Gene fusions and chimeric RNAs, and their implications in cancer

Identifying new cancer genes based on the integration of annotated gene sets via hypergraph neural networks

MOTIVATION

Identifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and biological processes. The knowledge of annotated gene sets is critical for discovering cancer genes but remains to be fully exploited.

RESULTS

Here, we present the DIsease-Specific Hypergraph neural network (DISHyper), a hypergraph-based computational method that integrates the knowledge from multiple types of annotated gene sets to predict cancer genes. First, our benchmark results demonstrate that DISHyper outperforms the existing state-of-the-art methods and highlight the advantages of employing hypergraphs for representing annotated gene sets. Second, we validate the accuracy of DISHyper-predicted cancer genes using functional validation results and multiple independent functional genomics data. Third, our model predicts 44 novel cancer genes, and subsequent analysis shows their significant associations with multiple types of cancers. Overall, our study provides a new perspective for discovering cancer genes and reveals previously undiscovered cancer genes.

AVAILABILITY AND IMPLEMENTATION

DISHyper is freely available for download at https://github.com/genemine/DISHyper.

Omics-based molecular classifications empowering in precision oncology

BACKGROUND

In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine.

CONCLUSION

This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.

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.

PIK3R1 fusion drives chemoresistance in ovarian cancer by activating ERK1/2 and inducing rod and ring-like structures

Gene fusions are common in high-grade serous ovarian cancer (HGSC). Such genetic lesions may promote tumorigenesis, but the pathogenic mechanisms are currently poorly understood. Here, we investigated the role of a PIK3R1-CCDC178 fusion identified from a patient with advanced HGSC. We show that the fusion induces HGSC cell migration by regulating ERK1/2 and increases resistance to platinum treatment. Platinum resistance was associated with rod and ring-like cellular structure formation. These structures contained, in addition to the fusion protein, CIN85, a key regulator of PI3K-AKT-mTOR signaling. Our data suggest that the fusion-driven structure formation induces a previously unrecognized cell survival and resistance mechanism, which depends on ERK1/2-activation.

Comparative genomics of macaques and integrated insights into genetic variation and population history

The crab-eating macaques ( Macaca fascicularis ) and rhesus macaques ( M. mulatta ) are widely studied nonhuman primates in biomedical and evolutionary research. Despite their significance, the current understanding of the complex genomic structure in macaques and the differences between species requires substantial improvement. Here, we present a complete genome assembly of a crab-eating macaque and 20 haplotype-resolved macaque assemblies to investigate the complex regions and major genomic differences between species. Segmental duplication in macaques is ∼42% lower, while centromeres are ∼3.7 times longer than those in humans. The characterization of ∼2 Mbp fixed genetic variants and ∼240 Mbp complex loci highlights potential associations with metabolic differences between the two macaque species (e.g., CYP2C76 and EHBP1L1 ). Additionally, hundreds of alternative splicing differences show post-transcriptional regulation divergence between these two species (e.g., PNPO ). We also characterize 91 large-scale genomic differences between macaques and humans at a single-base-pair resolution and highlight their impact on gene regulation in primate evolution (e.g., FOLH1 and PIEZO2 ). Finally, population genetics recapitulates macaque speciation and selective sweeps, highlighting potential genetic basis of reproduction and tail phenotype differences (e.g., STAB1 , SEMA3F , and HOXD13 ). In summary, the integrated analysis of genetic variation and population genetics in macaques greatly enhances our comprehension of lineage-specific phenotypes, adaptation, and primate evolution, thereby improving their biomedical applications in human diseases.

Recent advances in the investigation of fusion RNAs and their role in molecular pathology of cancer

Gene fusions have had a significant role in the development of various types of cancer, oftentimes involved in oncogenic activities through dysregulation of gene expression or signalling pathways. Some cancer-associated chromosomal translocations can undergo backsplicing, resulting in fusion-circular RNAs, a more stable isoform immune to RNase degradation. This stability makes fusion circular RNAs a promising diagnostic biomarker for cancer. While the detection of linear fusion RNAs and their function in certain cancers have been described in literature, fusion circular RNAs lag behind due to their low abundance in cancer cells. This review highlights current literature on the role of linear and circular fusion transcripts in cancer, tools currently available for detecting of these chimeric RNAs and their function and how they play a role in tumorigenesis.

