The Values of Systemic Immune-Inflammation Index and Neutrophil-Lymphocyte Ratio in the Localized Prostate Cancer and Benign Prostate Hyperplasia: A Retrospective Clinical Study

Geriatric Nutritional Risk Index (GNRI) and Prognostic Nutritional Index (PNI) Before Treatment as the Predictive Indicators for Bone Metastasis in Prostate Cancer Patients

Objective

Inflammation and nutritional status are involved in the occurrence and progression of cancer. The purpose of this study was to investigate the relationship of nutritional status indices (geriatric nutritional risk index (GNRI), neutrophil to albumin ratio (NAR), prognostic nutritional index (PNI)), and comprehensive inflammatory indices (pan-immune inflammation value (PIV), systemic immune inflammation index (SII), and system inflammation response index (SIRI)) and bone metastasis of prostate cancer.

Methods

A retrospective analysis was performed on 888 prostate cancer patients treated in Meizhou People's Hospital from November 2017 to December 2022. Clinical characteristics were collected, including age, body mass index (BMI), bone metastasis, and GNRI, NAR, PNI, PIV, SII, and SIRI levels. The optimal cutoff values of these indices were calculated by receiver operating characteristic (ROC) curve, and the relationship between these indices and bone metastasis was analyzed.

Results

There were 836 (94.1%) cases were ≥60 years old, indicating that the majority of prostate cancer patients were elderly men. There were 640 (72.1%) patients without bone metastasis and 248 (27.9%) patients with bone metastasis. The levels of GNRI and PNI in patients with bone metastasis were significantly lower than those without, while NAR, PIV, SII, and SIRI were not statistically significant. And the levels of GNRI and PNI in patients with multiple bone metastasis were significantly lower than those with single bone metastasis. When bone metastasis was taken as the endpoint of GNRI and PNI, the critical value of GNRI was 97.05 (sensitivity 55.2%, specificity 67.5%, area under the ROC curve (AUC) = 0.639), the PNI cutoff value was 44.925 (sensitivity 51.2%, specificity 67.2%, AUC = 0.634), and the AUC of GNRI plus PNI was 0.647.

Conclusion

Prostate cancer is more common in older men; about a quarter of patients have bone metastasis. GNRI and PNI have predictive efficacy in bone metastasis and multiple bone metastasis of prostate cancer, but NAR, PIV, SII, and SIRI do not.

Determination of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio and systemic immune-inflammation index in dogs with leptospirosis

Leptospirosis is a globally distributed zoonosis with multisystemic involvement in canine species, capable of causing a pulmonary hemorrhagic syndrome (LPHS) in the most severe cases. In humans, the neutrophil to lymphocyte ratio (NLR), platelets to lymphocytes (PLR) and systemic immune-inflammation index (SII) have been described as predictors of morbidity and mortality in various pathologies, but no such studies have been developed for canine leptospirosis. Hence, we aimed to assess the usefulness of NLR, PLR and SII in dogs affected with leptospirosis, focusing on those that died or survived after hospitalization, whether or not they developed LPHS. The leptospirosis group was composed by 36 dogs while the control group consisted of 32 healthy dogs. The NLR, associated with inflammation, demonstrated a threefold or greater increase in all leptospirosis groups compared to the control group (median 2.44 ± 1.66) (developing or not LPHS). Dogs that died (median 67.78 ± 158.67), developed LHPS (median 85.17 ± 143.77), or both developed LHPS and died (median 67.78 ± 155,14) had a lower PLR in comparison to the control group (median 101,82 ± 53,75) and the rest of groups, but no statistically significant differences were observed (p > 0.05). The SII was higher in leptospirosis-affected dogs that survived (median 1356,92 ± 2726,29) and statistically significant differences were observed in those who did not develop LPHS (median 1770,41 ± 2630,77; p < 0.05) compared to the control group (median 555,21 ± 313,26). Our data shows that NLR may be used as inflammation indicator, while more studies are needed for PLR and SII in canine leptospirosis.

Systemic immune-inflammation index is associated with high risk for prostate cancer among the U.S. elderly: Evidence from NHANES 2001-2010

Purpose

The Systemic Immuno-Inflammation Index (SII) is a crucial clinical measure of inflammation, and there is currently no solid evidence linking SII to an increased risk of prostate cancer (PCa). Through the analysis of serum total prostate-specific antigen (tPSA), free prostate-specific antigen (fPSA), and the tPSA/fPSA (fPSA%) ratio, this study sought to investigate the relationship between SII and PCa risk among the U.S. elderly.

