2025
Temporal Trends in Opioid Use and Associated Outcomes for Patients Living with Advanced Cancer
Jairam V, Lindsay M, Soulos P, Gross C, Prsic E, Baum L, Park H. Temporal Trends in Opioid Use and Associated Outcomes for Patients Living with Advanced Cancer. Journal Of Pain And Symptom Management 2025 PMID: 40403779, DOI: 10.1016/j.jpainsymman.2025.05.007.Peer-Reviewed Original ResearchPain-related ED visitsOpioid useGabapentinoid useOpioid-related encountersAdvanced cancerOpioid prescribingED visitsAdvanced solid tumor cancersEnd Results (SEER)-Medicare databaseHigh-risk opioid useNonopioid pain medicationsMultivariate logistic regression modelNon-cancer patientsSolid tumor cancersPain controlPain medicationInvestigate time trendsIndex dateLogistic regression modelsCancer cohortOpioidNoncancer patientsOpioid epidemicPatientsNoncancer cohortPhysical activity and mortality in melanoma patients within the Norwegian Women and Cancer study (NOWAC)
Perrier F, Ahimbisibwe A, Ghiasvand R, Rueegg C, Green A, Borch K, Braaten T, Weiderpass E, Valberg M, Robsahm T, Veierød M. Physical activity and mortality in melanoma patients within the Norwegian Women and Cancer study (NOWAC). International Journal Of Cancer 2025 PMID: 40181554, DOI: 10.1002/ijc.35430.Peer-Reviewed Original ResearchPre-diagnosis PAPre-DiagnosisPA levelsPhysical activityNorwegian womenPost-diagnosis physical activityCancer Registry of NorwayPopulation-based Norwegian WomenPost-diagnosis PAMelanoma-specific mortalityMiddle-aged Norwegian womenAssociated with lower riskOverall mortalityRegion of residenceTrajectory classesAssociated with decreased mortalityLatent class mixed modelsCancer RegistryOther causesSmoking statusDecreased riskSummary stageMelanoma diagnosisCancer studiesCancer cohort
2024
Harnessing TME depicted by histological images to improve cancer prognosis through a deep learning system
Gao R, Yuan X, Ma Y, Wei T, Johnston L, Shao Y, Lv W, Zhu T, Zhang Y, Zheng J, Chen G, Sun J, Wang Y, Yu Z. Harnessing TME depicted by histological images to improve cancer prognosis through a deep learning system. Cell Reports Medicine 2024, 5: 101536. PMID: 38697103, PMCID: PMC11149411, DOI: 10.1016/j.xcrm.2024.101536.Peer-Reviewed Original ResearchColorectal cancer cohortTumor microenvironmentCancer prognosisCancer cohortCancer Genome Atlas-Breast CancerAssociated with cancer prognosisImprove cancer prognosisPrognosis prediction modelBreast cancerConcordance indexClinical availabilitySurvival modelsSpatial transcriptomicsST expressionCancer typesPrognosisCancerSurvivalHistological images
2023
Anti-TIGIT Antibody Tiragolumab Alone or With Atezolizumab in Patients With Advanced Solid Tumors
Kim T, Bedard P, LoRusso P, Gordon M, Bendell J, Oh D, Ahn M, Garralda E, D’Angelo S, Desai J, Hodi F, Wainberg Z, Delord J, Cassier P, Cervantes A, Gil-Martin M, Wu B, Patil N, Jin Y, Hoang T, Mendus D, Wen X, Meng R, Cho B. Anti-TIGIT Antibody Tiragolumab Alone or With Atezolizumab in Patients With Advanced Solid Tumors. JAMA Oncology 2023, 9: 1574-1582. PMID: 37768658, PMCID: PMC10540058, DOI: 10.1001/jamaoncol.2023.3867.Peer-Reviewed Original ResearchConceptsObjective response rateAdvanced solid tumorsAdverse eventsPhase 1bAntitumor activityCancer cohortNon-small cell lung cancer (NSCLC) cohortFrequent treatment-related adverse eventsInvestigator-assessed objective response rateSolid tumorsCell lung cancer cohortTreatment-related adverse eventsMajority of AEsEnd pointClinical cutoff dateDose-escalation cohortsDose-expansion cohortsEsophageal cancer cohortPhase 2 dosePrior cancer therapyPrimary end pointSecondary end pointsHalf of patientsNew safety signalsAntitumor immune responseRelative Burden of Cancer and Noncancer Mortality Among Long-Term Survivors of Breast, Prostate, and Colorectal Cancer in the US
