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Mohammad T, Zolotovskaia MA, Suntsova MV, Buzdin AA. Cancer fusion transcripts with human non-coding RNAs. Front Oncol 2024; 14:1415801. [PMID: 38919532 PMCID: PMC11196610 DOI: 10.3389/fonc.2024.1415801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 05/27/2024] [Indexed: 06/27/2024] Open
Abstract
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.
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Affiliation(s)
- Tharaa Mohammad
- Laboratory for Translational and Genomic Bioinformatics, Moscow Center for Advanced Studies, Moscow, Russia
- Department of Molecular Genetic Technologies, Laboratory of Bioinformatics, Endocrinology Research Center, Moscow, Russia
| | - Marianna A. Zolotovskaia
- Laboratory for Translational and Genomic Bioinformatics, Moscow Center for Advanced Studies, Moscow, Russia
- Department of Molecular Genetic Technologies, Laboratory of Bioinformatics, Endocrinology Research Center, Moscow, Russia
- I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | | | - Anton A. Buzdin
- Laboratory for Translational and Genomic Bioinformatics, Moscow Center for Advanced Studies, Moscow, Russia
- Department of Molecular Genetic Technologies, Laboratory of Bioinformatics, Endocrinology Research Center, Moscow, Russia
- I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- PathoBiology Group, European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
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2
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Gao G, McClellan J, Barbeira AN, Fiorica PN, Li JL, Mu Z, Olopade OI, Huo D, Im HK. A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer. Am J Hum Genet 2024; 111:1100-1113. [PMID: 38733992 PMCID: PMC11179262 DOI: 10.1016/j.ajhg.2024.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 04/13/2024] [Accepted: 04/15/2024] [Indexed: 05/13/2024] Open
Abstract
Splicing-based transcriptome-wide association studies (splicing-TWASs) of breast cancer have the potential to identify susceptibility genes. However, existing splicing-TWASs test the association of individual excised introns in breast tissue only and thus have limited power to detect susceptibility genes. In this study, we performed a multi-tissue joint splicing-TWAS that integrated splicing-TWAS signals of multiple excised introns in each gene across 11 tissues that are potentially relevant to breast cancer risk. We utilized summary statistics from a meta-analysis that combined genome-wide association study (GWAS) results of 424,650 women of European ancestry. Splicing-level prediction models were trained in GTEx (v.8) data. We identified 240 genes by the multi-tissue joint splicing-TWAS at the Bonferroni-corrected significance level; in the tissue-specific splicing-TWAS that combined TWAS signals of excised introns in genes in breast tissue only, we identified nine additional significant genes. Of these 249 genes, 88 genes in 62 loci have not been reported by previous TWASs, and 17 genes in seven loci are at least 1 Mb away from published GWAS index variants. By comparing the results of our splicing-TWASs with previous gene-expression-based TWASs that used the same summary statistics and expression prediction models trained in the same reference panel, we found that 110 genes in 70 loci that are identified only by the splicing-TWASs. Our results showed that for many genes, expression quantitative trait loci (eQTL) did not show a significant impact on breast cancer risk, whereas splicing quantitative trait loci (sQTL) showed a strong impact through intron excision events.
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Affiliation(s)
- Guimin Gao
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Julian McClellan
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Alvaro N Barbeira
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Peter N Fiorica
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - James L Li
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Zepeng Mu
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Olufunmilayo I Olopade
- Section of Hematology and Oncology, Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA; Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA.
| | - Hae Kyung Im
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA.
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3
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Firouzabadi ED, Allami M, Mohammed EJ, Barzegar H, Dastpak M, Alemohammad R, Moghimi V, Mahmoudian RA, Nasrabadi F, Arghiani N, Kitamura Y, Hosseini SA, Ghasemi A, Farshchian M. Detection of novel PPP1R1B::STARD3 fusion transcript in acute myeloid leukemia: a case report. J Med Case Rep 2024; 18:269. [PMID: 38835078 PMCID: PMC11151611 DOI: 10.1186/s13256-024-04536-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 03/22/2024] [Indexed: 06/06/2024] Open
Abstract
BACKGROUND Acute myeloid leukemia (AML) is the second most common type of leukemia in children. Although prognostic and diagnostic tests of AML patients have improved, there is still a great demand for new reliable clinical biomarkers for AML. Read-through fusion transcripts (RTFTs) are complex transcripts of adjacent genes whose molecular mechanisms are poorly understood. This is the first report of the presence of the PPP1R1B::STARD3 fusion transcript in an AML patient. Here, we investigated the presence of PPP1R1B::STARD3 RTFT in a case of AML using paired-end RNA sequencing (RNA-seq). CASE PRESENTATION A Persian 12-year-old male was admitted to Dr. Sheikh Hospital of Mashhad, Iran, in September 2019 with the following symptoms, including fever, convulsions, hemorrhage, and bone pain. The patient was diagnosed with AML (non-M3-FAB subtype) based on cell morphologies and immunophenotypical features. Chromosomal analysis using the G-banding technique revealed t (9;22) (q34;q13). CONCLUSIONS Single-cell RNA sequencing (scRNA-seq) analysis suggested that the PPP1R1B promoter may be responsible for the PPP1R1B::STARD3 expression. Alterations in the level of lipid metabolites implicate cancer development, and this fusion can play a crucial role in the cholesterol movement in cancer cells. PPP1R1B::STARD3 may be considered a candidate for targeted therapies of the cholesterol metabolic and the PI3K/AKT signaling pathways involved in cancer development and progression.
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Affiliation(s)
- Elahe Dehghani Firouzabadi
- Stem Cell and Regenerative Medicine Research Group, Academic Center for Education, Culture, and Research (ACECR), Mashhad, Razavi Khorasan, Iran
- Department of Biology, Faculty of Science, Hakim Sabzevar University, Sabzevar, Iran
| | - Mohammed Allami
- Department of Dentistry, Al-Manara College for Medical Sciences, Maysan, Iraq
- Department of Biology, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran
| | - Eman Jassim Mohammed
- Department of Biology, College of Science, Mustansiriyah University, Baghdad, Iraq
| | - Hossein Barzegar
- Stem Cell and Regenerative Medicine Research Group, Academic Center for Education, Culture, and Research (ACECR), Mashhad, Razavi Khorasan, Iran
| | - Mahtab Dastpak
- Department of Cell Biology, Harvard Medical School, 240 Longwood Ave, Boston, MA, 02115, USA
| | - Reza Alemohammad
- Stem Cell and Regenerative Medicine Research Group, Academic Center for Education, Culture, and Research (ACECR), Mashhad, Razavi Khorasan, Iran
| | - Vahid Moghimi
- Stem Cell and Regenerative Medicine Research Group, Academic Center for Education, Culture, and Research (ACECR), Mashhad, Razavi Khorasan, Iran
- Department of Biology, Faculty of Science, Hakim Sabzevar University, Sabzevar, Iran
| | - Reihaneh Alsadat Mahmoudian
- Basic Sciences Research Institute, Mashhad University of Medical Sciences, Mashhad, Iran
- Cancer Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Fatemeh Nasrabadi
- Stem Cell and Regenerative Medicine Research Group, Academic Center for Education, Culture, and Research (ACECR), Mashhad, Razavi Khorasan, Iran
| | - Nahid Arghiani
- Department of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University, Stockholm, Sweden
- Department of Biochemistry and Biomedicine, School of Life Sciences, University of Sussex, Brighton, UK
| | - Yohei Kitamura
- Department of Neurosurgery, Keio University School of Medicine, Tokyo, Japan
| | | | - Ali Ghasemi
- Department of Pediatrics Hematology and Oncology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Moein Farshchian
- Stem Cell and Regenerative Medicine Research Group, Academic Center for Education, Culture, and Research (ACECR), Mashhad, Razavi Khorasan, Iran.
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4
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Singh S, Shi X, Haddox S, Elfman J, Ahmad SB, Lynch S, Manley T, Piczak C, Phung C, Sun Y, Sharma A, Li H. RTCpredictor: identification of read-through chimeric RNAs from RNA sequencing data. Brief Bioinform 2024; 25:bbae251. [PMID: 38796690 PMCID: PMC11128028 DOI: 10.1093/bib/bbae251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 03/30/2024] [Accepted: 05/09/2024] [Indexed: 05/28/2024] Open
Abstract
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.
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Affiliation(s)
- Sandeep Singh
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
| | - Xinrui Shi
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
| | - Samuel Haddox
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
| | - Justin Elfman
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
| | - Syed Basil Ahmad
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
| | - Sarah Lynch
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
| | - Tommy Manley
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
| | - Claire Piczak
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
| | - Christopher Phung
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
| | - Yunan Sun
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
| | - Aadi Sharma
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
| | - Hui Li
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States
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5
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Dondi A, Lischetti U, Jacob F, Singer F, Borgsmüller N, Coelho R, Heinzelmann-Schwarz V, Beisel C, Beerenwinkel N. Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer. Nat Commun 2023; 14:7780. [PMID: 38012143 PMCID: PMC10682465 DOI: 10.1038/s41467-023-43387-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 11/07/2023] [Indexed: 11/29/2023] Open
Abstract
Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read single-cell RNA sequencing (scRNA-seq) on clinical samples from three ovarian cancer patients presenting with omental metastasis and increase the PacBio sequencing depth to 12,000 reads per cell. Our approach captures 152,000 isoforms, of which over 52,000 were not previously reported. Isoform-level analysis accounting for non-coding isoforms reveals 20% overestimation of protein-coding gene expression on average. We also detect cell type-specific isoform and poly-adenylation site usage in tumor and mesothelial cells, and find that mesothelial cells transition into cancer-associated fibroblasts in the metastasis, partly through the TGF-β/miR-29/Collagen axis. Furthermore, we identify gene fusions, including an experimentally validated IGF2BP2::TESPA1 fusion, which is misclassified as high TESPA1 expression in matched short-read data, and call mutations confirmed by targeted NGS cancer gene panel results. With these findings, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine.
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Affiliation(s)
- Arthur Dondi
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Ulrike Lischetti
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland.
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031, Basel, Switzerland.
| | - Francis Jacob
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031, Basel, Switzerland
| | - Franziska Singer
- SIB Swiss Institute of Bioinformatics, Mattenstrasse 26, 4058, Basel, Switzerland
- ETH Zurich, NEXUS Personalized Health Technologies, Wagistrasse 18, 8952, Schlieren, Switzerland
| | - Nico Borgsmüller
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Ricardo Coelho
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031, Basel, Switzerland
| | - Viola Heinzelmann-Schwarz
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031, Basel, Switzerland
- University Hospital Basel, Gynecological Cancer Center, Spitalstrasse 21, 4031, Basel, Switzerland
| | - Christian Beisel
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland.
| | - Niko Beerenwinkel
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland.
- SIB Swiss Institute of Bioinformatics, Mattenstrasse 26, 4058, Basel, Switzerland.
