The efficacy of modified binding technique for renorrhaphy during robotic partial nephrectomy: surgical and functional outcomes from single-center experience.

BACKGROUND: To compare the traditional single-layer and double-layer suture renorrhaphy with modified "Binding" suture renorrhaphy (whole rim of the wound was closed by the all-layer flow suture starting from the parenchyma cut edges to hilum, followed by the final defect closure) in robotic partial nephrectomy (RPN) for treating localized renal cell carcinoma in our large institutional experience. METHODS: We retrospectively reviewed clinical data of 406 consecutive patients who underwent RPN from May 2018 and December 2020 in our center. The demographic and oncologic outcome variables were compared between different renal reconstruction groups and the effect of these suture techniques on renal function outcomes was also evaluated. RESULTS: For the single-layer group, median operative time and warm ischemic time were significantly less than that of the double-layer and "Binding" groups (p < 0.001), while the significantly lower eGFR drop (p = 0.014) was also detected within postoperative 3 months from baseline, but this difference lost its statistical significance from 3th month to the last follow-up. The changes in postoperative creatinine values were clinically insignificant among the three groups. In a sub-analysis over 258 patients with moderate/high nephrometry score, those patients who underwent "Binding" suture had an undifferentiated warm ischemic time, estimated blood loss, and length of hospitalization stay with a decreased risk of Grade III complications (postoperative hemorrhage requiring intervention) and improved renal function recovery during the whole follow-up. CONCLUSION: Single-layer suture renorrhaphy may be associated with better renal functional preservation and could prove to be reliable in patients with low-complexity tumor (RENAL score ≤ 6). Patients with moderate/high-complexity tumor (RENAL score ≥ 7) might represent a subgroup of patients having a functional benefit after "Binding" suture renorrhaphy even in the long-term period.

[Expression and significance analysis of GDF3 in testicular cancer based on TCGA and GTEx databases].

OBJECTIVE: To investigate the expression and significance of GDF3 in testicular cancer through bioinformatics analysis. METHODS: Using the TCGA and GTEx databases, differential expression analysis and pan-cancer analysis were performed to identify the target gene GDF3, and the clinical relevance of GDF3 in testicular cancer was analyzed using the UALCAN database. Based on the R packages "org.Hs.eg.db" and "clusterProfiler," gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore the potential functions of GDF3 in testicular cancer. The correlation of GDF3 with immune chemokines and immune inhibitors in testicular cancer was investigated using the TISIDB database. RESULTS: The GDF3 was significantly upregulated in testicular cancer (P<0.001) and closely associated with clinical staging (P<0.05) and tumor subtypes (P<0.001). The immune-related analysis revealed that GDF3 was strongly correlated with immune chemokines CCL26 (rho=0.599, P<0.001), CCL7 (rho=0.525, P<0.001), immune inhibitor ADORA2A (rho=0.723, P<0.001), and PVRL2 (rho=0.585, P<0.001). CONCLUSION: The GDF3 is closely related to the occurrence, development, and immune microenvironment of testicular cancer.

Identification of an IRGP Signature to Predict Prognosis and Immunotherapeutic Efficiency in Bladder Cancer.

BACKGROUND: Identify immune-related gene pairs (IRGPs) signature related to the prognosis and immunotherapeutic efficiency for bladder cancer (BLCA) patients. MATERIALS AND METHODS: One RNA-seq dataset (The Cancer Genome Atlas Program) and two microarray datasets (GSE13507 and GSE31684) were included in this study. We defined these cohorts as training set to construct IRGPs and one immunotherapy microarray dataset as validation set. Identifying BLCA subclasses based on IRGPs by consensus clustering. The Lasso penalized Cox proportional hazards regression model was used to construct prognostic signature and potential molecular mechanisms were analyzed. RESULTS: This signature can accurately predict the overall survival of BLCA patients and was verified in the immunotherapy validation set. IRGP-signatures can be used as independent prognostic risk factor in various clinical subgroups. Use the CIBERSORT algorithm to assess the abundance of infiltrating immune cells in each sample, and combine the results of the gene set enrichment analysis of a single sample to explore the differences in the immune microenvironment between IRPG signature groups. According to the results of GSVA, GSEA, and CIBERSORT algorithm, we found that IRGP is strikingly positive correlated with tumor microenvironment (TME) stromal cells infiltration, indicating that the poor prognosis and immunotherapy might be caused partly by enrichment of stromal cells. Finally, the results from the TIDE analysis revealed that IRGP could efficiently predict the response of immunotherapy in BLCA. CONCLUSION: The novel IRGP signature has a significant prognostic value for BLCA patients might facilitate personalized for immunotherapy.