Marked Prognostic Impact of Minimal Lymphatic Tumor Spread in Prostate Cancer

Size and SUVmax define the contribution of nodal metastases to PSA in oligorecurrent prostate cancer

BACKGROUND

To evaluate how prostate-specific antigen (PSA) levels decrease after removal of isolated prostate cancer (PCa) nodal metastases in relation to their diameter/volume ("PSA-density of PCa-metastases") and maximum standardized uptake value (SUVmax).

METHODS

A total of 83 consecutive patients with solitary nodal recurrence after radical prostatectomy who underwent prostate-specific membrane antigen-radioguided salvage surgery were retrospectively analyzed. Using multivariable linear regression models, the PSA-decrease after removal of each PCa-metastases (=PSA-contribution of each PCa-metastases) was correlated with the long axis diameter/estimated volume and the SUVmax of each removed metastasis. Sizes were measured by imaging and histopathologic examination.

RESULTS

A total of 83 patients were included with a median (interquartile range [IQR]) PSA-decrease of 0.56 [0.22, 1.31] ng/mL after salvage surgery. The median [IQR] long axis diameters in imaging and histopathological examination were 8.0 [6.0, 11.0] mm and 8.4 [5.5, 11.1] mm, respectively. The median [IQR] estimated volumes were 0.13 [0.05, 0.32] cc (imaging) and 0.05 [0.02, 0.17] cc (pathology). In multivariable linear regression analyses, the estimated PSA-contribution ([95% confidence interval [CI]) of each millimeter of long axis diameter was 0.09 [0.03, 0.14] ng/mL (imaging) or 0.08 [0.03, 0.12] ng/mL (histology). The minimum diameter for biochemical recurrence (PSA ≥ 0.2 ng/mL) was >2.2 mm (imaging) or >2.5 mm (histology). The estimated PSA-contribution [95% CI] of each cc cancer volume was 1.23 [0.51, 1.94] ng/mL (imaging) or 1.46 [0.40, 2.52] ng/mL (histology). SUVmax as surrogate parameter for tissue composition was associated with increased PSA-contribution of PCa-metastases (+0.03-0.05 ng/mL per unit increase).

CONCLUSIONS

The diameter/volume and SUVmax of metastatic tissue correlate with its contribution to PSA levels. Therefore, very small metastases may produce too little PSA for biochemical recurrence.

Biparametric MRI of the prostate radiomics model for prediction of pelvic lymph node metastasis in prostate cancers : a two-centre study

OBJECTIVES

Exploring the value of adding correlation analysis (radiomic features (RFs) of pelvic metastatic lymph nodes and primary lesions) to screen RFs of primary lesions in the feature selection process of establishing prediction model.

METHODS

A total of 394 prostate cancer (PCa) patients (263 in the training group, 74 in the internal validation group and 57 in the external validation group) from two tertiary hospitals were included in the study. The cases with pelvic lymph node metastasis (PLNM) positive in the training group were diagnosed by biopsy or MRI with a short-axis diameter ≥ 1.5 cm, PLNM-negative cases in the training group and all cases in validation group were underwent both radical prostatectomy (RP) and extended pelvic lymph node dissection (ePLND). The RFs of PLNM-negative lesion and PLNM-positive tissues including primary lesions and their metastatic lymph nodes (MLNs) in the training group were extracted from T2WI and apparent diffusion coefficient (ADC) map to build the following two models by fivefold cross-validation: the lesion model, established according to the primary lesion RFs selected by t tests and absolute shrinkage and selection operator (LASSO); the lesion-correlation model, established according to the primary lesion RFs selected by Pearson correlation analysis (RFs of primary lesions and their MLNs, correlation coefficient > 0.9), t test and LASSO. Finally, we compared the performance of these two models in predicting PLNM.

RESULTS

The AUC and the DeLong test of AUC in the lesion model and lesion-correlation model were as follows: training groups (0.8053, 0.8466, p = 0.0002), internal validation group (0.7321, 0.8268, p = 0.0429), and external validation group (0.6445, 0.7874, p = 0.0431), respectively.

CONCLUSION

The lesion-correlation model established by features of primary tumors correlated with MLNs has more advantages than the lesion model in predicting PLNM.

68Ga-PSMA-11 PET and mpMRI in the diagnosis of initial lymph node staging of prostate cancer: a head-to-head comparative meta-analysis

Purpose

This meta-analysis evaluates the comparative diagnostic efficacy of 68Ga-prostate-specific membrane antigen-11 PET (68Ga-PSMA-11 PET) and multiparametric MRI (mpMRI) for the initial lymph node staging of prostate cancer.

Methods

We searched PubMed and Embase databases through October 2023 for studies that provide a head-to-head comparison of 68Ga-PSMA-11 PET and mpMRI, using pelvic lymph node dissection as the gold standard. We assessed sensitivity and specificity using the DerSimonian and Laird method, with variance stabilization via the Freeman-Tukey double inverse sine transformation. The quality of included studies was evaluated using the Quality Assessment of Diagnostic Performance Studies (QUADAS-2) tool.

Results

The meta-analysis incorporated 13 articles, involving a total of 1,527 patients. 68Ga-PSMA-11 PET demonstrated an overall sensitivity of 0.73 (95% CI: 0.51-0.91) and a specificity of 0.94 (95% CI: 0.88-0.99). In comparison, mpMRI showed a sensitivity of 0.49 (95% CI: 0.30-0.68) and a specificity of 0.94 (95% CI: 0.88-0.99). Although 68Ga-PSMA-11 PET appeared to be more sensitive than mpMRI, the differences in sensitivity (p = 0.11) and specificity (p = 0.47) were not statistically significant.

Conclusion

Our findings indicated that 68Ga-PSMA-11 PET and mpMRI exhibit similar sensitivity and specificity in the diagnosis of initial lymph node staging of prostate cancer. However, given that most included studies were retrospective, further prospective studies with larger sample sizes are essential to validate these results.

Systematic Review Registration

PROSPERO code is CRD42023495266.

Size of lymph-node metastases in prostate cancer patients undergoing radical prostatectomy: implication for imaging and oncologic follow-up of 2705 lymph-node positive patients

BACKGROUND

Despite modern imaging modalities, lymph-node staging before radical prostatectomy (RP) remains challenging in patients with prostate cancer (PCa). The visibility of lymph-node metastases (LNMs) is critically influenced by their size.

OBJECTIVE

This study aims to describe the distribution of maximal tumor diameters (i.e., size) in LNMs of pN1-PCa at RP and its consequences on visibility in preoperative imaging and oncological outcomes.

DESIGN, SETTING, AND PARTICIPANTS

A total of 2705 consecutive patients with pN1-PCa at RP, harboring a cumulative 7510 LNMs, were analyzed. Descriptive and multivariable analyses addressed the risk of micrometastases (MM)-only disease and the visibility of LNMs. Kaplan-Meier curves and Cox analyses were used for biochemical recurrence-free survival (BCRFS) stratified for MM-only disease.

RESULTS

The median LNM size was 4.5mm (interquartile range (IQR): 2.0-9.0 mm). Of 7510 LNMs, 1966 (26%) were MM (≤ 2mm). On preoperative imaging, 526 patients (19%) showed suspicious findings (PSMA-PET/CT: 169/344, 49%). In multivariable analysis, prostate-specific antigen (PSA) (OR 0.98), age (OR 1.01), a Gleason score greater than 7 at biopsy (OR 0.73), percentage of positive cores at biopsy (OR 0.36), and neoadjuvant treatment (OR 0.51) emerged as independent predictors for less MM-only disease (p < 0.05). Patients with MM-only disease compared to those harboring larger LNMs had a longer BCRFS (median 60 versus 29 months, p < 0.0001).

CONCLUSION

Overall, 26% of LNMs were MM (≤ 2mm). Adverse clinical parameters were inversely associated with MM at RP. Consequently, PSMA-PET/CT did not detect a substantial proportion of LNMs. LNM size and count are relevant for prognosis.

The Hunt for Lymph Nodes: Is Total Submission of Standard-Template and Extended-Template Pelvic Lymph Node Dissections Necessary for Detecting Metastatic Prostate Cancer?

CONTEXT.—

There are no consensus guidelines on submission of pelvic lymph node dissection (PLND) specimens for radical prostatectomies. Complete submission is only performed by a minority of laboratories. Our institution has been following this practice for standard-template and extended-template PLND.

OBJECTIVE.—

To investigate the utility of total submission of PLND specimens for prostate cancer and understand its impact on patients and the laboratory.

DESIGN.—

Retrospective study examining 733 cases of radical prostatectomies with PLND performed at our institution. Reports and slides with positive lymph nodes (LNs) were reviewed. Data on LN yield, cassette usage, and impact of submission of remaining fat after dissection of grossly identifiable LNs were assessed.

RESULTS.—

Most cases involved submission of extra cassettes for remaining fat (97.5%, n = 697 of 715). Extended PLND yielded a higher mean number of total and positive LNs versus standard PLND (P < .001). However, extended PLND required significantly more cassettes for remaining fat (mean, 8; range, 0-44). There was poor correlation between number of cassettes submitted for PLND with total and positive LN yield and between remaining fat with LN yield. Most positive LNs were grossly identified (88.5%, n = 139 of 157) and were typically larger than those not. Only 4 cases (0.6%, n = 4 of 697) would have been understaged without complete submission of PLND.

CONCLUSIONS.—

Total submission of PLND increases detection of metastasis and LN yield yet increases workload significantly with only minimal patient management impact. Hence, we recommend that meticulous gross identification and submission of all LNs be pursued without the need to submit the remaining fat of PLND.

