2023
Machine learning-based cluster analysis of immune cell subtypes and breast cancer survival
Wang Z, Katsaros D, Wang J, Biglio N, Hernandez B, Fei P, Lu L, Risch H, Yu H. Machine learning-based cluster analysis of immune cell subtypes and breast cancer survival. Scientific Reports 2023, 13: 18962. PMID: 37923775, PMCID: PMC10624674, DOI: 10.1038/s41598-023-45932-4.Peer-Reviewed Original ResearchConceptsImmune cell clustersT cellsHost immunityImmune cellsUnsupervised hierarchical clusteringImmune responseCD8-positive T cellsMemory CD4 T cellsCox regression survival analysisRegulatory T cellsPositive T cellsCD4 T cellsDifferent immune cellsDistinct immune responsesBreast cancer survivalImmune cell subtypesMemory B cellsImmune cell typesRegression survival analysisCell clustersBreast cancer progressionT cell receptor signalingCytokine stormOverall survivalFavorable survival
2016
Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer
Hampras SS, Sucheston-Campbell LE, Cannioto R, Chang-Claude J, Modugno F, Dörk T, Hillemanns P, Preus L, Knutson KL, Wallace PK, Hong CC, Friel G, Davis W, Nesline M, Pearce CL, Kelemen LE, Goodman MT, Bandera EV, Terry KL, Schoof N, Eng KH, Clay A, Singh PK, Joseph JM, Aben KK, Anton-Culver H, Antonenkova N, Baker H, Bean Y, Beckmann MW, Bisogna M, Bjorge L, Bogdanova N, Brinton LA, Brooks-Wilson A, Bruinsma F, Butzow R, Campbell IG, Carty K, Cook LS, Cramer DW, Cybulski C, Dansonka-Mieszkowska A, Dennis J, Despierre E, Dicks E, Doherty JA, du Bois A, Dürst M, Easton D, Eccles D, Edwards RP, Ekici AB, Fasching PA, Fridley BL, Gao YT, Gentry-Maharaj A, Giles GG, Glasspool R, Gronwald J, Harrington P, Harter P, Hasmad HN, Hein A, Heitz F, Hildebrandt MA, Hogdall C, Hogdall E, Hosono S, Iversen ES, Jakubowska A, Jensen A, Ji BT, Karlan BY, Kellar M, Kelley JL, Kiemeney LA, Klapdor R, Kolomeyevskaya N, Krakstad C, Kjaer SK, Kruszka B, Kupryjanczyk J, Lambrechts D, Lambrechts S, Le ND, Lee AW, Lele S, Leminen A, Lester J, Levine DA, Liang D, Lissowska J, Liu S, Lu K, Lubinski J, Lundvall L, Massuger LF, Matsuo K, McGuire V, McLaughlin JR, McNeish I, Menon U, Moes-Sosnowska J, Narod SA, Nedergaard L, Nevalinna H, Nickels S, Nevanlinna H, Olson S, Orlow I, Weber R, Paul J, Pejovic T, Pelttari L, Perkins B, Permuth-Wey J, Pike M, Plisiecka-Halasa J, Poole E, Risch H, Rossing M, Rothstein J, Rudolph A, Runnebaum I, Rzepecka I, Salvesen H, Schernhammer E, Schmitt K, Schwaab I, Shu X, Shvetsov Y, Siddiqui N, Sieh W, Song H, Southey M, Tangen I, Teo S, Thompson P, Timorek A, Tsai Y, Tworoger S, Tyrer J, van Altena A, Vergote I, Vierkant R, Walsh C, Wang-Gohrke S, Wentzensen N, Whittemore A, Wicklund K, Wilkens L, Wu A, Wu X, Woo Y, Yang H, Zheng W, Ziogas A, Gayther S, Ramus S, Sellers T, Schildkraut J, Phelan C, Berchuck A, Chenevix-Trench G, Cunningham J, Pharoah P, Ness R, Odunsi K, Goode E, Moysich K. Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer. Oncotarget 2016, 7: 69097-69110. PMID: 27533245, PMCID: PMC5340115, DOI: 10.18632/oncotarget.10215.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinoma, Clear CellAdultAgedCarcinoma, Ovarian EpithelialFemaleGene Expression Regulation, NeoplasticGene FrequencyGenetic Predisposition to DiseaseGenotypeHumansMiddle AgedNeoplasms, Glandular and EpithelialOvarian NeoplasmsPolymorphism, Single NucleotideProtein Serine-Threonine KinasesReceptor, Transforming Growth Factor-beta Type IIReceptors, Transforming Growth Factor betaRisk FactorsT-Lymphocytes, RegulatoryConceptsOvarian cancerEpithelial ovarian cancer casesClear cell ovarian cancerClear cell EOCMediators of immunosuppressionSignificant global associationSubset of CD4Regulatory T cellsCell pathwaysOvarian cancer patientsOvarian cancer casesImmune complex receptorsGene-level associationsHistologic subtypeEOC patientsSignificant single SNP associationCancer patientsCancer casesT cellsT lymphocytesClear cellsImmune moleculesMRNA expressionCancerExpression levels
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