Herbert Yu, MD, PhD
Professor AdjunctAbout
Research
Overview
- Role of Genetic and Lifestyle Interplay in Uterus Cancer
- Molecular Characterization of the Insulin-like Growth Factor System in Breast Cancer and Ovarian Cancer and its Association with Tumor Progression
- Case-control Study of Pancreatic Cancer Etiologic Factors
- DNA Methylation in Cancer Risk and Progression
- Case-control study of Liver Cancer
- GWAS on Endometrial Cancer
Medical Research Interests
Breast Neoplasms; Gene-Environment Interaction; Liver Neoplasms; Molecular Epidemiology; Neoplasms; Ovarian Neoplasms; Uterine Neoplasms
Publications
2024
An Artificial Intelligence-Driven Preoperative Radiomic Subtype for Predicting the Prognosis and Treatment Response of Patients with Papillary Thyroid Carcinoma.
Li Q, Zhang W, Liao T, Gao Y, Zhang Y, Jin A, Ma B, Qu N, Zhang H, Zheng X, Li D, Yun X, Zhao J, Yu H, Gao M, Wang Y, Qian B. An Artificial Intelligence-Driven Preoperative Radiomic Subtype for Predicting the Prognosis and Treatment Response of Patients with Papillary Thyroid Carcinoma. Clinical Cancer Research 2024, 31: 139-150. PMID: 39535738, DOI: 10.1158/1078-0432.ccr-24-2356.Peer-Reviewed Original ResearchPapillary thyroid carcinomaPapillary thyroid carcinoma patientsDisease-free survivalThyroid carcinomaInflammatory subtypeRadiomics signatureTreatment responseSubtype of papillary thyroid carcinomaTianjin Medical University Cancer Institute and HospitalAssociated with poor disease-free survivalFudan University Shanghai Cancer CenterPoor disease-free survivalCancer Institute and HospitalTreatment response of patientsComplications risk stratificationShanghai Cancer CenterAnti-inflammatory traditional Chinese medicinesResponse of patientsPreoperative ultrasound imagingValidation set 2Clinicopathological variablesTraining set 1Evaluate prognosisPoor prognosisRisk stratificationSomatic gene mutations involved in DNA damage response/Fanconi anemia signaling are tissue- and cell-type specific in human solid tumors
Kumar S, Du W, Zhang J, Yu H, Deng Y, Fei P. Somatic gene mutations involved in DNA damage response/Fanconi anemia signaling are tissue- and cell-type specific in human solid tumors. Frontiers In Medicine 2024, 11: 1462810. PMID: 39421870, PMCID: PMC11483370, DOI: 10.3389/fmed.2024.1462810.Peer-Reviewed Original ResearchDNA damage responsePotential driver mutationsFanconi anemiaCellular defense networkHuman cancersStudy of DNA damage responseAlteration frequencyDriver mutationsFA proteinsPan-cancer samplesSignal transductionSomatic gene mutationsDamage responseFA signalingUBE2TMutated genesCellular insultsDevelopment of effective therapeutic strategiesCell-typeMutational signaturesGene alteration patternsGenesMutationsDefense networkProstate cancerAldehydes alter TGF-β signaling and induce obesity and cancer
Yang X, Bhowmick K, Rao S, Xiang X, Ohshiro K, Amdur R, Hassan M, Mohammad T, Crandall K, Cifani P, Shetty K, Lyons S, Merrill J, Vegesna A, John S, Latham P, Crawford J, Mishra B, Dasarathy S, Wang X, Yu H, Wang Z, Huang H, Krainer A, Mishra L. Aldehydes alter TGF-β signaling and induce obesity and cancer. Cell Reports 2024, 43: 114676. PMID: 39217614, PMCID: PMC11560041, DOI: 10.1016/j.celrep.2024.114676.Peer-Reviewed Original ResearchAldehyde dehydrogenase 2Small interfering RNADisease progression to cancerPro-oncogenic phenotypeTGF-bProgression to cancerGrowth factor BTGF-b signalingHuman metabolic syndromeSteatotic liver diseasePotential therapeutic targetMetabolic syndromePro-fibroticInduce obesityTherapeutic inhibitionLiver diseaseCurrent treatmentSmad3 signalingGlucose handlingTherapeutic targetFunctional phenotypeDehydrogenase 2Improve glucose handlingSPTBN1ObesityGenome-Wide Analysis to Assess if Heavy Alcohol Consumption Modifies the Association between SNPs and Pancreatic Cancer Risk.
