The landscape of chimeric RNAs in bladder urothelial carcinoma

Oncogenic SLC2A11-MIF fusion protein interacts with polypyrimidine tract binding protein 1 to facilitate bladder cancer proliferation and metastasis by regulating mRNA stability

Chimeric RNAs, distinct from DNA gene fusions, have emerged as promising therapeutic targets with diverse functions in cancer treatment. However, the functional significance and therapeutic potential of most chimeric RNAs remain unclear. Here we identify a novel fusion transcript of solute carrier family 2-member 11 (SLC2A11) and macrophage migration inhibitory factor (MIF). In this study, we investigated the upregulation of SLC2A11-MIF in The Cancer Genome Atlas cohort and a cohort of patients from Sun Yat-Sen Memorial Hospital. Subsequently, functional investigations demonstrated that SLC2A11-MIF enhanced the proliferation, antiapoptotic effects, and metastasis of bladder cancer cells in vitro and in vivo. Mechanistically, the fusion protein encoded by SLC2A11-MIF interacted with polypyrimidine tract binding protein 1 (PTBP1) and regulated the mRNA half-lives of Polo Like Kinase 1, Roundabout guidance receptor 1, and phosphoinositide-3-kinase regulatory subunit 3 in BCa cells. Moreover, PTBP1 knockdown abolished the enhanced impact of SLC2A11-MIF on biological function and mRNA stability. Furthermore, the expression of SLC2A11-MIF mRNA is regulated by CCCTC-binding factor and stabilized through RNA N4-acetylcytidine modification facilitated by N-acetyltransferase 10. Overall, our findings revealed a significant fusion protein orchestrated by the SLC2A11-MIF-PTBP1 axis that governs mRNA stability during the multistep progression of bladder cancer.

Cancer fusion transcripts with human non-coding RNAs

Cancer chimeric, or fusion, transcripts are thought to most frequently appear due to chromosomal aberrations that combine moieties of unrelated normal genes. When being expressed, this results in chimeric RNAs having upstream and downstream parts relatively to the breakpoint position for the 5'- and 3'-fusion components, respectively. As many other types of cancer mutations, fusion genes can be of either driver or passenger type. The driver fusions may have pivotal roles in malignisation by regulating survival, growth, and proliferation of tumor cells, whereas the passenger fusions most likely have no specific function in cancer. The majority of research on fusion gene formation events is concentrated on identifying fusion proteins through chimeric transcripts. However, contemporary studies evidence that fusion events involving non-coding RNA (ncRNA) genes may also have strong oncogenic potential. In this review we highlight most frequent classes of ncRNAs fusions and summarize current understanding of their functional roles. In many cases, cancer ncRNA fusion can result in altered concentration of the non-coding RNA itself, or it can promote protein expression from the protein-coding fusion moiety. Differential splicing, in turn, can enrich the repertoire of cancer chimeric transcripts, e.g. as observed for the fusions of circular RNAs and long non-coding RNAs. These and other ncRNA fusions are being increasingly recognized as cancer biomarkers and even potential therapeutic targets. Finally, we discuss the use of ncRNA fusion genes in the context of cancer detection and therapy.

RTCpredictor: identification of read-through chimeric RNAs from RNA sequencing data

Read-through chimeric RNAs are being recognized as a means to expand the functional transcriptome and contribute to cancer tumorigenesis when mis-regulated. However, current software tools often fail to predict them. We have developed RTCpredictor, utilizing a fast ripgrep tool to search for all possible exon-exon combinations of parental gene pairs. We also added exonic variants allowing searches containing common SNPs. To our knowledge, it is the first read-through chimeric RNA specific prediction method that also provides breakpoint coordinates. Compared with 10 other popular tools, RTCpredictor achieved high sensitivity on a simulated and three real datasets. In addition, RTCpredictor has less memory requirements and faster execution time, making it ideal for applying on large datasets.