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6
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Chen C, Qin F, Singh S, Tang Y, Li H. CTNNBIP1-CLSTN1 functions as a housekeeping chimeric RNA and regulates cell proliferation through SERPINE2. Cell Death Discov 2023; 9:369. [PMID: 37805599 PMCID: PMC10560238 DOI: 10.1038/s41420-023-01668-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 09/13/2023] [Accepted: 09/25/2023] [Indexed: 10/09/2023] Open
Abstract
The conventional understanding that chimeric RNAs are unique to carcinoma and are the products of chromosomal rearrangement is being challenged. However, experimental evidence supporting the function of chimeric RNAs in normal physiology is scarce. We decided to focus on one particular chimeric RNA, CTNNBIP1-CLSTN1. We examined its expression in various tissues and cell types and compared it quantitatively among cancer and noncancer cells. We further investigated its role in a panel of noncancer cells and investigated the functional mechanism. We found that this fusion transcript is expressed in almost all tissues and a wide range of cell types, including fibroblasts, epithelial cells, stem cells, vascular endothelial cells, and hepatocytes. In addition, the CTNNBIP1-CLSTN1 expression level in noncancerous cell lines was not evidently different from that in cancer cell lines. Furthermore, in at least three cell types, silencing CTNNBIP1-CLSTN1 significantly reduced the cell proliferation rate by inducing G2/M arrest and apoptosis. Importantly, rescue experiments confirmed that cell cycle arrest was restored by exogenous expression of the chimera but not the wild-type parental gene. Further evidence is provided that CTNNBIP1-CLSTN1 regulates cell proliferation through SERPINE2. Thus, CTNNBIP1-CLSTN1 is an example of a new class of fusion RNAs, dubbed "housekeeping chimeric RNAs".
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Affiliation(s)
- Chen Chen
- School of Basic Medical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, 450001, Henan, China
- Department of Clinical Laboratory, Qilu Hospital of Shandong University Dezhou Hospital, Dezhou, 253000, Shandong, China
| | - Fujun Qin
- School of Basic Medical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, 450001, Henan, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Sandeep Singh
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA, 22908, USA
- ICMR-Center for Research, Management and Control of Haemoglobinopathies (Unit of ICMR-National Institute of Immunohaematology, Mumbai), Chandrapur, Maharashtra, 442406, India
| | - Yue Tang
- School of Basic Medical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, 450001, Henan, China.
| | - Hui Li
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA, 22908, USA.
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7
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Mukherjee S, Mukherjee SB, Frenkel-Morgenstern M. Functional and regulatory impact of chimeric RNAs in human normal and cancer cells. WILEY INTERDISCIPLINARY REVIEWS. RNA 2023; 14:e1777. [PMID: 36633099 DOI: 10.1002/wrna.1777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 12/21/2022] [Accepted: 12/27/2022] [Indexed: 01/13/2023]
Abstract
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.
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Affiliation(s)
- Sumit Mukherjee
- Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
- Department of Computer Science, Ben-Gurion University, Beer-Sheva, Israel
- Cancer Data Science Laboratory (CDSL), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland, USA
| | - Sunanda Biswas Mukherjee
- Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Milana Frenkel-Morgenstern
- Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
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8
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Drazdauskienė U, Kapustina Ž, Medžiūnė J, Dubovskaja V, Sabaliauskaitė R, Jarmalaitė S, Lubys A. Fusion sequencing via terminator-assisted synthesis (FTAS-seq) identifies TMPRSS2 fusion partners in prostate cancer. Mol Oncol 2023; 17:993-1006. [PMID: 37300660 DOI: 10.1002/1878-0261.13428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 02/26/2023] [Accepted: 04/03/2023] [Indexed: 06/12/2023] Open
Abstract
Genetic rearrangements that fuse an androgen-regulated promoter area with a protein-coding portion of an originally androgen-unaffected gene are frequent in prostate cancer, with the fusion between transmembrane serine protease 2 (TMPRSS2) and ETS transcription factor ERG (ERG) (TMPRSS2-ERG fusion) being the most prevalent. Conventional hybridization- or amplification-based methods can test for the presence of expected gene fusions, but the exploratory analysis of currently unknown fusion partners is often cost-prohibitive. Here, we developed an innovative next-generation sequencing (NGS)-based approach for gene fusion analysis termed fusion sequencing via terminator-assisted synthesis (FTAS-seq). FTAS-seq can be used to enrich the gene of interest while simultaneously profiling the whole spectrum of its 3'-terminal fusion partners. Using this novel semi-targeted RNA-sequencing technique, we were able to identify 11 previously uncharacterized TMPRSS2 fusion partners and capture a range of TMPRSS2-ERG isoforms. We tested the performance of FTAS-seq with well-characterized prostate cancer cell lines and utilized the technique for the analysis of patient RNA samples. FTAS-seq chemistry combined with appropriate primer panels holds great potential as a tool for biomarker discovery that can support the development of personalized cancer therapies.
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Affiliation(s)
| | | | | | | | | | - Sonata Jarmalaitė
- National Cancer Institute, Vilnius, Lithuania
- Institute of Biosciences, Life Sciences Center, Vilnius University, Lithuania
| | - Arvydas Lubys
- Thermo Fisher Scientific Baltics, Vilnius, Lithuania
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9
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Singh S, Shi X, Ahmad SB, Manley T, Piczak C, Phung C, Sun Y, Lynch S, Sharma A, Li H. RTCpredictor: Identification of Read-Through Chimeric RNAs from RNA Sequencing Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.02.526869. [PMID: 36778443 PMCID: PMC9915620 DOI: 10.1101/2023.02.02.526869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
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.
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10
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Zhang L, Wang D, Han X, Guo X, Cao Y, Xia Y, Gao D. Novel read-through fusion transcript Bcl2l2-Pabpn1 in glioblastoma cells. J Cell Mol Med 2022; 26:4686-4697. [PMID: 35894779 PMCID: PMC9443946 DOI: 10.1111/jcmm.17481] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 03/11/2022] [Accepted: 06/19/2022] [Indexed: 11/29/2022] Open
Abstract
Read‐through fusion transcripts have recently been identified as chimeric RNAs and have since been linked to tumour growth in some cases. Many fusion genes generated by chromosomal rearrangements have been described in glioblastoma. However, read‐through fusion transcripts between neighbouring genes in glioblastoma remain unexplored. We performed paired‐end RNA‐seq of rat C6 glioma cells and normal cells and discovered a read‐through fusion transcript Bcl2l2‐Pabpn1 in which exon 3 of Bcl‐2‐like protein 2 (Bcl2l2) fused to exon 2 of Polyadenylate‐binding protein 1 (Pabpn1). This fusion transcript was found in both human glioblastoma and normal cells. Unlike other fusions reported in glioblastoma, Bcl2l2‐Pabpn1 appeared to result from RNA processing rather than genomic rearrangement. Bcl2l2‐Pabpn1 fusion transcript encoded a fusion protein with BH4, BCL and RRM domains. Functionally, Bcl2l2‐Pabpn1 knockdown by targeting its fusion junction decreased its expression, and suppressed cell proliferation, migration and invasion in vitro. Mechanistically, Bcl2l2‐Pabpn1 blocked Bax activity and activated PI3K/AKT pathway to promote glioblastoma progression. Together, our work characterized a glioblastoma‐associated Bcl2l2‐Pabpn1 fusion transcript shared by humans and rats.
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Affiliation(s)
- Lin Zhang
- Department of Neurobiology and Anatomy, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China.,School of Nursing, Xuzhou Medical University, Xuzhou, China
| | - Dan Wang
- School of Medical Information and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Xiao Han
- Nanjing Medical University, Nanjing, China
| | - Xiaoxiao Guo
- Department of Neurobiology and Anatomy, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China
| | - Yuanyuan Cao
- Department of Neurobiology and Anatomy, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China
| | - Ying Xia
- Department of Neurobiology and Anatomy, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China
| | - Dianshuai Gao
- Department of Neurobiology and Anatomy, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China
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11
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Regua AT, Najjar M, Lo HW. RET signaling pathway and RET inhibitors in human cancer. Front Oncol 2022; 12:932353. [PMID: 35957881 PMCID: PMC9359433 DOI: 10.3389/fonc.2022.932353] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Rearranged during transfection (RET) receptor tyrosine kinase was first identified over thirty years ago as a novel transforming gene. Since its discovery and subsequent pathway characterization, RET alterations have been identified in numerous cancer types and are most prevalent in thyroid carcinomas and non-small cell lung cancer (NSCLC). In other tumor types such as breast cancer and salivary gland carcinomas, RET alterations can be found at lower frequencies. Aberrant RET activity is associated with poor prognosis of thyroid and lung carcinoma patients, and is strongly correlated with increased risk of distant metastases. RET aberrations encompass a variety of genomic or proteomic alterations, most of which confer constitutive activation of RET. Activating RET alterations, such as point mutations or gene fusions, enhance activity of signaling pathways downstream of RET, namely PI3K/AKT, RAS/RAF, MAPK, and PLCγ pathways, to promote cell proliferation, growth, and survival. Given the important role that mutant RET plays in metastatic cancers, significant efforts have been made in developing inhibitors against RET kinase activity. These efforts have led to FDA approval of Selpercatinib and Pralsetinib for NSCLC, as well as, additional selective RET inhibitors in preclinical and clinical testing. This review covers the current biological understanding of RET signaling, the impact of RET hyperactivity on tumor progression in multiple tumor types, and RET inhibitors with promising preclinical and clinical efficacy.
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Affiliation(s)
- Angelina T. Regua
- Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Mariana Najjar
- Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Hui-Wen Lo
- Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, United States
- Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC, United States
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12
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Liu D, Li J, Hao W, Lin X, Xia J, Zhu J, Yang S, Yang X. Chimeric RNA TNNI2-ACTA1-V1 Regulates Cell Proliferation by Regulating the Expression of NCOA3. Front Vet Sci 2022; 9:895190. [PMID: 35898549 PMCID: PMC9309209 DOI: 10.3389/fvets.2022.895190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 06/15/2022] [Indexed: 11/13/2022] Open
Abstract
Chimeric RNA is a crucial target for tumor diagnosis and drug therapy, also having its unique biological role in normal tissues. TNNI2-ACTA1-V1 (TA-V1), a chimeric RNA discovered by our laboratory in porcine muscle tissue, can inhibit the proliferation of Porcine Skeletal Muscle Satellite Cells (PSCs). The regulatory mechanism of TA-V1 in PSCs remains unclear, but we speculate that NCOA3, DDR2 and RDX may be the target genes of TA-V1. In this study, we explored the effects of NCOA3, DDR2 and RDX on cell viability and cell proliferation by CCK-8 assay, EdU staining and flow cytometry. Furthermore, the regulatory pathway of proliferation in PSCs mediated by TA-V1 through NCOA3 or CyclinD1 was elucidated by co-transfection and co-immunoprecipitation (Co-IP). The results revealed that overexpression of NCOA3 significantly increased cell viability and the expression level of CyclinD1, and also promotes cell proliferation by changing cells from the G1 phase to the S phase. In addition, inhibiting the expression of NCOA3 substantially reduced cell viability and inhibited cell proliferation. Overexpression of DDR2 and RDX had no significant effect on cell viability and proliferation. Co-transfection experiments showed that NCOA3 could rescue the proliferation inhibition of PSCs caused by TA-V1. Co-IP assay indicated that TA-V1 directly interacts with NCOA3. Our study explores the hypothesis that TA-V1 directly regulates NCOA3, indirectly regulating CyclinD1, thereby regulating PSCs proliferation. We provide new putative mechanisms of porcine skeletal muscle growth and lay the foundation for the study of chimeric RNA in normal tissues.
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13
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Sun Y, Li H. Chimeric RNAs Discovered by RNA Sequencing and Their Roles in Cancer and Rare Genetic Diseases. Genes (Basel) 2022; 13:genes13050741. [PMID: 35627126 PMCID: PMC9140685 DOI: 10.3390/genes13050741] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 04/13/2022] [Accepted: 04/20/2022] [Indexed: 12/30/2022] Open
Abstract
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.
