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 indivi...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 preoperative 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.展开更多
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 predictio...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 deci-sions.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.展开更多
Perineural invasion(PNI),a particularly insidious form of tumor metastasis distinct from hematogenous or lymphatic spread,has the capacity to extend well beyond the primary tumor site,infiltrating distant regions devoi...Perineural invasion(PNI),a particularly insidious form of tumor metastasis distinct from hematogenous or lymphatic spread,has the capacity to extend well beyond the primary tumor site,infiltrating distant regions devoid of lymphatic or vascular structures.PNI often heralds a decrease in patient survival rates and is recognized as an indicator of an unfavorable prognosis across a variety of cancers.Despite its clinical significance,the underlying molecular mechanisms of PNI remain elusive,complicating the development of specific and efficacious diagnostic and therapeutic strategies.In the realm of cancer research,non-coding RNAs(ncRNAs)have attracted considerable attention due to their multifaceted roles and cancer-specific expression profiles,positioning them as promising candidates for applications in cancer diagnostics,prognostics,and treatment.Among the various types of ncRNAs,microRNAs(miRNAs),long non-coding RNAs(lncRNAs),and circular RNAs(circRNAs)have emerged as influential players in PNI.Their involvement is increasingly recognized as a contributing factor to tumor progression and therapeutic resistance.Our study synthesizes and explores the diverse functions and mechanisms of ncRNAs in relation to PNI in cancer.This comprehensive review aims to shed light on cutting-edge perspectives that could pave the way for innovative diagnostic and therapeutic approaches to address the challenges posed by PNI in oncology.展开更多
BACKGROUND The presence of perineural invasion(PNI)in patients with rectal cancer(RC)is associated with significantly poorer outcomes.However,traditional diagnostic modalities have many limitations.AIM To develop a de...BACKGROUND The presence of perineural invasion(PNI)in patients with rectal cancer(RC)is associated with significantly poorer outcomes.However,traditional diagnostic modalities have many limitations.AIM To develop a deep learning radiomics stacking nomogram model to predict preoperative PNI status in patients with RC.METHODS We recruited 303 RC patients and separated them into the training(n=242)and test(n=61)datasets on an 8:2 scale.A substantial number of deep learning and hand-crafted radiomics features of primary tumors were extracted from the arterial and venous phases of computed tomography(CT)images.Four machine learning models were used to predict PNI status in RC patients:support vector machine,k-nearest neighbor,logistic regression,and multilayer perceptron.The stacking nomogram was created by combining optimal machine learning models for the arterial and venous phases with predicting clinical variables.RESULTS With an area under the curve(AUC)of 0.964[95%confidence interval(CI):0.944-0.983]in the training dataset and an AUC of 0.955(95%CI:0.900-0.999)in the test dataset,the stacking nomogram demonstrated strong performance in predicting PNI status.In the training dataset,the AUC of the stacking nomogram was greater than that of the arterial support vector machine(ASVM),venous SVM,and CT-T stage models(P<0.05).Although the AUC of the stacking nomogram was greater than that of the ASVM in the test dataset,the difference was not particularly noticeable(P=0.05137).CONCLUSION The developed deep learning radiomics stacking nomogram was effective in predicting preoperative PNI status in RC patients.展开更多
BACKGROUND Significant correlation between lymphatic,microvascular,and perineural invasion(LMPI)and the prognosis of pancreatic neuroendocrine tumors(PENTs)was confirmed by previous studies.There was no previous study...BACKGROUND Significant correlation between lymphatic,microvascular,and perineural invasion(LMPI)and the prognosis of pancreatic neuroendocrine tumors(PENTs)was confirmed by previous studies.There was no previous study reported the relationship between magnetic resonance imaging(MRI)parameters and LMPI.AIM To determine the feasibility of using preoperative MRI of the pancreas to predict LMPI in patients with non-functioning PENTs(NFPNETs).METHODS A total of 61 patients with NFPNETs who underwent MRI scans and lymphadenectomy from May 2011 to June 2018 were included in this retrospective study.The patients were divided into group 1(n=34,LMPI negative)and group 2(n=27,LMPI positive).The clinical characteristics and qualitative MRI features were collected.In order to predict LMPI status in NF-PNETs,a multivariate logistic regression model was constructed.Diagnostic performance was evaluated by calculating the receiver operator characteristic(ROC)curve with area under ROC,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV)and accuracy.RESULTS There were significant differences in the lymph node metastasis stage,tumor grade,neuron-specific enolase levels,tumor margin,main pancreatic ductal dilatation,common bile duct dilatation,enhancement pattern,vascular and adjacent tissue involvement,synchronous liver metastases,the long axis of the largest lymph node,the short axis of the largest lymph node,number of the lymph nodes with short axis>5 or 10 mm,and tumor volume between two groups(P<0.05).Multivariate analysis showed that tumor margin(odds ratio=11.523,P<0.001)was a predictive factor for LMPI of NF-PNETs.The area under the receiver value for the predictive performance of combined predictive factors was 0.855.The sensitivity,specificity,PPV,NPV and accuracy of the model were 48.1%(14/27),97.1%(33/34),97.1%(13/14),70.2%(33/47)and 0.754,respectively.CONCLUSION Using preoperative MRI,ill-defined tumor margins can effectively predict LMPI in patients with NF-PNETs.展开更多
AIM: To investigate midkine (MK) and syndecan-3 protein expression in pancreatic cancer by immunohistochemistry, and to analyze their correlation with clinicopathological features, perineural invasion, and prognosis.
