2023
The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium
Bruin W, Abe Y, Alonso P, Anticevic A, Backhausen L, Balachander S, Bargallo N, Batistuzzo M, Benedetti F, Bertolin Triquell S, Brem S, Calesella F, Couto B, Denys D, Echevarria M, Eng G, Ferreira S, Feusner J, Grazioplene R, Gruner P, Guo J, Hagen K, Hansen B, Hirano Y, Hoexter M, Jahanshad N, Jaspers-Fayer F, Kasprzak S, Kim M, Koch K, Bin Kwak Y, Kwon J, Lazaro L, Li C, Lochner C, Marsh R, Martínez-Zalacaín I, Menchon J, Moreira P, Morgado P, Nakagawa A, Nakao T, Narayanaswamy J, Nurmi E, Zorrilla J, Piacentini J, Picó-Pérez M, Piras F, Piras F, Pittenger C, Reddy J, Rodriguez-Manrique D, Sakai Y, Shimizu E, Shivakumar V, Simpson B, Soriano-Mas C, Sousa N, Spalletta G, Stern E, Evelyn Stewart S, Szeszko P, Tang J, Thomopoulos S, Thorsen A, Yoshida T, Tomiyama H, Vai B, Veer I, Venkatasubramanian G, Vetter N, Vriend C, Walitza S, Waller L, Wang Z, Watanabe A, Wolff N, Yun J, Zhao Q, van Leeuwen W, van Marle H, van de Mortel L, van der Straten A, van der Werf Y, Thompson P, Stein D, van den Heuvel O, van Wingen G. The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium. Molecular Psychiatry 2023, 28: 4307-4319. PMID: 37131072, PMCID: PMC10827654, DOI: 10.1038/s41380-023-02077-0.Peer-Reviewed Original ResearchObsessive-compulsive disorderHealthy controlsFunctional connectivitySensorimotor networkOCD patientsResting-state functional connectivityWhole-brain functional connectivityResting-state connectivityPathophysiological modelPatient statusAccurate biomarkersWidespread abnormalitiesPatientsMajority of studiesEntire brainGeneralizability of resultsGroup differencesFunctional connectomeAbnormalitiesBiomarkersFunctional networksDisordersCurrent knowledgeIndividual levelIndependent samples
2022
Ancestry-driven recalibration of tumor mutational burden and disparate clinical outcomes in response to immune checkpoint inhibitors
Nassar AH, Adib E, Abou Alaiwi S, El Zarif T, Groha S, Akl EW, Nuzzo PV, Mouhieddine TH, Perea-Chamblee T, Taraszka K, El-Khoury H, Labban M, Fong C, Arora KS, Labaki C, Xu W, Sonpavde G, Haddad RI, Mouw KW, Giannakis M, Hodi FS, Zaitlen N, Schoenfeld AJ, Schultz N, Berger MF, MacConaill LE, Ananda G, Kwiatkowski DJ, Choueiri TK, Schrag D, Carrot-Zhang J, Gusev A. Ancestry-driven recalibration of tumor mutational burden and disparate clinical outcomes in response to immune checkpoint inhibitors. Cancer Cell 2022, 40: 1161-1172.e5. PMID: 36179682, PMCID: PMC9559771, DOI: 10.1016/j.ccell.2022.08.022.Peer-Reviewed Original ResearchConceptsTumor mutational burdenImproved outcomesMutational burdenSolid tumorsNon-small cell lung cancerImmune checkpoint inhibitor pembrolizumabHigh tumor mutational burdenCheckpoint inhibitor pembrolizumabTMB-high groupImmune checkpoint inhibitorsCell lung cancerDisparate clinical outcomesDiverse patient populationsCheckpoint inhibitorsClinical outcomesPatient populationLung cancerClinical cohortAccurate biomarkersUS FDATumorsBiomarker studiesNon-European ancestry populationsPrecision medicinePatients
2021
Unmet needs in basic and translational research in Cholangiocarcinoma
Cadamuro M, Macias R, Strain A, Strazzabosco M, Simioni P, Marin J, Fabris L. Unmet needs in basic and translational research in Cholangiocarcinoma. Liver International Communications 2021, 3: 5-16. DOI: 10.1002/lci2.39.Peer-Reviewed Original ResearchTranslational researchManagement of cholangiocarcinomaTumor-restraining functionsSystematic literature searchCCA managementPoor prognosisExtrahepatic cholangiocarcinomaDeep molecular phenotypingConsensus statementEnigmatic diseaseActionable mutationsCholangiocarcinomaAccurate biomarkersTumor microenvironmentLiterature searchExperimental modelEarly detectionMarked heterogeneityDiseaseMolecular phenotypingWide heterogeneityFurther studiesTumorsMolecular characterization studiesComplex role
2019
Serum MicroRNA Biomarkers Regulated by Simvastatin in a Primate Model of Endometriosis
