2020
Somatic mutation distributions in cancer genomes vary with three-dimensional chromatin structure
Akdemir K, Le V, Kim J, Killcoyne S, King D, Lin Y, Tian Y, Inoue A, Amin S, Robinson F, Nimmakayalu M, Herrera R, Lynn E, Chan K, Seth S, Klimczak L, Gerstung M, Gordenin D, O’Brien J, Li L, Deribe Y, Verhaak R, Campbell P, Fitzgerald R, Morrison A, Dixon J, Andrew Futreal P. Somatic mutation distributions in cancer genomes vary with three-dimensional chromatin structure. Nature Genetics 2020, 52: 1178-1188. PMID: 33020667, PMCID: PMC8350746, DOI: 10.1038/s41588-020-0708-0.Peer-Reviewed Original ResearchConceptsCancer genomesMutational processesGenome organizationThree-dimensional genome organizationThree-dimensional chromatin structureSomatic mutationsSpatial genome organizationMutation rate variationDifferent human cancer typesDifferent mutational processesWhole-genome datasetsActive mutational processesSpecific mutational processesChromatin structureHuman cancer typesMutation distributionInactive domainsDevelopment of cancerDriver genesGenomeMutational loadActive domainHuman cancersMutationsNovel therapeutic strategies
2013
Transcription factor-pathway coexpression analysis reveals cooperation between SP1 and ESR1 on dysregulating cell cycle arrest in non-hyperdiploid multiple myeloma
Wang X, Yan Z, Fulciniti M, Li Y, Gkotzamanidou M, Amin S, Shah P, Zhang Y, Munshi N, Li C. Transcription factor-pathway coexpression analysis reveals cooperation between SP1 and ESR1 on dysregulating cell cycle arrest in non-hyperdiploid multiple myeloma. Leukemia 2013, 28: 894-903. PMID: 23925045, PMCID: PMC4155324, DOI: 10.1038/leu.2013.233.Peer-Reviewed Original ResearchConceptsCell cycle arrestCycle arrestCoexpression analysisCell cycle arrest genesHyperdiploid MMCell cycle arrest pathwaysNon-hyperdiploid multiple myelomaDistinct chromosomal alterationsMyeloma subtypeMultiple myelomaTranscription factorsArrest pathwaysSp1Low coexpressionProper regulationHuman cancersDifferent survival outcomesChromosomal alterationsPlasma B cellsCoexpressionCell linesNovel hypothesisSurvival outcomesMyeloma proliferationClinical utility
2012
Integrative analysis of gene and miRNA expression profiles with transcription factor–miRNA feed-forward loops identifies regulators in human cancers
Yan Z, Shah P, Amin S, Samur M, Huang N, Wang X, Misra V, Ji H, Gabuzda D, Li C. Integrative analysis of gene and miRNA expression profiles with transcription factor–miRNA feed-forward loops identifies regulators in human cancers. Nucleic Acids Research 2012, 40: e135-e135. PMID: 22645320, PMCID: PMC3458521, DOI: 10.1093/nar/gks395.Peer-Reviewed Original ResearchConceptsFeed-forward loopTranscription factorsMiRNA expression profilesExpression profilesNovel feed-forward loopCancer-related transcription factorsExpression dataTF target genesMiRNA-mRNA interactionsCommon target genesMiR-15/miRMiRNA expression dataMiRNA partnersTranscriptome changesTarget genesDifferential genesIntegrative analysisMultiple cancer typesGenesMiRNA expressionHuman cancersLiterature validationBiological conditionsMiRNAsRegulator