Perineural invasion is associated with function-evoked pain and altered extracellular matrix in patients with head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is painful, and perineural invasion (PNI) has been associated with worst pain. Pain due to HNSCC is diverse and may vary based on clinicopathological factors. This study aims to characterize different pain patterns linked with PNI, its influence on daily functioning, and gain insights into molecular changes and pathways associated with PNI-related pain in HNSCC patients. We conducted a cross-sectional study across three medical centers (n=114), assessing pain phenotypes and their impact on daily functioning using two self-reported pain questionnaires, given to patients prior to their cancer surgery. Furthermore, we conducted RNA-seq analysis utilizing the TCGA dataset of HNSCC tumor from patients (n=192) to identify genes relevant to both PNI and pain. Upon adjusting for demographic and clinicopathological variables using linear regression models, we found that PNI independently predicted function-evoked pain according to the UCSF Oral Cancer Pain Questionnaire, as well as the worst pain intensity reported in the Brief Pain Inventory. Distinct pain patterns were observed to be associated with daily activities in varying manners. Our molecular analyses revealed significant disruptions in pathways associated with extracellular matrix (ECM) structure and organization. The top differentially expressed genes linked to the ECM are implicated in cancer development, pain, and neurodegenerative diseases. Our data underscore the importance of properly categorizing pain phenotypes in future studies aiming to uncover mechanistic underpinnings of pain. Additionally, we have compiled a list of genes of interest that could serve as targets for both cancer and cancer pain management. PERSPECTIVE: PNI independently predicts function-evoked pain. Different pain phenotypes affect daily activities differently. We identified a list of candidate genes involved in extracellular matrix structure and function that can be targeted for both cancer and cancer pain control.

Context-Dependent Regulation of Peripheral Nerve Abundance by the PI3K Pathway in the Tumor Microenvironment of Head and Neck Squamous Cell Carcinoma.

Recent studies have highlighted neurons and their associated Schwann cells (SCs) as key regulators of cancer development. However, the mode of their interaction with tumor cells or other components of the tumor microenvironment (TME) remains elusive. We established an SC-related 43-gene set as a surrogate for peripheral nerves in the TME. Head and neck squamous cell carcinoma (HNSCC) from The Cancer Genome Atlas (TCGA) were classified into low, intermediate and high SC score groups based on the expression of this gene set. Perineural invasion (PNI) and TGF-ß signaling were hallmarks of SChigh tumors, whereas SClow tumors were enriched for HPV16-positive OPSCC and higher PI3K-MTOR activity. The latter activity was partially explained by a higher frequency of PTEN mutation and PIK3CA copy number gain. The inverse association between PI3K-MTOR activity and peripheral nerve abundance was context-dependent and influenced by the TP53 mutation status. An in silico drug screening approach highlighted the potential vulnerabilities of HNSCC with variable SC scores and predicted a higher sensitivity of SClow tumors to DNA topoisomerase inhibitors. In conclusion, we have established a tool for assessing peripheral nerve abundance in the TME and provided new clinical and biological insights into their regulation. This knowledge may pave the way for new therapeutic strategies and impart proof of concept in appropriate preclinical models.

The Prognostic Value of Proliferative Activity in Cutaneous Melanoma: A Pilot Study Evaluating the Mitotic Rate and Ki67 Index to Predict Patient Outcomes.

Proliferative activity in cutaneous melanomas can be appreciated both histopathologically by counting mitotic figures and immunohistochemically through the Ki67 index, but the prognostic value of each method is still a matter of debate. In this context, we performed a retrospective study on 33 patients diagnosed with cutaneous melanomas between 2013 and 2018 in order to evaluate progression-free survival and overall survival. Multivariate Cox proportional hazards regression was performed by considering both clinical histopathological and immunohistochemical features. The mitotic rate was significantly independently associated with both outcomes, while the Ki67 index was not an independent prognostic factor. However, the Ki67 predictive accuracy could be improved by establishing both a cut-off value and a standardized protocol for evaluating its expression. Until these desiderata are met, the mitotic rate remains superior to the Ki67 index for predicting prognosis in cutaneous melanomas, as also has the advantage of being easily interpreted in a standard histopathological examination regardless of the pathologist's experience and with no further financial expenses. Importantly, this is one of very few articles that has shown perineural invasion to be an independent prognostic factor for both progression-free survival and overall survival in cutaneous melanomas. As a consequence, this parameter should become a mandatory feature in the histopathological evaluation of cutaneous melanomas as it can improve the identification of patients who are at high risk for disease progression.

