Fusion genes and chromosome translocations in the common epithelial cancers

High-resolution RNA-sequencing reveals TRIM33 :: CSDE1 gene fusion in metastasizing vulvar melanoma

Although mucosal melanomas are rare and constitute approximately 1.4% of all melanomas, the prognosis of patients with mucosal melanoma is poorer in comparison to cutaneous melanomas. Despite their poor prognosis, limited treatment options are currently available for patients with advanced disease. These noncutaneous subtypes of melanomas are not responding to treatment used for cutaneous melanomas. We performed RNA sequencing on four mucosal melanoma samples comprising of two primary tumors and two corresponding metastases. A TRIM33 :: CSDE1 fusion was detected in both the primary tumor and metastasis of a vulvar melanoma, supporting the fusion to be a driver in oncogenesis. Vulvar melanoma is the third tumor to have been reported to harbor TRIM33 :: CSDE1 fusion. Detecting fusions may have a clinically significant impact in patients with advanced mucosal melanoma who have failed front-line immunotherapy.

Full-length direct RNA sequencing reveals extensive remodeling of RNA expression, processing and modification in aging Caenorhabditis elegans

Organismal aging is marked by decline in cellular function and anatomy, ultimately resulting in death. To inform our understanding of the mechanisms underlying this degeneration, we performed standard RNA sequencing (RNA-seq) and Oxford Nanopore Technologies direct RNA-seq over an adult time course in Caenorhabditis elegans. Long reads allowed for identification of hundreds of novel isoforms and age-associated differential isoform accumulation, resulting from alternative splicing and terminal exon choice. Genome-wide analysis reveals a decline in RNA processing fidelity. Finally, we identify thousands of inosine and hundreds of pseudouridine edits genome-wide. In this first map of pseudouridine modifications for C. elegans, we find that they largely reside in coding sequences and that the number of genes with this modification increases with age. Collectively, this analysis discovers transcriptomic signatures associated with age and is a valuable resource to understand the many processes that dictate altered gene expression patterns and post-transcriptional regulation in aging.

Understanding variants of unknown significance and classification of genomic alterations

Despite recent efforts to issue clinical guidelines outlining strategies to define the pathogenicity of genomic variants, there is currently no standardized framework for which to make these assertions. This review does not present a step-by-step methodology, but rather takes a holistic approach to discuss many aspects which should be taken into consideration when determining variant pathogenicity. Categorization should be curated to reflect relevant findings within the scope of the specific medical context. Functional characterization should evaluate all available information, including results from literature reviews, different classes of genomic data repositories, and applicable computational predictive algorithms. This article further proposes a multidimensional view to infer pathogenic status from many genomic measurements across multiple axes. Notably, tumor suppressors and oncogenes exhibit fundamentally different biology which helps refine the importance of effects on splicing, mutation interactions, copy number thresholds, rearrangement annotations, germline status, and genome-wide signatures. Understanding these relevant datapoints with thoughtful perspective could aid in the reclassification of variants of unknown significance (VUS), which are ambiguously understood and currently have uncertain clinical implications. Ongoing assessments of VUS examining these relevant biological axes could lead to more accurate classification of variant pathogenicity interpretation in diagnostic oncology.

Full-length direct RNA sequencing reveals extensive remodeling of RNA expression, processing and modification in aging Caenorhabditis elegans

Organismal aging is marked by decline in cellular function and anatomy, ultimately resulting in death. To inform our understanding of the mechanisms underlying this degeneration, we performed standard RNA sequencing and Nanopore direct RNA sequencing over an adult time course in Caenorhabditis elegans. Long reads allowed for identification of hundreds of novel isoforms and age-associated differential isoform accumulation, resulting from alternative splicing and terminal exon choice. Genome-wide analysis reveals a decline in RNA processing fidelity and a rise in inosine and pseudouridine editing events in transcripts from older animals. In this first map of pseudouridine modifications for C. elegans, we find that they largely reside in coding sequences and that the number of genes with this modification increases with age. Collectively, this analysis discovers transcriptomic signatures associated with age and is a valuable resource to understand the many processes that dictate altered gene expression patterns and post-transcriptional regulation in aging.

Exploring a distinct FGFR2::DLG5 rearrangement in a low-grade neuroepithelial tumor: A case report and mini-review of protein fusions in brain tumors

We report the novel clinical presentation of a primary brain neoplasm in a 30-year-old man with a mass-like area in the anteromedial temporal lobe. Histopathological analysis revealed a low-grade neuroepithelial tumor with cytologically abnormal neurons and atypical glial cells within the cerebral cortex. Molecular analysis showed a previously undescribed FGFR2::DLG5 rearrangement. We discuss the clinical significance and molecular implications of this fusion event, shedding light on its potential impact on tumor development and patient prognosis. Additionally, an extensive review places the finding in this case in the context of protein fusions in brain tumors in general and highlights their diverse manifestations, underlying molecular mechanisms, and therapeutic implications.