Discovery of a polymorphic gene fusion via bottom-up chimeric RNA prediction

Gene fusions and their chimeric products are commonly linked with cancer. However, recent studies have found chimeric transcripts in non-cancer tissues and cell lines. Large-scale efforts to annotate structural variations have identified gene fusions capable of generating chimeric transcripts even in normal tissues. In this study, we present a bottom-up approach targeting population-specific chimeric RNAs, identifying 58 such instances in the GTEx cohort, including notable cases such as SUZ12P1-CRLF3, TFG-ADGRG7 and TRPM4-PPFIA3, which possess distinct patterns across different ancestry groups. We provide direct evidence for an additional 29 polymorphic chimeric RNAs with associated structural variants, revealing 13 novel rare structural variants. Additionally, we utilize the All of Us dataset and a large cohort of clinical samples to characterize the association of the SUZ12P1-CRLF3-causing variant with patient phenotypes. Our study showcases SUZ12P1-CRLF3 as a representative example, illustrating the identification of elusive structural variants by focusing on those producing population-specific fusion transcripts.

Versatile RNA: overlooked gems of the transcriptome

The critical role of RNA, its use and targetability concerning different aspects of human health are gaining more attention because our understanding of the versatility of RNA has dramatically evolved over the last decades. We now appreciate that RNA is far more critical than a messenger molecule and possesses many complicated functions. As a multifunctional molecule with its sequence, flexible structures and enzymatic abilities, RNA is genuinely powerful. Mammalian transcriptomes consist of a dynamically regulated plethora of coding and noncoding RNA types. However, some aspects of RNA metabolism remain to be explored. In this Viewpoint, we focus on the transcriptome's unconventional and possibly overlooked aspects to emphasize the importance of RNA in mammalian systems.

Functional and regulatory impact of chimeric RNAs in human normal and cancer cells

Fusions of two genes can lead to the generation of chimeric RNAs, which may have a distinct functional role from their original molecules. Chimeric RNAs could encode novel functional proteins or serve as novel long noncoding RNAs (lncRNAs). The appearance of chimeric RNAs in a cell could help to generate new functionality and phenotypic diversity that might facilitate this cell to survive against new environmental stress. Several recent studies have demonstrated the functional roles of various chimeric RNAs in cancer progression and are considered as biomarkers for cancer diagnosis and sometimes even drug targets. Further, the growing evidence demonstrated the potential functional association of chimeric RNAs with cancer heterogeneity and drug resistance cancer evolution. Recent studies highlighted that chimeric RNAs also have functional potentiality in normal physiological processes. Several functionally potential chimeric RNAs were discovered in human cancer and normal cells in the last two decades. This could indicate that chimeric RNAs are the hidden layer of the human transcriptome that should be explored from the functional insights to better understand the functional evolution of the genome and disease development that could facilitate clinical practice improvements. This review summarizes the current knowledge of chimeric RNAs and highlights their functional, regulatory, and evolutionary impact on different cancers and normal physiological processes. Further, we will discuss the potential functional roles of a recently discovered novel class of chimeric RNAs named sense-antisense/cross-strand chimeric RNAs generated by the fusion of the bi-directional transcripts of the same gene. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

Discovery of A Polymorphic Gene Fusion via Bottom-Up Chimeric RNA Prediction

Gene fusions and their chimeric products are typically considered hallmarks of cancer. However, recent studies have found chimeric transcripts in non-cancer tissues and cell lines. In addition, efforts to annotate structural variation at large scale have found examples of gene fusions with potential to produce chimeric transcripts in normal tissues. In this report, we provide a means for targeting population-specific chimeric RNAs to enrich for those generated by gene fusion events. We identify 57 such chimeric RNAs from the GTEx cohort, including SUZ12P1-CRLF3 and TFG-ADGRG7 , whose distribution we assessed across the populations of the 1000 Genomes Project. We reveal that SUZ12P1-CRLF3 results from a common complex structural variant in populations with African heritage, and identify its likely mechanism for formation. Additionally, we utilize a large cohort of clinical samples to characterize the SUZ12P1-CRLF3 chimeric RNA, and find an association between the variant and indications of Neurofibramatosis Type I. We present this gene fusion as a case study for identifying hard-to-find and potentially functional structural variants by selecting for those which produce population-specific fusion transcripts.

KEY POINTS

- Discovery of 57 polymorphic chimeric RNAs- Characterization of SUZ12P1-CRLF3 polymorphic chimeric RNA and corresponding rearrangement- Novel bottom-up approach to identify structural variants which produce transcribed gene fusions.

