Epigenetic targeting of DNA repair in lung cancer

Targeting the DNA Damage Response Machinery for Lung Cancer Treatment

Lung cancer is considered the most commonly diagnosed cancer and one of the leading causes of death globally. Despite the responses from small-cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) patients to conventional chemo- and radiotherapies, the current outcomes are not satisfactory. Recently, novel advances in DNA sequencing technologies have started to take off which have provided promising tools for studying different tumors for systematic mutation discovery. To date, a limited number of DDR inhibition trials have been conducted for the treatment of SCLC and NSCLC patients. However, strategies to test different DDR inhibitor combinations or to target multiple pathways are yet to be explored. With the various biomarkers that have either been recently discovered or are the subject of ongoing investigations, it is hoped that future trials would be designed to allow for studying targeted treatments in a biomarker-enriched population, which is defensible for the improvement of prognosis for SCLC and NSCLC patients. This review article sheds light on the different DNA repair pathways and some of the inhibitors targeting the proteins involved in the DNA damage response (DDR) machinery, such as ataxia telangiectasia and Rad3-related protein (ATR), DNA-dependent protein kinase (DNA-PK), and poly-ADP-ribose polymerase (PARP). In addition, the current status of DDR inhibitors in clinical settings and future perspectives are discussed.

DNA repair genes are associated with tumor tissue differentiation and immune environment in lung adenocarcinoma: a bioinformatics analysis based on big data

Background

Lung adenocarcinoma (LUAD) is the most common type of lung cancer. DNA repair genes (DRGs) is important in lung cancer. The relationship between the immune environment and the expression levels of DRGs in LUAD remains unclear. The purpose of this study is to assess the relationship between DRGs and the immune environment and clinical characteristics of LUAD.

Methods

Data of 169 LUAD cases were obtained from cbioportal. The RNA-seq data came from the The Cancer Genome Atlas (TCGA) database. We collected DRGs from the Reactom database (KW0037, Reactom.org). The 302 genes expressed in each sample were analyzed by hierarchical clustering and grouped using the Gene Cluster 3.0 program. The Java Treeview program was used to generate heat maps of cluster indications and tumor staging patterns. GraphPad Prism 8 was used to draw survival curves and compare overall survival (OS). For single genes, an OS difference analysis between low and high expression populations was performed in GraphPad Prism 8.

Results

Matrix clustering showed no difference in the prognosis of the two clusters. The comparison of subgroups showed that Subcluster 1 (SC1) had the best prognosis, and Subcluster 2 (SC2) had the worst. There was a significant difference in tumor grades between Cluster 1 and Cluster 2 (P=0.01). There were significant differences in smoking status, histological grade and adenocarcinoma subtype among subgroups. In Subcluster 3 (SC3), the proportion of poorly differentiated cases was highest. Immunological index analysis showed that there were significant differences between Cluster 1 and Cluster 2 in interferon, macrophages, monocytes, neutrophils, natural killer (NK) cells, and T cells. Tumor purity, interferon, macrophages, monocytes, neutrophils, NK cells, T cells, translation, and proliferation all showed significant differences between subgroups. In SC2, the proliferation index increased (0.082 vs. 0.070); the protein translation index decreased (0.134 vs. 0.137); and the interferon level increased (0.099 vs. 0.097). In SC3, the proliferation index decreased (0.076 vs. 0.071); the protein translation index decreased (0.140 vs. 0.136); and the level of neutrophils increased (0.083 vs. 0.086).

Conclusions

The differences of DRGs in LUAD are related to tissue differentiation and immune indicators but not to prognosis.

Pulmonary Inflammation and KRAS Mutation in Lung Cancer

Chronic lung infection and lung cancer are two of the most important pulmonary diseases. Respiratory infection and its associated inflammation have been increasingly investigated for their role in increasing the risk of respiratory diseases including chronic obstructive pulmonary disease (COPD) and lung cancer. Kirsten rat sarcoma viral oncogene (KRAS) is one of the most important regulators of cell proliferation, differentiation, and survival. KRAS mutations are among the most common drivers of cancer. Lung cancer harboring KRAS mutations accounted for ~25% of the incidence but the relationship between KRAS mutation and inflammation remains unclear. In this chapter, we will describe the roles of KRAS mutation in lung cancer and how elevated inflammatory responses may increase KRAS mutation rate and create a vicious cycle of chronic inflammation and KRAS mutation that likely results in persistent potentiation for KRAS-associated lung tumorigenesis. We will discuss in this chapter regarding the studies of KRAS gene mutations in specimens from lung cancer patients and in animal models for investigating the role of inflammation in increasing the risk of lung tumorigenesis driven primarily by oncogenic KRAS.