Kc M, Fan J, Hyslop T, Hassan S, Cecchini M, Wang S, Silber A, Leapman M, Leeds I, Wheeler S, Spees L, Gross C, Lustberg M, Greenup R, Justice A, Oeffinger K, Dinan M. Relative Burden of Cancer and Noncancer Mortality Among Long-Term Survivors of Breast, Prostate, and Colorectal Cancer in the US. JAMA Network Open 2023, 6: e2323115. PMID: 37436746, PMCID: PMC10339147, DOI: 10.1001/jamanetworkopen.2023.23115.Peer-Reviewed Original ResearchConceptsLong-term survivorsCancer-specific mortalityColorectal cancerCancer cohortReceptor statusInitial diagnosisGleason scoreProstate cancerBreast cancerLong-term adult survivorsMedian cancer-specific survivalEnd Results cancer registryProstate-specific antigen levelRectal cancer cohortCancer-specific survivalStage III diseaseYear of diagnosisProgesterone receptor statusEstrogen receptor statusProportion of deathsSurvival time ratioEarly-stage cancerNononcologic outcomesIndex cancerLocalized diseaseLung Cancer Screening Penetration in an Urban Underserved County
Lee K, Haramati L, Ye K, Lin J, Mardakhaev E, Gohari A. Lung Cancer Screening Penetration in an Urban Underserved County. Lung 2023, 201: 243-249. PMID: 36892635, DOI: 10.1007/s00408-023-00609-7.Peer-Reviewed Original ResearchConceptsLung cancer screening programsCancer screening programsRace/ethnicityLung cancerScreening programSocioeconomic statusMethodsThis retrospective cohort studyRetrospective cohort studyInstitutional review board approvalLung cancer screeningUrban medical centerReview board approvalSignificant differencesTwo-sample t-testLower SES neighborhoodsCohort studyMore patientsHispanic patientsCancer screeningCancer cohortUnderserved countiesInclusion criteriaMedical CenterBoard approvalPatients
2022
Social Support, social ties, and cognitive function of women with breast cancer: findings from the Women’s Health Initiative (WHI) Life and Longevity After Cancer (LILAC) Study
Yang Y, McLaughlin E, Naughton M, Lustberg M, Nolan T, Kroenke C, Weitlauf J, Saquib N, Shadyab A, Follis S, Pan K, Paskett E. Social Support, social ties, and cognitive function of women with breast cancer: findings from the Women’s Health Initiative (WHI) Life and Longevity After Cancer (LILAC) Study. Supportive Care In Cancer 2022, 31: 48. PMID: 36525119, PMCID: PMC9758078, DOI: 10.1007/s00520-022-07505-5.Peer-Reviewed Original ResearchConceptsWomen's Health Initiative (WHI) LifeBreast cancerMedian cognitive scoresCognitive functionCognitive scoresBreast cancer stage IMedical Outcomes Study Social Support SurveySocial supportCognitive functioningCancer stage IHigher social support scoresSocial Support SurveyMultivariable quantile regressionHigher cognitive functioningNon-Hispanic whitesSelf-reported cognitive functioningSocial support scoresMajority of participantsBaseline questionnaireCancer cohortHigh riskMethodsThe studyKruskal-Wallis testStage IHigh social supportThe Prostate Cancer Androgen Receptor Cistrome in African American Men Associates with Upregulation of Lipid Metabolism and Immune Response
