2019
Serum gamma-glutamyltransferase and the overall survival of metastatic pancreatic cancer
Xiao Y, Yang H, Lu J, Li D, Xu C, Risch HA. Serum gamma-glutamyltransferase and the overall survival of metastatic pancreatic cancer. BMC Cancer 2019, 19: 1020. PMID: 31664937, PMCID: PMC6819453, DOI: 10.1186/s12885-019-6250-8.Peer-Reviewed Original ResearchConceptsPancreatic ductal adenocarcinomaMetastatic pancreatic ductal adenocarcinomaOverall survivalSerum GGTSignificant dose-response associationCox proportional hazards modelMetastatic PDAC patientsDose-response associationMetastatic pancreatic cancerPancreatic cancer survivalSpecialized cancer hospitalBlood glucose levelsProportional hazards modelHazard ratioPrognostic roleCancer HospitalPDAC patientsCancer survivalSubgroup analysisPancreatic cancerDuctal adenocarcinomaMetastatic PCCancer occurrenceGlucose levelsMortality riskUse of aspirin, other nonsteroidal anti-inflammatory drugs and acetaminophen and risk of endometrial cancer: the Epidemiology of Endometrial Cancer Consortium
Webb PM, Na R, Weiderpass E, Adami HO, Anderson KE, Bertrand KA, Botteri E, Brasky TM, Brinton LA, Chen C, Doherty JA, Lu L, McCann SE, Moysich KB, Olson S, Petruzella S, Palmer JR, Prizment AE, Schairer C, Setiawan VW, Spurdle AB, Trabert B, Wentzensen N, Wilkens L, Yang HP, Yu H, Risch HA, Jordan SJ. Use of aspirin, other nonsteroidal anti-inflammatory drugs and acetaminophen and risk of endometrial cancer: the Epidemiology of Endometrial Cancer Consortium. Annals Of Oncology 2019, 30: 310-316. PMID: 30566587, PMCID: PMC6386026, DOI: 10.1093/annonc/mdy541.Peer-Reviewed Original ResearchConceptsNon-aspirin nonsteroidal anti-inflammatory drugsNonsteroidal anti-inflammatory drugsEndometrial Cancer ConsortiumEndometrial cancerAnti-inflammatory drugsObese womenOdds ratioCancer ConsortiumStudy-specific odds ratiosLogistic regressionStandard-dose aspirinUse of aspirinUse of acetaminophenConfidence intervalsTimes/weekCase-control studyRisk of cancerMixed-effects logistic regressionLow-dose formulationsLeast weekly useNormal weightPooled analysisInverse associationStratified analysisReduced risk
2018
Fallopian tube lesions in women at high risk for ovarian cancer: A multicenter study
Visvanathan K, Shaw P, May BJ, Bahadirli-Talbot A, Kaushiva A, Risch H, Narod S, Wang TL, Parkash V, Vang R, Levine DA, Soslow R, Kurman R, Shih IM. Fallopian tube lesions in women at high risk for ovarian cancer: A multicenter study. Cancer Prevention Research 2018, 11: canprevres.0009.2018. PMID: 30232083, PMCID: PMC6760670, DOI: 10.1158/1940-6207.capr-18-0009.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsBiomarkers, TumorBRCA1 ProteinBRCA2 ProteinCystadenocarcinoma, SerousDisease ProgressionFallopian Tube NeoplasmsFallopian TubesFemaleHumansMedical History TakingMiddle AgedOvarian NeoplasmsOvaryPrecancerous ConditionsPrevalencePrognosisProspective StudiesRetrospective StudiesSalpingo-oophorectomyConceptsSerous tubal intraepithelial lesionsHigh-grade serous ovarian carcinomaSerous tubal intraepithelial carcinomaP53 signatureRisk/protective factorsProtective factorsMultiple lesionsFallopian tubePrognosis of womenHigh-risk womenTubal intraepithelial carcinomaTubal intraepithelial lesionsSerous ovarian carcinomaPutative precursor lesionsYears of ageIntraepithelial lesionsIntraepithelial carcinomaMulticenter studyInvasive cancerOvarian carcinomaDisease progressionPrecursor lesionsEpidemiologic dataCombined prevalenceTubal lesionsA Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk
Lu Y, Beeghly-Fadiel A, Wu L, Guo X, Li B, Schildkraut JM, Im HK, Chen YA, Permuth JB, Reid BM, Teer JK, Moysich KB, Andrulis IL, Anton-Culver H, Arun BK, Bandera EV, Barkardottir RB, Barnes DR, Benitez J, Bjorge L, Brenton J, Butzow R, Caldes T, Caligo MA, Campbell I, Chang-Claude J, Claes KBM, Couch FJ, Cramer DW, Daly MB, deFazio A, Dennis J, Diez O, Domchek SM, Dörk T, Easton DF, Eccles DM, Fasching PA, Fortner RT, Fountzilas G, Friedman E, Ganz PA, Garber J, Giles GG, Godwin AK, Goldgar DE, Goodman MT, Greene MH, Gronwald J, Hamann U, Heitz F, Hildebrandt MAT, Høgdall CK, Hollestelle A, Hulick PJ, Huntsman DG, Imyanitov EN, Isaacs C, Jakubowska A, James P, Karlan BY, Kelemen LE, Kiemeney LA, Kjaer SK, Kwong A, Le ND, Leslie G, Lesueur F, Levine DA, Mattiello A, May T, McGuffog L, McNeish IA, Merritt MA, Modugno F, Montagna M, Neuhausen SL, Nevanlinna H, Nielsen FC, Nikitina-Zake L, Nussbaum RL, Offit K, Olah E, Olopade OI, Olson SH, Olsson H, Osorio A, Park SK, Parsons MT, Peeters PHM, Pejovic T, Peterlongo P, Phelan CM, Pujana MA, Ramus SJ, Rennert G, Risch H, Rodriguez GC, Rodríguez-Antona C, Romieu I, Rookus MA, Rossing MA, Rzepecka IK, Sandler DP, Schmutzler RK, Setiawan VW, Sharma P, Sieh W, Simard J, Singer CF, Song H, Southey MC, Spurdle AB, Sutphen R, Swerdlow AJ, Teixeira MR, Teo SH, Thomassen M, Tischkowitz M, Toland AE, Trichopoulou A, Tung N, Tworoger SS, van Rensburg EJ, Vanderstichele A, Vega A, Edwards DV, Webb PM, Weitzel JN, Wentzensen N, White E, Wolk A, Wu AH, Yannoukakos D, Zorn KK, Gayther SA, Antoniou AC, Berchuck A, Goode EL, Chenevix-Trench G, Sellers TA, Pharoah PDP, Zheng W, Long J. A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk. Cancer Research 2018, 78: 5419-5430. PMID: 30054336, PMCID: PMC6139053, DOI: 10.1158/0008-5472.can-18-0951.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesNovel lociGWAS lociCausal genesMajority of GWASTranscriptome-wide association studyAssociation studiesGenotype-Tissue Expression (GTEx) projectLarge-scale genome-wide association studiesHigh-density genotyping dataPlausible causal genesPotential novel lociNovel genetic lociGWAS-identified variantsRNA sequencing dataDisease susceptibility variantsBonferroni-corrected significance levelTranscriptomic analysisExpression projectGenetic lociSummary statistics dataRisk lociGene expressionSequencing dataGenes
2017
Epidemiologic factors that predict long-term survival following a diagnosis of epithelial ovarian cancer
Kim SJ, Rosen B, Fan I, Ivanova A, McLaughlin JR, Risch H, Narod SA, Kotsopoulos J. Epidemiologic factors that predict long-term survival following a diagnosis of epithelial ovarian cancer. British Journal Of Cancer 2017, 116: 964-971. PMID: 28208158, PMCID: PMC5379147, DOI: 10.1038/bjc.2017.35.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinoma, Clear CellAdenocarcinoma, MucinousAdultAgedCanadaCystadenocarcinoma, SerousEndometrial NeoplasmsEpidemiologic FactorsFemaleFollow-Up StudiesHormone Replacement TherapyHumansMiddle AgedNeoplasm InvasivenessNeoplasm StagingOvarian NeoplasmsParityPregnancyPrognosisReproductive HistoryYoung AdultConceptsOvarian cancer-specific mortalityCancer-specific mortalityHormone replacement therapyRisk of deathEpithelial ovarian cancerOvarian cancerHazard ratioEpidemiologic factorsOvulatory cyclesOvarian cancer-specific deathOvarian cancer-specific survivalInvasive epithelial ovarian cancerBMI 5 yearsCancer-specific survivalCancer-specific deathOntario Cancer RegistryProportional hazards regressionConfidence intervalsBorderline significant associationOvarian cancer developmentLong-term survivalGreater cumulative numberHRT useCancer RegistryHistologic subtypeSurvival predictors of Burkitt's lymphoma in children, adults and elderly in the United States during 2000–2013