Methods

Elderly male participants were gathered from the NHANES database between 2001 and 2010.SII was calculated by platelet count * neutrophil count/lymphocyte count. High risk individuals for prostate cancer were defined as those with tPSA > 4 ng/ml and fPSA% < 16%. Multivariate logistic regression models, restricted cubic spline curves, and subgroup analyses were used to assess the relationship between SII and PCa risk.

Results

This research comprised 2664 people in total, 137 (5.14%) of whom were deemed to be at high risk of developing PCa. Multivariate logistic regression analysis, after controlling for variables, revealed a significant positive correlation between high PCa risk and an increase in SII (p = 0.009). The RCS suggested a turning point at 9.01. Restricted cubic spline curves revealed a non-linear U-shaped association between SII and high PCa risk (p for nonlinear = 0.028). Education level, marital status, PIR, alcohol status, smoking status, rheumatoid arthritis status, and heart problem were not significantly correlated with this positive connection, according to subgroup analyses and interaction tests.

Conclusion

The results of this study suggest that inflammation represented by SII is associated with high PCa risk.

Association between lymphocyte-to-monocyte ratio and prostate cancer in men: A population-based study

Using the novel inflammatory biomarker lymphocyte-to-monocyte ratio (LMR), this work aimed to look into any potential connections between LMR and prostate cancer (PCa). A cross-sectional research investigation was conducted on 7706 male participants involved in the National Health and Nutrition Examination Survey from 2001 to 2010. Multivariate logistic regression modeling investigated the relationship between LMR levels and PCa risk. Furthermore, threshold analysis, subgroup analysis, interaction testing, and smoothed curve fitting were carried out. A significant negative correlation was seen between LMR and PCa risk (OR = 0.79, 95% CI: 0.65-0.97, P = .0002), even after controlling for potential confounding factors. A significant nonlinear negative correlation with a threshold effect and a breakpoint of 4.86 was found by smooth curve fitting between LMR and PCa. Subgroup analysis revealed a significant interaction (P for interaction = 0.0448) between the negative correlation between PCa and LMR about hypertension. Moreover, additional stratified smoothed curve fitting demonstrated a statistically significant inverse relationship between PCa risk and LMR. According to our findings, there is a substantial inverse relationship between PCa risk and LMR level. The inflammatory response-related index is quick, easy to use, and offers some clinical references. However, more extensive prospective investigations are required to confirm the involvement of LMR levels in PCa.

Associations of systemic immune-inflammation index with high risk for prostate cancer in middle-aged and older US males: A population-based study

BACKGROUND

Systemic immune-inflammation index (SII) provides convincing evaluation of systemic immune and inflammatory condition in human body. Its correlation with prostate cancer (PCa) risk remains uncharted. The principal objective of this investigation was to elucidate the association between SII and the risk for PCa in middle-aged and elderly males.

MATERIALS AND METHODS

Analysis entailed multivariate linear and logistic regression, generalized additive model, and smoothing curve fitting using resource from 2007 to 2010 National Health and Nutrition Examination Survey (NHANES). To ascertain robustness and consistency of this association across different demographic strata, we conducted rigorous subgroup analyses and interaction tests.

RESULTS

Among 3359 participants, those with elevated SII displayed higher total prostate-specific antigen (tPSA) levels, higher risk for PCa, and lower free/total PSA (f/t PSA) ratio. Specifically, each unit increase of log2 (SII) was associated with a 0.22 ng/mL increase in tPSA (β: 0.22, 95% confidence intervals [CI] 0.05-0.38), a 2.22% decline in f/t PSA ratio (β: -2.22, 95% CI -3.20 to -1.23), and a 52% increased odds of being at high risk for PCa (odds ratio [OR]: 1.52, 95% CI 1.13-2.04). People in the top quartile of log2 (SII) exhibited 0.55 ng/mL increased tPSA (β: 0.55, 95% CI 0.19-0.90), 4.39% reduced f/t PSA ratio (β: -4.39, 95% CI -6.50 to -2.27), and 168% increased odds of being at high risk for PCa (OR: 2.68, 95% CI 1.32-5.46) compared to those in the bottom quartile.

