An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles

Intratumor heterogeneity (ITH) is a biomarker of tumor progression, metastasis, and immune evasion. Previous studies evaluated ITH mostly based on DNA alterations. Here, we developed a new algorithm (DEPTH) for quantifying ITH based on mRNA alterations in the tumor. DEPTH scores displayed significant correlations with ITH-associated features (genomic instability, tumor advancement, unfavorable prognosis, immunosuppression, and drug response). Compared to DNA-based ITH scores (EXPANDS, PhyloWGS, MATH, and ABSOLUTE), DEPTH scores had stronger correlations with antitumor immune signatures, cell proliferation, stemness, tumor advancement, survival prognosis, and drug response. Compared to two other mRNA-based ITH scores (tITH and sITH), DEPTH scores showed stronger and more consistent associations with genomic instability, unfavorable tumor phenotypes and clinical features, and drug response. We further validated the reliability and robustness of DEPTH in 50 other datasets. In conclusion, DEPTH may provide new insights into tumor biology and potential clinical implications for cancer prognosis and treatment. Li et al develop an algorithm they call Deviating gene Expression Profiling Tumor Heterogeneity (DEPTH) to evaluate levels of intratumour heterogeneity (ITH) at the mRNA level based on the asynchrony of transcriptome alterations in tumors. Analysing TCGA and GEO data-sets, they show that this method is simpler, more effective, and more robust than other ITH scoring algorithms.