Mukhtar F, Boffetta P, Risch HA, Park JY, Bubu OM, Womack L, Tran TV, Zgibor JC, Luu HN. Survival predictors of Burkitt's lymphoma in children, adults and elderly in the United States during 2000–2013. International Journal Of Cancer 2017, 140: 1494-1502. PMID: 28006853, PMCID: PMC6919213, DOI: 10.1002/ijc.30576.Peer-Reviewed Original ResearchConceptsPredictors of survivalBurkitt's lymphomaSurvival predictorsMultiple primariesAge groupsCox proportional hazards regression modelFive-year relative survivalProportional hazards regression modelsStage II diseaseStage IV diseaseEnd Results (SEER) databaseAfrican American raceHazards regression modelsBL patientsElderly patientsPrognostic factorsResults databaseWorse outcomesElderly groupStage IIIAmerican raceRelative survivalHigh mortalityLymphomaDiseaseAspirin Use and Reduced Risk of Pancreatic Cancer
Risch HA, Lu L, Streicher SA, Wang J, Zhang W, Ni Q, Kidd MS, Yu H, Gao YT. Aspirin Use and Reduced Risk of Pancreatic Cancer. Cancer Epidemiology Biomarkers & Prevention 2017, 26: 68-74. PMID: 27999143, PMCID: PMC5225096, DOI: 10.1158/1055-9965.epi-16-0508.Peer-Reviewed Original ResearchConceptsPancreatic cancerAspirin useRegular useConfidence intervalsLong-term aspirin useControl subjects frequencyLow-dose aspirinAvoidance of smokingBody mass indexPopulation-based studyUnconditional logistic regressionABO blood groupRisk-benefit analysisAspirin typeCagA seropositivityDiabetes mellitusMass indexCigarette smokingCardiovascular diseaseAspirinCancerCertain cancersLogistic regressionBlood groupSubjects frequency
2016
Long non-coding RNAs, ASAP1-IT1, FAM215A, and LINC00472, in epithelial ovarian cancer
Fu Y, Biglia N, Wang Z, Shen Y, Risch HA, Lu L, Canuto EM, Jia W, Katsaros D, Yu H. Long non-coding RNAs, ASAP1-IT1, FAM215A, and LINC00472, in epithelial ovarian cancer. Gynecologic Oncology 2016, 143: 642-649. PMID: 27667152, PMCID: PMC5507336, DOI: 10.1016/j.ygyno.2016.09.021.Peer-Reviewed Original ResearchMeSH KeywordsAdaptor Proteins, Signal TransducingAdenocarcinoma, Clear CellAdultAgedAged, 80 and overCarcinoma, EndometrioidCarcinoma, Ovarian EpithelialHumansMiddle AgedNeoplasm GradingNeoplasm StagingNeoplasms, Cystic, Mucinous, and SerousNeoplasms, Glandular and EpithelialOvarian NeoplasmsPrognosisProportional Hazards ModelsReverse Transcriptase Polymerase Chain ReactionRNA, Long NoncodingYoung AdultConceptsEpithelial ovarian cancerOvarian cancerStage diseasePatient survivalGrade tumorsASAP1-IT1Survival associationsLong non-coding RNAsCox proportional hazards regression modelPrimary epithelial ovarian cancerProportional hazards regression modelsTumor samplesFresh frozen tumor samplesHigh expressionEarly-stage diseaseFavorable overall survivalLate-stage diseaseHazards regression modelsLow-grade tumorsHigh-grade tumorsOvarian cancer progressionNon-coding RNAsImportant biological actionsOverall survivalPoor prognosisLIN-28B/let-7a/IGF-II axis molecular subtypes are associated with epithelial ovarian cancer prognosis
Lu L, Katsaros D, Canuto EM, Biglia N, Risch HA, Yu H. LIN-28B/let-7a/IGF-II axis molecular subtypes are associated with epithelial ovarian cancer prognosis. Gynecologic Oncology 2016, 141: 121-127. PMID: 26751131, DOI: 10.1016/j.ygyno.2015.12.035.Peer-Reviewed Original ResearchConceptsEpithelial ovarian cancer prognosisOvarian cancer prognosisMolecular subtypesCancer prognosisSurvival analysisMultivariate Cox regression modelKaplan-Meier survival curvesEpithelial ovarian cancer tissuesCox regression modelEpithelial ovarian cancerReduced relapse riskOvarian cancer tissuesIGF-II mRNAQuantitative reverse transcription PCRRelapse riskReverse transcription-PCROvarian cancerBetter survivalCancer tissuesLin-28BSurvival curvesClinical implicationsIGFPrognosisSubtypes
