Emerging evidence indicates that circular RNAs (circRNAs) are implicated in cancer development. This study aimed to evaluate whether circulating circRNAs may serve as novel biomarkers for non‐small cell lung cancer (NSCLC). We used RNA sequencing (RNA‐seq) and quantitative real‐time PCR to explore cancer‐related circRNAs. Bioinformatics and functional analyses were performed to reveal biological effects of circRNAs on lung cancer cells. A total of 5471 distinct circRNAs were identified by total RNA‐seq, in which 185 were differentially expressed between cancerous and adjacent normal tissues. A circRNA derived from exon 5–7 of the FARSA gene, termed circFARSA, was observed to increase in cancerous tissues (P = 0.016), and was more abundant in patients’ plasma than controls (P < 0.001). Overexpression of circFARSA in A549 cell line significantly promoted cell migration and invasion. In silico analysis suggested that circFARSA might sponge miR‐330‐5p and miR‐326, thereby relieving their inhibitory effects on oncogene fatty acid synthase. Summarily, this study revealed circRNA profile of NSCLC for the first time and provided the evidence of plasma circFARSA as a potential noninvasive biomarker for this malignancy.

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (P_interaction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications.

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 autophagy‐related 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 = 1.33, 95% CI = 1.07–1.65; HR = 1.43, 95% CI = 1.13–1.81; HR = 1.38, 95% CI = 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 = 2.10, 95% CI = 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.

Introduction: Recently, several genome-wide association studies (GWAS) have identified novel single nucleotide polymorphisms (SNPs) associated with breast cancer risk. However, most of the studies were conducted among Caucasians and only one from Chinese. Methods: In the current study, we first tested whether 15 SNPs identified by previous GWAS were also breast cancer marker SNPs in this Chinese population. Then, we grouped the marker SNPs, and modeled them with clinical risk factors, to see the usage of these factors in breast cancer risk assessment. Two methods (risk factors counting and odds ratio (OR) weighted risk scoring) were used to evaluate the cumulative effects of the five significant SNPs and two clinical risk factors (age at menarche and age at first live birth). Results: Five SNPs located at 2q35, 3p24, 6q22, 6q25 and 10q26 were consistently associated with breast cancer risk in both testing set (878 cases and 900 controls) and validation set (914 cases and 967 controls) samples. Overall, all of the five SNPs contributed to breast cancer susceptibility in a dominant genetic model (2q35, rs13387042: adjusted OR = 1.26, P = 0.006; 3q24.1, rs2307032: adjusted OR = 1.24, P = 0.005; 6q22.33, rs2180341: adjusted OR = 1.22, P = 0.006; 6q25.1, rs2046210: adjusted OR = 1.51, P = 2.40 × 10^-8; 10q26.13, rs2981582: adjusted OR = 1.31, P = 1.96 × 10^-4). Risk score analyses (area under the curve (AUC): 0.649, 95% confidence interval (CI): 0.631 to 0.667; sensitivity = 62.60%, specificity = 57.05%) presented better discrimination than that by risk factors counting (AUC: 0.637, 95% CI: 0.619 to 0.655; sensitivity = 62.16%, specificity = 60.03%) (P < 0.0001). Absolute risk was then calculated by the modified Gail model and an AUC of 0.658 (95% CI = 0.640 to 0.676) (sensitivity = 61.98%, specificity = 60.26%) was obtained for the combination of five marker SNPs, age at menarche and age at first live birth. Conclusions: This study shows that five GWAS identified variants were also consistently validated in this Chinese population and combining these genetic variants with other risk factors can improve the risk predictive ability of breast cancer. However, more breast cancer associated risk variants should be incorporated to optimize the risk assessment.

Background and Aims: Innate lymphoid cells (ILCs) are tissue‐resident lymphocytes that play critical roles in cytokine‐mediated regulation of homeostasis and inflammation. However, relationships between their immune phenotypic characteristics and HCC remain largely unexplored. Approach and Results: We performed single‐cell RNA sequencing analysis on sorted hepatic ILC cells from human patients with HCC and validated using flow cytometry, multiplex immunofluorescence staining, and functional experiments. Moreover, we applied selection strategies to enrich ILC populations in HCC samples to investigate the effects of B cells on the immune reaction of inducible T cell costimulator (ICOS)⁺ ILC2 cells. Dysregulation of ILCs was manifested by the changes in cell numbers or subset proportions in HCC. Seven subsets of 3433 ILCs were identified with unique properties, of which ICOS⁺ ILC2a were preferentially enriched in HCC and correlated with poor prognosis. Mechanistically, we report that B cells, particularly resting naïve B cells, have a previously unrecognized function that is involved in inflammatory differentiation of ILC2 cells. B cell–derived ICOSL signaling was responsible for exacerbating inflammation through the increased production of IL‐13 in ICOS⁺ ILC2a cells. Heat shock protein 70 (HSP70) genes Heat Shock Protein Family A Member 1A (HSPA1A) and Heat Shock Protein Family A Member 1B (HSPA1B) were highly expressed in ILC2s in late‐stage HCC, and targeting to ICOS and its downstream effector HSP70 in ILC2s suppressed tumor growth and remodeled the immunosuppressive tumor microenvironment. Conclusions: This in‐depth understanding sheds light on B cell‐driven innate type 2 inflammation and provides a potential strategy for HCC immunotherapy.