AIMC Topic: Biomarkers, Tumor

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Integrating machine learning and experimental validation identifies a post-translational modification gene signature for prognosis and treatment response in breast cancer.

Scientific reports
Breast cancer (BC) is the most prevalent malignancy among women, and the steadily increasing disease burden has garnered considerable global attention. Post-translational modifications (PTMs) are critical in the initiation and progression of BC. This...

Acute myeloid leukemia risk stratification in younger and older patients through transcriptomic machine learning models.

Scientific reports
Acute Myeloid Leukemia (AML) is a genetically and clinically heterogeneous disease that can develop at any age. While AML incidence increases with age and distinct genetic alterations are observed in younger versus older patients, current classificat...

DCN, NPM3 and SULF1 are hub genes related to vasculogenic mimicry in lung adenocarcinoma.

Journal of cancer research and clinical oncology
AIM: Vasculogenic mimicry (VM), a process in which cancer cells form endothelial cell-independent vascular networks, is a hallmark of tumor aggressiveness in lung adenocarcinoma (LUAD) and supports tumor growth and metastasis. This study aims to iden...

Preoperative plasma ceramide profiling coupled with machine learning accurately predicts recurrence of hepatocellular carcinoma after resection.

Lipids in health and disease
BACKGROUND: Accurate stratification of recurrence risk after curative resection remains a critical challenge in the management of hepatocellular carcinoma (HCC). Dysregulated ceramide (CER) metabolism has been implicated in HCC progression and relaps...

Beyond single biomarkers: multi-omics strategies to predict immunotherapy outcomes in blood cancers.

Clinical and experimental medicine
Immunotherapy has revolutionized hematologic cancer treatment, yet responses remain unpredictable due to primary resistance, relapse, and life-threatening toxicities. Conventional biomarkers fail to capture the complexity of tumor-immune interactions...

Development of a diagnostic model for ovarian cancer based on machine learning algorithms and functional analysis of key biomarker SOX17.

Journal of ovarian research
BACKGROUND: Ovarian cancer (OC) demonstrates the poorest prognosis among gynecological malignancies, with five-year survival rates below 45%, primarily due to late-stage diagnosis. To address this challenge, we systematically identified OC-specific d...

Functional biomaterials and machine learning approaches for phenotyping heterogeneous tumor cells and extracellular vesicles.

Biomaterials science
Heterogeneity in cancer is known to be a contributor to the formation of metastatic lesions, poor prognosis, and ultimately undermines therapeutic efficacy. This same tumor heterogeneity is reflected in circulating tumor cells (CTCs) and tumor derive...

Construction and validation of an anoikis-related prognostic model for lung adenocarcinoma based on bulk and single-cell transcriptomic data.

PloS one
Lung adenocarcinoma (LUAD) is a highly aggressive lung cancer with poor prognosis due to lack of reliable biomarkers. Resistance to anoikis drives tumor progression and metastasis. This study aims to develop and validate an anoikis-related prognostic...

Entropy-Driven Nucleic Acid Amplifier Based on Spatial Confinement as a "Booster" for Detection of Extracellular Vesicle MicroRNAs to Diagnose Gastric Cancer and Monitor Therapeutic Response.

Analytical chemistry
Gastric cancer (GC) continues to pose a significant global health burden with persistent diagnostic challenges, especially in the detection of early-stage GC. Herein, a strand displacement reaction-mediated nucleic acid amplifier based on the spatial...

An innovative approach for predicting prostate cancer Gleason grading: machine learning-based fusion of multimodal ultrasound, clinical and laboratory indicators.

European journal of medical research
BACKGROUND: Prostate cancer is a common malignancy among elderly males with a growing incidence. While prostate biopsy remains the gold standard for diagnosis, this invasive procedure is poorly tolerated by some patients. The Gleason grade group (GGG...