DNA methylation in small cell lung cancer

Author:

Zhu Xianmin1ORCID,Gao Yuehua1,Feng Yimiao2,Zheng Jie2,Dong Yixiao1,Zhang Peng3,Zhu Yuming3,Fan Guoping1

Affiliation:

1. Shanghai Institute for Advanced Immunochemical Studies ShanghaiTech University Shanghai China

2. School of Information Science and Technology ShanghaiTech University Shanghai China

3. Department of Thoracic Surgery Shanghai Pulmonary Hospital, School of Medicine, Tongji University Shanghai China

Abstract

AbstractSmall cell lung cancer (SCLC) originates from pulmonary neuroendocrine cells and accounts for approximately 15% of lung cancer incidents. Patients with SCLC have a very low survival rate due to fast progression and early metastasis. Despite the recent approval of immune checkpoint blockade for treatment of SCLC by US FDA, conventional platinum chemotherapy remains the first‐line treatment which always develops quick drug resistance. To define targets for diagnosis and treatment, SCLC has been categorized by different molecular markers. The most popular markers include genomic mutations in tumour suppressor genes such as TP53 and RB1 and expression of lineage‐specific transcription factors (TFs), that is ASCL1, NEUROD1, POU2F3 and YAP1. As DNA methylation is an important hallmark of cancer, efforts were made to investigate the mechanisms of DNA methylation involved in SCLC progression. Indeed, SCLC has distinct pattern of DNA methylation due to its different features compared to non‐SCLC and other tumours. In this review, we summarized the mechanisms of DNA methylation in SCLC which are associated with lineage‐specific TFs, cell proliferation, anti‐apoptosis, drug resistance, immune evasion and metastasis. We foresaw the challenges of applying DNA methylation in clinical diagnosis and treatment and discussed new approaches and technologies to overcome them. Combined with other gene regulatory information such as transcription and histone modification, DNA methylation/hydroxymethylation in SCLC will be resolved at single‐cell resolution to dissect the tumour microenvironment. The huge multiomics data will be processed and integrated with clinical data such as clinical images and pathological histochemistry by artificial intelligence and cloud computing. Circulating cell‐free DNA methylation will greatly enhance early diagnosis and prognosis prediction. New organoid and organ chip models will break through the obstacles of sampling limitation, faithfully simulate the physiology of human tissues and enable examining spatiotemporal DNA methylation during SCLC progression.

Funder

National Natural Science Foundation of China

Publisher

Wiley

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