AIMC Topic: Biomarkers, Tumor

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Targeting INF2 with DiosMetin 7-O-β-D-Glucuronide: a new stratagem for colorectal cancer therapy.

BMC cancer
BACKGROUND AND PURPOSE: Colorectal cancer (CRC) is the third most prevalent malignancy in the gastrointestinal tract and the second leading cause of cancer-related deaths. Despite the identification of numerous biomarkers, their non-specific distribu...

Prediction of Lymph Node Metastasis in Non-Small Cell Lung Carcinoma Using Primary Tumor Somatic Mutation Data.

JCO clinical cancer informatics
PURPOSE: Lymph node metastasis (LNM) significantly affects prognosis and treatment strategies in non-small cell lung cancer (NSCLC). Current diagnostic methods, including imaging and histopathology, have limited sensitivity and specificity. This stud...

Development and validation of the Immune Profile Score (IPS), a novel multiomic algorithmic assay for stratifying outcomes in a real-world cohort of patients with advanced solid cancer treated with immune checkpoint inhibitors.

Journal for immunotherapy of cancer
BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed the oncology treatment landscape. Despite substantial improvements for some patients, the majority do not benefit from ICIs, indicating a need for predictive biomarkers to better inform...

Discovery of novel diagnostic biomarkers of hepatocellular carcinoma associated with immune infiltration.

Annals of medicine
OBJECTIVE: Diagnosis of hepatocellular carcinoma (HCC) remains challenging for clinicians. Machine learning approaches and big data analyses are viable strategies for identifying HCC diagnostic markers.

Disulfide bond-related gene signature development for bladder cancer prognosis prediction and immune microenvironment characterization.

Scientific reports
Bladder cancer is the fourth most common malignant tumor in men, with limited therapeutic biomarkers and heterogeneous responses to immunotherapy. Disulfide bond-driven cell death has emerged as a critical regulator of tumor progression and immune mi...

Immunological biomarkers and gene signatures predictive of radiotherapy resistance in non-small cell lung cancer.

Frontiers in immunology
INTRODUCTION: A significant challenge in treating non-small cell lung cancer (NSCLC) is its inherent resistance to radiation therapy, leading to poor patient prognosis. This study aimed to identify key genes influencing radiotherapy resistance in NSC...

An integrated analytical approach for biomarker discovery in esophageal cancer: Combining trace element and oxidative stress profiling with machine learning.

Journal of trace elements in medicine and biology : organ of the Society for Minerals and Trace Elements (GMS)
BACKGROUND: Early detection of esophageal squamous cell carcinoma (ESCC) significantly improves survival rates, yet reliable biochemical biomarkers for early diagnosis remain limited. The aim of this study is to identify potential early diagnostic bi...

Error Reduction in Leukemia Machine Learning Classification With Conformal Prediction.

JCO clinical cancer informatics
PURPOSE: Recent advances in machine learning have led to the development of classifiers that predict molecular subtypes of acute lymphoblastic leukemia (ALL) using RNA-sequencing (RNA-seq) data. Although these models have shown promising results, the...

Autophagy crosstalk with the immune microenvironment in chronic myeloid leukemia and serves as a biomarker for diagnosis and progression.

Frontiers in immunology
BACKGROUND: Previous studies have shown that autophagy is closely related to the occurrence, development, and treatment resistance of chronic myeloid leukemia (CML) and has dual roles in promoting cell survival and inducing cell death.

The Role of PANoptosis-Related Genes in Predicting Breast Cancer Survival and Immune Prospect.

BioMed research international
The function of PANoptosis in breast cancer (BC) remains indistinct. We constructed a nomogram model to predict the prognosis of BC to identify high-risk patients and help them receive more accurate treatment. We used Cox regression and least absol...