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BackgroundNeoadjuvant chemotherapy (NAC) has been expanded to hormone receptor (HR) positive breast cancer (BC) patients with operable disease, to increase the likelihood of breast-conserving surgery. Genomic profiling at baseline would reveal NAC response relevant genomic features and signaling pathways, guiding clinical NAC utilization based on patients’ genomic characteristics.MethodsWe prospectively studied stage II/III BC patients who were eligible for breast-conserving surgery. Patients received epirubicin and cyclophosphamide for 4 cycles, followed by another 4-cycle docetaxel, and human epidermal growth factor receptor (HER2) positive patients were additionally treated with herceptin when using docetaxel (EC-T(H)). NAC responses were evaluated as pathologic complete response (pCR) or non-pathologic complete response (non-pCR). Genomic features related to NAC responses were identified by profiling baseline tumor tissues sampled one day before NAC, using whole-exome sequencing. Differentially expressed genes and up-/down-regulated pathways were investigated by performing RNA-sequencing.ResultsA total of 25 stage II/III BC patients were enrolled, including 5 patients ultimately evaluated as pCR and 20 patients evaluated as non-pCR. PIK3CA (48%) and TP53 (40%) mutations were enriched in patients not achieving pCR. Mutated phosphatidylinositol-3-kinase-AKT (PI3K-AKT) pathway and homologous recombinational repair pathway were also more frequently observed in patients evaluated as non-pCR. Significant arm-level amplifications (8q24.23 and 17q12) and deletions (1p32.2, 4p14, 7q11.23, 10q21.3, 11q23.3, etc.) were identified among patients not achieving pCR, while patients achieving pCR displayed no significant copy number alterations. Significantly up-regulated expression of PI3K-AKT pathway genes was also detected among patients failed to achieve pCR, compared to patients achieving pCR.ConclusionCompared to BC patients achieving pCR to NAC, aberrant activation of PI3K-AKT pathway genes were more frequently observed in patients not achieving pCR, consistent with the significant up-regulation of PI3K-AKT pathway gene expression in the non-pCR subgroup. Together, these findings indicate that upregulated PI3K-AKT pathway serves as a potential indicator of lack of response to NAC in stage II/III BC patients, and other effective therapeutic options are urgently needed for those resistant patients.

IntroductionThis study aims to investigate whether the transrectal ultrasound-guided combined biopsy (CB) improves the detection rates of prostate cancer (PCa) and clinically significant PCa (csPCa) in biopsy-naïve patients. We also aimed to compare the Prostate Imaging Reporting and Data System (PI-RADS v2.1) score, ADC values, and PSA density (PSAd) in predicting csPCa by the combined prostate biopsy.MethodsThis retrospective and single-center study included 389 biopsy-naïve patients with PSA level 4~20 ng/ml, of whom 197 underwent prebiopsy mpMRI of the prostate. The mpMRI-based scores (PI-RADS v2.1 scores and ADC values) and clinical parameters were collected and evaluated by logistic regression analyses. Multivariable models based on the mpMRI-based scores and clinical parameters were developed by the logistic regression analyses to forecast biopsy outcomes of CB in biopsy-naïve patients. The ROC curves measured by the AUC values, calibration plots, and DCA were performed to assess multivariable models.ResultsThe CB can detect more csPCa compared with TRUSB (32.0% vs. 53%). The Spearman correlation revealed that Gleason scores of the prostate biopsy significantly correlated with PI-RADS scores and ADC values. The multivariate logistic regression confirmed that PI-RADS scores 4, 5, and prostate volume were important predictors of csPCa. The PI-RADS+ADC+PSAd (PAP) model had the highest AUCs of 0.913 for predicting csPCa in biopsy-naïve patients with PSA level 4~20 ng/ml. When the biopsy risk threshold of the PAP model was greater than or equal to 0.10, 51% of patients could avoid an unnecessary biopsy, and only 5% of patients with csPCa were missed.ConclusionThe prebiopsy mpMRI and the combined prostate biopsy have a high CDR of csPCa in biopsy-naïve patients. A multivariable model based on the mpMRI-based scores and PSAd could provide a reference for clinicians in forecasting biopsy outcomes in biopsy-naïve patients with PSA 4~20 ng/ml and make a more comprehensive assessment during the decision-making of the prostate biopsy.

