Yi Zhu

Proteomic landscape of epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is a deadly disease with limited diagnostic biomarkers and therapeutic targets. Here we conduct a comprehensive proteomic profiling of ovarian tissue and plasma samples from 813 patients with different histotypes and therapeutic regimens, covering the expression of 10,715 proteins. We identify eight proteins associated with tumor malignancy in the tissue specimens, which are further validated as potential circulating biomarkers in plasma. Targeted proteomics assays are developed for 12 tissue proteins and 7 blood proteins, and machine learning models are constructed to predict one-year recurrence, which are validated in an independent cohort. These findings contribute to the understanding of EOC pathogenesis and provide potential biomarkers for early detection and monitoring of the disease. Additionally, by integrating mutation analysis with proteomic data, we identify multiple proteins related to DNA damage in recurrent resistant tumors, shedding light on the molecular mechanisms underlying treatment resistance. This study provides a multi-histotype proteomic landscape of EOC, advancing our knowledge for improved diagnosis and treatment strategies.

Preoperative identification from occult leiomyosarcomas in laparoscopic hysterectomy and laparoscopic myomectomy: accuracy of the ultrasound scoring system (PRESS-US)

To assess the diagnostic performance and inter-observer agreement of a PREoperative sarcoma scoring based on ultrasound (PRESS-US) in differentiating uterine leiomyosarcoma (uLMS) from leiomyoma (LM). We conducted a retrospective evaluation of patients who underwent surgery and received standardized ultrasound examinations due to the presence of uterine myoma-like masses. Histological diagnosis was used as the reference standard. The masses were analyzed using morphological uterus sonographic assessment criteria, and the diagnostic accuracy of PRESS-US was evaluated using ROC curve analysis. Kappa (κ) statistics were used to assess the inter-observer agreement between a less experienced and an expert radiologist. Among the 646 patients, 632 (97.8%) were diagnosed with LM, and 14 (2.2%) had uLMS. The malignancy rates for low-risk and high-risk patients were 0.35% and 13.48%, respectively. The optimal PRESS-US cutoff was 17.5, resulting in an AUC of 89.7% (95% CI, 0.79-1.00), with a sensitivity of 85.7% and a specificity of 87.8%. The inter-observer agreement between a less experienced and an expert radiologist was excellent (κ = 0.811, P < 0.001). PRESS-US provides effective risk stratification for uLMS for radiologists with different levels of experience, with high reliability. Subgrouping high-risk patients helps in better risk stratification.

Resistance prediction in high‐grade serous ovarian carcinoma with neoadjuvant chemotherapy using data‐independent acquisition proteomics and an ovary‐specific spectral library

High‐grade serous ovarian carcinoma (HGSOC) is the most common subtype of ovarian cancer with 5‐year survival rates below 40%. Neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) is recommended for patients with advanced‐stage HGSOC unsuitable for primary debulking surgery (PDS). However, about 40% of patients receiving this treatment exhibited chemoresistance of uncertain molecular mechanisms and predictability. Here, we built a high‐quality ovary‐specific spectral library containing 130 735 peptides and 10 696 proteins on Orbitrap instruments. Compared to a published DIA pan‐human spectral library (DPHL), this spectral library provides 10% more ovary‐specific and 3% more ovary‐enriched proteins. This library was then applied to analyze data‐independent acquisition (DIA) data of tissue samples from an HGSOC cohort treated with NACT, leading to 10 070 quantified proteins, which is 9.73% more than that with DPHL. We further established a six‐protein classifier by parallel reaction monitoring (PRM) to effectively predict the resistance to additional chemotherapy after IDS (Log‐rank test, P  = 0.002). The classifier was validated with 57 patients from an independent clinical center ( P  = 0.014). Thus, we have developed an ovary‐specific spectral library for targeted proteome analysis, and propose a six‐protein classifier that could potentially predict chemoresistance in HGSOC patients after NACT‐IDS treatment.

The impact of Pegylated liposomal doxorubicin in recurrent ovarian cancer: an updated meta-analysis of randomized clinical trials

Abstract Background Previous meta-analysis studies suggested that pegylated liposomal doxorubicin (PLD) may improve the survival rate of patients with recurrent ovarian cancer. The aim of the present meta-analysis, then, was to further update the role of PLD in the treatment of recurrent ovarian cancer. Methods We performed a literature search using the electronic databases Medicine, EMBASE, Web of Science, and the Cochrane Library to 27 July 2020. We only restricted the randomized clinical trials. Study-specific hazard ratios and 95% confidence interval (HR/95% CI) and risk ratios and 95% confidence interval (RR/95% CI) were pooled using a random-effects model. Results Ten studies (12 trials) were included after screening 940 articles. We categorized the eligible studies into two groups: the doublet regimens (four trials, 1767 patients) showed that PLD plus carbo provided superior progression-free survival (PFS) (HR, 0.85; 95% CI, 0.74–0.97) and similar overall survival (OS) (HR, 1.00; 95% CI, 0.88–1.14) compared to paclitaxel (PAC) plus carboplatin (carbo). PLD plus carbo was associated with significantly more anemia and thrombocytopenia, and other side effects were well tolerated. The monotherapy regimens (eight trials, 1980 patients) showed that PLD possessed a similar PFS (HR, 1.02; 95% CI, 0.90–1.16) and OS (HR, 0.88; 95% CI, 0.77–1.01) relative to other monotherapies. PLD alone was also more associated with mucositis/stomatitis and hand-foot syndrome, while other side effects were well tolerated. Conclusions In platinum-sensitive recurrent ovarian cancer, PLD plus carbo was more effective than PAC plus carbo, while in platinum-resistant or -refractory recurrent ovarian cancer, PLD exhibited similar survival to other monotherapies. Regarding side effects, PLD plus carbo and mono chemotherapy were both well tolerated.

Accuracy of transvaginal sonoelastography for differential diagnosis between malignant and benign cervical lesions: A systematic review and meta‐analysis

AbstractBackgroundTo evaluate the performance of transvaginal sonoelastography (TVSE) for differential diagnosis between malignant and benign cervical lesions using a meta‐analysis.MethodsAn independent literature search was conducted on the English medical database, including PubMed, Embase and Medline, Cochrane Library, Web of Science, and OVID. The diagnostic accuracy of TVSE was compared with that of histopathology, which is the gold reference standard for diagnosis. The accuracy of TVSE was assessed by calculating the pooled sensitivity, specificity, diagnostic odds ratio, and area under the curve (AUC). The imaging mechanisms, assessment methods, and QUADAS scores were assessed with a meta‐regression analysis. A Deeks funnel plot was performed for evaluating publication bias.ResultsSix eligible studies reported a total sample of 615 cervical lesions (415 cancers, 200 benign lesions). TVSE showed a pooled diagnostic odds ratio of 21.42 (95% CI 13.65‐33.61), sensitivity of 0.87 (95% CI 0.84‐0.90), specificity of 0.79 (95% CI 0.72‐0.84), and an AUC of 0.892 (Q* = 0.822). The results of the meta‐regression analysis showed that the imaging mechanism (P = .253), the assessment method (P = .279), or QUADAS score (P = .205) did not affect the study heterogeneity.ConclusionTVSE has a relatively high and satisfactory value for differential diagnosis between malignant and benign cervical lesions. The diagnostic performance of strain elastography and shear wave elastography were similar and good. However, to accommodate heterogeneity and publication bias, high‐quality studies are required to further comparative effectiveness analyses to verify the efficacy of ultrasound detection.