Featured Publications
Exploiting Gene-Environment Independence for Analysis of Case–Control Studies: An Empirical Bayes-Type Shrinkage Estimator to Trade-Off Between Bias and Efficiency
Mukherjee B, Chatterjee N. Exploiting Gene-Environment Independence for Analysis of Case–Control Studies: An Empirical Bayes-Type Shrinkage Estimator to Trade-Off Between Bias and Efficiency. Biometrics 2007, 64: 685-694. PMID: 18162111, DOI: 10.1111/j.1541-0420.2007.00953.x.Peer-Reviewed Original ResearchConceptsGene-environment independenceShrinkage estimatorsLog odds ratio parametersCase-control dataGene-environment independence assumptionOdds ratio parametersCase-control estimatorsData-adaptive fashionData exampleProspective logistic regression analysisBinary exposureGene-environment associationsIndependence assumptionLogistic regression analysisCase-onlyMaximum likelihood frameworkEstimationSample sizeBinary genesRegression analysisChatterjeeExamplesWeighted averageAssumptions
2023
COVID-19 outcomes by cancer status, site, treatment, and vaccination
Salvatore M, Hu M, Beesley L, Mondul A, Pearce C, Friese C, Fritsche L, Mukherjee B. COVID-19 outcomes by cancer status, site, treatment, and vaccination. Cancer Epidemiology Biomarkers & Prevention 2023, 32: 748-759. PMID: 36626383, DOI: 10.1158/1055-9965.epi-22-0607.Peer-Reviewed Original ResearchMeSH KeywordsColorectal NeoplasmsCOVID-19Hematologic NeoplasmsHospitalizationHumansKidney NeoplasmsLung NeoplasmsRetrospective StudiesSARS-CoV-2VaccinationConceptsCOVID-19 outcomesCancer statusCancer diagnosisAssociated with higher ratesElectronic health record dataHealth record dataColorectal cancerIncreased riskAcademic medical centerKidney cancerCancer-free patientsIntensive care unit admissionCancer sitesAssociated with lower ratesChemotherapy receiptHigher ratesCOVID-19 precautionsRecord dataCOVID-19Logistic regressionMedical CenterUnit admissionRetrospective cohortVaccination statusLung cancer
2018
Novel Common Genetic Susceptibility Loci for Colorectal Cancer
Schmit SL, Edlund CK, Schumacher FR, Gong J, Harrison TA, Huyghe JR, Qu C, Melas M, Van Den Berg DJ, Wang H, Tring S, Plummer SJ, Albanes D, Alonso MH, Amos CI, Anton K, Aragaki AK, Arndt V, Barry EL, Berndt SI, Bezieau S, Bien S, Bloomer A, Boehm J, Boutron-Ruault MC, Brenner H, Brezina S, Buchanan DD, Butterbach K, Caan BJ, Campbell PT, Carlson CS, Castelao JE, Chan AT, Chang-Claude J, Chanock SJ, Cheng I, Cheng YW, Chin LS, Church JM, Church T, Coetzee GA, Cotterchio M, Correa M, Curtis KR, Duggan D, Easton DF, English D, Feskens EJM, Fischer R, FitzGerald LM, Fortini BK, Fritsche LG, Fuchs CS, Gago-Dominguez M, Gala M, Gallinger SJ, Gauderman WJ, Giles GG, Giovannucci EL, Gogarten SM, Gonzalez-Villalpando C, Gonzalez-Villalpando EM, Grady WM, Greenson JK, Gsur A, Gunter M, Haiman CA, Hampe J, Harlid S, Harju JF, Hayes RB, Hofer P, Hoffmeister M, Hopper JL, Huang SC, Huerta JM, Hudson TJ, Hunter DJ, Idos GE, Iwasaki M, Jackson RD, Jacobs EJ, Jee SH, Jenkins MA, Jia WH, Jiao S, Joshi AD, Kolonel LN, Kono S, Kooperberg C, Krogh V, Kuehn T, Küry S, LaCroix A, Laurie CA, Lejbkowicz F, Lemire M, Lenz HJ, Levine D, Li CI, Li L, Lieb W, Lin Y, Lindor NM, Liu YR, Loupakis F, Lu Y, Luh F, Ma J, Mancao C, Manion FJ, Markowitz SD, Martin V, Matsuda K, Matsuo K, McDonnell KJ, McNeil CE, Milne R, Molina AJ, Mukherjee B, Murphy N, Newcomb