A protein-encoding CCDC7 circular RNA inhibits the progression of prostate cancer by up-regulating FLRT3

Circular RNAs (circRNAs) are a family of endogenous RNAs that have become a focus of biological research in recent years. Emerging evidence has revealed that circRNAs exert biological functions by acting as transcriptional regulators, microRNA sponges, and binding partners with RNA-binding proteins. However, few studies have identified coding circRNAs, which may lead to a hidden repertoire of proteins. In this study, we unexpectedly discovered a protein-encoding circular RNA circCCDC7(15,16,17,18,19) while we were searching for prostate cancer related chimeric RNAs. circCCDC7(15,16,17,18,19) is derived from exon 19 back spliced to exon 15 of the CCDC7 gene. It is significantly downregulated in patients with high Gleason score. Prostate cancer patients with decreased circCCDC7(15,16,17,18,19) expression have a worse prognosis, while linear CCDC7 had no such association. Overexpressed circCCDC7(15,16,17,18,19) inhibited prostate cancer cell migration, invasion, and viability, supporting classification of circCCDC7(15,16,17,18,19) as a bona fide tumor suppressor gene. We provide evidence that its tumor suppressive activity is driven by the protein it encodes, and that circCCDC7(15,16,17,18,19) encodes a secretory protein. Consistently, conditioned media from circCCDC7(15,16,17,18,19) overexpressing cells has the same tumor suppressive activity. We further demonstrate that the tumor suppressive activity of circCCDC7(15,16,17,18,19) is at least partially mediated by FLRT3, whose expression also negatively correlates with Gleason score and clinical prognosis. In conclusion, circCCDC7(15,16,17,18,19) functions as a tumor suppressor in prostate cancer cells through the circCCDC7-180aa secretory protein it encodes, and is a promising therapeutic peptide for prostate cancer.

RNA fusion in human retinal development

Chimeric RNAs have been found in both cancerous and healthy human cells. They have regulatory effects on human stem/progenitor cell differentiation, stemness maintenance, and central nervous system development. However, whether they are present in human retinal cells and their physiological functions in the retinal development remain unknown. Based on the human embryonic stem cell-derived retinal organoids (ROs) spanning from days 0 to 120, we present the expression atlas of chimeric RNAs throughout the developing ROs. We confirmed the existence of some common chimeric RNAs and also discovered many novel chimeric RNAs during retinal development. We focused on CTNNBIP1-CLSTN1 (CTCL) whose downregulation caused precocious neuronal differentiation and a marked reduction of neural progenitors in human cerebral organoids. CTCL is universally present in human retinas, ROs, and retinal cell lines, and its loss-of-function biases the progenitor cells toward retinal pigment epithelial cell fate at the expense of retinal cells. Together, this work provides a landscape of chimeric RNAs and reveals evidence for their critical role in human retinal development.

Elaboration of NTRK-rearranged colorectal cancer: Integration of immunoreactivity pattern, cytogenetic identity, and rearrangement variant

Fused information from protein status, DNA breakage, and transcripts are still limited because of the low rate of activated-NTRK in colorectal cancer (CRC). In total, 104 archived CRC tissue samples with dMMR were analyzed using immunohistochemistry (IHC), polymerase chain reaction (PCR), and pyrosequencing to mine the NTRK-enriched CRC group, and then subjected to NTRK fusion detection using pan-tyrosine kinase IHC, fluorescence in situ hybridization (FISH), and DNA-/RNA-based next generation sequencing (NGS) assays. Of the 15 NTRK-enriched CRCs, eight NTRK fusions (53.3%, 8/15), including two TPM3(e7)-NTRK1(e10), one TPM3(e5)-NTRK1(e11), one LMNA(e10)-NTRK1(e10), two EML4(e2)-NTRK3(e14), and two ETV6(e5)-NTRK3(e15) fusions, were identified. There was no immunoreactivity for ETV6-NTRK3 fusion. In addition to cytoplasmic staining found in six specimens, membrane positive (TPM3-NTRK1 fusion) and nuclear positive (LMNA-NTRK1 fusion) were also observed in two of them. Atypical FISH-positive types were observed in four cases. Unlike IHC, NTRK-rearranged tumors appeared homogeneous on FISH. ETV6-NTRK3 may be missed in pan-TRK IHC screening for CRC. Regarding break-apart FISH, NTRK detection is difficult because of the diversity of signal patterns. Further research is warranted to identify the characteristics of NTRK-fusion CRCs.