CONCLUSION

Systemic immune and inflammatory condition, as represented by SII, is independently and positively associated with tPSA levels and the risk for PCa, as well as independently and negatively associated with f/t PSA ratio among middle-aged and older US males. These findings may enhance the effectiveness of PCa screening in predicting positive biopsy results.

Association between monocyte-to-lymphocyte ratio and prostate cancer in the U.S. population: a population-based study

Introduction

Monocyte-to-lymphocyte ratio (MLR) is a convenient and noninvasive inflammatory biomarker, and inflammation has been reported to be associated with prostate cancer (PCa). Our objective was to ascertain any possible correlation between PCa and MLR.

Methods

We utilized data from the 1999-2020 cycles of the National Health and Nutrition Examination Survey (NHANES) regarding MLR and PCa. The independent associations of MLR and other inflammatory biomarkers (platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), system inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI)) with PCa was investigated using weighted multivariate logistic regression and generalized additive models. Receiver operating characteristic (ROC) curves were conducted to evaluate and contrast their diagnostic capabilities.

Results

The analysis we conducted comprised 25,367 persons in total. The mean MLR was 0.31 ± 0.14. The prevalence of PCa was 3.1%. A positive association was found between MLR and PCa (OR = 2.28; 95% CI: 1.44, 3.62). According to the interaction tests, age, body mass index (BMI), hypertension, diabetes, and smoking status did not significantly impact the relationship between MLR and PCa (all p for interaction >0.05). ROC analysis showed that MLR had a stronger discriminative ability and accuracy in predicting PCa than other inflammatory biomarkers (NLR, SII, AISI, PLR, and SIRI).

Conclusion

MLR might be better than other inflammatory biomarkers (NLR, SIRI, AISI, PLR, and SII) in predicting PCa. American adults who have elevated levels of MLR, NLR, PLR, SII, and AISI should be aware that they have a greater risk of PCa.

Development and validation of a model for predicting the risk of prostate cancer

BACKGROUND

Abnormal hematologic parameters before patients undergoing prostate biopsy play a pivotal role in guiding the surgical management of prostate cancer (PCa) incidence. This study aims to establish the first nomogram for predicting PCa risk for better surgical management.

METHODS

We retrospectively reviewed and analyzed the data including basic information, preoperative hematologic parameters, and imaging examination of 540 consecutive patients who underwent transrectal ultrasound (TRUS)-guided prostate biopsy for elevated prostate-specific antigen (PSA) in our medical center between 2017 and 2021. Logistic regression analysis was used to determine the risk factors for PCa occurrence, and the nomogram was constructed to predict PCa occurrence. Finally, the data including 121 consecutive patients in 2022 were prospectively collected to further verify the results.

RESULTS

In retrospective analyses, univariate and multivariate logistic analyses identified that three variables including age, diabetes, and De Ritis ratio (aspartate transaminase/alanine transaminase, AST/ALT) were determined to be significantly associated with PCa occurrence. A nomogram was constructed based on these variables for predicting the risk of PCa, and a satisfied predictive accuracy of the model was determined with a C-index of 0.765, supported by a prospective validation group with a C-index of 0.736. The Decision curve analysis showed promising clinical application. In addition, our results also showed that the De Ritis ratio was significantly correlated with the clinical stage of PCa patients, including T, N, and M stages, but insignificantly related to the Gleason score.

CONCLUSIONS

The increased De Ritis ratio was significantly associated with the risk and clinical stage of PCa and this nomogram with good discrimination could effectively improve individualized surgical management for patient underdoing prostate biopsy.

Association between platelet‑to‑lymphocyte ratio and serum prostate specific antigen

There is evidence that the systemic inflammatory response may have an impact on prostate-specific antigen (PSA) levels. However, the relationship between the platelet-to-lymphocyte ratio (PLR) and PSA remains unclear. As a result, the relationship between PLR and PSA using the National Health and Nutrition Examination Survey (NHANES) database was examined. After the screening, 6,638 participants out of 52,186 in the NHANES survey conducted between 2001 to 2010 were suitable for the present study. The PLR was the independent variable in the present study, and PSA was the dependent variable. The selected subjects in the present study had an average age of 58.563±11.848 years. After controlling for covariates, the results showed that with every increase in PLR, the PSA concentration increased by 0.004 ng/ml (0.001, 0.007). This difference was statistically significant. Furthermore, a smoothing curve based on a fully adjusted model was created to investigate the possibility of a linear relationship between PLR and PSA concentration in men from USA. In men from USA, an independent and positive correlation between PLR and PSA was identified, which could potentially result in overdiagnosis of asymptomatic prostate cancer in populations with higher PLR levels.