PA, Offit K, Omichessan H, Palli D, Cotoré JPP, Pérez-Mayoral J, Pharoah PD, Potter JD, Qu C, Raskin L, Rennert G, Rennert HS, Riggs BM, Schafmayer C, Schoen RE, Sellers TA, Seminara D, Severi G, Shi W, Shibata D, Shu XO, Siegel EM, Slattery ML, Southey M, Stadler ZK, Stern MC, Stintzing S, Taverna D, Thibodeau SN, Thomas DC, Trichopoulou A, Tsugane S, Ulrich CM, van Duijnhoven FJB, van Guelpan B, Vijai J, Virtamo J, Weinstein SJ, White E, Win AK, Wolk A, Woods M, Wu AH, Wu K, Xiang YB, Yen Y, Zanke BW, Zeng YX, Zhang B, Zubair N, Kweon SS, Figueiredo JC, Zheng W, Le Marchand L, Lindblom A, Moreno V, Peters U, Casey G, Hsu L, Conti DV, Gruber SB. Novel Common Genetic Susceptibility Loci for Colorectal Cancer. Journal Of The National Cancer Institute 2018, 111: 146-157. PMID: 29917119, PMCID: PMC6555904, DOI: 10.1093/jnci/djy099.Peer-Reviewed Original Research
2016
Identification of Susceptibility Loci and Genes for Colorectal Cancer Risk
Zeng C, Matsuda K, Jia W, Chang J, Kweon S, Xiang Y, Shin A, Jee S, Kim D, Zhang B, Cai Q, Guo X, Long J, Wang N, Courtney R, Pan Z, Wu C, Takahashi A, Shin M, Matsuo K, Matsuda F, Gao Y, Oh J, Kim S, Jung K, Ahn Y, Ren Z, Li H, Wu J, Shi J, Wen W, Yang G, Li B, Ji B, Brenner H, Schoen R, Küry S, Gruber S, Schumacher F, Stenzel S, Casey G, Hopper J, Jenkins M, Kim H, Jeong J, Park J, Tajima K, Cho S, Kubo M, Shu X, Lin Y, Zeng Y, Zheng W, Baron J, Berndt S, Bezieau S, Brenner H, Caan B, Carlson C, Casey G, Chan A, Chang-Claude J, Chanock S, Conti D, Curtis K, Duggan D, Fuchs C, Gallinger S, Giovannucci E, Gruber S, Haile R, Harrison T, Hayes R, Hoffmeister M, Hopper J, Hsu L, Hudson T, Hunter D, Hutter C, Jackson R, Jenkins M, Jiao S, Küry S, Le Marchand L, Lemire M, Lindor N, Ma J, Newcomb P, Peters U, Potter J, Qu C, Schoen R, Schumacher F, Seminara D, Slattery M, Thibodeau S, White E, Zanke B, Blalock K, Campbell P, Casey G, Conti D, Edlund C, Figueiredo J, Gauderman W, Gong J, Green R, Gruber S, Harju J, Harrison T, Jacobs E, Jenkins M, Jiao S, Li L, Lin D, Manion F, Moreno V, Mukherjee B, Peters U, Raskin L, Schumacher F, Seminara D, Severi G, Stenzel S, Thomas D. Identification of Susceptibility Loci and Genes for Colorectal Cancer Risk. Gastroenterology 2016, 150: 1633-1645. PMID: 26965516, PMCID: PMC4909543, DOI: 10.1053/j.gastro.2016.02.076.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAsian PeopleBasic Helix-Loop-Helix Leucine Zipper Transcription FactorsCase-Control StudiesColorectal NeoplasmsEukaryotic Initiation Factor-3FemaleGenetic LociGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleMiddle AgedPolymorphism, Single NucleotideQb-SNARE ProteinsRibosomal ProteinsRisk FactorsSteroid 17-alpha-HydroxylaseSuppressor of Cytokine Signaling ProteinsYoung AdultConceptsEukaryotic translation initiation factor 3Translation initiation factor 3Ribosomal protein S2Initiation factor 3Transcription factor EBSOCS boxProtein S2Risk variantsReceptor domainSusceptibility lociProtein-coding genesGenome-wide association studiesFactor 3East Asian ancestryNearby genesEpigenomic databasesGenetic variationRisk lociGene expressionAutophagy pathwayAssociation studiesProtein synthesisLociGenesSignificant variantsMicrosatellite Alterations With Allelic Loss at 9p24.2 Signify Less-Aggressive Colorectal Cancer Metastasis
