A machine learning-based investigation of integrin expression patterns in cancer and metastasis DOI Creative Commons
Hossain Shadman,

Saghar Gomrok,

Christopher Litle

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 12, 2025

Integrins, a family of transmembrane receptor proteins, are well known to play important roles in cancer development and metastasis. However, comprehensive understanding these has not been achieved due the complex relationships between specific integrins, types, stages progression. Publicly accessible repositories from Genotype-Tissue Expression (GTEx) The Cancer Genome Atlas (TCGA) projects provide rich datasets for exploring using machine learning (ML). In this study, integrin RNA-Seq expression data ~ 8 healthy tissues GTEx corresponding tumors TCGA were selected. Integrin was used train ML models distinguish different tissues, solid tumors, as normal tumor samples same tissue type. These can classify by origin or disease status with high accuracy, integrins essential classifiers identified. some cases, only one two needed type, type accuracy > 0.9. For example, ITGA7 alone cancerous breast tissue. Additionally, co-expression networks compared found change significantly cancer, indicating changes functional involvement cancer. metastatic further examined AURORA project Metastatic Breast (MBC), several such ITGAD, ITGA4, ITGAL, ITGA11 have lower metastases than primary tumors.

Язык: Английский

A machine learning-based investigation of integrin expression patterns in cancer and metastasis DOI Creative Commons
Hossain Shadman,

Saghar Gomrok,

Christopher Litle

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 12, 2025

Integrins, a family of transmembrane receptor proteins, are well known to play important roles in cancer development and metastasis. However, comprehensive understanding these has not been achieved due the complex relationships between specific integrins, types, stages progression. Publicly accessible repositories from Genotype-Tissue Expression (GTEx) The Cancer Genome Atlas (TCGA) projects provide rich datasets for exploring using machine learning (ML). In this study, integrin RNA-Seq expression data ~ 8 healthy tissues GTEx corresponding tumors TCGA were selected. Integrin was used train ML models distinguish different tissues, solid tumors, as normal tumor samples same tissue type. These can classify by origin or disease status with high accuracy, integrins essential classifiers identified. some cases, only one two needed type, type accuracy > 0.9. For example, ITGA7 alone cancerous breast tissue. Additionally, co-expression networks compared found change significantly cancer, indicating changes functional involvement cancer. metastatic further examined AURORA project Metastatic Breast (MBC), several such ITGAD, ITGA4, ITGAL, ITGA11 have lower metastases than primary tumors.

Язык: Английский

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