myCAF-derived exosomal PWAR6 accelerates CRC liver metastasis via altering glutamine availability and NK cell function in the tumor microenvironment.

Background: Liver metastasis from colorectal cancer (CRC) is a major clinical challenge that severely affects patient survival. myofibroblastic cancer-associated fibroblasts (myCAFs) are a major component of the CRC tumor microenvironment, where they contribute to tumor progression and metastasis through exosomes.

Methods: Single-cell analysis highlighted a notable increase in myCAFs in colorectal cancer liver metastases (CRLM).

GPR37 promotes colorectal cancer against ferroptosis by reprogramming lipid metabolism via p38-SCD1 axis.

Colorectal cancer (CRC) is a prevalent malignant tumor worldwide, leading to significant morbidity and disease burden. Diagnostic indicators and treatment objectives for CRC are urgently needed. This study demonstrates that GPR37, a GPCR receptor, is highly expressed in CRC.

A comprehensive overview of the molecular features and therapeutic targets in BRAF-mutant colorectal cancer.

As one of the most prevalent digestive system tumours, colorectal cancer (CRC) poses a significant threat to global human health. With the emergence of immunotherapy and target therapy, the prognosis for the majority of CRC patients has notably improved. However, the subset of patients with BRAF exon 15 p.

Exceeding the limit for microscopic image translation with a deep learning-based unified framework.

Deep learning algorithms have been widely used in microscopic image translation. The corresponding data-driven models can be trained by supervised or unsupervised learning depending on the availability of paired data. However, general cases are where the data are only roughly paired such that supervised learning could be invalid due to data unalignment, and unsupervised learning would be less ideal as the roughly paired information is not utilized.

Lung Cancer Diagnosis on Virtual Histologically Stained Tissue Using Weakly Supervised Learning.

Lung adenocarcinoma (LUAD) is the most common primary lung cancer and accounts for 40% of all lung cancer cases. The current gold standard for lung cancer analysis is based on the pathologists' interpretation of hematoxylin and eosin (H&E)-stained tissue slices viewed under a brightfield microscope or a digital slide scanner. Computational pathology using deep learning has been proposed to detect lung cancer on histology images.

Function and mechanism of MCM8 in the development and progression of colorectal cancer.

Colorectal cancer (CRC) has become a global health problem which has almost highest morbidity and mortality in all types of cancers. This study aimed to uncover the biological functions and underlying mechanism of MCM8 in the development and progression of CRC. The expression level of MCM8 was found to be upregulated in CRC tissues and significantly associated with tumor grade and patients' survival.

Improving prognosis and assessing adjuvant chemotherapy benefit in locally advanced rectal cancer with deep learning for MRI: A retrospective, multi-cohort study.

Purpose: Adjuvant therapy is recommended to minimize the risk of distant metastasis (DM) and local recurrence (LR) in patients with locally advanced rectal cancer (LARC). However, its role is controversial. We aimed to develop a pretreatment MRI-based deep learning model to predict LR, DM, and overall survival (OS) over 5 years after surgery and to identify patients benefitting from adjuvant chemotherapy (AC).

Noninvasive predictive models based on lifestyle analysis and risk factors for early-onset colorectal cancer.

Background: Colorectal cancer (CRC) incidence has increased among patients aged <50 years. Exploring high-risk factors and screening high-risk populations may help lower early-onset CRC (EO-CRC) incidence. We developed noninvasive predictive models for EO-CRC and investigated its risk factors.

Early Detection of Molecular Residual Disease and Risk Stratification for Stage I to III Colorectal Cancer via Circulating Tumor DNA Methylation.

Importance: Detection of molecular residual disease and risk stratification as early as possible may improve the treatment of patients with cancer. Efficient pragmatic tests are therefore required.

Objective: To measure circulating tumor DNA (ctDNA) with 6 DNA methylation markers in blood samples and to evaluate the association of the presence of ctDNA with colorectal cancer (CRC) recurrence throughout the disease course.

Enhanced De Novo Lipid Synthesis Mediated by FASN Induces Chemoresistance in Colorectal Cancer.

Background: Oxaliplatin is one of the most widely used chemotherapy drugs for colorectal cancer (CRC). Resistance to oxaliplatin threatens the prognosis of CRC. Since previous studies have aroused interest in fatty acid metabolism in cancer, in this study, we determined whether fatty acid biosynthesis and the related regulating mechanism contribute to oxaliplatin resistance in CRC.

PTPRO represses colorectal cancer tumorigenesis and progression by reprogramming fatty acid metabolism.