Koi M, Garcia M, Choi C, Kim H, Koike J, Hemmi H, Nagasaka T, Okugawa Y, Toiyama Y, Kitajima T, Imaoka H, Kusunoki M, Chen Y, Mukherjee B, Boland C, Carethers J. Microsatellite Alterations With Allelic Loss at 9p24.2 Signify Less-Aggressive Colorectal Cancer Metastasis. Gastroenterology 2016, 150: 944-955. PMID: 26752111, PMCID: PMC4808397, DOI: 10.1053/j.gastro.2015.12.032.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorChi-Square DistributionChromosome AberrationsChromosomes, Human, Pair 9Colorectal NeoplasmsDisease ProgressionDisease-Free SurvivalFemaleGenetic Predisposition to DiseaseHumansJapanKaplan-Meier EstimateLiver NeoplasmsLogistic ModelsLoss of HeterozygosityMaleMicrosatellite RepeatsMiddle AgedNeoplasm Recurrence, LocalNeoplasm StagingOdds RatioPhenotypeProportional Hazards ModelsProto-Oncogene Proteins B-rafProto-Oncogene Proteins p21(ras)Republic of KoreaRisk FactorsTime FactorsTreatment OutcomeConceptsPrimary colorectal tumorsLoss of heterozygosityLiver metastasesColorectal cancerColorectal tumorsElevated microsatellite alterationsMicrosatellite alterationsStage IICurative treatment of patientsStage III colorectal cancerOverall survival of patientsSurvival of patientsIII colorectal cancerTumor to liverColorectal cancer recurrenceTreatment of patientsMatched liver metastasesCancer cell nucleiMatched metastasesDisease recurrenceOverall survivalPrognostic factorsAllelic lossNo significant differenceCurative treatment
2015
Genome-wide association study of colorectal cancer identifies six new susceptibility loci
Schumacher FR, Schmit SL, Jiao S, Edlund CK, Wang H, Zhang B, Hsu L, Huang SC, Fischer CP, Harju JF, Idos GE, Lejbkowicz F, Manion FJ, McDonnell K, McNeil CE, Melas M, Rennert HS, Shi W, Thomas DC, Van Den Berg DJ, Hutter CM, Aragaki AK, Butterbach K, Caan BJ, Carlson CS, Chanock SJ, Curtis KR, Fuchs CS, Gala M, Giovannucci EL, Gogarten SM, Hayes RB, Henderson B, Hunter DJ, Jackson RD, Kolonel LN, Kooperberg C, Küry S, LaCroix A, Laurie CC, Laurie CA, Lemire M, Levine D, Ma J, Makar KW, Qu C, Taverna D, Ulrich CM, Wu K, Kono S, West DW, Berndt SI, Bezieau S, Brenner H, Campbell PT, Chan AT, Chang-Claude J, Coetzee GA, Conti DV, Duggan D, Figueiredo JC, Fortini BK, Gallinger SJ, Gauderman WJ, Giles G, Green R, Haile R, Harrison TA, Hoffmeister M, Hopper JL, Hudson TJ, Jacobs E, Iwasaki M, Jee SH, Jenkins M, Jia WH, Joshi A, Li L, Lindor NM, Matsuo K, Moreno V, Mukherjee B, Newcomb PA, Potter JD, Raskin L, Rennert G, Rosse S, Severi G, Schoen RE, Seminara D, Shu XO, Slattery ML, Tsugane S, White E, Xiang YB, Zanke BW, Zheng W, Le Marchand L, Casey G, Gruber SB, Peters U. Genome-wide association study of colorectal cancer identifies six new susceptibility loci. Nature Communications 2015, 6: 7138. PMID: 26151821, PMCID: PMC4967357, DOI: 10.1038/ncomms8138.Peer-Reviewed Original ResearchMeSH KeywordsCase-Control StudiesColorectal NeoplasmsGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansOdds RatioPolymorphism, Single NucleotideConceptsNew susceptibility lociAssociation studiesSusceptibility lociSignificant genetic lociGenome-wide association studiesGenome-wide thresholdCommon genetic variantsRare pathogenic mutationsTwo-stage association studyGenetic lociGenetic epidemiology studiesGenetic variantsLociUnderlying biological mechanismsPathogenic mutationsBiological mechanismsAsian ConsortiumGenetic susceptibilityMutationsAdditional insightColorectal cancerCancerVariants