Biopsy-free AI-aided precision MRI assessment in prediction of prostate cancer biochemical recurrence

BACKGROUND

To investigate the predictive ability of high-throughput MRI with deep survival networks for biochemical recurrence (BCR) of prostate cancer (PCa) after prostatectomy.

METHODS

Clinical-MRI and histopathologic data of 579 (train/test, 463/116) PCa patients were retrospectively collected. The deep survival network (iBCR-Net) is based on stepwise processing operations, which first built an MRI radiomics signature (RadS) for BCR, and predicted the T3 stage and lymph node metastasis (LN+) of tumour using two predefined AI models. Subsequently, clinical, imaging and histopathological variables were integrated into iBCR-Net for BCR prediction.

RESULTS

RadS, derived from 2554 MRI features, was identified as an independent predictor of BCR. Two predefined AI models achieved an accuracy of 82.6% and 78.4% in staging T3 and LN+. The iBCR-Net, when expressed as a presurgical model by integrating RadS, AI-diagnosed T3 stage and PSA, can match a state-of-the-art histopathological model (C-index, 0.81 to 0.83 vs 0.79 to 0.81, p > 0.05); and has maximally 5.16-fold, 12.8-fold, and 2.09-fold (p < 0.05) benefit to conventional D'Amico score, the Cancer of the Prostate Risk Assessment (CAPRA) score and the CAPRA Postsurgical score.

CONCLUSIONS

AI-aided iBCR-Net using high-throughput MRI can predict PCa BCR accurately and thus may provide an alternative to the conventional method for PCa risk stratification.

Development of machine learning prognostic models for overall survival of prostate cancer patients with lymph node-positive

Prostate cancer (PCa) patients with lymph node involvement (LNI) constitute a single-risk group with varied prognoses. Existing studies on this group have focused solely on those who underwent prostatectomy (RP), using statistical models to predict prognosis. This study aimed to develop an easily accessible individual survival prediction tool based on multiple machine learning (ML) algorithms to predict survival probability for PCa patients with LNI. A total of 3280 PCa patients with LNI were identified from the Surveillance, Epidemiology, and End Results (SEER) database, covering the years 2000-2019. The primary endpoint was overall survival (OS). Gradient Boosting Survival Analysis (GBSA), Random Survival Forest (RSF), and Extra Survival Trees (EST) were used to develop prognosis models, which were compared to Cox regression. Discrimination was evaluated using the time-dependent areas under the receiver operating characteristic curve (time-dependent AUC) and the concordance index (c-index). Calibration was assessed using the time-dependent Brier score (time-dependent BS) and the integrated Brier score (IBS). Moreover, the beeswarm summary plot in SHAP (SHapley Additive exPlanations) was used to display the contribution of variables to the results. The 3280 patients were randomly split into a training cohort (n = 2624) and a validation cohort (n = 656). Nine variables including age at diagnosis, race, marital status, clinical T stage, prostate-specific antigen (PSA) level at diagnosis, Gleason Score (GS), number of positive lymph nodes, radical prostatectomy (RP), and radiotherapy (RT) were used to develop models. The mean time-dependent AUC for GBSA, RSF, and EST was 0.782 (95% confidence interval [CI] 0.779-0.783), 0.779 (95% CI 0.776-0.780), and 0.781 (95% CI 0.778-0.782), respectively, which were higher than the Cox regression model of 0.770 (95% CI 0.769-0.773). Additionally, all models demonstrated almost similar calibration, with low IBS. A web-based prediction tool was developed using the best-performing GBSA, which is accessible at https://pengzihexjtu-pca-n1.streamlit.app/ . ML algorithms showed better performance compared with Cox regression and we developed a web-based tool, which may help to guide patient treatment and follow-up.

Development and External Validation of a Machine Learning Model for Prediction of Lymph Node Metastasis in Patients with Prostate Cancer

BACKGROUND

Pelvic lymph node dissection (PLND) is the gold standard for diagnosis of lymph node involvement (LNI) in patients with prostate cancer. The Roach formula, Memorial Sloan Kettering Cancer Center (MSKCC) calculator, and Briganti 2012 nomogram are elegant and simple traditional tools used to estimate the risk of LNI and select patients for PLND.

OBJECTIVE

To determine whether machine learning (ML) can improve patient selection and outperform currently available tools for predicting LNI using similar readily available clinicopathologic variables.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective data for patients treated with surgery and PLND between 1990 and 2020 in two academic institutions were used.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We trained three models (two logistic regression models and one gradient-boosted trees-based model [XGBoost]) on data provided from one institution (n = 20267) with age, prostate-specific antigen (PSA) levels, clinical T stage, percentage positive cores, and Gleason scores as inputs. We externally validated these models using data from another institution (n = 1322) and compared their performance to that of the traditional models using the area under the receiver operating characteristic curve (AUC), calibration, and decision curve analysis (DCA).

RESULTS AND LIMITATIONS

LNI was present in 2563 patients (11.9%) overall, and in 119 patients (9%) in the validation data set. XGBoost had the best performance among all the models. On external validation, its AUC outperformed that of the Roach formula by 0.08 (95% confidence interval [CI] 0.042-0.12), the MSKCC nomogram by 0.05 (95% CI 0.016-0.070), and the Briganti nomogram by 0.03 (95% CI 0.0092-0.051; all p < 0.05). It also had better calibration and clinical utility in terms of net benefit on DCA across relevant clinical thresholds. The main limitation of the study is its retrospective design.

CONCLUSIONS

Taking all measures of performance together, ML using standard clinicopathologic variables outperforms traditional tools in predicting LNI.

PATIENT SUMMARY

Determining the risk of cancer spread to the lymph nodes in patients with prostate cancer allows surgeons to perform lymph node dissection only in patients who need it and avoid the side effects of the procedure in those who do not. In this study, we used machine learning to develop a new calculator to predict the risk of lymph node involvement that outperformed traditional tools currently used by oncologists.

Role of lymphatic invasion in predicting biochemical recurrence after radical prostatectomy

Objective

Lymphatic invasion in prostate cancer is associated with poor prognosis. However, there is no consensus regarding the clinical and prognostic value of lymphatic invasion. This study aimed to investigate the prognostic value of lymphatic invasion in biochemical recurrence (BCR) and compare the recurrence rates between patients with lymphatic invasion and lymph node metastasis.

Methods

We retrospectively analyzed 2,207 patients who underwent radical prostatectomy (RP) without pelvic lymph node dissection (PLND) and 742 patients who underwent RP with PLND for clinically localized or locally advanced prostate cancer, between 1993 and 2020, at Seoul National University Hospital. Kaplan-Meier analysis was performed to estimate BCR-free survival (BCRFS) using the log-rank test. The Cox proportional hazards model was used to identify the significant factors for BCR. Propensity score matching was performed with a 1:2 ratio to match age, initial PSA level, pathological T stage, and Gleason score to exclude confounding effects.

Results

Of the 2,207 patients who underwent RP without PLND, lymphatic invasion (L1Nx) was observed in 79 (3.5%) individuals. Among the 742 patients who underwent RP with PLND, lymph node metastases were found in 105 patients (14.2%). In patients with lymph node metastasis, lymphatic invasion was observed in 50 patients (47.6%), whereas lymphatic invasion was observed in 53 patients (8.3%) among those without lymph node metastasis. In patients who underwent RP without PLND, Kaplan-Meier analysis showed significantly poorer BCR-free survival in the L1Nx group than in the L0Nx group (p < 0.001). In patients who underwent RP with PLND, the L1N0, L0N1, and L1N1 groups showed significantly worse prognoses than the L0N0 group (p < 0.001). However, there was no significant difference in BCRFS between the L1N0 and lymph node metastasis groups, including the L0N1 and L1N1 groups. After propensity score matching at a 1:2 ratio, the L1Nx group showed significantly poorer outcomes in terms of BCRFS than the L0Nx group (p = 0.05). In addition, the L1N0 group showed a significantly worse prognosis than the L0N0 group after propensity score matching.

Conclusion

Lymphatic invasion in radical prostatectomy specimens is an independent prognostic factor, which can complement lymph node status for predicting biochemical recurrence. Considering lymphatic invasion as an adverse pathological finding, similar to lymph node metastasis, adjuvant therapy could be considered in patients with lymphatic invasion.

Immunomodulatory properties of the lymphatic endothelium in the tumor microenvironment

The tumor microenvironment (TME) is an intricate complex and dynamic structure composed of various cell types, including tumor, stromal and immune cells. Within this complex network, lymphatic endothelial cells (LECs) play a crucial role in regulating immune responses and influencing tumor progression and metastatic dissemination to lymph node and distant organs. Interestingly, LECs possess unique immunomodulatory properties that can either promote or inhibit anti-tumor immune responses. In fact, tumor-associated lymphangiogenesis can facilitate tumor cell dissemination and metastasis supporting immunoevasion, but also, different molecular mechanisms involved in LEC-mediated anti-tumor immunity have been already described. In this context, the crosstalk between cancer cells, LECs and immune cells and how this communication can shape the immune landscape in the TME is gaining increased interest in recent years. In this review, we present a comprehensive and updated report about the immunomodulatory properties of the lymphatic endothelium within the TME, with special focus on primary tumors and tumor-draining lymph nodes. Furthermore, we outline emerging research investigating the potential therapeutic strategies targeting the lymphatic endothelium to enhance anti-tumor immune responses. Understanding the intricate mechanisms involved in LEC-mediated immune modulation in the TME opens up new possibilities for the development of innovative approaches to fight cancer.