2015
Biological and Clinical Significance of MAD2L1 and BUB1, Genes Frequently Appearing in Expression Signatures for Breast Cancer Prognosis
Wang Z, Katsaros D, Shen Y, Fu Y, Canuto EM, Benedetto C, Lu L, Chu WM, Risch HA, Yu H. Biological and Clinical Significance of MAD2L1 and BUB1, Genes Frequently Appearing in Expression Signatures for Breast Cancer Prognosis. PLOS ONE 2015, 10: e0136246. PMID: 26287798, PMCID: PMC4546117, DOI: 10.1371/journal.pone.0136246.Peer-Reviewed Original ResearchConceptsBreast cancer prognosisCancer prognosisGene expression signaturesExpression signaturesPoor disease-free survivalDisease-free survivalBreast cancer patientsBreast cancer cell linesBreast cancer progressionMDA-MB-468Tumor cell growthMDA-MB-231Multiple gene expression signaturesCancer cell linesAggressive tumorsCancer patientsClinical significanceDisease outcomeTumor featuresClinical implicationsPrognosisCancer progressionBiologic relevanceHigh expressionCell proliferationPrognostic and predictive values of long non-coding RNA LINC00472 in breast cancer
Shen Y, Katsaros D, Loo LW, Hernandez BY, Chong C, Canuto EM, Biglia N, Lu L, Risch H, Chu WM, Yu H. Prognostic and predictive values of long non-coding RNA LINC00472 in breast cancer. Oncotarget 2015, 6: 8579-8592. PMID: 25865225, PMCID: PMC4496168, DOI: 10.18632/oncotarget.3287.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAntineoplastic Agents, HormonalBreast NeoplasmsCarcinomaCell DivisionCell Line, TumorCell MovementChemotherapy, AdjuvantDisease-Free SurvivalFemaleGene ExpressionGenes, Tumor SuppressorGenetic VectorsHumansMiddle AgedNeoplasm GradingNeoplasm StagingPrognosisRecurrenceRiskRNARNA, Long NoncodingRNA, NeoplasmTissue Array AnalysisTreatment OutcomeYoung AdultConceptsLINC00472 expressionBreast cancerPredictive valueBreast tumorsLow expressionBreast cancer cell proliferationFavorable molecular subtypesNormal-like tumorsFavorable disease outcomeAggressive breast tumorsRisk of relapseCell proliferationCancer cell proliferationBreast cancer cellsBreast tumor samplesAdjuvant chemoHormonal therapyLuminal AClinical managementDisease outcomeGene Expression Omnibus databaseMolecular subtypesLong non-coding RNALINC00472Tumor samplesMicroRNA let‐7a modifies the effect of self‐renewal gene HIWI on patient survival of epithelial ovarian cancer
Lu L, Katsaros D, Risch HA, Canuto EM, Biglia N, Yu H. MicroRNA let‐7a modifies the effect of self‐renewal gene HIWI on patient survival of epithelial ovarian cancer. Molecular Carcinogenesis 2015, 55: 357-365. PMID: 25630839, DOI: 10.1002/mc.22285.Peer-Reviewed Original ResearchConceptsEpithelial ovarian cancerKaplan-Meier survival curvesOverall survivalHIWI expressionLet-7a expressionPatient survivalLet-7aClinical relevanceMultivariate Cox proportional hazards regression analysisCox proportional hazards regression analysisCox proportional hazards regression modelSurvival curvesProportional hazards regression analysisProportional hazards regression modelsLow let-7aHazards regression analysisRisk of deathPoor overall survivalHazards regression modelsMiRNA let-7aPrimary EOC tissuesQuantitative reverse transcription PCRU-shape associationEOC prognosisPrognostic significancePrognostic value of INPP4B protein immunohistochemistry in ovarian cancer.