AIM To investigate the relationship between autophagy and perineural invasion(PNI), clinical features, and prognosis in patients with pancreatic cancer. METHODS Clinical and pathological data were retrospectively coll...AIM To investigate the relationship between autophagy and perineural invasion(PNI), clinical features, and prognosis in patients with pancreatic cancer. METHODS Clinical and pathological data were retrospectively collected from 109 patients with pancreatic ductal adenocarcinoma who underwent radical resection at the First Affiliated Hospital of Zhengzhou University from January 2011 to August 2016. Expression levels of the autophagy-related protein microtubuleassociated protein 1 A/1 B-light chain 3(LC3) and PNI marker ubiquitin carboxy-terminal hydrolase(UCH) in pancreatic cancer tissues were detected by immunohistochemistry. The correlations among LC3 expression, PNI, and clinical pathological features in pancreatic cancer were analyzed. The patients were followed for further survival analysis. RESULTS In 109 cases of pancreatic cancer, 68.8%(75/109) had evidence of PNI and 61.5%(67/109) had high LC3 expression. PNI was associated with lymph node metastasis, pancreatitis, and CA19-9 levels(P < 0.05). LC3 expression was related to lymph node metastasis(P < 0.05) and was positively correlated with neural invasion(P < 0.05, r = 0.227). Multivariate logistic regression analysis indicated that LC3 expression, lymph node metastasis, pancreatitis, and CA19-9 level were factors that influenced neural invasion, whereas only neural invasion itself was an independent factor for high LC3 expression. Univariate analysis showed that LC3 expression, neural invasion, and CA19-9 level were related to the overall survival of pancreatic cancer patients(P < 0.05). Multivariate COX regression analysis indicated that PNI and LC3 expression were independent risk factors for poor prognosis in pancreatic cancer(P < 0.05). CONCLUSION PNI in patients with pancreatic cancer is positively related to autophagy. Neural invasion and LC3 expression are independent risk factors for pancreatic cancer with a poor prognosis.展开更多
BACKGROUND Perineural invasion(PNI),as a key pathological feature of tumor spread,has emerged as an independent prognostic factor in patients with rectal cancer(RC).The preoperative stratification of RC patients accor...BACKGROUND Perineural invasion(PNI),as a key pathological feature of tumor spread,has emerged as an independent prognostic factor in patients with rectal cancer(RC).The preoperative stratification of RC patients according to PNI status is beneficial for individualized treatment and improved prognosis.However,the preoperative evaluation of PNI status is still challenging.AIM To establish a radiomics model for evaluating PNI status preoperatively in RC patients.METHODS This retrospective study enrolled 303 RC patients in a single institution from March 2018 to October 2019.These patients were classified as the training cohort(n=242)and validation cohort(n=61)at a ratio of 8:2.A large number of intraand peritumoral radiomics features were extracted from portal venous phase images of computed tomography(CT).After deleting redundant features,we tested different feature selection(n=6)and machine-learning(n=14)methods to form 84 classifiers.The best performing classifier was then selected to establish Rad-score.Finally,the clinicoradiological model(combined model)was developed by combining Rad-score with clinical factors.These models for predicting PNI were compared using receiver operating characteristic curve(ROC)analysis and area under the ROC curve(AUC).RESULTS One hundred and forty-four of the 303 patients were eventually found to be PNIpositive.Clinical factors including CT-reported T stage(cT),N stage(cN),and carcinoembryonic antigen(CEA)level were independent risk factors for predicting PNI preoperatively.We established Rad-score by logistic regression analysis after selecting features with the L1-based method.The combined model was developed by combining Rad-score with cT,cN,and CEA.The combined model showed good performance to predict PNI status,with an AUC of 0.828[95%confidence interval(CI):0.774-0.873]in the training cohort and 0.801(95%CI:0.679-0.892)in the validation cohort.For comparison of the models,the combined model achieved a higher AUC than the clinical model(cT+cN+CEA)achieved(P<0.001 in the training cohort,and P=0.045 in the validation cohort).CONCLUSION The combined model incorporating Rad-score and clinical factors can provide an individualized evaluation of PNI status and help clinicians guide individualized treatment of RC patients.展开更多
AIM To detect the expression of pleiotrophin(PTN) and N-syndecan in pancreatic cancer and analyze their association with tumor progression and perineural invasion(PNI).METHODS An orthotopic mouse model of pancreatic c...AIM To detect the expression of pleiotrophin(PTN) and N-syndecan in pancreatic cancer and analyze their association with tumor progression and perineural invasion(PNI).METHODS An orthotopic mouse model of pancreatic cancer was created by injecting tumor cells subcapsularly in a root region of the pancreas beneath the spleen. Pancreatic cancer tissues were taken from 36 mice that survived for more than 90 d. PTN and N-syndecan proteins were detected by immunohistochemistry and analyzed for their correlation with pathological features, PNI, and prognosis.RESULTS The expression rates of PTN and N-syndecan proteinswere 66.7% and 61.1%, respectively, in cancer tissue. PTN and N-syndecan expression was associated with PNI(P = 0.019 and P = 0.032, respectively). High PTN expression was closely associated with large bloody ascites(P = 0.009), liver metastasis(P = 0.035), and decreased survival time(P = 0.022). N-syndecan expression was significantly associated with tumor size(P = 0.025), but not with survival time(P = 0.539). CONCLUSION High PTN and N-syndecan expression was closely associated with metastasis and poor prognosis, suggesting that they may promote tumor progression and PNI in the orthotopic mouse model of pancreatic cancer.展开更多
BACKGROUND:Cholangiocarcinoma,a type of malignant tumor,originates from epithelial cells of the bile duct.Perineural invasion is common path for cholangiocarcinoma metastasis,and it is highly correlated with postopera...BACKGROUND:Cholangiocarcinoma,a type of malignant tumor,originates from epithelial cells of the bile duct.Perineural invasion is common path for cholangiocarcinoma metastasis,and it is highly correlated with postoperative recurrence and poor prognosis.It has been reported that muscarinic acetylcholine receptor M3(mAChR M3) is widely expressed in digestive tract cancer,and may play an important role in the proliferation,differentiation,transformation and carcinogenesis of tumors.This study was to explore the effect of mAChR M3 on the growth of cholangiocarcinoma cells in vitro and provide a new approach to the pathogenesis and treatment of cholangiocarcinoma.METHODS:Streptavidin-biotin complex immunohistochemistry was carried out to assess the expression of mAChR M3 in surgical specimens of cholangiocarcinomas(40 cases) and normal bile duct tissues(9),as well as to investigate nerve infiltration.The cholangiocarcinoma cells were treated with different concentrations of selective M-receptor agonist pilocarpine and M-receptor blocker atropine sulfate to induce changes in cell proliferation.The experimental data were analyzed by the Chi-square test.RESULTS:The strongly-positive expression rate of mAChR M3 was much higher in poorly-differentiated(69%,9/13) than in well-and moderately-differentiated cholangiocarcinomas(30%,8/27)(χ 2 =5.631,P<0.05).The strongly-positive mAChR M3 expression rate in hilar cholangiocarcinoma(50%,14/28) was higher than that in cholangiocarcinomas from the middle and lower common bile duct(25%,3/12)(χ 2 =2.148,P<0.05).Cholangiocarcinomas with distant metastasis had a stronglypositive expression rate(75%,9/12),which was much higher than those without distant metastasis(29%,8/28)(χ 2 =7.410,P<0.01).The absorbance value in the pilocarpine+atropine group was significantly higher than the corresponding value in the pilocarpine group.CONCLUSIONS:The expression of mAChR M3 is influenced by the extent of differentiation,distant metastasis and the site of cholangiocarcinoma.It also plays a key role in the proliferation and metastasis of cholangiocarcinoma.展开更多
