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A prognostic model for ovarian neoplasms established by an integrated analysis of 1580 transcriptomic profiles.
Hua, Yanjiao; Cai, Du; Shirley, Cole Andrea; Mo, Sien; Chen, Ruyun; Gao, Feng; Chen, Fangying.
Afiliação
  • Hua Y; The Reproductive Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, China.
  • Cai D; Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510655, China.
  • Shirley CA; Guangdong Institute of Gastroenterology, Guangzhou, 510655, Guangdong Province, China.
  • Mo S; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510655, Guangdong Province, China.
  • Chen R; Sun Yat-Sen University, Guangzhou, 510080, Guangdong Province, People's Republic of China.
  • Gao F; The Reproductive Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, China.
  • Chen F; Sun Yat-Sen University, Guangzhou, 510080, Guangdong Province, People's Republic of China.
Sci Rep ; 13(1): 19429, 2023 11 08.
Article em En | MEDLINE | ID: mdl-37940688
ABSTRACT
Even after debulking surgery combined with chemotherapy or new adjuvant chemotherapy paired with internal surgery, the average year of disease free survival in advanced ovarian cancer was approximately 1.7 years1. The development of a molecular predictor of early recurrence would allow for the identification of ovarian cancer (OC) patients with high risk of relapse. The Ovarian Cancer Disease Free Survival Predictor (ODFSP), a predictive model constructed from a special set of 1580 OC tumors in which gene expression was assessed using both microarray and sequencing platforms, was created by our team. To construct gene expression barcodes that were resistant to biases caused by disparate profiling platforms and batch effects, we employed a meta-analysis methodology that was based on the binary gene pair technique. We demonstrate that ODFSP is a reliable single-sample predictor of early recurrence (1 year or less) using the largest pool of OC transcriptome data sets available to date. The ODFSP model showed significantly high prognostic value for binary recurrence prediction unaffected by clinicopathologic factors, with a meta-estimate of the area under the receiver operating curve of 0.64 (P = 4.6E-05) and a D-index (robust hazard ratio) of 1.67 (P = 9.2E-06), respectively. GO analysis of ODFSP's 2040 gene pairs (collapsed to 886 distinct genes) revealed the involvement in small molecular catabolic process, sulfur compound metabolic process, organic acid catabolic process, sulfur compound biosynthetic process, glycosaminoglycan metabolic process and aminometabolic process. Kyoto encyclopedia of genes and genomes pathway analysis of ODFSP's signature genes identified prominent pathways that included cAMP signaling pathway and FoxO signaling pathway. By identifying individuals who might benefit from a more aggressive treatment plan or enrolment in a clinical trial but who will not benefit from standard surgery or chemotherapy, ODFSP could help with treatment decisions.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Ovarianas / Transcriptoma Limite: Female / Humans Idioma: En Revista: Sci Rep Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Ovarianas / Transcriptoma Limite: Female / Humans Idioma: En Revista: Sci Rep Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China