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.

The peptide woods are lovely, dark and deep: Hunting for novel cancer antigens

Harnessing the patient's immune system to control a tumor is a proven avenue for cancer therapy. T cell therapies as well as therapeutic vaccines, which target specific antigens of interest, are being explored as treatments in conjunction with immune checkpoint blockade. For these therapies, selecting the best suited antigens is crucial. Most of the focus has thus far been on neoantigens that arise from tumor-specific somatic mutations. Although there is clear evidence that T-cell responses against mutated neoantigens are protective, the large majority of these mutations are not immunogenic. In addition, most somatic mutations are unique to each individual patient and their targeting requires the development of individualized approaches. Therefore, novel antigen types are needed to broaden the scope of such treatments. We review high throughput approaches for discovering novel tumor antigens and some of the key challenges associated with their detection, and discuss considerations when selecting tumor antigens to target in the clinic.

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.

Integrating Pharmacogenomics Data-Driven Computational Drug Prediction with Single-Cell RNAseq to Demonstrate the Efficacy of a NAMPT Inhibitor against Aggressive, Taxane-Resistant, and Stem-like Cells in Lethal Prostate Cancer

Metastatic prostate cancer/PCa is the second leading cause of cancer deaths in US men. Most early-stage PCa are dependent on overexpression of the androgen receptor (AR) and, therefore, androgen deprivation therapies/ADT-sensitive. However, eventual resistance to standard medical castration (AR-inhibitors) and secondary chemotherapies (taxanes) is nearly universal. Further, the presence of cancer stem-like cells (EMT/epithelial-to-mesenchymal transdifferentiation) and neuroendocrine PCa (NEPC) subtypes significantly contribute to aggressive/lethal/advanced variants of PCa (AVPC). In this study, we introduced a pharmacogenomics data-driven optimization-regularization-based computational prediction algorithm ("secDrugs") to predict novel drugs against lethal PCa. Integrating secDrug with single-cell RNA-sequencing/scRNAseq as a 'Double-Hit' drug screening tool, we demonstrated that single-cells representing drug-resistant and stem-cell-like cells showed high expression of the NAMPT pathway genes, indicating potential efficacy of the secDrug FK866 which targets NAMPT. Next, using several cell-based assays, we showed substantial impact of FK866 on clinically advanced PCa as a single agent and in combination with taxanes or AR-inhibitors. Bulk-RNAseq and scRNAseq revealed that, in addition to NAMPT inhibition, FK866 regulates tumor metastasis, cell migration, invasion, DNA repair machinery, redox homeostasis, autophagy, as well as cancer stemness-related genes, HES1 and CD44. Further, we combined a microfluidic chip-based cell migration assay with a traditional cell migration/'scratch' assay and demonstrated that FK866 reduces cancer cell invasion and motility, indicating abrogation of metastasis. Finally, using PCa patient datasets, we showed that FK866 is potentially capable of reversing the expression of several genes associated with biochemical recurrence, including IFITM3 and LTB4R. Thus, using FK866 as a proof-of-concept candidate for drug repurposing, we introduced a novel, universally applicable preclinical drug development pipeline to circumvent subclonal aggressiveness, drug resistance, and stemness in lethal PCa.

Chimeric RNA RRM2-C2orf48 plays an oncogenic role in the development of NNK-induced lung cancer

Chimeric RNAs have been used as biomarkers and therapeutic targets for multiple types of cancers. However, less attention has been paid to their mechanism of action in neoplasia. Here, we reported that high-expressed chimeric RNA RRM2-C2orf48 was found in malignantly transformed BEAS-2B cells induced by 4-(methyl nitrosamine)-1-(3-pyridinyl)-1-butanone (NNK) in 74 lung cancer patients and several lung cancer cell lines. The expression level of RRM2-C2orf48 was significantly correlated with lymph node metastasis, distant metastasis, tumor-lymph node-metastasis (TNM) stage, and smoking. Overexpressing RRM2-C2orf48 promoted cell growth and accelerated the process of NNK-induced lung cancer. RRM2-C2orf48 knockdown inhibited the growth of RRM2-C2orf48-overexpressing BEAS-2B cells. Finally, we identified miR-219a-2-3p as a potential target of RRM2-C2orf48 in lung cancer. In summary, chimeric RNA RRM2-C2orf48 accelerated the process of NNK-induced lung cancer, and miR-219a-2-3p may be involved in this process.

