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Evaluation of Low Coverage Whole Genome Sequencing as a New Method for Detecting Malignant Ovarian Mass

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Abstract To evaluate whether low coverage whole genome sequencing is suitable for the detection of malignant pelvic mass and compare its diagnostic value with traditional tumor markers. We enrolled 63 patients with a pelvic mass suspicious for ovarian malignancy. Each patient underwent low coverage whole genome sequencing (LCWGS) and traditional tumor markers test. The pelvic masses were finally confirmed via pathological examination. The copy number variants (CNVs) of whole genome were detected and the Stouffers Z-scores for each CNV was extracted. The risk of malignancy (RM) of each suspicious sample was calculated based on the CNV counts and Z-scores, which was subsequently compared with ovarian cancer markers CA125 and HE4, and the risk of ovarian malignancy algorithm (ROMA). Receiver Operating Characteristic Curve (ROC) were used to access the diagnostic value of variables. As confirmed by pathological diagnosis, 44 (70%) patients with malignancy and 19 patients with benign mass were identified. Our results showed that CA125 and HE4, the CNV, the mean of Z-scores (Zmean), the max of Z-scores (Zmax), the RM and the ROMA were significantly different between patients with malignant and benign masses. The area under curve ( AUC) of CA125, HE4, CNV, Zmax, and Zmean was 0.775, 0.866, 0.786, 0.685 and 0.725 respectively. ROMA and RM showed similar AUC (0.876 and 0.837), but differed in sensitivity and specificity. After all, we develop a LCWGS based method for the identification of pelvic mass of suspicious ovarian cancer. LCWGS shows accurate result and could be complementary with the existing diagnostic methods.
Title: Evaluation of Low Coverage Whole Genome Sequencing as a New Method for Detecting Malignant Ovarian Mass
Description:
Abstract To evaluate whether low coverage whole genome sequencing is suitable for the detection of malignant pelvic mass and compare its diagnostic value with traditional tumor markers.
We enrolled 63 patients with a pelvic mass suspicious for ovarian malignancy.
Each patient underwent low coverage whole genome sequencing (LCWGS) and traditional tumor markers test.
The pelvic masses were finally confirmed via pathological examination.
The copy number variants (CNVs) of whole genome were detected and the Stouffers Z-scores for each CNV was extracted.
The risk of malignancy (RM) of each suspicious sample was calculated based on the CNV counts and Z-scores, which was subsequently compared with ovarian cancer markers CA125 and HE4, and the risk of ovarian malignancy algorithm (ROMA).
Receiver Operating Characteristic Curve (ROC) were used to access the diagnostic value of variables.
As confirmed by pathological diagnosis, 44 (70%) patients with malignancy and 19 patients with benign mass were identified.
Our results showed that CA125 and HE4, the CNV, the mean of Z-scores (Zmean), the max of Z-scores (Zmax), the RM and the ROMA were significantly different between patients with malignant and benign masses.
The area under curve ( AUC) of CA125, HE4, CNV, Zmax, and Zmean was 0.
775, 0.
866, 0.
786, 0.
685 and 0.
725 respectively.
ROMA and RM showed similar AUC (0.
876 and 0.
837), but differed in sensitivity and specificity.
After all, we develop a LCWGS based method for the identification of pelvic mass of suspicious ovarian cancer.
LCWGS shows accurate result and could be complementary with the existing diagnostic methods.

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