A Comprehensive Review and Androgen Deprivation Therapy and Its Impact on Alzheimer's Disease Risk in Older Men with Prostate Cancer

Prostate cancer (PCa) is one of the most prevalent malignancies affecting males worldwide. Despite reductions in mortality rates due to advances in early identification and treatment methods, PCa remains a major health concern. Recent research has shed light on a possible link between PCa and Alzheimer's disease (AD), which is a significant neurological ailment that affects older males all over the world. Androgen deprivation therapy (ADT), a cornerstone therapeutic method used in conjunction with radiation and palliative care in advanced metastatic PCa cases, is critical for disease management. Evidence reveals a relationship between ADT and cognitive impairment. Hormonal manipulation may cause long-term cognitive problems through processes such as amyloid beta (Aβ) aggregation and neurofibrillary tangles (NFTs). Fluctuations in basal androgen levels can upset the delicate balance of genes that are sensitive to androgen levels, contributing to cognitive impairment. This detailed review dives into the various aspects of PCa aetiology and its relationship with cognitive decline. It investigates the discovery of particular biomarkers, as well as microRNAs (miRNAs), which play important roles in pathogenic progression. The review attempts to identify potential biomarkers associated with ADT-induced cerebral changes, including Aβ oligomer buildup, NFT formation, and tauopathy, which can contribute to early-onset dementia and cognitive impairment. Besides it further aims to provide insights into innovative diagnostic and therapeutic avenues for alleviating PCa and ADT-related cognitive sequelae by unravelling these complicated pathways and molecular mechanisms.

Identification of gene fusions associated with amyotrophic lateral sclerosis

INTRODUCTION/AIMS

Genetics is an important risk factor for amyotrophic lateral sclerosis (ALS), a neurodegenerative disease affecting motor neurons. Recent findings demonstrate that in addition to specific genetic mutations, structural variants caused by genetic instability can also play a causative role in ALS. Genomic instability can lead to deletions, duplications, insertions, inversions, and translocations in the genome, and these changes can sometimes lead to fusion of distinct genes into a single transcript. Gene fusion events have been studied extensively in cancer; however, they have not been thoroughly investigated in ALS. The aim of this study was to determine whether gene fusions are present in ALS.

METHODS

Gene fusions were identified using STAR Fusion v1.10.0 software in bulk RNA-Seq data from human postmortem samples from publicly available data sets from Target ALS and the New York Genome Center ALS Consortium.

RESULTS

We report the presence of gene fusion events in several brain regions as well as in spinal cord samples in ALS. Although most gene fusions were intra-chromosomal events between neighboring genes and present in both ALS and control samples, there was a significantly greater number of unique gene fusions in ALS compared to controls. Lastly, we identified specific gene fusions with a significant burden in ALS, that were absent from both control samples and known cancer gene fusion databases.

DISCUSSION

Collectively, our findings reveal an enrichment of gene fusions in ALS and suggest that these events may be an additional genetic cause linked to ALS pathogenesis.

Treatment for a primary multidrug-resistant B-cell acute lymphoblastic leukemia patient carrying a SSBP2-CSF1R fusion gene: a case report

SSBP2-CSF1R is an important biomarker for clinical diagnosis and prognosis of Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL). This case report presents a pediatric Ph-like ALL patient carrying the SSBP2-CSF1R fusion gene. The patient was resistant to most conventional chemotherapy regimens and to dasatinib, an inhibitor that has been reported to have a therapeutic effect on SSBP2-CSF1R fusion Ph-like ALL, as she remained minimal residual disease (MRD) positive (detection by flow cytometry) and SSBP2-CSF1R fusion gene (detection by RT-PCR) positive after five rounds of such regimens. We thus conducted a large-scale in vitro screening to assess the sensitivity of the patient's leukemic cells to anti-cancer drugs. Based on the susceptibility results, we chose to combine cytarabine, homoharringtonine, dexamethasone, fludarabine, vindesine, and epirubicin for treatment. Clinical results showed that after a course of treatment, both MRD and SSBP2-CSF1R fusion gene turned negative, and there was no recurrence during an 18-month follow-up. In conclusion, our study suggests that the SSBP2-CSF1R fusion gene may be an important biomarker of primary drug resistance in Ph-like ALL, and indicate that the combination of cytarabine, homoharringtonine, dexamethasone, fludarabine, vindesine, and epirubicin can achieve optimal therapeutic results in this category of patients.

Progressive insights into fibrosarcoma diagnosis and treatment: leveraging fusion genes for advancements

Fibrosarcoma, originating from fibroblast cells, represents a malignant neoplasm that can manifest across all genders and age groups. Fusion genes are notably prevalent within the landscape of human cancers, particularly within the subtypes of fibrosarcoma, where they exert substantial driving forces in tumorigenesis. Many fusion genes underlie the pathogenic mechanisms triggering the onset of this disease. Moreover, a close association emerges between the spectrum of fusion gene types and the phenotypic expression of fibrosarcoma, endowing fusion genes not only as promising diagnostic indicators for fibrosarcoma but also as pivotal foundations for its subcategorization. Concurrently, an increasing number of chimeric proteins encoded by fusion genes have been substantiated as specific targets for treating fibrosarcoma, consequently significantly enhancing patient prognoses. This review comprehensively delineates the mechanisms behind fusion gene formation in fibrosarcoma, the lineage of fusion genes, methodologies employed in detecting fusion genes within fibrosarcoma, and the prospects of targeted therapeutic interventions driven by fusion genes within the fibrosarcoma domain.