Berchuck J, Adib E, Alaiwi S, Dash A, Shin J, Lowder D, McColl C, Castro P, Carelli R, Benedetti E, Deng J, Robertson M, Baca S, Bell C, McClure H, Zarif T, Davidsohn M, Lakshminarayanan G, Rizwan K, Skapura D, Grimm S, Davis C, Ehli E, Kelleher K, Seo J, Mitsiades N, Coarfa C, Pomerantz M, Loda M, Ittmann M, Freedman M, Kaochar S. The Prostate Cancer Androgen Receptor Cistrome in African American Men Associates with Upregulation of Lipid Metabolism and Immune Response. Cancer Research 2022, 82: 2848-2859. PMID: 35731919, PMCID: PMC9379363, DOI: 10.1158/0008-5472.can-21-3552.Peer-Reviewed Original ResearchConceptsProstate cancerImmune responseProstate tumorsAndrogen receptorAggressiveness of prostate cancerLipid metabolismAA prostate tumorsPrimary prostate tumorsProstate cancer cohortProstate cancer progressionAA prostate cancerIncreased androgen signalingEA prostate cancerLevels of lipid metabolismImmune response genesAR cistromeUpregulation of lipid metabolismAndrogen signalingPoor prognosisClinical developmentLipid metabolism gene expressionMetabolomics dataCancer cohortProstateInhibitors of metabolic enzymesA general calculus of fitness landscapes finds genes under selection in cancers
Hsu TK, Asmussen J, Koire A, Choi BK, Gadhikar M, Huh E, Lin CH, Konecki D, Kim YW, Pickering C, Kimmel M, Donehower L, Frederick M, Myers JN, Katsonis P, Lichtarge O. A general calculus of fitness landscapes finds genes under selection in cancers. Genome Research 2022, 32: gr.275811.121. PMID: 35301263, PMCID: PMC9104707, DOI: 10.1101/gr.275811.121.Peer-Reviewed Original ResearchConceptsEvolution of traitsFitness landscapeGenotype-phenotype relationshipsEvolutionary relationshipsComplex traitsPositive selectionGenomic searchSpecific traitsCancer InsightsGenesGenetic variantsFunctional impactTraitsExperimental supportLandscapeVariantsPhenotypeEvolutionSelectionGenotypesCancer cohort
2021
Quantitative Assessment of CD200 and CD200R Expression in Lung Cancer
Vathiotis IA, MacNeil T, Zugazagoitia J, Syrigos KN, Aung TN, Gruver AM, Vaillancourt P, Hughes I, Hinton S, Driscoll K, Rimm DL. Quantitative Assessment of CD200 and CD200R Expression in Lung Cancer. Cancers 2021, 13: 1024. PMID: 33804482, PMCID: PMC7957629, DOI: 10.3390/cancers13051024.Peer-Reviewed Original ResearchLung cancer patientsCD200R expressionClinicopathologic characteristicsPD-L1Cancer patientsLung cancerImmune cellsLarge-cell neuroendocrine carcinoma patientsMutation statusNon-small cell lung cancer patientsCell lung cancer patientsQuantitative immunofluorescenceMultiplexed quantitative immunofluorescenceNeuroendocrine carcinoma patientsExpression of CD200Lung cancer cohortTumor cell stainingLCNEC patientsOverall survivalCarcinoma patientsImmune checkpointsImmune therapyTumor positivitySquamous differentiationCancer cohort
2020
Detection of Pathogenic Variants With Germline Genetic Testing Using Deep Learning vs Standard Methods in Patients With Prostate Cancer and Melanoma