2012
On the equivalence of posterior inference based on retrospective and prospective likelihoods: application to a case‐control study of colorectal cancer
Ghosh M, Song J, Forster J, Mitra R, Mukherjee B. On the equivalence of posterior inference based on retrospective and prospective likelihoods: application to a case‐control study of colorectal cancer. Statistics In Medicine 2012, 31: 2196-2208. PMID: 22495822, DOI: 10.1002/sim.5358.Peer-Reviewed Original ResearchConceptsPosterior inferenceCase-control study of colorectal cancerOdds ratio parametersCategorical response dataBayesian analysis of dataStudy of colorectal cancerCase-control studyGeneral classProspective likelihoodSimulation studyCategorical responsesBayesian analysisColorectal cancerMatched case-control studyInferenceAnalysis of dataResponse dataPriorsRetrospective designRetrospective modelEquivalenceLikelihood‐based methods for regression analysis with binary exposure status assessed by pooling
Lyles R, Tang L, Lin J, Zhang Z, Mukherjee B. Likelihood‐based methods for regression analysis with binary exposure status assessed by pooling. Statistics In Medicine 2012, 31: 2485-2497. PMID: 22415630, PMCID: PMC3528351, DOI: 10.1002/sim.4426.Peer-Reviewed Original ResearchConceptsPopulation-based case-control study of colorectal cancerCase-control study of colorectal cancerPopulation-based case-control studyStudy of colorectal cancerExposure statusBinary outcomesRegression modelsCase-control sampleLogistic regression modelsGene-disease associationsObserved binary outcomeStudy designEpidemiological studiesColorectal cancerAssess exposureMaximum likelihood analysisRegression analysisLikelihood-based methodsExposure assessmentMaximum likelihood approachLikelihood approachCross-sectionSimulation studyOutcomesLikelihood analysis
2011
Logistic regression analysis of biomarker data subject to pooling and dichotomization
Zhang Z, Liu A, Lyles R, Mukherjee B. Logistic regression analysis of biomarker data subject to pooling and dichotomization. Statistics In Medicine 2011, 31: 2473-2484. PMID: 21953741, DOI: 10.1002/sim.4367.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkersColorectal NeoplasmsComputer SimulationData Interpretation, StatisticalHumansLogistic ModelsPolymorphism, Single NucleotideProspective StudiesConceptsPopulation-based case-control study of colorectal cancerCase-control study of colorectal cancerProspective logistic regression modelPopulation-based case-control studyStudy of colorectal cancerEpidemiological studiesLogistic regression modelsAnalysis of epidemiological dataLogistic regression analysisBinary exposurePooled measureColorectal cancerRegression modelsEpidemiological dataRegression analysisAnalysis of biomarker dataDisease statusExposed subjectsBiomarker dataChoice of designSubjectsEstimated parametersStatusRecommendationsMRE11 Deficiency Increases Sensitivity to Poly(ADP-ribose) Polymerase Inhibition in Microsatellite Unstable Colorectal Cancers