Objective： To develop and validate a radiomics prediction model for individualized prediction of perineural invasion（PNI） in colorectal cancer（CRC）.Methods： After computed tomography（CT） radiomics features ext...Objective： To develop and validate a radiomics prediction model for individualized prediction of perineural invasion（PNI） in colorectal cancer（CRC）.Methods： After computed tomography（CT） radiomics features extraction, a radiomics signature was constructed in derivation cohort（346 CRC patients）. A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen（CEA） level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation（separate from the cohort used to build the model） was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram.Results： The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell＇s concordance index（c-index）： 0.817; 95% confidence interval（95% CI）： 0.811–0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination（c-index： 0.803; 95% CI： 0.794–0.812）.Conclusions： Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.展开更多
BACKGROUND Cachexia is responsible for the low quality of life in pancreatic adenocarcinoma(PDAC).The rapid disease progression and patient deterioration seems related to perineural invasion,but the relationship betwe...BACKGROUND Cachexia is responsible for the low quality of life in pancreatic adenocarcinoma(PDAC).The rapid disease progression and patient deterioration seems related to perineural invasion,but the relationship between cachexia and perineural invasion for the evolution of the disease has been rarely studied.As perineural invasion is difficult to be highlighted,a biomarker such as the neurotrophic factor Midkine(MK)which promotes the neuronal differentiation and the cell migration could be helpful.Also,Activin(ACV)has been described as cachexia related to PDAC.However,their role for assessing and predicting the disease course in daily practice is not known.AIM To assess the relationship between perineural invasion and cachexia and their biomarkers,MK and ACV,respectively,and their prognostic value.METHODS This study included prospectively enrolled patients with proven adenocarcinoma and a matched group of controls without any malignancies.Patients with other causes of malnutrition were excluded.The plasma levels of ACV and MK were analyzed using western blotting and were correlated with the clinicopathological features and survival data.These results were validated by immunohistochemical analyses of the pancreatic tumor tissue of the patients included in the study and a supplementary group of surgically resected specimens from patients with a benign disease.RESULTS The study comprised 114 patients with PDAC,125 controls and a supplementary group of 14 benign pancreatic tissue samples.ACV and MK were both overexpressed more frequently in the plasma of patients with PDAC than in the controls(63% vs 32% for ACV,P<0.001;47%vs 16%for MK,P<0.001),with similar levels in pancreatic tissue the MK protein expression was closely related to the advanced clinical stage(P=0.006),the presence of metastasis(P=0.04),perineural invasion(P=0.03)and diabetes(P=0.002),but with no influence on survival.No correlation between clinicopathological factors and ACV expression was noted.Cachexia,present in 19%of patients,was unrelated to ACV or MK level.Higher ACV expression was associated with a shorter survival(P=0.008).CONCLUSION The MK was a biomarker of perineural invasion,associated with tumor stage and diabetes,but without prognostic value as ACV.Cachexia was unrelated to perineural invasion,ACV level or survival.展开更多
BACKGROUND Rectal cancer(RC)is one of the most common diagnosed cancers,and one of the major causes of cancer-related death nowadays.Majority of the current guidelines rely on TNM classification regarding therapy regi...BACKGROUND Rectal cancer(RC)is one of the most common diagnosed cancers,and one of the major causes of cancer-related death nowadays.Majority of the current guidelines rely on TNM classification regarding therapy regiments,however recent studies suggest that additional histopathological findings could affect the disease course.AIM To determine whether perineural invasion alone or in combination with lymphovascular invasion have an effect on 5-years overall survival(OS)of RC patients.METHODS A prospective study included newly diagnosed stage I-III RC patients treated and followed at the Digestive Surgery Clinic,Clinical Center of Serbia,between the years of 2014–2016.All patients had their diagnosis histologically confirmed in accordance with both TMN and Dukes classification.In addition,the patient’s demographics,surgical details,postoperative pathological details,differentiation degree and their correlation with OS was investigated.RESULTS Of 245 included patients with stage Ⅰ-Ⅲ RC,lymphovascular invasion(LVI)was identified in 92 patients(38%),whereas perineural invasion(PNI)was present in 46 patients(19%).Using Kaplan-Meier analysis for overall survival rate,we have found that both LVI and PNI were associated with lower survival rates(P<0.01).Moreover when Cox multiple regression model was used,LVI,PNI,older age,male gender were predictors of poor prognosis(HR=5.49;95%CI:2.889-10.429;P<0.05).CONCLUSION LVI and PNI were significant factors predicting worse prognosis in early and intermediate RC patients,hence more aggressive therapy should be reserved for these patients after curative resection.展开更多
Pancreatic Cancer （PCa） is characterized by prominently local nerve alterations and perineural invasion （PNI）, which frequently affects the extrapancreatic nerve plexus, causing severe pain and retropancreatic tum...Pancreatic Cancer （PCa） is characterized by prominently local nerve alterations and perineural invasion （PNI）, which frequently affects the extrapancreatic nerve plexus, causing severe pain and retropancreatic tumor extension. It precludes curative resection, promotes local recurrence, and at the last negatively influences the prognosis of patients. Recent research on PNI in PCa has revealed the critical involvement of numerous nerve- or cancer cell-derived molecules in vitro and in vivo. However, the mechanisms contributing to alteration and invasion of intrapancreatic nerves and the spread of cancer cells along extrapancreatic nerves in pancreatic cancer patients are still poorly understood. This review focuses on perineural invasion in pancreatic cancer and provides an outline of the characteristics and molecular mechanisms of perineural invasion in pancreatic cancer.展开更多
