Cancer-associated fibroblasts (CAFs) play crucial roles in mediating tumor growth and metastasis via transferring exosomes to neighboring cells, whereas the mechanisms by which CAFs regulate the tumorgenesis of prostate cancer (PC) remain largely unknown. In this study, CAFs and normal fibroblasts (NFs) were isolated from PC tissues and adjacent normal tissues, respectively. Exosomes (NFs-Exo and CAFs-Exo) were then isolated from the supernatant of NFs and CAFs. Next, the differentially expressed miRNAs (DEMs) between NFs-Exo and CAFs-Exo were identified using RNA-sequencing. Cell viability, migration and invasion were detected with CCK-8 and Transwell assays. Protein expression was measured with western blot. We found that CAFs-Exo remarkably enhanced PC cell migration, invasion, stemness, epithelial-mesenchymal transition (EMT) and metastasis. Significantly, miR-1290 level was upregulated in CAFs-Exo compared to NFs-Exo. In addition, CAFs could transfer exosomes to PC cells, resulting in a marked increase of miR-1290 level in cells. Moreover, exosomal miR-1290 could inhibit GSK3β/β-catenin signaling by binding with the downstream target GSK3β mRNA. Meanwhile, miR-1290 antagomir notably reversed the effects of CAFs-Exo on PC cells through activating GSK3β/β-catenin signaling. Collectively, exosomal miR-1290 from CAFs could promote PC cell growth and metastasis via inhibiting GSK3β/β-catenin signaling, suggesting that miR-1290 may serve as potential therapeutic target for the treatment of PC.

Purpose: To evaluate the diagnostic values of systemic immune-inflammation index (SII) and neutrophil–lymphocyte ratio (NLR) in patients with localized prostate cancer (PCa).Methods: Between January 2014 and December 2019, 117 patients with benign prostate hyperplasia (BPH) and 278 patients with localized PCa who underwent radical prostatectomy (RP) were included in this study. The inflammatory markers including SII, NLR, platelet–lymphocyte ratio (PLR), lymphocyte–monocyte ratio (LMR), lymphocyte ratio (LR), neutrophil ratio (NR), mean platelet volume (MPV), and red cell distribution (RDW) of these two groups were examined and analyzed. ROC curve analysis was performed to assess the discriminative ability of inflammatory markers and their combination with tPSA for PCa. The binary logistic regression model was used to evaluate the association between significant inflammatory markers and risk of PCa.Results: The pathological results from RP specimen comprised 72 (25.90%) patients with pT1, 168 (60.43%) patients with pT2, and 38 (13.67%) patients with pT3. According to Student’s t test, patients with PCa had higher NLR (p = 0.034), SII (p = 0.008), and NR (p = 0.004), and lower LR (p = 0.025), MPV (p = 0.003), and TPV (p = 0.022) compared with patients with BPH; the distribution of age, PLR, LMR, RDW, f/t PSA ratio, and BMI did not show any significant differences. The AUC for NLR, SII, NR, and tPSA was 0.697 (p = 0.015), 0.719 (p < 0.001), 0.647 (p = 0.009), and 0.708 (p < 0.001), with threshold values of 1.6, 471.86, 65.15%, and 12.89 ng/ml, respectively. Patients were divided into two groups according to the threshold values, respectively. By using the multivariable logistic regression models, NLR ≥ 1.6 (OR, 2.731; 95% CI, 0.937–7.961, p = 0.042), SII ≥ 471.86 (OR, 1.274; 95% CI 0.473–3.433; p = 0.033), and PSA ≥ 12.89 ng/ml (OR, 1.443; 95% CI, 0.628–3.944; p = 0.014) were independent risk factors associated with PCa. The AUC for combination of NLR, SII, and NR with tPSA was 0.705 (p < 0.001), 0.725 (p < 0.001), and 0.704 (p < 0.001), respectively.Conclusion: This study demonstrated that SII, NLR, and NR were all independent risk factors of PCa. These factors alone could provide better screen methods for PCa before biopsy. In addition, SII is a more powerful tool among these three inflammatory markers associated with PCa. Besides, combination of SII and NLR with tPSA had not much advantage compared with themselves alone.