Exploration of diagnostic biomarkers, microenvironment characteristics, and ursolic acid's therapeutic effect for benign prostate hyperplasia

Benign prostatic hyperplasia (BPH) and early-stage prostate cancer (PC) have similar symptoms, making it challenging to differentially diagnose these two conditions. The study used Weighted Gene Co-Expression Network Analysis, as well as two machine learning strategies to identify BPH-specific biomarkers based on an integrated transcriptome data from 922 samples. Eight prognostic genes (ALCAM, COL6A2, CRISP2, FOXF2, IGF1, PTN, SCN7A, and UAP1) were identified to be BPH-specific biomarkers with high accuracy and specificity. Moreover, we constructed a seven-gene diagnostic classifier to distinguish BPH from PC. The infiltrations of plasmacytoid dendritic cells and neutrophil cells showed distinct differences between BPH and non-BPH groups. Additionally, ursolic acid can reverse transcriptional features associated with the occurrence and progression of BPH. Both in vivo and in vitro experiments have confirmed that it induces apoptosis of BPH cells and inhibits cell proliferation by promoting cell cycle S-phase arrest. The diagnostic biomarkers, microenvironment characteristics, and therapeutic effect of ursolic acid explored in this study offer new diagnostic and therapeutic strategies for BPH.

Role of inflammatory factors in prediction of Gleason score and its upgrading in localized prostate cancer patients after radical prostatectomy

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.

Prognostic significance of pretreatment systemic immune-inflammation index in patients with prostate cancer: a meta-analysis

BACKGROUND

The SII (systemic immune-inflammation index) has been extensively reported to have a prognostic value in prostate cancer (PCa), despite the unconformable results. The purpose of this meta-analysis is to quantify the effect of pretreatment SII on survival outcomes in patients with PCa.

METHODS

The following databases were searched: Web of Science, Cochrane Library, PubMed, Embase, and China National Knowledge Infrastructure (CNKI). For exploration of the SII's correlations with the overall survival (OS) and the progression-free survival/biochemical recurrence-free survival (PFS/bRFS) in PCa, the pooled hazard ratios (HRs) were assessed within 95% confidence intervals (CIs).

RESULTS

The present meta-analysis covered 10 studies with 8133 patients. Among the PCa population, a high SII was linked significantly to poor OS (HR = 2.63, 95% CI = 1.87-3.70, p < 0.001), and worse PFS/bRFS (HR = 2.49, 95% CI = 1.30-4.77, p = 0.006). However, a high SII was not linked significantly to T stage (OR = 1.69, 95% CI = 0.86-3.33, p = 0.128), the metastasis to lymph node (OR = 1.69, 95% CI = 0.69-4.16, p = 0.251), age (OR = 1.41, 95% CI = 0.88-2.23, p = 0.150), or the Gleason score (OR = 1.32, 95% CI = 0.88-1.96, p = 0.178).

CONCLUSIONS

For the PCa sufferers, the SII might be a promising prognostic biomarker, which is applicable to the high-risk subgroup identification, and provide personalized therapeutic strategies.

Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4-20 ng/mL

Excessive prostate biopsy is a common problem for clinicians. Although some hematological and bi-parametric magnetic resonance imaging (bpMRI) parameters might help increase the rate of positive prostate biopsies, there is a lack of studies on whether their combination can further improve clinical detection efficiency. We retrospectively enrolled 394 patients with PSA levels of 4-20 ng/mL who underwent prebiopsy bpMRI during 2010-2021. Based on bpMRI and hematological indicators, six models and a nomogram were constructed to predict the outcomes of biopsy. Furthermore, we constructed and evaluated a risk scoring model based on the nomogram. Age, prostate-specific antigen (PSA) density (PSAD), systemic immune-inflammation index, cystatin C level, and the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 score were significant predictors of prostate cancer (PCa) on multivariable logistic regression analyses (P < 0.05) and the five parameters were used to construct the XYFY nomogram. The area under the receiver operating characteristic (ROC) curve (AUC) of the nomogram was 0.916. Based on the nomogram, a risk scoring model (XYFY risk model) was constructed and then we divided the patients into low-(XYFY score: < 95), medium-(XYFY score: 95-150), and, high-risk (XYFY score: > 150) groups. The predictive values for diagnosis of PCa and clinically-significant PCa among the three risk groups were 3.0%(6/201), 41.8%(51/122), 91.5%(65/71); 0.5%(1/201), 19.7%(24/122), 60.6%(43/71), respectively. In conclusion, in this study, we used hematological and bpMRI parameters to establish and internally validate a XYFY risk scoring model for predicting the biopsy outcomes for patients with PSA levels of 4-20 ng/mL and this risk model would support clinical decision-making and reduce excessive biopsies.

