J 2021

OCaMIR-A Noninvasive, Diagnostic Signature for Early-Stage Ovarian Cancer: A Multi-cohort Retrospective and Prospective Study

KANDIMALLA, R., W. WANG, F. YU, N. X. ZHOU, F. GAO et. al.

Základní údaje

Originální název

OCaMIR-A Noninvasive, Diagnostic Signature for Early-Stage Ovarian Cancer: A Multi-cohort Retrospective and Prospective Study

Autoři

KANDIMALLA, R., W. WANG, F. YU, N. X. ZHOU, F. GAO, M. SPILLMAN, Lucie MOUKOVÁ (203 Česká republika), Ondřej SLABÝ (203 Česká republika, domácí), B. SALHIA, S. T. ZHOU, X. WANG (garant) a A. GOEL

Vydání

Clinical cancer research, Philadelphia, AMER ASSOC CANCER RESEARCH, 2021, 1078-0432

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30204 Oncology

Stát vydavatele

Slovinsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Impakt faktor

Impact factor: 13.801

Kód RIV

RIV/00216224:14110/21:00124276

Organizační jednotka

Lékařská fakulta

UT WoS

000680860800017

Klíčová slova anglicky

OCaMIR; Early-Stage Ovarian Cancer

Štítky

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 28. 2. 2022 07:26, Mgr. Tereza Miškechová

Anotace

V originále

Purpose Due to the lack of effective screening approaches and early detection biomarkers, ovarian cancer has the highest mortality rates among gynecologic cancers. Herein, we undertook a systematic biomarker discovery and validation approach to identify microRN A (mi RNA) biomarkers for the early detection of ovarian cancer. Experimental Design: During the discovery phase, we performed small RNA sequencing in stage I high-grade serous ovarian cancer (n = 31), which was subsequently validated in multiple, independent data sets (TCGA, n = 543; GSE65819, n = 87). Subsequently, we performed multivariate logistic regressionbased training in a serum data set (GSE106817, n = 640), followed by its independent validation in three retrospective data sets (GSE31568, n = 85; GSE113486, n = 140; Czech Republic cohort, n = 192) and one prospective serum cohort (n = 95). In addition, we evaluated the specificity of OCaMIR, by comparing its performance in several other cancers (GSE31568 cohort, n = 369). Results: The OCalvIIR demonstrated a robust diagnostic accuracy in the stage I high-grade serous ovarian cancer patients in the discovery cohort (AUC = 0.99), which was consistently reproducible in both stage ] (AUC = 0.96) and all stage patients (AUC - 0.89) in the TCGA cohort. Logistic regression-based training and validation of OCaMIR achieved AUC values of 0.89 (GSE106817), 0.85 (GSE31568), 0.86 (GSE113486), and 0.82 (Czech Republic cohort) in the retrospective serum validation cohorts, as well as prospective validation cohort (AUC = 0.92). More importantly, OCaMIR demonstrated a significantly superior diagnostic performance compared with CA125 levels, even in stage I patients, and was more cost-effective, highlighting its potential role for screening and early detection of ovarian cancer. Conclusions: Small RNA sequencing identified a robust noninvasive miRNA signature for early-stage serous ovarian cancer detection.