The Role of Perineural Invasion in Prostate Cancer and Its Prognostic Significance

Immunostaining for Mismatch Repair Complex Proteins Impacts on Clinical-Pathological Characteristics and Prognosis of Adenoid Cystic Carcinoma of Salivary Glands

OBJECTIVE

To evaluate the influence of MMR proteins on clinicopathological characteristics and prognosis of salivary gland adenoid cystic carcinoma (ACC).

METHOD

The solid pattern of ACC showed lower expression for MSH2 (p = 0.039). Significant imbalance in MSH2/MSH6 immunostaining was observed in all histological patterns (p < 0.001), and imbalance in PMS2/MLH1 immunostaining was observed in the cribriform pattern (p = 0.011). The presence of capsule was associated with high expression of MSH6 (p = 0.019), MLH1 (p = 0.045) and PMS2 (p = 0.009). The absence of cribriform pattern (p = 0.002) and capsule pattern (p = 0.025), as well as low expression for MSH6 (p = 0.006) and PMS2 (p = 0.037) were associated with lower overall survival. In multivariate analysis, loss of MSH2 (p = 0.039) and MLH1 (p = 0.017) were significantly associated with worse overall survival.

RESULTS

Twenty-four ACC were clinical-pathologically evaluated and we perform immunohistochemistry for MSH2, MSH6, PMS2 and MLH1. Percentage counting of positive cells was performed in 10 fields of each histological pattern (cribriform, tubular and solid) and the averages of the 30 fields were considered for evaluation with other clinical-pathological variables (Kruskal-Wallis/Dunn, Friedman/Dunn, chi-square, Log-Rank Mantel-Cox tests and Cox regression; SPSS v20.0, p < 0.05).

DISCUSSION

Salivary glands' ACC shows imbalance of the MMR complex and loss of expression of its components is associated with the overall survival of these patients.

Nomogram-based prognostic model construction for progression to castration-resistant prostate cancer in patients with high tumor burden and osseous metastatic prostate cancer

This study aims to construct a Nomogram model to predict the risk of developing castration-resistant prostate cancer (CRPC) in patients with high tumor burden (HTB) and osseous metastatic prostate cancer (PCa), and to identify key prognostic factors. A retrospective analysis was conducted on patients with HTB and osseous metastatic PCa treated at The Sixth Affiliated Hospital, School of Medicine, South China University of Technology and the Second Affiliated Hospital of Guangzhou Medical University from January 2018 to February 2022. Patients' baseline data and laboratory indexes were collected. Cox regression analysis identified neural invasion (NI; P<0.001, HR: 2.371, 95% CI: 1.569-3.582), Gleason score (P=0.002, HR: 1.787, 95% CI: 1.241-2.573), initial PSA (P=0.004, HR: 1.677, 95% CI: 1.174-2.396), and lactate dehydrogenase (LDH; P<0.001, HR: 2.729, 95% CI: 1.855-4.014) as significant prognostic factors for progression to CRPC. The constructed Nomogram model exhibited high accuracy in predicting one- and two-year progression to CRPC, with external validation confirming its predictive performance. Time-dependent receiver operating characteristic (ROC) curves indicated that the areas under the curves (AUCs) of the model for one- and two-year progression to CRPC were 0.81 and 0.76, respectively. This model demonstrates high predictive performance, aiding clinical decision-making and providing personalized treatment strategies for patients with HTB and osseous metastatic PCa.

Rita Levi-Montalcini: From Persecution to the Nobel Prize and an Honorary Degree From a Canadian University

Rita Levi-Montalcini (RLM) is recognized as a prestigious and renowned researcher of her time. She was the fourth woman to earn the Nobel Prize in Physiology and Medicine in 1986 for the discovery of nerve growth factor (NGF). We review her biography and scientific discovery, and provide an example of why her discovery is still important. She had a special relationship with McGill University, Canada, which we describe. We searched for articles and books about her for biographical and scientific material and met with Dr. Claudio Cuello, Former Chair of McGill's Faculty of Medicine.  RLM was born in 1909 in Turin, Italy, where she had studied medicine. She started her career in research. Because of the anti-Jewish racial laws in Italy in 1938, she went underground and continued her projects in her bedroom. After the war, she visited St. Louis, USA, and conducted research there. Her experiments confirmed that tumors release a factor that causes nerve growth and cancer proliferation. Initially, scientists responded to this discovery with skepticism, but after its purification in 1959 and determination of its protein structure in 1971, NGF became widely accepted. Currently, crosstalk between cancers and nerves is poorly understood. The example of prostate cancer shows that surgical or chemical denervation of sympathetic nerves prevents the initiation of prostate tumors, whereas inhibition of parasympathetic nerve signaling reduces the spread of prostate cancer. McGill University awarded RLM a doctoral degree in 2011. It was the first time in its history that the University awarded an honorary doctorate outside of Canada, and the second one outside of Quebec. Through her discovery of NGF, RLM exemplified the power of passion and determination despite the obstacles she faced. Her relentless dedication has led to remarkable achievements.

CCL2/CCR2 Expression in Locally Advanced Prostate Cancer and Patient Long-Term Outcome: 10-Year Results from the TROG 03.04 RADAR Trial

This study investigated the prognostic value of the chemokine C-C motif ligand 2 (CCL2) and its receptor C-C motif chemokine receptor 2 (CCR2) expression in locally advanced prostate cancer treated with radiotherapy and androgen deprivation using the 10-year outcome data from the TROG 03.04 RADAR clinical trial. CCL2 and CCR2 protein expression in prostate cancer biopsies at the time of diagnosis were quantified by immunohistochemistry and digital quantification. CCR2 protein expression was detected in prostate cancer cells and was associated with prostate-specific antigen serum concentration (p = 0.045). However, neither CCL2 nor CCR2 tissue expression could predict prostate cancer progression, or other clinicopathological parameters including perineural invasion and patient outcome. In serum samples, CCL2 concentration at the time of diagnosis, as assayed by enzyme-linked immunosorbent assay, was significantly higher in patients with prostate cancer compared with benign prostatic hyperplasia (median difference 0.22 ng/mL, 95% CI, 0.17-0.30) (p < 0.0001) and normal controls (median difference 0.13 ng/mL, 95% CI, 0.13-0.17) (p < 0.0001). However, circulating CCL2 was not statistically significant as a predictor of disease progression and patient outcome. In conclusion, this study shows that although CCL2 and CCR2 are expressed in prostate cancer, with an increased level of CCL2 in the serum, neither CCL2 nor CCR2 expression has a clinical prognostic value in locally advanced prostate cancer.

Head and Neck Osteosarcoma: Perineural Invasion is Associated With Disease-Free Survival and Tumor Metastasis

BACKGROUND

Head and neck osteosarcoma (HNOS) is the most common bone malignancy in the head and neck region, accounting for 10% of all osteosarcoma cases. Perineural invasion (PNI) is a notable indication of aggressive tumor behavior, which includes the phenomenon of tumor cells invading any of the 3 layers of the nerve sheath or tumor cells gathering, encircling one-third of the nerve circumference, and infiltrating and metastasizing along the nerve. PNI has been reported in various malignant tumors and is considered to be linked to poor prognosis.

PURPOSE

The study's purpose is to measure the association between PNI and survival outcomes in patients with HNOS.

STUDY DESIGN, SETTING, SAMPLE

This retrospective cohort study focused on HNOS patients who underwent surgery at the Department of Oral and Maxillofacial Head and Neck Oncology, Shanghai Ninth People's Hospital School of Medicine, Shanghai Jiao Tong University, from January 1, 2019 to December 31, 2021. Patients who did not undergo complete surgical resection of the tumor, did not receive a conventional osteosarcoma diagnosis, and had positive surgical margins were eliminated.

PREDICTOR VARIABLE

The predictor variable is PNI status. The pathological section of the tumor was consistent with any of the PNI features, which was considered PNI-positive.

MAIN OUTCOME VARIABLE(S)

The primary outcome variables were 3-year disease-free survival (DFS) and 3-year overall survival. Secondary outcomes were 3-year tumor local recurrence and 3-year metastasis (MT).

COVARIATES

Covariates were categorized into the following categories: demographic variables (age, sex), clinical variables (tumor region, primary tumor), and treatment variables (chemotherapy, radiotherapy).

