2024
Training pathologists to assess stromal tumour‐infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research
Ly A, Garcia V, Blenman K, Ehinger A, Elfer K, Hanna M, Li X, Peeters D, Birmingham R, Dudgeon S, Gardecki E, Gupta R, Lennerz J, Pan T, Saltz J, Wharton K, Ehinger D, Acs B, Dequeker E, Salgado R, Gallas B. Training pathologists to assess stromal tumour‐infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research. Histopathology 2024, 84: 915-923. PMID: 38433289, PMCID: PMC10990791, DOI: 10.1111/his.15140.Peer-Reviewed Original ResearchStromal tumor-infiltrating lymphocytesTumor-infiltrating lymphocytesUS Food and Drug AdministrationFood and Drug AdministrationBreast cancerPathologist's visual assessmentDrug AdministrationSignificant interobserver variabilityPredicative biomarkerTILs assessmentTrained pathologistsInterobserver agreementInterobserver variabilityVisual assessmentGold standardReference standardBreastCME coursesClinical practiceClinical careCancerMedical educationPathologistsLymphocytesExpert commentary
2023
Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer
Page D, Broeckx G, Jahangir C, Verbandt S, Gupta R, Thagaard J, Khiroya R, Kos Z, Abduljabbar K, Haab G, Acs B, Akturk G, Almeida J, Alvarado‐Cabrero I, Azmoudeh‐Ardalan F, Badve S, Baharun N, Bellolio E, Bheemaraju V, Blenman K, Fujimoto L, Bouchmaa N, Burgues O, Cheang M, Ciompi F, Cooper L, Coosemans A, Corredor G, Portela F, Deman F, Demaria S, Dudgeon S, Elghazawy M, Ely S, Fernandez‐Martín C, Fineberg S, Fox S, Gallagher W, Giltnane J, Gnjatic S, Gonzalez‐Ericsson P, Grigoriadis A, Halama N, Hanna M, Harbhajanka A, Hardas A, Hart S, Hartman J, Hewitt S, Hida A, Horlings H, Husain Z, Hytopoulos E, Irshad S, Janssen E, Kahila M, Kataoka T, Kawaguchi K, Kharidehal D, Khramtsov A, Kiraz U, Kirtani P, Kodach L, Korski K, Kovács A, Laenkholm A, Lang‐Schwarz C, Larsimont D, Lennerz J, Lerousseau M, Li X, Ly A, Madabhushi A, Maley S, Narasimhamurthy V, Marks D, McDonald E, Mehrotra R, Michiels S, Minhas F, Mittal S, Moore D, Mushtaq S, Nighat H, Papathomas T, Penault‐Llorca F, Perera R, Pinard C, Pinto‐Cardenas J, Pruneri G, Pusztai L, Rahman A, Rajpoot N, Rapoport B, Rau T, Reis‐Filho J, Ribeiro J, Rimm D, Vincent‐Salomon A, Salto‐Tellez M, Saltz J, Sayed S, Siziopikou K, Sotiriou C, Stenzinger A, Sughayer M, Sur D, Symmans F, Tanaka S, Taxter T, Tejpar S, Teuwen J, Thompson E, Tramm T, Tran W, van der Laak J, van Diest P, Verghese G, Viale G, Vieth M, Wahab N, Walter T, Waumans Y, Wen H, Yang W, Yuan Y, Adams S, Bartlett J, Loibl S, Denkert C, Savas P, Loi S, Salgado R, Stovgaard E. Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer. The Journal Of Pathology 2023, 260: 514-532. PMID: 37608771, PMCID: PMC11288334, DOI: 10.1002/path.6165.Peer-Reviewed Original ResearchPitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer
Thagaard J, Broeckx G, Page D, Jahangir C, Verbandt S, Kos Z, Gupta R, Khiroya R, Abduljabbar K, Haab G, Acs B, Akturk G, Almeida J, Alvarado‐Cabrero I, Amgad M, Azmoudeh‐Ardalan F, Badve S, Baharun N, Balslev E, Bellolio E, Bheemaraju V, Blenman K, Fujimoto L, Bouchmaa N, Burgues O, Chardas A, Cheang M, Ciompi F, Cooper L, Coosemans A, Corredor G, Dahl A, Portela F, Deman F, Demaria S, Hansen J, Dudgeon S, Ebstrup T, Elghazawy M, Fernandez‐Martín C, Fox S, Gallagher W, Giltnane J, Gnjatic S, Gonzalez‐Ericsson P, Grigoriadis A, Halama N, Hanna M, Harbhajanka A, Hart S, Hartman J, Hauberg S, Hewitt S, Hida A, Horlings H, Husain Z, Hytopoulos E, Irshad S, Janssen E, Kahila M, Kataoka T, Kawaguchi K, Kharidehal D, Khramtsov A, Kiraz U, Kirtani P, Kodach L, Korski K, Kovács A, Laenkholm A, Lang‐Schwarz C, Larsimont D, Lennerz J, Lerousseau M, Li X, Ly A, Madabhushi A, Maley S, Narasimhamurthy V, Marks D, McDonald E, Mehrotra R, Michiels S, Minhas F, Mittal S, Moore D, Mushtaq S, Nighat H, Papathomas T, Penault‐Llorca F, Perera R, Pinard C, Pinto‐Cardenas J, Pruneri G, Pusztai L, Rahman A, Rajpoot N, Rapoport B, Rau T, Reis‐Filho J, Ribeiro J, Rimm D, Roslind A, Vincent‐Salomon A, Salto‐Tellez M, Saltz J, Sayed S, Scott E, Siziopikou K, Sotiriou C, Stenzinger A, Sughayer M, Sur D, Fineberg S, Symmans F, Tanaka S, Taxter T, Tejpar S, Teuwen J, Thompson E, Tramm T, Tran W, van der Laak J, van Diest P, Verghese G, Viale G, Vieth M, Wahab N, Walter T, Waumans Y, Wen H, Yang W, Yuan Y, Zin R, Adams S, Bartlett J, Loibl S, Denkert C, Savas P, Loi S, Salgado R, Stovgaard E. Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer. The Journal Of Pathology 2023, 260: 498-513. PMID: 37608772, PMCID: PMC10518802, DOI: 10.1002/path.6155.Peer-Reviewed Original ResearchConceptsTumor-infiltrating lymphocytesTriple-negative breast cancerBreast cancerTIL assessmentHER2-positive breast cancerRoutine clinical managementTIL evaluationTumor-immune interactionsClinical managementDiscordant assessmentsClinical significancePrognostic biomarkerTIL quantificationCancerDaily practicePatientsTrialsTissue patternsAssessmentLymphocytesBiomarkers
2020
Report 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 assessmentReviewCancerPitfalls 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 studiesAssessment