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Affiliation(s)
- Yunan Sun
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA;
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Hui Li
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA;
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
- Correspondence:
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14
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Lovino M, Montemurro M, Barrese VS, Ficarra E. Identifying the oncogenic potential of gene fusions exploiting miRNAs. J Biomed Inform 2022; 129:104057. [PMID: 35339665 DOI: 10.1016/j.jbi.2022.104057] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 03/14/2022] [Accepted: 03/15/2022] [Indexed: 12/11/2022]
Abstract
It is estimated that oncogenic gene fusions cause about 20% of human cancer morbidity. Identifying potentially oncogenic gene fusions may improve affected patients' diagnosis and treatment. Previous approaches to this issue included exploiting specific gene-related information, such as gene function and regulation. Here we propose a model that profits from the previous findings and includes the microRNAs in the oncogenic assessment. We present ChimerDriver, a tool to classify gene fusions as oncogenic or not oncogenic. ChimerDriver is based on a specifically designed neural network and trained on genetic and post-transcriptional information to obtain a reliable classification. The designed neural network integrates information related to transcription factors, gene ontologies, microRNAs and other detailed information related to the functions of the genes involved in the fusion and the gene fusion structure. As a result, the performances on the test set reached 0.83 f1-score and 96% recall. The comparison with state-of-the-art tools returned comparable or higher results. Moreover, ChimerDriver performed well in a real-world case where 21 out of 24 validated gene fusion samples were detected by the gene fusion detection tool Starfusion. ChimerDriver integrates transcriptional and post-transcriptional information in an ad-hoc designed neural network to effectively discriminate oncogenic gene fusions from passenger ones. ChimerDriver source code is freely available at https://github.com/martalovino/ChimerDriver.
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Affiliation(s)
- Marta Lovino
- University of Modena and Reggio Emilia, Via Vivarelli 10/1, 41125 Modena, Italy.
| | | | - Venere S Barrese
- Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino, Italy
| | - Elisa Ficarra
- University of Modena and Reggio Emilia, Via Vivarelli 10/1, 41125 Modena, Italy
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15
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The Fusion of CLEC12A and MIR223HG Arises from a trans-Splicing Event in Normal and Transformed Human Cells. Int J Mol Sci 2021; 22:ijms222212178. [PMID: 34830054 PMCID: PMC8625150 DOI: 10.3390/ijms222212178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 10/30/2021] [Accepted: 11/03/2021] [Indexed: 11/17/2022] Open
Abstract
Chimeric RNAs are often associated with chromosomal rearrangements in cancer. In addition, they are also widely detected in normal tissues, contributing to transcriptomic complexity. Despite their prevalence, little is known about the characteristics and functions of chimeric RNAs. Here, we examine the genetic structure and biological roles of CLEC12A-MIR223HG, a novel chimeric transcript produced by the fusion of the cell surface receptor CLEC12A and the miRNA-223 host gene (MIR223HG), first identified in chronic myeloid leukemia (CML) patients. Surprisingly, we observed that CLEC12A-MIR223HG is not just expressed in CML, but also in a variety of normal tissues and cell lines. CLEC12A-MIR223HG expression is elevated in pro-monocytic cells resistant to chemotherapy and during monocyte-to-macrophage differentiation. We observed that CLEC12A-MIR223HG is a product of trans-splicing rather than a chromosomal rearrangement and that transcriptional activation of CLEC12A with the CRISPR/Cas9 Synergistic Activation Mediator (SAM) system increases CLEC12A-MIR223HG expression. CLEC12A-MIR223HG translates into a chimeric protein, which largely resembles CLEC12A but harbours an altered C-type lectin domain altering key disulphide bonds. These alterations result in differences in post-translational modifications, cellular localization, and protein-protein interactions. Taken together, our observations support a possible involvement of CLEC12A-MIR223HG in the regulation of CLEC12A function. Our workflow also serves as a template to study other uncharacterized chimeric RNAs.
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16
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Zhou Y, El-Bahrawy M. Gene fusions in tumourigenesis with particular reference to ovarian cancer. J Med Genet 2021; 58:789-795. [PMID: 34462289 DOI: 10.1136/jmedgenet-2021-108010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 08/11/2021] [Indexed: 11/04/2022]
Abstract
Gene fusion, a genomic event that generates a novel gene from two independent genes, has long been known to be implicated in tumourigenesis and cancer progression. It has thus served as a diagnostic and prognostic biomarker in cancer, as well as an ideal therapeutic target in cancer therapy. Gene fusion can arise from chromosomal rearrangement and alternative splicing of transcripts, resulting in deregulation of proto-oncogenes or creation of an oncogenic novel gene. Largely facilitated by next generation sequencing technologies, a plethora of novel gene fusions have been identified in a variety of cancers, which leaves us the challenge of functionally characterising these candidate gene fusions. In this review, we summarise the molecular mechanisms, the oncogenic consequences and the therapeutic implications of verified gene fusions. We also discuss recent studies on gene fusions in both common and rare subtypes of ovarian tumours and how these findings can be translated to cancer therapies to benefit patients carrying these gene fusions.
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Affiliation(s)
- Yi Zhou
- Surgery and Cancer, Imperial College London, London, UK
| | - Mona El-Bahrawy
- Metabolism, Digestion and Reproduction, Imperial College London, London, UK .,Pathology, Alexandria University Faculty of Medicine, Alexandria, Egypt
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17
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Mukherjee S, Heng HH, Frenkel-Morgenstern M. Emerging Role of Chimeric RNAs in Cell Plasticity and Adaptive Evolution of Cancer Cells. Cancers (Basel) 2021; 13:4328. [PMID: 34503137 PMCID: PMC8431553 DOI: 10.3390/cancers13174328] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 08/22/2021] [Accepted: 08/23/2021] [Indexed: 12/12/2022] Open
Abstract
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.
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Affiliation(s)
- Sumit Mukherjee
- Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel;
| | - Henry H. Heng
- Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, MI 48201, USA;
- Department of Pathology, Wayne State University School of Medicine, Detroit, MI 48201, USA
| | - Milana Frenkel-Morgenstern
- Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel;
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18
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Wang Y, Zou Q, Li F, Zhao W, Xu H, Zhang W, Deng H, Yang X. Identification of the cross-strand chimeric RNAs generated by fusions of bi-directional transcripts. Nat Commun 2021; 12:4645. [PMID: 34330918 PMCID: PMC8324879 DOI: 10.1038/s41467-021-24910-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 07/14/2021] [Indexed: 12/22/2022] Open
Abstract
A major part of the transcriptome complexity is attributed to multiple types of DNA or RNA fusion events, which take place within a gene such as alternative splicing or between different genes such as DNA rearrangement and trans-splicing. In the present study, using the RNA deep sequencing data, we systematically survey a type of non-canonical fusions between the RNA transcripts from the two opposite DNA strands. We name the products of such fusion events cross-strand chimeric RNA (cscRNA). Hundreds to thousands of cscRNAs can be found in human normal tissues, primary cells, and cancerous cells, and in other species as well. Although cscRNAs exhibit strong tissue-specificity, our analysis identifies thousands of recurrent cscRNAs found in multiple different samples. cscRNAs are mostly originated from convergent transcriptions of the annotated genes and their anti-sense DNA. The machinery of cscRNA biogenesis is unclear, but the cross-strand junction events show some features related to RNA splicing. The present study is a comprehensive survey of the non-canonical cross-strand RNA junction events, a resource for further characterization of the originations and functions of the cscRNAs.
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Affiliation(s)
- Yuting Wang
- MOE Key Laboratory of Bioinformatics, Center for Synthetic & Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China.,Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Science, Beijing, China
| | - Qin Zou
- MOE Key Laboratory of Bioinformatics, Center for Synthetic & Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China
| | - Fajin Li
- MOE Key Laboratory of Bioinformatics, Center for Synthetic & Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China.,Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Science, Beijing, China
| | - Wenwei Zhao
- MOE Key Laboratory of Bioinformatics, Center for Synthetic & Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China
| | - Hui Xu
- MOE Key Laboratory of Bioinformatics, Center for Synthetic & Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China
| | - Wenhao Zhang
- MOE Key Laboratory of Bioinformatics, Center for Synthetic & Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China
| | - Haiteng Deng
- MOE Key Laboratory of Bioinformatics, Center for Synthetic & Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China
| | - Xuerui Yang
- MOE Key Laboratory of Bioinformatics, Center for Synthetic & Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China.
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19
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Quistgaard EM. BAP31: Physiological functions and roles in disease. Biochimie 2021; 186:105-129. [PMID: 33930507 DOI: 10.1016/j.biochi.2021.04.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 04/20/2021] [Accepted: 04/21/2021] [Indexed: 12/22/2022]
Abstract
B-cell receptor-associated protein 31 (BAP31 or BCAP31) is a ubiquitously expressed transmembrane protein found mainly in the endoplasmic reticulum (ER), including in mitochondria-associated membranes (MAMs). It acts as a broad-specificity membrane protein chaperone and quality control factor, which can promote different fates for its clients, including ER retention, ER export, ER-associated degradation (ERAD), or evasion of degradation, and it also acts as a MAM tetherer and regulatory protein. It is involved in several cellular processes - it supports ER and mitochondrial homeostasis, promotes proliferation and migration, plays several roles in metabolism and the immune system, and regulates autophagy and apoptosis. Full-length BAP31 can be anti-apoptotic, but can also mediate activation of caspase-8, and itself be cleaved by caspase-8 into p20-BAP31, which promotes apoptosis by mobilizing ER calcium stores at MAMs. BAP31 loss-of-function mutations is the cause of 'deafness, dystonia, and central hypomyelination' (DDCH) syndrome, characterized by severe neurological symptoms and early death. BAP31 is furthermore implicated in a growing number of cancers and other diseases, and several viruses have been found to target it to promote their survival or life cycle progression. The purpose of this review is to provide an overview and examination of the basic properties, functions, mechanisms, and roles in disease of BAP31.
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Affiliation(s)
- Esben M Quistgaard
- Department of Molecular Biology and Genetics - DANDRITE, Aarhus University, Gustav Wieds Vej 10, DK-8000 Aarhus C, Denmark.
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20
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Fusion transcript discovery using RNA sequencing in formalin-fixed paraffin-embedded specimen. Crit Rev Oncol Hematol 2021; 160:103303. [DOI: 10.1016/j.critrevonc.2021.103303] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 03/15/2021] [Accepted: 03/16/2021] [Indexed: 02/07/2023] Open
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21
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Maspero D, Dassano A, Pintarelli G, Noci S, De Cecco L, Incarbone M, Tosi D, Santambrogio L, Dragani TA, Colombo F. Read-through transcripts in lung: germline genetic regulation and correlation with the expression of other genes. Carcinogenesis 2021; 41:918-926. [PMID: 32157280 DOI: 10.1093/carcin/bgaa020] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 01/24/2020] [Accepted: 03/06/2020] [Indexed: 11/14/2022] Open
Abstract
Transcripts originating from the transcriptional read through of two adjacent, similarly oriented genes have been identified in normal and neoplastic tissues, but their functional role and the mechanisms that regulate their expression are mostly unknown. Here, we investigated whether the expression of read-through transcripts previously identified in the non-involved lung tissue of lung adenocarcinoma patients was genetically regulated. Data on genome-wide single nucleotide variant genotypes and expression levels of 10 read-through transcripts in 201 samples of lung tissue were combined to identify expression quantitative trait loci (eQTLs). Then, to identify genes whose expression levels correlated with the 10 read-through transcripts, we used whole transcriptome profiles available for 154 patients. For 8 read-though transcripts, we identified 60 eQTLs (false discovery rate <0.05), including 17 cis-eQTLs and 43 trans-eQTLs. These eQTLs did not maintain their behavior on the 'parental' genes involved in the read-through transcriptional event. The expression levels of 7 read-through transcripts were found to correlate with the expression of other genes: CHIA-PIFO and CTSC-RAB38 correlated with CHIA and RAB38, respectively, while 5 other read-through transcripts correlated with 43 unique non-parental transcripts; thus offering indications about the molecular processes in which these chimeric transcripts may be involved. We confirmed 9 eQTLs (for 4 transcripts) in the non-involved lung tissue from an independent series of 188 lung adenocarcinoma patients. Therefore, this study indicates that the expression of four read-through transcripts in normal lung tissue is under germline genetic regulation, and that this regulation is independent of that of the genes involved in the read-through event.