Salmena L, Shaw P, Fans I, McLaughlin, Rosen B, Risch H, Mitchell C, Sun P, Narod SA, Kotsopoulos J. Prognostic value of INPP4B protein immunohistochemistry in ovarian cancer. European Journal Of Gynaecological Oncology 2015, 36: 260-7. PMID: 26189250.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinoma, Clear CellAdultAgedBiomarkers, TumorCarcinoma, EndometrioidCarcinoma, Ovarian EpithelialFemaleHumansImmunohistochemistryMiddle AgedNeoplasm StagingNeoplasms, Cystic, Mucinous, and SerousNeoplasms, Glandular and EpithelialOvarian NeoplasmsPhosphoric Monoester HydrolasesPrognosisProportional Hazards ModelsPTEN PhosphohydrolaseTumor Suppressor Protein p53Young AdultConceptsAberrant p53 expressionOvarian cancerP53 expressionHazard ratioLoss of PTENOvarian tumorsOvarian cancer tissue samplesEndometrioid ovarian tumorsProtein expressionSurvival hazard ratioEpithelial ovarian tumorsPoor disease outcomePossible prognostic roleProportional hazards modelCancer tissue samplesPrognostic roleEndometrioid tumorsEndometrioid subtypePrognostic valuePoor prognosisSerous subtypeProtein immunohistochemistryDisease outcomeTissue microarrayHazards model
2014
Integrative post-genome-wide association analysis of CDKN2A and TP53 SNPs and risk of esophageal adenocarcinoma
Buas MF, Levine DM, Makar KW, Utsugi H, Onstad L, Li X, Galipeau PC, Shaheen NJ, Hardie LJ, Romero Y, Bernstein L, Gammon MD, Casson AG, Bird NC, Risch HA, Ye W, Liu G, Corley DA, Blount PL, Fitzgerald RC, Whiteman DC, Wu AH, Reid BJ, Vaughan TL. Integrative post-genome-wide association analysis of CDKN2A and TP53 SNPs and risk of esophageal adenocarcinoma. Carcinogenesis 2014, 35: 2740-2747. PMID: 25280564, PMCID: PMC4247522, DOI: 10.1093/carcin/bgu207.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinomaAgedBarrett EsophagusCase-Control StudiesCyclin-Dependent Kinase Inhibitor p16Disease ProgressionEsophageal NeoplasmsFemaleFollow-Up StudiesGenome-Wide Association StudyHumansMaleMiddle AgedNeoplasm StagingPolymorphism, Single NucleotidePrognosisRisk FactorsTumor Suppressor Protein p53ConceptsEsophageal adenocarcinomaBarrett's esophagusSingle nucleotide polymorphismsRisk of EACPredictors of progressionGermline single nucleotide polymorphismsTP53 single nucleotide polymorphismsNucleotide polymorphismsCDKN2A polymorphismsEA tumorsFrequent somatic mutationsProspective cohortCDKN2A variantsMale genderRisk factorsReduced riskTumor suppressor gene CDKN2ACaucasian raceMiR-663bEA casesSomatic alterationsGermline variationAdenocarcinomaGenes CDKN2AEsophagusIntrauterine devices and endometrial cancer risk: A pooled analysis of the Epidemiology of Endometrial Cancer Consortium
Felix AS, Gaudet MM, La Vecchia C, Nagle CM, Shu XO, Weiderpass E, Adami HO, Beresford S, Bernstein L, Chen C, Cook LS, De Vivo I, Doherty JA, Friedenreich CM, Gapstur SM, Hill D, Horn‐Ross P, Lacey JV, Levi F, Liang X, Lu L, Magliocco A, McCann SE, Negri E, Olson SH, Palmer JR, Patel AV, Petruzella S, Prescott J, Risch HA, Rosenberg L, Sherman ME, Spurdle AB, Webb PM, Wise LA, Xiang Y, Xu W, Yang HP, Yu H, Zeleniuch‐Jacquotte A, Brinton LA. Intrauterine devices and endometrial cancer risk: A pooled analysis of the Epidemiology of Endometrial Cancer