The predictive value of machine learning and nomograms for lymph node metastasis of prostate cancer: a systematic review and meta-analysis

BACKGROUND

In clinical practice, there are currently a variety of nomograms for predicting lymph node metastasis (LNM) of prostate cancer. At the same time, some scholars have introduced machine learning (ML) into the prediction of LNM of prostate cancer. However, the predictive value of nomograms and ML remains controversial. Based on this situation, this systematic review and meta-analysis was performed to explore the predictive value of various nomograms currently recommended and newly-developed ML models for LNM in prostate cancer patients.

EVIDENCE ACQUISITION

Cochrane, PubMed, Embase, and Web of Science were searched up to November 1, 2022. The risk of bias in the included studies was evaluated using the Prediction model Risk of Bias Assessment Tool (PROBAST). The concordance index (C-index), sensitivity, and specificity were adopted to evaluate the predictive accuracy of the models.

RESULTS

Thirty-one studies (18,803 patients) were included. Seven kinds of nomograms currently recommended, dominated by Briganti nomogram or MSKCC nomogram, were covered in the included studies. For newly-developed ML models, the C-index for LNM prediction in the training set and validation set was 0.846 [95%CI (0.818, 0.873)] and 0.862 [95%CI (0.819-0.905)] respectively. Most ML models in the training set were based on Logistic Regression (LR), which had a sensitivity of 0.78 [95%CI (0.70, 0.85)] and a specificity of 0.85 [95%CI (0.77, 0.90)] in the training set, and a sensitivity of 0.81 [95%CI (0.67, 0.89)] and a specificity of 0.82 [95%CI (0.75, 0.88)] in the validation set. For the recommended nomograms, the C-index in the validation set was 0.745 [95%CI (0.701, 0.790)] for the Briganti nomogram and 0.714 [95%CI (0.662, 0.765)] for the MSKCC nomogram.

CONCLUSION

The predictive accuracy of ML is superior to existing clinically recommended nomograms, and appropriate updates can be conducted to existing nomograms according to special situations.

Application of machine learning algorithm in prediction of lymph node metastasis in patients with intermediate and high-risk prostate cancer

PURPOSE

This study aims to establish the best prediction model of lymph node metastasis (LNM) in patients with intermediate- and high-risk prostate cancer (PCa) through machine learning (ML), and provide the guideline of accurate clinical diagnosis and precise treatment for clinicals.

METHODS

A total of 24,470 patients with intermediate- and high-risk PCa were included in this study. Multivariate logistic regression model was used to screen the independent risk factors of LNM. At the same time, six algorithms, namely random forest (RF), naive Bayesian classifier (NBC), xgboost (XGB), gradient boosting machine (GBM), logistic regression (LR) and decision tree (DT) are used to establish risk prediction models. Based on the best prediction performance of ML algorithm, a prediction model is established, and the performance of the model is evaluated from three aspects: area under curve (AUC), sensitivity and specificity.

RESULTS

In multivariate logistic regression analysis, T stage, PSA, Gleason score and bone metastasis were independent predictors of LNM in patients with intermediate- and high-risk PCa. By comprehensively comparing the prediction model performance of training set and test set, GBM model has the best prediction performance (F1 score = 0.838, AUROC = 0.804). Finally, we developed a preliminary calculator model that can quickly and accurately calculate the regional LNM in patients with intermediate- and high-risk PCa.

CONCLUSION

T stage, PSA, Gleason and bone metastasis were independent risk factors for predicting LNM in patients with intermediate- and high-risk PCa. The prediction model established in this study performs well; however, the GBM model is the best one.

Exosomal cargos-mediated metabolic reprogramming in tumor microenvironment

Metabolic reprogramming is one of the hallmarks of cancer. As nutrients are scarce in the tumor microenvironment (TME), tumor cells adopt multiple metabolic adaptations to meet their growth requirements. Metabolic reprogramming is not only present in tumor cells, but exosomal cargos mediates intercellular communication between tumor cells and non-tumor cells in the TME, inducing metabolic remodeling to create an outpost of microvascular enrichment and immune escape. Here, we highlight the composition and characteristics of TME, meanwhile summarize the components of exosomal cargos and their corresponding sorting mode. Functionally, these exosomal cargos-mediated metabolic reprogramming improves the "soil" for tumor growth and metastasis. Moreover, we discuss the abnormal tumor metabolism targeted by exosomal cargos and its potential antitumor therapy. In conclusion, this review updates the current role of exosomal cargos in TME metabolic reprogramming and enriches the future application scenarios of exosomes.

Application of Indocyanine Green in Combination with Da Vinci Xi Robot in Surgeries on the Upper Urinary Tract: A Case Series Study

BACKGROUND

To explore the application value of intraoperative imaging by indocyanine green (ICG) injection through the collection system of the urinary tract for Da Vinci Xi robot navigation in complex surgeries on the upper urinary tract.

METHODS

Data of 14 patients who underwent complex surgeries of the upper urinary tract post-ICG injection through the collection system of the urinary tract in combination with Da Vinci Xi robot navigation in the Tianjin First Central Hospital between December 2019 and October 2021 were analyzed in this retrospective study. The operation duration, estimated blood loss, and exposure time of ureteral stricture to ICG were evaluated. The renal functions and tumor relapse were evaluated after surgery.

RESULTS

Of the fourteen patients, three had distal ureteral stricture, five had ureteropelvic junction obstruction, four presented duplicate kidney and ureter, one had a giant ureter, and one presented an ipsilateral native ureteral tumor after renal transplantation. The surgeries in all patients were successful, with no conversion to open surgery. In addition, no injury to the surrounding organs, anastomotic stenosis or leakage, or ICG injection-related side effects were detected. Imaging at 3 months post-operatively revealed improved renal functions compared to those before the operation. No tumor recurrence or metastasis was observed in patient 14.

CONCLUSION

Fluorescence imaging compensating for the inadequacy of tactile feedback in the surgical operating system has advantages in identifying the ureter, determining the site of ureteral stricture, and protecting the blood flow for the ureter.

Correlation analysis between immune-related genes and cell infiltration revealed prostate cancer immunotherapy biomarkers linked to T cells gamma delta

Prostate cancer (PCa) is a urological malignancy with poor prognosis. Immune-related genes are associated with immune infiltration in prostate cancer, but their role in immunogenic PCa is less well understood. We assessed the infiltration patterns of 22 immune cells in PCa and the relationship of immune-related differentially expressed genes (IDEGs) with them. The 87 IDEGs are involved in the interaction between the extracellular matrix and the tumor microenvironment. The model, including seven IDEGs (SLPI, DES, IAPP, NPY, ISG15, PLA2G2A, and HLA-DMB), showed a good predictive power. The SLPI expression is positively correlated with the infiltration level of T cells gamma delta. In addition, PCa has high infiltration levels in Macrophages M1 (18.07%) and Dendritic cells activated (17.64%). The correlation analysis between IDEGs and immune cell infiltration suggested that PCa immunotherapy biomarkers may be closely related to T cells gamma delta.

Multiparametric MRI-based radiomics model to predict pelvic lymph node invasion for patients with prostate cancer

OBJECTIVE

To identify which patient with prostate cancer (PCa) could safely avoid extended pelvic lymph node dissection (ePLND) by predicting lymph node invasion (LNI), via a radiomics-based machine learning approach.

METHODS

An integrative radiomics model (IRM) was proposed to predict LNI, confirmed by the histopathologic examination, integrating radiomics features, extracted from prostatic index lesion regions on MRI images, and clinical features via SVM. The study cohort comprised 244 PCa patients with MRI and followed by radical prostatectomy (RP) and ePLND within 6 months between 2010 and 2019. The proposed IRM was trained in training/validation set and evaluated in an internal independent testing set. The model's performance was measured by area under the curve (AUC), sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). AUCs were compared via Delong test with 95% confidence interval (CI), and the rest measurements were compared via chi-squared test or Fisher's exact test.

RESULTS

Overall, 17 (10.6%) and 14 (16.7%) patients with LNI were included in training/validation set and testing set, respectively. Shape and first-order radiomics features showed usefulness in building the IRM. The proposed IRM achieved an AUC of 0.915 (95% CI: 0.846-0.984) in the testing set, superior to pre-existing nomograms whose AUCs were from 0.698 to 0.724 (p < 0.05).

CONCLUSION

The proposed IRM could be potentially feasible to predict the risk of having LNI for patients with PCa. With the improved predictability, it could be utilized to assess which patients with PCa could safely avoid ePLND, thus reduce the number of unnecessary ePLND.

KEY POINTS

• The combination of MRI-based radiomics features with clinical information improved the prediction of lymph node invasion, compared with the model using only radiomics features or clinical features. • With improved prediction performance on predicting lymph node invasion, the number of extended pelvic lymph node dissection (ePLND) could be reduced by the proposed integrative radiomics model (IRM), compared with the existing nomograms.

Prognostic Impact of Lymphatic Invasion in Patients with High-Risk Prostate Cancer after Robot-Assisted Radical Prostatectomy and Extended Lymph Node Dissection: A Single-Institution Prospective Cohort Study

The prognostic impact of lymphatic invasion in patients with high-risk prostate cancer (PC) remains unclear. The aim of our single-institution prospective cohort study was to examine the impact of lymphatic invasion on biochemical recurrence (BCR) in patients with high-risk PC according to National Comprehensive Cancer Network (NCCN) criteria who underwent robot-assisted radical prostatectomy (RARP) and extended lymph node dissection (eLND). A total of 183 patients were included who underwent RARP and eLND for NCCN high-risk PC between June 2014 and August 2019. Lymphatic invasion in resected specimens was observed in 47 patients (26%), whereas lymph node metastasis was observed in 17 patients (9%). During follow-up, BCR was observed in 48 patients (26%). The BCR rate in patients with lymphatic invasion was significantly higher than that in patients without lymphatic invasion (p < 0.01). According to multivariable Cox proportional hazards regression analyses, lymphatic invasion was a significant independent predictor of BCR in the overall patient group and was independently associated with BCR, even in patients without lymph node metastasis. In conclusion, evaluation of lymphatic invasion could be useful in predicting BCR in patients undergoing RARP and eLND for high-risk PC.

