Kim Blenman, PhD, MS
Assistant Professor of Medicine (Medical Oncology) and Assistant Professor of Computer ScienceDownloadHi-Res Photo
Cards
Appointments
Medical Oncology
Primary
About
Titles
Assistant Professor of Medicine (Medical Oncology) and Assistant Professor of Computer Science
Biography
Dr Blenman is an immunologist, clinical chemist, and computer scientist with expertise in clinical and translational research. She uses and develops novel software tools and wet lab methods to understand the mechanisms responsible for disparities in disease pathogenesis, therapeutic response, and therapy-induced toxicity.
Appointments
Medical Oncology
Assistant ProfessorPrimary
Other Departments & Organizations
Education & Training
- Postdoctoral Fellow
- City of Hope Comprehensive Cancer Center
- Fellowship
- University of California – College of Medicine, San Francisco
- PhD
- University of Florida College of Medicine
- MS
- University of Florida College of Medicine
Research
Overview
Medical Research Interests
Algorithms; Breast Neoplasms; Clinical Trial; Computer Graphics; Data Visualization; Head and Neck Neoplasms; Image Processing, Computer-Assisted; Immunotherapy; Medical Informatics Computing; Melanoma; Multiomics; Multiple Myeloma
Public Health Interests
Bioinformatics; Biomarkers; Cancer; Clinical Trials; Immunology; Pharmaceuticals and Medical Devices
- View Lab Website
Blenman Innovation Group
Publications
2024
Circulating tumor DNA fraction predicts residual cancer burden post-neoadjuvant chemotherapy in triple negative breast cancer
Shan N, Gould B, Wang X, Bonora G, Blenman K, Foldi J, Campos G, Walsh M, Du P, Pusztai L. Circulating tumor DNA fraction predicts residual cancer burden post-neoadjuvant chemotherapy in triple negative breast cancer. The Journal Of Liquid Biopsy 2024, 6: 100168. DOI: 10.1016/j.jlb.2024.100168.Peer-Reviewed Original ResearchAltmetricConceptsTriple negative breast cancerResidual cancer burdenCirculating tumor DNANegative breast cancerPathological responsePost-NACBreast cancerPlasma circulating tumor DNATriple negative breast cancer patientsResidual cancer burden scoreCirculating tumour DNA fractionPost-neoadjuvant chemotherapyPre-NAC samplesWeekly nab-paclitaxelTumor DNA methylation profilesTumor DNA fractionHot spot mutationsYouden's J statisticNab-paclitaxelPre-NACTumor variantsTumor DNATumor fractionClinical trialsDNA methylation profilesMicrobiome-Based Cancer Therapeutics
Luvhengo T, Miya T, Demetriou D, Blenman K, Dlamini Z. Microbiome-Based Cancer Therapeutics. 2024, 208-226. DOI: 10.1201/9781032706450-16.Peer-Reviewed Original ResearchPeripheral blood immune parameters, response, and adverse events after neoadjuvant chemotherapy plus durvalumab in early-stage triple-negative breast cancer
Foldi J, Blenman K, Marczyk M, Gunasekharan V, Polanska A, Gee R, Davis M, Kahn A, Silber A, Pusztai L. Peripheral blood immune parameters, response, and adverse events after neoadjuvant chemotherapy plus durvalumab in early-stage triple-negative breast cancer. Breast Cancer Research And Treatment 2024, 208: 369-377. PMID: 39002068, DOI: 10.1007/s10549-024-07426-3.Peer-Reviewed Original ResearchConceptsImmune-related adverse eventsTriple-negative breast cancerAssociated with pathological responsePathological complete responseNeoadjuvant chemotherapyCytokine levelsPathological responseAdverse eventsBreast cancerEarly-stage triple-negative breast cancerPatients treated with immune checkpoint inhibitorsB cell clonal expansionMeasured serum cytokine levelsImmune checkpoint inhibitorsGM-CSF levelsPeripheral blood cytokine levelsBlood cytokine levelsSerum cytokine levelsB cell receptorMagnetic bead panelBenjamini-Hochberg correctionSample of patientsImmunoSEQ platformCheckpoint inhibitorsComplete responsePredicting peripheral neuropathy following neoadjuvant therapy in patients with breast cancer.
