2020
Pitfalls 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
2011
Artificial neural network analysis of circulating tumor cells in metastatic breast cancer patients
Giordano A, Giuliano M, De Laurentiis M, Eleuteri A, Iorio F, Tagliaferri R, Hortobagyi GN, Pusztai L, De Placido S, Hess K, Cristofanilli M, Reuben JM. Artificial neural network analysis of circulating tumor cells in metastatic breast cancer patients. Breast Cancer Research And Treatment 2011, 129: 451-458. PMID: 21710134, DOI: 10.1007/s10549-011-1645-5.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorBreast NeoplasmsFemaleHumansImmunohistochemistryKaplan-Meier EstimateLinear ModelsMiddle AgedNeoplastic Cells, CirculatingNeural Networks, ComputerPrognosisProportional Hazards ModelsReceptor, ErbB-2Receptors, EstrogenReceptors, ProgesteroneRetrospective StudiesRisk AssessmentRisk FactorsSurvival RateTexasTime FactorsConceptsMetastatic breast cancer patientsRisk of deathBreast cancer patientsCTC countMBC patientsPrognostic effectCancer patientsTumor subtypesTumor cellsMD Anderson Cancer CenterConsecutive MBC patientsTriple-negative MBCMetastatic disease sitesAnderson Cancer CenterTumor molecular subtypeNumber of CTCsMolecular tumor subtypesVisceral metastasesOverall survivalCancer CenterHER2 statusProgesterone receptorMolecular subtypesTherapy typePrognostic tool