AlDubayan S, Conway J, Camp S, Witkowski L, Kofman E, Reardon B, Han S, Moore N, Elmarakeby H, Salari K, Choudhry H, Al-Rubaish A, Al-Sulaiman A, Al-Ali A, Taylor-Weiner A, Van Allen E. Detection of Pathogenic Variants With Germline Genetic Testing Using Deep Learning vs Standard Methods in Patients With Prostate Cancer and Melanoma. JAMA 2020, 324: 1957-1969. PMID: 33201204, PMCID: PMC7672519, DOI: 10.1001/jama.2020.20457.Peer-Reviewed Original ResearchMeSH KeywordsCross-Sectional StudiesDeep LearningDNA Mutational AnalysisFemaleGenetic Predisposition to DiseaseGenetic TestingGerm-Line MutationHigh-Throughput Nucleotide SequencingHumansMaleMelanomaMiddle AgedNeural Networks, ComputerPredictive Value of TestsProstatic NeoplasmsSensitivity and SpecificityConceptsAmerican College of Medical Genetics and GenomicsGermline genetic testingCancer predisposition genesDetection of pathogenic variantsVariant detection performanceACMG genesNegative predictive valuePositive predictive valuePathogenic variantsGenetic testingProstate cancer cohortCriterion reference standardVariant detectionMendelian genesProstate cancerCancer cohortGermline pathogenic variantsCross-sectional studyGenetic testing methodsGermline variant detectionMelanoma cohortPathogenic germline alterationsMain OutcomesConvenience cohortClinical data collectionThe T cell differentiation landscape is shaped by tumour mutations in lung cancer
Ghorani E, Reading J, Henry J, Massy M, Rosenthal R, Turati V, Joshi K, Furness A, Ben Aissa A, Saini S, Ramskov S, Georgiou A, Sunderland M, Wong Y, Mucha M, Day W, Galvez-Cancino F, Becker P, Uddin I, Oakes T, Ismail M, Ronel T, Woolston A, Jamal-Hanjani M, Veeriah S, Birkbak N, Wilson G, Litchfield K, Conde L, Guerra-Assunção J, Blighe K, Biswas D, Salgado R, Lund T, Bakir M, Moore D, Hiley C, Loi S, Sun Y, Yuan Y, AbdulJabbar K, Turajilic S, Herrero J, Enver T, Hadrup S, Hackshaw A, Peggs K, McGranahan N, Chain B, Swanton C, Quezada S. The T cell differentiation landscape is shaped by tumour mutations in lung cancer. Nature Cancer 2020, 1: 546-561. PMID: 32803172, PMCID: PMC7115931, DOI: 10.1038/s43018-020-0066-y.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerTumor mutational burdenT cellsUntreated non-small cell lung cancerLung cancerCD8 T cell differentiationHigh-dimensional flow cytometryAssociated with poor survivalPersistent antigen exposureCD8 T cellsCD4 T cellsCell lung cancerT cell functionT cell differentiationImmunotherapy outcomesTumor neoantigensUntreated tumorsMutational burdenAntigen exposureTumor mutationsPoor survivalCancer cohortGene signatureTherapeutic manipulationFlow cytometry
2019
Histone-Related Genes Are Hypermethylated in Lung Cancer and Hypermethylated HIST1H4F Could Serve as a Pan-Cancer Biomarker
Dong S, Li W, Wang L, Hu J, Song Y, Zhang B, Ren X, Ji S, Li J, Xu P, Liang Y, Chen G, Lou J, Yu W. Histone-Related Genes Are Hypermethylated in Lung Cancer and Hypermethylated HIST1H4F Could Serve as a Pan-Cancer Biomarker. Cancer Research 2019, 79: 6101-6112. PMID: 31575549, DOI: 10.1158/0008-5472.can-19-1019.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiomarkers, TumorBronchoalveolar Lavage FluidCell Line, TumorCpG IslandsDatasets as TopicDNA MethylationEarly Detection of CancerFemaleGene Expression Regulation, NeoplasticGenetic LociHistonesHumansLung NeoplasmsMaleMiddle AgedPromoter Regions, GeneticWhole Genome SequencingConceptsHistone-related genesWhole-genome DNA methylation analysisDNA methylation analysisHistone genesCancer Genome AtlasMethylation signaturesMethylation analysisGenesGenome AtlasPan-CancerBronchoalveolar lavage fluid samplesHypermethylationLavage fluid samplesEarly cancer diagnosisTCGA datasetPan-cancer biomarkerLung cancerTCGACancer-related deathsLung cancer cohortMethylationCancer cohortTumor typesTumorigenesisCancer diagnosis
2018
Minimal microsatellite shift in microsatellite instability high endometrial cancer: a significant pitfall in diagnostic interpretation