Background. Inflammation and tumorigenesis are related. We conducted this study to evaluate whether inflammatory factors (IFs) have a diagnostic value for pathology and a predictive value for survival and recurrence in bladder cancer patients undergoing total cystectomy. Methods. The patients who were diagnosed with bladder cancer and underwent total cystectomy in our center from 2014 to 2020 were enrolled. The values of neutrophil to lymphocyte ratio (NLR), derived neutrophil to lymphocyte ratio (dNLR), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), and systemic immune-inflammation index (SII) were calculated by blood routine test results before operation. The AUC of ROC was calculated to judge the diagnostic value of the IFs in pathology and their corresponding cut-off values. For overall survival (OS) and recurrence-free survival (RFS), the above IFs were grouped according to the cut-off value. The differences between different groups were analyzed by the Kaplan-Meier curves, and the predictive value of these IFs was determined by the Cox proportional hazards regression model. Results. A total of 79 patients were enrolled. All IFs had no diagnostic value for the pathological grade, tumor T stage, and systemic metastasis. Only NLR (AUC=0.706, cut‐offvalue=3.12, sensitivity=75.00%, specificity=70.00%, P=0.014), dNLR (AUC=0.700, cut‐offvalue=2.49, sensitivity=66.67%, specificity=76.67%, P=0.015), and SII (AUC=0.704, cut‐offvalue=463.56, sensitivity=100.00%, specificity=40.00%, P=0.004) had a diagnostic value for lymph node metastasis. The median follow-up time was 31 months, and there was no significant difference in OS between the two groups for all IFs. For RFS, Kaplan-Meier suggested PLR might be predictive when the cut-off value was 266.70 (P=0.044), but the subsequent Cox proportional hazards regression analysis showed that all IFs had no predictive value for OS and RFS. Conclusions. We found that in patients undergoing total cystectomy preoperative NLR, dNLR and SII had a diagnostic value for lymph node metastasis, while all these five IFs had no predictive value for OS and RFS. However, this conclusion needs to be further verified by large-scale studies in the future.

We conducted this study to evaluate the diagnostic value of Inflammatory Factors (IFs) in the pathology of bladder cancer patients. The patients who were diagnosed with urothelial bladder carcinoma (bladder cancer) and underwent surgical treatment in our center from 2014 to 2019 were enrolled. The values of Neutrophil to Lymphocyte Ratio (NLR), derived Neutrophil to Lymphocyte Ratio (dNLR), Platelet to Lymphocyte Ratio (PLR), Lymphocyte to Monocyte Ratio (LMR), Systemic Immune-inflammation Index (SII), and Prognostic Nutritional Index (PNI) were calculated by blood routine test results before operation. After obtaining the postoperative pathology of the patients, the Area Under Curve (AUC) of Receiver Operating Characteristic (ROC) curves was calculated to evaluate the diagnostic value of these IFs in pathology and their corresponding cut-off values. A total of 641 bladder cancer patients were enrolled. The median values of NLR, dNLR, PLR, LMR, SII, and PNI were 6.33, 4.09, 156.47, 2.66, 1114.29, and 51.45, respectively. Grouped patients according to the pathological grade, the NLR, dNLR, PLR, and SII of the high-grade group were significantly higher than those of the low-grade group (P < 0.001, P < 0.001, P < 0.001, and P < 0.001, respectively), while the LMR and PNI were significantly lower than those of the low-grade group (P = 0.003 and P < 0.001). Divided patients into non-muscle invasion group (Tis + Ta + T1) and muscle invasion group (T2 + T3 + T4), in which NLR, dNLR, PLR, and SII in the muscle invasion group were significantly higher than those in the non-muscle invasion group (P < 0.001, P < 0.001, P < 0.001, and P < 0.001, respectively), while LMR and PNI were significantly lower than those in the low-grade group (P = 0.012 and P < 0.001). ROC curves analyses showed that NLR, dNLR, PLR, LMR, SII, and PNI had predictive value for pathological grade (P < 0.001, P < 0.001, P < 0.001, P < 0.001, P < 0.001, P < 0.001, and P < 0.001, respectively) and muscle invasion (P < 0.001, P < 0.001, P < 0.001, P < 0.001, P < 0.001, P < 0.001, and P < 0.001, respectively). The results suggest the higher NLR, dNLR, PLR, SII, and lower LMR and PNI are associated with higher risk of high-grade and muscle invasive disease. However, this conclusion needs to be further clarified in the future.