Fusion proteins mediate alternation of protein interaction networks in cancers

Fusions of two different genes could lead to the production of chimeric RNAs, which could be translated into novel fusion (or chimeric) proteins. Fusion proteins often act as oncoproteins and drive cancer development, particularly in leukemia and lymphomas. Fusion proteins modify the existing protein-protein interaction (PPI) networks, which could eliminate some PPIs by removing protein domains in such fusions. This alternation of protein interaction networks could impact the signaling pathways and switch on the cancer-promoting activity that could drive the generation of cancer phenotypes and/or loss of controlled apoptosis. Thus, knowledge of the fusion proteins and their protein interaction networks could facilitate a deeper molecular understanding of cancer development, which could help to design new approaches for cancer therapies. Here, we discuss the structural features of fusion proteins and how they impact the PPI networks in cancers. Further, we discuss how to analyze the fusion protein-mediated alternation of PPI networks in cancers.

Fusion Genes in Prostate Cancer: A Comparison in Men of African and European Descent

Simple Summary

Men of African origin have a 2–3 times greater chance of developing prostate cancer than those of European origin, and of patients that are diagnosed with the disease, men of African descent are 2 times more likely to die compared to white men. Men of African origin are still greatly underrepresented in genetic studies and clinical trials. This, unfortunately, means that new discoveries in cancer treatment are missing key information on the group with a greater chance of mortality. A fusion gene is a hybrid gene formed from two previously independent genes. Fusion genes have been found to be common in all main types of human cancer. The objective of this study was to increase our knowledge of fusion genes in prostate cancer using computational approaches and to compare fusion genes between men of African and European origin. This identified novel gene fusions unique to men of African origin and suggested that this group has a greater number of fusion genes.

Abstract

Prostate cancer is one of the most prevalent cancers worldwide, particularly affecting men living a western lifestyle and of African descent, suggesting risk factors that are genetic, environmental, and socioeconomic in nature. In the USA, African American (AA) men are disproportionately affected, on average suffering from a higher grade of the disease and at a younger age compared to men of European descent (EA). Fusion genes are chimeric products formed by the merging of two separate genes occurring as a result of chromosomal structural changes, for example, inversion or trans/cis-splicing of neighboring genes. They are known drivers of cancer and have been identified in 20% of cancers. Improvements in genomics technologies such as RNA-sequencing coupled with better algorithms for prediction of fusion genes has added to our knowledge of specific gene fusions in cancers. At present AA are underrepresented in genomic studies of prostate cancer. The primary goal of this study was to examine molecular differences in predicted fusion genes in a cohort of AA and EA men in the context of prostate cancer using computational approaches. RNA was purified from prostate tissue specimens obtained at surgery from subjects enrolled in the study. Fusion gene predictions were performed using four different fusion gene detection programs. This identified novel putative gene fusions unique to AA and suggested that the fusion gene burden was higher in AA compared to EA men.

The Landscape of Novel Expressed Chimeric RNAs in Rheumatoid Arthritis

In cancers and other complex diseases, the fusion of two genes can lead to the production of chimeric RNAs, which are associated with disease development. Several recurrent chimeric RNAs are expressed in different cancers and are thus used for clinical cancer diagnosis. Rheumatoid arthritis (RA) is an immune-mediated joint disorder resulting in synovial inflammation and joint destruction. Despite advances in therapy, many patients do not respond to treatment and present persistent inflammation. Understanding the landscape of chimeric RNA expression in RA patients could provide a better insight into RA pathogenesis, which might provide better treatment strategies and tailored therapies. Accordingly, we analyzed the publicly available RNA-seq data of synovium tissue from 151 RA patients and 28 healthy controls and were able to identify 37 recurrent chimeric RNAs found to be expressed in at least 3 RA samples. Furthermore, the parental genes of these 37 recurrent chimeric RNAs were found to be differentially expressed and enriched in immune-related processes, such as adaptive immune response and the positive regulation of B-cell activation. Interestingly, the appearance of 5 coding and 23 non-coding chimeric RNAs might be associated with regulating their parental gene expression, leading to the generation of dysfunctional immune responses, such as inflammation and bone destruction. Therefore, in this paper, we present the first study to demonstrate the novel chimeric RNAs that are highly expressed and functional in RA.

