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1.
Aging (Albany NY) ; 13(8): 11833-11859, 2021 04 22.
Artigo em Inglês | MEDLINE | ID: mdl-33885377

RESUMO

Transcriptome differences between Hodgkin's lymphoma (HL), diffuse large B-cell lymphoma (DLBCL), and mantle cell lymphoma (MCL), which are all derived from B cell, remained unclear. This study aimed to construct lymphoma-specific diagnostic models by screening lymphoma marker genes. Transcriptome data of HL, DLBCL, and MCL were obtained from public databases. Lymphoma marker genes were screened by comparing cases and controls as well as the intergroup differences among lymphomas. A total of 9 HL marker genes, 7 DLBCL marker genes, and 4 MCL marker genes were screened in this study. Most HL marker genes were upregulated, whereas DLBCL and MCL marker genes were downregulated compared to controls. The optimal HL-specific diagnostic model contains one marker gene (MYH2) with an AUC of 0.901. The optimal DLBCL-specific diagnostic model contains 7 marker genes (LIPF, CCDC144B, PRO2964, PHF1, SFTPA2, NTS, and HP) with an AUC of 0.951. The optimal MCL-specific diagnostic model contains 3 marker genes (IGLV3-19, IGKV4-1, and PRB3) with an AUC of 0.843. The present study reveals the transcriptome data-based differences between HL, DLBCL, and MCL, when combined with other clinical markers, may help the clinical diagnosis and prognosis.


Assuntos
Biomarcadores Tumorais/genética , Doença de Hodgkin/diagnóstico , Linfoma Difuso de Grandes Células B/diagnóstico , Linfoma de Célula do Manto/diagnóstico , Modelos Genéticos , Estudos de Casos e Controles , Conjuntos de Dados como Assunto , Diagnóstico Diferencial , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Doença de Hodgkin/genética , Doença de Hodgkin/mortalidade , Humanos , Linfoma Difuso de Grandes Células B/genética , Linfoma Difuso de Grandes Células B/mortalidade , Linfoma de Célula do Manto/genética , Linfoma de Célula do Manto/mortalidade , Estadiamento de Neoplasias , Prognóstico , Intervalo Livre de Progressão , Transcriptoma/genética
2.
Oncol Rep ; 45(3): 1235-1248, 2021 03.
Artigo em Inglês | MEDLINE | ID: mdl-33650672

RESUMO

Breast cancer is the most common type of cancer amongst women worldwide, and numerous microRNAs (miRNAs/miRs) are involved in the initiation and progression of breast cancer. The aim of the present study was to identify hub miRNAs and determine the underlying mechanisms regulated by these miRNAs in breast cancer. Breast invasive carcinoma transcriptome data (including mRNAs and miRNAs), and clinical data were acquired from The Cancer Genome Atlas database. Differential gene expression analysis, co­expression network analysis, gene set enrichment analysis (GSEA) and prognosis analysis were used to screen the hub miRNAs and explore their functions. Functional experiments were used to determine the underlying mechanisms of the hub miRNAs in breast cancer cells. The results revealed that low miR150 expression predicted a more advanced disease stage, and was associated with a less favorable prognosis. Through the combined use of five miRNA­target gene prediction tools, 31 potential miR150 target genes were identified. GSEA revealed that low miR150 expression was associated with the upregulation of several cancer­associated signaling pathways, and the downregulation of several tumor suppressor genes. Furthermore, miR150 independently affected overall survival in patients, and interacted with its target genes to indirectly affect overall and disease­free survival. Functional experiments demonstrated that miR150 positively regulated B and T lymphocyte attenuator (BTLA), and the downregulation of miR150 and BTLA combined promoted cell migration. In conclusion, the present study revealed that low miR150 expression was associated with less favorable clinical features, upregulation of several carcinogenic signaling pathways, and poor patient survival. Additionally, a miR150­BTLA axis was suggested to regulate cell viability and migration.


Assuntos
Neoplasias da Mama/genética , Carcinogênese/genética , MicroRNAs/genética , Neoplasias da Mama/mortalidade , Neoplasias da Mama/patologia , Carcinogênese/patologia , Linhagem Celular Tumoral , Movimento Celular , Sobrevivência Celular , Feminino , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Humanos , MicroRNAs/metabolismo , Prognóstico , Receptores Imunológicos/genética , Receptores Imunológicos/metabolismo , Transdução de Sinais , Análise de Sobrevida
3.
Oncotarget ; 8(4): 6775-6786, 2017 Jan 24.
Artigo em Inglês | MEDLINE | ID: mdl-28036274

RESUMO

Breast cancer is the most commonly diagnosed malignancy in women. Several key genes and pathways have been proven to correlate with breast cancer pathology. This study sought to explore the differences in key transcription factors (TFs), transcriptional regulation networks and dysregulated pathways in different tissues in breast cancer. We employed 14 breast cancer datasets from NCBI-GEO and performed an integrated analysis in three different tissues including breast, blood and saliva. The results showed that there were eight genes (CEBPD, EGR1, EGR2, EGR3, FOS, FOSB, ID1 and NFIL3) down-regulated in breast tissue but up-regulated in blood tissue. Furthermore, we identified several unreported tissue-specific TFs that may contribute to breast cancer, including ATOH8, DMRT2, TBX15 and ZNF367. The dysregulation of these TFs damaged lipid metabolism, development, cell adhesion, proliferation, differentiation and metastasis processes. Among these pathways, the breast tissue showed the most serious impairment and the blood tissue showed a relatively moderate damage, whereas the saliva tissue was almost unaffected. This study could be helpful for future biomarker discovery, drug design, and therapeutic and predictive applications in breast cancers.


Assuntos
Biomarcadores Tumorais/genética , Neoplasias da Mama/genética , Biologia Computacional/métodos , Mineração de Dados/métodos , Perfilação da Expressão Gênica/métodos , Fatores de Transcrição/genética , Transcriptoma , Algoritmos , Biomarcadores Tumorais/sangue , Neoplasias da Mama/sangue , Neoplasias da Mama/patologia , Bases de Dados Genéticas , Feminino , Regulação Neoplásica da Expressão Gênica , Redes Reguladoras de Genes , Predisposição Genética para Doença , Humanos , Análise de Sequência com Séries de Oligonucleotídeos , Fenótipo , Saliva/metabolismo , Transdução de Sinais/genética , Fatores de Transcrição/sangue
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