Revealing the prognostic and clinicopathological significance of systemic immune-inflammation index in patients with different stage prostate cancer: A systematic review and meta-analysis

Background

A novel inflammatory marker called the systemic immune-inflammation index (SII) was applied to predict the prognosis of different cancers. However, the role of SII in prostate cancer (PCa) remains unclear. This systematic review aims to explore the prognostic role of SII in different stage PCa.

Methods

We comprehensively searched three public databases: PubMed, EMBASE, and the Cochrane Library. The hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs) were extracted to evaluate the association between SII and the prognosis and clinicopathological characteristics in different stage PCa patients.

Results

Ten studies and 7,986 patients were enrolled in our meta-analysis, 1,442 patients were diagnosed with metastatic-castration resistant prostate cancer (mCRPC), and 6544 patients were diagnosed with non-metastatic prostate cancer (nmPCa). According to the pooled results, we found that a high SII was associated with worse overall survival (OS) in mCRPC patients (HR = 1.94, 95% CI: 1.26–3.01, p = 0.003), and a high SII was associated with biochemical recurrence-free survival (BFS) in nmPCa patients (HR = 1.85, 95% CI: 1.06–3.24, p = 0.031). But there was no significant association observed between SII and progression-free survival (PFS) in mCRPC patients (HR = 1.90, 95% CI: 0.87–4.14, p = 0.107). And we found that the high SII was associated with advanced tumor stage of PCa (OR = 2.19, 95% CI: 1.11–4.33, p = 0.024), presence of lymph node involvement (OR = 2.72, 95% CI: 1.96–3.76, p &lt; 0.001) and Gleason score (OR = 1.27, 95% CI: 1.13–1.44, p &lt; 0.001).

Conclusion

High SII was associated with bad OS in mCRPC patients, and associated with bad BFS and some adverse pathological features in nmPCa patients. We think SII can be a prognostic predictor for PCa patients. The application of SII will advance the diagnosis and treatment of different stage prostate cancer.

The Values of Systemic Immune-Inflammation Index and Neutrophil-Lymphocyte Ratio in Predicting Biochemical Recurrence in Patients With Localized Prostate Cancer After Radical Prostatectomy

Purpose

To investigate the association between preoperative systemic immune-inflammation index (SII) and neutrophil-lymphocyte ratio (NLR) and oncological outcomes in localized prostate cancer (PCa) patients after radical prostatectomy (RP).

Methods

Between January 2014 and December 2019, 291 patients with pathologically confirmed localized PCa who underwent RP were included in this study. The threshold values of SII and NLR for biochemical recurrence (BCR) were calculated according to Youden's index based on the receiver operating characteristic (ROC) curve, then the patients were divided into two groups by the threshold values of SII and NLR, and the clinicopathological outcomes were analyzed and compared between groups, respectively. The binary logistic regression model was used to evaluate the association between SII, NLR, and pathological outcomes including Gleason score (GS) and pathological T (pT) stage. Kaplan-Meier curves and univariable and multivariable Cox regression models were used to determine the association between high SII, high NLR, and BCR-free survival, respectively.

Results

The median follow-up time was 48 months (IQR 36-62), and 114 (39.18%) patients developed BCR. The AUC of SII for BCR was 0.813 (P < 0.001), with a threshold value of 528.54, a sensitivity of 72.9%, and a specificity of 76.3%; the AUC of NLR for BCR was 0.824 (P < 0.001), with a threshold value of 2.62, a sensitivity of 71.2%, and a specificity of 81.6%. Patients were divided into two groups according to the threshold values of SII and NLR, respectively. Patients in the high SII group had higher tPSA, GS, pT stage, and BCR rate than patients in the low SII group (P = 0.004, 0.04, 0.007, and <0.001, respectively), and patients in the high NLR group had higher tPSA, GS, pT stage, and BCR rate than patients in the low NLR group (P = 0.04, 0.02, 0.006, and <0.001, respectively). Multivariable logistic regression analysis revealed that high SII was significantly correlated with adverse pathological outcomes of GS (HR, 1.656; 95% CI, 1.00-2.742, P = 0.042) and pT stage (HR, 1.478; 95% CI, 0.972-3.64, P = 0.028); there was no association between high NLR and pathological events. Kaplan-Meier analysis showed significantly poorer BCR-free survival in patients with high SII or high NLR (P < 0.001 and <0.001, respectively). By using the multivariable Cox regression model, high SII (HR, 4.521; 95% CI, 2.262-9.037, P < 0.001) and high NLR (HR, 4.787; 95% CI, 2.339-9.798, P < 0.001) were both significant predictors of BCR after RP.

