Abstract

Background: Radio-, chemo- and chemoradio-therapy are essential strategies for cancer therapy. However, there are no reliable non-invasive methods for assessing the effectiveness of these therapies before treatment. Recently, plasma cell-free DNA (cfDNA) was found to reflect the global nucleosome footprint and gene expression status of cancer and immune cells in cancer patients. Therefore, we hypothesized that cfDNA could be used to evaluate the effectiveness of cancer therapy. Methods: In this study, we implemented whole genome sequencing (WGS) of cfDNA collected from patients with three types of cancer before therapy. In addition to promoter profiling, we found that the global chromatin profiles between the sensitive and non-sensitive groups of each cancer type also showed significant changes. To further compare their potentials for effectiveness evaluation of cancer therapy, we developed classifiers based on the WGS data derived from 194 locally advanced rectal cancer (LARC) patients with multiple machine learning models for identifying LARC with pathological complete response (pCR). Findings: We found that not only the promoter profiling but also some variables of global chromatin profiles of cfDNA between the sensitive and non-sensitive groups of cancer patients showed significant difference. By comparing their performance for effectiveness evaluation, we found that the predictive classifier based on promoter profiling with the SVM model (PPCET) had the largest AUC of 0.89 (95% CI 0.83-0.94), which may highlight the potential applications of promoter profiling as a novel non-invasive in vivo approach for assessing the effectiveness of cancer therapy. Interpretation: PPCET is a non-invasive technique for predicting the effectiveness of cancer therapy before treatment that may help to prevent indiscriminate use of drugs, reduce toxicity and side effects, and improve the curative effect and quality of life. Funding Statement: This work was supported by National Natural Science Foundation of China [81802435]; China Postdoctoral Science Foundation funded project [2019T120742, 2016M602486]; Natural Science Foundation of Guangdong Province [2018A030313286, 2015B020233009]; Science and Technology Program of Guangzhou [201604020104, 201803040009]. Declaration of Interests: The authors declare that they have no conflicts of interest. Ethics Approval Statement: All plasma samples were obtained under Institutional Review Board approved protocols with informed consent from all participants for research use.

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