Construction of a preoperative nomogram model for predicting perineural invasion in advanced gastric cancer.

Objective: This study aimed to develop and validate a clinical and imaging-based nomogram for preoperatively predicting perineural invasion (PNI) in advanced gastric cancer. Methods: A retrospective cohort of 351 patients with advanced gastric cancer who underwent surgical resection was included. Multivariable logistic regression analysis was conducted to identify independent risk factors for PNI and to construct the nomogram. The performance of the nomogram was assessed using calibration curves, the concordance index (C-index), the area under the curve (AUC), and decision curve analysis (DCA). The disparity in disease-free survival (DFS) between the nomogram-predicted PNI-positive group and the nomogram-predicted PNI-negative group was evaluated using the Log-Rank test and Kaplan-Meier analysis. Results: Extramural vascular invasion (EMVI), Borrmann classification, tumor thickness, and the systemic inflammation response index (SIRI) emerged as independent risk factors for PNI. The nomogram model demonstrated a commendable AUC value of 0.838. Calibration curves exhibited excellent concordance, with a C-index of 0.814. DCA indicated that the model provided good clinical net benefit. The DFS of the nomogram-predicted PNI-positive group was significantly lower than that of the nomogram-predicted PNI-negative group (p < 0.001). Conclusion: This study successfully developed a preoperative nomogram model that not only effectively predicted PNI in gastric cancer but also facilitated postoperative risk stratification.

[Amplifiation of the c-MYC gene in acinar prostate adenocarcinoma. Morphogenic comparisons]. / Amplifikatsiya gena c-MYC pri atsinarnoi adenokartsinome prostaty. Morfogeneticheskie sopostavleniya.

OBJECTIVE: The purpose of this work was to evaluate c-MYC gene amplification in the substrate of prostate acinar adenocarcinoma at various Gleason scores and various stages of the disease, taking into account the morphological characteristics of the tumor. MATERIAL AND METHODS: The number of cases in the study was 82, including the control group - 12 cases. Morphological assessment included: determination of the total Gleason score, grading group, assessment of lymphovascular/perineural invasion, and architectural characteristics of the tumor. Gene amplification was assessed by FISH using the c-MYC (8q24)/SE8 probe. RESULTS: In all cases of the study group, amplification of the c-MYC gene was detected in the tumor, with a significant difference from the control group (p<0.05). When assessing cases with 4-6 fold copies of the gene, significant differences were established between patients with stages II and III of the disease and stage IV (10.0 and 13.5 versus 30.0) (p<0.05). Cluster amplification of the c-MYC gene was detected with equal frequency in groups of patients with stages III and IV of the disease, while in stage II of the disease, the event almost did not occur (p<0.05). A significant increase in the level of c-MYC gene amplification was found in groups with advanced stages of the disease (p<0.02). Non-cluster amplification significantly distinguishes T4M0 and T4M1 stage patients from the rest with a significant increase in the score (p<0.05). In the metastatic stage of the disease, there was an increase c-MYC gene amplification compared to the non-metastatic stage (p<0.02). The copy number of the c-MYC gene was significantly higher in cases with perineural and lymphovascular invasion, as well as in cases of cribriform tumor organization (p<0.05). CONCLUSION: Amplification of the c-MYC gene in prostate tumor cells is associated with advanced stages of the disease (T4M0 and T4M1) with an increase in the copy number of the gene during the metastatic stage of the process. It was found that increased amplification of the c-MYC gene distinguishes groups of patients whose tumors exhibit perineural and lymphovascular invasion, as well as a cribriform pattern of tumor organization.

Effect of Epidermal Growth Factor Receptor Mutation on Positron Emission Tomography/Computed Tomography in Lung Cancer.