Reactive Oxygen Species in Regulating Lymphangiogenesis and Lymphatic Function

The lymphatic system is pivotal for immunosurveillance and the maintenance of tissue homeostasis. Lymphangiogenesis, the formation of new lymphatic vessels from pre-existing vessels, has both physiological and pathological roles. Recent advances in the molecular mechanisms regulating lymphangiogenesis have opened a new area of research on reparative lymphangiogenesis for the treatment of various pathological disorders comprising neurological disorders, cardiac repair, autoimmune disease, obesity, atherosclerosis, etc. Reactive oxygen species (ROS) produced by the various cell types serve as signaling molecules in several cellular mechanisms and regulate various aspects of growth-factor-mediated responses, including lymphangiogenesis. The ROS, including superoxide anion, hydrogen peroxide, and nitric oxide, play both beneficial and detrimental roles depending upon their levels and cellular microenvironment. Low ROS levels are essential for lymphangiogenesis. On the contrary, oxidative stress due to enhanced ROS generation and/or reduced levels of antioxidants suppresses lymphangiogenesis via promoting lymphatic endothelial cell apoptosis and death. In this review article, we provide an overview of types and sources of ROS, discuss the role of ROS in governing lymphangiogenesis and lymphatic function, and summarize the role of lymphatics in various diseases.

Validation of In Vivo Nodal Assessment of Solid Malignancies with USPIO-Enhanced MRI: A Workflow Protocol

Background: In various cancer types, the first step towards extended metastatic disease is the presence of lymph node metastases. Imaging methods with sufficient diagnostic accuracy are required to personalize treatment. Lymph node metastases can be detected with ultrasmall superparamagnetic iron oxide (USPIO)-enhanced magnetic resonance imaging (MRI), but this method needs validation. Here, a workflow is presented, which is designed to compare MRI-visible lymph nodes on a node-to-node basis with histopathology. Methods: In patients with prostate, rectal, periampullary, esophageal, and head-and-neck cancer, in vivo USPIO-enhanced MRI was performed to detect lymph nodes suspicious of harboring metastases. After lymphadenectomy, but before histopathological assessment, a 7 Tesla preclinical ex vivo MRI of the surgical specimen was performed, and in vivo MR images were radiologically matched to ex vivo MR images. Lymph nodes were annotated on the ex vivo MRI for an MR-guided pathological examination of the specimens. Results: Matching lymph nodes of ex vivo MRI to pathology was feasible in all cancer types. The annotated ex vivo MR images enabled a comparison between USPIO-enhanced in vivo MRI and histopathology, which allowed for analyses on a nodal, or at least on a nodal station, basis. Conclusions: A workflow was developed to validate in vivo USPIO-enhanced MRI with histopathology. Guiding the pathologist towards lymph nodes in the resection specimens during histopathological work-up allowed for the analysis at a nodal basis, or at least nodal station basis, of in vivo suspicious lymph nodes with corresponding histopathology, providing direct information for validation of in vivo USPIO-enhanced, MRI-detected lymph nodes.

Preoperative red cell distribution width is associated with postoperative lymphovascular invasion in prostate cancer patients treated with radical prostatectomy: A retrospective study

PURPOSE

To investigate the relationship between baseline clinicopathological and laboratory variables especially hematological parameters and lymphovascular invasion (LVI) in patients who underwent radical prostatectomy (RP).

METHODS

We retrospectively evaluated 348 prostate cancer (PCa) patients who underwent RP in our center between May 2018 and June 2021. We divided them into non-LVI and LVI groups based on LVI status, and compared clinicopathological characteristics between non-LVI and LVI groups. Clinicopathological parameters including age, body mass index (BMI), history of hypertension and diabetes mellitus, neoadjuvant hormonal therapy (NHT), pathological stage T (pT) and lymph node status (pN), ISUP (international society of urological pathology) grade, positive surgical margin (PSM) rate, and hematological parameters containing prostate-specific antigen (PSA), whole blood parameters and inflammatory indexes were collected. The association between the clinicopathological parameters and the presence of LVI was identified by multivariate logistic regression analysis.

RESULTS

The pathological results of the RP specimen consisted of 53 (15.2%) patients with LVI and 295 (84.8%) cases without LVI. The level of PSA, percentages of advanced pT and grade, pN1, and PSM were significantly higher in the LVI group when compared with the non-LVI counterpart (p<0.001, p<0.001, p<0.001, p<0.001, p=0.007, respectively). Among the whole blood parameters, only red cell distribution width (RDW) was significantly different (41.2 ± 2.5 vs. 42.1 ± 3.1, p=0.035). Multivariate regression analysis demonstrated that RDW and NHT were negatively correlated with the presence of LVI (OR = 0.870, p=0.024; OR = 0.410, p=0.025), while PSA, ISUP, and pT were positively correlated with the presence of LVI (OR=1.013, p=0.005; OR =1.589, p=0.001; OR=1.655, p=0.008) after adjusting for confounding factors.

CONCLUSIONS

RDW rather than other whole blood parameters was independently and negatively associated with the presence of LVI in PCa patients, suggesting that RDW might play an essential role in PCa invasion.

Issues of origin, morphology and clinical significance of tumor microvessels in gastric cancer

Gastric cancer (GC) remains a serious oncological problem, ranking third in the structure of mortality from malignant neoplasms. Improving treatment outcomes for this pathology largely depends on understanding the pathogenesis and biological characteristics of GC, including the identification and characterization of diagnostic, prognostic, predictive, and therapeutic biomarkers. It is known that the main cause of death from malignant neoplasms and GC, in particular, is tumor metastasis. Given that angiogenesis is a critical process for tumor growth and metastasis, it is now considered an important marker of disease prognosis and sensitivity to anticancer therapy. In the presented review, modern concepts of the mechanisms of tumor vessel formation and the peculiarities of their morphology are considered; data on numerous factors influencing the formation of tumor microvessels and their role in GC progression are summarized; and various approaches to the classification of tumor vessels, as well as the methods for assessing angiogenesis activity in a tumor, are highlighted. Here, results from studies on the prognostic and predictive significance of tumor microvessels in GC are also discussed, and a new classification of tumor microvessels in GC, based on their morphology and clinical significance, is proposed for consideration.

Application of Machine Learning Techniques to Predict Bone Metastasis in Patients with Prostate Cancer

Objective

This study aimed to develop and validate a machine learning model for predicting bone metastases (BM) in prostate cancer (PCa) patients.

Methods

Demographic and clinicopathologic variables of PCa patients in the Surveillance, Epidemiology and End Results (SEER) database from 2010 to 2017 were retrospectively analyzed. We used six different machine learning algorithms, including Decision tree (DT), Random forest (RF), Multilayer Perceptron (MLP), Logistic regression (LR), Naive Bayes classifiers (NBC), and eXtreme gradient boosting (XGB), to build prediction models. External validation using data from 644 PCa patients of the First Affiliated Hospital of Nanchang University from 2010 to 2016. The performance of the models was evaluated using the area under receiver operating characteristic curve (AUC), accuracy score, sensitivity (recall rate) and specificity. A web predictor was developed based on the best performance model.

Results

A total of 207,137 PCa patients from SEER were included in this study. Of whom, 6725 (3.25%) developed BM. Gleason score, Prostate-specific antigen (PSA) value, T, N stage and age were found to be the risk factors of BM. The XGB model offered the best predictive performance among these 6 models (AUC: 0.962, accuracy: 0.884, sensitivity (recall rate): 0.906, and specificity: 0.879). An XGB model-based web predictor was developed to predict BM in PCa patients.

Conclusion

This study developed a machine learning model and a web predictor for predicting the risk of BM in PCa patients, which may help physicians make personalized clinical decisions and treatment strategy for patients.

Artificial Intelligence Combined With Big Data to Predict Lymph Node Involvement in Prostate Cancer: A Population-Based Study

Background

A more accurate preoperative prediction of lymph node involvement (LNI) in prostate cancer (PCa) would improve clinical treatment and follow-up strategies of this disease. We developed a predictive model based on machine learning (ML) combined with big data to achieve this.

Methods

Clinicopathological characteristics of 2,884 PCa patients who underwent extended pelvic lymph node dissection (ePLND) were collected from the U.S. National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. Eight variables were included to establish an ML model. Model performance was evaluated by the receiver operating characteristic (ROC) curves and calibration plots for predictive accuracy. Decision curve analysis (DCA) and cutoff values were obtained to estimate its clinical utility.

Results

Three hundred and forty-four (11.9%) patients were identified with LNI. The five most important factors were the Gleason score, T stage of disease, percentage of positive cores, tumor size, and prostate-specific antigen levels with 158, 137, 128, 113, and 88 points, respectively. The XGBoost (XGB) model showed the best predictive performance and had the highest net benefit when compared with the other algorithms, achieving an area under the curve of 0.883. With a 5%~20% cutoff value, the XGB model performed best in reducing omissions and avoiding overtreatment of patients when dealing with LNI. This model also had a lower false-negative rate and a higher percentage of ePLND was avoided. In addition, DCA showed it has the highest net benefit across the whole range of threshold probabilities.

Conclusions

We established an ML model based on big data for predicting LNI in PCa, and it could lead to a reduction of approximately 50% of ePLND cases. In addition, only ≤3% of patients were misdiagnosed with a cutoff value ranging from 5% to 20%. This promising study warrants further validation by using a larger prospective dataset.

