Therapeutic Role of Retroperitoneal Lymphadenectomy in 170 Patients With Ovarian Clear Cell Cancer

IntroductionWe evaluated the therapeutic role of retroperitoneal lymphadenectomy in patients with ovarian clear cell cancer (OCCC).Materials and MethodsWe retrospectively reviewed 170 OCCC patients diagnosed at two hospitals in China between April 2010 and August 2020. Clinical data were abstracted, and patients were followed until February 2021. Patients were divided into retroperitoneal lymphadenectomy and no lymphadenectomy groups. The Kaplan–Meier method was used to compare progression-free (PFS) and overall survival (OS) between the two groups. Statistical differences were determined by the log-rank test. The COX proportional hazards regression model was applied to identify predictors of tumor recurrence.ResultsThe median age was 52 years; 90 (52.9%) and 80 (47.1%) patients were diagnosed as early and advanced stage, respectively. Clinically positive and negative nodes was found in 40 (23.5%) and 119 (70.0%) patients, respectively. Of all the 170 patients, 124 (72.9%) patients underwent retroperitoneal lymphadenectomy, while 46 (27.1%) did not. The estimated 2-year PFS and 5-year OS rates were 71.4% and 65.9% in the lymphadenectomy group, and 72.0% and 73.7% in no lymphadenectomy group (p = 0.566 and 0.669, respectively). There was also no difference in survival between the two groups when subgroup analysis was performed stratified by early and advanced stage, or in patients with clinically negative nodes. Multivariate analysis showed that retroperitoneal lymphadenectomy were not an independent predictor of tumor recurrence.ConclusionRetroperitoneal lymphadenectomy provided no survival benefit in patients diagnosed with OCCC. A prospective clinical trial is needed to confirm the present results.

CD147 expression lacks prognostic relevance in esophageal cancer

Introduction The role of CD147 as an important indicator of tumor prognosis remains controversially discussed in literature. We focused on the prognostic significance of CD147 expression in esophageal cancer patients. While some studies report that CD147 is an unfavorable prognostic factor in esophageal squamous cell carcinoma, others showed no significant correlation. However, only one study draws attention to the significance of CD147 in esophageal adenocarcinoma, which is one of the most rapidly increasing neoplasms in the western world. Methods To finally clarify the impact of CD147 as a prognostic factor, especially for esophageal adenocarcinomas, we analyzed CD147 expression in a tissue microarray of 359 esophageal adenocarcinomas and 254 esophageal squamous cell cancer specimens. For the immuno-histochemical analysis, we used a primary antibody specific for CD147. Staining intensity and proportion of positive tumor cells were scored (negative, weak, moderate, strong staining). These findings were compared to normal esophageal tissue and correlated to the histopathological tumor phenotype and survival data. Results CD147 expression was detectable in weak intensities in benign esophageal tissue (85.78%) and expressed in predominately moderate to strong intensities in esophageal cancer (88.34%). Strong CD147 immunostaining was linked to increased infiltration depth (p = 0.015) and differentiation (p = 0.016) in esophageal squamous cell cancer but revealed no significant correlation with histopathology of adenocarcinoma. Moreover, CD147 intensity was unrelated to overall survival in this collective for both subtypes of esophageal cancer. Conclusion Thus, our data show that CD147 has no prognostic value, neither in esophageal adenocarcinoma nor squamous cell carcinoma.

Pattern of Nutritional status in Node Negative versus Node Positive Head and Neck Cancer patients undergoing treatment - a prospective cohort study

Purpose The aim of this study was to study the nutritional profile of node negative and node positive patients undergoing treatment for head and neck squamous cell cancer (HNSCC). Methods This prospective cohort study was conducted between 2018 and 2020. Patients diagnosed with HNSCC, planned for treatment were enrolled after written informed consent. In Node negative(N0) and Node positive(N+) cohorts of patients, nutritional status was determined using- anthropometric measures and Subjective Global Assessment (SGA) scale pre-treatment, during and after treatment. Statistical analysis was performed using SPSS version 22. Data was analyzed using parametric and non-parametric tests, p value of 0.05 was considered significant. Results 161 patients were analyses, 73 N0 and 88 N+ cohorts. Pre-treatment, 9.6 to 20.4% patients in N0 and 23.9 to 32.8% patients in N+ cohorts were malnourished. Incidence of malnutrition at completion of treatment was 40.8–52.5% overall, 20.5–41.1% N0, 39.5–62.8% N+. Mean reduction in weight (11.1% ±7.82 v/s 6.26% ±8.3, p=0.000), mean reduction in BMI (2.57 ±1.87 v/s 1.29 ±1.62, p=0.000), median reduction in MUAC (2cm v/s 1cm, p=0.000) and median increase in SGA score were higher (13 v/s 6, p=0.000) in multi-modality as compared to single modality treatment. Similar findings were noted in N0 and N+ cohorts. Conclusion As compared to N0, N+ patients had higher burden of malnutrition at diagnosis, more worsening of nutritional parameters during treatment. More decline in Nutritional status was seen in patients receiving multi-modality as compared to single modality treatment.

Establishment of a Prognostic Prediction and Drug Selection Model for Patients with Clear Cell Renal Cell Carcinoma by Multiomics Data Analysis

Rationale. Patients with clear cell renal cell cancer (ccRCC) may have completely different treatment choices and prognoses due to the wide range of heterogeneity of the disease. However, there is a lack of effective models for risk stratification, treatment decision-making, and prognostic prediction of renal cancer patients. The aim of the present study was to establish a model to stratify ccRCC patients in terms of prognostic prediction and drug selection based on multiomics data analysis. Methods. This study was based on the multiomics data (including mRNA, lncRNA, miRNA, methylation, and WES) of 258 ccRCC patients from TCGA database. Firstly, we screened the feature values that had impact on the prognosis and obtained two subtypes. Then, we used 10 algorithms to achieve multiomics clustering and conducted pseudotiming analysis to further validate the robustness of our clustering method, based on which the two subtypes of ccRCC patients were further subtyped. Meanwhile, the immune infiltration was compared between the two subtypes, and drug sensitivity and potential drugs were analyzed. Furthermore, to analyze the heterogeneity of patients at the multiomics level, biological functions between two subtypes were compared. Finally, Boruta and PCA methods were used for dimensionality reduction and cluster analysis to construct a renal cancer risk model based on mRNA expression. Results. A prognosis predicting model of ccRCC was established by dividing patients into the high- and low-risk groups. It was found that overall survival (OS) and progression-free interval (PFI) were significantly different between the two groups ( p < 0.01 ). The area under the OS time-dependent ROC curve for 1, 3, 5, and 10 years in the training set was 0.75, 0.72, 0.71, and 0.68, respectively. Conclusion. The model could precisely predict the prognosis of ccRCC patients and may have implications for drug selection for ccRCC patients.