BACKGROUND/AIM: This study analyzed the effect of epidermal growth factor receptor (EGFR) mutations on fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (F-18 FDG PET/CT) results in lung cancer and the pathological findings in patients subjected to surgery. PATIENTS AND METHODS: A total of 210 patients diagnosed with lung cancer by F-18 FDG PET/CT at Inje University Busan Paik Hospital between January 2018 and December 2023 were recruited. EGFR mutation tests were performed on biopsy specimens. Overall, 78 patients (37.1%) with EGFR mutations were included in this study. Twenty-seven patients (12.9%) had distant metastases at the time of diagnosis. Of all patients, 69 (32.9%) underwent surgery at our hospital, and their pathological findings were analyzed. RESULTS: The maximum standardized uptake value (SUVmax) of F-18 FDG PET/CT was <10 in patients with EGFR mutations. Patients with EGFR mutations were not commonly diagnosed with diabetes. When analyzing the pathological findings after surgery in the 69 patients, adenocarcinoma was more common in those with EGFR mutations. In contrast, perineural invasion was more common in patients without EGFR mutations. When analyzing the results of 69 patients with postoperative pathology, 25 relapsed during the median follow-up of 21.7 months (range=0.9-58.4 months). Patients who underwent surgery and had EGFR mutations (n=26) exhibited lower recurrence rates compared to those without EGFR mutations. Disease-free survival was longer in patients with EGFR mutations. CONCLUSION: In non-small-cell lung cancer with an EGFR mutation, the F-18 FDG PET/CT SUVmax value and the probability of recurrence were lower. EGFR mutations are associated with low-glucose metabolism.

Spectral CT in the evaluation of perineural invasion status in rectal cancer.

PURPOSE: To investigate whether preoperative spectral CT quantitative parameters can assess perineural invasion (PNI) status in rectal cancer. METHODS: Sixty-two patients diagnosed with rectal cancer who underwent preoperative spectral CT were retrospectively enrolled and divided into positive and negative PNI groups according to histopathologic results. The CT attenuation value (HU) of virtual monochromatic images (40-70 keV), spectral curve slope (K(HU)), effective atomic number (Zeff), and iodine concentration (IC) from spectral CT were compared between these two groups using t test or rank sum test. A nomogram was established by incorporating the independent predictors to assess the overall diagnostic efficacy. The area under the ROC curves (AUCs) were compared using the DeLong test. RESULTS: The preoperative spectral CT parameters (40-70 keV attenuation, K(HU), Zeff, and IC) were significantly higher in the PNI-positive group compared to the PNI-negative group (all p < 0.05). The highest predictive efficiency of PNI was observed at 40 keV attenuation, with an area under the curve (AUC), sensitivity, specificity, and accuracy of 0.847, 81.8%, 72.5%, and 75.8%, respectively. Binary logistic regression demonstrated that the clinical feature (cN stage) and 40 keV attenuation were independent predictors of PNI status. The nomogram incorporating these two predictors (cN stage and 40 keV attenuation) exhibited the best evaluation efficacy, with an AUC, sensitivity, specificity, and accuracy of 0.885, 86.4%, 77.5%, and 80.6%. CONCLUSION: Spectral CT quantitative parameters proved valuable in the preoperative assessment of PNI status in rectal cancer patients. The combination of spectral CT parameters and clinical features could further enhance the diagnostic efficiency.

Preoperative prediction of perineural invasion of rectal cancer based on a magnetic resonance imaging radiomics model: A dual-center study.