Ni Z, Kundu P, McKean D, Wheeler W, Albanes D, Andreotti G, Antwi S, Arslan A, Bamlet W, Beane-Freeman L, Berndt S, Bracci P, Brennan P, Buring J, Chanock S, Gallinger S, Gaziano J, Giles G, Giovannucci E, Goggins M, Goodman P, Haiman C, Hassan M, Holly E, Hung R, Katzke V, Kooperberg C, Kraft P, LeMarchand L, Li D, McCullough M, Milne R, Moore S, Neale R, Oberg A, Patel A, Peters U, Rabe K, Risch H, Shu X, Smith-Byrne K, Visvanathan K, Wactawski-Wende J, White E, Wolpin B, Yu H, Zeleniuch-Jacquotte A, Zheng W, Zhong J, Amundadottir L, Stolzenberg-Solomon R, Klein A. Genome-Wide Analysis to Assess if Heavy Alcohol Consumption Modifies the Association between SNPs and Pancreatic Cancer Risk. Cancer Epidemiology Biomarkers & Prevention 2024, 33: 1229-1239. PMID: 38869494, PMCID: PMC11928872, DOI: 10.1158/1055-9965.epi-24-0096.Peer-Reviewed Original ResearchConceptsPancreatic cancer riskHeavy alcohol consumptionCancer riskSingle-nucleotide polymorphismsAlcohol consumptionExpression quantitative trait lociQuantitative trait lociAssociated with pancreatic cancer riskGenome-wide interaction analysisGenome-wide significant evidenceEtiology of pancreatic cancerFixed-effect meta-analysesGenomic regionsGenome-wide significant evidence of associationLead single-nucleotide polymorphismsTrait lociGenetic variantsEuropean ancestry populationsEvidence of associationGenome-wide association studiesAnalysis of single-nucleotide polymorphismsCase-control studyPancreatic cancerGenome-wide analysisAncestry populations459 REGULATION OF CEACAM1 IN METABOLIC DYSFUNCTION ASSOCIATED STEATOHEPATITIS (MASH) AND HCC BY TGF-β SIGNALING
Bhowmick K, Yang X, Xiang X, Ohshiro K, Latham P, Crawford J, Amdur R, Hassan M, Mohammad T, Crandall K, Cifani P, Mishra B, Dasarathy S, Wang X, Yu H, Wang Z, Krainer A, Mishra L. 459 REGULATION OF CEACAM1 IN METABOLIC DYSFUNCTION ASSOCIATED STEATOHEPATITIS (MASH) AND HCC BY TGF-β SIGNALING. Gastroenterology 2024, 166: s-1547. DOI: 10.1016/s0016-5085(24)04005-8.Peer-Reviewed Original ResearchSu1127 MYOSTATIN CONTRIBUTES TO ALTERATIONS IN METABOLIC PATHWAYS AND MUSCLE ATROPHY IN MASH AND HCC AND IS A PROMISING BIOMARKER WITH METABOLIC MARKER PKM2 FOR RISK STRATIFICATION OF HCC
Bhowmick K, Xiang X, Ohshiro K, Amdur R, Yang X, Wong L, Shetty K, Latham P, Lau L, Crandall K, Cifani P, Cacaj F, Mishra B, Dasarathy S, Wang X, Yu H, Wang Z, Krainer A, Satapathy S, Crawford J, Mishra L. Su1127 MYOSTATIN CONTRIBUTES TO ALTERATIONS IN METABOLIC PATHWAYS AND MUSCLE ATROPHY IN MASH AND HCC AND IS A PROMISING BIOMARKER WITH METABOLIC MARKER PKM2 FOR RISK STRATIFICATION OF HCC. Gastroenterology 2024, 166: s-666. DOI: 10.1016/s0016-5085(24)01982-6.Peer-Reviewed Original ResearchHypertension and risk of endometrial cancer: a pooled analysis in the Epidemiology of Endometrial Cancer Consortium (E2C2)
Habeshian T, Peeri N, De Vivo I, Schouten L, Shu X, Cote M, Bertrand K, Chen Y, Clarke M, Clendenen T, Cook L, Costas L, Dal Maso L, Freudenheim J, Friedenreich C, Gallagher G, Gierach G, Goodman M, Jordan S, La Vecchia C, Lacey J, Levi F, Liao L, Lipworth L, Lu L, Matias-Guiu X, Moysich K, Mutter G, Na R, Naduparambil J, Negri E, O'Connell K, O'Mara T, Hernández I, Palmer J, Parazzini F, Patel A, Penney K, Prizment A, Ricceri F, Risch H, Sacerdote C, Sandin S, Stolzenberg-Solomon R, van den Brandt