AIMC Topic: Gene Expression Regulation, Neoplastic

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Machine learning-driven classification and prognostic prediction of kidney renal clear cell carcinoma using APOBEC family expression signatures.

Scientific reports
Apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like (APOBEC) cytidine deaminases are a highly evolutionarily conserved protein family. Their members are closely associated with DNA damage repair and involved in the genesis and progressio...

Serum-MiR-CanPred: deep learning framework for pan-cancer classification and miRNA-targeted drug discovery.

RNA biology
Cancer diagnosis at an early stage is crucial for improving overall health outcomes. However, existing cancer diagnostic techniques are mostly invasive and tend to identify the disease only in its advanced stages. MicroRNAs (miRNAs), which are small ...

Ensemble model for neoadjuvant chemotherapy response prediction and treatment sensitivity in TNBC based on DNA replication stress signatures.

Scientific reports
Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer. Although neoadjuvant chemotherapy (NACT) has some effectiveness in TNBC, a portion of patients still do not benefit from them. The critical role of DNA replication ...

BRCAGenie: A machine learning-driven 43-gene polygenic risk score model for precision prediction of breast cancer survival.

Journal of translational medicine
BACKGROUND: Breast cancer is one of the most prevalent malignancies globally, imposing a substantial disease burden. Its inherent heterogeneity complicates prognosis and treatment, underscoring the need for accurate survival prediction models to guid...

Comprehensive analysis of coagulation-associated gene signature in bladder cancer diagnosis, prognosis, and immunotherapy.

Scientific reports
In recent years, research on the relationship between coagulation system abnormalities and tumor immunity has been widely reported. Bladder cancer (BC), as an immunogenic tumor, holds great promise in immunotherapy. The role of coagulation-related ge...

MX1 is a novel crucial prognostic and therapeutic target inducing chemoresistance in right-sided colon cancer: insights from machine learning-based multi-omics analysis.

Human genomics
BACKGROUND: Recent studies have increasingly emphasized the poorer survival outcomes and reduced treatment responses associated with right-sided colon cancer (RCC). However, the underlying molecular mechanisms remain poorly understood. This study aim...

Identification and analysis of metabolic reprogramming-related genes in triple-negative breast cancer.

Clinical and experimental medicine
Triple-negative breast cancer (TNBC) is notorious for its rapid progression, tendency to metastasize, high recurrence rates, dismal outcomes, and limited treatment options, underscoring the urgent need to uncover new biomarkers and molecular pathways...

Machine learning identifies exosome related gene signatures for early prediction of non-small cell lung cancer.

Scientific reports
Non-small cell lung cancer (NSCLC) remains a major health challenge worldwide, mainly due to the lack of effective early diagnostic biomarkers. Exosome-related genes have recently emerged as potential diagnostic markers due to their roles in tumor pr...

Programmed cell death-related genes define distinct molecular subtypes and risk profiles in hepatocellular carcinoma.

Scientific reports
Hepatocellular carcinoma (HCC) is a biologically and clinically heterogeneous malignancy, whose initiation and progression are increasingly recognized to be driven by the aberrant regulation of programmed cell death (PCD) pathways. To elucidate this ...