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bioRxiv · 10.1101/2021.07.30.454426

A new single-cell level R-index for EGFR-TKI resistance and survival prediction in LUAD

Liu, Z.·Xie, X.·Li, L.·Xie, L.·Gao, X.·Xia, X.·Deng, H.·Yang, Y.·Yang, M.·Chang, L.-P.·Yi, X.·He, Z.·Zhou, C.
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Abstract

EGFR-TKIs achieved excellent efficacy in EGFR-mutated patients. Unfortunately, most patients would inevitably develop progressive disease within a median of 10 to 14 months. Predicting the resistance probability remains a challenge. Therefore, we created an R-index model trained by single-cell RNA data with the OCLR algorithm. This model can be applied to estimate the level of EGFR-TKI resistance in cell line and xenograft mice models and predict prognosis in multiple cohorts. Comparing the high and the low R-index group, we found that the glycolysis pathway and KRAS up-regulation pathway were related to resistance, and MDSC was the leading cause of immunosuppression in the tumor microenvironment. These results are consistent with previous studies indicating that the R-index provides an insight into resistance status and a new way to explore resistance mechanisms and clinical treatment by the combination of Glucose metabolism-targeted or MDSC-targeted therapies. This is the first quantification method of EGFR-TKI resistance based on single-cell sequencing data solving the problem of the mixed resistance state of tumor cells and helping explore transcriptome characteristics of drug-resistant cell populations.

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Liu, Z., Xie, X., Li, L., Xie, L., Gao, X., Xia, X., Deng, H., Yang, Y., Yang, M., Chang, L.-P., Yi, X., He, Z., Zhou, C.. 2021-08-01. A new single-cell level R-index for EGFR-TKI resistance and survival prediction in LUAD. https://doi.org/10.1101/2021.07.30.454426

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