Exploration of Prognostic Immune-Related Genes and lncRNAs Biomarkers in Kidney Renal Clear Cell Carcinoma and Its Crosstalk with Acute Kidney Injury.
Chenxia JuanYe ZhuYan ZhouWeiwei ZhuXufang WangWeiming HeYan ChenPublished in: Journal of oncology (2022)
Kidney renal clear cell carcinoma (KIRC) has a poor prognosis and a high death rate globally. Cancer prognosis is strongly linked to immune-related genes (IRGs), according to numerous research. We utilized KIRC RNA-seq data from the TCGA database to build a prognostic model incorporating seven immune-related (IR) lncRNAs, and we constructed the model using LASSO regression. Additionally, we calculated a risk score for each patient using a prognostic model that divided patients into high-risk and low-risk groups. The ESTIMATE and CIBERSORT methodologies were then used to analyze the differences in the tumor microenvironment of the two groups of patients. Finally, we predicted three small molecule drugs that may have potential therapeutic effects for high-risk patients. We combined the acute kidney injury dataset to obtain differential genes that may serve standard biological functions with two risk groups. Our study shows that the model we constructed for IR-lncRNAs has reliable predictive efficacy for patients with KIRC.
Keyphrases
- acute kidney injury
- end stage renal disease
- poor prognosis
- small molecule
- ejection fraction
- rna seq
- newly diagnosed
- prognostic factors
- long non coding rna
- single cell
- squamous cell carcinoma
- clear cell
- emergency department
- gene expression
- patient reported outcomes
- genome wide
- transcription factor
- young adults
- data analysis
- deep learning
- lymph node metastasis