ANALYSES

Analytic statistical methods were used for the data analysis. Pearson χ2 or Fisher's exact test was used to describe the baseline data. Kaplan-Meier is used to calculate survival rates. The Cox regression model was adapted for univariate and multivariate analysis. A P value less than .05 indicated statistical significance.

RESULTS

The study sample comprised 70 patients; 33 (47.1%) were male, and the mean age was 42.2 (standard deviation: 16.7) years. There were 15 (21.4%) cases of PNI. The 3-year DSF rate and OS rate were 67.3% and 82.0%, respectively. PNI-positive resulted in higher risk for MT (P ＜ .01, hazard ratio: 5.95, 95% confidence interval: 1.62-21.86) and negative impact on DFS (P < .01, hazard ratio: 6.35, 95% confidence interval: 2.11-19.17) for HNOS patients.

CONCLUSION AND RELEVANCE

Positive PNI status was associated with decreased DFS and increased risk of MT.

Validation of prostate and breast cancer detection artificial intelligence algorithms for accurate histopathological diagnosis and grading: a retrospective study with a Japanese cohort

Prostate and breast cancer incidence rates have been on the rise in Japan, emphasising the need for precise histopathological diagnosis to determine patient prognosis and guide treatment decisions. However, existing diagnostic methods face numerous challenges and are susceptible to inconsistencies between observers. To tackle these issues, artificial intelligence (AI) algorithms have been developed to aid in the diagnosis of prostate and breast cancer. This study focuses on validating the performance of two such algorithms, Galen Prostate and Galen Breast, in a Japanese cohort, with a particular focus on the grading accuracy and the ability to differentiate between invasive and non-invasive tumours. The research entailed a retrospective examination of 100 consecutive prostate and 100 consecutive breast biopsy cases obtained from a Japanese institution. Our findings demonstrated that the AI algorithms showed accurate cancer detection, with AUCs of 0.969 and 0.997 for the Galen Prostate and Galen Breast, respectively. The Galen Prostate was able to detect a higher Gleason score in four adenocarcinoma cases and detect a previously unreported cancer. The two algorithms successfully identified relevant pathological features, such as perineural invasions and lymphovascular invasions. Although further improvements are required to accurately differentiate rare cancer subtypes, these findings highlight the potential of these algorithms to enhance the precision and efficiency of prostate and breast cancer diagnosis in Japan. Furthermore, this validation paves the way for broader adoption of these algorithms as decision support tools within the Asian population.

Hallmarks of perineural invasion in pancreatic ductal adenocarcinoma: new biological dimensions

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignant tumor with a high metastatic potential. Perineural invasion (PNI) occurs in the early stages of PDAC with a high incidence rate and is directly associated with a poor prognosis. It involves close interaction among PDAC cells, nerves and the tumor microenvironment. In this review, we detailed discuss PNI-related pain, six specific steps of PNI, and treatment of PDAC with PNI and emphasize the importance of novel technologies for further investigation.

Development and Validation of a Biparametric MRI Deep Learning Radiomics Model with Clinical Characteristics for Predicting Perineural Invasion in Patients with Prostate Cancer

RATIONALE AND OBJECTIVES

Perineural invasion (PNI) is an important prognostic biomarker for prostate cancer (PCa). This study aimed to develop and validate a predictive model integrating biparametric MRI-based deep learning radiomics and clinical characteristics for the non-invasive prediction of PNI in patients with PCa.

MATERIALS AND METHODS

In this prospective study, 557 PCa patients who underwent preoperative MRI and radical prostatectomy were recruited and randomly divided into the training and the validation cohorts at a ratio of 7:3. Clinical model for predicting PNI was constructed by univariate and multivariate regression analyses on various clinical indicators, followed by logistic regression. Radiomics and deep learning methods were used to develop different MRI-based radiomics and deep learning models. Subsequently, the clinical, radiomics, and deep learning signatures were combined to develop the integrated deep learning-radiomics-clinical model (DLRC). The performance of the models was assessed by plotting the receiver operating characteristic (ROC) curves and precision-recall (PR) curves, as well as calculating the area under the ROC and PR curves (ROC-AUC and PR-AUC). The calibration curve and decision curve were used to evaluate the model's goodness of fit and clinical benefit.