Vilar E, Bartnik C, Stenzel S, Raskin L, Ahn J, Moreno V, Mukherjee B, Iniesta M, Morgan M, Rennert G, Gruber S. MRE11 Deficiency Increases Sensitivity to Poly(ADP-ribose) Polymerase Inhibition in Microsatellite Unstable Colorectal Cancers. Cancer Research 2011, 71: 2632-2642. PMID: 21300766, PMCID: PMC3407272, DOI: 10.1158/0008-5472.can-10-1120.Peer-Reviewed Original ResearchMeSH KeywordsAcid Anhydride HydrolasesBenzimidazolesCell Line, TumorColorectal NeoplasmsDNA DamageDNA Repair EnzymesDNA-Binding ProteinsEnzyme InhibitorsGene Expression ProfilingGene Expression Regulation, NeoplasticGene Knockdown TechniquesHumansMicrosatellite InstabilityMRE11 Homologue ProteinMutationPoly (ADP-Ribose) Polymerase-1Poly(ADP-ribose) Polymerase InhibitorsPoly(ADP-ribose) PolymerasesRad51 RecombinaseRecombination, GeneticConceptsPoly(ADP-riboseDouble strand breaksColorectal cancer cell linesPARP-1 inhibitionCell linesPARP-1ABT-888PARP-1 inhibitorsColorectal cancerPoly(ADP-ribose) polymeraseRepetitive DNA sequencesWild-type cell linesMSI cell linesMicrosatellite instabilityConcept of synthetic lethalityMicrosatellite instability colorectal tumorsSensitivity to poly(ADP-riboseMutant Mre11Short hairpin RNAPoly(ADP-ribose) polymerase inhibitionDNA sequencesDNA mismatch repairCell line modelsSecondary to mutationsSynthetic lethality
2010
Risk of colorectal cancer in self‐reported inflammatory bowel disease and modification of risk by statin and NSAID use
Samadder N, Mukherjee B, Huang S, Ahn J, Rennert H, Greenson J, Rennert G, Gruber S. Risk of colorectal cancer in self‐reported inflammatory bowel disease and modification of risk by statin and NSAID use. Cancer 2010, 117: 1640-1648. PMID: 21472711, PMCID: PMC3117060, DOI: 10.1002/cncr.25731.Peer-Reviewed Original ResearchConceptsRisk of colorectal cancerAssociated with reduced risk of colorectal cancerHistory of inflammatory bowel diseaseRisk of inflammatory bowel diseaseAssociated with reduced riskLong-term statin useColorectal cancerMolecular Epidemiology of Colorectal Cancer studyPersonal history of inflammatory bowel diseaseIncreased risk of CRCReduced risk of colorectal cancerRelative riskIBD-associated colorectal cancerIncident colorectal cancerNonsteroidal anti-inflammatory drugsUnconditional logistic regressionNonsteroidal anti-inflammatory drug useStatin useModification of riskReduced riskInflammatory bowel diseaseColorectal cancer studyIn-person interviewsNon-IBD colorectal cancersCase-control studyMissing Exposure Data in Stereotype Regression Model: Application to Matched Case–Control Study with Disease Subclassification
Ahn J, Mukherjee B, Gruber S, Sinha S. Missing Exposure Data in Stereotype Regression Model: Application to Matched Case–Control Study with Disease Subclassification. Biometrics 2010, 67: 546-558. PMID: 20560931, PMCID: PMC3119773, DOI: 10.1111/j.1541-0420.2010.01453.x.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBayes TheoremBiometryCase-Control StudiesClassificationColorectal NeoplasmsComputer SimulationHumansRegression AnalysisConceptsStereotype regression modelSubtypes of casesDeletion of observationsExpectation/conditional maximization algorithmBaseline category logit modelEstimation of model parametersMissingness mechanismData mechanismCase-control dataProportional oddsBayesian approachCategorical responsesCase-control studyCase-control study of colorectal cancerMissingnessMaximization algorithmCategorical outcomesMonte CarloModel assumptionsRegression modelsStudy of colorectal cancerModel parametersNonidentifiabilityDisease subclassificationMultinomial logit model
2009
Case–Control Studies of Gene–Environment Interaction: Bayesian Design and Analysis
