PurposeLymph node (LN) involvement is a key factor in ovarian clear cell carcinoma (OCCC) although, there several indicators can be used to define prognosis. This study examines the prognostic performances of each indicator for OCCC patients by comparing the number of lymph nodes examined (TNLE), the number of positive lymph nodes (PLN), lymph node ratio (LNR), and log odds of metastatic lymph nodes (LODDS).Methods1,300 OCCC patients who underwent lymphadenectomy between 2004 and 2015 were extracted from the Surveillance Epidemiology and End Results (SEER) database. Primary outcomes were Overall Survival (OS) and the cumulative incidence of Cancer-Specific Survival (CSS). Kaplan–Meier’s and Fine-Gray’s tests were implemented to assess OS and CSS rates. After conducting multivariate analysis, nomograms using OS and CSS were constructed based upon an improved LN system. Each nomograms’ performance was assessed using Receiver Operating Characteristics (ROC) curves, calibration curves, and the C-index which were compared to traditional cancer staging systems.ResultsMultivariate Cox’s regression analysis was used to assess prognostic factors for OS, including age, T stage, M stage, SEER stage, and LODDS. To account for the CSS endpoint, a proportional subdistribution hazard model was implemented which suggested that the T stage, M stage, SEER stage, and LNR are all significant. This enabled us to develop a LODDS-based nomogram for OS and a LNR-based nomogram for CSS. C-indexes for both the OS and CSS nomograms were higher than the traditional American Joint Committee on Cancer (AJCC), 8th edition, staging system. Area Under the Curve (AUC) values for predicting 3- and 5-year OS and CSS between nomograms also highlighted an improvement upon the AJCC staging system. Calibration curves also performed with consistency, which was verified using a validation cohort.ConclusionsLODDS and LNR may be better predictors than N stage, TNLE, and PLNs. For OCCC patients, both the LODDS-based and LNR-based nomograms performed better than the AJCC staging system at predicting OS and CSS. However, further large sample, real-world studies are necessary to validate the assertion.

Objective This study explored serum protein biomarkers for predicting the efficacy of first-line chemotherapy in advanced epithelial ovarian cancer using MALDI-TOF-MS combined with magnetic bead technology. Methods A total of 182 epithelial ovarian cancer patients were admitted to the Department of Gynaecologic Oncology, Cancer Hospital of the Chinese Academy of Medical Sciences between March 2018 and September 2018. Sixty-four of these patients had stage III/IV disease and received neoadjuvant chemotherapy followed by interval debulking surgery (NACT-IDS) and adjuvant chemotherapy (mucinous and low-grade serous carcinoma were excluded). Serum samples were collected before treatment. After a median follow-up time of 16 months, 25 chemosensitive patients with progression-free survival (PFS) >12 months and 10 chemoresistant patients <6 months after adjuvant chemotherapy were selected as the research subjects. Matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) was used for peptide profiling of the serum samples to compare significantly differentially expressed peptides between the chemosensitive group and chemoresistant group (score >5), and peptide peaks with AUC ≥ 0.8 were identified. Liquid chromatography–mass spectrometry (LC‒MS/MS) was further used to determine the composition of the differentially expressed peptides. Results In the range of 1000-10000 m/z, 71 differential peptide peaks between the chemoresistant and chemosensitive groups were initially detected. ROC curve analysis showed that among the 71 differential protein peaks, there were 22 differential polypeptide peaks with an AUC ≥0.8, of which 10 were highly expressed in the chemoresistant group and 12 were highly expressed in the chemosensitive group. LC‒MS/MS analysis identified the protein components of 4 polypeptide peaks among the 10 differentially expressed polypeptide peaks in the chemoresistant group: 4634.22 m/z as fragments of serum amyloid A-1, 1287.56 m/zas fragments of prothrombin, and 1099.56 m/z and 2018.39 m/z as fragments of complement C3; the sensitivity and specificity of these three proteins for predicting first-line chemotherapeutic efficacy were 100%, 100%, and 96% and 80%, 100%, and 100%, respectively. No protein component was identified among the 12 differential protein peaks in the chemosensitive group. Conclusion Serum amyloid A-1, prothrombin and complement C3 were highly expressed in chemoresistant patients; thus, they might be related to the poor efficacy of paclitaxel/carboplatin first-line chemotherapy in advanced ovarian cancer. It is necessary to further explore their predictive value.