BACKGROUND: Perineural invasion (PNI) has been used as an important pathological indicator and independent prognostic factor for patients with rectal cancer (RC). Preoperative prediction of PNI status is helpful for individualized treatment of RC. Recently, several radiomics studies have been used to predict the PNI status in RC, demonstrating a good predictive effect, but the results lacked generalizability. The preoperative prediction of PNI status is still challenging and needs further study. AIM: To establish and validate an optimal radiomics model for predicting PNI status preoperatively in RC patients. METHODS: This retrospective study enrolled 244 postoperative patients with pathologically confirmed RC from two independent centers. The patients underwent pre-operative high-resolution magnetic resonance imaging (MRI) between May 2019 and August 2022. Quantitative radiomics features were extracted and selected from oblique axial T2-weighted imaging (T2WI) and contrast-enhanced T1WI (T1CE) sequences. The radiomics signatures were constructed using logistic regression analysis and the predictive potential of various sequences was compared (T2WI, T1CE and T2WI + T1CE fusion sequences). A clinical-radiomics (CR) model was established by combining the radiomics features and clinical risk factors. The internal and external validation groups were used to validate the proposed models. The area under the receiver operating characteristic curve (AUC), DeLong test, net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration curve, and decision curve analysis (DCA) were used to evaluate the model performance. RESULTS: Among the radiomics models, the T2WI + T1CE fusion sequences model showed the best predictive performance, in the training and internal validation groups, the AUCs of the fusion sequence model were 0.839 [95% confidence interval (CI): 0.757-0.921] and 0.787 (95%CI: 0.650-0.923), which were higher than those of the T2WI and T1CE sequence models. The CR model constructed by combining clinical risk factors had the best predictive performance. In the training and internal and external validation groups, the AUCs of the CR model were 0.889 (95%CI: 0.824-0.954), 0.889 (95%CI: 0.803-0.976) and 0.894 (95%CI: 0.814-0.974). Delong test, NRI, and IDI showed that the CR model had significant differences from other models (P < 0.05). Calibration curves demonstrated good agreement, and DCA revealed significant benefits of the CR model. CONCLUSION: The CR model based on preoperative MRI radiomics features and clinical risk factors can preoperatively predict the PNI status of RC noninvasively, which facilitates individualized treatment of RC patients.

The prognostic and predictive significance of perineural invasion in stage I to III colon cancer: a propensity score matching-based analysis.

BACKGROUND: Colorectal cancer (CRC) presents with varying prognoses, and identifying factors for predicting metastasis and outcomes is crucial. Perineural invasion (PNI) is a debated prognostic factor for CRC, particularly in stage I-III patients, but its role in guiding adjuvant chemotherapy for node-positive colon cancer remains uncertain. METHODS: We conducted a single-center study using data from the Colorectal Section Tumor Registry Database at Chang Gung Memorial Hospital, Taiwan. This prospective study involved 3,327 CRC patients, 1,536 of whom were eligible after application of the exclusion criteria, to investigate the prognostic value of PNI in stage I-III patients and its predictive value for node-positive/negative cancer patients receiving adjuvant chemotherapy. Propensity score matching (PSM) was used to minimize selection bias, and follow-up was performed with standardized procedures. RESULTS: PNI-positive (PNI+) tumors were associated with higher preoperative CEA levels and more frequent adjuvant chemotherapy. After PSM, PNI + tumors were associated with marginally significantly lower 5-year disease-free survival (DFS) and significantly lower overall survival (OS) rates in stages III CRC. However, no significant differences were observed in stages I and II. Subgroup analysis showed that among PNI + tumors, only poorly differentiated tumors had higher odds of recurrence. PNI did not predict outcomes in node-negative colon cancer. Adjuvant chemotherapy benefited PNI + patients with node-positive but not those with node-negative disease. CONCLUSIONS: Our study indicates that PNI is an independent poor prognostic factor in stage III colon cancer but does not predict outcomes in node-negative disease. Given the potential adverse effects of adjuvant chemotherapy, our findings discourage its use in node-negative colon cancer when PNI is present.

Perineural invasion in cervical cancer: A multicenter retrospective study.