RTCpredictor: Identification of Read-Through Chimeric RNAs from RNA Sequencing Data

Read-through chimeric RNAs are gaining attention in cancer and other research fields, yet current tools often fail in predicting them. We have thus developed the first read-through chimeric RNA specific prediction method, RTCpredictor, utilizing a fast ripgrep algorithm to search for all possible exon-exon combinations of parental gene pairs. Compared with other ten popular tools, RTCpredictor achieved top performance on both simulated and real datasets. We randomly selected up to 30 candidate read-through chimeras predicted from each software method and experimentally validated a total of 109 read-throughs and on this set, RTCpredictor outperformed all the other methods. In addition, RTCpredictor ( https://github.com/sandybioteck/RTCpredictor ) has less memory requirements and faster execution time.

Recent advances in cancer fusion transcript detection

Extensive investigation of gene fusions in cancer has led to the discovery of novel biomarkers and therapeutic targets. To date, most studies have neglected chromosomal rearrangement-independent fusion transcripts and complex fusion structures such as double or triple-hop fusions, and fusion-circRNAs. In this review, we untangle fusion-related terminology and propose a classification system involving both gene and transcript fusions. We highlight the importance of RNA-level fusions and how long-read sequencing approaches can improve detection and characterization. Moreover, we discuss novel bioinformatic tools to identify fusions in long-read sequencing data and strategies to experimentally validate and functionally characterize fusion transcripts.

Profile of chimeric RNAs and TMPRSS2-ERG e2e4 isoform in neuroendocrine prostate cancer

Purpose

Specific gene fusions and their fusion products (chimeric RNA and protein) have served as ideal diagnostic markers and therapeutic targets for cancer. However, few systematic studies for chimeric RNAs have been conducted in neuroendocrine prostate cancer (NEPC). In this study, we explored the landscape of chimeric RNAs in different types of prostate cancer (PCa) cell lines and aimed to identify chimeric RNAs specifically expressed in NEPC.

Methods

To do so, we employed the RNA-seq data of eight prostate related cell lines from Cancer Cell Line Encyclopedia (CCLE) for chimeric RNA identification. Multiple filtering criteria were used and the candidate chimeric RNAs were characterized at multiple levels and from various angles. We then performed experimental validation on all 80 candidates, and focused on the ones that are specific to NEPC. Lastly, we studied the clinical relevance and effect of one chimera in neuroendocrine process.

Results

Out of 80 candidates, 15 were confirmed to be expressed preferentially in NEPC lines. Among them, 13 of the 15 were found to be specifically expressed in NEPC, and four were further validated in another NEPC cell line. Importantly, in silico analysis showed that tumor malignancy may be correlated to the level of these chimeric RNAs. Clinically, the expression of TMPRSS2-ERG (e2e4) was elevated in tumor tissues and indicated poor clinical prognosis, whereas the parental wild type transcripts had no such association. Furthermore, compared to the most frequently detected TMPRSS2-ERG form (e1e4), e2e4 encodes 31 more amino acids and accelerated neuroendocrine process of prostate cancer.

Conclusions

In summary, these findings painted the landscape of chimeric RNA in NEPC and supported the idea that some chimeric RNAs may represent additional biomarkers and/or treatment targets independent of parental gene transcripts.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-022-00893-5.

Chimeric RNAs Discovered by RNA Sequencing and Their Roles in Cancer and Rare Genetic Diseases

Chimeric RNAs are transcripts that are generated by gene fusion and intergenic splicing events, thus comprising nucleotide sequences from different parental genes. In the past, Northern blot analysis and RT-PCR were used to detect chimeric RNAs. However, they are low-throughput and can be time-consuming, labor-intensive, and cost-prohibitive. With the development of RNA-seq and transcriptome analyses over the past decade, the number of chimeric RNAs in cancer as well as in rare inherited diseases has dramatically increased. Chimeric RNAs may be potential diagnostic biomarkers when they are specifically expressed in cancerous cells and/or tissues. Some chimeric RNAs can also play a role in cell proliferation and cancer development, acting as tools for cancer prognosis, and revealing new insights into the cell origin of tumors. Due to their abilities to characterize a whole transcriptome with a high sequencing depth and intergenically identify spliced chimeric RNAs produced with the absence of chromosomal rearrangement, RNA sequencing has not only enhanced our ability to diagnose genetic diseases, but also provided us with a deeper understanding of these diseases. Here, we reviewed the mechanisms of chimeric RNA formation and the utility of RNA sequencing for discovering chimeric RNAs in several types of cancer and rare inherited diseases. We also discussed the diagnostic, prognostic, and therapeutic values of chimeric RNAs.

