Dataset Information

Prognostic value of the TCGA molecular classification in uterine carcinosarcoma.

ABSTRACT:

Background

The TCGA molecular groups of endometrial carcinoma are "POLE-mutated" (POLEmut), "microsatellite-instable/mismatch repair-deficient" (MSI/MMRd), "TP53-mutated/p53-abnormal" (TP53mut/p53abn), and "no specific molecular profile" (NSMP).

Objective

Prognostic assessment of the TCGA groups in uterine carcinosarcoma (UCS).

Search strategy

Systematic review from January 2000 to January 2021.

Selection criteria

Studies assessing the TCGA groups in UCS.

Data collection and analysis

Progression-free survival (PFS) and overall survival (OS) were assessed by Kaplan-Meier and Cox analyses (reference: TP53mut/p53abn group) and compared with endometrioid and serous carcinomas (original TCGA cohort), with a significant P < 0.050.

Main results

Five studies with 263 UCS were included. Compared with TP53mut/p53abn UCS, MSI/MMRd UCS showed significantly better PFS (P < 0.001) but similar OS (P = 0.788), whereas NSMP UCS showed similar PFS (P = 0.936) and OS (P = 0.240). Compared with their endometrioid/serous counterparts, NSMP and TP53mut/p53abn UCS showed significantly worse PFS (P < 0.001 and P = 0.004) and OS (P < 0.001 and P < 0.001), while MSI/MMRd UCS showed similar PFS (P = 0.595) but significantly worse OS (P < 0.001). The POLEmut group showed neither recurrences nor deaths in both the UCS and the endometrioid/serous carcinoma cohorts.

Conclusion

POLEmut UCS show excellent prognosis, whereas TP53mut/p53abn and NSMP UCS show a prognosis even worse than that of TP53mut/p53abn endometrioid/serous carcinomas. The prognosis of MSI/MMRd UCS remains to be defined.

SUBMITTER: Travaglino A

PROVIDER: S-EPMC9292561 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prognostic value of the TCGA molecular classification in uterine carcinosarcoma.

Travaglino Antonio A Raffone Antonio A Raimondo Diego D Arciuolo Damiano D Angelico Giuseppe G Valente Michele M Scaglione Giulia G D'alessandris Nicoletta N Casadio Paolo P Inzani Frediano F Mollo Antonio A Santoro Angela A Seracchioli Renato R Franco Zannoni Gian G

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics 20211011 1

<h4>Background</h4>The TCGA molecular groups of endometrial carcinoma are "POLE-mutated" (POLEmut), "microsatellite-instable/mismatch repair-deficient" (MSI/MMRd), "TP53-mutated/p53-abnormal" (TP53mut/p53abn), and "no specific molecular profile" (NSMP).<h4>Objective</h4>Prognostic assessment of the TCGA groups in uterine carcinosarcoma (UCS).<h4>Search strategy</h4>Systematic review from January 2000 to January 2021.<h4>Selection criteria</h4>Studies assessing the TCGA groups in UCS.<h4>Data col ...[more]

PMID: 34536971

Similar Datasets

Project description:ImportanceThe risk stratification of adrenocortical carcinoma (ACC) based on tumor proliferation index and stage is limited. Adjuvant therapy after surgery is recommended for most patients. Pan-genomic studies have identified distinct molecular groups closely associated with outcome.ObjectiveTo compare the molecular classification for prognostic assessment of ACC with other known prognostic factors.Design, setting, and participantsIn this retrospective biomarker analysis, ACC tumor samples from 368 patients who had undergone surgical tumor removal were collected from March 1, 2005, to September 30, 2015 (144 in the training cohort and 224 in the validation cohort) at 21 referral centers with a median follow-up of 35 months (interquartile range, 18-74 months). Data were analyzed from March 2016 to March 2018.ExposuresMeta-analysis of pan-genomic studies (transcriptome, methylome, chromosome alteration, and mutational profiles) was performed on the training cohort. Targeted biomarker analysis, including targeted gene expression (BUB1B and PINK1), targeted methylation (PAX5, GSTP1, PYCARD, and PAX6), and targeted next-generation sequencing, was performed on the training and validation cohorts.Main outcomes and measuresDisease-free survival. Cox proportional hazards regression and C indexes were used to assess the prognostic value of each model.ResultsOf the 368 patients (mean [SD] age, 49 [16] years), 144 were in the training cohort (100 [69.4%] female) and 224 were in the validation cohort (142 [63.4%] female). In the training cohort, pan-genomic measures classified ACC into 3 molecular groups (A1, A2, and A3-B), with 5-year survival of 9% for group A1, 45% for group A2, and 82% for group A3-B (log-rank P < .001). Molecular class was an independent prognostic factor of recurrence in stage I to III ACC after complete surgery (hazard ratio, 55.91; 95% CI, 8.55-365.40; P < .001). The combination of European Network for the Study of Adrenal Tumors (ENSAT) stage, tumor proliferation index, and molecular class provided the most discriminant prognostic model (C index, 0.88). In the validation cohort, the molecular classification, determined by targeted biomarker measures, was confirmed as an independent prognostic factor of recurrence (hazard ratio, 5.96 [95% CI, 1.81-19.58], P = .003 for the targeted classifier combining expression, methylation, and chromosome alterations; and 2.61 [95% CI, 1.31-5.19], P = .006 for the targeted classifier combining methylation, chromosome alterations, and mutational profile). The prognostic value of the molecular markers was limited for patients with stage IV ACC.Conclusions and relevanceThe findings suggest that in localized ACC, targeted classifiers may be used as independent markers of recurrence. The determination of molecular class may improve individual prognostic assessment and thus may spare unnecessary adjuvant treatment.

Dataset Information

Prognostic value of the TCGA molecular classification in uterine carcinosarcoma.

Background

Objective

Search strategy

Selection criteria

Data collection and analysis

Main results

Conclusion

Publications

Prognostic value of the TCGA molecular classification in uterine carcinosarcoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets