AIMC Topic: Tumor Microenvironment

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Recognition of molecular clusters and a novel prognostic signature based on natural killer cell-related genes in skin cutaneous melanoma.

World journal of surgical oncology
BACKGROUND: Skin cutaneous melanoma (SKCM) is the third most common type of cutaneous malignant tumor with a poor prognosis. This research aimed to recognize molecular clusters and develop a novel prognostic signature based on natural killer (NK) cel...

Machine learning integration of bulk and single-cell RNA-seq data reveals glycolytic heterogeneity in colorectal cancer.

Medical oncology (Northwood, London, England)
As one of the most prevalent malignancies worldwide, colorectal cancer (CRC) exhibits a strong metabolic dependency on glycolysis, which fuels tumor expansion and shapes an immunosuppressive microenvironment. Despite its clinical significance, the re...

MZB1-Driven Endoplasmic reticulum stress model as a predictor of breast cancer progression and survival.

Functional & integrative genomics
Endoplasmic reticulum (ER) stress and its associated unfolded protein response (UPR) have been demonstrated to play a crucial role in cancer's progression, but their prognostic significance in breast cancer (BC) remains unclear. In this study, a reli...

Deep learning-based spatial analysis on tumor and immune cells of pathology images predicts MIBC prognosis.

PloS one
OBJECTIVE: Muscle-invasive bladder cancer (MIBC) is a highly aggressive disease with a poor prognosis. This study aims to explore the correlation between the spatial distribution of lymphocyte aggregates and the prognosis of MIBC using deep learning.

Unveiling the role of coagulation-related genes in acute myeloid leukemia prognosis and immune microenvironment through machine learning.

European journal of medical research
BACKGROUND: Acute Myeloid Leukemia (AML) is a highly heterogeneous hematologic malignancy influenced by various factors affecting prognosis. Recently, the role of coagulation-related genes in tumor biology has garnered increasing attention. This stud...

Machine learning derived development and validation of extracellular matrix related signature for predicting prognosis in adolescents and young adults glioma.

Scientific reports
The mortality rates have been increasing for glioma in adolescents and young adults (AYAs, aged 15-39 years). However, current biomarkers for clinical assessment in AYAs glioma are limited, prompting the urgent need for identifying ideal prognostic s...

Identifying ferroptosis-related genes in lung adenocarcinoma using random walk with restart in the PPI network.

Scientific reports
Lung adenocarcinoma (LUAD), the most common non-small cell lung cancer subtype, often presents with subtle early symptoms leading to delayed diagnosis. Ferroptosis, a cell death process associated with iron metabolism dysregulation, has been linked t...

Identification of prognostic genes related to T cell proliferation in papillary thyroid cancer based on single-cell RNA sequencing and bulk RNA sequencing data.

Clinical and experimental medicine
Papillary thyroid carcinoma (PTC) is the main pathological subtype of thyroid cancer. Given the strong association between T cells and PTC, this study focused on the prognostic value and potential molecular mechanisms of T cell proliferation-related ...