Kurt Schalper, MD, PhD
Professor of PathologyDownloadHi-Res Photo
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Appointments
Pathology
Primary
Medical Oncology and Hematology
Secondary
Additional Titles
Director, Translational Immuno-oncology Laboratory
Contact Info
Appointments
Pathology
Primary
Medical Oncology and Hematology
Secondary
Additional Titles
Director, Translational Immuno-oncology Laboratory
Contact Info
Appointments
Pathology
Primary
Medical Oncology and Hematology
Secondary
Additional Titles
Director, Translational Immuno-oncology Laboratory
Contact Info
About
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Titles
Professor of Pathology
Director, Translational Immuno-oncology Laboratory
Biography
I trained as cell biologist, surgical pathologist and served in clinical molecular diagnostics. In addition, during my postdoctoral work at Yale I focused in developing strategies to objectively and quantitatively measure key immunotherapy related biomarkers in immune cells and cancer tissues. Most of this work has been performed in close collaboration with other Yale researchers and published in peer-reviewed journals. Recently, I was appointed to lead the Translational Immuno-Oncology Laboratory (T.I.L.) in the Yale Cancer Center, that aims to produce and support high quality translational research in immuno-oncology through standardized analyses of biomarkers and cross-integration with other Yale resources.
Last Updated on April 07, 2025.
Appointments
Pathology
ProfessorPrimaryMedical Oncology and Hematology
Associate Professor on TermSecondary
Other Departments & Organizations
- Cancer Immunology
- Human and Translational Immunology Program
- Internal Medicine
- Medical Oncology and Hematology
- Molecular Medicine, Pharmacology, and Physiology
- Pathology
- Pathology and Molecular Medicine
- Pathology Research
- Program in Translational Biomedicine (PTB)
- Schalper Lab
- Yale Cancer Center
- Yale Center for Immuno-Oncology
- Yale Combined Program in the Biological and Biomedical Sciences (BBS)
- Yale-UPR Integrated HIV Basic and Clinical Sciences Initiative
Education & Training
- PhD
- Universidad Catolica de Chile (2008)
- MD
- San Sebastian University (2003)
Research
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Overview
Medical Research Interests
Breast Neoplasms; Pathology
ORCID
0000-0001-5692-4833- View Lab Website
Schalper Lab
Research at a Glance
Yale Co-Authors
Frequent collaborators of Kurt Schalper's published research.
Publications Timeline
A big-picture view of Kurt Schalper's research output by year.
Research Interests
Research topics Kurt Schalper is interested in exploring.
David Rimm, MD, PhD
Roy S. Herbst, MD, PhD
Hongyu Zhao, PhD
Lajos Pusztai, MD, DPhil
Michael Cecchini, MD
Thazin Nwe Aung, PhD
111Publications
10,567Citations
Breast Neoplasms
Publications
2026
Machine learning assessment of pathologic response in lung cancer resections after neoadjuvant therapy - IASLC MPR Project
Dacic S, Shenker D, Redman M, Brunner L, Saqi A, Cooper W, Borczuk A, Chung J, Glass C, Lopez J, Roden A, Sholl L, Weissferdt A, Brosnan-Cashman J, Hennek S, Grullon S, Posadas J, Fujimoto J, Connolly C, Wynes M, -Espiridion B, Lee J, Berezowska S, Chou T, Kerr K, Nicholson A, Schalper K, Tsao M, Ready N, Cascone T, Heymach J, Sepesi B, Shu C, Rizvi N, Sonett J, Altorki N, Provencio M, Bunn P, Kris M, Travis W, Yu L, Wistuba I, Committee I. Machine learning assessment of pathologic response in lung cancer resections after neoadjuvant therapy - IASLC MPR Project. Journal Of Thoracic Oncology 2026, 103953. PMID: 42229633, DOI: 10.1016/j.jtho.2026.103953.Peer-Reviewed Original ResearchAltmetricConceptsPathological responseViable tumorTumor bedAssessment of pathological responseSurgically resected lung cancerAssessment of PRResidual viable tumorRelapse-free survivalLung cancer resectionSquamous cell carcinomaMachine learning assessmentNeoadjuvant therapyEvaluation of PRNonsquamous carcinomaOverall survivalCancer resectionCell carcinomaDiscordant casesLung cancerCarcinomaTumorConvex hull algorithmPathologistsTB areasSurvivalNSCLC brain metastases exhibit reduced HLA-I antigen presentation machinery and immune evasion independent of IFNγ signaling defects