RESULTS

The DLRC model demonstrated the highest performance in both the training and the validation cohorts, with ROC-AUCs of 0.914 and 0.848, respectively, and PR-AUCs of 0.948 and 0.926, respectively. The DLRC model showed good calibration and clinical benefit in both cohorts.

CONCLUSION

The DLRC model, which integrated clinical, radiomics, and deep learning signatures, can serve as a robust tool for predicting PNI in patients with PCa, thus aiding in developing effective treatment strategies.

Perineural invasion as a predictor of local recurrence in cats with squamous cell carcinoma treated with electrochemotherapy

Introduction

Squamous cell carcinoma (SCC) is a malignant neoplasm that accounts for approximately 15-25% and 70-80% of all feline cutaneous and oral tumors, respectively. Similar to that in humans, feline SCC can be highly invasive locally; however, its metastasis rate is low. Thus, effective local treatment may be curative for most patients, and includes surgery, electrochemotherapy (ECT), cryosurgery, or a combination of these. However, this neoplasia can manifest more aggressively in some patients, leading to higher recurrence rates. In humans, perineural invasion (PNI) has been described as a relevant tumor dissemination pathway associated with high-risk SCC, resulting in higher recurrence rates, resistance to local treatments, and short survival. However, PNI and its prognostic value have not been described in feline SCC. This study aimed to evaluate the PNI in a feline population with SCC treated with ECT and correlate its presence with the occurrence of local recurrence and other clinical variables.

Methods

Twenty-four cats histopathologically diagnosed with SCC between 2013 and 2021 were retrospectively selected from the medical records of the Oncological Center Vet Cancer (São Paulo, SP, Brazil). The inclusion criteria were ECT as the sole therapy, histopathological evaluation of PNI, and absence of distant metastatic disease.

Results

The complete response rate was 96% (23/24), and PNI was identified in 33% of the cats (8/24, PNI-positive group), whereas 67% were free of this invasion (16/24, PNI-negative group). All PNI-positive cats developed local recurrence, whereas only five PNI-negative cats experienced recurrence. Local recurrence was significantly associated with PNI (p = 0.03).

Discussion

The results of this study are preliminary but promising. The data obtained are the first regarding PNI occurrence in feline SCC and pave the way for further studies, mainly to correlate the PNI with survival data and better define its prognostic value.

Perineural invasion score system and clinical outcomes in resected pancreatic cancer patients

BACKGROUND/OBJECTIVES

Perineural invasion (PNI), classified according to its presence or absence in tumor specimens, is recognized as a poor prognostic factor in pancreatic ductal adenocarcinoma (PDAC) patients. Herein, we identified five histological features of PNI and investigated their impact on survival outcomes of PDAC resected patients.

METHODS

Five histopathological features of PNI (diameter, number, site, sheath involvement, and mitotic figures within perineural invasion) were combined in an additional final score (ranging from 0 to 8), and clinical data of PDAC patients were retrospectively analyzed. PNI + patients were stratified in two categories according to the median score value (<6 and ≥ 6, respectively). Impact of PNI on disease-free survival (DFS) and overall survival (OS) were analyzed.

RESULTS

Forty-five patients were enrolled, of whom 34 with PNI (PNI+) and 11 without PNI (PNI-). The DFS was 11 months vs. not reached (NR) (p = 0.258), while the OS was 19 months vs. NR (p = 0.040) in PNI+ and PNI- patients, respectively. A ≥6 PNI was identified as an independent predictor of worse OS vs. <6 PNI + patients (29 vs. 11 months, p < 0.001) and <6 PNI+ and PNI- patients (43 vs. 11 months, p < 0.001). PNI ≥6 was an independent negative prognostic factor of DFS vs. <6 PNI+ and PNI- patients (13 vs. 6 months, p = 0.022).

CONCLUSIONS

We report a PNI scoring system that stratifies surgically-treated PDAC patients in a graded manner that correlates with patient prognosis better than the current dichotomous (presence/absence) definition. However, further and larger studies are needed to support this PNI scoring system.

