Colon Cancer

Macrophage-Induced Senescent Cancer-Associated Fibroblasts Promote SASP-Mediated Chemoresistance in Colorectal Cancer.

Cancer-associated fibroblasts (CAFs) play a crucial role in the tumor microenvironment (TME) by influencing tumor progression, metastasis, and therapy resistance. Accumulating evidence suggests that CAFs undergo senescence, which can impact their effects on the TME. Here, we developed a machine learning-based prediction model, the Cellular Senescence Prediction Model (CSPM), to accurately identify...

Radiomics Models as Tools for Predicting Genetic Mutations in Colorectal Cancer: A Systematic Review and Meta-Analysis.

BACKGROUND: The evaluation of genetic mutations is crucial for personalized therapy in colorectal cancer (CRC), but the invasive tissue biopsy is subject to sampling bias and other complications. Radiomics has emerged as a non-invasive tool to predict these mutations from standard medical images. In this systematic review and meta-analysis, we aimed to evaluate the diagnostic accuracy and methodol...

Evaluation of the Applicability of Synthetic Data in the Development of Colorectal Cancer Survival Prediction Models: External Validation of Advanced Machine Learning Models Based on National Cancer Data Center Data.

BACKGROUND: Limited data availability and privacy constraints hinder the development of robust survival prediction models for personalized treatment. ...

HyCANet: a hybrid convolutional-attention network with cross-attention fusion for lung cancer histopathological classification.

Histopathology interpretation of lung cancer involves careful examination of tissue morphology, especially differentiating benign lung tissue, adenoca...

Retrospective detail reconstruction network for mitigating shallow information loss in colorectal polyp segmentation.

Existing medical polyp segmentation networks predominantly rely on hierarchical feature representations to improve boundary delineation. However, we i...

ALDH18A1 silencing inhibits lung adenocarcinoma progression through mitochondrial dysfunction and PPAR signaling pathway activation.

BACKGROUND: Lung adenocarcinoma (LUAD) remains a prevalent malignant tumor characterized by a dismal prognosis. This study aimed to reveal potential m...

A morphology-guided ViT-CNN approach for the detection of lung and colon cancer using H&E-stained biopsy images.

The accurate categorisation of histopathological images is crucial for the reliable identification of morphologically similar cancers, including lung ...

Expression characteristics analysis, establishment of prognostic model and screening of key regulators based on selenium protein-related genes in rectal adenocarcinoma.

BACKGROUND: Selenium is an essential trace element in the human body and plays a significant role in multiple cancers. This study aims to comprehensiv...

Targeting galactose metabolic reprogramming overcomes immunotherapy resistance in KRAS-mutant lung adenocarcinoma: Integrative multi-omics and machine learning approaches.

BACKGROUND: KRAS-mutant lung adenocarcinoma (LUAD) is associated with aggressive phenotypes and therapy resistance, which highlights an urgent need to...

Diagnostic performance of machine learning models based on dual-phase 99mTc-MIBI SPECT/CT semiquantitative parameters for differentiating benign and malignant pulmonary nodules.

PURPOSE: To evaluate the diagnostic value of machine learning models based on dual-phase 99mTc-MIBI SPECT/CT semiquantitative parameters for different...

Investigating tryptophan metabolism in colorectal cancer using Single-cell RNA sequencing based on machine learning techniques.

BACKGROUND: Colorectal cancer (CRC) is characterized by genetic variation, epigenetic alterations, microenvironmental imbalance, and metabolic reprogr...

Evaluating the Accuracy of ChatGPT-4o in Addressing Complex Clinical Questions Based on NCCN Guidelines for Rectal Adenocarcinoma.

INTRODUCTION: The management of rectal adenocarcinoma requires navigation of complex, branching guideline pathways encompassing neoadjuvant sequencing...

Integrative single-cell and multi-omics analysis of ZBTB21-mediated serine metabolism in colorectal cancer: from metabolic reprogramming to immune microenvironment modulation.

BACKGROUND: Colorectal cancer (CRC) exhibits pronounced biological diversity, a feature increasingly attributed to alterations in cellular metabolic r...

Identification of exosome-related genes signature based on bioinformatics and machine learning for prognostic prediction in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a prevalent malignant tumor with increasing incidence and mortality rates worldwide. Exosomes are secretory ves...

Rethinking cancer screening in Italy: equity, performance and innovation.

OBJECTIVES: To examine the current performance of cancer screening programs in Italy, evaluate the evolving regulatory and clinical guideline framewor...

Selective state space U net for linear complexity globally coherent high resolution image segmentation.

Accurate segmentation of high-resolution images requires the simultaneous preservation of fine-grained spatial details and the modeling of long-range ...

Machine learning-driven development of a novel unfolded protein response-related gene signature for predicting lung adenocarcinoma patient prognosis.

Lung adenocarcinoma (LUAD) is the most common lung cancer histological subtype. Although the unfolded protein response (UPR) has been linked to variou...

Machine learning models using 18F-FDG PET/CT radiomics for RAS mutation prediction and prognostic stratification in colorectal cancer.

OBJECTIVE: To evaluate a machine learning (ML) model that integrates clinical data and 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG)-PET radiomic features...

Comprehensive identification of three key genes and three key DNA methylation CpG sites associated with prognosis and prediction in colon adenocarcinoma.

Colon adenocarcinoma (COAD) is a common cancer with high incidence and mortality rates worldwide. DNA methylation has a significant impact on the occu...

Pan-cancer analysis of tissue-plasma genomic concordance reveals enhanced concordance with liver metastasis and plasma clonality as predictor of poorer overall survival.

Circulating tumor DNA (ctDNA) enables noninvasive tumor genotyping, yet its concordance with tissue remains unclear. Using a 437-gene panel in 1111 pa...