Clinicopathological Analysis of the ISUP Grade Group And Other Parameters in Prostate Cancer: Elucidation of Mutual Impact of the Various Parameters

Background

Prostate cancer has become increasingly common worldwide. Although Grade group (GG) is widely accepted as an indicator of prostate cancer grade, there are malignancies that cannot be defined by GG alone. Moreover, the relationship between GG and other parameters remains unclear. Herein, we aimed to explore the biological characteristics of prostate cancer.

Methods

This study included 299 radical prostatectomy cases. The Chi-square test and analysis of variance were used to analyze the association of GG with binary and continuous variables. We then conducted morphological analyses. Multivariate analyses were performed to extract the data on risk factors for biochemical recurrence (BCR) and lymph node metastasis.

Results

The lymphatic, venous, perineural, and seminal vesicle invasion rates were 37/299 (12.4%), 25/299 (8.4%), 280/299 (93.6%), and 23/299 (7.7%), respectively. The extraprostatic extension (EPE), positive surgical margin, tertiary Gleason pattern 5, intraductal carcinoma of the prostate gland, and lymph node metastasis rates were 89/299 (29.8%), 106/299 (35.5%), 33/260 (12.7%), 56/299 (18.7%), and 23/299 (7.7%), respectively. As GG increased, various parameters became easier to visualize; however, there were differences between the parameters. Postoperative BCR was observed in 31/242 (12.8%) cases without preoperative hormone therapy; GG2, GG3, GG4, and GG5 accounted for 4, 7, 7, and 13 cases, respectively. Multivariate analyses revealed that GG and tumor diameter were significant risk factors for early BCR, whereas lymphatic invasion, EPE, and seminal vesicle invasion were significant risk factors for lymph node metastasis. For BCR, the odds ratios (ORs) for GG and tumor diameter were 2.253 (95% confidence interval (CI]): 1.297–3.912; P=0.004) and 1.074 (95% CI: 1.011–1.142; P=0.022), respectively. For lymph node metastasis, ORs for the presence of lymphatic invasion, EPE, and seminal vesicle invasion were 7.425 (95% CI: 1.688–22.583; P=0.004), 4.391 (95% CI: 1.037–18.589; P=0.044), and 5.755 (95% CI: 1.308–25.316; P=0.021), respectively.

Conclusions

We summarized various parameters correlating with each GG. Through multivariate analyses, we established the independent risk factors for early BCR and lymph node metastasis. In addition to GG, other important indices of malignancy were determined and weighted to provide a basis for future investigations.

Impact of positive surgical margin status in predicting early biochemical recurrence after robot-assisted radical prostatectomy

BACKGROUND

We investigated the association between positive surgical margin (PSM) status and biochemical recurrence (BCR) after robot-assisted radical prostatectomy (RARP) to develop a prognostic factor-based risk stratification model for BCR.

METHODS

We analyzed the data of 483 patients who underwent RARP at our hospital between October 2010 and April 2019; 435 patients without neoadjuvant therapy were finally included. The BCR-free survival rate was determined using Kaplan-Meier analysis. Effects of the PSM status, including the number of PSMs, Gleason score (GS) at a PSM, and the maximum PSM length for BCR, were investigated using Cox regression analysis.

RESULTS

BCR was confirmed after RARP in 61 patients (14.0%), and PSM was confirmed in 74 patients (17.0%); PSM was a significant predictor of BCR (p < 0.001). The median number of PSMs was 2 (1-6), and the median maximum length of PSM was 6.0 (2.0-17.0) mm. Multivariable analysis showed lymph node invasion (p < 0.001), GS of ≥ 7 at a PSM (p = 0.022) and a maximum PSM length of > 6.0 mm (p = 0.003) were significant predictors of BCR. We classified the patients without lymph node invasion into good-, intermediate-, and poor-risk groups according to the other two risk factors (presence of 0, 1, and 2 factors, respectively) and rates of 1-year BCR-free survival (100.0, 72.7, and 48.1%, respectively).

CONCLUSION

Higher GS at PSM and greater length of PSM were significant predictors of BCR after RARP, and console surgeons should be careful to prevent PSM during RARP.

Significant reduction of lymphoceles after radical prostatectomy and pelvic lymph node dissection

OBJECTIVES

To reduce the risk of symptomatic lymphocele (SLC), we present a technique using peritoneal fenestration that allows lymphatic fluid to drain into the abdomen, as SLC formation after open retropubic radical prostatectomy (ORP) with pelvic lymph node dissection (PLND) is a common adverse event.

PATIENTS AND METHODS

We identified 1513 patients who underwent ORP with PLND between July 2018 and November 2019. Of those, 307 patients (20.3%) received peritoneal fenestration and 1206 (79.7%) no fenestration. The rate of LCs and the necessity for intervention were analysed by uni- and multivariable logistic regression (MLR) models. A propensity score matching was performed, as well.

RESULTS

The median (interquartile range [IQR]) age was 65 (60-70) years. A median (IQR) of 16 (10-22) lymph nodes were dissected, 22 vs 14 lymph nodes in the fenestration vs non-fenestration group (P < 0.001). Overall, 189 patients (12.5%) were diagnosed with a LC after ORP, while 21 patients (6.8%) in the fenestration and 168 (13.9%) in the non-fenestration group had LCs (P = 0.001). In 70 patients (4.7%), LCs required further intervention, categorised as Clavien-Dindo Grade IIIa/b, with a smaller proportion in the fenestration group (2.9% vs 5.0% in the non-fenestration group, P < 0.001). There were no Clavien-Dindo Grade IV or V complications, in particular no abdominal complications in association with peritoneal fenestration observed. In MLR, peritoneal fenestration was associated with a reduced risk of LCs (odds ratio [OR] 0.33, 95% confidence interval [CI] 0.2-0.5; P < 0.001). The risk reduction was also shown after propensity score matching (OR 0.38, 95% CI 0.21-0.68; P = 0.001). The number needed to treat was 14.

CONCLUSIONS

Peritoneal fenestration may decrease the rate of SLC after ORP with (extended) PLND. Therefore, it should be part of the operative strategy.

Integration of clinicopathologic identification and deep transferrable image feature representation improves predictions of lymph node metastasis in prostate cancer

Background

Accurate identification of pelvic lymph node metastasis (PLNM) in patients with prostate cancer (PCa) is crucial for determining appropriate treatment options. Here, we built a PLNM-Risk calculator to obtain a precisely informed decision about whether to perform extended pelvic lymph node dissection (ePLND).

Methods

The PLNM-Risk calculator was developed in 280 patients and verified internally in 71 patients and externally in 50 patients by integrating a set of radiologists’ interpretations, clinicopathological factors and newly refined imaging indicators from MR images with radiomics machine learning and deep transfer learning algorithms. Its clinical applicability was compared with Briganti and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms.

Findings

The PLNM-Risk achieved good diagnostic discrimination with areas under the receiver operating characteristic curve (AUCs) of 0.93 (95% CI, 0.90-0.96), 0.92 (95% CI, 0.84-0.97) and 0.76 (95% CI, 0.62-0.87) in the training/validation, internal test and external test cohorts, respectively. If the number of ePLNDs missed was controlled at < 2%, PLNM-Risk provided both a higher number of ePLNDs spared (PLNM-Risk 59.6% vs MSKCC 44.9% vs Briganti 38.9%) and a lower number of false positives (PLNM-Risk 59.3% vs MSKCC 70.1% and Briganti 72.7%). In follow-up, patients stratified by the PLNM-Risk calculator showed significantly different biochemical recurrence rates after surgery.

Interpretation

The PLNM-Risk calculator offers a noninvasive clinical biomarker to predict PLNM for patients with PCa. It shows improved accuracy of diagnosis support and reduced overtreatment burdens for patients with findings suggestive of PCa.

Funding

This work was supported by the Key Research and Development Program of Jiangsu Province (BE2017756) and the Suzhou Science and Technology Bureau-Science and Technology Demonstration Project (SS201808).

External validation of the Memorial Sloan Kettering Cancer Centre and Briganti nomograms for the prediction of lymph node involvement of prostate cancer using clinical stage assessed by magnetic resonance imaging

OBJECTIVES

To evaluate the impact of using clinical stage assessed by multiparametric magnetic resonance imaging (mpMRI) on the performance of two established nomograms for the prediction of pelvic lymph node involvement (LNI) in patients with prostate cancer.

PATIENTS AND METHODS

Patients undergoing robot-assisted extended pelvic lymph node dissection (ePLND) from 2015 to 2019 at three teaching hospitals were retrospectively evaluated. Risk of LNI was calculated four times for each patient, using clinical tumour stage (T-stage) assessed by digital rectal examination (DRE) and by mpMRI, in the Memorial Sloan Kettering Cancer Centre (MSKCC; 2018) and Briganti (2012) nomograms. Discrimination (area under the curve [AUC]), calibration, and the net benefit of these four strategies were assessed and compared.

RESULTS

A total of 1062 patients were included, of whom 301 (28%) had histologically proven LNI. Using DRE T-stage resulted in AUCs of 0.71 (95% confidence interval [CI] 0.70-0.72) for the MSKCC and 0.73 (95% CI 0.72-0.74) for the Briganti nomogram. Using mpMRI T-stage, the AUCs were 0.72 (95% CI 0.71-0.73) for the MSKCC and 0.75 (95% CI 0.74-0.76) for the Briganti nomogram. mpMRI T-stage resulted in equivalent calibration compared with DRE T-stage. Combined use of mpMRI T-stage and the Briganti 2012 nomogram was shown to be superior in terms of AUC, calibration, and net benefit. Use of mpMRI T-stage led to increased sensitivity for the detection of LNI for all risk thresholds in both models, countered by a decreased specificity, compared with DRE T-stage.

