Chinese lung cancer patients have distinct epidemiologic and genomic features, highlighting the presence of specific etiologic mechanisms other than smoking. Here, we present a comprehensive genomic landscape of 149 non-small cell lung cancer (NSCLC) cases and identify 15 potential driver genes. We reveal that Chinese patients are specially characterized by not only highly clustered EGFR mutations but a mutational signature (MS3, 33.7%), that is associated with inflammatory tumor-infiltrating B lymphocytes (P = 0.001). The EGFR mutation rate is significantly increased with the proportion of the MS3 signature (P = 9.37 × 10−5). TCGA data confirm that the infiltrating B lymphocyte abundance is significantly higher in the EGFR-mutated patients (P = 0.007). Additionally, MS3-high patients carry a higher contribution of distant chromosomal rearrangements >1 Mb (P = 1.35 × 10−7), some of which result in fusions involving genes with important functions (i.e., ALK and RET). Thus, inflammatory infiltration may contribute to the accumulation of EGFR mutations, especially in never-smokers.

Approximately 20% of HER2 positive breast cancer develops disease recurrence after adjuvant trastuzumab treatment. This study aimed to develop a molecular prognostic model that can reliably stratify patients by risk of developing disease recurrence. Using miRNA microarrays, nine miRNAs that differentially expressed between the recurrent and non-recurrent patients were identified. Then, we validated the expression of these miRNAs using qRT-PCR in training set (n = 101), and generated a 2-miRNA (miR-4734 and miR-150-5p) based prognostic signature. The prognostic accuracy of this classifier was further confirmed in an internal testing set (n = 57), and an external independent testing set (n = 53). Besides, by comparing the ROC curves, we found the incorporation of this miRNA based classifier into TNM stage could improve the prognostic performance of TNM system. The results indicated the 2-miRNA based signature was a reliable prognostic biomarker for patients with HER2 positive breast cancer.

The aim of this article was to evaluate whether genetic variants in autophagy-related genes affect the overall survival (OS) of non-small cell lung cancer (NSCLC) patients. We analyzed 14 single nucleotide polymorphisms (SNPs) in core autophagyrelated genes for OS in 1,001 NSCLC patients. Three promising SNPs in ATG10 were subsequently annotated by the expression quantitative trait loci (eQTL) and methylation quantitative trait loci (meQTL) analyses based on Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) datasets. We observed that the variants of rs10514231, rs1864182 and rs1864183 were associated with poor lung cancer survival (HR 5 1.33, 95% CI 5 1.07-1.65; HR 5 1.43, 95% CI 5 1.13-1.81; HR 5 1.38, 95% CI 5 1.14-1.68, respectively) and positively correlated with ATG10 expression (all p < 0.05) from GTEx and TCGA datasets. The elevated expression of ATG10 may predict shorter survival time in lung cancer patients in TCGA dataset (HR 5 2.10, 95% CI 5 1.33-3.29). Moreover, the variants of rs10514231 and rs1864182 were associated with the increased methylation levels of cg17942617 (meQTL), which in turn contributed to the elevated ATG10 expression and decreased survival time. Further functional assays revealed that ATG10 facilitated lung cancer cell proliferation and migration. Our findings suggest that eQTL/meQTL variations of ATG10 could influence lung cancer survival through regulating ATG10 expression.Lung cancer, especially non-small cell lung cancer (NSCLC), remains the leading cause of cancer death globally and is characterized by its high incidence, poor prognosis.1,2 In spite of recent advances in clinical therapy, 5-year survival rate of NSCLC patients is lower than 20% in the developed and developing world. 3 Some prognostic parameters, such as smoking, tumor size and clinical stages, have been identified to predict survival of NSCLC. However, recent studies demonstrated that genetic and epigenetic factors also affected the survival of lung cancer. [4][5][6][7] Autophagy is a cellular recycling mechanism by which cells capture, degrade and recycle intracellular proteins and organelles in lysosomes. [8][9][10][11] Autophagosome formation requires two crucial ubiquitin-proteasome systems, the ATG12 and the microtubule-associated protein 1 light chain 3 B (LC3B) systems, which are correlated with expansion of

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