Purpose: Post-operative radiotherapy (PORT) for resected cutaneous squamous cell carcinoma (CSCC) with perineural invasion (PNI) is controversial. Therefore, we conducted a survey to review treatment recommendations a...Purpose: Post-operative radiotherapy (PORT) for resected cutaneous squamous cell carcinoma (CSCC) with perineural invasion (PNI) is controversial. Therefore, we conducted a survey to review treatment recommendations among Radiation Oncologists (ROs) in the management of CSCC with PNI. Materials & Methods: In March 2011, we contacted all ROs and trainees in the US through email addresses listed in the 2009 ASTRO directory. Our web-based survey presented clinical vignettes involving Mohs micrographically resected CSCC with microscopic PNI (mPNI) or clinical PNI (cPNI). For each vignette, ROs were asked to indicate if PORT was appropriate and to further specify the dose and volume to treat. Results: Three hundred fifty two responses were completed and analyzed. The majority of ROs (72%) had over 10 years of post residency experience. 64% of the sampled ROs had a special interest in treating head and neck cancers, and 64% treated 4 or more cases per year. Approximately 95% recommended PORT for cPNI whereas 59% recommended PORT for mPNI. Post residency experience (10+ yrs vs. <10 yrs) was associated with a greater propensity to recommend PORT for mPNI (48% vs. 30%, p = 0.005) and for mPNI of deep subcutaneous non-named nerve involvement (80% vs. 60%, p = 0.001). ROs treating 8 or more cases per year (vs. <7) were more likely to recommend PORT for mPNI in immunocompromised patients (74% vs. 57%, p = 0.01). Conclusions: Our study demonstrates significant variability among ROs in the management of CSCC with mPNI. For cases of cPNI, an overwhelming majority recommended PORT. In cases of mPNI, there was no consensus for recommending PORT, although experienced practitioners had a lower threshold for offering treatment. These results indicate the need for prospective clinical studies to clarify the role of PORT in CSCC patients with mPNI.展开更多
This study was designed to define possible preoperative predictors of positive surgical margin after laparoscopic radical prostatectomy. We retrospectively analyzed the records of 296 patients with prostate cancer dia...This study was designed to define possible preoperative predictors of positive surgical margin after laparoscopic radical prostatectomy. We retrospectively analyzed the records of 296 patients with prostate cancer diagnosed by prostate biopsy, and eventually treated with laparoscopic radical prostatectomy. The prognostic impact of age, prostate volume, preoperative prostate-specific antigen, biopsy Gleason score, maximum percentage tumor per core, number of positive cores, biopsy perineurat invasion, capsule invasion on imaging, and tumor laterality on surgical margin was assessed. The overall positive surgical margin rate was 29.1%. Gleason score, number of positive cores, perineural invasion, tumor laterality in the biopsy specimen, and prostate volume significantly correlated with risk of positive surgical margin by univariate analysis （P 〈 0.05）. Gleason score （odds ratio [OR] = 2.286, 95% confidence interval [95% CI] = 1.431-3.653, P= 0.001）, perineural invasion （OR = 4.961, 95% CI = 2.656-9.270, P〈 0.001）, and number of positive cores （OR = 4.403, 95% CI = 1.878-10.325, P = 0.001） were independent predictors of positive surgical margin at the multivariable logistic regression analysis. Patients with perineural invasion, higher biopsy Gleason scores and/or a large number of positive cores in biopsy pathology had more possibility of capsule invasion. The positive surgical margin rate in patients with capsule invasion （49.5%） was much higher than that with localized disease （17.8%）. In contrast, prostate volume showed a protective effect against positive surgical margin （OR = 0.572, 95% CI = 0.346-0.945, P = 0.029）. Gleason score, perineural invasion, and number of positive cores in the biopsy specimen were preoperative independent predictors of positive surgical margin after laparoscopic radical prostatectomy while prostate volume was a protective factor against positive surgical margin.展开更多
Background：Perineural invasion （PNI） is a histopathological characteristic of pancreatic cancer （PanCa）.The aim of this study was to observe the treatment effect of continuous low-dose-rate （CLDR） irradiation t...Background：Perineural invasion （PNI） is a histopathological characteristic of pancreatic cancer （PanCa）.The aim of this study was to observe the treatment effect of continuous low-dose-rate （CLDR） irradiation to PNI and assess the PNI-related pain relief caused by iodine-125 （125I） seed implantation.Methods：The in vitro PNI model established by co-culture with dorsal root ganglion （DRG） and cancer cells was interfered under 2 and 4 Gy of 125I seeds CLDR irradiation.The orthotopic models of PNI were established,and 125I seeds were implanted in tumor.The PNI-related molecules were analyzed.In 30 patients with panCa,the pain relief was assessed using a visual analog scale （VAS）.Pain intensity was measured before and 1 week,2 weeks,and 1,3,and 6 months after 125I seed implantation.Results：The co-culture of DRG and PanCa cells could promote the growth of PanCa cells and DRG neurites.In co-culture groups,the increased number of DRG neurites and pancreatic cells in radiation group was significantly less.In orthotopic models,the PNI-positive rate in radiation and control group was 3/11 and 7/11;meanwhile,the degrees of PNI between radiation and control groups was significant difference （P 〈 0.05）.At week 2,the mean VAS pain score in patients decreased by 50% and significantly improved than the score at baseline （P 〈 0.05）.The pain scores were lower in all patients,and the pain-relieving effect was retained about 3 months.Conclusions：The CLDR irradiation could inhibit PNI of PanCa with the value of further study.The CLDR irradiation could do great favor in preventing local recurrence and alleviating pain.展开更多
Pancreatic ductal adenocarcinoma(PDAC)is an aggressive malignant disease with a unique tumor microenvironment surrounded by an interlaced network of cancer and noncancerous cells.Recent works have revealed that the dy...Pancreatic ductal adenocarcinoma(PDAC)is an aggressive malignant disease with a unique tumor microenvironment surrounded by an interlaced network of cancer and noncancerous cells.Recent works have revealed that the dynamic interaction between cancer cells and neuronal cells leads to perineural invasion(PNI),a clinical pathological feature of PDAC.The formation and function of PNI are dually regulated by molecular(e.g.,involving neurotrophins,cytokines,chemokines,and neurotransmitters),metabolic(e.g.,serine metabolism),and cellular mechanisms(e.g.,involving Schwann cells,stromal cells,T cells,and macrophages).Such integrated mechanisms of PNI not only support tumor development,growth,invasion,and metastasis but also mediate the formation of pain,all of which are closely related to poor disease prognosis in PDAC.This review details the modulation,signaling pathways,detection,and clinical relevance of PNI and highlights the opportunities for further exploration that may benefit PDAC patients.展开更多
This letter comments on the article that developed and tested a machine learning model that predicts lymphovascular invasion/perineural invasion status by combining clinical indications and spectral computed tomograph...This letter comments on the article that developed and tested a machine learning model that predicts lymphovascular invasion/perineural invasion status by combining clinical indications and spectral computed tomography characteristics accurately.We review the research content,methodology,conclusions,strengths and weaknesses of the study,and introduce follow-up research to this work.展开更多
文摘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 preoperative 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.