Wu X, Snir O, Rottmann D, Wong S, Buza N, Hui P. Minimal microsatellite shift in microsatellite instability high endometrial cancer: a significant pitfall in diagnostic interpretation. Modern Pathology 2018, 32: 650-658. PMID: 30443012, DOI: 10.1038/s41379-018-0179-3.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overBiomarkers, TumorColorectal Neoplasms, Hereditary NonpolyposisDNA-Binding ProteinsEndometrial NeoplasmsFemaleGenetic LociGenetic Predisposition to DiseaseHumansImmunohistochemistryMicrosatellite InstabilityMiddle AgedMismatch Repair Endonuclease PMS2MutL Protein Homolog 1MutS Homolog 2 ProteinPhenotypePolymerase Chain ReactionPredictive Value of TestsReproducibility of ResultsConceptsEndometrial cancerMLH1/PMS2Endometrial carcinomaMSH6 lossMicrosatellite shiftCancer cohortMismatch repair deficiency testingMicrosatellite instability-high colorectal cancerEndometrial cancer cohortLoss of PMS2Clear cell carcinomaColorectal cancer cohortHigh colorectal cancerLynch syndrome familiesMSH2/MSH6PMS2 lossCell carcinomaColorectal cancerDeficiency testingSolid malignanciesColorectal carcinomaCarcinomaCancerIsolated lossMSH-6Hepatocellular Carcinoma Outcome is Predicted by Expression of Neuronal Calcium Sensor 1
Schuette D, Moore LM, Robert ME, Taddei TH, Ehrlich BE. Hepatocellular Carcinoma Outcome is Predicted by Expression of Neuronal Calcium Sensor 1. Cancer Epidemiology Biomarkers & Prevention 2018, 27: cebp.0167.2018. PMID: 29789326, PMCID: PMC8465775, DOI: 10.1158/1055-9965.epi-18-0167.Peer-Reviewed Original ResearchConceptsNeuronal calcium sensor-1Hepatocellular carcinomaDisease outcomePrognostic biomarkerIncidence of HCCWorse disease outcomesCancer-related deathLiver cancer cohortExpression levelsFurther functional assessmentEarly tumor detectionProspective cohortAsian patientsPatient survivalVariety of Ca2Tumor microarrayHCC patientsMetastatic cancerBreast cancerCancer cohortAggressive phenotypeNovel biomarkersFunctional assessmentPredictive valueTumor progression
2017
Impact of Sixteen Established Pancreatic Cancer Susceptibility Loci in American Jews
Streicher SA, Klein AP, Olson SH, Amundadottir LT, DeWan AT, Zhao H, Risch HA. Impact of Sixteen Established Pancreatic Cancer Susceptibility Loci in American Jews. Cancer Epidemiology Biomarkers & Prevention 2017, 26: 1540-1548. PMID: 28754795, PMCID: PMC5626623, DOI: 10.1158/1055-9965.epi-17-0262.Peer-Reviewed Original ResearchConceptsWhite European subjectsCancer susceptibility lociHigh riskEuropean subjectsAshkenazi JewsPancreatic Cancer Case-Control ConsortiumPancreatic cancer cohortPancreatic cancer patientsUnconditional logistic regressionSusceptibility lociCancer patientsPancreatic cancerCancer cohortGenetic Epidemiology ResearchLogistic regressionAdult HealthEpidemiology researchCase-control sampleRiskORSSubjectsIndividual ORsMinor allele frequencyExome Sequencing of African-American Prostate Cancer Reveals Loss-of-Function ERF Mutations