Generation and Application of Inducible Chimeric RNA ASTN2-PAPPAas Knockin Mouse Model

Chimeric RNAs (chiRNAs) play many previously unrecognized roles in different diseases including cancer. They can not only be used as biomarkers for diagnosis and prognosis of various diseases but also serve as potential therapeutic targets. In order to better understand the roles of chiRNAs in pathogenesis, we inserted human sequences into mouse genome and established a knockin mouse model of the tamoxifen-inducible expression of ASTN2-PAPPA antisense chimeric RNA (A-P_aschiRNA). Mice carrying the A-P_aschiRNA knockin gene do not display any apparent abnormalities in growth, fertility, histological, hematopoietic, and biochemical indices. Using this model, we dissected the role of A-P_aschiRNA in chemical carcinogen 4-nitroquinoline 1-oxide (4NQO)-induced carcinogenesis of esophageal squamous cell carcinoma (ESCC). To our knowledge, we are the first to generate a chiRNA knockin mouse model using the Cre-loxP system. The model could be used to explore the roles of chiRNA in pathogenesis and potential targeted therapies.

RNA editing affects cis-regulatory elements and predicts adverse cancer survival

BACKGROUND

RNA editing exerts critical impacts on numerous biological processes and thus are implicated in crucial human phenotypes, including tumorigenesis and prognosis. While previous studies have analyzed aggregate RNA editing activity at the sample level and associated it with overall cancer survival, there is not yet a large-scale disease-specific survival study to examine genome-wide RNA editing sites' prognostic value taking into account the host gene expression and clinical variables.

METHODS

In this study, we solved comprehensive Cox proportional models of disease-specific survival on individual RNA-editing sites plus host gene expression and critical demographic covariates. This allowed us to interrogate the prognostic value of a large number of RNA-editing sites at single-nucleotide resolution.

RESULTS

As a result, we identified 402 gene-proximal RNA-editing sites that generally predict adverse cancer survival. For example, an RNA-editing site residing in ZNF264 indicates poor survival of uterine corpus endometrial carcinoma, with a hazard ratio of 2.13 and an adjusted p-value of 4.07 × 10-7 . Some of these prognostic RNA-editing sites mediate the binding of RNA binding proteins and microRNAs, thus propagating their impacts to extensive regulatory targets.

CONCLUSIONS

In conclusion, RNA editing affects cis-regulatory elements and predicts adverse cancer survival.

Transcript-Level Dysregulation of BCL2 Family Genes in Acute Myeloblastic Leukemia

The expression of apoptosis-related BCL2 family genes, fine-tuned in normal cells, is dysregulated in many neoplasms. In acute myeloid leukemia (AML), this problem has not been studied comprehensively. To address this issue, RNA-seq data were used to analyze the expression of 26 BCL2 family members in 27 AML FAB M1 and M2 patients, divided into subgroups differently responding to chemotherapy. A correlation analysis, analysis of variance, and Kaplan-Meier analysis were applied to associate the expression of particular genes with other gene expression, clinical features, and the presence of mutations detected by exome sequencing. The expression of BCL2 family genes was dysregulated in AML, as compared to healthy controls. An upregulation of anti-apoptotic and downregulation of pro-apoptotic genes was observed, though only a decrease in BMF, BNIP1, and HRK was statistically significant. In a group of patients resistant to chemotherapy, overexpression of BCL2L1 was manifested. In agreement with the literature data, our results reveal that BCL2L1 is one of the key players in apoptosis regulation in different types of tumors. An exome sequencing data analysis indicates that BCL2 family genes are not mutated in AML, but their expression is correlated with the mutational status of other genes, including those recurrently mutated in AML and splicing-related. High levels of some BCL2 family members, in particular BIK and BCL2L13, were associated with poor outcome.

Comparative study of bioinformatic tools for the identification of chimeric RNAs from RNA Sequencing

Chimeric RNAs are gaining more and more attention as they have broad implications in both cancer and normal physiology. To date, over 40 chimeric RNA prediction methods have been developed to facilitate their identification from RNA sequencing data. However, a limited number of studies have been conducted to compare the performance of these tools; additionally, previous studies have become outdated as more software tools have been developed within the last three years. In this study, we benchmarked 16 chimeric RNA prediction software, including seven top performers in previous benchmarking studies, and nine that were recently developed. We used two simulated and two real RNA-Seq datasets, compared the 16 tools for their sensitivity, positive prediction value (PPV), F-measure, and also documented the computational requirements (time and memory). We noticed that none of the tools are inclusive, and their performance varies depending on the dataset and objects. To increase the detection of true positive events, we also evaluated the pair-wise combination of these methods to suggest the best combination for sensitivity and F-measure. In addition, we compared the performance of the tools for the identification of three classes (read-through, inter-chromosomal and intra-others) of chimeric RNAs. Finally, we performed TOPSIS analyses and ranked the weighted performance of the 16 tools.