Non-Canonical Splicing and Its Implications in Brain Physiology and Cancer

The advance of experimental and computational techniques has allowed us to highlight the existence of numerous different mechanisms of RNA maturation, which have been so far unknown. Besides canonical splicing, consisting of the removal of introns from pre-mRNA molecules, non-canonical splicing events may occur to further increase the regulatory and coding potential of the human genome. Among these, splicing of microexons, recursive splicing and biogenesis of circular and chimeric RNAs through back-splicing and trans-splicing processes, respectively, all contribute to expanding the repertoire of RNA transcripts with newly acquired regulatory functions. Interestingly, these non-canonical splicing events seem to occur more frequently in the central nervous system, affecting neuronal development and differentiation programs with important implications on brain physiology. Coherently, dysregulation of non-canonical RNA processing events is associated with brain disorders, including brain tumours. Herein, we summarize the current knowledge on molecular and regulatory mechanisms underlying canonical and non-canonical splicing events with particular emphasis on cis-acting elements and trans-acting factors that all together orchestrate splicing catalysis reactions and decisions. Lastly, we review the impact of non-canonical splicing on brain physiology and pathology and how unconventional splicing mechanisms may be targeted or exploited for novel therapeutic strategies in cancer.

Genion, an accurate tool to detect gene fusion from long transcriptomics reads

BACKGROUND

The advent of next-generation sequencing technologies empowered a wide variety of transcriptomics studies. A widely studied topic is gene fusion which is observed in many cancer types and suspected of having oncogenic properties. Gene fusions are the result of structural genomic events that bring two genes closely located and result in a fused transcript. This is different from fusion transcripts created during or after the transcription process. These chimeric transcripts are also known as read-through and trans-splicing transcripts. Gene fusion discovery with short reads is a well-studied problem, and many methods have been developed. But the sensitivity of these methods is limited by the technology, especially the short read length. Advances in long-read sequencing technologies allow the generation of long transcriptomics reads at a low cost. Transcriptomic long-read sequencing presents unique opportunities to overcome the shortcomings of short-read technologies for gene fusion detection while introducing new challenges.

RESULTS

We present Genion, a sensitive and fast gene fusion detection method that can also detect read-through events. We compare Genion against a recently introduced long-read gene fusion discovery method, LongGF, both on simulated and real datasets. On simulated data, Genion accurately identifies the gene fusions and its clustering accuracy for detecting fusion reads is better than LongGF. Furthermore, our results on the breast cancer cell line MCF-7 show that Genion correctly identifies all the experimentally validated gene fusions.

CONCLUSIONS

Genion is an accurate gene fusion caller. Genion is implemented in C++ and is available at https://github.com/vpc-ccg/genion .

FPIA: A database for gene fusion profiling and interactive analyses

As one of the hallmarks of cancer, gene fusions play an important role in tumorigenesis, and have been established as biomarkers and therapeutic targets. Although recent years have witnessed the development of gene fusion databases, a tool with interactive analytic functions is still lacking. Here, we introduce FPIA (Fusion Profiling Interactive Analysis), a web server to perform interactive and customizable analysis on fusion genes. With this platform, researchers can easily explore fusion-associated biological and molecular differences including gene expression, tumor purity and ploidy, mutation, copy number variations, protein expression, immune cell infiltration, stemness, telomere length, microsatellite instability, survival, and novel peptides based on 33 cancer types from TCGA data. Currently, it contains 31 633 fusion events from 6910 patients. FPIA complements the existing gene fusion annotation databases with its multi-omics analytic capacity, integrated analysis features, customized analysis selection, and user-friendly design. The comprehensive data analyses by FPIA will greatly facilitate data mining, hypothesis generation, and therapeutic target discovery. FPIA is available at http://bioinfo-sysu.com/fpia.