CONCLUSION

T-stage as assessed by mpMRI is an appropriate alternative for T-stage assessed by DRE to determine nomogram-based risk of LNI in patients with prostate cancer, and was associated with improved model performance of both the MSKCC 2018 and Briganti 2012 nomograms.

Impact of Lymphovascular Invasion on Overall Survival in Patients With Prostate Cancer Following Radical Prostatectomy: Stage-per-Stage Analysis

BACKGROUND

The detrimental impact of lymphovascular invasion (LVI) in prostate cancer (PCa) on biochemical recurrence has been described; the impact of LVI on overall survival (OS) remains unclear. This investigation sought to evaluate the impact of LVI on OS in patients with PCa.

METHODS

We examined men with nonmetastatic PCa treated with radical prostatectomy between 2010 and 2015. Only men with documented LVI status were included (n = 232,704). Patients were stratified according to final pathologic T stage (pT2, pT3a, and pT3b).

RESULTS

Of the 232,704 patients who met inclusion criteria, 17,758 (8%) were found to have LVI on final pathology. Overall, 174,838 (75%), 40,281 (17%), and 17,585 (8%) patients had pT2, pT3a, and pT3b disease, respectively. Median follow-up was 42.7 months (27.1-58.7). At 5 years, the OS in LVI versus non-LVI patients was 94% versus 95% in pT2 (P = .0004), 92% versus 95% in pT3a (P < .0001), and 86% versus 92% in pT3b (P < .0001). On multivariable analysis, LVI status was not an independent predictor of OS in pT2 disease (hazard ratio, 1.12; 95% confidence interval [CI], 0.93-1.36; P = .2). In pT3a and pT3b disease, presence of LVI had 1.2-fold (95% CI, 1.03-1.44; P = .02) and 1.4-fold (95% CI, 1.20-1.59; P < .001) higher overall mortality than their counterparts without LVI.

CONCLUSIONS

Our report demonstrates the detrimental impact of LVI on OS in locally advanced PCa (pT3a and higher). This information may prove valuable when risk stratifying based on final pathology.

Effect of the Number of Removed Lymph Nodes on Survival in Patients with FIGO Stage IB-IIA Cervical Squamous Cell Carcinoma following Open Radical Hysterectomy with Pelvic Lymphadenectomy: A Retrospective Cohort Study

Objective

To determine whether the number of removed lymph nodes (RLN) is associated with survival in patients with International Federation of Gynecology and Obstetrics (FIGO) stage IB-IIA cervical squamous cell carcinoma (CSCC).

Methods

We reviewed the medical records of FIGO stage IB-IIA CSCC patients who underwent standardized radical hysterectomy with pelvic lymphadenectomy (RHPL) in our center between 2006 and 2014. The X-tile software was performed to calculate the optimal grouping of cutoff points for RLN. The impact of RLN on progression-free survival (PFS) and overall survival (OS) was analyzed using Cox regression analysis.

Results

Among 3,127 patients, the mean number of RLN was 22, and positive lymph node (LN) was found in 668 (21.4%) patients. X-tile plots identified “21” and “16” as the optimal cutoff value of RLN to divide the patients into two groups in terms of PFS and OS separately. In all patients, the number of RLN was not associated with PFS (P=0.182) or OS (P=0.193). Moreover, in both LN positive and negative patients, the number of RLN was not associated with either PFS (P=0.212 and P=0.540, respectively) or OS (P=0.173 and P=0.497, respectively). Cox regression analysis showed that the number of RLN was not an independent prognostic factor for PFS or OS.

Conclusion

If standardized RHPL was performed, the number of RLN was not an independent prognostic factor for survival of patients with FIGO stage IB-IIA CSCC.

Evaluation of lymphovascular invasion as a prognostic predictor of overall survival after radical prostatectomy

OBJECTIVE

To assess the prognostic ability of lymphovascular invasion (LVI) as a predictor of overall survival (OS).

MATERIALS AND METHODS

We included 126,682 prostate cancer (CaP) cM0 patients who underwent radical prostatectomy with lymph node dissection between 2010 and 2015, within the National Cancer Database. Patients who received androgen deprivation therapy were included. Patients were divided into four sub-cohorts based on LVI and lymph node invasion (LNI) status: pL₀N₀, pL₁N₀, pL₀N₁, and pL₁N₁. Kaplan-Meier curves estimated OS and Cox-regression analysis tested the relationship between LVI and OS.

RESULTS

Median (IQR) age and PSA at diagnosis were 62 (57-66) years and 5.7 (4.5-8.9) ng/ml, respectively. Most patients had pT2 stage (68.5%), and pathological Gleason 3+4 (46.7%). 10.0% and 4.0% patients had LVI and LNI, respectively. Median follow-up was 42 months (27-58). At 5-years, OS was 96.5% in pL₀N₀ patients vs 93.1% pL₁N₀ patients vs 93.3% in pL₀N₁ patients vs 86.6% pL₁N₁ patients. LVI was an independent predictor of OS (hazard ratio [HR]:1.28). LVI showed interaction with LNI, as LVI was associated with a higher overall-mortality in patients with LNI (HR:1.66), than in patients without LNI (HR:1.22). (all P<0.0001) CONCLUSIONS: Our report highlights the detrimental impact of LVI on OS. Patients with LVI alone fared similarly to patients with LNI alone. Patients with both LVI and LNI had worse OS than those with only LVI or LNI, implying a synergetic detrimental interaction. Our findings demonstrate an important utility that LVI can provide in deciding patients' prognoses.

Establishment and validation of a novel predictive model to quantify the risk of bone metastasis in patients with prostate cancer

Background

Patients with prostate cancer (PCa) commonly suffer from bone metastasis during disease progression. This study aims to construct and validate a nomogram to quantify bone metastasis risk in patients with PCa.

Methods

Clinicopathological data of patients diagnosed with PCa between 2010 and 2015 were retrospectively retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Predictors for bone metastasis were identified by logistic regression analyses to establish a nomogram. The concordance index (c-index) and calibration plots were generated to assess the nomogram’s discrimination, and the area under the receiver operating characteristic curve (AUC) was used to compare the precision of the nomogram with routine staging systems. The nomogram’s clinical performance was evaluated by decision curve analysis (DCA) and clinical impact curves (CIC). Independent prognostic factors were identified by Cox regression analysis.

Results

A total of 168,414 eligible cases were randomly assigned to the training cohort or validation cohort at a ratio of 1:1. The nomogram, which was established based on independent factors, showed good accuracy, with c-indexes of 0.911 in the training set and 0.910 in the validation set. Calibration plots also approached 45 degrees. After other distant metastatic sites were included in the predictive model, the new nomogram displayed superior prediction performance. The AUCs and net benefit of the nomograms were both higher than those of other routine staging systems. Furthermore, bone metastasis prediction points were shown to be a new risk factor for overall survival.

Conclusions

Novel validated nomograms can effectively predict the risk of bone metastasis in patients with PCa and help clinicians improve cancer management.

A novel robust nomogram based on peripheral monocyte counts for predicting lymph node metastasis of prostate cancer

Accurate methods for identifying pelvic lymph node metastasis (LNM) of prostate cancer (PCa) prior to surgery are still lacking. We aimed to investigate the predictive value of peripheral monocyte count (PMC) for LNM of PCa in this study. Two hundred and ninety-eight patients from three centers were divided into a training set (n = 125) and a validation set (n = 173). In the training set, the independent predictors of LNM were analyzed using univariate and multivariate logistic regression analyses, and the optimal cutoff value was calculated by the receiver operating characteristic (ROC) curve. The sensitivity and specificity of the optimal cutoff were authenticated in the validation cohort. Finally, a nomogram based on the PMC was constructed for predicting LNM. Multivariate analyses of the training cohort demonstrated that clinical T stage, preoperative Gleason score, and PMC were independent risk factors for LNM. The subsequent ROC analysis showed that the optimal cutoff value of PMC for diagnosing LNM was 0.405 × 109 l^-1 with a sensitivity of 60.0% and a specificity of 67.8%. In the validation set, the optimal cutoff value showed significantly higher sensitivity than that of conventional magnetic resonance imaging (MRI) (0.619 vs 0.238, P < 0.001). The nomogram involving PMC, free prostate-specific antigen (fPSA), clinical T stage, preoperative Gleason score, and monocyte-to-lymphocyte ratio (MLR) was generated, which showed a robust predictive capacity for predicting LNM before the operation. Our results indicated that PMC as a single agent, or combined with other clinical parameters, showed a robust predictive capacity for LNM in PCa. It can be employed as a complementary factor for the decision of whether to conduct pelvic lymph node dissection.

Oncological outcomes of pathologically organ-confined, lymph node-positive prostate cancer after radical prostatectomy

BACKGROUND

The aim of this study was to investigate the impact of lymph-node involvement on oncological outcomes in patients with pathologically organ-confined prostate cancer (pT2 CaP) after radical prostatectomy (RP).

METHODS

We retrospectively analyzed 9,631 pT2 CaP patients who underwent RP at a single institution between 1998 and 2018. Kaplan-Meier plots and Cox regression models (CRMs) assessed biochemical recurrence (BCR)-free survival and metastasis-free survival (MFS) according to N-stage. In subgroup analyses of N1 patients, Kaplan-Meier plots and CRMs were stratified according to adjuvant treatment.

