Transmembrane (TMEM) protein genes are a class of proteins that spans membranes and function to many physiological processes. However, there is very little known about TMEM gene expression, especially in cancer tissue. Using single-cell and bulk RNA sequence may facilitate the understanding of this poorly characterized protein genes in PDAC.
We selected the TMEM family genes through the Human Protein Atlas and characterized their expression by single-cell and bulk transcriptomic datasets. Identification of the key TMEM genes was performed through three machine learning algorithms: LASSO, SVM-RFE and RF-SRC. Then, we established TMEM gene riskscore and estimate its implication in predicting survival and response to systematic therapy. Additionally, we explored the difference and impact of TMEM gene expression in PDAC through immunohistochemistry and cell line research.
5 key TMEM genes (ANO1, TMEM59, TMEM204, TMEM205, TMEM92) were selected based on the single-cell analysis and machine learning survival outcomes. Patients stratified into the high and low-risk groups based on TMEM riskscore, were observed with distinct overall survival in internal and external datasets. Moreover, through bulk RNA-sequence and immunohistochemical staining we verified the protein expression of TMEM genes in PDAC and revealed TMEM92 as an essential regulator of pancreatic cancer cell proliferation, migration, and invasion.
Our study on TMEM gene expression and behavior in PDAC has revealed unique characteristics, offering potential for precise therapeutic approaches. Insights into molecular mechanisms expand understanding of PDAC complexity and TMEM gene roles. Such knowledge may inform targeted therapy development, benefiting patients.