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Affiliation(s)
- Davide Maspero
- Genetic Epidemiology and Pharmacogenomics Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.,Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy
| | - Alice Dassano
- Genetic Epidemiology and Pharmacogenomics Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Giulia Pintarelli
- Genetic Epidemiology and Pharmacogenomics Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Sara Noci
- Genetic Epidemiology and Pharmacogenomics Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Loris De Cecco
- Platform of Integrated Biology, Department of Applied Research and Technology Development, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Matteo Incarbone
- Department of Surgery, IRCCS Multimedica, Sesto S. Giovanni, Milan, Italy
| | - Davide Tosi
- Department of Surgery, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Università degli Studi di Milano, Milan, Italy
| | - Luigi Santambrogio
- Department of Surgery, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Università degli Studi di Milano, Milan, Italy
| | - Tommaso A Dragani
- Genetic Epidemiology and Pharmacogenomics Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Francesca Colombo
- Genetic Epidemiology and Pharmacogenomics Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
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22
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Taniue K, Akimitsu N. Fusion Genes and RNAs in Cancer Development. Noncoding RNA 2021; 7:10. [PMID: 33557176 PMCID: PMC7931065 DOI: 10.3390/ncrna7010010] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 02/02/2021] [Accepted: 02/03/2021] [Indexed: 02/07/2023] Open
Abstract
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.
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Affiliation(s)
- Kenzui Taniue
- Isotope Science Center, The University of Tokyo, 2-11-16, Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan
- Cancer Genomics and Precision Medicine, Division of Gastroenterology and Hematology/Oncology, Department of Medicine, Asahikawa Medical University, 2-1 Midorigaoka Higashi, Asahikawa, Hokkaido 078-8510, Japan
| | - Nobuyoshi Akimitsu
- Isotope Science Center, The University of Tokyo, 2-11-16, Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan
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23
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Liu CC, Veeraraghavan J, Tan Y, Kim JA, Wang X, Loo SK, Lee S, Hu Y, Wang XS. A Novel Neoplastic Fusion Transcript, RAD51AP1-DYRK4, Confers Sensitivity to the MEK Inhibitor Trametinib in Aggressive Breast Cancers. Clin Cancer Res 2021; 27:785-798. [PMID: 33172895 PMCID: PMC7934498 DOI: 10.1158/1078-0432.ccr-20-2769] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 09/18/2020] [Accepted: 11/04/2020] [Indexed: 01/19/2023]
Abstract
PURPOSE Luminal B breast tumors are more aggressive estrogen receptor-positive (ER+) breast cancers characterized by aggressive clinical behavior and a high risk of metastatic dissemination. The underlying pathologic molecular events remain poorly understood with a paucity of actionable genetic drivers, which hinders the development of new treatment strategies. EXPERIMENTAL DESIGN We performed large-scale RNA sequencing analysis to identify chimerical transcripts preferentially expressed in luminal B breast cancer. The lead candidate was validated by reverse transcription PCR in breast cancer tissues. The effects of inducible ectopic expression or genetic silencing were assessed by phenotypic assays such as MTS, transwell, and transendothelial migration assays, and by clonogenic assays to assess MEK inhibitor sensitivity. Subcellular fractionation, Western blots, and immunoprecipitation were performed to characterize the protein products and elucidate the engaged mechanisms. RESULTS Here we report a novel tumor-specific chimeric transcript RAD51AP1-DYRK4 preferentially expressed in luminal B tumors. Analysis of 200 ER+ breast tumors detected RAD51AP1-DYRK4 overexpression in 19 tumors (9.5%), which is markedly enriched in the luminal B tumors (17.5%). Ectopic expression of RAD51AP1-DYRK4, but not wild-type RAD51AP1, leads to marked activation of MEK/ERK signaling, and endows increased cell motility and transendothelial migration. More importantly, RAD51AP1-DYRK4 appears to endow increased sensitivity to the MEK inhibitor trametinib through attenuating compensatory activation of HER2/PI3K/AKT under MEK inhibition. CONCLUSIONS This discovery sheds light on a new area of molecular pathobiology of luminal B tumors and implies potential new therapeutic opportunities for more aggressive breast tumors overexpressing this fusion.
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Affiliation(s)
- Chia-Chia Liu
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jamunarani Veeraraghavan
- Lester & Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas
- Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Ying Tan
- Lester & Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas
- Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Jin-Ah Kim
- Lester & Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas
- Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Xian Wang
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
- Lester & Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas
- Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Suet Kee Loo
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Sanghoon Lee
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Yiheng Hu
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
- Lester & Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas
- Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Xiao-Song Wang
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania.
- Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
- Lester & Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas
- Department of Medicine, Baylor College of Medicine, Houston, Texas
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24
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Chen W, Cui W, Qiu Y, Cui D. Research Progress of Chimeric RNA and Health. Health (London) 2021. [DOI: 10.4236/health.2021.134036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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25
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Minati R, Perreault C, Thibault P. A Roadmap Toward the Definition of Actionable Tumor-Specific Antigens. Front Immunol 2020; 11:583287. [PMID: 33424836 PMCID: PMC7793940 DOI: 10.3389/fimmu.2020.583287] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 10/30/2020] [Indexed: 12/15/2022] Open
Abstract
The search for tumor-specific antigens (TSAs) has considerably accelerated during the past decade due to the improvement of proteogenomic detection methods. This provides new opportunities for the development of novel antitumoral immunotherapies to mount an efficient T cell response against one or multiple types of tumors. While the identification of mutated antigens originating from coding exons has provided relatively few TSA candidates, the possibility of enlarging the repertoire of targetable TSAs by looking at antigens arising from non-canonical open reading frames opens up interesting avenues for cancer immunotherapy. In this review, we outline the potential sources of TSAs and the mechanisms responsible for their expression strictly in cancer cells. In line with the heterogeneity of cancer, we propose that discrete families of TSAs may be enriched in specific cancer types.
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Affiliation(s)
- Robin Minati
- École Normale Supérieure de Lyon, Université Claude Bernard Lyon I, Université de Lyon, Lyon, France
- Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC, Canada
| | - Claude Perreault
- Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC, Canada
- Department of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Pierre Thibault
- Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC, Canada
- Department of Chemistry, Université de Montréal, Montréal, QC, Canada
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26
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Li Z, Yin C, Li B, Yu QY, Mao WJ, Li J, Lin JP, Meng YQ, Feng HM, Jing T. DUS4L Silencing Suppresses Cell Proliferation and Promotes Apoptosis in Human Lung Adenocarcinoma Cell Line A549. Cancer Manag Res 2020; 12:9905-9913. [PMID: 33116848 PMCID: PMC7553766 DOI: 10.2147/cmar.s265671] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Accepted: 09/17/2020] [Indexed: 12/25/2022] Open
Abstract
Purpose This study aims to investigate the potential role of DUS4L (dihydrouridine synthase 4 like) in lung adenocarcinoma (LUAD) and explore its associated pathways in human LUAD. Methods Firstly, we evaluated the relationships between clinicopathological characteristics and DUS4L expression via analysis of TCGA RNA sequencing data and other publicly available databases. Then, DUS4L was effectively silenced in LUAD cell line A549 using the lentiviral shRNA (short-hairpin RNA) transfection to assess its effects on cell proliferation, cycle and apoptosis in LUAD cells. RNA-seq technology was applied to shDUS4L and shCtrl-transfected cells to generate the corresponding gene expression profiles. Differentially expressed genes (DEGs) were identified using the DESeq2 program package. Also, DEGs were subjected to Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis to explore the associated molecular signaling pathways and relevant biological functions. Results Analysis of TCGA data revealed that DUS4L was highly upregulated in LUAD tissues which was related to clinical T and TNM stages of LUAD. The knockdown of DUS4L effectively inhibited cell proliferation and promoted apoptosis in A549 cells. Furthermore, the DEGs between the shDUS4L and shCtrl A549 cells were mainly enriched in biological processes associated with spliceosome, ribosome, RNA catabolic process, ncRNA (non-coding RNA) processing, and p53 signaling pathway. Conclusion Altogether, our results suggest that DUS4L is significantly associated with tumorigenesis and could be utilized as a novel biomarker and therapeutic target for LUAD.
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Affiliation(s)
- Zheng Li
- Department of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, Lanzhou 730030, People's Republic of China
| | - Ci Yin
- Department of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, Lanzhou 730030, People's Republic of China
| | - Bin Li
- Department of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, Lanzhou 730030, People's Republic of China
| | - Qi-Yao Yu
- Department of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, Lanzhou 730030, People's Republic of China
| | - Wen-Jie Mao
- Department of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, Lanzhou 730030, People's Republic of China
| | - Jie Li
- Department of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, Lanzhou 730030, People's Republic of China
| | - Jun-Ping Lin
- Department of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, Lanzhou 730030, People's Republic of China
| | - Yu-Qi Meng
- Department of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, Lanzhou 730030, People's Republic of China
| | - Hai-Ming Feng
- Department of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, Lanzhou 730030, People's Republic of China
| | - Tao Jing
- Department of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, Lanzhou 730030, People's Republic of China
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27
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Abstract
Our understanding of the human genome has continuously expanded since its draft publication in 2001. Over the years, novel assays have allowed us to progressively overlay layers of knowledge above the raw sequence of A's, T's, G's, and C's. The reference human genome sequence is now a complex knowledge base maintained under the shared stewardship of multiple specialist communities. Its complexity stems from the fact that it is simultaneously a template for transcription, a record of evolution, a vehicle for genetics, and a functional molecule. In short, the human genome serves as a frame of reference at the intersection of a diversity of scientific fields. In recent years, the progressive fall in sequencing costs has given increasing importance to the quality of the human reference genome, as hundreds of thousands of individuals are being sequenced yearly, often for clinical applications. Also, novel sequencing-based assays shed light on novel functions of the genome, especially with respect to gene expression regulation. Keeping the human genome annotation up to date and accurate is therefore an ongoing partnership between reference annotation projects and the greater community worldwide.
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Affiliation(s)
- Daniel R Zerbino
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton CB10 1SD, United Kingdom; , ,
| | - Adam Frankish
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton CB10 1SD, United Kingdom; , ,
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton CB10 1SD, United Kingdom; , ,
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28
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Han C, Sun LY, Wang WT, Sun YM, Chen YQ. Non-coding RNAs in cancers with chromosomal rearrangements: the signatures, causes, functions and implications. J Mol Cell Biol 2020; 11:886-898. [PMID: 31361891 PMCID: PMC6884712 DOI: 10.1093/jmcb/mjz080] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 05/24/2019] [Accepted: 05/26/2019] [Indexed: 12/25/2022] Open
Abstract
Chromosomal translocation leads to the juxtaposition of two otherwise separate DNA loci, which could result in gene fusion. These rearrangements at the DNA level are catastrophic events and often have causal roles in tumorigenesis. The oncogenic DNA messages are transferred to RNA molecules, which are in most cases translated into cancerous fusion proteins. Gene expression programs and signaling pathways are altered in these cytogenetically abnormal contexts. Notably, non-coding RNAs have attracted increasing attention and are believed to be tightly associated with chromosome-rearranged cancers. These RNAs not only function as modulators in downstream pathways but also directly affect chromosomal translocation or the associated products. This review summarizes recent research advances on the relationship between non-coding RNAs and chromosomal translocations and on diverse functions of non-coding RNAs in cancers with chromosomal rearrangements.