Consortium. International Journal Of Cancer 2014, 136: e410-e422. PMID: 25242594, PMCID: PMC4267918, DOI: 10.1002/ijc.29229.Peer-Reviewed Original ResearchConceptsEndometrial Cancer ConsortiumEndometrial cancer riskIntrauterine deviceEC riskPooled analysisCancer riskLast useCancer ConsortiumOlder ageUse of IUDsMultivariable logistic regressionConfidence intervalsPooled odds ratioCase-control studyInert intrauterine deviceDuration of useHeavy bleedingOdds ratioReversible contraceptivesHormonal changesEC casesReduced riskBiologic effectsUterine environmentLogistic regressionRisk Factors for Ovarian Cancers With and Without Microsatellite Instability
Segev Y, Pal T, Rosen B, McLaughlin JR, Sellers TA, Risch HA, Zhang S, Sun P, Narod SA, Schildkraut J. Risk Factors for Ovarian Cancers With and Without Microsatellite Instability. International Journal Of Gynecological Cancer 2014, 24: 664-669. PMID: 24755492, DOI: 10.1097/igc.0000000000000134.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinoma, Clear CellAdenocarcinoma, MucinousBRCA1 ProteinBRCA2 ProteinBreast NeoplasmsCanadaCystadenocarcinoma, SerousDNA, NeoplasmEndometrial NeoplasmsFemaleGenetic Predisposition to DiseaseHumansMicrosatellite InstabilityMicrosatellite RepeatsMiddle AgedMutationNeoplasm StagingOvarian NeoplasmsPrognosisRisk FactorsSyndromeUnited StatesConceptsOvarian cancer patientsOral contraceptive useBody mass indexEpithelial ovarian cancerOvarian cancerCancer patientsHistologic subtypeMass indexTubal ligationRisk factorsBRCA2 mutationsContraceptive usePast oral contraceptive usePrimary epithelial ovarian cancerOvarian cancer risk factorsBRCA1 mutationsNational Cancer Institute criteriaProtective factorsSpecific histologic subtypesCancer risk factorsPopulation-based studyMSI-high cancersCases of cancerMSI-high tumorsBRCA2 mutation status
2013
Association between ultraviolet radiation, skin sun sensitivity and risk of pancreatic cancer
Tran B, Whiteman DC, Webb PM, Fritschi L, Fawcett J, Risch HA, Lucas R, Pandeya N, Schulte A, Neale RE, Group F. Association between ultraviolet radiation, skin sun sensitivity and risk of pancreatic cancer. Cancer Epidemiology 2013, 37: 886-892. PMID: 24075798, DOI: 10.1016/j.canep.2013.08.013.Peer-Reviewed Original ResearchConceptsHigh ambient ultraviolet radiationPancreatic cancerAmbient ultraviolet radiationLower riskAustralian case-control studyPancreatic cancer incidenceSkin sun sensitivityCase-control studyMarkers of exposureFair skin colorCancer incidenceInverse associationSkin lesionsSun exposureLesion treatmentSun sensitivityCancerLight skin colorSkin typeSkin colorDark skin colorUltraviolet radiationIndividual-level studiesSkin lesion treatmentRiskGenital Powder Use and Risk of Ovarian Cancer: A Pooled Analysis of 8,525 Cases and 9,859 Controls
