2024
Charting the metabolic biogeography of the colorectum in cancer: challenging the right sided versus left sided classification
Jain A, Morris M, Berardi D, Arora T, Domingo-Almenara X, Paty P, Rattray N, Kerekes D, Lu L, Khan S, Johnson C. Charting the metabolic biogeography of the colorectum in cancer: challenging the right sided versus left sided classification. Molecular Cancer 2024, 23: 211. PMID: 39342363, PMCID: PMC11438248, DOI: 10.1186/s12943-024-02133-5.Peer-Reviewed Original ResearchConceptsRectal cancerNormal mucosaMetabolite abundancePatient-matched tumorTumor-specific metabolitesMetabolic heterogeneityPatient survivalRectosigmoid colonSigmoid colonAnatomic subsitePatient-matched normal mucosaTransverse colonMetabolomic profilesAscending colonCRC biomarkersMetabolome DatabaseDescending colonMetabolite changesLeft-sidedRight-sidedColorectumRisk factorsMetabolome mapCancerTumor
2022
Oral Cyanobacteria and Hepatocellular Carcinoma
Hernandez BY, Zhu X, Risch HA, Lu L, Ma X, Irwin ML, Lim JK, Taddei TH, Pawlish KS, Stroup AM, Brown R, Wang Z, Wong LL, Yu H. Oral Cyanobacteria and Hepatocellular Carcinoma. Cancer Epidemiology Biomarkers & Prevention 2022, 31: 221-229. PMID: 34697061, PMCID: PMC8755591, DOI: 10.1158/1055-9965.epi-21-0804.Peer-Reviewed Original ResearchConceptsHepatitis B virusHepatitis C virusHepatocellular carcinomaRisk factorsLiver diseaseHCC casesOral microbiomeU.S. case-control studyIndependent risk factorChronic liver diseaseFatty liver diseaseHCC risk factorsGut microbial alterationsType 2 diabetesCase-control studyLiver cancer developmentNSAID useAspirin useC virusB virusHCC riskNegative historyOral samplesSignificant associationCancer development
2021
Intratumour microbiome associated with the infiltration of cytotoxic CD8+ T cells and patient survival in cutaneous melanoma
Zhu G, Su H, Johnson CH, Khan SA, Kluger H, Lu L. Intratumour microbiome associated with the infiltration of cytotoxic CD8+ T cells and patient survival in cutaneous melanoma. European Journal Of Cancer 2021, 151: 25-34. PMID: 33962358, PMCID: PMC8184628, DOI: 10.1016/j.ejca.2021.03.053.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overBacteriaBacterial LoadBacterial TranslocationChemokinesClostridialesCytotoxicity, ImmunologicFemaleGastrointestinal MicrobiomeHumansLymphocyte CountLymphocytes, Tumor-InfiltratingMaleMelanomaMiddle AgedPrognosisSkin NeoplasmsT-Lymphocytes, CytotoxicTumor MicroenvironmentYoung AdultConceptsT cellsCutaneous melanomaPatient survivalGut microbiomeAdjusted hazard ratioT cell infiltrationChemokine gene expressionChemokine levelsCytotoxic CD8Hazard ratioSystemic inflammationShorter survivalCCL5 expressionPatient outcomesCD8Immune responseMortality riskGut microbiotaSurvival analysisMelanomaTumor nicheHuman cancersSurvivalSignificant correlationPositive association“Randomized trial of physical activity on quality of life and lung cancer biomarkers in patients with advanced stage lung cancer: a pilot study”