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Affiliation(s)
- Cai Han
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, Sun Yat-sen University, Guangzhou 510275, China
| | - Lin-Yu Sun
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, Sun Yat-sen University, Guangzhou 510275, China
| | - Wen-Tao Wang
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, Sun Yat-sen University, Guangzhou 510275, China
| | - Yu-Meng Sun
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, Sun Yat-sen University, Guangzhou 510275, China
| | - Yue-Qin Chen
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, Sun Yat-sen University, Guangzhou 510275, China
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29
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Abstract
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.
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Affiliation(s)
- Xinrui Shi
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Sandeep Singh
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Emily Lin
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Hui Li
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA, United States; Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA, United States.
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30
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Ding S, Li S, Zhang S, Li Y. Genetic Alterations and Checkpoint Expression: Mechanisms and Models for Drug Discovery. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1248:227-250. [PMID: 32185713 DOI: 10.1007/978-981-15-3266-5_10] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
In this chapter, we will sketch a story that begins with the breakdown of chromosome homeostasis and genomic stability. Genomic alterations may render tumor cells eternal life at the expense of immunogenicity. Although antitumor immunity can be primed through neoantigens or inflammatory signals, tumor cells have evolved countermeasures to evade immune surveillance and strike back by modulating immune checkpoint related pathways. At present, monoclonal antibody drugs targeting checkpoints like PD-1 and CTLA-4 have significantly prolonged the survival of a variety of cancer patients, and thus have marked a great achievement in the history of antitumor therapy. Nevertheless, this is not the end of the story. As the relationship between genomic alteration and checkpoint expression is being delineated though the advances of preclinical animal models and emerging technologies, novel checkpoint targets are on the way to be discovered.
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Affiliation(s)
- Shuai Ding
- The State Key Laboratory of Pharmaceutical Biotechnology and MOE Key Laboratory of Model Animals for Disease Study, Department of Rheumatology and Immunology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Model Animal Research Center of Nanjing University, Nanjing, Jiangsu, 210061, China
| | - Siqi Li
- The State Key Laboratory of Pharmaceutical Biotechnology and MOE Key Laboratory of Model Animals for Disease Study, Department of Rheumatology and Immunology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Model Animal Research Center of Nanjing University, Nanjing, Jiangsu, 210061, China
| | - Shujie Zhang
- The State Key Laboratory of Pharmaceutical Biotechnology and MOE Key Laboratory of Model Animals for Disease Study, Department of Rheumatology and Immunology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Model Animal Research Center of Nanjing University, Nanjing, Jiangsu, 210061, China
| | - Yan Li
- The State Key Laboratory of Pharmaceutical Biotechnology and MOE Key Laboratory of Model Animals for Disease Study, Department of Rheumatology and Immunology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Model Animal Research Center of Nanjing University, Nanjing, Jiangsu, 210061, China.
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31
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McCartney AM, Hyland EM, Cormican P, Moran RJ, Webb AE, Lee KD, Hernandez-Rodriguez J, Prado-Martinez J, Creevey CJ, Aspden JL, McInerney JO, Marques-Bonet T, O'Connell MJ. Gene Fusions Derived by Transcriptional Readthrough are Driven by Segmental Duplication in Human. Genome Biol Evol 2020; 11:2678-2690. [PMID: 31400206 PMCID: PMC6764479 DOI: 10.1093/gbe/evz163] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/17/2019] [Indexed: 12/14/2022] Open
Abstract
Gene fusion occurs when two or more individual genes with independent open reading frames becoming juxtaposed under the same open reading frame creating a new fused gene. A small number of gene fusions described in detail have been associated with novel functions, for example, the hominid-specific PIPSL gene, TNFSF12, and the TWE-PRIL gene family. We use Sequence Similarity Networks and species level comparisons of great ape genomes to identify 45 new genes that have emerged by transcriptional readthrough, that is, transcription-derived gene fusion. For 35 of these putative gene fusions, we have been able to assess available RNAseq data to determine whether there are reads that map to each breakpoint. A total of 29 of the putative gene fusions had annotated transcripts (9/29 of which are human-specific). We carried out RT-qPCR in a range of human tissues (placenta, lung, liver, brain, and testes) and found that 23 of the putative gene fusion events were expressed in at least one tissue. Examining the available ribosome foot-printing data, we find evidence for translation of three of the fused genes in human. Finally, we find enrichment for transcription-derived gene fusions in regions of known segmental duplication in human. Together, our results implicate chromosomal structural variation brought about by segmental duplication with the emergence of novel transcripts and translated protein products.
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Affiliation(s)
- Ann M McCartney
- Bioinformatics and Molecular Evolution Group, School of Biotechnology, Dublin City University, Ireland.,Computational and Molecular Evolutionary Biology Group, School of Biology, Faculty of Biological Sciences, The University of Leeds, United Kingdom
| | - Edel M Hyland
- Bioinformatics and Molecular Evolution Group, School of Biotechnology, Dublin City University, Ireland.,Institute for Global Food Security, Queens University Belfast, United Kingdom
| | - Paul Cormican
- Teagasc Animal and Bioscience Research Department, Animal & Grassland Research and Innovation Centre, Teagasc, Grange, Dunsany, County Meath, Ireland
| | - Raymond J Moran
- Bioinformatics and Molecular Evolution Group, School of Biotechnology, Dublin City University, Ireland.,Computational and Molecular Evolutionary Biology Group, School of Biology, Faculty of Biological Sciences, The University of Leeds, United Kingdom
| | - Andrew E Webb
- Bioinformatics and Molecular Evolution Group, School of Biotechnology, Dublin City University, Ireland
| | - Kate D Lee
- Bioinformatics and Molecular Evolution Group, School of Biotechnology, Dublin City University, Ireland.,School of Biological Sciences, University of Auckland, New Zealand.,School of Fundamental Sciences, Massey University, New Zealand
| | | | - Javier Prado-Martinez
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain.,Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom
| | - Christopher J Creevey
- Institute for Global Food Security, Queens University Belfast, United Kingdom.,Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, United Kingdom
| | - Julie L Aspden
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, The University of Leeds, United Kingdom
| | - James O McInerney
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, M13 9PL, United Kingdom.,School of Life Sciences, Faculty of Medicine and Health Sciences, The University of Nottingham, NG7 2RD, United Kingdom
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain.,Catalan Institution of Research and Advanced Studies (ICREA), Passeig de Lluís Companys, 23, 08010, Barcelona, Spain.,NAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain.,Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, c/ Columnes s/n, 08193 Cerdanyola del Vallés, Barcelona, Spain
| | - Mary J O'Connell
- Bioinformatics and Molecular Evolution Group, School of Biotechnology, Dublin City University, Ireland.,Computational and Molecular Evolutionary Biology Group, School of Biology, Faculty of Biological Sciences, The University of Leeds, United Kingdom.,School of Life Sciences, Faculty of Medicine and Health Sciences, The University of Nottingham, NG7 2RD, United Kingdom
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32
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Vellichirammal NN, Albahrani A, Banwait JK, Mishra NK, Li Y, Roychoudhury S, Kling MJ, Mirza S, Bhakat KK, Band V, Joshi SS, Guda C. Pan-Cancer Analysis Reveals the Diverse Landscape of Novel Sense and Antisense Fusion Transcripts. MOLECULAR THERAPY. NUCLEIC ACIDS 2020; 19:1379-1398. [PMID: 32160708 PMCID: PMC7044684 DOI: 10.1016/j.omtn.2020.01.023] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 01/03/2020] [Accepted: 01/14/2020] [Indexed: 01/26/2023]
Abstract
Gene fusions that contribute to oncogenicity can be explored for identifying cancer biomarkers and potential drug targets. To investigate the nature and distribution of fusion transcripts in cancer, we examined the transcriptome data of about 9,000 primary tumors from 33 different cancers in TCGA (The Cancer Genome Atlas) along with cell line data from CCLE (Cancer Cell Line Encyclopedia) using ChimeRScope, a novel fusion detection algorithm. We identified several fusions with sense (canonical, 39%) or antisense (non-canonical, 61%) transcripts recurrent across cancers. The majority of the recurrent non-canonical fusions found in our study are novel, unexplored, and exhibited highly variable profiles across cancers, with breast cancer and glioblastoma having the highest and lowest rates, respectively. Overall, 4,344 recurrent fusions were identified from TCGA in this study, of which 70% were novel. Additional analysis of 802 tumor-derived cell line transcriptome data across 20 cancers revealed significant variability in recurrent fusion profiles between primary tumors and corresponding cell lines. A subset of canonical and non-canonical fusions was validated by examining the structural variation evidence in whole-genome sequencing (WGS) data or by Sanger sequencing of fusion junctions. Several recurrent fusion genes identified in our study show promise for drug repurposing in basket trials and present opportunities for mechanistic studies.
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Affiliation(s)
| | - Abrar Albahrani
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Jasjit K Banwait
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA; Bioinformatics and Systems Biology Core. University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Nitish K Mishra
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - You Li
- HitGen, South Keyuan Road 88, Chengdu, China
| | - Shrabasti Roychoudhury
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Mathew J Kling
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Sameer Mirza
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Kishor K Bhakat
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Vimla Band
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Shantaram S Joshi
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Chittibabu Guda
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA; Bioinformatics and Systems Biology Core. University of Nebraska Medical Center, Omaha, NE 68198, USA.
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33
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Calabrese C, Davidson NR, Demircioğlu D, Fonseca NA, He Y, Kahles A, Lehmann KV, Liu F, Shiraishi Y, Soulette CM, Urban L, Greger L, Li S, Liu D, Perry MD, Xiang Q, Zhang F, Zhang J, Bailey P, Erkek S, Hoadley KA, Hou Y, Huska MR, Kilpinen H, Korbel JO, Marin MG, Markowski J, Nandi T, Pan-Hammarström Q, Pedamallu CS, Siebert R, Stark SG, Su H, Tan P, Waszak SM, Yung C, Zhu S, Awadalla P, Creighton CJ, Meyerson M, Ouellette BFF, Wu K, Yang H, Brazma A, Brooks AN, Göke J, Rätsch G, Schwarz RF, Stegle O, Zhang Z. Genomic basis for RNA alterations in cancer. Nature 2020; 578:129-136. [PMID: 32025019 PMCID: PMC7054216 DOI: 10.1038/s41586-020-1970-0] [Citation(s) in RCA: 241] [Impact Index Per Article: 60.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Accepted: 12/11/2019] [Indexed: 01/27/2023]
Abstract
Transcript alterations often result from somatic changes in cancer genomes1. Various forms of RNA alterations have been described in cancer, including overexpression2, altered splicing3 and gene fusions4; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)5. Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.
