Mutational signatures in squamous cell carcinoma of the lung

Comparative genomic analysis of esophageal squamous cell carcinoma among different geographic regions

Introduction

Esophageal squamous cell carcinoma (ESCC) shows remarkable variation in incidence, survival, and risk factors. Although the genomic characteristics of ESCC have been extensively characterized, the genomic differences between different geographic regions remain unclear.

Methods

In this study, we sequenced 111 patients with ESCC from northern (NC) and southern (SC) China, combined their data with those of 1081 cases from previous reports, and performed a comparative analysis among different regions. In total, 644 ESCC cases were collected from six geographic regions (NC, SC, Xinjiang, China [XJC], Japan [JP], Vietnam [VN], and Europe & America [EA]) as the discovery cohort. Validation cohort 1 included 437 patients with ESCC from the NC region. Validation cohort 2 included 54 and 57 patients from the NC and SC regions, respectively.

Results

Patients with ESCC in different regions had different genomic characteristics, including DNA signatures, tumor mutation burdens, significantly mutated genes (SMGs), altered signaling pathways, and genes associated with clinical features. Based on both the DNA mutation signature and the mutation profile of the most common genes, the NC and SC groups were clustered close together, followed by the JP, XJC, EA, and VN groups. Compared to patients with ESCC from SC, SMGs, including KMT2D, FAT1, and NOTCH1 were more frequently identified in patients with ESCC from NC. Furthermore, some genes (TDG and DNAH8) correlated with overall survival in completely opposite ways in patients with ESCC from different geographical regions.

Conclusions

Our study provides insights into genomic differences in ESCC among different regions. These differences may be related to differences in environmental carcinogens, incidence, and survival.

γH2AX, a DNA Double-Strand Break Marker, Correlates with PD-L1 Expression in Smoking-Related Lung Adenocarcinoma

In recent years, the choice of immune checkpoint inhibitors (ICIs) as a treatment based on high expression of programmed death-ligand 1 (PD-L1) in lung cancers has been increasing in prevalence. The high expression of PD-L1 could be a predictor of ICI efficacy as well as high tumor mutation burden (TMB), which is determined using next-generation sequencing (NGS). However, a great deal of effort is required to perform NGS to determine TMB. The present study focused on γH2AX, a double-strand DNA break marker, and the suspected positive relation between TMB and γH2AX was investigated. We assessed the possibility of γH2AX being an alternative marker of TMB or PD-L1. One hundred formalin-fixed, paraffin-embedded specimens of lung cancer were examined. All of the patients in the study received thoracic surgery, having been diagnosed with lung adenocarcinoma or squamous cell carcinoma. The expressions of γH2AX and PD-L1 (clone: SP142) were evaluated immunohistochemically. Other immunohistochemical indicators, p53 and Ki-67, were also used to estimate the relationships of γH2AX. Positive relationships between γH2AX and PD-L1 were proven, especially in lung adenocarcinoma. Tobacco consumption was associated with higher expression of γH2AX, PD-L1, Ki-67, and p53. In conclusion, the immunoexpression of γH2AX could be a predictor for the adaptation of ICIs as well of as PD-L1 and TMB.

Identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes

Largely, cancer development is driven by acquisition and positive selection of somatic mutations that increase proliferation and survival of tumor cells. As a result, genes related to cancer development tend to have an excess of somatic mutations in them. An excess of missense and/or nonsense mutations in a gene is an indicator of its cancer relevance. To identify genes with an excess of potentially functional missense or nonsense mutations one needs to compare the observed and expected numbers of mutations in the gene. We estimated the expected numbers of missense and nonsense mutations in individual human genes using (i) the number of potential sites for missense and nonsense mutations in individual transcripts and (ii) histology-specific nucleotide context-dependent mutation rates. To estimate mutation rates defined as the number of mutations per site per tumor we used silent mutations reported in the Catalog Of Somatic Mutations In Cancer (COSMIC). The estimates were nucleotide context dependent. We have identified 26 genes with an excess of missense and/or nonsense mutations for lung adenocarcinoma, 18 genes for small cell lung cancer, and 26 genes for squamous cell carcinoma of the lung. These genes include known genes and novel lung cancer gene candidates.