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
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.