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Affiliation(s)
| | - Claudia Calabrese
- 0000 0000 9709 7726grid.225360.0European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Natalie R. Davidson
- 0000 0001 2156 2780grid.5801.cETH Zurich, Zurich, Switzerland ,0000 0001 2171 9952grid.51462.34Memorial Sloan Kettering Cancer Center, New York, NY USA ,000000041936877Xgrid.5386.8Weill Cornell Medical College, New York, NY USA ,0000 0001 2223 3006grid.419765.8SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,0000 0004 0478 9977grid.412004.3University Hospital Zurich, Zurich, Switzerland
| | - Deniz Demircioğlu
- 0000 0001 2180 6431grid.4280.eNational University of Singapore, Singapore, Singapore ,0000 0004 0620 715Xgrid.418377.eGenome Institute of Singapore, Singapore, Singapore
| | - Nuno A. Fonseca
- 0000 0000 9709 7726grid.225360.0European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Yao He
- 0000 0001 2256 9319grid.11135.37Peking University, Beijing, China
| | - André Kahles
- 0000 0001 2156 2780grid.5801.cETH Zurich, Zurich, Switzerland ,0000 0001 2171 9952grid.51462.34Memorial Sloan Kettering Cancer Center, New York, NY USA ,0000 0001 2223 3006grid.419765.8SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,0000 0004 0478 9977grid.412004.3University Hospital Zurich, Zurich, Switzerland
| | - Kjong-Van Lehmann
- 0000 0001 2156 2780grid.5801.cETH Zurich, Zurich, Switzerland ,0000 0001 2171 9952grid.51462.34Memorial Sloan Kettering Cancer Center, New York, NY USA ,0000 0001 2223 3006grid.419765.8SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,0000 0004 0478 9977grid.412004.3University Hospital Zurich, Zurich, Switzerland
| | - Fenglin Liu
- 0000 0001 2256 9319grid.11135.37Peking University, Beijing, China
| | - Yuichi Shiraishi
- 0000 0001 2151 536Xgrid.26999.3dThe University of Tokyo, Minato-ku, Japan
| | - Cameron M. Soulette
- 0000 0001 0740 6917grid.205975.cUniversity of California, Santa Cruz, Santa Cruz, CA USA
| | - Lara Urban
- 0000 0000 9709 7726grid.225360.0European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Liliana Greger
- 0000 0000 9709 7726grid.225360.0European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Siliang Li
- 0000 0001 2034 1839grid.21155.32BGI-Shenzhen, Shenzhen, China ,China National GeneBank-Shenzhen, Shenzhen, China
| | - Dongbing Liu
- 0000 0001 2034 1839grid.21155.32BGI-Shenzhen, Shenzhen, China ,China National GeneBank-Shenzhen, Shenzhen, China
| | - Marc D. Perry
- 0000 0004 0626 690Xgrid.419890.dOntario Institute for Cancer Research, Toronto, Ontario, Canada ,0000 0001 2297 6811grid.266102.1University of California, San Francisco, San Francisco, CA USA
| | - Qian Xiang
- 0000 0004 0626 690Xgrid.419890.dOntario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Fan Zhang
- 0000 0001 2256 9319grid.11135.37Peking University, Beijing, China
| | - Junjun Zhang
- 0000 0004 0626 690Xgrid.419890.dOntario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Peter Bailey
- 0000 0001 2193 314Xgrid.8756.cUniversity of Glasgow, Glasgow, UK
| | - Serap Erkek
- 0000 0004 0495 846Xgrid.4709.aEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Katherine A. Hoadley
- 0000000122483208grid.10698.36The University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Yong Hou
- 0000 0001 2034 1839grid.21155.32BGI-Shenzhen, Shenzhen, China ,China National GeneBank-Shenzhen, Shenzhen, China
| | - Matthew R. Huska
- 0000 0001 1014 0849grid.419491.0Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany
| | - Helena Kilpinen
- 0000000121901201grid.83440.3bUniversity College London, London, UK
| | - Jan O. Korbel
- 0000 0004 0495 846Xgrid.4709.aEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Maximillian G. Marin
- 0000 0001 0740 6917grid.205975.cUniversity of California, Santa Cruz, Santa Cruz, CA USA
| | - Julia Markowski
- 0000 0001 1014 0849grid.419491.0Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany
| | - Tannistha Nandi
- 0000 0004 0620 715Xgrid.418377.eGenome Institute of Singapore, Singapore, Singapore
| | - Qiang Pan-Hammarström
- 0000 0001 2034 1839grid.21155.32BGI-Shenzhen, Shenzhen, China ,0000 0004 1937 0626grid.4714.6Karolinska Institutet, Stockholm, Sweden
| | - Chandra Sekhar Pedamallu
- grid.66859.34Broad Institute, Cambridge, MA USA ,0000 0001 2106 9910grid.65499.37Dana-Farber Cancer Institute, Boston, MA USA ,000000041936754Xgrid.38142.3cHarvard Medical School, Boston, MA USA
| | - Reiner Siebert
- grid.410712.1Ulm University and Ulm University Medical Center, Ulm, Germany
| | - Stefan G. Stark
- 0000 0001 2156 2780grid.5801.cETH Zurich, Zurich, Switzerland ,0000 0001 2171 9952grid.51462.34Memorial Sloan Kettering Cancer Center, New York, NY USA ,0000 0001 2223 3006grid.419765.8SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,0000 0004 0478 9977grid.412004.3University Hospital Zurich, Zurich, Switzerland
| | - Hong Su
- 0000 0001 2034 1839grid.21155.32BGI-Shenzhen, Shenzhen, China ,China National GeneBank-Shenzhen, Shenzhen, China
| | - Patrick Tan
- 0000 0004 0620 715Xgrid.418377.eGenome Institute of Singapore, Singapore, Singapore ,0000 0004 0385 0924grid.428397.3Duke-NUS Medical School, Singapore, Singapore
| | - Sebastian M. Waszak
- 0000 0004 0495 846Xgrid.4709.aEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Christina Yung
- 0000 0004 0626 690Xgrid.419890.dOntario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Shida Zhu
- 0000 0001 2034 1839grid.21155.32BGI-Shenzhen, Shenzhen, China ,China National GeneBank-Shenzhen, Shenzhen, China
| | - Philip Awadalla
- 0000 0004 0626 690Xgrid.419890.dOntario Institute for Cancer Research, Toronto, Ontario, Canada ,0000 0001 2157 2938grid.17063.33University of Toronto, Toronto, Ontario Canada
| | - Chad J. Creighton
- 0000 0001 2160 926Xgrid.39382.33Baylor College of Medicine, Houston, TX USA
| | - Matthew Meyerson
- grid.66859.34Broad Institute, Cambridge, MA USA ,0000 0001 2106 9910grid.65499.37Dana-Farber Cancer Institute, Boston, MA USA ,000000041936754Xgrid.38142.3cHarvard Medical School, Boston, MA USA
| | | | - Kui Wu
- 0000 0001 2034 1839grid.21155.32BGI-Shenzhen, Shenzhen, China ,China National GeneBank-Shenzhen, Shenzhen, China
| | - Huanming Yang
- 0000 0001 2034 1839grid.21155.32BGI-Shenzhen, Shenzhen, China
| | | | - Alvis Brazma
- 0000 0000 9709 7726grid.225360.0European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Angela N. Brooks
- 0000 0001 0740 6917grid.205975.cUniversity of California, Santa Cruz, Santa Cruz, CA USA ,grid.66859.34Broad Institute, Cambridge, MA USA ,0000 0001 2106 9910grid.65499.37Dana-Farber Cancer Institute, Boston, MA USA
| | - Jonathan Göke
- 0000 0004 0620 715Xgrid.418377.eGenome Institute of Singapore, Singapore, Singapore ,0000 0004 0620 9745grid.410724.4National Cancer Centre Singapore, Singapore, Singapore
| | - Gunnar Rätsch
- 0000 0001 2156 2780grid.5801.cETH Zurich, Zurich, Switzerland ,0000 0001 2171 9952grid.51462.34Memorial Sloan Kettering Cancer Center, New York, NY USA ,000000041936877Xgrid.5386.8Weill Cornell Medical College, New York, NY USA ,0000 0001 2223 3006grid.419765.8SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,0000 0004 0478 9977grid.412004.3University Hospital Zurich, Zurich, Switzerland
| | - Roland F. Schwarz
- 0000 0000 9709 7726grid.225360.0European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK ,0000 0001 1014 0849grid.419491.0Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany ,0000 0004 0492 0584grid.7497.dGerman Cancer Consortium (DKTK), partner site Berlin, Germany ,0000 0004 0492 0584grid.7497.dGerman Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oliver Stegle
- 0000 0000 9709 7726grid.225360.0European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK ,0000 0004 0495 846Xgrid.4709.aEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany ,0000 0004 0492 0584grid.7497.dGerman Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Zemin Zhang
- 0000 0001 2256 9319grid.11135.37Peking University, Beijing, China
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34
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Barresi V, Cosentini I, Scuderi C, Napoli S, Di Bella V, Spampinato G, Condorelli DF. Fusion Transcripts of Adjacent Genes: New Insights into the World of Human Complex Transcripts in Cancer. Int J Mol Sci 2019; 20:ijms20215252. [PMID: 31652751 PMCID: PMC6862657 DOI: 10.3390/ijms20215252] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 10/18/2019] [Accepted: 10/20/2019] [Indexed: 12/12/2022] Open
Abstract
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.
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Affiliation(s)
- Vincenza Barresi
- Department of Biomedical and Biotechnological Sciences, Section of Medical Biochemistry, University of Catania, 95123 Catania, Italy.
| | - Ilaria Cosentini
- Department of Biomedical and Biotechnological Sciences, Section of Medical Biochemistry, University of Catania, 95123 Catania, Italy.
| | - Chiara Scuderi
- Department of Biomedical and Biotechnological Sciences, Section of Medical Biochemistry, University of Catania, 95123 Catania, Italy.
| | - Salvatore Napoli
- Department of Biomedical and Biotechnological Sciences, Section of Medical Biochemistry, University of Catania, 95123 Catania, Italy.
| | - Virginia Di Bella
- Department of Biomedical and Biotechnological Sciences, Section of Medical Biochemistry, University of Catania, 95123 Catania, Italy.
| | - Giorgia Spampinato
- Department of Biomedical and Biotechnological Sciences, Section of Medical Biochemistry, University of Catania, 95123 Catania, Italy.
| | - Daniele Filippo Condorelli
- Department of Biomedical and Biotechnological Sciences, Section of Medical Biochemistry, University of Catania, 95123 Catania, Italy.
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35
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Wu H, Li X, Li H. Gene fusions and chimeric RNAs, and their implications in cancer. Genes Dis 2019; 6:385-390. [PMID: 31832518 PMCID: PMC6889028 DOI: 10.1016/j.gendis.2019.08.002] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2019] [Revised: 08/03/2019] [Accepted: 08/21/2019] [Indexed: 01/26/2023] Open
Abstract
Gene fusions are appreciated as ideal cancer biomarkers and therapeutic targets. Chimeric RNAs are traditionally thought to be products of gene fusions, and thus, also cancer-specific. Recent research has demonstrated that chimeric RNAs can be generated by intergenic splicing in the absence of gene fusion, and such chimeric RNAs are also found in normal physiology. These new findings challenge the traditional theory of chimeric RNAs exclusivity to cancer, and complicates use of chimeric RNAs in cancer detection. Here, we provide an overview of gene fusions and chimeric RNAs, and emphasize their differences. We note that gene fusions are able to generate chimeric RNAs in accordance with the central dogma of biology, and that chimeric RNAs may also be able to influence the generation of the gene fusions per the “horse before the cart” hypothesis. We further expand upon the “horse before the cart” hypothesis, summarizing current evidence in support of the theory and exploring its potential impact on the field.
