Literature DB >> 33016563

High-grade serous peritoneal cancer follows a high stromal response signature and shows worse outcome than ovarian cancer.

Francis Jacob1, Rosa Lina Marchetti2, André B Kind2, Kenneth Russell3, Andreas Schoetzau1, Viola A Heinzelmann-Schwarz1,2.   

Abstract

In the era of personalized medicine, where transition from organ-based to individualized genetic diagnosis takes place, the tailoring of treatment in cancer becomes increasingly important. This is particularly true for high-grade, advanced FIGO stage serous adenocarcinomas of the ovary (OC), fallopian tube (TC), and peritoneum (PC), which are currently all treated identically. We analyzed three independent patient cohorts using histopathologically classified diagnosis and various molecular approaches (transcriptomics, immunohistochemistry, next-generation sequencing, fluorescent and chromogenic in situ hybridization). Using multivariate Cox regression model, we found that PC is more aggressive compared with advanced-stage OC independent of residual disease as shown by an earlier relapse-free survival in two large cohorts (HR: 2.63, CI: 1.59-4.37, P < 0.001, and HR: 1.66, CI: 1.04-2.63, P < 0.033). In line with these findings, transcriptomic data revealed differentially expressed gene signatures identifying PC as high stromal response tumors. The third independent cohort (n = 4054) showed a distinction between these cancer types for markers suggested to be predictive for chemotherapy drug response. Our findings add additional evidence that ovarian and peritoneal cancers are epidemiologically and molecularly distinct diseases. Moreover, our data also suggest consideration of the tumor-sampling site for future diagnosis and treatment decisions.
© 2020 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.

Entities:  

Keywords:  gene signature; metastasis; ovarian cancer; peritoneal cancer; predictive biomarker

Year:  2020        PMID: 33016563      PMCID: PMC7782088          DOI: 10.1002/1878-0261.12811

Source DB:  PubMed          Journal:  Mol Oncol        ISSN: 1574-7891            Impact factor:   6.603


  47 in total

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Authors:  C S Park; T-K Kim; H G Kim; Y-J Kim; M H Jeoung; W R Lee; N K Go; K Heo; S Lee
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9.  curatedOvarianData: clinically annotated data for the ovarian cancer transcriptome.

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Journal:  PLoS One       Date:  2014-04-14       Impact factor: 3.240

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  1 in total

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