基金Supported by Science and Technology Project of Fujian Province,No.2022Y0025.
文摘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 deci-sions.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.
基金Foundation of Henan Educational Committee,Grant Number 22A310024Natural Science Foundation for Young Teachers’Basic Research of Zhengzhou University,Grant Number JC202035025.
文摘Perineural invasion(PNI),a particularly insidious form of tumor metastasis distinct from hematogenous or lymphatic spread,has the capacity to extend well beyond the primary tumor site,infiltrating distant regions devoid of lymphatic or vascular structures.PNI often heralds a decrease in patient survival rates and is recognized as an indicator of an unfavorable prognosis across a variety of cancers.Despite its clinical significance,the underlying molecular mechanisms of PNI remain elusive,complicating the development of specific and efficacious diagnostic and therapeutic strategies.In the realm of cancer research,non-coding RNAs(ncRNAs)have attracted considerable attention due to their multifaceted roles and cancer-specific expression profiles,positioning them as promising candidates for applications in cancer diagnostics,prognostics,and treatment.Among the various types of ncRNAs,microRNAs(miRNAs),long non-coding RNAs(lncRNAs),and circular RNAs(circRNAs)have emerged as influential players in PNI.Their involvement is increasingly recognized as a contributing factor to tumor progression and therapeutic resistance.Our study synthesizes and explores the diverse functions and mechanisms of ncRNAs in relation to PNI in cancer.This comprehensive review aims to shed light on cutting-edge perspectives that could pave the way for innovative diagnostic and therapeutic approaches to address the challenges posed by PNI in oncology.
文摘BACKGROUND The presence of perineural invasion(PNI)in patients with rectal cancer(RC)is associated with significantly poorer outcomes.However,traditional diagnostic modalities have many limitations.AIM To develop a deep learning radiomics stacking nomogram model to predict preoperative PNI status in patients with RC.METHODS We recruited 303 RC patients and separated them into the training(n=242)and test(n=61)datasets on an 8:2 scale.A substantial number of deep learning and hand-crafted radiomics features of primary tumors were extracted from the arterial and venous phases of computed tomography(CT)images.Four machine learning models were used to predict PNI status in RC patients:support vector machine,k-nearest neighbor,logistic regression,and multilayer perceptron.The stacking nomogram was created by combining optimal machine learning models for the arterial and venous phases with predicting clinical variables.RESULTS With an area under the curve(AUC)of 0.964[95%confidence interval(CI):0.944-0.983]in the training dataset and an AUC of 0.955(95%CI:0.900-0.999)in the test dataset,the stacking nomogram demonstrated strong performance in predicting PNI status.In the training dataset,the AUC of the stacking nomogram was greater than that of the arterial support vector machine(ASVM),venous SVM,and CT-T stage models(P<0.05).Although the AUC of the stacking nomogram was greater than that of the ASVM in the test dataset,the difference was not particularly noticeable(P=0.05137).CONCLUSION The developed deep learning radiomics stacking nomogram was effective in predicting preoperative PNI status in RC patients.
基金Supported by Beijing Hospitals Authority Youth Program,No.QML20231103.
文摘BACKGROUND Significant correlation between lymphatic,microvascular,and perineural invasion(LMPI)and the prognosis of pancreatic neuroendocrine tumors(PENTs)was confirmed by previous studies.There was no previous study reported the relationship between magnetic resonance imaging(MRI)parameters and LMPI.AIM To determine the feasibility of using preoperative MRI of the pancreas to predict LMPI in patients with non-functioning PENTs(NFPNETs).METHODS A total of 61 patients with NFPNETs who underwent MRI scans and lymphadenectomy from May 2011 to June 2018 were included in this retrospective study.The patients were divided into group 1(n=34,LMPI negative)and group 2(n=27,LMPI positive).The clinical characteristics and qualitative MRI features were collected.In order to predict LMPI status in NF-PNETs,a multivariate logistic regression model was constructed.Diagnostic performance was evaluated by calculating the receiver operator characteristic(ROC)curve with area under ROC,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV)and accuracy.RESULTS There were significant differences in the lymph node metastasis stage,tumor grade,neuron-specific enolase levels,tumor margin,main pancreatic ductal dilatation,common bile duct dilatation,enhancement pattern,vascular and adjacent tissue involvement,synchronous liver metastases,the long axis of the largest lymph node,the short axis of the largest lymph node,number of the lymph nodes with short axis>5 or 10 mm,and tumor volume between two groups(P<0.05).Multivariate analysis showed that tumor margin(odds ratio=11.523,P<0.001)was a predictive factor for LMPI of NF-PNETs.The area under the receiver value for the predictive performance of combined predictive factors was 0.855.The sensitivity,specificity,PPV,NPV and accuracy of the model were 48.1%(14/27),97.1%(33/34),97.1%(13/14),70.2%(33/47)and 0.754,respectively.CONCLUSION Using preoperative MRI,ill-defined tumor margins can effectively predict LMPI in patients with NF-PNETs.
基金Supported by National Natural Science Foundation of China,No.U1204819the Health Science and Technology Innovation Talents Program of Henan Province,No.4203
文摘AIM: To investigate midkine (MK) and syndecan-3 protein expression in pancreatic cancer by immunohistochemistry, and to analyze their correlation with clinicopathological features, perineural invasion, and prognosis.