Vilariño N, de Rodas M, Villalba-Esparza M, Rajendran B, Huang B, Hijazo-Pechero S, Costantini A, Ranjan K, Ramos-Paradas J, Lu B, Nadal E, Goldberg S, Nguyen D, Schalper K. NSCLC brain metastases exhibit reduced HLA-I antigen presentation machinery and immune evasion independent of IFNγ signaling defects. Molecular Cancer 2026 PMID: 42210261, DOI: 10.1186/s12943-026-02687-6.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerAntigen presentation machineryImmune checkpoint inhibitorsTumor-infiltrating lymphocytesNon-small cell lung cancer brain metastasisBrain metastasesAPM componentsPresentation machineryImmune evasionImmune checkpoint inhibitor resistanceNon-malignant stromal cellsHuman tumorsLung cancer brain metastasisMultiplexed quantitative immunofluorescenceCancer brain metastasesSignaling defectsCell lung cancerUnfavorable clinical featuresPotential translational significanceSignaling markersAssociated with unfavorable clinical featuresIFNG signalingCheckpoint inhibitorsMetastatic lesionsExtracranial diseaseTumor cell-intrinsic programs of metabolic adaptation and immune evasion in colorectal cancer liver metastases (CRCLMs).
Li X, Ashley K, Iyer K, Aung T, Cecchini M, Schalper K. Tumor cell-intrinsic programs of metabolic adaptation and immune evasion in colorectal cancer liver metastases (CRCLMs). Journal Of Clinical Oncology 2026, 44: 3554-3554. DOI: 10.1200/jco.2026.44.16_suppl.3554.Peer-Reviewed Original ResearchConceptsColorectal cancer liver metastasesDigital spatial profilingLiver metastasesGene Set Enrichment AnalysisImmune evasionPrimary CRCIndependent cohortTranslational relevanceExpression relative to normal tissueCancer liver metastasesCell-intrinsic programsGeoMx Digital Spatial ProfilerAcute-phase responseImmunotherapy resistancePrimary tumorNon-tumor tissuesMetabolic adaptationSurvival outcomesTissue microarrayTreatment resistanceUnfavorable survivalCellular metabolic adaptationMalignant cellsLiver microenvironmentTherapeutic vulnerabilitiesAI-derived CD8⁺ cytotoxic T-cell immune signatures from baseline H&E images to predict immunotherapy benefit over chemotherapy in non–small cell lung cancer: Blinded validation in CheckMate-227 (CM227).
Barrera C, Safta W, Mutha P, Khorrami M, Grootendorst D, Mustatea O, Eddy N, Pathak T, de Rodas Gregorio M, Schalper K, Ramalingam S, Velcheti V, Madabhushi A. AI-derived CD8⁺ cytotoxic T-cell immune signatures from baseline H&E images to predict immunotherapy benefit over chemotherapy in non–small cell lung cancer: Blinded validation in CheckMate-227 (CM227). Journal Of Clinical Oncology 2026, 44: 8534-8534. DOI: 10.1200/jco.2026.44.16_suppl.8534.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerCell lung cancerImmune signaturesPD-L1Survival benefitAdvanced non-small cell lung cancerIV non-small cell lung cancerStage IV non-small cell lung cancerLung cancerMulti-institutional retrospective cohortNo significant OS differenceAssociated with longer OSAssociated with favorable OSEvaluate PD-L1First-line nivolumabSignificant OS differencePD-L1 expressionNon-overlapping cohortsTreatment-specific analysesNSCLC ptsSuperior OSAntitumor immunityImmunotherapy benefitLonger OSFavorable OSPretreatment spatial immune architecture and 1-year clinical benefit to first-line ICB in advanced melanoma.