Conclusion

High SII was significantly related to unfavorable clinicopathological outcomes. High preoperative SII and NLR were related to higher BCR rate in localized PCa after RP, and they were all independent risk factors associated with shorter BCR-free survival. These two factors might provide promising and inexpensive methods for predicting clinical outcomes in patients with RP.

Template-Independent Poly(A)-Tail Decay and RNASEL as Potential Cellular Biomarkers for Prostate Cancer Development

Simple Summary

The ultimate need in cancer tissue is to adapt translation machinery to accelerated protein synthesis in a rapidly proliferating environment. Our study was designed with the aim of integrating fundamental and clinical research to find new biomarkers for prostate cancer (PC) with clinical usefulness for the stratification prediction of healthy tissue transition into malignant phenotype. This study revealed: (i) an entirely novel mechanism of the regulatory influence of Poly(A) deadenylase in mRNAs translational activity and the 3′ mRNA untranslated region (3′UTR) length in cancer tissue and its regulation by the poly(A) decay; (ii) the RNASEL interrelationship with the inflammatory pattern of PC and corresponding tumor-adjacent and healthy tissue; and (iii) the sensitivity, specificity, and predictive value of these enzymes. The proposed manuscript is based on the use of specific biochemical and immunoassay methods with the principal research adapted for the use of tissue specimens.

Abstract

The post-transcriptional messenger RNA (mRNA) decay and turnover rate of the template-independent poly(A) tail, localized at the 3′-untranslated region (3′UTR) of mRNA, have been documented among subtle mechanisms of uncontrolled cancer tissue growth. The activity of Poly(A) deadenylase and the expression pattern of RNASEL have been examined. A total of 138 prostate tissue specimens from 46 PC patients (cancer specimens, corresponding adjacent surgically healthy tissues, and in their normal counterparts, at least 2 cm from carcinoma) were used. For the stratification prediction of healthy tissue transition into malignant phenotype, the enzyme activity of tumor-adjacent tissue was considered in relation to the presence of microfocal carcinoma. More than a four-times increase in specific enzyme activity (U/L g.prot) was registered in PC on account of both the dissociation of its inhibitor and genome reprogramming. The obtained ROC curve and Youden index showed that Poly(A) deadenylase identified PC with a sensitivity of 93.5% and a specificity of 94.6%. The RNASEL expression profile was raised significantly in PC, but the sensitivity was 40.5% and specificity was 86.9%. A significantly negative correlation between PC and control tissue counterparts with a higher expression pattern in lymphocyte-infiltrated samples were reported. In conclusion, significantly upregulated Poly(A) deadenylase activity may be a checkpoint for the transition of precancerous lesion to malignancy, while RNASEL may predict chronic inflammation.

The tumor innate immune microenvironment in prostate cancer: an overview of soluble factors and cellular effectors

Prostate cancer (PCa) accounts as the most common non-cutaneous disease affecting males, and as the first cancer, for incidence, in male. With the introduction of the concept of immunoscore, PCa has been classified as a cold tumor, thus driving the attention in the development of strategies aimed at blocking the infiltration/activation of immunosuppressive cells, while favoring the infiltration/activation of anti-tumor immune cells. Even if immunotherapy has revolutionized the approaches to cancer therapy, there is still a window failure, due to the immune cell plasticity within PCa, that can acquire pro-tumor features, subsequent to the tumor microenvironment (TME) capability to polarize them. This review discussed selected relevant soluble factors [transforming growth factor-beta (TGFβ), interleukin-6 (IL-6), IL-10, IL-23] and cellular components of the innate immunity, as drivers of tumor progression, immunosuppression, and angiogenesis within the PCa-TME.