Landscape of Chimeric RNAs in Non-Cancerous Cells

Gene fusions and their products (RNA and protein) have been traditionally recognized as unique features of cancer cells and are used as ideal biomarkers and drug targets for multiple cancer types. However, recent studies have demonstrated that chimeric RNAs generated by intergenic alternative splicing can also be found in normal cells and tissues. In this study, we aim to identify chimeric RNAs in different non-neoplastic cell lines and investigate the landscape and expression of these novel candidate chimeric RNAs. To do so, we used HEK-293T, HUVEC, and LO2 cell lines as models, performed paired-end RNA sequencing, and conducted analyses for chimeric RNA profiles. Several filtering criteria were applied, and the landscape of chimeric RNAs was characterized at multiple levels and from various angles. Further, we experimentally validated 17 chimeric RNAs from different classifications. Finally, we examined a number of validated chimeric RNAs in different cancer and non-cancer cells, including blood from healthy donors, and demonstrated their ubiquitous expression pattern.

α-E-Catenin (CTNNA1) Inhibits Cell Proliferation, Invasion and EMT of Bladder Cancer

Aim

Bladder cancer (BLCA) is an urogenital system tumor with a high morbidity. We aimed to explore the function and potential mechanism of α-E-catenin (CTNNA1) in BLCA.

Methods

The CTNNA1 expression in BLCA tissues was detected using qRT-PCR and immunohistochemistry. QRT-PCR and Western blot were performed to measure the CTNNA1 expression in BLCA cell lines. CTNNA1 expression was up-regulated in T24 and UMUC-2 cells by CTNNA1 overexpression plasmid transfection. Cell proliferation, apoptosis, migration and invasion were respectively assessed by CCK-8 assay, flow cytometry, wound healing assay and transwell assay. The expression levels of epithelial–mesenchymal transition (EMT)-related factors were tested by qRT-PCR and Western blot. BLCA nude mice models were constructed to explore the effects of CTNNA1 on BLCA in vivo. Gene set enrichment analysis (GSEA) was proceeded to identify the CTNNA1-related pathways in BLCA.

Results

The expressions of CTNNA1 were down-regulated in BLCA tissues and cell lines, and its low expression indicated poor prognosis of BLCA patients. CTNNA1 inhibited cell proliferation, migration, invasion and EMT and promoted cell apoptosis in BLCA cells. CTNNA1 enhanced E-cadherin expression and suppressed N-cadherin, snail, MMP2 and MMP9 expressions in BLCA cells, which suggested that CTNNA1 repressed EMT in BLCA cells. Moreover, CTNNA1 could inhibit tumor growth in vivo. CTNNA1 was positively associated with P53 and apoptosis pathways in BLCA cells.

Conclusion

CTNNA1 inhibited cell proliferation, migration, invasion and EMT and promoted cell apoptosis in BLCA via activating P53 and apoptosis pathways. CTNNA1 might be a novel target in BLCA therapy.

Transcriptome and Gene Fusion Analysis of Synchronous Lesions Reveals lncMRPS31P5 as a Novel Transcript Involved in Colorectal Cancer

Fusion genes and epigenetic regulators (i.e., miRNAs and long non-coding RNAs) constitute essential pieces of the puzzle of the tumor genomic landscape, in particular in mechanisms behind the adenoma-to-carcinoma progression of colorectal cancer (CRC). In this work, we aimed to identify molecular signatures of the different steps of sporadic CRC development in eleven patients, of which synchronous samples of adenomas, tumors, and normal tissues were analyzed by RNA-Seq. At a functional level, tumors and adenomas were all characterized by increased activity of the cell cycle, cell development, cell growth, and biological proliferation functions. In contrast, organic survival and apoptosis-related functions were inhibited both in tumors and adenomas at different levels. At a molecular level, we found that three individuals shared a tumor-specific fusion named MRPS31-SUGT1, generated through an intra-chromosomal translocation on chromosome 13, whose sequence resulted in being 100% identical to the long non-coding RNA (lncRNA) MRPS31P5. Our analyses suggest that MRPS31P5 could take part to a competitive endogenous (ce)RNA network by acting as a miRNA sponge or/and as an interactor of other mRNAs, and thus it may be an important gene expression regulatory factor and could be used as a potential biomarker for the detection of early CRC events.

