2021
Deep learning trained on hematoxylin and eosin tumor region of Interest predicts HER2 status and trastuzumab treatment response in HER2+ breast cancer
Farahmand S, Fernandez AI, Ahmed FS, Rimm DL, Chuang JH, Reisenbichler E, Zarringhalam K. Deep learning trained on hematoxylin and eosin tumor region of Interest predicts HER2 status and trastuzumab treatment response in HER2+ breast cancer. Modern Pathology 2021, 35: 44-51. PMID: 34493825, PMCID: PMC10221954, DOI: 10.1038/s41379-021-00911-w.Peer-Reviewed Original ResearchConceptsHER2 statusBreast cancerTreatment responseHER2-positive breast cancerAnti-HER2 agentsPre-treatment samplesNeoadjuvant chemotherapyTrastuzumab therapyClinical outcomesClinical evaluationProtein immunohistochemistryHER2 amplificationTrastuzumab responseTumor stainTreatment selectionTCGA testPathology teamTumor regionCancer featuresCancerPatientsHER2Current standardImmunohistochemistryHematoxylin
2002
Subjective Differences in Outcome Are Seen as a Function of the Immunohistochemical Method Used on a Colorectal Cancer Tissue Microarray
Chung GG, Kielhorn EP, Rimm DL. Subjective Differences in Outcome Are Seen as a Function of the Immunohistochemical Method Used on a Colorectal Cancer Tissue Microarray. Clinical Colorectal Cancer 2002, 1: 237-242. PMID: 12450422, DOI: 10.3816/ccc.2002.n.005.Peer-Reviewed Original ResearchConceptsTissue microarrayTissue sectionsColorectal cancer tissue microarraySemiquantitative grading systemColorectal cancer specimensCancer tissue microarrayPatient outcomesLarge cohortSubjective assessmentCancer specimensImmunohistochemical methodsGrading systemNuclear stainingPathology literatureProtein expressionTissue samplesCell preparationsExpression levelsBeta-catenin antibodyCurrent standardImmunohistochemistryCohortOutcomesApparent increaseExpression