Development and validation of a novel predictive model for postpancreatectomy hemorrhage using lasso-logistic regression: an international multicenter observational study of 9,631 pancreatectomy patients.

BACKGROUND: Hemorrhage following pancreatectomy represents a grave complication, exerting a significant impact on patient prognosis. The formulation of a precise predictive model for postpancreatectomy hemorrhage risk holds substantial importance in enhancing surgical safety and improving patient outcomes. MATERIALS AND METHODS: This study utilized the patient cohort from the American College of Surgeons National Surgical Quality Improvement Program database, who underwent pancreatectomy between 2014 and 2017 (n=5779), as the training set to establish the Lasso-logistic model. For external validation, a patient cohort (n=3852) from the Chinese National Multicenter Database of Pancreatectomy Patients, who underwent the procedure between 2014 and 2020, was employed. A predictive nomogram for postpancreatectomy hemorrhage was developed, and polynomial equations were extracted. The performance of the predictive model was assessed through the receiver operating characteristic curve, calibration curve, and decision curve analysis. RESULTS: In the training and validation cohorts, 9.0% (520/5779) and 8.5% (328/3852) of patients, respectively, experienced postpancreatectomy hemorrhage. Following selection via lasso and logistic regression, only nine predictive factors were identified as independent risk factors associated with postpancreatectomy hemorrhage. These included five preoperative indicators (BMI, ASA ≥3, preoperative obstructive jaundice, chemotherapy within 90 days before surgery, and radiotherapy within 90 days before surgery), two intraoperative indicators (total operation time, vascular resection), and two postoperative indicators (postoperative septic shock, pancreatic fistula). The new model demonstrated high predictive accuracy, with an area under the receiver operating characteristic curve of 0.87 in the external validation cohort. Its predictive performance significantly surpassed that of the previous five postpancreatectomy hemorrhage risk prediction models (P<0.001, likelihood ratio test). CONCLUSION: The Lasso-logistic predictive model we developed, constructed from nine rigorously selected variables, accurately predicts the risk of PPH. It has the potential to significantly enhance the safety of pancreatectomy surgeries and improve patient outcomes.

Expression, prognostic value and mechanism of SP100 family in pancreatic adenocarcinoma.

BACKGROUND: Pancreatic adenocarcinoma (PAAD) is one of the most aggressive malignancies with a very poor prognosis. Exploring more therapeutic targets and prognostic biomarkers is of great significance to improve the prognosis of PAAD patients. Increasing evidence supports that the speckled protein (SP) 100 family is associated with human cancer and immune disorders. However, the function of the SP100 family members in PAAD is still unclear. METHODS: R, Cytoscape, cBioPortal, and other software and online databases were used to comprehensively analyze the expression characteristics, prognostic value, and oncogenic mechanism of the SP100 family in PAAD. RESULTS: The high expression of SP100 family members in PAAD was significantly correlated with poor clinicopathological features and poor prognosis of PAAD patients. Mechanistically, TP53 mutations were significantly associated with the expression levels of the SP100 family members, which were significantly coexpressed with M6A methylation regulators and were activated in multiple oncogenic pathways, including the EMT pathways. Moreover, we found that their expression levels were significantly correlated with the sensitivity of multiple traditional chemotherapeutic drugs. CONCLUSION: The SP100 family is closely related to the occurrence and development of PAAD and can be used as a new biomarker and therapeutic target for patients with PAAD.

Protocadherin-1 serves as a prognostic biomarker and promotes pancreatic cancer progression by suppressing CD8+ T cell infiltration through CCL5-CCR5 axis.

Previous studies have shown that Protocadherins (PCDHs) enhance tumor proliferation, invasion, and metastasis; yet their role in pancreatic cancer (PC) progression and the tumor immune microenvironment remains unclear. This study aims to elucidate the role of PCDH1 in different cancer types, with a particular focus on its impact on immune suppression in PC. Utilizing data from TCGA, GTEx, and Gent2 databases, we assessed the expression of PCDH1 across various cancer types. The prognostic value of PCDH1 was demonstrated through Cox regression, Kaplan-Meier analysis, and ROC curve, while its relationship with gene mutations, tumor mutational burden (TMB), immune cell infiltration, and other clinical factors was investigated using Spearman correlation. Furthermore, the effect of PCDH1 on PC malignancy was experimentally validated by a series of in vitro and in vivo assays. Our results show a significant upregulation of PCDH1 in various tumor types, which is associated with poor prognosis, suggesting its potential application as an independent prognostic biomarker. Notably, in PC, PCDH1 exhibited significant associations with gene mutations, TMB, and immune cell infiltration. Clinical validations revealed a correlation between high PCDH1 expression and poor prognosis, coupled with a low level of CD8+ T cell infiltration. Furthermore, both in vitro and in vivo experiments confirmed the role of PCDH1 in promoting PC cell proliferation and migration while inhibiting CD8+ T cell recruitment through its modulation of CCL5-CCR5 axis. In conclusion, PCDH1 regulates the proliferation and migration of PC cells as well as CD8+ T cell infiltration in PC. PCDH1 may serve as a prognostic biomarker in multiple tumor types.