Amrane K, Hemon P, Delarue Y, Robert C, Foulquier N, LE Meur C, LE Rochais M, Marec N, Pradier O, Misery L, Legoupil D, Schalper K, Uguen A, Alemany P, Massard C, Berthou C, Flippot R, Italiano A. Pretreatment spatial immune architecture and 1-year clinical benefit to first-line ICB in advanced melanoma. Journal Of Clinical Oncology 2026, 44: 9539-9539. DOI: 10.1200/jco.2026.44.16_suppl.9539.Peer-Reviewed Original ResearchConceptsImmune checkpoint blockadeT cellsImaging Mass CytometryTumor cellsPD-L1HLA-DRCutaneous melanomaTumor densityTumor microenvironmentAssociated with lackPlasma cellsB cellsDensity of B cellsTumor PD-L1Progression-free survivalAssociated with lack of benefitHLA-DR expressionAdvanced cutaneous melanomaT cell enrichmentTumor marker expressionB cell densityLack of benefitCheckpoint blockadeAdvanced melanomaMelanoma cohortDistinct genomic and immunologic tumor evolution in germline TP53-driven breast cancers
Boruah N, Hoyos D, Moses R, Hausler R, Desai H, Le A, Good M, Kelly G, Raghavakaimal A, Tayeb M, Narasimhamurthy M, Doucette A, Gabriel P, Feldman M, Park J, Lopez de Rodas M, Schalper K, Goldfarb S, Nayak A, Levine A, Greenbaum B, Maxwell K. Distinct genomic and immunologic tumor evolution in germline TP53-driven breast cancers. Nature Communications 2026 PMID: 42168203, DOI: 10.1038/s41467-026-73163-4.Peer-Reviewed Original ResearchCitationsAltmetricConceptsLi-Fraumeni syndromeCytotoxic T cellsSporadic BCBreast cancerT cellsBreast tissueP53 target genes BaxT cell infiltrationPremenopausal breast cancerNormal breast tissueTarget genes BaxLow CD8TP53 alterationsInvasive BCLi-FraumeniBiallelic lossGene BaxChromosomal instabilityOncogenic variantsTumor evolutionCancerAneuploid segmentBreastTissueCD8Conventional type-1 DC density is associated with checkpoint inhibitor response across multiple types of cancer
Lopez-Janeiro A, González-Gomariz J, Issa F, Hester J, Porciuncula A, Teijeira A, Luri-Rey C, Ruiz-Guillamon D, Perez-Gracia J, Perez-Ruiz E, Barragan I, Martín-Algarra S, Sanmamed M, Ortego I, Rodriguez-Ruiz M, Alexandru R, Rodriguez I, Arrieta-Aranzueque S, Rimm D, Aung T, Schalper K, de Andrea C, Melero I. Conventional type-1 DC density is associated with checkpoint inhibitor response across multiple types of cancer. Journal Of Clinical Investigation 2026, 136: e200987. PMID: 42065248, PMCID: PMC13132367, DOI: 10.1172/jci200987.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsNon-small-cell lung cancerCD8+ T cellsCytotoxic T lymphocytesCheckpoint inhibitorsT cellsCD8+ T cell infiltrationConventional type 1 dendritic cellsContext of costimulatory moleculesType 1 dendritic cellsTissue immunofluorescenceCancer typesT lymphocyte densityCheckpoint inhibitor responseT cell infiltrationT cell activationT cell transcriptsAntigens to CD8Multiple cancer typesCostimulatory moleculesUrothelial cancerDendritic cellsFlt3-LCCL5 chemokinesClinical benefitT lymphocytesLeveraging multi-modal foundation models for analysing spatial multi-omic and histopathology data
Liu T, Huang T, Ding T, Wu H, Humphrey P, Perincheri S, Schalper K, Ying R, Xu H, Zou J, Mahmood F, Zhao H. Leveraging multi-modal foundation models for analysing spatial multi-omic and histopathology data. Nature Biomedical Engineering 2026, 1-18. PMID: 41644824, DOI: 10.1038/s41551-025-01602-6.Peer-Reviewed Original ResearchThis study presents spEMO, an AI framework integrating histopathology images and spatial multi-omics data to improve biological discovery, disease prediction, and medical reporting.
