Cancer is a leading cause of death worldwide, particularly because of its high mortality rate in patients who are diagnosed at late stages. Conventional biomarkers originating from blood are widely used for cancer diagnosis, but their low sensitivity and specificity limit their widespread application in cancer screening among the general population. Currently, emerging studies are exploiting novel, highly-accurate biomarkers in human body fluids that are obtainable through minimally invasive techniques, which is defined as liquid biopsy. Circular RNAs (circRNAs) are a newly discovered class of noncoding RNAs generated mainly by pre-mRNA splicing. Following the rapid development of high-throughput transcriptome analysis techniques, numerous circRNAs have been recognized to exist stably and at high levels in body fluids, including plasma, serum, exosomes, and urine. CircRNA expression patterns exhibit distinctly differences between patients with cancer and healthy controls, suggesting that circRNAs in body fluids potentially represent novel biomarkers for monitoring cancer development and progression. In this study, we summarized the expression of circRNAs in body fluids in a pan-cancer dataset and characterized their clinical applications in liquid biopsy for cancer diagnosis and prognosis. In addition, a user-friendly web interface was developed to visualize each circRNA in fluids (https://mulongdu.shinyapps.io/circrnas_in_fluids/).

Background: Exosomes have emerged as vital biomarkers of multiple cancers and contain abundant circular RNAs (circRNAs). However, the potential for exosomal circRNAs to be used in diagnostics and their molecular mechanism of action in colorectal cancer (CRC) remain unclear. Methods: CRC-specific exosomal circRNAs were identified by RNA sequencing, exoRBase database and a tissue microarray. The diagnostic performance of plasma exosomal circRNAs was evaluated among cancer-free controls, precancer individuals, CRC patients, and patients with other types of cancer. The corresponding biological functions were mainly assessed using circRNA pull-down, proteomic analysis, and RNA immunoprecipitation assay underlying cellular and mouse models. Results: CircLPAR1 was encapsulated in exosomes with high stability and detectability, and its expression in plasma exosomes was remarkably decreased during CRC development but recovered after surgery. Exosomal circLPAR1 showed cancer specificity in CRC diagnosis and increased the diagnostic performance to an area under the receiver operating characteristic curve of 0.875, as determined by analysing its performance in combination with common clinical biomarkers CEA and CA19–9. Additionally, circLPAR1 was downregulated in CRC tissues and was associated with overall survival. Mechanistically, exosomal circLPAR1 was internalized by CRC cells, and it suppressed tumor growth, likely because exosomal circLPAR1 directly bound with eIF3h specifically suppressed the METTL3-eIF3h interaction, decreasing the translation of oncogene BRD4. Conclusions: This comprehensive study highlights plasma exosomal circLPAR1 as a promising predictor in CRC diagnosis and describes its biological regulation of colorectal tumorigenesis. This study provides a new perspective on early diagnosis in the clinic and pathogenesis in disease development.

Background: The association between vitamin E and cancer risk has been widely investigated by observational studies, but the findings remain inconclusive. Here, we aimed to evaluate the causal effect of circulating vitamin E on the risk of ten common cancers, including bladder, breast, colorectal, esophagus, lung, oral and pharynx, ovarian, pancreatic, prostate, and kidney cancer. Methods: A Mendelian randomization (MR) analytic framework was applied to data from a cancer-specific genome-wide association study (GWAS) comprising a total of 297,699 cancer cases and 304,736 controls of European ancestry. Three genetic instrumental variables associated with circulating vitamin E were selected. Summary statistic-based methods of inverse variance weighting (IVW) and likelihood-based approach, as well as the individual genotyping-based method of genetic risk score (GRS) were used. Multivariable IVW analysis was further performed to control for potential confounding effects. Furthermore, the UK Biobank cohort was used as external validation, supporting 355,543 European participants (incident cases ranged from 437 for ovarian cancer to 4882 for prostate cancer) for GRS-based estimation of circulating vitamin E, accompanied by a one-sample MR analysis of dietary vitamin E intake underlying the time-to-event analytic framework. Results: Specific to cancer GWAS, we found that circulating vitamin E was significantly associated with increased bladder cancer risk (odds ratios [OR]_IVW = 6.23, P_IVW = 3.05×10^-3) but decreased breast cancer risk (OR_IVW = 0.68, P_IVW = 8.19×10^-3); however, the significance of breast cancer was dampened (P_{multivariable IVW} > 0.05) in the subsequent multivariable MR analysis. In the validation stage of the UK Biobank cohort, we did not replicate convincing causal effects of genetically predicted circulating vitamin E concentrations and dietary vitamin E intake on the risk of ten cancers. Conclusions: This large-scale population study upon data from cancer-specific GWAS and a longitudinal biobank cohort indicates plausible non-causal associations between circulating vitamin E and ten common cancers in the European populations. Further studies regarding ancestral diversity are warranted to validate such causal associations.

Genome-wide association studies (GWASs) underlying case-control design have uncovered hundreds of genetic loci involved in tumorigenesis and provided rich resources for identifying risk factors and biomarkers associated with cancer susceptibility. However, the application of GWAS in determining the genetic architecture of cancer survival remains unestablished. Here, we systematically evaluated genetic effects at the genome-wide level on cancer survival that included overall survival (OS) and cancer-specific survival (CSS), leveraging data deposited in the UK Biobank cohort of a total of 19 628 incident patients across 17 cancer types. Furthermore, we assessed the causal effects of risk factors and circulating biomarkers on cancer prognosis via a Mendelian randomization (MR) analytic framework, which integrated cancer survival GWAS dataset, along with phenome-wide association study (PheWAS) and blood genome-wide gene expression/DNA methylation quantitative trait loci (eQTL/meQTL) datasets. On average, more than 10 traits, 700 genes, and 4,500 CpG sites were prone to cancer prognosis. Finally, we developed a user-friendly online database, SUrvival related cancer Multi-omics database via MEndelian Randomization (SUMMER; http://njmu-edu.cn:3838/SUMMER/), to help users query, browse, and download cancer survival results. In conclusion, SUMMER provides an important resource to assist the research community in understanding the genetic mechanisms of cancer survival.