RESULTS

Of 9,631 pT2 staged patients, 241 (2.5%) harbored lymph-node metastases after RP (pN1). The median follow-up was 60.8 months. No pT2 N1-staged patient died due to CaP. The 5-year BCR-free survival rates were 54.7 vs. 88.4% in pT2 N1 vs. pT2 N0 patients, respectively (P < 0.001). The 5-year MFS rates were 92.5 vs. 98.9% in pT2 N1 vs. pT2 N0 patients, respectively (P < 0.001). Within pT2 N1 patients, presence of ≥3 positive lymph nodes was an independent risk factor for BCR (hazard ratio [HR] 3.4, P < 0.001) and for metastatic progression (HR 1.7, P = 0.04). Finally, 3-year BCR-free survival was improved in pT2 N1 patients treated with adjuvant radiation therapy (87.1% vs. 63.7% for patients who received other treatment options [P < 0.001]).

CONCLUSION

Patients with pathologically organ-confined but lymph node-positive CaP exhibited favorable oncological outcomes after RP. Presence of ≥3 positive LNs predicted higher rates of BCR and metastatic progression. In consequence, in pT2 N1 patients treated with RP with ≥3 positive LNs, adjuvant treatment may be considered.9.

Cellular Origins of the Lymphatic Endothelium: Implications for Cancer Lymphangiogenesis

The lymphatic system plays important roles in physiological and pathological conditions. During cancer progression in particular, lymphangiogenesis can exert both positive and negative effects. While the formation of tumor associated lymphatic vessels correlates with metastatic dissemination, increased severity and poor patient prognosis, the presence of functional lymphatics is regarded as beneficial for anti-tumor immunity and cancer immunotherapy delivery. Therefore, a profound understanding of the cellular origins of tumor lymphatics and the molecular mechanisms controlling their formation is required in order to improve current strategies to control malignant spread. Data accumulated over the last decades have led to a controversy regarding the cellular sources of tumor-associated lymphatic vessels and the putative contribution of non-endothelial cells to this process. Although it is widely accepted that lymphatic endothelial cells (LECs) arise mainly from pre-existing lymphatic vessels, additional contribution from bone marrow-derived cells, myeloid precursors and terminally differentiated macrophages, has also been claimed. Here, we review recent findings describing new origins of LECs during embryonic development and discuss their relevance to cancer lymphangiogenesis.

High B7-H3 expression is linked to increased risk of prostate cancer progression

B7-H3 is a member of the B7 superfamily of immune checkpoint molecules. B7-H3 up regulation has been linked to cancer development and progression in many tumors including prostate cancer. To clarify the potential utility of B7-H3 as a prognostic biomarker, B7-H3 expression was analyzed by immunohistochemistry in more than 17 000 prostate cancers. Normal prostatic glands were largely B7-H3 negative, while membranous B7-H3 immunostaining was seen in 47.0% of analyzed cancers. B7-H3 immunostaining was weak in 12.3%, moderate in 21.1% and strong in 13.5% of cases. High B7-H3 expression was associated with pT, Gleason score, lymph node metastasis, high Ki67 labeling index and early prostate-specific antigen recurrence (P < 0.0001 each). High B7-H3 expression was also linked to high androgen receptor expression and TMPRSS2:V-ets avian erythroblastosis virus E26 oncogene homolog (ERG) fusions (P < 0.0001 each). Multivariate analyses showed a strong independent prognostic impact of high B7-H3 expression in all cancers and in the ERG negative subgroup. Comparison with previously analyzed frequent chromosomal deletions revealed a close association with Phosphatase and Tensin Homolog deletions. Analysis of B7-H3, alone or in combination with other markers, might be of clinical utility, especially in the subgroup of ERG negative prostate cancers.

Biological functions of lymphatic vessels

The general functions of lymphatic vessels in fluid transport and immunosurveillance are well recognized. However, accumulating evidence indicates that lymphatic vessels play active and versatile roles in a tissue- and organ-specific manner during homeostasis and in multiple disease processes. This Review discusses recent advances to understand previously unidentified functions of adult mammalian lymphatic vessels, including immunosurveillance and immunomodulation upon pathogen invasion, transport of dietary fat, drainage of cerebrospinal fluid and aqueous humor, possible contributions toward neurodegenerative and neuroinflammatory diseases, and response to anticancer therapies.

Up regulation of the Hippo signalling effector YAP1 is linked to early biochemical recurrence in prostate cancers

The transcriptional coactivator YAP1 controls the balance between cell proliferation and apoptosis. YAP1 overexpression is linked to poor prognosis in many cancer types, yet its role in prostate cancer is unknown. Here, we applied YAP1 immunohistochemistry to a tissue microarray containing 17,747 clinical prostate cancer specimens. Cytoplasmic and nuclear YAP1 staining was seen in 81% and 63% of tumours. For both cytoplasmic and nuclear YAP1 staining, high levels were associated with advanced tumour stage, classical and quantitative Gleason grade, positive nodal stage, positive surgical margin, high KI67 labelling index, and early biochemical recurrence (p < 0.0001 each). The prognostic role of YAP1 staining was independent of established prognostic features in multivariate models (p < 0.001). Comparison with previously studied molecular markers identified associations between high YAP1 staining, TMPRSS2:ERG fusion (p < 0.0001), high androgen receptor (AR) expression (p < 0.0001), high Ki67 labelling index (p < 0.0001), and PTEN and 8p deletions (p < 0.0001 each). In conclusion, high YAP1 protein expression is an independent predictor of unfavourable disease course in prostate cancer. That cytoplasmic and nuclear YAP1 staining is equally linked to phenotype and prognosis fits well to a model where YAP1 activation during tumour progression includes up regulation, cytoplasmic accumulation and subsequent translocation to the nucleus.

Small-volume lymph node involvement and biochemical recurrence after robot-assisted radical prostatectomy with extended lymph node dissection in prostate cancer

BACKGROUND

We investigated prognostic factors for biochemical recurrence (BCR) after robot-assisted radical prostatectomy (RARP) with extended pelvic lymph node (LN) dissection.

METHODS

We included 173 patients who underwent RARP with extended pelvic LN dissection without neoadjuvant therapy at our hospital between October 2010 and April 2018. BCR was defined as prostate serum antigen (PSA) levels ≥ 0.2 ng/mL; BCR-free survival rates were determined using Kaplan-Meier analysis. We used Cox regression analysis to evaluate effects of PSA and pathologic variables on BCR.

RESULTS

Median follow-up was 27.9 (range 6.1-86.9) months. Five-year BCR-free survival was 89.5%. In multivariate analysis, positive LNs (HR 7.117; 95% CI 2.826-17.925; P < 0.001) and Gleason score (GS) ≥ 8 (HR 2.612; 95% CI 1.051-6.489; P = 0.039) were significant predictors of BCR. Patients with 1 or 2 positive LNs (n = 10) had significantly higher BCR-free survival rates than patients with ≥ 3 positive LNs (n = 5). We, therefore, stratified the patients as low-risk (GS < 8 and no positive LNs), intermediate-risk: (either GS ≥ 8 or positive LNs) and high-risk (both GS ≥ 8 and positive LNs). Their 1-year BCR-free survival rates were low-risk: 94.6%, intermediate-risk: 88.5%, and high-risk: 33.3% (P < 0.05).

CONCLUSIONS

Patients with 1-2 positive LNs and GS < 8 have low risk for BCR; close observation without immediate adjuvant hormonal therapy can be considered for these patients.

Upregulation of PTTG1 is associated with poor prognosis in prostate cancer

Pituitary tumor-transforming gene 1 (PTTG1) is a regulator of chromosome stability. PTTG1 overexpression had been associated with tumor aggressiveness in several cancer types. To examine its prognostic utility in prostate cancer, a tissue microarray including 12 427 tumors with clinical and molecular data was analyzed by immunohistochemistry. PTTG1 immunostaining was largely absent in normal prostate epithelial cells. In cancers, staining was considered weak in 5.4%, moderate in 5.6% and strong in 0.8%. Strong staining was linked to advanced pT stage, high classical and quantitative Gleason grade, high Ki67-labeling index (all P < 0.0001) and lymph node metastasis (P = 0.0083). The prognostic impact of PTTG1 expression was independent of established preoperative and postoperative prognostic features. Comparison with molecular features revealed that PTTG1 upregulation was associated with nine of 12 common genomic deletions (P < 0.05), p53 alterations and high androgen receptor levels (P < 0.001 each), but was unrelated to the TMPRSS2:ERG fusion status. In conclusion, these data identify PTTG1 as a strong and independent prognostic feature in prostate cancer. PTTG1 measurement, either alone or in combination with other biomarkers might be instrumental for determining prostate cancer aggressiveness.

Loss of the adhesion molecule CEACAM1 is associated with early biochemical recurrence in TMPRSS2:ERG fusion-positive prostate cancers

Altered expression of the carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) has been linked to adverse tumor features in various cancer types. To better understand the role of CEACAM1 in prostate cancer, we analyzed a tissue microarray containing tumor spots from 17,747 prostate cancer patients by means of immunohistochemistry. Normal prostate glands showed intense membranous CEACAM1 positivity. Immunostaining was interpretable in 13,625 cancers and was considered high in 28%, low in 43% and absent in 29% of tumors. Low and lost CEACAM1 expression was strongly linked to adverse tumor features including high classical and quantitative Gleason grade, lymph node metastasis, advanced tumor stage, positive surgical margin, a high number of genomic deletions and early biochemical recurrence (p < 0.0001 each). Subset analysis of molecularly defined cancer subsets revealed that these associations were strongest in V-ets avian erythroblastosis virus E26 oncogene homolog (ERG) fusion-positive cancers and that CEACAM1 loss was prognostic even in tumors harboring genomic deletions of the phosphatase and tensin homolog tumor suppressor (p < 0.0001). Multivariate analysis suggested that CEACAM1 analysis can provide independent prognostic information beyond established prognosis parameters at the stage of the initial biopsy when therapy decisions must be taken. In conclusion, loss of CEACAM1 expression predicts poor prognosis in prostate cancer and might provide clinically useful prognostic information particularly in cancers harboring the TMPRSS2:ERG fusion.

