Objective: To utilize low-coverage whole genome sequencing technology for the analysis of chromosomal instability (CIN) in endometrial cytology and to enhance the accuracy of early diagnosis and screening for endometrial cancer.Methods: We collected 45 endometrial cytology specimens, which included 21 endometrial cancer specimens, 1 specimen of endometrial atypical hyperplasia (pre-cancer), 13 specimens of benign endometrial lesions, and 10 specimens from patients with normal endometrium.These Leather Coasters specimens were analyzed using low-coverage next-generation sequencing technology.
The results were compared to the gold standard of pathological diagnosis.Diagnostic models were constructed based on genome-wide chromosomal-arm-level copy number alterations (CNAs) and mutations.We calculated sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) to assess diagnostic performance.
Results: CIN was detected in all endometrial cytology specimens at the level of multiple CNAs and mutations.Endometrial carcinoma was set as positive, while normal, benign lesions and endometrial atypical hyperplasia were set as negative.- For CNAs (one or more chromosome arms): Sensitivity was 76.
2 % (16/21), specificity was 100 % (24/24), accuracy was 88.9 % (40/45), PPV was 100 % (16/16), and NPV was 82.8 % (24/29).
- For mutations: Sensitivity was 81.0 % (17/21), specificity was 100 % (24/24), PPV was 100 % (17/17), NPV was 85.8 % (24/28), and accuracy was 91.
1 % (41/45).Combining CNAs and mutations: Sensitivity was 95.2 % (20/21), specificity was 100 % (24/24), PPV was 100 % Badges (20/20), NPV was 96.
0 % (24/25), and accuracy was 97.8 % (44/45).Conclusion: The detection of chromosomal instability (CIN) in endometrial cytology specimens is a viable first-line method for the screening of endometrial cancer.
This approach can enhance early diagnosis and improve patient outcomes by enabling more timely and accurate identification of malignancies.