Terry KL, Karageorgi S, Shvetsov YB, Merritt MA, Lurie G, Thompson PJ, Carney ME, Weber RP, Akushevich L, Lo-Ciganic WH, Cushing-Haugen K, Sieh W, Moysich K, Doherty JA, Nagle CM, Berchuck A, Pearce CL, Pike M, Ness RB, Webb PM, Study A, Rossing M, Schildkraut J, Risch H, Goodman M. Genital Powder Use and Risk of Ovarian Cancer: A Pooled Analysis of 8,525 Cases and 9,859 Controls. Cancer Prevention Research 2013, 6: 811-821. PMID: 23761272, PMCID: PMC3766843, DOI: 10.1158/1940-6207.capr-13-0037.Peer-Reviewed Original ResearchMeSH KeywordsCase-Control StudiesFemaleHumansMiddle AgedOdds RatioOvarian NeoplasmsPowdersPrognosisTalcConceptsEpithelial ovarian cancerOvarian cancerPowder usePopulation-based case-control studyMost histologic subtypesEpithelial ovarian cancer riskBorderline serous tumorsOvarian cancer riskCase-control studySubtype-specific riskConditional logistic regressionHistologic subtypeHistologic typeSerous tumorsPotential confoundersPooled analysisPooled ORsModifiable exposuresCancer riskTumor behaviorEpidemiologic investigationsCancerLogistic regressionLifetime numberCarcinogenic effectsRisk Factors for Ovarian Cancers With and Without Microsatellite Instability
Segev Y, Pal T, Rosen B, McLaughlin JR, Sellers TA, Risch HA, Zhang S, Ping S, Narod SA, Schildkraut J. Risk Factors for Ovarian Cancers With and Without Microsatellite Instability. International Journal Of Gynecological Cancer 2013, 23: 1010. PMID: 23748177, PMCID: PMC3740723, DOI: 10.1097/igc.0b013e31829a5527.Peer-Reviewed Original ResearchConceptsOvarian cancer patientsOral contraceptive useBody mass indexEpithelial ovarian cancerOvarian cancerCancer patientsHistologic subtypeMass indexHistologic findingsTubal ligationRisk factorsContraceptive usePast oral contraceptive usePrimary epithelial ovarian cancerOvarian cancer risk factorsBRCA1 mutationsNational Cancer Institute criteriaProtective factorsDifferent histologic findingsSpecific histologic subtypesCancer risk factorsPopulation-based studyMSI-high cancersMSI-high tumorsBRCA2 mutation statusPolymorphisms in Inflammation Pathway Genes and Endometrial Cancer Risk
Delahanty RJ, Xiang YB, Spurdle A, Beeghly-Fadiel A, Long J, Thompson D, Tomlinson I, Yu H, Lambrechts D, Dörk T, Goodman MT, Zheng Y, Salvesen HB, Bao PP, Amant F, Beckmann MW, Coenegrachts L, Coosemans A, Dubrowinskaja N, Dunning A, Runnebaum IB, Easton D, Ekici AB, Fasching PA, Halle MK, Hein A, Howarth K, Gorman M, Kaydarova D, Krakstad C, Lose F, Lu L, Lurie G, O'Mara T, Matsuno RK, Pharoah P, Risch H, Corssen M, Trovik J, Turmanov N, Wen W, Lu W, Cai Q, Zheng W, Shu XO. Polymorphisms in Inflammation Pathway Genes and Endometrial Cancer Risk. Cancer Epidemiology Biomarkers & Prevention 2013, 22: 216-223. PMID: 23221126, PMCID: PMC3677562, DOI: 10.1158/1055-9965.epi-12-0903.Peer-Reviewed Original ResearchMeSH KeywordsAsian PeopleBiomarkers, TumorCase-Control StudiesChinaEndometrial NeoplasmsFemaleFollow-Up StudiesGene Expression ProfilingGenetic Predisposition to DiseaseHumansInflammationLinkage DisequilibriumMiddle AgedNeoplasm StagingOligonucleotide Array Sequence AnalysisPolymorphism, Single NucleotidePrognosisRisk FactorsConceptsEndometrial cancer riskEndometrial cancer casesEndometrial cancerSingle nucleotide polymorphismsOdds ratioCancer casesEndometrial carcinogenesisCancer riskStage IConfidence intervalsInflammation pathway genesInflammatory pathway genesAllelic odds ratioChronic inflammationEpidemiologic evidenceInflammatory pathwaysPathway genesSignificant associationStage IIGenetic susceptibilityMMP9 polymorphismsAdditional studiesCancerGenetic polymorphismsFollow-up genotyping