基金Supported by the National Natural Science Foundation of China,No.U1504815
文摘AIM To investigate the relationship between autophagy and perineural invasion(PNI), clinical features, and prognosis in patients with pancreatic cancer. METHODS Clinical and pathological data were retrospectively collected from 109 patients with pancreatic ductal adenocarcinoma who underwent radical resection at the First Affiliated Hospital of Zhengzhou University from January 2011 to August 2016. Expression levels of the autophagy-related protein microtubuleassociated protein 1 A/1 B-light chain 3(LC3) and PNI marker ubiquitin carboxy-terminal hydrolase(UCH) in pancreatic cancer tissues were detected by immunohistochemistry. The correlations among LC3 expression, PNI, and clinical pathological features in pancreatic cancer were analyzed. The patients were followed for further survival analysis. RESULTS In 109 cases of pancreatic cancer, 68.8%(75/109) had evidence of PNI and 61.5%(67/109) had high LC3 expression. PNI was associated with lymph node metastasis, pancreatitis, and CA19-9 levels(P < 0.05). LC3 expression was related to lymph node metastasis(P < 0.05) and was positively correlated with neural invasion(P < 0.05, r = 0.227). Multivariate logistic regression analysis indicated that LC3 expression, lymph node metastasis, pancreatitis, and CA19-9 level were factors that influenced neural invasion, whereas only neural invasion itself was an independent factor for high LC3 expression. Univariate analysis showed that LC3 expression, neural invasion, and CA19-9 level were related to the overall survival of pancreatic cancer patients(P < 0.05). Multivariate COX regression analysis indicated that PNI and LC3 expression were independent risk factors for poor prognosis in pancreatic cancer(P < 0.05). CONCLUSION PNI in patients with pancreatic cancer is positively related to autophagy. Neural invasion and LC3 expression are independent risk factors for pancreatic cancer with a poor prognosis.
基金This study was reviewed and approved by the Ethics Committee of West China Hospital of Sichuan University(Approved No.1159).
文摘BACKGROUND Perineural invasion(PNI),as a key pathological feature of tumor spread,has emerged as an independent prognostic factor in patients with rectal cancer(RC).The preoperative stratification of RC patients according to PNI status is beneficial for individualized treatment and improved prognosis.However,the preoperative evaluation of PNI status is still challenging.AIM To establish a radiomics model for evaluating PNI status preoperatively in RC patients.METHODS This retrospective study enrolled 303 RC patients in a single institution from March 2018 to October 2019.These patients were classified as the training cohort(n=242)and validation cohort(n=61)at a ratio of 8:2.A large number of intraand peritumoral radiomics features were extracted from portal venous phase images of computed tomography(CT).After deleting redundant features,we tested different feature selection(n=6)and machine-learning(n=14)methods to form 84 classifiers.The best performing classifier was then selected to establish Rad-score.Finally,the clinicoradiological model(combined model)was developed by combining Rad-score with clinical factors.These models for predicting PNI were compared using receiver operating characteristic curve(ROC)analysis and area under the ROC curve(AUC).RESULTS One hundred and forty-four of the 303 patients were eventually found to be PNIpositive.Clinical factors including CT-reported T stage(cT),N stage(cN),and carcinoembryonic antigen(CEA)level were independent risk factors for predicting PNI preoperatively.We established Rad-score by logistic regression analysis after selecting features with the L1-based method.The combined model was developed by combining Rad-score with cT,cN,and CEA.The combined model showed good performance to predict PNI status,with an AUC of 0.828[95%confidence interval(CI):0.774-0.873]in the training cohort and 0.801(95%CI:0.679-0.892)in the validation cohort.For comparison of the models,the combined model achieved a higher AUC than the clinical model(cT+cN+CEA)achieved(P<0.001 in the training cohort,and P=0.045 in the validation cohort).CONCLUSION The combined model incorporating Rad-score and clinical factors can provide an individualized evaluation of PNI status and help clinicians guide individualized treatment of RC patients.
基金Supported by the National Natural Science Foundation of China,No.U1204819Health Science and Technology Innovation Talents Program of Henan Province,No.4203
文摘AIM To detect the expression of pleiotrophin(PTN) and N-syndecan in pancreatic cancer and analyze their association with tumor progression and perineural invasion(PNI).METHODS An orthotopic mouse model of pancreatic cancer was created by injecting tumor cells subcapsularly in a root region of the pancreas beneath the spleen. Pancreatic cancer tissues were taken from 36 mice that survived for more than 90 d. PTN and N-syndecan proteins were detected by immunohistochemistry and analyzed for their correlation with pathological features, PNI, and prognosis.RESULTS The expression rates of PTN and N-syndecan proteinswere 66.7% and 61.1%, respectively, in cancer tissue. PTN and N-syndecan expression was associated with PNI(P = 0.019 and P = 0.032, respectively). High PTN expression was closely associated with large bloody ascites(P = 0.009), liver metastasis(P = 0.035), and decreased survival time(P = 0.022). N-syndecan expression was significantly associated with tumor size(P = 0.025), but not with survival time(P = 0.539). CONCLUSION High PTN and N-syndecan expression was closely associated with metastasis and poor prognosis, suggesting that they may promote tumor progression and PNI in the orthotopic mouse model of pancreatic cancer.
文摘BACKGROUND:Cholangiocarcinoma,a type of malignant tumor,originates from epithelial cells of the bile duct.Perineural invasion is common path for cholangiocarcinoma metastasis,and it is highly correlated with postoperative recurrence and poor prognosis.It has been reported that muscarinic acetylcholine receptor M3(mAChR M3) is widely expressed in digestive tract cancer,and may play an important role in the proliferation,differentiation,transformation and carcinogenesis of tumors.This study was to explore the effect of mAChR M3 on the growth of cholangiocarcinoma cells in vitro and provide a new approach to the pathogenesis and treatment of cholangiocarcinoma.METHODS:Streptavidin-biotin complex immunohistochemistry was carried out to assess the expression of mAChR M3 in surgical specimens of cholangiocarcinomas(40 cases) and normal bile duct tissues(9),as well as to investigate nerve infiltration.The cholangiocarcinoma cells were treated with different concentrations of selective M-receptor agonist pilocarpine and M-receptor blocker atropine sulfate to induce changes in cell proliferation.The experimental data were analyzed by the Chi-square test.RESULTS:The strongly-positive expression rate of mAChR M3 was much higher in poorly-differentiated(69%,9/13) than in well-and moderately-differentiated cholangiocarcinomas(30%,8/27)(χ 2 =5.631,P<0.05).The strongly-positive mAChR M3 expression rate in hilar cholangiocarcinoma(50%,14/28) was higher than that in cholangiocarcinomas from the middle and lower common bile duct(25%,3/12)(χ 2 =2.148,P<0.05).Cholangiocarcinomas with distant metastasis had a stronglypositive expression rate(75%,9/12),which was much higher than those without distant metastasis(29%,8/28)(χ 2 =7.410,P<0.01).The absorbance value in the pilocarpine+atropine group was significantly higher than the corresponding value in the pilocarpine group.CONCLUSIONS:The expression of mAChR M3 is influenced by the extent of differentiation,distant metastasis and the site of cholangiocarcinoma.It also plays a key role in the proliferation and metastasis of cholangiocarcinoma.