2025
Society for Immunotherapy of Cancer: Standards for Reporting of Multiplex Immunohistochemistry/Immunofluorescence Assays (STORMI)
Sater S, Bifulco C, Rodriguez-Canales J, Yeong J, Akturk G, Angelo M, Ballesteros-Merino C, Bankhead P, Basu S, Blando J, Brajkovic S, Cassano M, Chen B, Coskun A, Cottrell T, De Andrea C, Edwards R, Egelston C, Engle L, Ernstoff M, Fan R, Feldman M, Fox B, Galon J, Gartrell R, Gnjatic S, Green B, Gulley J, Hellebust A, Hewitt S, Hollmann T, Horn L, Howat W, Hoyt C, Jensen S, Kulasinghe A, Lassoued W, Lott S, Mansfield J, Marwitz S, Netto G, Page D, Parra E, Rimm D, Rodig S, Salgado R, Schapiro D, Schalper K, Sunshine J, Surace M, Szalay A, Thurin M, Villasboas J, Wharton K, Wistuba I, Yearley J, Yuan Y, Zaki G, Ziai J, Taube J. Society for Immunotherapy of Cancer: Standards for Reporting of Multiplex Immunohistochemistry/Immunofluorescence Assays (STORMI). Journal For ImmunoTherapy Of Cancer 2025, 13: e012280. PMID: 41423269, PMCID: PMC12718562, DOI: 10.1136/jitc-2025-012280.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsSociety for Immunotherapy of CancerSociety for ImmunotherapyImmunotherapy of cancerPractice guidelinesTumor microenvironmentMultiplex immunofluorescenceConsensus checklistBiomarker discovery effortsAntibody-based technologiesCell clustersInfectious diseasesBiomarkersAnalytical validationCross-study comparisonsMET (c-Met) protein overexpression is an emerging protein biomarker in non-small cell lung cancer
Tsao M, Sholl L, Shiller M, Illei P, Wistuba I, Beasley M, Schalper K, Simmons A, Ansell P, Beruti S, Mino-Kenudson M. MET (c-Met) protein overexpression is an emerging protein biomarker in non-small cell lung cancer. Npj Precision Oncology 2025, 9: 369. PMID: 41266553, PMCID: PMC12635195, DOI: 10.1038/s41698-025-01144-9.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsCitationsAltmetricConceptsNon-small cell lung cancerIHC-based biomarkersCell lung cancerClinically relevant biomarkersAntibody-drug conjugatesProtein biomarkersPrognostic valueGenomic aberrationsLung cancerProtein overexpressionC-MetMet proteinRelevant biomarkersBiomarkersMetSOverexpressionImmunohistochemistryProteinCancerClinic
Clinical Trials
Current Trials
Determining Mechanisms of Sensitivity and Resistance to Anti-Cancer Therapy for Advanced Lung Cancer
IRB ID1603017333RoleSub InvestigatorPrimary Completion Date06/16/2036Recruiting Participants
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- November 12, 2025
Twenty-Seven YSM Faculty Members Recognized for Highly Cited Research
- October 10, 2025
‘Google Maps’ Approach to Revolutionize Lung Cancer Treatment
- October 08, 2025
Yale Cancer Experts to Present This Week at Top International Oncology Conference
- May 23, 2025
Rimm Lab Marks 30 Years of Research, Innovation, Training at Yale Pathology
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