Bade BC, Gan G, Li F, Lu L, Tanoue L, Silvestri GA, Irwin ML. “Randomized trial of physical activity on quality of life and lung cancer biomarkers in patients with advanced stage lung cancer: a pilot study”. BMC Cancer 2021, 21: 352. PMID: 33794808, PMCID: PMC8015735, DOI: 10.1186/s12885-021-08084-0.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerAdvanced-stage lung cancerStage lung cancerUsual carePhysical activityIntervention groupQuality of lifeLung cancerEligible patientsStage III/IV non-small cell lung cancerLow baseline physical activityHome-based physical activityAdvanced stage diseaseSoluble PD-1Stage IV adenocarcinomaBaseline physical activityMinority of patientsCell lung cancerPatient-reported outcomesEffects of exerciseRole functioning domainsLung cancer biologyAspects of QoL.Mobile health interventionsCancer biomarkersInterplay between RNA Methylation Eraser FTO and Writer METTL3 in Renal Clear Cell Carcinoma Patient Survival
Zhao J, Lu L. Interplay between RNA Methylation Eraser FTO and Writer METTL3 in Renal Clear Cell Carcinoma Patient Survival. Recent Patents On Anti-Cancer Drug Discovery 2021, 16: 363-376. PMID: 33563180, DOI: 10.2174/1574892816666210204125155.Peer-Reviewed Original ResearchConceptsMETTL3 mRNASurvival analysisFTO mRNAKaplan-Meier survival curvesAdjusted hazard ratioMultivariate Cox regressionRenal clear cell carcinomaClear cell carcinomaInflammation-related genesPotential prognostic markerM6A methyltransferase METTL3Upregulation of FTOHazard ratioCox regressionPatient survivalPrognostic valueCell carcinomaPrognostic markerSuperior survivalImmune responseMETTL3 expressionDifferential expressionClinical relevanceLower DNA methylationSurvival curves
2020
Gene Alterations of N6‐Methyladenosine (m6A) Regulators in Colorectal Cancer: A TCGA Database Study
Zhang Q, Cai Y, Kurbatov V, Khan SA, Lu L, Zhang Y, Johnson CH. Gene Alterations of N6‐Methyladenosine (m6A) Regulators in Colorectal Cancer: A TCGA Database Study. BioMed Research International 2020, 2020: 8826456. PMID: 33415160, PMCID: PMC7769650, DOI: 10.1155/2020/8826456.Peer-Reviewed Original ResearchMeSH KeywordsAdenosineAgedAlpha-Ketoglutarate-Dependent Dioxygenase FTOColorectal NeoplasmsDatabases, GeneticDisease-Free SurvivalDNA Copy Number VariationsFemaleGene Expression Regulation, NeoplasticGenes, NeoplasmHumansMaleMultivariate AnalysisMutationNerve Tissue ProteinsPrognosisProportional Hazards ModelsRNA Splicing FactorsRNA, MessengerConceptsDisease-free survivalImmune cell infiltrationM6A regulatorsCRC patientsCRC casesCell infiltrationMRNA expressionWorse overall survivalN6-methyladenosine regulatorsMicrosatellite instability statusMessenger RNA expressionCancer Genome AtlasOverall survivalColorectal cancerCRC tissuesDatabase studyImmune functionInstability statusColon tissuesRole of m6AGene alterationsRNA expressionCRCGenome AtlasGenetic mutationsRegulation and characterization of tumor-infiltrating immune cells in breast cancer
Dai Q, Wu W, Amei A, Yan X, Lu L, Wang Z. Regulation and characterization of tumor-infiltrating immune cells in breast cancer. International Immunopharmacology 2020, 90: 107167. PMID: 33223469, PMCID: PMC7855363, DOI: 10.1016/j.intimp.2020.107167.Peer-Reviewed Original ResearchConceptsTumor-infiltrating immune cellsT cell activation statusImmune cellsCell activation statusT cell activationPatient survivalM2 macrophagesT cellsBreast cancerCell activationT cell peripheral toleranceTumor-infiltrating B cellsMultivariate Cox regression modelActivation statusBreast cancer patient survivalEffector T cellsT cell subsetsBreast cancer patientsImmune cell infiltrationAbundant plasma cellsCox regression modelKaplan-Meier survivalImmune cell typesMolecular pathwaysCancer patient survivalSyndecan-1 and KRAS Gene Expression Signature Associates With Patient Survival in Pancreatic Cancer.