基金supported by the National Key Research and Development Program of China (No. 2017YFC1309100)the National Natural Scientific Foundation of China (No. 81771912, 81701782 and 81601469)
文摘Objective： To develop and validate a radiomics prediction model for individualized prediction of perineural invasion（PNI） in colorectal cancer（CRC）.Methods： After computed tomography（CT） radiomics features extraction, a radiomics signature was constructed in derivation cohort（346 CRC patients）. A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen（CEA） level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation（separate from the cohort used to build the model） was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram.Results： The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell＇s concordance index（c-index）： 0.817; 95% confidence interval（95% CI）： 0.811–0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination（c-index： 0.803; 95% CI： 0.794–0.812）.Conclusions： Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.
基金partially funded by the“Iuliu Hatieganu”University of Medicine and Pharmacy,Cluj-Napoca,through the Doctoral Research Project-2015(No.7690/36/15.04.2016)
文摘BACKGROUND Cachexia is responsible for the low quality of life in pancreatic adenocarcinoma(PDAC).The rapid disease progression and patient deterioration seems related to perineural invasion,but the relationship between cachexia and perineural invasion for the evolution of the disease has been rarely studied.As perineural invasion is difficult to be highlighted,a biomarker such as the neurotrophic factor Midkine(MK)which promotes the neuronal differentiation and the cell migration could be helpful.Also,Activin(ACV)has been described as cachexia related to PDAC.However,their role for assessing and predicting the disease course in daily practice is not known.AIM To assess the relationship between perineural invasion and cachexia and their biomarkers,MK and ACV,respectively,and their prognostic value.METHODS This study included prospectively enrolled patients with proven adenocarcinoma and a matched group of controls without any malignancies.Patients with other causes of malnutrition were excluded.The plasma levels of ACV and MK were analyzed using western blotting and were correlated with the clinicopathological features and survival data.These results were validated by immunohistochemical analyses of the pancreatic tumor tissue of the patients included in the study and a supplementary group of surgically resected specimens from patients with a benign disease.RESULTS The study comprised 114 patients with PDAC,125 controls and a supplementary group of 14 benign pancreatic tissue samples.ACV and MK were both overexpressed more frequently in the plasma of patients with PDAC than in the controls(63% vs 32% for ACV,P<0.001;47%vs 16%for MK,P<0.001),with similar levels in pancreatic tissue the MK protein expression was closely related to the advanced clinical stage(P=0.006),the presence of metastasis(P=0.04),perineural invasion(P=0.03)and diabetes(P=0.002),but with no influence on survival.No correlation between clinicopathological factors and ACV expression was noted.Cachexia,present in 19%of patients,was unrelated to ACV or MK level.Higher ACV expression was associated with a shorter survival(P=0.008).CONCLUSION The MK was a biomarker of perineural invasion,associated with tumor stage and diabetes,but without prognostic value as ACV.Cachexia was unrelated to perineural invasion,ACV level or survival.
文摘BACKGROUND Rectal cancer(RC)is one of the most common diagnosed cancers,and one of the major causes of cancer-related death nowadays.Majority of the current guidelines rely on TNM classification regarding therapy regiments,however recent studies suggest that additional histopathological findings could affect the disease course.AIM To determine whether perineural invasion alone or in combination with lymphovascular invasion have an effect on 5-years overall survival(OS)of RC patients.METHODS A prospective study included newly diagnosed stage I-III RC patients treated and followed at the Digestive Surgery Clinic,Clinical Center of Serbia,between the years of 2014–2016.All patients had their diagnosis histologically confirmed in accordance with both TMN and Dukes classification.In addition,the patient’s demographics,surgical details,postoperative pathological details,differentiation degree and their correlation with OS was investigated.RESULTS Of 245 included patients with stage Ⅰ-Ⅲ RC,lymphovascular invasion(LVI)was identified in 92 patients(38%),whereas perineural invasion(PNI)was present in 46 patients(19%).Using Kaplan-Meier analysis for overall survival rate,we have found that both LVI and PNI were associated with lower survival rates(P<0.01).Moreover when Cox multiple regression model was used,LVI,PNI,older age,male gender were predictors of poor prognosis(HR=5.49;95%CI:2.889-10.429;P<0.05).CONCLUSION LVI and PNI were significant factors predicting worse prognosis in early and intermediate RC patients,hence more aggressive therapy should be reserved for these patients after curative resection.
文摘Pancreatic Cancer （PCa） is characterized by prominently local nerve alterations and perineural invasion （PNI）, which frequently affects the extrapancreatic nerve plexus, causing severe pain and retropancreatic tumor extension. It precludes curative resection, promotes local recurrence, and at the last negatively influences the prognosis of patients. Recent research on PNI in PCa has revealed the critical involvement of numerous nerve- or cancer cell-derived molecules in vitro and in vivo. However, the mechanisms contributing to alteration and invasion of intrapancreatic nerves and the spread of cancer cells along extrapancreatic nerves in pancreatic cancer patients are still poorly understood. This review focuses on perineural invasion in pancreatic cancer and provides an outline of the characteristics and molecular mechanisms of perineural invasion in pancreatic cancer.