OBJECTIVE: The study aimed to evaluate the accuracy of perineural invasion (PNI) diagnosis in cervical cancer, and to analyze the impact of PNI on the prognosis and postoperative adjuvant treatment decisions for cervical cancer. METHODS: A retrospective pathological review of PNI in cervical cancer was conducted from 2004 to 2016 in 15 hospitals. RESULTS: This study included a total of 1208 cases, comprising 273 cases with PNI and 935 cases without. The false positive rate and false negative rate of PNI diagnosis were 5.35% (50/935) and 33.33% (91/273), respectively. Adenocarcinoma, deep stromal invasion, lymphovascular space invasion (LVSI) (+), and margin involvement were independent risk factors for PNI. Both 5-year overall survival rate (OS) and 5-year disease-free survival rate (DFS) of PNI group were worse than non-PNI group. PNI was an independent risk factor for 5-year OS and 5-year DFS. In cases receiving standard postoperative adjuvant treatment, among those with two intermediate-risk factors, both 5-year OS and DFS were worse in the PNI group. Among cases with three intermediate-risk factors or at least one high-risk factor, there was no difference in 5-year OS between the two groups, but 5-year DFS was worse in the PNI group. CONCLUSION: The diagnosis of PNI in cervical cancer was not accurate. Adenocarcinoma, deep stromal invasion, LVSI, and margin involvement were independent risk factors for PNI. PNI was an independent risk factor for 5-year OS and DFS. PNI has the potential to serve as a new high-risk factor, thus providing guidance for postoperative adjuvant therapy.

The depth of perineural invasion is an independent prognostic factor for stage II colorectal cancer.

BACKGROUND: Perineural invasion (PNI) is the invasion of nerves by cancer cells and is associated with poor survival in stage II colorectal cancer. However, PNI can be further subdivided according to the depth of invasion, and the depth of PNI has not been clearly linked to prognosis. METHOD: This study aimed to assess the prognostic value of different depths of PNI in stage II colorectal cancer. We defined PNI in the submucosal plexus and myenteric plexus as superficial perineural invasion (sup-PNI) and PNI in the subserous plexus as deep perineural invasion (deep-PNI). Patients were divided into three groups based on the depth of PNI: sup-PNI, deep-PNI and non-PNI. Then, univariate and multivariate Cox regression analyses were conducted to evaluate the role of PNI in the prognosis of stage II colorectal cancer. RESULTS: This study enrolled 3508 patients with stage II colorectal cancer who underwent resection for primary colorectal lesions between January 2013 and September 2019. Clinicopathological features, including elevated carcinoembryonic antigen (CEA) levels, T4 stage, poor differentiation, deficient DNA mismatch repair (dMMR), and vascular invasion, were correlated with deep-PNI. Multivariate analyses revealed that deep-PNI was associated with worse overall survival (OS; hazard ratio [HR], 3.546; 95% confidence interval [CI], 2.307-5.449; P < 0.001) and disease-free survival (DFS; HR, 2.921; 95% CI, 2.032-4.198; P < 0.001), compared with non-PNI. Conversely, no significant difference in OS or DFS was observed between the sup-PNI and non-PNI groups in multivariate analyses. CONCLUSIONS: The study demonstrated that the depth of PNI was an independent prognostic factor for patients with stage II colorectal cancer, and patients with deep PNI had a worse prognosis. Thus, patients with PNI require further subdivision according to the depth of invasion.

The value of machine learning based on CT radiomics in the preoperative identification of peripheral nerve invasion in colorectal cancer: a two-center study.

BACKGROUND: We aimed to explore the application value of various machine learning (ML) algorithms based on multicenter CT radiomics in identifying peripheral nerve invasion (PNI) of colorectal cancer (CRC). METHODS: A total of 268 patients with colorectal cancer who underwent CT examination in two hospitals from January 2016 to December 2022 were considered. Imaging and clinicopathological data were collected through the Picture Archiving and Communication System (PACS). The Feature Explorer software (FAE) was used to identify the peripheral nerve invasion of colorectal patients in center 1, and the best feature selection and classification channels were selected. Finally, the best feature selection and classifier pipeline were verified in center 2. RESULTS: The six-feature models using RFE feature selection and GP classifier had the highest AUC values, which were 0.610, 0.699, and 0.640, respectively. FAE generated a more concise model based on one feature (wavelet-HLL-glszm-LargeAreaHighGrayLevelEmphasis) and achieved AUC values of 0.614 and 0.663 on the validation and test sets, respectively, using the "one standard error" rule. Using ANOVA feature selection, the GP classifier had the best AUC value in a one-feature model, with AUC values of 0.611, 0.663, and 0.643 on the validation, internal test, and external test sets, respectively. Similarly, when using the "one standard error" rule, the model based on one feature (wave-let-HLL-glszm-LargeAreaHighGrayLevelEmphasis) achieved AUC values of 0.614 and 0.663 on the validation and test sets, respectively. CONCLUSIONS: Combining artificial intelligence and radiomics features is a promising approach for identifying peripheral nerve invasion in colorectal cancer. This innovative technique holds significant potential for clinical medicine, offering broader application prospects in the field. CRITICAL RELEVANCE STATEMENT: The multi-channel ML method based on CT radiomics has a simple operation process and can be used to assist in the clinical screening of patients with CRC accompanied by PNI. KEY POINTS: • Multi-channel ML in the identification of peripheral nerve invasion in CRC. • Multi-channel ML method based on CT-radiomics can detect the PNI of CRC. • Early preoperative identification of PNI in CRC is helpful to improve the formulation of treatment strategies and the prognosis of patients.