Wu Y, Huang H, Fervers B, Lu L. Syndecan-1 and KRAS Gene Expression Signature Associates With Patient Survival in Pancreatic Cancer. Pancreas 2020, 49: 1187-1194. PMID: 32898003, DOI: 10.1097/mpa.0000000000001654.Peer-Reviewed Original ResearchConceptsSyndecan-1Patient survivalPancreatic cancerAdjusted hazard ratioPancreatic cancer patientsKRAS somatic mutationsSDC1 mRNASomatic mutationsHazard ratioCancer patientsClinical dataSurvival analysisKRASPatientsKyoto EncyclopediaKRAS mRNAElevated mortalityGenomes (KEGG) pathway analysisCancerPathway analysisLower methylationMolecular characteristicsSurvivalMRNANegative correlationRisk factors for hepatocellular carcinoma (HCC) in the northeast of the United States: results of a case–control study
Shen Y, Risch H, Lu L, Ma X, Irwin ML, Lim JK, Taddei T, Pawlish K, Stroup A, Brown R, Wang Z, Jia W, Wong L, Mayne ST, Yu H. Risk factors for hepatocellular carcinoma (HCC) in the northeast of the United States: results of a case–control study. Cancer Causes & Control 2020, 31: 321-332. PMID: 32060838, PMCID: PMC7136513, DOI: 10.1007/s10552-020-01277-1.Peer-Reviewed Original ResearchConceptsRisk of HCCCase-control studyHepatocellular carcinomaRisk factorsHCV infectionHCC riskOdds ratioHepatitis C virus antibodyUnconditional logistic regression modelsElevated HCC riskRapid case ascertainmentC virus antibodyHeavy alcohol intakeConfidence intervalsFamily cancer historyImportant risk factorRandom digit dialingLow socioeconomic statusUnhealthy lifestyle choicesLower household incomeLogistic regression modelsNSAID useAlcohol intakeCigarette smokingHigher BMI
2019
Transfer RNA methyltransferase gene NSUN2 mRNA expression modifies the effect of T cell activation score on patient survival in head and neck squamous carcinoma
Lu L, Gaffney SG, Cannataro VL, Townsend J. Transfer RNA methyltransferase gene NSUN2 mRNA expression modifies the effect of T cell activation score on patient survival in head and neck squamous carcinoma. Oral Oncology 2019, 101: 104554. PMID: 31887619, PMCID: PMC7273869, DOI: 10.1016/j.oraloncology.2019.104554.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiomarkersFemaleGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateLymphocyte ActivationMaleMethyltransferasesMiddle AgedNeoplasm GradingNeoplasm StagingPrognosisProportional Hazards ModelsSquamous Cell Carcinoma of Head and NeckT-LymphocytesYoung AdultConceptsT cell activation scoreT cell activation statusAdjusted hazard ratioPatient survivalHPV statusHazard ratioActivation statusActivation scoresKaplan-Meier survival curvesImmune checkpoint blockadeCox regression modelNeck squamous carcinomaPotential therapeutic targetT cell activationHNSCC patientsSquamous carcinomaPatient mortalityLonger survivalExhaustion groupsTherapeutic targetSurvival curvesSignificant associationMRNA expressionPatientsSurvivalBRCA1 mRNA expression modifies the effect of T cell activation score on patient survival in breast cancer
Lu L, Huang H, Zhou J, Ma W, Mackay S, Wang Z. BRCA1 mRNA expression modifies the effect of T cell activation score on patient survival in breast cancer. BMC Cancer 2019, 19: 387. PMID: 31023256, PMCID: PMC6482542, DOI: 10.1186/s12885-019-5595-3.Peer-Reviewed Original ResearchConceptsT cell activation statusCell activation statusPatient survivalT cell activationBreast cancerActivation statusCCND1 levelsCell activationT cell activation scoreCCND1 expressionKaplan-Meier survival curvesAdjusted hazard ratioCCND1 expression levelsBreast cancer patient survivalImmune checkpoint blockadeBetter overall survivalBreast cancer patientsCox regression modelCancer patient survivalT cell recognitionBRCA1 levelsBRCA1 mRNA expressionCheckpoint blockadeHazard ratioOverall survivalTen-Year Comparison Study of Type 1 and 2 Endometrial Cancers: Risk Factors and Outcomes
