IGF2BP2-related modification patterns in pancreatic cancer: A machine learning-driven approach towards personalized treatment.

Pancreatic cancer (PC) is a malignant digestive system tumor with a very poor prognosis. N6-methyladenosine (m6A) is mediated by a variety of readers and participates in important regulatory roles in PC. Based on TCGA_PAAD, ICGC_AU_PAAD, ICGC_CA_PAAD, GSE28735 and GSE62452 datasets, We mapped the multi-omics changes of m6A readers in PC and found that m6A readers, especially IGF2BP family genes, had specific changes and were significantly associated with poor prognosis. An unsupervised consensus clustering algorithm was used to explore the correlation between specific expression patterns of m6A readers in PC and enrichment pathways, tumor immunity and clinical molecular subtypes. Then, the principal component analysis (PCA) algorithm was used to quantify specific expression patterns and screen core genes. Machine learning algorithms such as Bootstrapping and RSF were used to quantify the expression patterns of core genes and construct a prognostic scoring model for PC patients. What's more, pharmacogenomic databases were used to screen sensitive drug targets and small molecule compounds for high-risk PC patients in an all-around and multi-angle way. Our study has not only provided new insights into personalized prognostication approaches, but also thrown light on integrating tailored risk stratification with precision therapy based on IGF2BP2-mediated m6A modification patterns.

A multidimensional analysis of ZW10 interacting kinetochore protein in human tumors.

ZW10 interacting kinetochore protein (ZWINT), an essential part of the kinetochore complex, plays a crucial role in maintaining genome stability by correcting improper attachments between the kinetochore and microtubules. An initial analysis of The Cancer Genome Atlas and Gene Expression Omnibus databases revealed that ZWINT is significantly expressed across a diverse range of tumor types. We subsequently investigated the influence of ZWINT on clinical outcomes and potential signaling pathways. A multidimensional analysis of ZWINT revealed significant statistical associations between ZWINT expression and clinical outcomes, as well as the E2F1 oncogenic signature. Experimental validation confirmed the increased expression of ZWINT in both pancreatic cancer cell lines and pancreatic adenocarcinoma tissues. Furthermore, our findings indicate that ZWINT promotes the proliferation of PANC-1 cells through cell cycle regulation. This comprehensive analysis of ZWINT suggests a strong correlation between its expression and various types of tumors, especially pancreatic adenocarcinoma (PAAD), indicating its potential oncogenic role. These findings enhance our understanding of the function of ZWINT in carcinogenesis.

Comprehensive analysis of COMMD10 as a novel prognostic biomarker for gastric cancer.

Background: COMMD10 has an important role in the development of certain tumors, but its relevance to gastric cancer (GC) is unclear. The purpose of this study is to investigate the difference of COMMD10 expression in gastric adenocarcinoma (STAD) and analyze the correlation between COMMD10 expression and prognosis of STAD patients. Methods: The expression levels of COMMD10 between STAD and normal tissues were explored using the The Cancer Genome Atlas (TCGA) database. In addition, the expression of COMMD10 in GC was further validated by immunohistochemistry (IHC) staining, qRT-PCR and Western blot. Dot blot experiments were used for exploring m6A expression levels in tissues with high and low COMMD10 expression. Kaplan-Meier analysis and COX regression analysis were used to explore the relationship between COMMD10 and STAD prognosis. A nomogram was constructed to predict the survival probability of STAD patients. GO and KEGG functional enrichment of COMMD10-related genes were performed. The Corrlot software package was used to analyze the correlation between COMMD10 expression levels and m6A modifications in STAD. An analysis of immune infiltration based on the CIBERSOFT and the single-sample GSEA (ssGSEA) method was performed. Results: COMMD10 expression was significantly associated with multiple cancers, including STAD in TCGA. COMMD10 expression was elevated in STAD cancer tissues compared to paracancerous tissues. COMMD10 upregulation was associated with poorer overall survival (OS), clinical stage, N stage, and primary treatment outcome in STAD. Functional enrichment of COMMD10-related genes was mainly involved in biological processes such as RNA localization, RNA splicing, RNA transport, mRNA surveillance pathways, and spliceosomes. The dot blot experiment showed that m6A levels were higher in cancer tissues with high COMMD10 expression compared with paracancerous tissues. COMMD10 was significantly correlated with most m6A-related genes. COMMD10 was involved in STAD immune cells infiltration, correlated with macrophage cells expression. Conclusion: High COMMD10 expression was significantly associated with poor prognosis in STAD patients, and its functional realization was related to m6A modification. COMMD10 involved in STAD immune infiltration.

Immune cells regulate matrix metalloproteinases to reshape the tumor microenvironment to affect the invasion, migration, and metastasis of pancreatic cancer.

This study aimed to identify author, country, institutional, and journal collaborations and assess their impact, along with knowledge base, as well as identify existing trends, and uncover emerging topics related to matrix metalloproteinase and pancreatic-cancer research. A total of 1474 Articles and reviews were obtained from the Web of Science Core Collection and analyzed by Citespace and Vosviewer. CANCER RESEARCH, CLINICAL CANCER RESEARCH, and FRONTIERS IN IMMUNOLOGY are the most influential journals. The three main aspects of research in matrix metalloproteinases-pancreatic cancer-related fields included the pathogenesis mechanism of pancreatic cancer, how matrix metalloproteinases affect the metastasis of pancreatic cancer, and what role matrix metalloproteinases play in pancreatic cancer treatment. Tumor microenvironment, pancreatic stellate cells, drug resistance, and immune cells have recently emerged as research hot spots. In the future, exploring how immune cells affect matrix metalloproteinases and reshape the tumor microenvironment may be the key to curing pancreatic cancer. This study thus offers a comprehensive overview of the matrix metalloproteinases-pancreatic cancer-related field using bibliometrics and visual methods, providing a valuable reference for researchers interested in matrix metalloproteinases-pancreatic cancer.