The Crosstalk between Nerves and Cancer-A Poorly Understood Phenomenon and New Possibilities

INTRODUCTION

Crosstalk occurs between nerve and cancer cells. These interactions are important for cancer homeostasis and metabolism. Nerve cells influence the tumor microenvironment (TME) and participate in metastasis through neurogenesis, neural extension, and axonogenesis. We summarized the past and current literature on the interaction between nerves and cancer, with a special focus on pancreatic ductal adenocarcinoma (PDAC), prostate cancer (PCa), and the role of the nerve growth factor (NGF) in cancer.

MATERIALS/METHODS

We reviewed PubMed and Google Scholar for the relevant literature on the relationship between nerves, neurotrophins, and cancer in general and specifically for both PCa and PDAC.

RESULTS

The NGF helped sustain cancer cell proliferation and evade immune defense. It is a neuropeptide involved in neurogenic inflammation through the activation of several cells of the immune system by several proinflammatory cytokines. Both PCa and PDAC employ different strategies to evade immune defense. The prostate is richly innervated by both the sympathetic and parasympathetic nerves, which helps in both growth control and homeostasis. Newly formed autonomic nerve fibers grow into cancer cells and contribute to cancer initiation and progression through the activation of β-adrenergic and muscarinic cholinergic signaling. Surgical or chemical sympathectomy prevents the development of prostate cancer. Beta-blockers have a high therapeutic potential for cancer, although current clinical data have been contradictory. With a better understanding of the beta-receptors, one could identify specific receptors that could have an effect on prostate cancer development or act as therapeutic agents.

CONCLUSION

The bidirectional crosstalk between the nervous system and cancer cells has emerged as a crucial regulator of cancer and its microenvironment. Denervation has been shown to be promising in vitro and in animal models. Additionally, there is a potential relationship between cancer and psychosocial biology through neurotransmitters and neurotrophins.

Development of risk-score model in patients with negative surgical margin after robot-assisted radical prostatectomy

A total of 739 patients underwent RARP as initial treatment for PCa from November 2011 to October 2018. Data on BCR status, clinical and pathological parameters were collected from the clinical records. After excluding cases with neoadjuvant and/or adjuvant therapies, presence of lymph node or distant metastasis, and positive SM, a total of 537 cases were eligible for the final analysis. The median follow-up of experimental cohort was 28.0 (interquartile: 18.0-43.0) months. We identified the presence of International Society of Urological Pathology grade group (ISUP-GG) ≥ 4 (Hazard ratio (HR) 3.20, 95% Confidence Interval (95% CI) 1.70-6.03, P < 0.001), lymphovascular invasion (HR 2.03, 95% CI 1.00-4.12, P = 0.049), perineural invasion (HR 10.7, 95% CI 1.45-79.9, P = 0.020), and maximum tumor diameter (MTD) > 20 mm (HR 1.9, 95% CI 1.01-3.70, P = 0.047) as significant factors of BCR in the multivariate analysis. We further developed a risk model according to these factors. Based on this model, 1-year, 3-year, and 5-year BCR-free survival were 100%, 98.9%, 98.9% in the low-risk group; 99.1%, 94.1%, 86.5% in the intermediate-risk group; 93.9%, 84.6%, 58.1% in the high-risk group. Internal validation using the bootstrap method showed a c-index of 0.742 and an optimism-corrected c-index level of 0.731. External validation was also carried out using an integrated database derived from 3 other independent institutions including a total of 387 patients for the final analysis. External validation showed a c-index of 0.655. In conclusion, we identified risk factors of biochemical failure in patients showing negative surgical margin after RARP and further developed a risk model using these risk factors.