Feiger B, Biancalana M, Shelton A, Blenman K, Lustberg M. Predicting peripheral neuropathy following neoadjuvant therapy in patients with breast cancer. Journal Of Clinical Oncology 2024, 42: e12639-e12639. DOI: 10.1200/jco.2024.42.16_suppl.e12639.Peer-Reviewed Original ResearchAltmetricConceptsBreast cancer patientsNeoadjuvant chemotherapyPeripheral neuropathyNeoadjuvant therapyBreast cancerCancer patientsAdministration of neoadjuvant chemotherapyCohort of breast cancer patientsLikelihood of breast-conserving surgeryContrast-enhanced magnetic resonance imagingQuality of lifeDynamic contrast-enhanced magnetic resonance imagingBreast-conserving surgeryReduced tumor burdenTreatment-induced neuropathyOccurrence of neuropathyInduce peripheral neuropathyDensity of blood vesselsPatients' quality of lifeMagnetic resonance imagingAmeliorate neuropathyDCE-MRI dataTumor burdenCumulative toxic effectsIntratumoral vascularityTraining 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 ResearchCitationsAltmetricConceptsStromal 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 commentaryReproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models
Elfer K, Gardecki E, Garcia V, Ly A, Hytopoulos E, Wen S, Hanna M, Peeters D, Saltz J, Ehinger A, Dudgeon S, Li X, Blenman K, Chen W, Green U, Birmingham R, Pan T, Lennerz J, Salgado R, Gallas B. Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models. Modern Pathology 2024, 37: 100439. PMID: 38286221, DOI: 10.1016/j.modpat.2024.100439.Peer-Reviewed Original ResearchCitationsConceptsArtificial intelligenceAnnotation of medical imagesMedical imagesTesting artificial intelligenceTest data setsArtificial intelligence modelsAnnotation effortEvaluative annotationsDiagnostic image analysisIntelligence modelsAnnotation workflowData setsDigital pathologyAnnotationQuality frameworkIntelligenceArtificialWorkflowImage analysisPrediction modelMetadataConsolidated Standards of Reporting TrialsFrameworkImagesStandards for Reporting Diagnostic AccuracyImage‐based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno‐oncology Biomarker Working Group on Breast Cancer
Jahangir C, Page D, Broeckx G, Gonzalez C, Burke C, Murphy C, Reis‐Filho J, Ly A, Harms P, Gupta R, Vieth M, Hida A, Kahila M, Kos Z, van Diest P, Verbandt S, Thagaard J, Khiroya R, Abduljabbar K, Haab G, Acs B, Adams S, Almeida J, Alvarado‐Cabrero I, Azmoudeh‐Ardalan F, Badve S, Baharun N, Bellolio E, Bheemaraju V, Blenman K, Fujimoto L, Burgues O, Chardas A, Cheang M, Ciompi F, Cooper L, Coosemans A, Corredor G, Portela F, Deman F, Demaria S, Dudgeon S, Elghazawy M, Fernandez‐Martín C, Fineberg S, Fox S, Giltnane J, Gnjatic S, Gonzalez‐Ericsson P, Grigoriadis A, Halama N, Hanna M, Harbhajanka A, Hart S, Hartman J, Hewitt S, Horlings H, Husain Z, Irshad S, Janssen E, Kataoka T, Kawaguchi K, Khramtsov A, Kiraz U, Kirtani P, Kodach L, Korski K, Akturk G, Scott E, Kovács A, Lænkholm A, Lang‐Schwarz C, Larsimont D, Lennerz J, Lerousseau M, Li X, Madabhushi A, Maley S, Narasimhamurthy V, Marks D, McDonald E, Mehrotra R, Michiels S, Kharidehal D, 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, Rajpoot N, Rapoport B, Rau T, Ribeiro J, Rimm D, Vincent‐Salomon A, Saltz J, Sayed S, Hytopoulos E, Mahon 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, Verghese G, Viale G, Wahab N, Walter T, Waumans Y, Wen H, Yang W, Yuan Y, Bartlett J, Loibl S, Denkert C, Savas P, Loi S, Stovgaard E, Salgado R, Gallagher W, Rahman A. Image‐based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno‐oncology Biomarker Working Group on Breast Cancer. The Journal Of Pathology 2024, 262: 271-288. PMID: 38230434, PMCID: PMC11288342, DOI: 10.1002/path.6238.