High RSF1 protein expression is an independent prognostic feature in prostate cancer

Background: Remodelling and spacing factor 1 (RSF1) is involved in the regulation of chromatin remodelling and represents a potential therapeutic target. High RSF1 expression has been linked to adverse tumour features in many cancer types, but its role in prostate cancer is uncertain.Methods: In this study, RSF1 expression was analysed by immunohistochemistry on a tissue microarray with 17,747 prostate cancers.Results: Nuclear RSF1 staining of 16,456 interpetable cancers was considered strong, moderate, weak and negative in 25.2%, 48.7%, 5.3% and 20.8% of cancers respectively. Positive RSF1 expression was associated with advanced tumour stage, high Gleason grade, lymph node metastasis (p < .0001 each), early biochemical recurrence (p < .0003) and more frequent in the ERG positive than in the ERG negative subset (88% versus 71%; p < .0001). Subset analysis revealed, that associations between RSF1 expression and unfavourable tumour phenotype and PSA recurrence were present in both subgroups but stronger in the ERG negative than in the ERG positive subset. The univariate Cox proportional hazard ratio for PSA recurrence-free survival for strong versus negative RSF1 expression was a weak 1.60 compared with 5.91 for the biopsy Gleason grade ≥4 + 4 versus ≤3 + 3. The positive association of RSF1 protein detection with deletion of 3p13, 10q23 (PTEN), 12p13, 16q23, and 17p13 (p < .0001 each) suggest a role of high RSF1 expression in the development of genomic instability.Conclusion: In summary, the results of our study identify RSF1 as an independent prognostic marker in prostate cancer with a particularly strong role in ERG negative cases.

Claudin-1 upregulation is associated with favorable tumor features and a reduced risk for biochemical recurrence in ERG-positive prostate cancer

BACKGROUND

Claudin-1 is a membrane-tight junction protein and important for the sealing of the paracellular cleft in epithelial and endothelial cells. Differential expression of Claudin-1 is linked to disease outcome in various cancers.

MATERIAL AND METHODS

To evaluate the potential relevance of Claudin-1 expression in prostate cancer, a tissue microarray containing samples of 17,747 tumors with annotated clinico-pathological and molecular data was immunohistochemically analyzed for Claudin-1 expression.

RESULTS

In normal prostate, glandular cells were always Claudin-1-negative while there was a strong staining of gland-surrounding basal cells. In contrast to normal prostatic glands, a positive Claudin-1 immunostaining, was found, however, in 38.7% of 12,441 interpretable cancers and was considered weak in 12.7%, moderate in 13.2%, and strong in 12.8% of cases. Positive Claudin-1 immunostaining was associated with favorable tumor features like low pT (p = 0.0032), low Gleason grade (p< 0.0001), and a reduced risk of PSA recurrence (p = 0.0005). A positive Claudin-1 staining was markedly more frequent in ERG-positive (63%) than in ERG-negative cancers (23%; p < 0.0001). Subset analyses revealed that all associations of Claudin-1 expression and favorable phenotype and prognosis were driven by ERG-positive cancers. Multivariate analyses revealed, however, that even in ERG-positive cancers, the prognostic impact of high Claudin-1 expression was not independent of established clinico-pathological parameters. Comparison with 12 previously analyzed chromosomal deletions identified conspicuous associations with PTEN and 12p13 deletions potentially indicating functional interactions.

CONCLUSION

These data identify a peculiar role for Claudin-1 in prostate cancer. The protein is overexpressed in a fraction of prostate cancers and increased Claudin-1 expression levels predict a favorable prognosis in ERG-positive cancer.

The significance of micro-lymphatic invasion and pathological Gleason score in prostate cancer patients with pathologically organ-confined disease and negative surgical margins after robot-assisted radical prostatectomy

BACKGROUND

The development process of recurrence in prostate cancer patients with pathologically organ-confined (pT2) disease and negative surgical margins is unclear. The aim of the present study was to determine factors associated with the development of biochemical recurrence following robot-assisted radical prostatectomy among those prostate cancer patients.

METHODS

We retrospectively reviewed the data of patients who underwent robot-assisted radical prostatectomy without neoadjuvant endocrine therapy. We evaluated prognostic factors in 1096 prostate cancer patients with pT2 disease and negative surgical margins. Univariate and multivariate Cox proportional hazards regression analyses were used to identify independent predictors for biochemical recurrence.

RESULTS

Of the 1096 patients, 55 experienced biochemical recurrence during the follow-up period. The 5-year biochemical recurrence-free survival rate for patients with pT2 and negative surgical margins was 91.8%. On univariate analysis, clinical stage, biopsy Gleason score, percent of positive core, pathological Gleason score, and the presence of micro-lymphatic invasion were significantly associated with biochemical recurrence. On a multivariate analysis, the presence of micro-lymphatic invasion and a pathological Gleason score ≥ 4 + 3 were significant prognostic factors for biochemical recurrence. Based on these factors, we developed a risk stratification model. The biochemical recurrence-free survival rate differed significantly among the risk groups.

CONCLUSIONS

The prognosis of prostate cancer patients with pT2 disease and negative surgical margins is favorable. However, patients with the presence of micro-lymphatic invasion and a pathological Gleason score ≥ 4 + 3 tend to experience biochemical recurrence more often after surgery. Therefore, careful follow-up might be necessary for those patients.

Impact of Adherence to Multidisciplinary Recommendations for Adjuvant Treatment in Radical Prostatectomy Patients With High Risk of Recurrence

INTRODUCTION

The purpose of this study was to investigate adherence to recommended adjuvant radiotherapy (aRT) in radical prostatectomy (RP) patients with adverse pathologic features and to analyse the outcome of patients who followed or denied this recommendation.

PATIENTS AND METHODS

We included 1140 consecutive RP patients (2006-2015) with non-organ confined (pT3) prostate cancer and either positive surgical margins (R1) and/or lymph node involvement (pN1) and non-detectable postoperative prostate-specific antigen who received multidisciplinary aRT recommendations. Patients were stratified into adherence versus non-adherence to recommendations. Additionally, subgroups within pathologic criteria (pT3R1N0, pT3R0N1, pT3R1N1) were analyzed. Kaplan-Meier, as well as multivariable Cox regression analyses were used to assess biochemical recurrence (BCR)-free survival, metastasis-free survival, cancer-specific survival, and overall survival.

RESULTS

Overall, 508 (44.6%) patients were non-adherent. Of those, 273 (53.6%) did not receive any RT, and 235 (46.4%) received salvage RT. At 8 years, BCR-free survival was 57.7 versus 20.1%, metastasis-free survival was 76.5 versus 75.4%, cancer-specific survival was 91.7 versus 87.4%, and overall survival was 80.4 versus 75.8% in adherent versus non-adherent patients, respectively (P < .001). In multivariable Cox regression predicting BCR, metastatic progression, cancer-specific mortality, and overall mortality, non-adherence to aRT recommendation represented an independent predictor (hazard ratio [HR], 3.8; 95% confidence interval [CI], 3.1-4.5; HR, 1.6; 95% CI, 1.2-2.2; HR, 2.8; 95% CI, 1.5-5.3; and HR, 1.8; 95% CI, 1.2-2.8, respectively).

CONCLUSIONS

Only about 55% of patients followed our multidisciplinary recommendations. Adherent patients were significantly less likely to experience BCR, metastatic progression, cancer-specific mortality, and overall mortality. Thus, patients with high risk of recurrence may be advised about the possibility of improved oncologic outcomes in case of adherence to aRT recommendations.

Development and internal validation of a novel model and markers to identify the candidates for lymph node metastasis in patients with prostate cancer

BACKGROUND

High-grade prostate cancer (PCa) has a poor prognosis, and up to 15% of patients worldwide experience lymph node invasion (LNI). To further improve the prediction lymph node invasion in prostate cancer, we adopted risk scores of the genes expression based on the nomogram in guidelines.

METHODS

We analyzed clinical data from 320 PCa patients from the Cancer Genome Atlas database. Weighted gene coexpression network analysis was used to identify the genes that were significantly associated with LNI in PCa (n = 390). Analyses using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases were performed to identify the activated signaling pathways. Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors for the presence of LNI.

RESULTS

We found that patients with actual LNI and predicted LNI had the worst survival outcomes. The 7 most significant genes (CTNNAL1, ENSA, MAP6D1, MBD4, PRCC, SF3B2, TREML1) were selected for further analysis. Pathways in the cell cycle, DNA replication, oocyte meiosis, and 9 other pathways were dramatically activated during LNI in PCa. Multivariate analyses identified that the risk score (odds ratio [OR] = 1.05 for 1% increase, 95% confidence interval [CI]: 1.04-1.07, P < .001), serum PSA level, clinical stage, primary biopsy Gleason grade (OR = 2.52 for a grade increase, 95% CI: 1.27-5.22, P = .096), and secondary biopsy Gleason grade were independent predictors of LNI. A nomogram built using these predictive variables showed good calibration and a net clinical benefit, with an area under the curve (AUC) value of 90.2%.

CONCLUSIONS

In clinical practice, the application of our nomogram might contribute significantly to the selection of patients who are good candidates for surgery with extended pelvic lymph node dissection.