Mukherjee B, Ahn J, Gruber S, Ghosh M, Chatterjee N. Case–Control Studies of Gene–Environment Interaction: Bayesian Design and Analysis. Biometrics 2009, 66: 934-948. PMID: 19930190, PMCID: PMC3103064, DOI: 10.1111/j.1541-0420.2009.01357.x.Peer-Reviewed Original ResearchConceptsGene-environment interactionsCase-control study of colorectal cancerStudy of gene-environment interactionsStudy of colorectal cancerGene-environment independenceRed meat consumptionBayesian designCase-control studyBayesian approachSample size determination criteriaCase-controlEpidemiological studiesColorectal cancerFrequentist counterpartsNatural wayMeat consumptionAnalyze current dataHypothesis testingDetermination criteriaSmokingEpidemiological exposureAnalysis strategyStudyGene Expression Patterns in Mismatch Repair-Deficient Colorectal Cancers Highlight the Potential Therapeutic Role of Inhibitors of the Phosphatidylinositol 3-Kinase-AKT-Mammalian Target of Rapamycin Pathway
Vilar E, Mukherjee B, Kuick R, Raskin L, Misek D, Taylor J, Giordano T, Hanash S, Fearon E, Rennert G, Gruber S. Gene Expression Patterns in Mismatch Repair-Deficient Colorectal Cancers Highlight the Potential Therapeutic Role of Inhibitors of the Phosphatidylinositol 3-Kinase-AKT-Mammalian Target of Rapamycin Pathway. Clinical Cancer Research 2009, 15: 2829-2839. PMID: 19351759, PMCID: PMC3425357, DOI: 10.1158/1078-0432.ccr-08-2432.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAntineoplastic AgentsBenzoquinonesCell CycleCell Line, TumorChromonesColorectal NeoplasmsComputational BiologyDNA Mismatch RepairDrug Evaluation, PreclinicalEnzyme InhibitorsGene Expression ProfilingHumansHydroxamic AcidsImmunosuppressive AgentsLactams, MacrocyclicMicrosatellite InstabilityMorpholinesPhosphoinositide-3 Kinase InhibitorsProto-Oncogene Proteins c-aktSirolimusConceptsGene expression informationColorectal cancerCell linesExpression informationGene expression dataSystems biology toolsLY-294002Gene expression patternsLow molecular weight compoundsPhosphatidylinositol 3-kinase-Akt-mammalian target of rapamycin pathwayMutant cellsBioinformatics approachTarget of rapamycin pathwayExpression dataMismatch repair-deficient colorectal cancerMolecular weight compoundsGroup of patientsCell cycleBiology toolsApoptosis effectExpression patternsPotential therapeutic roleTrichostatin AMSI-HWeight compounds
2008
Adenoma-infiltrating Lymphocytes (AILs) are a Potential Marker of Hereditary Nonpolyposis Colorectal Cancer
Polydorides A, Mukherjee B, Gruber S, McKenna B, Appelman H, Greenson J. Adenoma-infiltrating Lymphocytes (AILs) are a Potential Marker of Hereditary Nonpolyposis Colorectal Cancer. The American Journal Of Surgical Pathology 2008, 32: 1661-1666. PMID: 18753941, PMCID: PMC3500084, DOI: 10.1097/pas.0b013e31816ffa80.Peer-Reviewed Original ResearchConceptsHereditary nonpolyposis colorectal cancer syndromeColorectal adenomasControl adenomasHereditary nonpolyposis colorectal cancer patientsColorectal cancer syndromePresence of high-grade dysplasiaTumor-infiltrating lymphocytesHigh-grade dysplasiaPresence of necrosisNumbers of mitotic figuresColorectal cancer patientsHost immune responseVillous componentCancer syndromesLack of dirty necrosisSerrated architectureMicrosatellite-unstable colorectal cancersPatient ageGeneral populationPoor differentiationDirty necrosisInexpensive markerHistological featuresColorectal cancerAdenomas