The indicators for rapid assessment of the severity of acute cholangitis remain highly debated. Therefore, this study aimed to evaluate the efficacy of various inflammatory and immune-nutritional markers in predicting the severity of acute cholangitis. The prognostic roles of the following markers were investigated: Systemic Immune-Inflammatory Index (SII), Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), Albumin (Alb), and Prognostic Nutritional Index (PNI). A total of 139 patients with acute cholangitis were included in the study. The inflammatory and immune-nutritional markers with better predictive efficacy were selected to construct a combined predictive score. According to the survival ROC curve analysis, the combined NLR and PNI score, termed PNS, demonstrated the best prognostic performance with an AUC of 0.853. Multivariable survival analysis identified the following independent prognostic factors: PNS (p = 0.010) and Prothrombin Time (PT) (p = 0.003). The results indicate that PNS = 2 is associated with a higher incidence of severe cholangitis.

Background: Pancreatic cancer is a common malignant tumor. Multiple studies have shown that procollagen lysyl-hydroxylase (PLOD) family genes were closely related to tumor progression and metastasis in a variety of human cancers. This study aimed to explore the prognosis and biological role of PLOD family genes in pancreatic adenocarcinoma (PAAD). Methods: GEPIA, GEO, HPA, CCLE, Kaplan–Meier plotter, cBioPortal, LinkedOmics, DAVID6.8, STRING, and TIMER were employed to determine the prognostic values and biological function of PLOD family members in PAAD. Results: The mRNA and protein expression patterns of PLOD family members were noticeably up-regulated in PAAD compared with normal tissues. PLOD family gene expression was also up-regulated in pancreatic cancer cell lines. PLOD1 was correlated with histological and pathological grades of pancreatic cancer. PLOD2 was related to histological grade. The high expression of PLOD1-2 was correlated with the poor overall survival rate and relapse-free survival rate in patients with PAAD. Additionally, PLODs showed high sensitivity and specificity in distinguishing pancreatic cancer from normal tissues. Through the functional enrichment analysis of PLOD-related genes in PAAD, we found that PLODs were enriched in collagen fiber tissue structure, lysine degradation, and collagen biosynthesis. Pathway analysis confirmed that PLODs regulated the proliferation, migration, and metastasis of pancreatic cancer through the RalGEF-Ral signaling pathway. Furthermore, the level of expression of PLOD1-2 was positively correlated with the activity of tumor-infiltrating immune cells, including CD8+T cells, neutrophils, macrophages, and dendritic cells. The level of expression of PLOD3 was inversely correlated with the level of infiltration of CD8+T cells. PLOD1 and PLOD2 were highly expressed in pancreatic cancer tissues with TP53 and KRAS mutations, respectively. However, the level of expression of PLOD3 in SMAD4 wild-type pancreatic cancer was increased. Conclusion: The findings showed that individual PLOD genes or PLOD family genes could be potential prognostic biomarkers for PAAD.

BACKGROUND The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are novel inflammatory indicators that can be used to predict the severity and prognosis of various diseases. We categorize acute pancreatitis by etiology into acute biliary pancreatitis (ABP) and hypertriglyceridemia-induced acute pancreatitis (HTGP). AIM To investigate the clinical significance of NLR and PLR in assessing persistent organ failure (POF) in HTGP and ABP. METHODS A total of 1450 patients diagnosed with acute pancreatitis (AP) for the first time at Shanxi Bethune Hospital between January 2012 and January 2023 were enrolled. The patients were categorized into two groups according to the etiology of AP: ABP in 530 patients and HTGP in 241 patients. We collected and compared the clinical data of the patients, including NLR, PLR, and AP prognostic scoring systems, within 48 h of hospital admission. RESULTS The NLR (9.1 vs 6.9, P < 0.001) and PLR (203.1 vs 160.5, P < 0.001) were significantly higher in the ABP group than in the HTGP group. In the HTGP group, both NLR and PLR were significantly increased in patients with severe AP and those with a SOFA score ≥ 3. Likewise, in the ABP group, NLR and PLR were significantly elevated in patients with severe AP, modified computed tomography severity index score ≥ 4, Japanese Severity Score ≥ 3, and modified Marshall score ≥ 2. Moreover, NLR and PLR showed predictive value for the development of POF in both the ABP and HTGP groups. CONCLUSION NLR and PLR vary between ABP and HTGP, are strongly associated with AP prognostic scoring systems, and have predictive potential for the occurrence of POF in both ABP and HTGP.

Background and Aims: Lenvatinib is recognized as a first-line therapy for inoperable hepatocellular carcinoma (HCC) patients. Growing evidence indicates that the lenvatinib resistance can be acquired in HCC cells via kinase rewiring. Approach and Results: We established acquired lenvatinib resistance organoids and HCC cell lines. NIMA-related coiled-coil kinase 7 (NEK7) was identified as an HCC lenvatinib acquired resistance gene by kinase CRISPR–Cas9 genetic screen. Functional analyses demonstrate that NEK7 enhanced lenvatinib resistance in HCC and NEK7 knock down or knock out display the anti-tumor effects in acquired lenvatinib HCC cells and organoids. Mechanistically, NEK7 binds to EGFR, leading to the phosphorylation of EGFR (Endothelial growth factor receptor) specifically at the serine 1070 residue, which contributes to the activation of MAPK (Mitogen-activated protein kinase) and PI3K/AKT (Phosphoinositide 3-kinase/Akt) signaling pathways. Consistently, designed inhibitory peptides targeting domain from amino acids 979 to 1099 were proved to inhibit phosphorylation of EGFR S1070 site and therapeutically inhibit anti-tumor of acquired lenvatinib resistance HCC. Conclusions: Our results unveil insights into the acquired lenvatinib resistance mechanism that NEK7 phosphorylates EGFR at S1070 to promote acquired lenvatinib resistance in HCC. Export

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.

Liver cancer is one of the most common malignant tumors in the world, and its incidence and mortality are increasing year by year. The prognosis of liver cancer depends on the stage of liver cancer, the treatment method, the liver function, and individual differences. The prognosis of liver cancer mainly worsens with the progression of the stage. The prediction and staging system of liver cancer prognosis plays a very important role in the outcome of liver cancer prognosis, providing some guidance for clinical practice and bringing benefits for patients. This article reports on the prediction models and staging systems that have been applied in the field of liver cancer in the past 5 years, objectively analyzes the advantages and disadvantages, applicable population of each model and staging system, and searches for other patient and clinical characteristics that need to be considered for successfully establishing a prediction model, aiming to improve the specificity, sensitivity, and accuracy of liver cancer prediction and increase the overall survival rate of liver cancer.