Landscape characterization of chimeric RNAs in colorectal cancer

Gene fusions and their fusion products have been recognized as ideal biomarkers and drug targets for cancer. However, few recurrent gene fusions were found in colorectal cancer (CRC), despite comprehensive studies. We believe that chimeric RNAs, in the absence of chromosomal rearrangement, may represent a new repertoire of biomarkers and/or therapeutic targets in CRC. In this study, we aim to identify such recurrent chimeric RNAs, and investigate their clinical implications. To do so, we performed extensive data mining for chimeric RNAs using The Cancer Genome Atlas CRC RNA-Seq datasets. Multiple filtering criteria were applied, and the landscape of chimeric RNAs at multiple levels, from various angles, was analyzed. Eleven frequent, cancer biased chimeric RNAs were validated. The expression of RRM2-C2orf48 correlates with poor clinical outcomes, while the expression of parental RRM2 and C2orf48 correlates with positive clinical outcomes. Mechanistically, it is a product of cis-splicing between adjacent genes. Silencing of RRM2-C2orf48 resulted in reduced cellular proliferation in colon cancer cells, whereas overexpressed chimera promoted cell proliferation. These findings suggest that frequent chimeric RNAs are present in CRCs, and that chimeric RNAs may have different expression profiles and functions from parental genes, thus representing a new repertoire of biomarkers and therapeutic targets.

Chimeric RNAs in cancer

Chimeric RNAs are hybrid transcripts containing exons from two separate genes. Chimeric RNAs are traditionally considered to be transcribed from fusion genes caused by chromosomal rearrangement. These canonical chimeric RNAs are well characterized to be expressed in a cancer-unique pattern and/or act as oncogene products. However, benefited by the development of advanced deep sequencing technologies, novel types of non-canonical chimeric RNAs have been discovered to be generated from intergenic splicing without genomic aberrations. They can be formed through trans-splicing or cis-splicing between adjacent genes (cis-SAGe) mechanisms. Non-canonical chimeric RNAs are widely detected in normal physiology, although several have been shown to have a cancer-specific expression pattern. Further studies have indicated that some of them play fundamental roles in controlling cell growth and motility, and may have functions independent of the parental genes. These discoveries are unveiling a new layer of the functional transcriptome and are also raising the possibility of utilizing non-canonical chimeric RNAs as cancer diagnostic markers and therapeutic targets. In this chapter, we will overview different categories of chimeric RNAs and their expression in various types of cancerous and normal samples. Acknowledging that chimeric RNAs are not unique to cancer, we will discuss both bioinformatic and biological methods to identify credible cancer-specific chimeric RNAs. Furthermore, we will describe downstream methods to explore their molecular processing mechanisms and potential functions. A better understanding of the biogenesis mechanisms and functional products of cancer-specific chimeric RNAs will pave ways for the development of novel cancer biomarkers and therapeutic targets.

BCL-w: apoptotic and non-apoptotic role in health and disease

The BCL-2 family of proteins integrates signals that trigger either cell survival or apoptosis. The balance between pro-survival and pro-apoptotic proteins is important for tissue development and homeostasis, while impaired apoptosis contributes to several pathologies and can be a barrier against effective treatment. BCL-w is an anti-apoptotic protein that shares a sequence similarity with BCL-X_L, and exhibits a high conformational flexibility. BCL-w level is controlled by a number of signaling pathways, and the repertoire of transcriptional regulators largely depends on the cellular and developmental context. As only a few disease-relevant genetic alterations of BCL2L2 have been identified, increased levels of BCL-w might be a consequence of abnormal activation of signaling cascades involved in the regulation of BCL-w expression. In addition, BCL-w transcript is a target of a plethora of miRNAs. Besides its originally recognized pro-survival function during spermatogenesis, BCL-w has been envisaged in different types of normal and diseased cells as an anti-apoptotic protein. BCL-w contributes to survival of senescent and drug-resistant cells. Its non-apoptotic role in the promotion of cell migration and invasion has also been elucidated. Growing evidence indicates that a high BCL-w level can be therapeutically relevant in neurodegenerative disorders, neuron dysfunctions and after small intestinal resection, whereas BCL-w inhibition can be beneficial for cancer patients. Although several drugs and natural compounds can bi-directionally affect BCL-w level, agents that selectively target BCL-w are not yet available. This review discusses current knowledge on the role of BCL-w in health, non-cancerous diseases and cancer.