文摘Purpose: Post-operative radiotherapy (PORT) for resected cutaneous squamous cell carcinoma (CSCC) with perineural invasion (PNI) is controversial. Therefore, we conducted a survey to review treatment recommendations among Radiation Oncologists (ROs) in the management of CSCC with PNI. Materials & Methods: In March 2011, we contacted all ROs and trainees in the US through email addresses listed in the 2009 ASTRO directory. Our web-based survey presented clinical vignettes involving Mohs micrographically resected CSCC with microscopic PNI (mPNI) or clinical PNI (cPNI). For each vignette, ROs were asked to indicate if PORT was appropriate and to further specify the dose and volume to treat. Results: Three hundred fifty two responses were completed and analyzed. The majority of ROs (72%) had over 10 years of post residency experience. 64% of the sampled ROs had a special interest in treating head and neck cancers, and 64% treated 4 or more cases per year. Approximately 95% recommended PORT for cPNI whereas 59% recommended PORT for mPNI. Post residency experience (10+ yrs vs. <10 yrs) was associated with a greater propensity to recommend PORT for mPNI (48% vs. 30%, p = 0.005) and for mPNI of deep subcutaneous non-named nerve involvement (80% vs. 60%, p = 0.001). ROs treating 8 or more cases per year (vs. <7) were more likely to recommend PORT for mPNI in immunocompromised patients (74% vs. 57%, p = 0.01). Conclusions: Our study demonstrates significant variability among ROs in the management of CSCC with mPNI. For cases of cPNI, an overwhelming majority recommended PORT. In cases of mPNI, there was no consensus for recommending PORT, although experienced practitioners had a lower threshold for offering treatment. These results indicate the need for prospective clinical studies to clarify the role of PORT in CSCC patients with mPNI.
文摘This study was designed to define possible preoperative predictors of positive surgical margin after laparoscopic radical prostatectomy. We retrospectively analyzed the records of 296 patients with prostate cancer diagnosed by prostate biopsy, and eventually treated with laparoscopic radical prostatectomy. The prognostic impact of age, prostate volume, preoperative prostate-specific antigen, biopsy Gleason score, maximum percentage tumor per core, number of positive cores, biopsy perineurat invasion, capsule invasion on imaging, and tumor laterality on surgical margin was assessed. The overall positive surgical margin rate was 29.1%. Gleason score, number of positive cores, perineural invasion, tumor laterality in the biopsy specimen, and prostate volume significantly correlated with risk of positive surgical margin by univariate analysis （P 〈 0.05）. Gleason score （odds ratio [OR] = 2.286, 95% confidence interval [95% CI] = 1.431-3.653, P= 0.001）, perineural invasion （OR = 4.961, 95% CI = 2.656-9.270, P〈 0.001）, and number of positive cores （OR = 4.403, 95% CI = 1.878-10.325, P = 0.001） were independent predictors of positive surgical margin at the multivariable logistic regression analysis. Patients with perineural invasion, higher biopsy Gleason scores and/or a large number of positive cores in biopsy pathology had more possibility of capsule invasion. The positive surgical margin rate in patients with capsule invasion （49.5%） was much higher than that with localized disease （17.8%）. In contrast, prostate volume showed a protective effect against positive surgical margin （OR = 0.572, 95% CI = 0.346-0.945, P = 0.029）. Gleason score, perineural invasion, and number of positive cores in the biopsy specimen were preoperative independent predictors of positive surgical margin after laparoscopic radical prostatectomy while prostate volume was a protective factor against positive surgical margin.
基金This study was supported by the grants from the Beijing Municipal Science and Technology Commission （No. Z141107002514184）, the National Natural Science Foundation of China （No. 81272667）, and the Beijing Municipal Science and Technology Commission （No. Z151100004015213）.
文摘Background：Perineural invasion （PNI） is a histopathological characteristic of pancreatic cancer （PanCa）.The aim of this study was to observe the treatment effect of continuous low-dose-rate （CLDR） irradiation to PNI and assess the PNI-related pain relief caused by iodine-125 （125I） seed implantation.Methods：The in vitro PNI model established by co-culture with dorsal root ganglion （DRG） and cancer cells was interfered under 2 and 4 Gy of 125I seeds CLDR irradiation.The orthotopic models of PNI were established,and 125I seeds were implanted in tumor.The PNI-related molecules were analyzed.In 30 patients with panCa,the pain relief was assessed using a visual analog scale （VAS）.Pain intensity was measured before and 1 week,2 weeks,and 1,3,and 6 months after 125I seed implantation.Results：The co-culture of DRG and PanCa cells could promote the growth of PanCa cells and DRG neurites.In co-culture groups,the increased number of DRG neurites and pancreatic cells in radiation group was significantly less.In orthotopic models,the PNI-positive rate in radiation and control group was 3/11 and 7/11;meanwhile,the degrees of PNI between radiation and control groups was significant difference （P 〈 0.05）.At week 2,the mean VAS pain score in patients decreased by 50% and significantly improved than the score at baseline （P 〈 0.05）.The pain scores were lower in all patients,and the pain-relieving effect was retained about 3 months.Conclusions：The CLDR irradiation could inhibit PNI of PanCa with the value of further study.The CLDR irradiation could do great favor in preventing local recurrence and alleviating pain.
文摘Pancreatic ductal adenocarcinoma(PDAC)is an aggressive malignant disease with a unique tumor microenvironment surrounded by an interlaced network of cancer and noncancerous cells.Recent works have revealed that the dynamic interaction between cancer cells and neuronal cells leads to perineural invasion(PNI),a clinical pathological feature of PDAC.The formation and function of PNI are dually regulated by molecular(e.g.,involving neurotrophins,cytokines,chemokines,and neurotransmitters),metabolic(e.g.,serine metabolism),and cellular mechanisms(e.g.,involving Schwann cells,stromal cells,T cells,and macrophages).Such integrated mechanisms of PNI not only support tumor development,growth,invasion,and metastasis but also mediate the formation of pain,all of which are closely related to poor disease prognosis in PDAC.This review details the modulation,signaling pathways,detection,and clinical relevance of PNI and highlights the opportunities for further exploration that may benefit PDAC patients.
文摘This letter comments on the article that developed and tested a machine learning model that predicts lymphovascular invasion/perineural invasion status by combining clinical indications and spectral computed tomography characteristics accurately.We review the research content,methodology,conclusions,strengths and weaknesses of the study,and introduce follow-up research to this work.