Computational analysis of sense-antisense chimeric transcripts reveals their potential regulatory features and the landscape of expression in human cells

Many human genes are transcribed from both strands and produce sense-antisense gene pairs. Sense-antisense (SAS) chimeric transcripts are produced upon the coalescing of exons/introns from both sense and antisense transcripts of the same gene. SAS chimera was first reported in prostate cancer cells. Subsequently, numerous SAS chimeras have been reported in the ChiTaRS-2.1 database. However, the landscape of their expression in human cells and functional aspects are still unknown. We found that longer palindromic sequences are a unique feature of SAS chimeras. Structural analysis indicates that a long hairpin-like structure formed by many consecutive Watson-Crick base pairs appears because of these long palindromic sequences, which possibly play a similar role as double-stranded RNA (dsRNA), interfering with gene expression. RNA-RNA interaction analysis suggested that SAS chimeras could significantly interact with their parental mRNAs, indicating their potential regulatory features. Here, 267 SAS chimeras were mapped in RNA-seq data from 16 healthy human tissues, revealing their expression in normal cells. Evolutionary analysis suggested the positive selection favoring sense-antisense fusions that significantly impacted the evolution of their function and structure. Overall, our study provides detailed insight into the expression landscape of SAS chimeras in human cells and identifies potential regulatory features.

Emerging Role of Chimeric RNAs in Cell Plasticity and Adaptive Evolution of Cancer Cells

Gene fusions can give rise to somatic alterations in cancers. Fusion genes have the potential to create chimeric RNAs, which can generate the phenotypic diversity of cancer cells, and could be associated with novel molecular functions related to cancer cell survival and proliferation. The expression of chimeric RNAs in cancer cells might impact diverse cancer-related functions, including loss of apoptosis and cancer cell plasticity, and promote oncogenesis. Due to their recurrence in cancers and functional association with oncogenic processes, chimeric RNAs are considered biomarkers for cancer diagnosis. Several recent studies demonstrated that chimeric RNAs could lead to the generation of new functionality for the resistance of cancer cells against drug therapy. Therefore, targeting chimeric RNAs in drug resistance cancer could be useful for developing precision medicine. So, understanding the functional impact of chimeric RNAs in cancer cells from an evolutionary perspective will be helpful to elucidate cancer evolution, which could provide a new insight to design more effective therapies for cancer patients in a personalized manner.

Potential role of chimeric genes in pathway-related gene co-expression modules

Background

Gene fusion has epigenetic modification functions. The novel proteins encoded by gene fusion products play a role in cancer development. Therefore, a better understanding of the novel protein products may provide insights into the pathogenesis of tumors. However, the characteristics of chimeric genes are rarely studied. Here, we used weighted co-expression network analysis to investigate the biological roles and underlying mechanisms of chimeric genes.

Methods

Download the pig transcriptome data, we screened chimeric genes and parental genes from 688 sequences and 153 samples, predict their domains, and analyze their associations. We constructed a co-expression network of chimeric genes in pigs and conducted Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis on the generated modules using DAVID to identify key networks and modules related to chimeric genes.

Results

Our findings showed that most of the protein domains of chimeric genes were derived from fused pre-genes. Chimeric genes were enriched in modules involved in the negative regulation of cell proliferation and protein localization to centrosomes. In addition, the chimeric genes were related to the growth factor-β superfamily, which regulates cell growth and differentiation. Furthermore, in helper T cells, chimeric genes regulate the specific recognition of T cell receptors, implying that chimeric genes play a key role in the regulation pathway of T cells. Chimeric genes can produce new domains, and some chimeric genes are a key role involved in pathway-related function.

Conclusions

Most chimeric genes show binding activity. Domains of chimeric genes are derived from several combinations of parent genes. Chimeric genes play a key role in the regulation of several cellular pathways. Our findings may provide new directions to explore the roles of chimeric genes in tumors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02248-9.

Chimeric RNA ASTN2-PAPPAas aggravates tumor progression and metastasis in human esophageal cancer

Transcription-induced chimeric RNAs are an emerging area of research into molecular signatures for disease biomarker and therapeutic target development. Despite their importance, little is known for chimeric RNAs-relevant roles and the underlying mechanisms for cancer pathogenesis and progression. Here we describe a unique ASTN2-PAPPA_antisense chimeric RNA (A-P_aschiRNA) that could be the first reported chimeric RNA derived from the splicing of exons and intron antisense of two neighboring genes, respectively. Aberrant A-P_aschiRNA level in ESCC tissues was associated with tumor progression and patients' outcome. In vitro and in vivo studies demonstrated that A-P_aschiRNA aggravated ESCC metastasis and enhanced stemness through modulating OCT4. Mechanistic studies demonstrated that ERK5-mediated non-canonical PAF1 activity was required for A-P_aschiRNA-induced cancer malignancy. The study defined an undocumented function of chimeric RNAs in aggravating cancer stemness and metastasis.