Huang F, Mosquera J, Garofalo A, Oh C, Baco M, Amin-Mansour A, Rabasha B, Bahl S, Mullane S, Robinson B, Aldubayan S, Khani F, Karir B, Kim E, Chimene-Weiss J, Hofree M, Romanel A, Osborne J, Kim J, Azabdaftari G, Woloszynska-Read A, Sfanos K, De Marzo A, Demichelis F, Gabriel S, Van Allen E, Mesirov J, Tamayo P, Rubin M, Powell I, Garraway L. Exome Sequencing of African-American Prostate Cancer Reveals Loss-of-Function ERF Mutations. Cancer Discovery 2017, 7: 973-983. PMID: 28515055, PMCID: PMC5836784, DOI: 10.1158/2159-8290.cd-16-0960.Peer-Reviewed Original ResearchConceptsProstate cancerRecurrent loss-of-function mutationsSystematic genome sequencingCastration-resistant prostate cancerLethal castration-resistant prostate cancerProstate cancer tumor suppressor geneCancer sequencing studiesCancer genome characterizationLoss-of-function mutationsIncreased anchorage-independent growthPrimary prostate cancerAfrican American menProstate cancer cohortAnchorage-independent growthTumor suppressor geneProstate cancer genesGene expression signaturesTranscriptional repressorGenomic characterizationSequencing studiesExome sequencingCancer genesAndrogen signalingGene mutationsCancer cohortCalcium Sensor, NCS-1, Promotes Tumor Aggressiveness and Predicts Patient Survival
Moore LM, England A, Ehrlich BE, Rimm DL. Calcium Sensor, NCS-1, Promotes Tumor Aggressiveness and Predicts Patient Survival. Molecular Cancer Research 2017, 15: 942-952. PMID: 28275088, PMCID: PMC5500411, DOI: 10.1158/1541-7786.mcr-16-0408.Peer-Reviewed Original ResearchConceptsBreast cancer cellsNCS-1Breast cancer patient cohortsNCS-1 expressionLymph node statusCancer cellsShorter survival rateIndependent breast cancer cohortsCancer patient cohortsBreast cancer cohortMB-231 breast cancer cellsPaclitaxel-induced cell deathAggressive tumor phenotypeNeuronal model systemClinical outcomesClinicopathologic featuresNeuronal calcium sensor-1Node statusPatient cohortProgesterone receptorWorse outcomesBreast cancerCalcium-binding proteinsCancer cohortEstrogen receptorCorrelation of sentinel lymph node immune cells with disease-free survival and metastasis in breast cancer patients using 4-color chromogen-based immunohistochemistry and quantitative imaging microscopy
Blenman K. Correlation of sentinel lymph node immune cells with disease-free survival and metastasis in breast cancer patients using 4-color chromogen-based immunohistochemistry and quantitative imaging microscopy. The Journal Of Immunology 2017, 198: 197.7-197.7. DOI: 10.4049/jimmunol.198.supp.197.7.Peer-Reviewed Original ResearchDisease-free survivalShorter disease-free survivalOnly immune cellsBreast cancer patientsT cellsCancer cell invasionImmune cellsB cellsDistant metastasisCancer patientsDendritic cellsLocal metastasisCell invasionOdds of metastasisT cell reductionCancer cellsBreast cancer cohortSentinel lymphUnivariate analysisCancer cohortPatientsMetastasisLogistic regressionCell reductionSurvival
2014
Quantitative assessment of miR34a as an independent prognostic marker in breast cancer
Agarwal S, Hanna J, Sherman ME, Figueroa J, Rimm DL. Quantitative assessment of miR34a as an independent prognostic marker in breast cancer. British Journal Of Cancer 2014, 112: 61-68. PMID: 25474246, PMCID: PMC4453614, DOI: 10.1038/bjc.2014.573.Peer-Reviewed Original ResearchConceptsDisease-specific survivalBreast cancer cohortPoor disease-specific survivalDisease-specific deathIndependent breast cancer cohortsBreast cancerCancer cohortPoor outcomeCohort 1Multivariate Cox proportional hazards analysisCox proportional hazards analysisNode-positive populationX-tile softwareNode-negative patientsProportional hazards analysisTumor suppressorBreast cancer patientsIndependent prognostic markerExpression of miR34aReceptor statusNode statusPreclinical observationsTumor sizeCancer patientsCohort 2
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