Molecular pathway of pancreatic cancer-associated neuropathic pain.

The pancreas is a heterocrine gland that has both exocrine and endocrine parts. Most pancreatic cancer begins in the cells that line the ducts of the pancreas and is called pancreatic ductal adenocarcinoma (PDAC). PDAC is the most encountered pancreatic cancer type. One of the most important characteristic features of PDAC is neuropathy which is primarily due to perineural invasion (PNI). PNI develops tumor microenvironment which includes overexpression of fibroblasts cells, macrophages, as well as angiogenesis which can be responsible for neuropathy pain. In tumor microenvironment inactive fibroblasts are converted into an active form that is cancer-associated fibroblasts (CAFs). Neurotrophins they also increase the level of Substance P, calcitonin gene-related peptide which is also involved in pain. Matrix metalloproteases are the zinc-associated proteases enzymes which activates proinflammatory interleukin-1ß into its activated form and are responsible for release and activation of Substance P which is responsible for neuropathic pain by transmitting pain signal via dorsal root ganglion. All the molecules and their role in being responsible for neuropathic pain are described below.

Periampullary cancer and neurological interactions: current understanding and future research directions.

Periampullary cancer is a malignant tumor occurring around the ampullary region of the liver and pancreas, encompassing a variety of tissue types and sharing numerous biological characteristics, including interactions with the nervous system. The nervous system plays a crucial role in regulating organ development, maintaining physiological equilibrium, and ensuring life process plasticity, a role that is equally pivotal in oncology. Investigations into nerve-tumor interactions have unveiled their key part in controlling cancer progression, inhibiting anti-tumor immune responses, facilitating invasion and metastasis, and triggering neuropathic pain. Despite many mechanisms by which nerve fibers contribute to cancer advancement still being incompletely understood, the growing emphasis on the significance of nerves within the tumor microenvironment in recent years has set the stage for the development of groundbreaking therapies. This includes combining current neuroactive medications with established therapeutic protocols. This review centers on the mechanisms of Periampullary cancer's interactions with nerves, the influence of various types of nerve innervation on cancer evolution, and outlines the horizons for ongoing and forthcoming research.

Peeping Beyond TNM Stage: Prognostic Factors Affecting Oncological Outcomes in Surgically Treated Early Oral Cancer.

Surgery is the primary modality for the treatment of early oral cancer. The present study aims to evaluate the oncological outcomes, patterns of failure, and prognostic predictors of recurrence in patients of early oral cancer (Stage I and II) treated by surgery alone. It is a single institutional, observational retrospective cohort study conducted from 2012 to 2017.The study was approved by institutional ethics committee. All consecutive patients who underwent upfront curative surgery alone (wide excision of tumour + neck dissection) for pathologically proven early oral cavity SCC(Squamous Cell Carcinoma) pT1-2N0 were included in the study. 113 patients were included in the study after a median follow-up of 58.2 months. The median age was 58.5 years. 25 patients were stage I, and 88 patients were stage II. The most common subsite was buccal mucosa. There were 31 recurrences and 24 deaths. Using Kaplan Meier method, 3 and 5 year overall survival was 92% and 71.8%, respectively, while 3 year and 5 year recurrence-free survival was 77.9% and 69.4%, respectively. Perineural invasion and poor differentiation affected recurrence-free survival significantly (p value < 0.05). More than one-fourth of surgically treated early oral SCC patients developed recurrence. Presence of poorly differentiated histology and the perineural invasion were the high risk factors which hampered the recurrence free survival. High consumption of betel quid consumption in this part of the world leads to differences in the involved subsite from the Western literature. Adding adjuvant treatment in the presence of these adverse histopathological features may improve prognosis. Randomised studies are warranted to answer this dilemma. Level of Evidence IV.