Feinberg J, Albright B, Black J, Lu L, Passarelli R, Gysler S, Whicker M, Altwerger G, Menderes G, Hui P, Santin AD, Azodi M, Silasi DA, Ratner ES, Litkouhi B, Schwartz PE. Ten-Year Comparison Study of Type 1 and 2 Endometrial Cancers: Risk Factors and Outcomes. Gynecologic And Obstetric Investigation 2019, 84: 290-297. PMID: 30602164, DOI: 10.1159/000493132.Peer-Reviewed Original ResearchConceptsType 2 cancerHormone replacement therapyCox regression modelType 2 diseaseRisk factorsEndometrial cancerType 1Use of HRTLess obese patientsBaseline risk factorsEndometrial cancer casesMajor cardiovascular diseasesObese patientsOral contraceptivesOverall survivalClinical courseDiabetes mellitusRetrospective reviewRegression modelsReplacement therapyCardiovascular diseaseCancer casesAdvanced stageHigh mortalityRecurrence
2018
Epithelial membrane protein 2: a novel biomarker for circulating tumor cell recovery in breast cancer
Chen Q, Yao L, Burner D, Minev B, Lu L, Wang M, Ma W. Epithelial membrane protein 2: a novel biomarker for circulating tumor cell recovery in breast cancer. Clinical And Translational Oncology 2018, 21: 433-442. PMID: 30218306, DOI: 10.1007/s12094-018-1941-1.Peer-Reviewed Original ResearchConceptsEpithelial membrane protein-2MDA-MB-231 cellsBreast cancerBreast cancer cellsNovel biomarkersMCF7 cellsCancer cellsAnti-pan cytokeratinPrimary breast cancerBreast cancer patientsMesenchymal transition eventsPatient blood samplesTumor cell recoveryFlow cytometric assayCTC countCancer patientsHealthy donorsBlood samplesMembrane protein 2Cytometric assayTumor cellsEMP2 expressionCancerCell spikingBiomarkersRandomized controlled trial of weight loss versus usual care on telomere length in women with breast cancer: the lifestyle, exercise, and nutrition (LEAN) study
Sanft T, Usiskin I, Harrigan M, Cartmel B, Lu L, Li FY, Zhou Y, Chagpar A, Ferrucci LM, Pusztai L, Irwin ML. Randomized controlled trial of weight loss versus usual care on telomere length in women with breast cancer: the lifestyle, exercise, and nutrition (LEAN) study. Breast Cancer Research And Treatment 2018, 172: 105-112. PMID: 30062572, DOI: 10.1007/s10549-018-4895-7.Peer-Reviewed Original ResearchConceptsBreast cancer survivorsWeight loss interventionUsual care groupBody mass indexBreast cancer riskCancer survivorsUsual careLoss interventionBreast cancerStage 0Quantitative polymerase chain reactionCare groupTelomere lengthCancer riskStage II/III breast cancerObese breast cancer survivorsWeight lossI breast cancerNon-Hispanic whitesPurposeSome studiesMass indexIntervention groupPhysical activityBlood samplesConclusionOur findingsGenome-wide association analysis identifies a meningioma risk locus at 11p15.5
