Infiltrating bladder cancer: prognostic factors, follow-up and treatment of relapses

Serum amyloid A protein in cancer prognosis: a meta-analysis and systematic review

Background

Published studies showed divergent results of the prognostic value of serum amyloid A protein (SAA) in patients with different cancers. Therefore, we conducted this meta-analysis so as to assess the association between SAA and cancer prognosis.

Methods

A comprehensive search was conducted to identify the literatures working over SAA and survival in patients with cancers published until January 2020. Sufficient data for assessing overall survival in cancers were extracted descriptively and quantitatively from the studies and a pooled odds ratio was calculated using the Mantel-Haenszel fixed-effect or random-effect model.

Results

Ten eligible papers were identified by two reviewers independently, including 4 studies that evaluated renal cell carcinoma (RCC), 2 studies evaluated lung cancer and the other 3 studies evaluated melanoma, gastric cancer and different cancers. Elevated SAA expression and shorter overall survival (OS) had a statistically significant relation [pooled 1-year OR was 5.07, 95% confidence interval (CI), 3.71–6.94, Q=9.15, I²=0%; pooled 3-year OR was 4.21, 95% CI, 3.18–5.56, Q=14.94, I²=46%; pooled 5-year OR was 5.69, 95% CI, 2.66–12.18, Q=24.83, I²=80%]. Subgroup analysis of RCC patients showed remarkable association between SAA and shorter OS (pooled 1-year OR =4.76, 95% CI, 3.00–7.56, Q=4.18, I²=4%; pooled 3-year OR =4.89, 95% CI, 3.06–7.81, Q=2.88, I²=0%).

Conclusions

High SAA status is correlated with an unfavorable OS in different cancers, especially in RCC, and digestive cancer.

Population-based outcome of muscle-invasive bladder cancer following radical cystectomy: who can benefit from adjuvant chemotherapy?

Background

The benefit of adjuvant chemotherapy remains controversial in muscle-invasive bladder cancer (MIBC) after radical cystectomy. The present study’s primary objective was to construct a predictive tool for the reasonable application of adjuvant chemotherapy.

Methods

All of the patients analyzed in the present study were recruited from the Surveillance Epidemiology and End Results program between 2004 and 2015. Propensity score matching (PSM) was used to reduce inherent selection bias. Cox proportional hazards models were applied to identify the independent prognostic factors of overall survival (OS) and cancer-specific survival (CSS), which were further used to construct prognostic nomogram and risk stratification systems to predict survival outcomes. The prognostic nomogram’s performance was assessed by concordance index (C-index), receiver-operating characteristic (ROC) and calibration curves. Decision curve analysis (DCA) was performed to evaluate the clinical net benefit of the prognostic nomogram.

Results

A total of 6,384 patients with or without adjuvant chemotherapy were included after PSM. Several independent predictors for OS and CSS were identified and further applied to establish a nomogram for 3-, 5- and 10-year, respectively. The nomogram showed favorable discriminative ability for the prediction of OS and CSS, with a C-index of 0.709 [95% confidence interval (CI): 0.699–0.719] for OS and 0.728 (95% CI: 0.718–0.738) for CSS. ROC and calibration curves showed satisfactory consistency. The DCA revealed high clinical positive net benefits of the prognostic nomogram. The different risk stratification systems showed that adjuvant chemotherapy resulted in better OS (P<0.001) and CSS (P<0.001) than without adjuvant chemotherapy for high-risk patients; while the OS (P=0.350) and CSS (P=0.260) for low-risk patients were comparable.

Conclusions

We have constructed a predictive model and different risk stratifications for selecting a population that could benefit from postoperative adjuvant chemotherapy. Adjuvant chemotherapy was found to be beneficial for high-risk patients, while low-risk patients should be carefully monitored.

A Comparative Meta-Analysis and in silico Analysis of Differentially Expressed Genes and Proteins in Canine and Human Bladder Cancer

Canine and human bladder cancer present similar anatomical, morphological, and molecular characteristics, and dogs can be considered a model for human bladder cancer. However, the veterinary literature lacks information regarding cross-validation analysis between human and canine large-scale data. Therefore, this research aimed to perform a meta-analysis of the canine literature on bladder cancer, identifying genes and proteins previously evaluated in these studies. In addition, we also performed a cross-validation of the canine transcriptome data and the human data from The Cancer Genome Atlas (TCGA) to identify potential markers for both species. The meta-analysis was performed using the following indexing terms: “bladder” AND “carcinoma” AND “dog” in different international databases, and 385 manuscripts were identified in our initial search. Then, several inclusion criteria were applied, and only 25 studies met these criteria. Among these studies, five presented transcriptome data, and 20 evaluated only isolated genes or proteins. Regarding the studies involving isolated protein analysis, the HER-2 protein was the most studied (3/20), followed by TAG-72 (2/20), COX-2 (2/20), survivin (2/20), and CK7 (2/20), and the remaining nine studies evaluated one isolated protein each. Regarding the cross-validation analysis of human and canine transcriptome data, we identified 35 dysregulated genes, including ERBB2, TP53, EGFR, and E2F2. Our results demonstrate that the canine literature on bladder cancer previously focused on the evaluation of isolated markers with no association with patient survival. This limitation may be related to the lack of a homogenous protocol for treating patients and the lack of follow-up during treatment. In addition, the lack of information regarding tumor muscle invasion can be considered an important limitation when comparing human and canine bladder tumors. Our in silico analysis involving canine and human transcriptome data provided several genes with the potential to be markers for both human and canine bladder tumors, and these genes should be considered for future studies on canine bladder cancer.