Clinical impact of perineural invasion encircled completely vs. incompletely by prostate cancer on needle core biopsy

The clinical significance of the pattern or degree of perineural invasion (PNI) by prostate cancer remains largely unknown. We herein assessed radical prostatectomy findings and postoperative oncologic outcomes in 125 patients who had undergone systematic sextant prostate biopsy exhibiting only a single focus of PNI encircled completely (n = 57; 46 %) vs. incompletely (n = 68; 54 %) by cancer. Between these two cohorts, there were no significant differences in clinicopathological features on biopsy or prostatectomy, including tumor grade, stage, and length or volume, and surgical margin status, as well as the need for adjuvant therapy immediately after prostatectomy. Similarly, survival analysis demonstrated no significant difference in the risk of disease progression following prostatectomy in patients with encircled vs. non-encircled PNI on biopsy (P = 0.679). When the non-encircled cases were further divided into four groups [i.e. 1-25 % enclosed (n = 12; 18 %), 26-50 % enclosed (n = 18; 26 %), 51-75 % enclosed (n = 10; 15 %), 76-99 % enclosed (n = 28; 41 %)], the rates of progression-free survival were comparable among the five groups (P = 0.954). In prostate biopsy specimens exhibiting PNI at only one focus, the degree of nerve involvement thus appears to have little clinical impact. Accordingly, PNI detected on prostate biopsy may need to be similarly taken into consideration irrespective of the degree of nerve involvement.

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.

Advances in landscape and related therapeutic targets of the prostate tumor microenvironment

The distinct tumor microenvironment (TME) of prostate cancer (PCa), which promotes tumor proliferation and progression, consists of various stromal cells, immune cells, and a dense extracellular matrix (ECM). The understanding of the prostate TME extends to tertiary lymphoid structures (TLSs) and metastasis niches to provide a more concise comprehension of tumor metastasis. These constituents collectively structure the hallmarks of the pro-tumor TME, including immunosuppressive, acidic, and hypoxic niches, neuronal innervation, and metabolic rewiring. In combination with the knowledge of the tumor microenvironment and the advancement of emerging therapeutic technologies, several therapeutic strategies have been developed, and some of them have been tested in clinical trials. This review elaborates on PCa TME components, summarizes various TME-targeted therapies, and provides insights into PCa carcinogenesis, progression, and therapeutic strategies.

Predicting Tumor Perineural Invasion Status in High-Grade Prostate Cancer Based on a Clinical-Radiomics Model Incorporating T2-Weighted and Diffusion-Weighted Magnetic Resonance Images

PURPOSE

To explore the role of bi-parametric MRI radiomics features in identifying PNI in high-grade PCa and to further develop a combined nomogram with clinical information.

METHODS

183 high-grade PCa patients were included in this retrospective study. Tumor regions of interest (ROIs) were manually delineated on T2WI and DWI images. Radiomics features were extracted from lesion area segmented images obtained. Univariate logistic regression analysis and the least absolute shrinkage and selection operator (LASSO) method were used for feature selection. A clinical model, a radiomics model, and a combined model were developed to predict PNI positive. Predictive performance was estimated using receiver operating characteristic (ROC) curves, calibration curves, and decision curves.

RESULTS

The differential diagnostic efficiency of the clinical model had no statistical difference compared with the radiomics model (area under the curve (AUC) values were 0.766 and 0.823 in the train and test group, respectively). The radiomics model showed better discrimination in both the train cohort and test cohort (train AUC: 0.879 and test AUC: 0.908) than each subcategory image (T2WI train AUC: 0.813 and test AUC: 0.827; DWI train AUC: 0.749 and test AUC: 0.734). The discrimination efficiency improved when combining the radiomics and clinical models (train AUC: 0.906 and test AUC: 0.947).

CONCLUSION

The model including radiomics signatures and clinical factors can accurately predict PNI positive in high-grade PCa patients.

An Overview of the Molecular Cues and Their Intracellular Signaling Shared by Cancer and the Nervous System: From Neurotransmitters to Synaptic Proteins, Anatomy of an All-Inclusive Cooperation

We propose an overview of the molecular cues and their intracellular signaling involved in the crosstalk between cancer and the nervous system. While "cancer neuroscience" as a field is still in its infancy, the relation between cancer and the nervous system has been known for a long time, and a huge body of experimental data provides evidence that tumor-nervous system connections are widespread. They encompass different mechanisms at different tumor progression steps, are multifaceted, and display some intriguing analogies with the nervous system's physiological processes. Overall, we can say that many of the paradigmatic "hallmarks of cancer" depicted by Weinberg and Hanahan are affected by the nervous system in a variety of manners.