhani S, Kim SR, Schnitt S, Colpaert C, Sotiriou C, Scherer SJ, Ignatiadis M, Badve S, Pierce RH, Viale G, Sirtaine N, Penault-Llorca F, Sugie T, Fineberg S, Paik S, Srinivasan A, Richardson A, Wang Y, Chmielik E, Brock J, Johnson DB, Balko J, Wienert S, Bossuyt V, Michiels S, Ternes N, Burchardi N, Luen SJ, Savas P, Klauschen F, Watson PH, Nelson BH, Criscitiello C, O’Toole S, Larsimont D, de Wind R, Curigliano G, André F, Lacroix-Triki M, van de Vijver M, Rojo F, Floris G, Bedri S, Sparano J, Rimm D, Nielsen T, Kos Z, Hewitt S, Singh B, Farshid G, Loibl S, Allison KH, Tung N, Adams S, Willard-Gallo K, Horlings HM, Gandhi L, Moreira A, Hirsch F, Dieci MV, Urbanowicz M, Brcic I, Korski K, Gaire F, Koeppen H, Lo A, Giltnane J, Rebelatto MC, Steele KE, Zha J, Emancipator K, Juco JW, Denkert C, Reis-Filho J, Loi S, Fox SB. Assessing Tumor-Infiltrating Lymphocytes in Solid Tumors. Advances In Anatomic Pathology 2017, 24: 311-335. PMID: 28777143, PMCID: PMC5638696, DOI: 10.1097/pap.0000000000000161.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorBiopsyBrain NeoplasmsCarcinoma, Non-Small-Cell LungCarcinoma, Squamous CellEndometrial NeoplasmsFemaleGastrointestinal NeoplasmsHead and Neck NeoplasmsHumansImmunohistochemistryLung NeoplasmsLymphocytes, Tumor-InfiltratingMelanomaMesotheliomaOvarian NeoplasmsPathologyPhenotypePredictive Value of TestsSkin NeoplasmsSquamous Cell Carcinoma of Head and NeckUrogenital NeoplasmsConceptsTumor-infiltrating lymphocytesDifferent tumor typesSolid tumorsTumor typesTIL assessmentImmune responsePrimary brain tumorsCommon solid tumorsInvasive breast carcinomaRoutine clinical biomarkersWorking Group guidelinesPrognostic implicationsBreast carcinomaGroup guidelinesGynecologic systemGastrointestinal tractSimple biomarkerBrain tumorsGenitourinary systemPredictive valueClinical biomarkersStandardized methodologyTumorsAvailable evidenceImmunotherapyObjective measurement and clinical significance of IDO1 protein in hormone receptor-positive breast cancer
Carvajal-Hausdorf DE, Mani N, Velcheti V, Schalper KA, Rimm DL. Objective measurement and clinical significance of IDO1 protein in hormone receptor-positive breast cancer. Journal For ImmunoTherapy Of Cancer 2017, 5: 81. PMID: 29037255, PMCID: PMC5644103, DOI: 10.1186/s40425-017-0285-7.Peer-Reviewed Original ResearchConceptsHormone receptor-positive breast cancerReceptor-positive breast cancerIDO1 expressionBreast cancerIndependent negative prognostic markerB cell infiltrationImmune suppressive pathwaysAdvanced solid tumorsTumor-infiltrating lymphocytesT cell responsesClinico-pathological featuresClinico-pathological characteristicsProportional hazards modelNegative prognostic markerDegradation of tryptophanMann-Whitney testFoxp3 levelsIDO1 blockadeIDO1 levelsEffector CD4Durable responsesOverall survivalImmune toleranceMultivariable analysisPrognostic marker