circFBXO7/miR-96-5p/MTSS1 axis is an important regulator in the Wnt signaling pathway in ovarian cancer.

BACKGROUND: CircRNAs are a novel class of evolutionarily conserved noncoding RNA molecules that form covalently closed continuous loop structures without 5' caps and 3' poly(A) tails. Accumulating evidence suggests that circRNAs play important regulatory roles in cancer and are promising biomarkers for cancer diagnosis and prognosis, as well as targets for cancer therapy. In this study, we identify and explore the role of a novel circRNA, circFBXO7, in ovarian cancer. METHODS: rRNA-depleted RNA-sequencing was performed to identify differentially expressed circRNAs between ovarian cancerous and normal tissues. qRT-PCR and single-molecule RNA in-situ hybridization was used to quantify circFBXO7 expression in tumor tissues. The association of circFBXO7 expression with patient prognosis was evaluated by Kaplan-Meier survival analysis. The biological function of circFBXO7 was also investigated using loss-of-function and gain-of-function assays in vivo and in vitro. Luciferase reporter and TOP/FOP-Flash reporter assays were then conducted together with RNA immunoprecipitation and western blot to assess the circFBXO7/miR-96-5p/MTSS1/Wnt/ß-catenin axis. RESULTS: circFBXO7 was downregulated in ovarian cancer which was associated with poor prognosis. Biologically, circFBXO7 overexpression significantly suppressed ovarian cancer cell proliferation, migration, and invasion in vitro, and inhibited tumor growth and metastasis in vivo, whereas its knockdown exerted an opposite role. Mechanistically, circFBXO7 functioned as a competing endogenous RNA for miR-96-5p to regulate the expression of MTSS1. Consequently, downregulation of MTSS1 led to excessive accumulation of ß-catenin and increased phosphorylation of GSK3ß, leading to the translocation of ß-catenin to the nucleus, thereby activating the Wnt/ß-catenin signaling pathway and ultimately promoting ovarian cancer progression. CONCLUSIONS: Our findings indicate that circFBXO7 acts as a bone fide tumor suppressor in ovarian cancer and that the circFBXO7/miR-96-5p/MTSS1 axis is an important regulator in the Wnt/ß-catenin signaling pathway which may provide a promising target for ovarian cancer therapy.

DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies.

Although rapid progress has been made in computational approaches for prioritizing cancer driver genes, research is far from achieving the ultimate goal of discovering a complete catalog of genes truly associated with cancer. Driver gene lists predicted from these computational tools lack consistency and are prone to false positives. Here, we developed an approach (DriverML) integrating Rao's score test and supervised machine learning to identify cancer driver genes. The weight parameters in the score statistics quantified the functional impacts of mutations on the protein. To obtain optimized weight parameters, the score statistics of prior driver genes were maximized on pan-cancer training data. We conducted rigorous and unbiased benchmark analysis and comparisons of DriverML with 20 other existing tools in 31 independent datasets from The Cancer Genome Atlas (TCGA). Our comprehensive evaluations demonstrated that DriverML was robust and powerful among various datasets and outperformed the other tools with a better balance of precision and sensitivity. In vitro cell-based assays further proved the validity of the DriverML prediction of novel driver genes. In summary, DriverML uses an innovative, machine learning-based approach to prioritize cancer driver genes and provides dramatic improvements over currently existing methods. Its source code is available at https://github.com/HelloYiHan/DriverML.

Long noncoding RNA LCAT1 functions as a ceRNA to regulate RAC1 function by sponging miR-4715-5p in lung cancer.

INTRODUCTION: Long noncoding RNAs (lncRNAs) are emerging as key players in the development and progression of cancer. However, the biological role and clinical significance of most lncRNAs in lung carcinogenesis remain unclear. In this study, we identified and explored the role of a novel lncRNA, lung cancer associated transcript 1 (LCAT1), in lung cancer. METHODS: We predicted and validated LCAT1 from RNA-sequencing (RNA-seq) data of lung cancer tissues. The LCAT1-miR-4715-5p-RAC1 axis was assessed by dual-luciferase reporter and RNA immunoprecipitation (RIP) assays. Signaling pathways altered by LCAT1 knockdown were identified using RNA-seq. Furthermore, the mechanism of LCAT1 was investigated using loss-of-function and gain-of-function assays in vivo and in vitro. RESULTS: LCAT1 is an oncogene that is significantly upregulated in lung cancer tissues and associated with poor prognosis. LCAT1 knockdown caused growth arrest and cell invasion in lung cancer cells in vitro, and inhibited tumorigenesis and metastasis in the mouse xenografts. Mechanistically, LCAT1 functions as a competing endogenous RNA for miR-4715-5p, thereby leading to the upregulation of the activity of its endogenous target, Rac family small GTPase 1 (RAC1). Moreover, EHop-016, a small molecule inhibitor of RAC1, as an adjuvant could improve the Taxol monotherapy against lung cancer cells in vitro. CONCLUSIONS: LCAT1-miR-4715-5p-RAC1/PAK1 axis plays an important role in the progression of lung cancer. Our findings may provide valuable drug targets for treating lung cancer. The novel combination therapy of Taxol and EHop-016 for lung cancer warrants further investigation, especially in lung cancer patients with high LCAT1 expression.