A prediction nomogram for perineural invasion in colorectal cancer patients: a retrospective study.

BACKGROUND: Perineural invasion (PNI), as the fifth recognized pathway for the spread and metastasis of colorectal cancer (CRC), has increasingly garnered widespread attention. The preoperative identification of whether colorectal cancer (CRC) patients exhibit PNI can assist clinical practitioners in enhancing preoperative decision-making, including determining the necessity of neoadjuvant therapy and the appropriateness of surgical resection. The primary objective of this study is to construct and validate a preoperative predictive model for assessing the risk of perineural invasion (PNI) in patients diagnosed with colorectal cancer (CRC). MATERIALS AND METHODS: A total of 335 patients diagnosed with colorectal cancer (CRC) at a single medical center were subject to random allocation, with 221 individuals assigned to a training dataset and 114 to a validation dataset, maintaining a ratio of 2:1. Comprehensive preoperative clinical and pathological data were meticulously gathered for analysis. Initial exploration involved conducting univariate logistic regression analysis, with subsequent inclusion of variables demonstrating a significance level of p < 0.05 into the multivariate logistic regression analysis, aiming to ascertain independent predictive factors, all while maintaining a p-value threshold of less than 0.05. From the culmination of these factors, a nomogram was meticulously devised. Rigorous evaluation of this nomogram's precision and reliability encompassed Receiver Operating Characteristic (ROC) curve analysis, calibration curve assessment, and Decision Curve Analysis (DCA). The robustness and accuracy were further fortified through application of the bootstrap method, which entailed 1000 independent dataset samplings to perform discrimination and calibration procedures. RESULTS: The results of multivariate logistic regression analysis unveiled independent risk factors for perineural invasion (PNI) in patients diagnosed with colorectal cancer (CRC). These factors included tumor histological differentiation (grade) (OR = 0.15, 95% CI = 0.03-0.74, p = 0.02), primary tumor location (OR = 2.49, 95% CI = 1.21-5.12, p = 0.013), gross tumor type (OR = 0.42, 95% CI = 0.22-0.81, p = 0.01), N staging in CT (OR = 3.44, 95% CI = 1.74-6.80, p < 0.001), carcinoembryonic antigen (CEA) level (OR = 3.13, 95% CI = 1.60-6.13, p = 0.001), and platelet-to-lymphocyte ratio (PLR) (OR = 2.07, 95% CI = 1.08-3.96, p = 0.028).These findings formed the basis for constructing a predictive nomogram, which exhibited an impressive area under the receiver operating characteristic (ROC) curve (AUC) of 0.772 (95% CI, 0.712-0.833). The Hosmer-Lemeshow test confirmed the model's excellent fit (p = 0.47), and the calibration curve demonstrated consistent performance. Furthermore, decision curve analysis (DCA) underscored a substantial net benefit across the risk range of 13% to 85%, reaffirming the nomogram's reliability through rigorous internal validation. CONCLUSION: We have formulated a highly reliable nomogram that provides valuable assistance to clinical practitioners in preoperatively assessing the likelihood of perineural invasion (PNI) among colorectal cancer (CRC) patients. This tool holds significant potential in offering guidance for treatment strategy formulation.

Preoperative prediction of lymphovascular and perineural invasion in gastric cancer using spectral computed tomography imaging and machine learning.

