Functional Interrogation of Enhancer Connectome Prioritizes Candidate Target Genes at Ovarian Cancer Susceptibility Loci

Loop Catalog: a comprehensive HiChIP database of human and mouse samples

HiChIP enables cost-effective and high-resolution profiling of regulatory and structural loops. To leverage the increasing number of publicly available HiChIP datasets from diverse cell lines and primary cells, we developed the Loop Catalog (https://loopcatalog.lji.org), a web-based database featuring HiChIP loop calls for 1319 samples across 133 studies and 44 high-resolution Hi-C loop calls. We demonstrate its utility in interpreting fine-mapped GWAS variants (SNP-to-gene linking), in identifying enriched sequence motifs and motif pairs at loop anchors, and in network-level analysis of loops connecting regulatory elements (community detection). Our comprehensive catalog, spanning over 4M unique 5kb loops, along with the accompanying analysis modalities constitutes an important resource for studies in gene regulation and genome organization.

Identification of lncRNAs Deregulated in Epithelial Ovarian Cancer Based on a Gene Expression Profiling Meta-Analysis

Epithelial ovarian cancer (EOC) is one of the deadliest gynecological cancers worldwide, mainly because of its initially asymptomatic nature and consequently late diagnosis. Long non-coding RNAs (lncRNA) are non-coding transcripts of more than 200 nucleotides, whose deregulation is involved in pathologies such as EOC, and are therefore envisaged as future biomarkers. We present a meta-analysis of available gene expression profiling (microarray and RNA sequencing) studies from EOC patients to identify lncRNA genes with diagnostic and prognostic value. In this meta-analysis, we include 46 independent cohorts, along with available expression profiling data from EOC cell lines. Differential expression analyses were conducted to identify those lncRNAs that are deregulated in (i) EOC versus healthy ovary tissue, (ii) unfavorable versus more favorable prognosis, (iii) metastatic versus primary tumors, (iv) chemoresistant versus chemosensitive EOC, and (v) correlation to specific histological subtypes of EOC. From the results of this meta-analysis, we established a panel of lncRNAs that are highly correlated with EOC. The panel includes several lncRNAs that are already known and even functionally characterized in EOC, but also lncRNAs that have not been previously correlated with this cancer, and which are discussed in relation to their putative role in EOC and their potential use as clinically relevant tools.

CRISPR/Cas13-Based Platforms for a Potential Next-Generation Diagnosis of Colorectal Cancer through Exosomes Micro-RNA Detection: A Review

Simple Summary

Colorectal cancer is one of the most prevalent cancers, whereas a significant number of cases are diagnosed in late cancer stages, and survival rates drop dramatically. Micro-RNAs (miRNAs) from cancer-derived exosomes have shown promising diagnosis potential. Our review aims to present CRISPR/Cas-based molecular platforms as an inexpensive, swift, and robust detection tool of cancer-derived exosome micro-RNAs to streamline future applications based on the novel CRISPR/Cas-based platforms to achieve early CRC diagnosis.

Abstract

Colorectal cancer (CRC) is the third most prevalent cancer with the second highest mortality rate worldwide. CRC is a heterogenous disease with multiple risk factors associated, including obesity, smoking, and use of alcohol. Of total CRC cases, 60% are diagnosed in late stages, where survival can drop to about 10%. CRC screening programs are based primarily on colonoscopy, yet this approach is invasive and has low patient adherence. Therefore, there is a strong incentive for developing molecular-based methods that are minimally invasive and have higher patient adherence. Recent reports have highlighted the importance of extracellular vesicles (EVs), specifically exosomes, as intercellular communication vehicles with a broad cargo, including micro-RNAs (miRNAs). These have been syndicated as robust candidates for diagnosis, primarily for their known activities in cancer cells, including immunoevasion, tumor progression, and angiogenesis, whereas miRNAs are dysregulated by cancer cells and delivered by cancer-derived exosomes (CEx). Quantitative polymerase chain reaction (qPCR) has shown good results detecting specific cancer-derived exosome micro-RNAs (CEx-miRNAs) associated with CRC, but qPCR also has several challenges, including portability and sensitivity/specificity issues regarding experiment design and sample quality. CRISPR/Cas-based platforms have been presented as cost-effective, ultrasensitive, specific, and robust clinical detection tools in the presence of potential inhibitors and capable of delivering quantitative and qualitative real-time data for enhanced decision-making to healthcare teams. Thereby, CRISPR/Cas13-based technologies have become a potential strategy for early CRC diagnosis detecting CEx-miRNAs. Moreover, CRISPR/Cas13-based platforms’ ease of use, scalability, and portability also showcase them as a potential point-of-care (POC) technology for CRC early diagnosis. This study presents two potential CRISPR/Cas13-based methodologies with a proposed panel consisting of four CEx-miRNAs, including miR-126, miR-1290, miR-23a, and miR-940, to streamline novel applications which may deliver a potential early diagnosis and prognosis of CRC.

The Molecular Landscape Influencing Prognoses of Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is one of the major increasing lethal malignancies of the gynecological tract, mostly due to delayed diagnosis and chemoresistance, as well as its very heterogeneous genetic makeup. Application of high-throughput molecular technologies, gene expression microarrays, and powerful preclinical models has provided a deeper understanding of the molecular characteristics of EOC. Therefore, molecular markers have become a potent tool in EOC management, including prediction of aggressiveness, prognosis, and recurrence, and identification of novel therapeutic targets. In addition, biomarkers derived from genomic/epigenomic alterations (e.g., gene mutations, copy number aberrations, and DNA methylation) enable targeted treatment of affected signaling pathways in advanced EOC, thereby improving the effectiveness of traditional treatments. This review outlines the molecular landscape and discusses the impacts of biomarkers on the detection, diagnosis, surveillance, and therapeutic targets of EOC. These findings focus on the necessity to translate these potential biomarkers into clinical practice.