Purpose: To investigate the role of inflammatory factors including systemic immune-inflammation index (SII) and neutrophil to lymphocyte ratio (NLR) in predicting Gleason Score (GS) and Gleason Score upgrading (GSU) in localized prostate cancer (PCa) after radical prostatectomy (RP).Methods: The data of 297 patients who underwent prostate biopsy and RP in our center from January 2014 to March 2020 were retrospectively analyzed. Preoperative clinical characteristics including age, values of tPSA, total prostate volume (TPV), f/t PSA ratio, body mass index (BMI), biopsy GS and inflammatory factors including SII, NLR, lymphocyte to monocyte (LMR), neutrophil ratio (NR), platelet to lymphocyte ratio (PLR), lymphocyte ratio (LR), mean platelet volume (MPV) and red cell distribution (RDW) as well as pathological T (pT) stage were collected and compared according to the grades of RP GS (GS ≤ 6 and GS≥7), respectively. ROC curve analysis was used to confirm the discriminative ability of inflammatory factors including SII, NLR and their combination with tPSA for predicting GS and GSU. By using univariate and multivariate logistic regression analysis, the association between significant inflammatory markers and grades of GS were evaluated.Results: Patients enrolled were divided into low (GS ≤ 6) and high (GS≥7) groups by the grades of GS. The median values of clinical factors were 66.08 ± 6.04 years for age, 36.62 ± 23.15 mL for TPV, 26.16 ± 33.59 ng/mL for tPSA and 0.15 ± 0.25 for f/t PSA ratio, 22.34 ± 3.14 kg/m² for BMI, 15 (5.1%) were pT1, 116 (39.1%) were pT2 and 166 (55.9%) were pT3. According to the student’s t test, patients in high GS group had a greater proportion of patients with pT3 (P<0.001), and higher NLR (P=0.04), SII (P=0.037) and tPSA (P=0.015) compared with low GS group, the distribution of age, TPV, f/t PSA ratio, BMI, LMR, NR, PLR, LR, MPV and RDW did not show any significantly statistical differences. The AUC for SII, NLR and tPSA was 0.732 (P=0.007), 0.649 (P=0.045) and 0.711 (P=0.015), with threshold values of 51l.08, 2.3 and 10.31ng/mL, respectively. According to the multivariable logistic regression models, NLR ≥ 2.3 (OR, 2.463; 95% CI, 0.679-10.469, P=0.042), SII ≥ 511.08 (OR, 3.519; 95% CI 0.891-12.488; P=0.003) and tPSA ≥ 10.31 ng/mL (OR, 4.146; 95% CI, 1.12-15.35; P=0.033) were all independent risk factors associated with higher GS. The AUC for combination of SII, NLR with tPSA was 0.758 (P=0.003) and 0.756 (P=0.003), respectively. GSU was observed in a total of 48 patients with GS ≤ 6 (55.17%). Then patients were divided into 2 groups (high and low) according to the threshold value of SII, NLR, tPSA, SII+tPSA and NLR+tPSA, respectively, when the GSU rates were compared with regard to these factors, GSU rate in high level group was significantly higher than that in low level group, P=0.001, 0.044, 0.017, <0.001 and <0.001, respectively.Conclusion: High SII, NLR and tPSA were associated with higher GS and higher GSU rate. SII was likely to be a more favorable biomarker for it had the largest AUC area compared with tPSA and NLR; the combination of SII or NLR with tPSA had greater values for predicting GS and GSU compared with NLR, SII or tPSA alone, since the AUC area of combination was much higher. SII, NLR were all useful inflammatory biomarkers for predicting GS and detecting GSU among localized PCa patients with biopsy GS ≤ 6.