Transcriptome analysis identifies genetic risk markers and explores the pathogenesis for inflammatory bowel disease.

Inflammatory bowel disease (IBD) is an incurable and disabling bowel disease driven by multiple risk factors that severely limit patients' quality of life. We integrated the RNA-sequencing data of 1238 IBD patients, and investigated the pathogenesis of IBD by combining transcriptional element prediction analysis and immune-related analysis. Here, we first determined that KIAA1109 is inhibited in IBD patients. The expression of KIAA1109 and NOD2, the key receptor of NOD-like receptors, showed a negative correlation. The NOD-like receptor signaling pathway is activated and exerts transcriptional regulation on the chemokines CXCL1 and CXCL2 through the activation of the transcription factors NFκB and AP1. Analysis of immune infiltration revealed that the expression of chemokines CXCL1 and CXCL2 may regulate the inflammatory response induced by immune cells. These findings suggest that the KIAA1109-NOD2-NFκB/AP1-CXCL1/CXCL2 regulatory axis is the molecular mechanism of IBD pathogenesis, which will provide a new perspective for the diagnosis, treatment and management of IBD patients.

Pan-cancer tRNA-derived fragment CAT1 coordinates RBPMS to stabilize NOTCH2 mRNA to promote tumorigenesis.

Transfer RNA-derived fragments (tRFs) are a class of small non-coding regulatory RNAs that are involved in the pathophysiology of many diseases. However, the role of tRFs in cancer progression remains largely elusive. Here, we demonstrate that a pan-cancer 3'-tRF, CAT1 (cancer associated tRF 1), is ubiquitously upregulated in tumors and associated with poor prognosis of a variety of cancers, including lung cancer. The upregulated CAT1 in cancer cells binds to RNA-binding protein with multiple splicing (RBPMS) and displaces NOTCH2 association from RBPMS, thereby inhibiting the subsequent CCR4-NOT deadenylation-complex-mediated NOTCH2 mRNA decay. The CAT1-enhanced NOTCH2 expression promotes lung cancer cell proliferation and metastasis in vitro and in vivo. In addition, plasma CAT1 levels are substantially increased in patients with lung cancer compared to non-cancer control subjects. Our findings reveal an intrinsic connection between cancer-specific upregulation of CAT1 and cancer progression, show the regulation of NOTCH signaling in cancer by a 3'-tRF, and highlight its great clinical potential.

LCAT1 is an oncogenic LncRNA by stabilizing the IGF2BP2-CDC6 axis.

Long non-coding RNAs (lncRNAs) is known to play vital roles in modulating tumorigenesis. We previously reported that LCAT1, a novel lncRNA, promotes the growth and metastasis of lung cancer cells both in vitro and in vivo. However, the underlying mechanism(s) of LCAT1 as an oncogenic regulator remains elusive. Here, we showed that LCAT1 physically interacts with and stabilizes IGF2BP2, an m6A reader protein, by preventing its degradation via autolysosomes. IGF2BP2 is overexpressed in lung cancer tissues, which is associated with poor survival of non-small cell lung cancer patients, suggesting its oncogenic role. Biologically, IGF2BP2 depletion inhibits growth and survival as well as the migration of lung cancer cells. Mechanistically, the LCAT1/IGF2BP2 complex increased the levels of CDC6, a key cell cycle regulator, by stabilizing its mRNA in an m6A-dependent manner. Like IGF2BP2, CDC6 is also overexpressed in lung cancer tissues with poor patient survival, and CDC6 knockdown has oncogenic inhibitory activity. Taken together, the LCAT1-IGF2BP2-CDC6 axis appears to play a vital role in promoting the growth and migration of lung cancer cells, and is a potential therapeutic target for lung cancer. Importantly, our finding also highlights a previously unknown critical role of LCAT1 in m6A-dependent gene regulation by preventing autolytic degradation of IGF2BP2.

An integrated epigenomic-transcriptomic landscape of lung cancer reveals novel methylation driver genes of diagnostic and therapeutic relevance.