Background: Abnormal expression of protein tyrosine phosphatases (PTPs) has been reported to be a crucial cause of cancer. As a member of PTPs, protein tyrosine phosphatase receptor type O (PTPRO) has been revealed to play tumor suppressive roles in several cancers, while its roles in colorectal cancer (CRC) remains to be elucidated. Hence, we aimed to explore the roles and mechanisms of PTPRO in CRC initiation and progression.

Bulk and single-cell transcriptome profiling reveal necroptosis-based molecular classification, tumor microenvironment infiltration characterization, and prognosis prediction in colorectal cancer.

Background: Necroptosis is a new form of programmed cell death that is associated with cancer initiation, progression, immunity, and chemoresistance. However, the roles of necroptosis-related genes (NRGs) in colorectal cancer (CRC) have not been explored comprehensively.

Methods: In this study, we obtained NRGs and performed consensus molecular subtyping by "ConsensusClusterPlus" to determine necroptosis-related subtypes in CRC bulk transcriptomic data.

Ferroptosis-associated molecular classification characterized by distinct tumor microenvironment profiles in colorectal cancer.

Ferroptosis is a non-apoptotic form of cell death recognized in recent years. Nonetheless, the potential role of ferroptosis-associated genes in immune regulation and tumor microenvironment formation remains unknown. In this study, we characterized the ferroptosis-associated patterns of colorectal cancer through integrative analyses of multiple datasets with transcriptomics, genomics, and single-cell transcriptome profiling.

Development of a novel combined nomogram model integrating deep learning-pathomics, radiomics and immunoscore to predict postoperative outcome of colorectal cancer lung metastasis patients.

Limited previous studies focused on the death and progression risk stratification of colorectal cancer (CRC) lung metastasis patients. The aim of this study is to construct a nomogram model combing machine learning-pathomics, radiomics features, Immunoscore and clinical factors to predict the postoperative outcome of CRC patients with lung metastasis. In this study, a total of 103 CRC patients having metastases limited to lung and undergoing radical lung resection were identified.

GT Factor ZmGT-3b Is Associated With Regulation of Photosynthesis and Defense Response to Infection in Maize Seedling.

It is of critical importance for plants to correctly and efficiently allocate their resources between growth and defense to optimize fitness. Transcription factors (TFs) play crucial roles in the regulation of plant growth and defense response. Trihelix TFs display multifaceted functions in plant growth, development, and responses to various biotic and abiotic stresses.

Lnc-RP11-536 K7.3/SOX2/HIF-1α signaling axis regulates oxaliplatin resistance in patient-derived colorectal cancer organoids.

Background: Resistance to oxaliplatin is a major obstacle for the management of locally advanced and metastatic colon cancer (CC). Although long noncoding RNAs (lncRNAs) play key roles in CC, the relationships between lncRNAs and resistance to oxaliplatin have been poorly understood yet.

Methods: Chemo-sensitive and chemo-resistant organoids were established from colon cancer tissues of the oxaliplatin-sensitive or -resistant patients.

MTAP Deficiency-Induced Metabolic Reprogramming Creates a Vulnerability to Cotargeting Purine Synthesis and Glycolysis in Pancreatic Cancer.

Methylthioadenosine phosphorylase (MTAP) is a key enzyme associated with the salvage of methionine and adenine that is deficient in 20% to 30% of pancreatic cancer. Our previous study revealed that MTAP deficiency indicates a poor prognosis for patients with pancreatic ductal adenocarcinoma (PDAC). In this study, bioinformatics analysis of The Cancer Genome Atlas (TCGA) data indicated that PDACs with MTAP deficiency display a signature of elevated glycolysis.

Nomogram of conditional survival probability of long-term Survival for Metastatic Colorectal Cancer: A Real-World Data Retrospective Cohort Study from SEER database.

Background: Many patients with metastatic colorectal cancer (mCRC) have better prognosis than the prediction at diagnosis. Compared with invariable traditional Kaplan Meier assessment, conditional survival (CS) assessment has become a more accurate and informative assessment method to predict survival time.

Materials And Methods: Patients with mCRC between 2010 and 2015 were extracted from Surveillance, Epidemiology and End Results linked database.

Comprehensive Transcriptomic Analysis Reveals Prognostic Value of an EMT-Related Gene Signature in Colorectal Cancer.

Lymph node metastasis (LNM) is closely related to the postoperative recurrence of colorectal cancer (CRC), and greatly affects patient survival. Conducting Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA), we found that the epithelial-mesenchymal transition (EMT) signaling pathway is the signaling pathway most relevant to the process of LNM. An EMT-related gene signature was identified from a discovery dataset obtained 489 patients using LIMMA and LASSO Cox methods.