Claus EB, Cornish AJ, Broderick P, Schildkraut JM, Dobbins SE, Holroyd A, Calvocoressi L, Lu L, Hansen HM, Smirnov I, Walsh KM, Schramm J, Hoffmann P, Nöthen MM, Jöckel KH, Swerdlow A, Larsen SB, Johansen C, Simon M, Bondy M, Wrensch M, Houlston RS, Wiemels JL. Genome-wide association analysis identifies a meningioma risk locus at 11p15.5. Neuro-Oncology 2018, 20: 1485-1493. PMID: 29762745, PMCID: PMC6176799, DOI: 10.1093/neuonc/noy077.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedBiomarkers, TumorCase-Control StudiesChromosomes, Human, Pair 11FemaleFollow-Up StudiesGenetic LociGenetic Predisposition to DiseaseGenome-Wide Association StudyGenotypeHumansLinkage DisequilibriumMaleMeningeal NeoplasmsMeningiomaMiddle AgedPolymorphism, Single NucleotidePrognosisRisk FactorsYoung AdultConceptsGenome-wide association studiesRisk lociGenome-wide association analysisSusceptibility lociNeural crest-derived structuresSignificant heritable basisNumber of genesIndependent sample seriesNew susceptibility lociHeritable basisGenetic basisGenome ProjectAssociation studiesAssociation analysisLinkage disequilibriumLociMeningioma developmentReference panelPolygenic modelCentral roleUK10K dataAdult brain tumorsRIC8AMeningeal coveringsGenesHigh tRNA Transferase NSUN2 Gene Expression is Associated with Poor Prognosis in Head and Neck Squamous Carcinoma
Lu L, Zhu G, Zeng H, Xu Q, Holzmann K. High tRNA Transferase NSUN2 Gene Expression is Associated with Poor Prognosis in Head and Neck Squamous Carcinoma. Cancer Investigation 2018, 36: 246-253. PMID: 29775108, DOI: 10.1080/07357907.2018.1466896.Peer-Reviewed Original ResearchConceptsPotential independent prognostic markerShorter overall survivalIndependent prognostic markerHigher mortality riskNeck squamous carcinomaPotential therapeutic targetRandom-effects modelOverall survivalSquamous carcinomaPoor prognosisPrognostic valuePrognostic markerMortality riskTherapeutic targetHNSCCNormal tissuesCell developmentExpressionGene expressionRNA methylationPatientsCarcinomaPrognosisNSUN2Important role
2017
Association of tRNA methyltransferase NSUN2/IGF-II molecular signature with ovarian cancer survival
Yang JC, Risch E, Zhang M, Huang C, Huang H, Lu L. Association of tRNA methyltransferase NSUN2/IGF-II molecular signature with ovarian cancer survival. Future Oncology 2017, 13: 1981-1990. PMID: 28829218, DOI: 10.2217/fon-2017-0084.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinoma, Clear CellAdenocarcinoma, MucinousAdultAgedAged, 80 and overBiomarkers, TumorCystadenocarcinoma, SerousEndometrial NeoplasmsFemaleFollow-Up StudiesHumansInsulin-Like Growth Factor IIMethyltransferasesMiddle AgedNeoplasm Recurrence, LocalOvarian NeoplasmsPrognosisSurvival RateConceptsOvarian cancer survivalIGF-IICancer survivalOvarian cancerDisease progression-free survivalMultivariate Cox regression modelProgression-free survivalRisk of deathCox regression modelIGF-II expressionClinical followSurvival analysisClinical implicationsIGFNormal tissuesHeterogeneous outcomesSurvivalCancerMolecular signaturesAssociationRegression modelsRNA sequencingSupNSUN2RelapseElevated T cell activation score is associated with improved survival of breast cancer
Lu L, Bai Y, Wang Z. Elevated T cell activation score is associated with improved survival of breast cancer. Breast Cancer Research And Treatment 2017, 164: 689-696. PMID: 28488141, DOI: 10.1007/s10549-017-4281-x.Peer-Reviewed Original ResearchConceptsT cell activation scoreBreast cancer patientsOverall survivalPatients' overall survivalCancer patientsImproved survivalPD-1Activation scoresBreast cancerCell death-1 receptorLow PD-1 expressionMultivariate Cox regression analysisT-lymphocyte antigen-4Kaplan-Meier survival curvesT cell activation statusDeath-1 receptorPD-1 expressionEffector T cellsImmune checkpoint blockadeCox regression analysisPoor overall survivalCox regression modelT cell functionActivation groupCell activation statusAspirin 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 prognosis