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Gene Expression Regulation, Neoplastic

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Unsupervised machine learning-based stratification and immune deconvolution of liver hepatocellular carcinoma.

BMC cancer
BACKGROUND: Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer and a leading cause of cancer-related deaths globally. The tumour microenvironment (TME) influences treatment response and prognosis, yet its heterogeneity remains ...

Endometrial tumorigenesis involves epigenetic plasticity demarcating non-coding somatic mutations and 3D-genome alterations.

Genome biology
BACKGROUND: The incidence and mortality of endometrial cancer (EC) is on the rise. Eighty-five percent of ECs depend on estrogen receptor alpha (ERα) for proliferation, but little is known about its transcriptional regulation in these tumors.

Predicting breast cancer prognosis based on a novel pathomics model through CHEK1 expression analysis using machine learning algorithms.

PloS one
BACKGROUND: Checkpoint kinase 1 (CHEK1) is often overexpressed in solid tumors. Nonetheless, the prognostic significance of CHEK1 in breast cancer (BrC) remains unclear. This study used pathomics leverages machine learning to predict BrC prognosis ba...

Development of a prognostic model for osteosarcoma based on macrophage polarization-related genes using machine learning: implications for personalized therapy.

Clinical and experimental medicine
While neoadjuvant chemotherapy combined with surgical resection has improved the prognosis for patients with osteosarcoma, its impact on metastatic and recurrent cases remains limited. Immunotherapy is emerging as a promising alternative. However, th...

Multi-dimensional characterization of cellular states reveals clinically relevant immunological subtypes and therapeutic vulnerabilities in ovarian cancer.

Journal of translational medicine
BACKGROUND: Diverse cell types and cellular states in the tumor microenvironment (TME) are drivers of biological and therapeutic heterogeneity in ovarian cancer (OV). Characterization of the diverse malignant and immunology cellular states that make ...

Transcriptomics-based exploration of ubiquitination-related biomarkers and potential molecular mechanisms in laryngeal squamous cell carcinoma.

BMC medical genomics
BACKGROUND: One of the most common and prevalent cancers is laryngeal squamous cell carcinoma (LSCC), which poses a great threat to the life and health of the patient. Nonetheless, it has been demonstrated that ubiquitination is crucial for the devel...

Integrating Machine Learning and Bulk and Single-Cell RNA Sequencing to Decipher Diverse Cell Death Patterns for Predicting the Prognosis of Neoadjuvant Chemotherapy in Breast Cancer.

International journal of molecular sciences
Breast cancer (BRCA) continues to pose a serious risk to women's health worldwide. Neoadjuvant chemotherapy (NAC) is a critical treatment strategy. Nevertheless, the heterogeneity in treatment outcomes necessitates the identification of reliable biom...

Machine learning and single-cell analysis uncover distinctive characteristics of CD300LG within the TNBC immune microenvironment: experimental validation.

Clinical and experimental medicine
Investigating the essential function of CD300LG within the tumor microenvironment in triple-negative breast cancer (TNBC). Transcriptomic and single-cell data from TNBC were systematically collected and integrated. Four machine learning algorithms we...

Feasibility of machine learning-based modeling and prediction to assess osteosarcoma outcomes.

Scientific reports
Osteosarcoma, an aggressive bone malignancy predominantly affecting children and adolescents, is characterized by a poor prognosis and high mortality rates. The development of reliable prognostic tools is critical for advancing personalized treatment...