P, Webb P, Wentzensen N, Wijayabahu A, Wilkens L, Xu W, Yu H, Zeleniuch-Jacquotte A, Zheng W, Du M, Setiawan V. Hypertension and risk of endometrial cancer: a pooled analysis in the Epidemiology of Endometrial Cancer Consortium (E2C2). Cancer Epidemiology Biomarkers & Prevention 2024, 33: 788-795. PMID: 38530242, PMCID: PMC11145161, DOI: 10.1158/1055-9965.epi-23-1444.Peer-Reviewed Original ResearchConceptsEpidemiology of Endometrial Cancer ConsortiumRisk of endometrial cancerComponents of metabolic syndromeCancer ConsortiumRisk factorsAssociated with endometrial cancer riskIncidence rates of endometrial cancerMultivariable unconditional logistic regression modelStronger magnitude of associationEtiology of endometrial cancerStudy designUnconditional logistic regression modelsIncreased risk of endometrial cancerEndometrial cancer riskRates of endometrial cancerUsers of postmenopausal hormone therapyConfidence intervalsRising prevalence of obesityPrevalence of obesityEndometrial cancerMagnitude of associationEndometrial cancer casesMetabolic syndromeBody mass indexLogistic regression modelsDetection of hepatocellular carcinoma methylation markers in salivary DNA
Mezzacappa C, Wang Z, Lu L, Risch H, Taddei T, Yu H. Detection of hepatocellular carcinoma methylation markers in salivary DNA. Bioscience Reports 2024, 44: bsr20232063. PMID: 38457142, PMCID: PMC10958141, DOI: 10.1042/bsr20232063.Peer-Reviewed Original ResearchHepatocellular carcinoma screeningCase patientsHepatocellular carcinomaControl subjectsDiagnosis of hepatocellular carcinomaAssociated with hepatocellular carcinomaScreening testSalivary DNASaliva-based testCpG sitesStudy of risk factorsSalivary DNA methylationDNA methylationViral hepatitisCirculating DNAAlterations to DNA methylationRisk factorsMethylation markersPatientsRegulation of cell cycle progressionBlood samplesCell cycle progressionAffected individualsAlternative to blood samplingMultiple comparisonsMechanistically based blood proteomic markers in the TGF-β pathway stratify risk of hepatocellular cancer in patients with cirrhosis.
Xiang X, Bhowmick K, Shetty K, Ohshiro K, Yang X, Wong L, Yu H, Latham P, Satapathy S, Brennan C, Dima R, Chambwe N, Sharifova G, Cacaj F, John S, Crawford J, Huang H, Dasarathy S, Krainer A, He A, Amdur R, Mishra L. Mechanistically based blood proteomic markers in the TGF-β pathway stratify risk of hepatocellular cancer in patients with cirrhosis. Genes & Cancer 2024, 15: 1-14. PMID: 38323119, PMCID: PMC10843195, DOI: 10.18632/genesandcancer.234.Peer-Reviewed Original ResearchHepatocellular carcinomaPyruvate kinase M2TGF-bPresence of hepatocellular carcinomaEarly detection of HCCRisk of hepatocellular cancerDetection of hepatocellular carcinomaAdvanced incurable stageRisk-stratifying biomarkersTGF-B pathwayAssociated with hepatocellular carcinomaProteomic markersEarly detectionBiologically relevant markersIncurable stageBlood-based biomarkersHepatocellular cancerRisk stratificationStratify riskNon-HCCClinical variablesBlood levelsLiver diseaseAnimal modelsBiological role
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
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Chronic Disease Epidemiology
PO Box 208034, 60 College Street
New Haven, CT 06520-8034
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New Haven, CT 06510