Background: Aberrant DNA methylation occurs commonly during carcinogenesis and is of clinical value in human cancers. However, knowledge of the impact of DNA methylation changes on lung carcinogenesis and progression remains limited. Methods: Genome-wide DNA methylation profiles were surveyed in 18 pairs of tumors and adjacent normal tissues from non-small cell lung cancer (NSCLC) patients using Reduced Representation Bisulfite Sequencing (RRBS). An integrated epigenomic-transcriptomic landscape of lung cancer was depicted using the multi-omics data integration method. Results: We discovered a large number of hypermethylation events pre-marked by poised promoter in embryonic stem cells, being a hallmark of lung cancer. These hypermethylation events showed a high conservation across cancer types. Eight novel driver genes with aberrant methylation (e.g., PCDH17 and IRX1) were identified by integrated analysis of DNA methylome and transcriptome data. Methylation level of the eight genes measured by pyrosequencing can distinguish NSCLC patients from lung tissues with high sensitivity and specificity in an independent cohort. Their tumor-suppressive roles were further experimentally validated in lung cancer cells, which depend on promoter hypermethylation. Similarly, 13 methylation-driven ncRNAs (including 8 lncRNAs and 5 miRNAs) were identified, some of which were co-regulated with their host genes by the same promoter hypermethylation. Finally, by analyzing the transcription factor (TF) binding motifs, we uncovered sets of TFs driving the expression of epigenetically regulated genes and highlighted the epigenetic regulation of gene expression of TCF21 through DNA methylation of EGR1 binding motifs. Conclusions: We discovered several novel methylation driver genes of diagnostic and therapeutic relevance in lung cancer. Our findings revealed that DNA methylation in TF binding motifs regulates target gene expression by affecting the binding ability of TFs. Our study also provides a valuable epigenetic resource for identifying DNA methylation-based diagnostic biomarkers, developing cancer drugs for epigenetic therapy and studying cancer pathogenesis.

LCAT3, a novel m6A-regulated long non-coding RNA, plays an oncogenic role in lung cancer via binding with FUBP1 to activate c-MYC.

BACKGROUND: Long non-coding RNAs (lncRNAs) are important epigenetic regulators, which play critical roles in diverse physiological and pathological processes. However, the regulatory mechanism of lncRNAs in lung carcinogenesis remains elusive. Here, we characterized a novel oncogenic lncRNA, designated as Lung Cancer Associated Transcript 3 (LCAT3). METHODS: We predicted and validated LCAT3 by analyzing RNA-sequencing (RNA-seq) data of lung cancer tissues from TCGA. Methylated RNA immunoprecipitation was performed to assess m6A modification on LCAT3. The LCAT3-FUBP1-MYC axis was assessed by dual-luciferase reporter, RNA immunoprecipitation and Chromatin immunoprecipitation assays. Signaling pathways altered by LCAT3 knockdown were identified using RNA-seq. Furthermore, the mechanism of LCAT3 was investigated using loss-of-function and gain-of-function assays in vivo and in vitro. RESULTS: LCAT3 was found to be up-regulated in lung adenocarcinomas (LUAD), and its over-expression was associated with the poor prognosis of LUAD patients. LCAT3 upregulation is attributable to N6-methyladenosine (m6A) modification mediated by methyltransferase like 3 (METTL3), leading to LCAT3 stabilization. Biologically, loss-of-function assays revealed that LCAT3 knockdown significantly suppressed lung cancer cell proliferation, migration and invasion in vitro, and inhibited tumor growth and metastasis in vivo. LCAT3 knockdown induced cell cycle arrest at the G1 phase. Mechanistically, LCAT3 recruited Far Upstream Element Binding Protein 1 (FUBP1) to the MYC far-upstream element (FUSE) sequence, thereby activating MYC transcription to promote proliferation, survival, invasion and metastasis of lung cancer cells. CONCLUSIONS: Taken together, we identified and characterized LCAT3 as a novel oncogenic lncRNA in the lung, and validated the LCAT3-FUBP1-MYC axis as a potential therapeutic target for LUAD.

Global identification and characterization of tRNA-derived RNA fragment landscapes across human cancers.

Transfer RNA-derived RNA fragments (tRFs) are a class of small non-coding RNAs that are abundant in many organisms, but their role in cancer has not been fully explored. Here, we report a functional genomic landscape of tRFs in 8118 specimens across 15 cancer types from The Cancer Genome Atlas. These tRFs exhibited characteristics of widespread expression, high sequence conservation, cytoplasmic localization, specific patterns of tRNA cleavage and conserved cleavage in tissues. A cross-tumor analysis revealed significant commonality among tRF expression subtypes from distinct tissues of origins, characterized by upregulation of a group of tRFs with similar size and activation of cancer-associated signaling. One of the largest superclusters was composed of 22 nt 3'-tRFs upregulated in 13 cancer types, all of which share the activation of Ras/MAPK, RTK and TSC/mTOR signaling. tRF-based subgrouping provided clinically relevant stratifications and significantly improved outcome prediction by incorporating clinical variables. Additionally, we discovered 11 cancer driver tRFs using an effective approach for accurately exploring cross-tumor and platform trends. As a proof of concept, we performed comprehensive functional assays on a non-microRNA driver tRF, 5'-IleAAT-8-1-L20, and validated its oncogenic roles in lung cancer in vitro and in vivo. Our study also provides a valuable tRF resource for identifying diagnostic and prognostic biomarkers, developing cancer therapy and studying cancer pathogenesis.