BACKGROUND: Lymphovascular invasion (LVI) and perineural invasion (PNI) are important prognostic factors for gastric cancer (GC) that indicate an increased risk of metastasis and poor outcomes. Accurate preoperative prediction of LVI/PNI status could help clinicians identify high-risk patients and guide treatment decisions. However, prior models using conventional computed tomography (CT) images to predict LVI or PNI separately have had limited accuracy. Spectral CT provides quantitative enhancement parameters that may better capture tumor invasion. We hypothesized that a predictive model combining clinical and spectral CT parameters would accurately preoperatively predict LVI/PNI status in GC patients. AIM: To develop and test a machine learning model that fuses spectral CT parameters and clinical indicators to predict LVI/PNI status accurately. METHODS: This study used a retrospective dataset involving 257 GC patients (training cohort, n = 172; validation cohort, n = 85). First, several clinical indicators, including serum tumor markers, CT-TN stages and CT-detected extramural vein invasion (CT-EMVI), were extracted, as were quantitative spectral CT parameters from the delineated tumor regions. Next, a two-step feature selection approach using correlation-based methods and information gain ranking inside a 10-fold cross-validation loop was utilized to select informative clinical and spectral CT parameters. A logistic regression (LR)-based nomogram model was subsequently constructed to predict LVI/PNI status, and its performance was evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS: In both the training and validation cohorts, CT T3-4 stage, CT-N positive status, and CT-EMVI positive status are more prevalent in the LVI/PNI-positive group and these differences are statistically significant (P < 0.05). LR analysis of the training group showed preoperative CT-T stage, CT-EMVI, single-energy CT values of 70 keV of venous phase (VP-70 keV), and the ratio of standardized iodine concentration of equilibrium phase (EP-NIC) were independent influencing factors. The AUCs of VP-70 keV and EP-NIC were 0.888 and 0.824, respectively, which were slightly greater than those of CT-T and CT-EMVI (AUC = 0.793, 0.762). The nomogram combining CT-T stage, CT-EMVI, VP-70 keV and EP-NIC yielded AUCs of 0.918 (0.866-0.954) and 0.874 (0.784-0.936) in the training and validation cohorts, which are significantly higher than using each of single independent factors (P < 0.05). CONCLUSION: The study found that using portal venous and EP spectral CT parameters allows effective preoperative detection of LVI/PNI in GC, with accuracy boosted by integrating clinical markers.

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.

Clinical significance of location of perineural cancer invasion detected on prostate needle core biopsy.

The clinical impact of site-specific perineural invasion (PNI) in prostate cancer remains poorly understood. We compared radical prostatectomy findings and oncologic outcomes in 434 patients with single-site PNI on systematic sextant biopsy. PNI was present in the right apex (n = 62; 14%), right mid (n = 70; 16%), right base (n = 89; 21%), left apex (n = 64; 15%), left mid (n = 58; 13%), and left base (n = 91; 21%). There were no significant differences in biopsy or prostatectomy findings, when comparing apex vs. mid vs. base PNI. Univariate analysis revealed that apex-localized PNI was associated with a significantly higher risk of progression, compared with base (P = 0.037) or mid/base (P = 0.024) PNI. Multivariable analysis showed that apex-localized PNI was an independent risk factor for progression (hazard ratio 2.049, P = 0.002). Among biopsies demonstrating PNI at one sextant site, apex-localized PNI is independently associated with poorer prognosis, though not worse histopathologic features on prostatectomy, compared with mid or base PNI.

Mapping functional to morphological variation reveals the basis of regional extracellular matrix subversion and nerve invasion in pancreatic cancer.

Intratumor morphological heterogeneity of pancreatic ductal adenocarcinoma (PDAC) predicts clinical outcomes but is only partially understood at the molecular level. To elucidate the gene expression programs underpinning intratumor morphological variation in PDAC, we investigated and deconvoluted at single cell level the molecular profiles of histologically distinct clusters of PDAC cells. We identified three major morphological and functional variants that co-exist in varying proportions in all PDACs, display limited genetic diversity, and are associated with a distinct organization of the extracellular matrix: a glandular variant with classical ductal features; a transitional variant displaying abortive ductal structures and mixed endodermal and myofibroblast-like gene expression; and a poorly differentiated variant lacking ductal features and basement membrane, and showing neuronal lineage priming. Ex vivo and in vitro evidence supports the occurrence of dynamic transitions among these variants in part influenced by extracellular matrix composition and stiffness and associated with local, specifically neural, invasion.