IntroductionBladder cancer (BC) is a significant carcinoma of the urinary system that has a high incidence of morbidity and death owing to the challenges in accurately identifying people with early-stage BC and the lack of effective treatment options for those with advanced BC. Thus, there is a need to define new markers of prognosis and prediction.MethodsIn this study, we have performed a comprehensive proteomics experiment by label-free quantitative proteomics to compare the proteome changes in the serum of normal people and bladder cancer patients—the successful quantification of 2064 Quantifiable proteins in total. A quantitative analysis was conducted to determine the extent of changes in protein species' relative intensity and reproducibility. There were 43 upregulated proteins and 36 downregulated proteins discovered in non-muscle invasive bladder cancer and normal individuals. Sixty-four of these proteins were elevated, and 51 were downregulated in muscle-invasive and non-muscle-invasive bladder cancer, respectively. Functional roles of differentially expressed proteins were annotated using Gene Ontology (GO) and Clusters of Orthologous Groups of Proteins (COG). To analyze the functions and pathways enriched by differentially expressed proteins, GO enrichment analysis, protein domain analysis, and KEGG pathway analysis were performed. The proteome differences were examined and visualized using radar plots, heat maps, bubble plots, and Venn diagrams.ResultsAs a result of combining the Venn diagram with protein-protein interactions (PPIs), Chloride intracellular channel 1 (CLIC1) was identified as the primary protein. Using the Gene Set Cancer Analysis (GSCA) website, the influence of CLIC1 on immune infiltration was analyzed. A negative correlation between CD8 naive and CLIC1 levels was found. For validation, immunohistochemical (IHC), qPCR, and western blotting (WB) were performed.Further, we found that CLIC1 was associated with a poor prognosis of bladder cancer in survival analysis.DiscussionOur research screened CLIC1 as a tumor-promoting protein in bladder cancer for the first time using serum mass spectrometry. And CLIC1 associated with tumor stage, and immune infiltrate. The prognostic biomarker and therapeutic target CLIC1 may be new for bladder cancer patients.

Background: To investigate the prognostic role of tumor size in patients with pathological T2N0M0 and T3aN0M0 renal cell carcinoma (RCC) treated by radical surgery.Methods: A total of 3,662 cases were retrospectively analyzed from the Surveillance, Epidemiology and End Results (SEER) from 2010 to 2012. Overall survival (OS) and cancer-specific survival (CSS) data were obtained. The log-rank test was used to compare survival distributions and Cox proportional hazards model was used for univariate and multivariate analyses, respectively.Results: In the low-risk T3aN0M0 (perinephric fatty infiltration or sinus fatty infiltration only) group, patients with tumor size ≤ 7 cm were associated with a better OS (P = 0.009) and CSS (P < 0.001) than those with tumor size >7 cm. However, there was no difference in OS (P = 0.129) and CSS (P = 0.539) between T2bN0M0 patients and low-risk T3aN0M0 patients with tumor size ≤ 7 cm. A new T classification grouping patients with both T2bN0M0 and T3aN0M0 with tumor diameter ≤ 7 cm into the same staging category (pT2aN0M0, pT2bN0M0+low-risk pT3aN0M0 [tumor diameter ≤ 7cm], low-risk pT3aN0M0 [tumor diameter >7 cm], high-risk pT3aN0M0) was proposed and it was found as an independent predictive variable for OS and CSS.Conclusions: Findings from the present study suggest that the reclassification of pT2N0M0 and pT3aN0M0 RCC can lead to better prediction of OS and CSS.