The landscape of chimeric RNAs in non-diseased tissues and cells

Chimeric RNAs and their encoded proteins have been traditionally viewed as unique features of neoplasia, and have been used as biomarkers and therapeutic targets for multiple cancers. Recent studies have demonstrated that chimeric RNAs also exist in non-cancerous cells and tissues, although large-scale, genome-wide studies of chimeric RNAs in non-diseased tissues have been scarce. Here, we explored the landscape of chimeric RNAs in 9495 non-diseased human tissue samples of 53 different tissues from the GTEx project. Further, we established means for classifying chimeric RNAs, and observed enrichment for particular classifications as more stringent filters are applied. We experimentally validated a subset of chimeric RNAs from each classification and demonstrated functional relevance of two chimeric RNAs in non-cancerous cells. Importantly, our list of chimeric RNAs in non-diseased tissues overlaps with some entries in several cancer fusion databases, raising concerns for some annotations. The data from this study provides a large repository of chimeric RNAs present in non-diseased tissues, which can be used as a control dataset to facilitate the identification of true cancer-specific chimeras.

Fusion Transcripts of Adjacent Genes: New Insights into the World of Human Complex Transcripts in Cancer

The awareness of genome complexity brought a radical approach to the study of transcriptome, opening eyes to single RNAs generated from two or more adjacent genes according to the present consensus. This kind of transcript was thought to originate only from chromosomal rearrangements, but the discovery of readthrough transcription opens the doors to a new world of fusion RNAs. In the last years many possible intergenic cis-splicing mechanisms have been proposed, unveiling the origins of transcripts that contain some exons of both the upstream and downstream genes. In some cases, alternative mechanisms, such as trans-splicing and transcriptional slippage, have been proposed. Five databases, containing validated and predicted Fusion Transcripts of Adjacent Genes (FuTAGs), are available for the scientific community. A comparative analysis revealed that two of them contain the majority of the results. A complete analysis of the more widely characterized FuTAGs is provided in this review, including their expression pattern in normal tissues and in cancer. Gene structure, intergenic splicing patterns and exon junction sequences have been determined and here reported for well-characterized FuTAGs. The available functional data and the possible roles in cancer progression are discussed.

Functional heritage: the evolution of chimeric RNA into a gene

Once believed to be unique features of neoplasia, chimeric RNAs are now being discovered in normal physiology. We speculated that some chimeric RNAs may be functional precursors of genes, and that forming chimeric RNA at the transcriptional level may be a 'trial' mechanism before the functional element is fixed into the genome. Supporting this idea, we identified a chimeric RNA, HNRNPA1L2-SUGT1 (H-S), whose sequence is highly similar to that of a 'pseudogene' MRPS31P5. Sequence analysis revealed that MRPS31P5 transcript is more similar to H-S chimeric RNA than its 'parent' gene, MRPS31. Evolutionarily, H-S precedes MRPS31P5, as it can be detected bioinformatically and experimentally in marmosets, which do not yet possess MRPS31P5 in their genome. Conversely, H-S is minimally expressed in humans, while instead, MRPS31P5 is abundantly expressed. Silencing H-S in marmoset cells resulted in similar phenotype as silencing MRPS31P5 in human cells. In addition, whole transcriptome analysis and candidate downstream target validation revealed common signalling pathways shared by the two transcripts. Interestingly, H-S failed to rescue the phenotype caused by silencing MPRS31P5 in human and rhesus cells, whereas MRPS31P5 can at least partially rescue the phenotype caused by silencing H-S in marmoset cells, suggesting that MRPS31P5 may have further evolved into a distinct entity. Thus, multiple lines of evidence support that MRPS31P5 is not truly a pseudogene of MRPS31, but a likely functional descendent of H-S chimera. Instead being a gene fusion product, H-S is a product of cis-splicing between adjacent genes, while MRPS31P5 is likely produced by genome rearrangement.