Fusion Genes and RNAs in Cancer Development

Fusion RNAs are a hallmark of some cancers. They result either from chromosomal rearrangements or from splicing mechanisms that are non-chromosomal rearrangements. Chromosomal rearrangements that result in gene fusions are particularly prevalent in sarcomas and hematopoietic malignancies; they are also common in solid tumors. The splicing process can also give rise to more complex RNA patterns in cells. Gene fusions frequently affect tyrosine kinases, chromatin regulators, or transcription factors, and can cause constitutive activation, enhancement of downstream signaling, and tumor development, as major drivers of oncogenesis. In addition, some fusion RNAs have been shown to function as noncoding RNAs and to affect cancer progression. Fusion genes and RNAs will therefore become increasingly important as diagnostic and therapeutic targets for cancer development. Here, we discuss the function, biogenesis, detection, clinical relevance, and therapeutic implications of oncogenic fusion genes and RNAs in cancer development. Further understanding the molecular mechanisms that regulate how fusion RNAs form in cancers is critical to the development of therapeutic strategies against tumorigenesis.

annoFuse: an R Package to annotate, prioritize, and interactively explore putative oncogenic RNA fusions

BACKGROUND

Gene fusion events are significant sources of somatic variation across adult and pediatric cancers and are some of the most clinically-effective therapeutic targets, yet low consensus of RNA-Seq fusion prediction algorithms makes therapeutic prioritization difficult. In addition, events such as polymerase read-throughs, mis-mapping due to gene homology, and fusions occurring in healthy normal tissue require informed filtering, making it difficult for researchers and clinicians to rapidly discern gene fusions that might be true underlying oncogenic drivers of a tumor and in some cases, appropriate targets for therapy.

RESULTS

We developed annoFuse, an R package, and shinyFuse, a companion web application, to annotate, prioritize, and explore biologically-relevant expressed gene fusions, downstream of fusion calling. We validated annoFuse using a random cohort of TCGA RNA-Seq samples (N = 160) and achieved a 96% sensitivity for retention of high-confidence fusions (N = 603). annoFuse uses FusionAnnotator annotations to filter non-oncogenic and/or artifactual fusions. Then, fusions are prioritized if previously reported in TCGA and/or fusions containing gene partners that are known oncogenes, tumor suppressor genes, COSMIC genes, and/or transcription factors. We applied annoFuse to fusion calls from pediatric brain tumor RNA-Seq samples (N = 1028) provided as part of the Open Pediatric Brain Tumor Atlas (OpenPBTA) Project to determine recurrent fusions and recurrently-fused genes within different brain tumor histologies. annoFuse annotates protein domains using the PFAM database, assesses reciprocality, and annotates gene partners for kinase domain retention. As a standard function, reportFuse enables generation of a reproducible R Markdown report to summarize filtered fusions, visualize breakpoints and protein domains by transcript, and plot recurrent fusions within cohorts. Finally, we created shinyFuse for algorithm-agnostic interactive exploration and plotting of gene fusions.

CONCLUSIONS

annoFuse provides standardized filtering and annotation for gene fusion calls from STAR-Fusion and Arriba by merging, filtering, and prioritizing putative oncogenic fusions across large cancer datasets, as demonstrated here with data from the OpenPBTA project. We are expanding the package to be widely-applicable to other fusion algorithms and expect annoFuse to provide researchers a method for rapidly evaluating, prioritizing, and translating fusion findings in patient tumors.

RNA sequencing: new technologies and applications in cancer research

Over the past few decades, RNA sequencing has significantly progressed, becoming a paramount approach for transcriptome profiling. The revolution from bulk RNA sequencing to single-molecular, single-cell and spatial transcriptome approaches has enabled increasingly accurate, individual cell resolution incorporated with spatial information. Cancer, a major malignant and heterogeneous lethal disease, remains an enormous challenge in medical research and clinical treatment. As a vital tool, RNA sequencing has been utilized in many aspects of cancer research and therapy, including biomarker discovery and characterization of cancer heterogeneity and evolution, drug resistance, cancer immune microenvironment and immunotherapy, cancer neoantigens and so on. In this review, the latest studies on RNA sequencing technology and their applications in cancer are summarized, and future challenges and opportunities for RNA sequencing technology in cancer applications are discussed.