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsImmune profileInternational Immuno-Oncology Biomarker Working GroupIdentification of clinically relevant biomarkersField of immuno-oncologyBiomarker Working GroupManagement of cancer patientsImmune profiling of tumorsClinical trial perspectiveTranslational implicationsProfiling of tumorsIndividual tumor cellsPredicting disease prognosisClinically relevant biomarkersSubtypes of cancerImmuno-oncologyTumor microenvironmentMultiplex immunohistochemistryTreatment responseTumor cellsBreast cancerTumor samplesCancer patientsTreatment choiceDisease prognosisRelevant biomarkers
2023
Initial interactions with the FDA on developing a validation dataset as a medical device development tool
Hart S, Garcia V, Dudgeon S, Hanna M, Li X, Blenman K, Elfer K, Ly A, Salgado R, Saltz J, Gupta R, Hytopoulos E, Larsimont D, Lennerz J, Gallas B. Initial interactions with the FDA on developing a validation dataset as a medical device development tool. The Journal Of Pathology 2023, 261: 378-384. PMID: 37794720, PMCID: PMC10841854, DOI: 10.1002/path.6208.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsPitfalls 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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsTumor-infiltrating lymphocytesTriple-negative breast cancerBreast cancerTIL assessmentHER2-positive breast cancerRoutine clinical managementTIL evaluationTumor-immune interactionsClinical managementDiscordant assessmentsClinical significancePrognostic biomarkerTIL quantificationCancerDaily practicePatientsTrialsTissue patternsAssessmentLymphocytesBiomarkersSpatial 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 ResearchCitationsAltmetricMeSH Keywords and Concepts
Clinical Trials
Current Trials
Impact of obesity and sedentary lifestyles on immune response to and clinical outcomes of immunotherapies
HIC ID2000032988RolePrincipal InvestigatorPrimary Completion Date06/01/2023Recruiting Participants
Academic Achievements & Community Involvement
See Below
honor Career Development Award
National AwardBreast Cancer Research Foundation-American Association for Cancer Research (BCRF-AACR)Details03/31/2022United Stateshonor Blavatnik Funding and Pitchfest 2019 Quarterfinalist
Yale University AwardYale UniversityDetails09/03/2018United Stateshonor Melanoma Research Alliance Young Investigator Award
National AwardMelanoma Research AllianceDetails05/15/2015United States
News & Links
Media
- Kim R.M. Blenman* and Marcus W. Bosenberg. Immune cell and cell cluster phenotyping, quantitation, and visualization using in silico multiplexed images and tissue cytometry. Cytometry A, 2019. PMID: 30468565. [*Corresponding Author].
News
- April 12, 2024
Yale Cancer Center Faculty and Trainees Present at AACR Annual Meeting
- October 12, 2023
Yale Cancer Center Researchers Awarded 2023-2024 Grants from the Breast Cancer Research Foundation
- September 20, 2023
Smilow Shares CME: Perspectives on the USPSTF Breast Screening Recommendations
- November 08, 2022
Biomarkers could determine the need for chemotherapy in young patients with ER+ breast cancer
Related Links
- Yale School of Medicine Committee on the Status of Women in Medicine
- Yale School of Medicine Minority Organization for Retention and Expansion
- TissueGnostics EACR Industry Symposium 2021: The spatial dynamics of the TIME
- Yale University Women Faculty Forum
- Practical approaches for using tissue cytometry for clinical and research applications