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1.
Cancer Med ; 11(6): 1573-1586, 2022 03.
Artigo em Inglês | MEDLINE | ID: mdl-35137551

RESUMO

Understanding the complex tumor microenvironment is key to the development of personalized therapies for the treatment of cancer including colorectal cancer (CRC). In the past decade, significant advances in the field of immunotherapy have changed the paradigm of cancer treatment. Despite significant improvements, tumor heterogeneity and lack of appropriate classification tools for CRC have prevented accurate risk stratification and identification of a wider patient population that may potentially benefit from targeted therapies. To identify novel signatures for accurate prognostication of CRC, we quantified gene expression of 12 immune-related genes using a medium-throughput NanoString quantification platform in 93 CRC patients. Multivariate prognostic analysis identified a combined four-gene prognostic signature (TGFB1, PTK2, RORC, and SOCS1) (HR: 1.76, 95% CI: 1.05-2.95, *p < 0.02). The survival trend was captured in an independent gene expression data set: GSE17536 (177 patients; HR: 3.31, 95% CI: 1.99-5.55, *p < 0.01) and GSE14333 (226 patients; HR: 2.47, 95% CI: 1.35-4.53, *p < 0.01). Further, gene set enrichment analysis of the TCGA data set associated higher prognostic scores with epithelial-mesenchymal transition (EMT) and inflammatory pathways. Comparatively, a lower prognostic score was correlated with oxidative phosphorylation and MYC and E2F targets. Analysis of immune parameters identified infiltration of T-reg cells, CD8+ T cells, M2 macrophages, and B cells in high-risk patient groups along with upregulation of immune exhaustion genes. This molecular study has identified a novel prognostic gene signature with clinical utility in CRC. Therefore, along with prognostic features, characterization of immune cell infiltrates and immunosuppression provides actionable information that should be considered while employing personalized medicine.


Assuntos
Linfócitos T CD8-Positivos , Neoplasias Colorretais , Linfócitos T CD8-Positivos/patologia , Neoplasias Colorretais/patologia , Regulação Neoplásica da Expressão Gênica , Humanos , Prognóstico , Microambiente Tumoral/genética
2.
PLoS One ; 15(10): e0240976, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33075099

RESUMO

The extensively employed limited-gene coverage NGS panels lead to clinically inadequate molecular profiling of myeloid neoplasms. The aim of the present investigation was to assess performance and clinical utility of a comprehensive DNA panel for myeloid neoplasms. Sixty-one previously well characterized samples were sequenced using TSO500 library preparation kit on NextSeq550 platform. Variants with a VAF ≥ 5% and a total read depth of >50X were filtered for analysis. The following results were recorded-for clinical samples: clinical sensitivity (97%), specificity (100%), precision (100%) and accuracy (99%) whereas reference control results were 100% for analytical sensitivity, specificity, precision and accuracy, with high intra- and inter-run reproducibility. The panel identified 880 variants across 292 genes, of which, 749 variants were in genes not covered in the 54 gene panel. The investigation revealed 14 variants in ten genes, and at least one was present in 96.2% patient samples that were pathogenic/ likely pathogenic in myeloid neoplasms. Also, 15 variants in five genes were found to be pathogenic/ likely pathogenic in other tumor types. Further, the TMB and MSI scores ranged from 0-7 and 0-9, respectively. The high analytical performance and clinical utility of this comprehensive NGS panel makes it practical and clinically relevant for adoption in clinical laboratories for routine molecular profiling of myeloid neoplasms.


Assuntos
Variação Genética , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Leucemia Mieloide/genética , Síndromes Mielodisplásicas/genética , Transtornos Mieloproliferativos/genética , Idoso , Análise Custo-Benefício , Feminino , Redes Reguladoras de Genes , Humanos , Masculino , Instabilidade de Microssatélites , Mutação , Análise de Sequência de DNA , Fatores de Tempo
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