Cosar E, Mamillapalli R, Moridi I, Duleba A, Taylor HS. Serum MicroRNA Biomarkers Regulated by Simvastatin in a Primate Model of Endometriosis. Reproductive Sciences 2019, 26: 1343-1350. PMID: 29587611, PMCID: PMC6949973, DOI: 10.1177/1933719118765971.Peer-Reviewed Original ResearchConceptsEndometriosis groupPrimate modelSerum microRNA BiomarkersReproductive-aged womenSerum miRNA expressionTreatment of endometriosisNoninvasive diagnostic strategyMiR-150-5pNonhuman primate modelEstrogen-dependent diseaseReal-time polymerase chain reactionQuantitative real-time polymerase chain reactionTime polymerase chain reactionEndometriosis treatmentEndometriosis severitySimvastatin treatmentHuman endometriosisEndometriosisAccurate biomarkersHuman patientsMiR-451aControl expression levelsDiagnostic strategiesSpecific biomarkersSerum samples
2014
Methylation of Twelve CpGs in Human Papillomavirus Type 16 (HPV16) as an Informative Biomarker for the Triage of Women Positive for HPV16 Infection
Brandsma JL, Harigopal M, Kiviat NB, Sun Y, Deng Y, Zelterman D, Lizardi PM, Shabanova VS, Levi A, Yaping T, Hu X, Feng Q. Methylation of Twelve CpGs in Human Papillomavirus Type 16 (HPV16) as an Informative Biomarker for the Triage of Women Positive for HPV16 Infection. Cancer Prevention Research 2014, 7: 526-533. PMID: 24556390, DOI: 10.1158/1940-6207.capr-13-0354.Peer-Reviewed Original ResearchConceptsCervical intraepithelial neoplasiaCytology samplesCutoff scoreColposcopy of womenCervical cancer preventionManagement of womenDetection of CIN3Cervical cytology samplesHuman papillomavirus type 16Human papillomavirus type 16 DNAMethylation biomarkersPapillomavirus type 16Histologic severityIntraepithelial neoplasiaCervical cancerHPV16 infectionCancer preventionDNA bisulfite sequencingType 16Prognostic potentialAccurate biomarkersProspective biomarkersScreening testInformative biomarkersBiomarkers
2012
Cell-free microRNAs in urine as diagnostic and prognostic biomarkers of bladder cancer
YUN S, JEONG P, KIM W, KIM T, LEE Y, SONG P, CHOI Y, KIM I, MOON S, KIM W. Cell-free microRNAs in urine as diagnostic and prognostic biomarkers of bladder cancer. International Journal Of Oncology 2012, 41: 1871-1878. PMID: 22961325, DOI: 10.3892/ijo.2012.1622.Peer-Reviewed Original ResearchConceptsBladder cancerCell-free miRNAsMiR-200aMiR-145Transitional cell carcinomaBladder cancer patientsNon-cancer controlsHealthy normal controlsMiR-145 levelsMiR-200a levelsCell-free microRNAsNMIBC recurrenceIndependent predictorsClinicopathological featuresCell carcinomaCancer patientsPrognostic biomarkerUrinary bladderHigh riskNoninvasive biomarkersNormal controlsAccurate biomarkersMultivariate analysisPatientsCancer
2011
Consistent metagenes from cancer expression profiles yield agent specific predictors of chemotherapy response
Li Q, Eklund AC, Birkbak NJ, Desmedt C, Haibe-Kains B, Sotiriou C, Symmans WF, Pusztai L, Brunak S, Richardson AL, Szallasi Z. Consistent metagenes from cancer expression profiles yield agent specific predictors of chemotherapy response. BMC Bioinformatics 2011, 12: 310. PMID: 21798043, PMCID: PMC3155975, DOI: 10.1186/1471-2105-12-310.Peer-Reviewed Original ResearchConceptsEarly-stage lung cancerStage lung cancerNegative breast cancerCancer treatment decisionsHuman tumor samplesNeoadjuvant therapyChemotherapy responseLung cancerBreast cancerTreatment decisionsIndependent cohortPrognostic classifierAccurate biomarkersCancer expression profilesTumor typesPotential biomarkersTumor samplesConclusionsThese resultsSpecific predictorsStrong associationReliable predictorCohortCancerPredictorsBiomarkers
2006
Comprehensive Phenotyping in Multiple Sclerosis: Discovery Based Proteomics and the Current Understanding of Putative Biomarkers
O’Connor K, Roy SM, Becker CH, Hafler DA, Kantor AB. Comprehensive Phenotyping in Multiple Sclerosis: Discovery Based Proteomics and the Current Understanding of Putative Biomarkers. Disease Markers 2006, 22: 213-225. PMID: 17124343, PMCID: PMC3851054, DOI: 10.1155/2006/670439.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsMultiple sclerosisMagnetic resonance imagingPutative biomarkersComprehensive phenotypingMonitoring of progressionComponent expression levelsClinical evaluationCSF proteinAccurate biomarkersCerebrospinal fluid chemistryControl groupTherapeutic interventionsPatient careAccurate diagnosisResonance imagingDisease pathologyFurther evaluationBiomarkersPreliminary dataExpression levelsSclerosisDiagnosisCSFSingle testNovel assessment
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