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Affiliation(s)
- Hao Wu
- Department of Gastrointestinal Surgery, The Third Xiangya Hospital of Central South University, Changsha, Hunan, 410013, China
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA, 22908, USA
| | - Xiaorong Li
- Department of Gastrointestinal Surgery, The Third Xiangya Hospital of Central South University, Changsha, Hunan, 410013, China
| | - Hui Li
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA, 22908, USA
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA, 22908, USA
- Corresponding author. Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA, 22908, USA. Fax: +1 434 2437244. http://lilab.medicine.virginia.edu
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36
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Tang Y, Ma S, Wang X, Xing Q, Huang T, Liu H, Li Q, Zhang Y, Zhang K, Yao M, Yang GL, Li H, Zang X, Yang B, Guan F. Identification of chimeric RNAs in human infant brains and their implications in neural differentiation. Int J Biochem Cell Biol 2019; 111:19-26. [DOI: 10.1016/j.biocel.2019.03.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 03/06/2019] [Accepted: 03/30/2019] [Indexed: 02/07/2023]
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37
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Chen CY, Chuang TJ. Comment on "A comprehensive overview and evaluation of circular RNA detection tools". PLoS Comput Biol 2019; 15:e1006158. [PMID: 31150384 PMCID: PMC6544197 DOI: 10.1371/journal.pcbi.1006158] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 03/17/2018] [Indexed: 11/18/2022] Open
Affiliation(s)
- Chia-Ying Chen
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
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38
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Latysheva NS, Babu MM. Molecular Signatures of Fusion Proteins in Cancer. ACS Pharmacol Transl Sci 2019; 2:122-133. [PMID: 32219217 PMCID: PMC7088938 DOI: 10.1021/acsptsci.9b00019] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Indexed: 01/07/2023]
Abstract
![]()
Although gene fusions
are recognized as driver mutations in a wide
variety of cancers, the general molecular mechanisms underlying oncogenic
fusion proteins are insufficiently understood. Here, we employ large-scale
data integration and machine learning and (1) identify three functionally
distinct subgroups of gene fusions and their molecular signatures;
(2) characterize the cellular pathways rewired by fusion events across
different cancers; and (3) analyze the relative importance of over
100 structural, functional, and regulatory features of ∼2200
gene fusions. We report subgroups of fusions that likely act as driver
mutations and find that gene fusions disproportionately affect pathways
regulating cellular shape and movement. Although fusion proteins are
similar across different cancer types, they affect cancer type-specific
pathways. Key indicators of fusion-forming proteins include high and
nontissue specific expression, numerous splice sites, and higher centrality
in protein-interaction networks. Together, these findings provide
unifying and cancer type-specific trends across diverse oncogenic
fusion proteins.
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Affiliation(s)
- Natasha S Latysheva
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - M Madan Babu
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
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39
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Singh A, Zahra S, Das D, Kumar S. AtFusionDB: a database of fusion transcripts in Arabidopsis thaliana. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2019; 2019:5277248. [PMID: 30624648 PMCID: PMC6323297 DOI: 10.1093/database/bay135] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 11/29/2018] [Indexed: 02/02/2023]
Abstract
Fusion transcripts are chimeric RNAs generated as a result of fusion either at DNA or RNA level. These novel transcripts have been extensively studied in the case of human cancers but still remain underexamined in plants. In this study, we introduce the first plant-specific database of fusion transcripts named AtFusionDB (http://www.nipgr.res.in/AtFusionDB). This is a comprehensive database that contains the detailed information about fusion transcripts identified in model plant Arabidopsis thaliana. A total of 82 969 fusion transcript entries generated from 17 181 different genes of A. thaliana are available in this database. Apart from the basic information consisting of the Ensembl gene names, official gene name, tissue type, EricScore, fusion type, AtFusionDB ID and sample ID (e.g. Sequence Read Archive ID), additional information like UniProt, gene coordinates (together with the function of parental genes), junction sequence, expression level of both parent genes and fusion transcript may be of high utility to the user. Two different types of search modules viz. ‘Simple Search’ and ‘Advanced Search’ in addition to the ‘Browse’ option with data download facility are provided in this database. Three different modules for mapping and alignment of the query sequences viz. BLASTN, SW Align and Mapping are incorporated in AtFusionDB. This database is a head start for exploring the complex and unexplored domain of gene/transcript fusion in plants.
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Affiliation(s)
- Ajeet Singh
- Bioinformatics Laboratory, National Institute of Plant Genome Research Aruna Asaf Ali Marg, New Delhi, India
| | - Shafaque Zahra
- Bioinformatics Laboratory, National Institute of Plant Genome Research Aruna Asaf Ali Marg, New Delhi, India
| | - Durdam Das
- Bioinformatics Laboratory, National Institute of Plant Genome Research Aruna Asaf Ali Marg, New Delhi, India
| | - Shailesh Kumar
- Bioinformatics Laboratory, National Institute of Plant Genome Research Aruna Asaf Ali Marg, New Delhi, India
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40
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Abstract
Serum amyloid A (SAA) proteins were isolated and named over 50 years ago. They are small (104 amino acids) and have a striking relationship to the acute phase response with serum levels rising as much as 1000-fold in 24 hours. SAA proteins are encoded in a family of closely-related genes and have been remarkably conserved throughout vertebrate evolution. Amino-terminal fragments of SAA can form highly organized, insoluble fibrils that accumulate in “secondary” amyloid disease. Despite their evolutionary preservation and dynamic synthesis pattern SAA proteins have lacked well-defined physiologic roles. However, considering an array of many, often unrelated, reports now permits a more coordinated perspective. Protein studies have elucidated basic SAA structure and fibril formation. Appreciating SAA’s lipophilicity helps relate it to lipid transport and metabolism as well as atherosclerosis. SAA’s function as a cytokine-like protein has become recognized in cell-cell communication as well as feedback in inflammatory, immunologic, neoplastic and protective pathways. SAA likely has a critical role in control and possibly propagation of the primordial acute phase response. Appreciating the many cellular and molecular interactions for SAA suggests possibilities for improved understanding of pathophysiology as well as treatment and disease prevention.
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Affiliation(s)
- George H Sack
- Departments of Biological Chemistry and Medicine, The Johns Hopkins University School of Medicine, 725 N. Wolfe Street, Physiology 615, Baltimore, MD, 21205, USA.
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41
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Jung J, Jang K, Ju JM, Lee E, Lee JW, Kim HJ, Kim J, Lee SB, Ko BS, Son BH, Lee HJ, Gong G, Ahn SY, Choi JK, Singh SR, Chang S. Novel cancer gene variants and gene fusions of triple-negative breast cancers (TNBCs) reveal their molecular diversity conserved in the patient-derived xenograft (PDX) model. Cancer Lett 2018; 428:127-138. [DOI: 10.1016/j.canlet.2018.04.020] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Revised: 04/15/2018] [Accepted: 04/17/2018] [Indexed: 12/20/2022]
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42
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Chen S, Liu M, Huang T, Liao W, Xu M, Gu J. GeneFuse: detection and visualization of target gene fusions from DNA sequencing data. Int J Biol Sci 2018; 14:843-848. [PMID: 29989075 PMCID: PMC6036752 DOI: 10.7150/ijbs.24626] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2017] [Accepted: 03/06/2018] [Indexed: 12/31/2022] Open
Abstract
In recent years, gene fusion detection for cancer treatment has become increasingly important since more therapeutic agents have been developed to suppress fusion kinases. Although a number of tools have been developed to detect gene fusions from DNA sequencing data, most of them are not sensitive enough for processing the data from the samples with low tumor DNA composition, like cell-free tumor DNA. In this paper, we will introduce GeneFuse, a tool to detect and visualize gene fusions with high sensitivity and specificity. GeneFuse focuses on the curated gene fusions, which are available in COSMIC (the Catalogue of Somatic Mutations in Cancer) database. For each detected fusion, GeneFuse reports its genome locus, inferred protein forms, and supporting sequencing reads. The fusion detection results are visualized in an HTML page for cloud-friendly validation. GeneFuse is an open source tool available at GitHub: https://github.com/OpenGene/GeneFuse
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Affiliation(s)
- Shifu Chen
- HaploX Biotechnology, Shenzhen, China.,Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Ming Liu
- HaploX Biotechnology, Shenzhen, China
| | | | | | | | - Jia Gu
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
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43
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Zhao S, Løvf M, Carm KT, Bakken AC, Hoff AM, Skotheim RI. Novel transcription-induced fusion RNAs in prostate cancer. Oncotarget 2018; 8:49133-49143. [PMID: 28467780 PMCID: PMC5564755 DOI: 10.18632/oncotarget.17099] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Accepted: 04/03/2017] [Indexed: 12/21/2022] Open
Abstract
Prostate cancer is a clinically and pathologically heterogeneous disease with a broad spectrum of molecular abnormalities in the genome and transcriptome. One key feature is the involvement of chromosomal rearrangements creating fusion genes. Recent RNA-sequencing technology has uncovered that fusions which are not caused by chromosomal rearrangements, but rather meditated at transcription level, are common in both healthy and diseased cells. Such fusion transcripts have been proven highly associated with prostate cancer development and progression. To discover novel fusion transcripts, we analyzed RNA sequencing data from 44 primary prostate tumors and matched benign tissues from The Cancer Genome Atlas. Twenty-one high-confident candidates were significantly enriched in malignant vs. benign samples. Thirteen of the candidates have not previously been described in prostate cancer, and among them, five long intergenic non-coding RNAs are involved as fusion partners. Their expressions were validated in 50 additional prostate tumor samples and seven prostate cancer cell lines. For four fusion transcripts, we found a positive correlation between their expression and the expression of the 3′ partner gene. Among these, differential exon usage and qRT-PCR analyses in particular support that SLC45A3-ELK4 is mediated by an RNA polymerase read-through mechanism.
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Affiliation(s)
- Sen Zhao
- Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital-Norwegian Radium Hospital, Oslo, Norway.,Center for Cancer Biomedicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Marthe Løvf
- Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital-Norwegian Radium Hospital, Oslo, Norway.,Center for Cancer Biomedicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Kristina Totland Carm
- Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital-Norwegian Radium Hospital, Oslo, Norway.,Center for Cancer Biomedicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Anne Cathrine Bakken
- Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital-Norwegian Radium Hospital, Oslo, Norway.,Center for Cancer Biomedicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Andreas M Hoff
- Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital-Norwegian Radium Hospital, Oslo, Norway.,Center for Cancer Biomedicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Rolf I Skotheim
- Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital-Norwegian Radium Hospital, Oslo, Norway.,Center for Cancer Biomedicine, Faculty of Medicine, University of Oslo, Oslo, Norway.,Department of Informatics, Faculty of Natural Science and Mathematics, University of Oslo, Oslo, Norway
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44
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Tang Y, Qin F, Liu A, Li H. Recurrent fusion RNA DUS4L-BCAP29 in non-cancer human tissues and cells. Oncotarget 2018; 8:31415-31423. [PMID: 28415823 PMCID: PMC5458218 DOI: 10.18632/oncotarget.16329] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Accepted: 03/09/2017] [Indexed: 01/09/2023] Open
Abstract
Traditional gene fusions are involved in the development of various neoplasia. DUS4L-BCAP29, a chimeric fusion RNA, has been reported to be a cancer-fusion in prostate and gastric cancer, in addition to playing a tumorigenic role. Here, we showed that the DUS4L-BCAP29 fusion transcript exists in a variety of normal tissues. It is also present in non-cancer epithelial, as well as in fibroblast cell lines. Quantitatively, the fusion transcript has a comparable expression in non-cancerous, gastric and prostate cell lines and tissues as in the cancer cell lines and tissues. The loss-of-function approach as previously reported is not sufficient to prove the functionality of the fusion. On the other hand, the gain-of-function approach showed that overexpression of DUS4L-BCAP29 promotes cell growth and motility, even in non-cancer cells. Finally, we provide further evidence that the fusion transcript is a product of cis-splicing between adjacent genes. In summary, we believe that in contrast to traditional gene fusions, DUS4L-BCAP29 cannot be used as a cancer biomarker. Instead, it is a fusion transcript that exists in normal physiology and that its pro-growth effect is not unique to cancer cells.
