Identification of Novel Fusion Transcripts in High Grade Serous Ovarian Cancer

Unravelling a novel CTNND1-RAB6A fusion transcript: Implications in colon cancer cell migration

The interchange of DNA sequences between genes may occur because of chromosomal rearrangements leading to the formation of chimeric genes. These chimeric genes have been linked to various cancers, accumulated significant interest in recent times. We used paired-end RNA-seq. data of four CRC and one normal sample generated from our previous study. The STAR-Fusion pipeline was utilized to identify the fusion genes unique to CRC. The in-silico identified fusion gene(s) were explored for their diagnostic, prognostic and therapeutic biomarker potential using TCGA-datasets, then validated through PCR and DNA sequencing. Further, cell line-based studies were performed to gain functional insights of the novel fusion transcript CTNND1-RAB6A, which was amplified in one sample. Sequencing revealed that there was a total loss of the CTNND1 gene, whereas RAB6A retained its coding sequence. Further, RAB6A was functionally characterized for its oncogenic potential in HCT116 cell line. RAB6A under-expression was found to be significantly associated with increased cell migration and is proposed to be regulated via the RAB6A-ECR1-Liprin-α axis. We conclude that RAB6A gene may play significant role in CRC oncogenesis, and could be used as a potential biomarker and therapeutic target in future for better management of a subset of CRCs harbouring this fusion.

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.

Identification of functional pathways and molecular signatures in neuroendocrine neoplasms by multi-omics analysis

BACKGROUND

Neuroendocrine neoplasms (NENs) represent a heterogeneous class of rare tumors with increasing incidence. They are characterized by the ability to secrete peptide hormones and biogenic amines but other reliable biomarkers are lacking, making diagnosis and identification of the primary site very challenging. While in some NENs, such as the pancreatic ones, next generation sequencing technologies allowed the identification of new molecular hallmarks, our knowledge of the molecular profile of NENs from other anatomical sites is still poor.

METHODS

Starting from the concept that NENs from different organs may be clinically and genetically correlated, we applied a multi-omics approach by combining multigene panel testing, CGH-array, transcriptome and miRNome profiling and computational analyses, with the aim to highlight common molecular and functional signatures of gastroenteropancreatic (GEP)-NENs and medullary thyroid carcinomas (MTCs) that could aid diagnosis, prognosis and therapy.

RESULTS

By comparing genomic and transcriptional profiles, ATM-dependent signaling emerged among the most significant pathways at multiple levels, involving gene variations and miRNA-mediated regulation, thus representing a novel putative druggable pathway in these cancer types. Moreover, a set of circulating miRNAs was also selected as possible diagnostic/prognostic biomarkers useful for clinical management of NENs.

CONCLUSIONS

These findings depict a complex molecular and functional landscape of NENs, shedding light on novel therapeutic targets and disease biomarkers to be exploited.