Prognostic value, immune signature and molecular mechanisms of the SUMO family in pancreatic adenocarcinoma.

Background: Pancreatic adenocarcinoma (PAAD) has a high degree of malignancy and a very poor prognosis, and the 5-year overall survival rate of patients is approximately 7%. To improve the prognosis of patients with PAAD, a more comprehensive and in-depth study of the pathogenesis of PAAD and the identification of new diagnostic markers and treatment targets are urgently needed. Increasing evidence supports that the small ubiquitin-like modifier (SUMO) family is closely related to the occurrence and development of a variety of cancers. However, the function of the SUMO family in PAAD is not clear, and related research is very scarce. Methods: R, Cytoscape, cBioPortal, and other software and online databases were used to comprehensively analyze the expression characteristics, prognostic value, and oncogenic mechanism of the SUMO family in PAAD. Results: SUMO family members are highly expressed in PAAD, and high expression of SUMO family members is significantly associated with poor clinicopathological features and poor prognosis in PAAD patients. In addition, SUMO family members are significantly coexpressed with M6A methylation regulators and various oncogenes and play an activating role in various oncogenic pathways, including EMT. Furthermore, it is worth noting that the close association between SUMO family members and TP53 mutation status and the negative regulatory effect of SUMO1/2 on PAAD immunity may represent the potential mechanism by which SUMO family members promote the development of PAAD. Moreover, the coexpression characteristics of SUMO family members and a variety of cancer-promoting immune checkpoint genes, as well as the positive correlation between SUMO4 expression level and the sensitivity of various targeted or chemotherapeutic drugs, including gemcitabine, paclitaxel, and doxorubicin, suggest future clinical directions of this study. Conclusion: The SUMO family is closely related to the occurrence and development of PAAD and can be used as a new biomarker and therapeutic target for patients with PAAD.

A Comprehensive Risk Assessment and Stratification Model of Papillary Thyroid Carcinoma Based on the Autophagy-Related LncRNAs.

Background: Papillary thyroid carcinoma (PTC) is one of the most common malignant carcinomas in the endocrine system, and it has a growing incidence worldwide. Despite the development of diagnosis and treatment modalities for thyroid carcinoma, the outcome remains uncertain. Autophagy participates in the process of cancer invasion, malignancy, metastasis, and drug resistance. Emerging research has shown that long noncoding RNAs (lncRNAs) play an important role in the process of different types of cancers. However, the interaction between the process of autophagy and lncRNA and the value of autophagy-related lncRNA for risk assessment, prediction of drug sensitivity, and prognosis prediction in PTC patients remains unknown. Materials and Methods: We screened 1,283 autophagy-related lncRNAs and identified 144 lncRNAs with prognostic value in The Cancer Genome Atlas (TCGA) cohorts. Univariate and multivariate Cox regression analyses were used to establish the prognosis-related autophagy-related lncRNA risk classification consisting of 10 lncRNAs to indicate the level of risk, according to which the patients were grouped into high-risk group and low risk-group. Results: The high-risk group had dramatically worse overall survival compared with the low-risk group. Cox regression analysis was performed to confirm the independent prognostic value of the autophagy-related lncRNA risk stratification, and the time-dependent receiver operating characteristic curves of the risk stratification were 0.981 (1 year), 0.906 (3 years), and 0.963 (5 years). LncRNA CRNDE (LINC00180) is overexpressed in the tumor, and its high expression matched with poorer survival state. So, we chose it for further experiment. Finally, knockdown of the CRNDE in PTC increased the sensitivity to sorafenib. Conclusion: Collectively, we successfully established a novel risk stratification for PTC based on the expression profiles of autophagy-related lncRNAs.