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Affiliation(s)
- Yue Tang
- College of Life Sciences, Zhengzhou University, Zhengzhou, Henan 450008, P.R. China.,Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA.,College of Basic Medical Sciences, Zhengzhou University, Zhengzhou, Henan, 450001, P.R. China
| | - Fujun Qin
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Aiqun Liu
- Department of Endoscopy, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Hui Li
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
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45
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46
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Cieślik M, Chinnaiyan AM. Cancer transcriptome profiling at the juncture of clinical translation. Nat Rev Genet 2017; 19:93-109. [PMID: 29279605 DOI: 10.1038/nrg.2017.96] [Citation(s) in RCA: 156] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Methodological breakthroughs over the past four decades have repeatedly revolutionized transcriptome profiling. Using RNA sequencing (RNA-seq), it has now become possible to sequence and quantify the transcriptional outputs of individual cells or thousands of samples. These transcriptomes provide a link between cellular phenotypes and their molecular underpinnings, such as mutations. In the context of cancer, this link represents an opportunity to dissect the complexity and heterogeneity of tumours and to discover new biomarkers or therapeutic strategies. Here, we review the rationale, methodology and translational impact of transcriptome profiling in cancer.
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Affiliation(s)
- Marcin Cieślik
- Michigan Center for Translational Pathology, University of Michigan.,Department of Pathology, University of Michigan
| | - Arul M Chinnaiyan
- Michigan Center for Translational Pathology, University of Michigan.,Department of Pathology, University of Michigan.,Comprehensive Cancer Center, University of Michigan.,Department of Urology, University of Michigan.,Howard Hughes Medical Institute, University of Michigan, Ann Arbor, Michigan 48109, USA
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47
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Pintarelli G, Dassano A, Cotroneo CE, Galvan A, Noci S, Piazza R, Pirola A, Spinelli R, Incarbone M, Palleschi A, Rosso L, Santambrogio L, Dragani TA, Colombo F. Read-through transcripts in normal human lung parenchyma are down-regulated in lung adenocarcinoma. Oncotarget 2017; 7:27889-98. [PMID: 27058892 PMCID: PMC5053695 DOI: 10.18632/oncotarget.8556] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2015] [Accepted: 02/18/2016] [Indexed: 12/26/2022] Open
Abstract
Read-through transcripts result from the continuous transcription of adjacent, similarly oriented genes, with the splicing out of the intergenic region. They have been found in several neoplastic and normal tissues, but their pathophysiological significance is unclear. We used high-throughput sequencing of cDNA fragments (RNA-Seq) to identify read-through transcripts in the non-involved lung tissue of 64 surgically treated lung adenocarcinoma patients. A total of 52 distinct read-through species was identified, with 24 patients having at least one read-through event, up to a maximum of 17 such transcripts in one patient. Sanger sequencing validated 28 of these transcripts and identified an additional 15, for a total of 43 distinct read-through events involving 35 gene pairs. Expression levels of 10 validated read-through transcripts were measured by quantitative PCR in pairs of matched non-involved lung tissue and lung adenocarcinoma tissue from 45 patients. Higher expression levels were observed in normal lung tissue than in the tumor counterpart, with median relative quantification ratios between normal and tumor varying from 1.90 to 7.78; the difference was statistically significant (P < 0.001, Wilcoxon's signed-rank test for paired samples) for eight transcripts: ELAVL1–TIMM44, FAM162B–ZUFSP, IFNAR2–IL10RB, INMT–FAM188B, KIAA1841–C2orf74, NFATC3–PLA2G15, SIRPB1–SIRPD, and SHANK3–ACR. This report documents the presence of read-through transcripts in apparently normal lung tissue, with inter-individual differences in patterns and abundance. It also shows their down-regulation in tumors, suggesting that these chimeric transcripts may function as tumor suppressors in lung tissue.
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Affiliation(s)
- Giulia Pintarelli
- Department of Predictive and Prevention Medicine, Fondazione IRCCS, Istituto Nazionale dei Tumori, Milan, Italy
| | - Alice Dassano
- Department of Predictive and Prevention Medicine, Fondazione IRCCS, Istituto Nazionale dei Tumori, Milan, Italy
| | - Chiara E Cotroneo
- Department of Predictive and Prevention Medicine, Fondazione IRCCS, Istituto Nazionale dei Tumori, Milan, Italy.,Present Address: UCD School of Biomolecular and Biomedical Science, University College Dublin, Belfield, Dublin, Ireland
| | - Antonella Galvan
- Formerly, Department of Predictive and Prevention Medicine, Fondazione IRCCS, Istituto Nazionale dei Tumori, Milan, Italy
| | - Sara Noci
- Department of Predictive and Prevention Medicine, Fondazione IRCCS, Istituto Nazionale dei Tumori, Milan, Italy
| | - Rocco Piazza
- Department of Health Sciences, University of Milano-Bicocca, Monza, Italy.,Hematology and Clinical Research Unit, San Gerardo Hospital, Monza, Italy
| | - Alessandra Pirola
- Department of Health Sciences, University of Milano-Bicocca, Monza, Italy
| | - Roberta Spinelli
- Formerly, Department of Health Sciences, University of Milano-Bicocca, Monza, Italy
| | - Matteo Incarbone
- Department of Surgery, San Giuseppe Hospital, Multimedica, Milan, Italy
| | - Alessandro Palleschi
- Department of Surgery, IRCCS Fondazione Cà Granda Ospedale Maggiore Policlinico, Università degli Studi di Milano, Milan, Italy
| | - Lorenzo Rosso
- Department of Surgery, IRCCS Fondazione Cà Granda Ospedale Maggiore Policlinico, Università degli Studi di Milano, Milan, Italy
| | - Luigi Santambrogio
- Department of Surgery, IRCCS Fondazione Cà Granda Ospedale Maggiore Policlinico, Università degli Studi di Milano, Milan, Italy
| | - Tommaso A Dragani
- Department of Predictive and Prevention Medicine, Fondazione IRCCS, Istituto Nazionale dei Tumori, Milan, Italy
| | - Francesca Colombo
- Department of Predictive and Prevention Medicine, Fondazione IRCCS, Istituto Nazionale dei Tumori, Milan, Italy
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48
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Chwalenia K, Qin F, Singh S, Tangtrongstittikul P, Li H. Connections between Transcription Downstream of Genes and cis-SAGe Chimeric RNA. Genes (Basel) 2017; 8:genes8110338. [PMID: 29165374 PMCID: PMC5704251 DOI: 10.3390/genes8110338] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 11/10/2017] [Accepted: 11/16/2017] [Indexed: 02/03/2023] Open
Abstract
cis-Splicing between adjacent genes (cis-SAGe) is being recognized as one way to produce chimeric fusion RNAs. However, its detail mechanism is not clear. Recent study revealed induction of transcriptions downstream of genes (DoGs) under osmotic stress. Here, we investigated the influence of osmotic stress on cis-SAGe chimeric RNAs and their connection to DoGs. We found, the absence of induction of at least some cis-SAGe fusions and/or their corresponding DoGs at early time point(s). In fact, these DoGs and their cis-SAGe fusions are inversely correlated. This negative correlation was changed to positive at a later time point. These results suggest a direct competition between the two categories of transcripts when total pool of readthrough transcripts is limited at an early time point. At a later time point, DoGs and corresponding cis-SAGe fusions are both induced, indicating that total readthrough transcripts become more abundant. Finally, we observed overall enhancement of cis-SAGe chimeric RNAs in KCl-treated samples by RNA-Seq analysis.
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Affiliation(s)
- Katarzyna Chwalenia
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA.
| | - Fujun Qin
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA.
| | - Sandeep Singh
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA.
| | | | - Hui Li
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA.
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA.
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49
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Li Z, Qin F, Li H. Chimeric RNAs and their implications in cancer. Curr Opin Genet Dev 2017; 48:36-43. [PMID: 29100211 DOI: 10.1016/j.gde.2017.10.002] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2017] [Revised: 09/06/2017] [Accepted: 10/02/2017] [Indexed: 11/26/2022]
Abstract
Chimeric RNAs have been believed to be solely produced by gene fusions resulting from chromosomal rearrangement, thus unique features of cancer. Detected chimeric RNAs have also been viewed as surrogates for the presence of gene fusions. However, more and more research has demonstrated that chimeric RNAs in general are not a hallmark of cancer, but rather widely present in non-cancerous cells and tissues. At the same time, they may be produced by other mechanisms other than chromosomal rearrangement. The field of non-canonical chimeric RNAs is still in its infancy, with many challenges ahead, including the lack of a unified terminology. However, we believe that these non-canonical chimeric RNAs will have significant impacts in cancer detection and treatment.
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Affiliation(s)
- Zi Li
- Department of Pathology, University of Virginia, Charlottesville, VA 22908, USA; Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha 410011, China
| | - Fujun Qin
- Department of Pathology, University of Virginia, Charlottesville, VA 22908, USA
| | - Hui Li
- Department of Pathology, University of Virginia, Charlottesville, VA 22908, USA.
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50
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Sunil M, Hariharan N, Dixit S, Choudhary B, Srinivasan S. Differential genomic arrangements in Caryophyllales through deep transcriptome sequencing of A. hypochondriacus. PLoS One 2017; 12:e0180528. [PMID: 28786999 PMCID: PMC5546567 DOI: 10.1371/journal.pone.0180528] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Accepted: 06/17/2017] [Indexed: 12/28/2022] Open
Abstract
Genome duplication event in edible dicots under the orders Rosid and Asterid, common during the oligocene period, is missing for species under the order Caryophyllales. Despite this, grain amaranths not only survived this period but display many desirable traits missing in species under rosids and asterids. For example, grain amaranths display traits like C4 photosynthesis, high-lysine seeds, high-yield, drought resistance, tolerance to infection and resilience to stress. It is, therefore, of interest to look for minor genome rearrangements with potential functional implications that are unique to grain amaranths. Here, by deep sequencing and assembly of 16 transcriptomes (86.8 billion bases) we have interrogated differential genome rearrangement unique to Amaranthus hypochondriacus with potential links to these phenotypes. We have predicted 125,581 non-redundant transcripts including 44,529 protein coding transcripts identified based on homology to known proteins and 13,529 predicted as novel/amaranth specific coding transcripts. Of the protein coding de novo assembled transcripts, we have identified 1810 chimeric transcripts. More than 30% and 19% of the gene pairs within the chimeric transcripts are found within the same loci in the genomes of A. hypochondriacus and Beta vulgaris respectively and are considered real positives. Interestingly, one of the chimeric transcripts comprises two important genes, namely DHDPS1, a key enzyme implicated in the biosynthesis of lysine, and alpha-glucosidase, an enzyme involved in sucrose catabolism, in close proximity to each other separated by a distance of 612 bases in the genome of A. hypochondriacus in a convergent configuration. We have experimentally validated that transcripts of these two genes are also overlapping in the 3' UTR with their expression negatively correlated from bud to mature seed, suggesting a potential link between the high seed lysine trait and unique genome organization.
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Affiliation(s)
- Meeta Sunil
- Institute of Bioinformatics and Applied Biotechnology, Bangalore, Karnataka, India
- Manipal University, Manipal, Karnataka, India
| | - Nivedita Hariharan
- Institute of Bioinformatics and Applied Biotechnology, Bangalore, Karnataka, India
| | - Shubham Dixit
- Institute of Bioinformatics and Applied Biotechnology, Bangalore, Karnataka, India
| | - Bibha Choudhary
- Institute of Bioinformatics and Applied Biotechnology, Bangalore, Karnataka, India
| | - Subhashini Srinivasan
- Institute of Bioinformatics and Applied Biotechnology, Bangalore, Karnataka, India
- * E-mail:
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