Fusion genes as biomarkers in pediatric cancers: A review of the current state and applicability in diagnostics and personalized therapy

The incidence of pediatric cancers is rising steadily across the world, along with the challenges in understanding the molecular mechanisms and devising effective therapeutic strategies. Pediatric cancers are presented with diverse molecular characteristics and more distinct subtypes when compared to adult cancers. Recent studies on the genomic landscape of pediatric cancers using next-generation sequencing (NGS) approaches have redefined this field by providing better subtype characterization and novel actionable targets. Since early identification and personalized treatment strategies influence therapeutic outcomes, survival, and quality of life in pediatric cancer patients, the quest for actionable biomarkers is of great value in this field. Fusion genes that are prevalent and recurrent in several pediatric cancers are ideally suited in this context due to their disease-specific occurrence. In this review, we explore the current status of fusion genes in pediatric cancer subtypes and their use as biomarkers for diagnosis and personalized therapy. We discuss the technological advancements made in recent years in NGS sequencing and their impact on fusion detection algorithms that have revolutionized this field. Finally, we also discuss the advantages of pairing liquid biopsy protocols for fusion detection and their eventual use in diagnosis and treatment monitoring.

Blockade of IGF/IGF-1R signaling axis with soluble IGF-1R mutants suppresses the cell proliferation and tumor growth of human osteosarcoma

Primary bone tumor, also known as osteosarcoma (OS), is the most common primary malignancy of bone in children and young adults. Current treatment protocols yield a 5-year survival rate of near 70% although approximately 80% of patients have metastatic disease at the time of diagnosis. However, long-term survival rates have remained virtually unchanged for nearly four decades, largely due to our limited understanding of the disease process. One major signaling pathway that has been implicated in human OS tumorigenesis is the insulin-like growth factor (IGF)/insulin-like growth factor-1 receptor (IGF1R) signaling axis. IGF1R is a heterotetrameric α2β2 receptor, in which the α subunits comprise the ligand binding site, whereas the β subunits are transmembrane proteins containing intracellular tyrosine kinase domains. Although numerous strategies have been devised to target IGF/IGF1R axis, most of them have failed in clinical trials due to the lack of specificity and/or limited efficacy. Here, we investigated whether a more effective and specific blockade of IGF1R activity in human OS cells can be accomplished by employing dominant-negative IGF1R (dnIGF1R) mutants. We engineered the recombinant adenoviruses expressing two IGF1R mutants derived from the α (aa 1-524) and β (aa 741-936) subunits, and found that either dnIGF1Rα and/or dnIGF1Rβ effectively inhibited cell migration, colony formation, and cell cycle progression of human OS cells, which could be reversed by exogenous IGF1. Furthermore, dnIGF1Rα and/or dnIGF1Rβ inhibited OS xenograft tumor growth in vivo, with the greatest inhibition of tumor growth shown by dnIGF1Rα. Mechanistically, the dnIGF1R mutants down-regulated the expression of PI3K/AKT and RAS/RAF/MAPK, BCL2, Cyclin D1 and most EMT regulators, while up-regulating pro-apoptotic genes in human OS cells. Collectively, these findings strongly suggest that the dnIGF1R mutants, especially dnIGF1Rα, may be further developed as novel anticancer agents that target IGF signaling axis with high specificity and efficacy.

RNA structures in alternative splicing and back-splicing

Alternative splicing greatly expands the transcriptomic and proteomic diversities related to physiological and developmental processes in higher eukaryotes. Splicing of long noncoding RNAs, and back- and trans- splicing further expanded the regulatory repertoire of alternative splicing. RNA structures were shown to play an important role in regulating alternative splicing and back-splicing. Application of novel sequencing technologies made it possible to identify genome-wide RNA structures and interaction networks, which might provide new insights into RNA splicing regulation in vitro to in vivo. The emerging transcription-folding-splicing paradigm is changing our understanding of RNA alternative splicing regulation. Here, we review the insights into the roles and mechanisms of RNA structures in alternative splicing and back-splicing, as well as how disruption of these structures affects alternative splicing and then leads to human diseases. This article is categorized under: RNA Processing > Splicing Regulation/Alternative Splicing RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.