Neuronal DNA double-strand breaks lead to genome structural variations and 3D genome disruption in neurodegeneration

Persistent DNA double-strand breaks (DSBs) in neurons are an early pathological hallmark of neurodegenerative diseases including Alzheimer's disease (AD), with the potential to disrupt genome integrity. We used single-nucleus RNA-seq in human postmortem prefrontal cortex samples and found that excitatory neurons in AD were enriched for somatic mosaic gene fusions. Gene fusions were particularly enriched in excitatory neurons with DNA damage repair and senescence gene signatures. In addition, somatic genome structural variations and gene fusions were enriched in neurons burdened with DSBs in the CK-p25 mouse model of neurodegeneration. Neurons enriched for DSBs also had elevated levels of cohesin along with progressive multiscale disruption of the 3D genome organization aligned with transcriptional changes in synaptic, neuronal development, and histone genes. Overall, this study demonstrates the disruption of genome stability and the 3D genome organization by DSBs in neurons as pathological steps in the progression of neurodegenerative diseases.

Integrative Identification by Hi-C Revealed Distinct Advanced Structural Variations in Lung Adenocarcinoma Tissue

Advanced three-dimensional structure variations of chromatin in large genome fragments, such as conversion of A/B compartment, topologically associated domains (TADs) and chromatin loops are related closely to occurrence of malignant tumors. However, the structural characteristics of lung cancer still remain uncovered. In this study, we used high-throughput chromosome (Hi-C) conformation capture technology to detect the advanced structural variations in chromatin of two non-smoking lung adenocarcinoma (LUAD) tumor and paired normal tissues. The results indicate that significant chromatin variations are detected in tumor tissues compared with normal tissues. At compartment scale, the main conversion type of compartment is A → B in tumor tissues, which are concentrated mainly on chromosome 3 (Chr3) (33.6%). A total of 216 tumor-specific TADs are identified in tumor tissues, which are distributed mainly in Chr1 (19), Chr2 (15) and Chr3 (17). Forty-one distinct enhancer-promoter loops are observed in tumor tissue, which are associated closely to tumor-related pathways including mitogen-activated protein kinase (MAPK), Phosphatidylinositol-3-kinase-Protein kinase B (PI3K-AKT), Ras, Wnt and Ras1. The most important observation in this study is that we identify five important genes (SYT16, NCEH1, NXPE3, MB21D2, and DZIP1L), which are detected in both A → B compartment, TADs and chromatin loops in tumor samples, and four of these genes (NCEH1, NXPE3, MB21D2, and DZIP1L) locate on q arm of Chr3. Further gene expression and invasion experiment analysis show that NCEH1, MB21D2 and SYT16 are involved in the tumor development. Thus, we provide a comprehensive overview of advanced structures in LUAD for the first time and provide a basis for further research on the genetic variation of this tumor.

Gene Fusion Detection and Characterization in Long-Read Cancer Transcriptome Sequencing Data with FusionSeeker

Gene fusions are prevalent in a wide array of cancer types with different frequencies. Long-read transcriptome sequencing technologies, such as PacBio, Iso-Seq, and Nanopore direct RNA sequencing, provide full-length transcript sequencing reads, which could facilitate detection of gene fusions. In this work, we developed a method, FusionSeeker, to comprehensively characterize gene fusions in long-read cancer transcriptome data and reconstruct accurate fused transcripts from raw reads. FusionSeeker identified gene fusions in both exonic and intronic regions, allowing comprehensive characterization of gene fusions in cancer transcriptomes. Fused transcript sequences were reconstructed with FusionSeeker by correcting sequencing errors in the raw reads through partial order alignment algorithm. Using these accurate transcript sequences, FusionSeeker refined gene fusion breakpoint positions and predicted breakpoints at single bp resolution. Overall, FusionSeeker will enable users to discover gene fusions accurately using long-read data, which can facilitate downstream functional analysis as well as improved cancer diagnosis and treatment.

SIGNIFICANCE

FusionSeeker is a new method to discover gene fusions and reconstruct fused transcript sequences in long-read cancer transcriptome sequencing data to help identify novel gene fusions important for tumorigenesis and progression.

Neoplasia-associated Chromosome Translocations Resulting in Gene Truncation

Chromosomal translocations in cancer as well as benign neoplasias typically lead to the formation of fusion genes. Such genes may encode chimeric proteins when two protein-coding regions fuse in-frame, or they may result in deregulation of genes via promoter swapping or translocation of the gene into the vicinity of a highly active regulatory element. A less studied consequence of chromosomal translocations is the fusion of two breakpoint genes resulting in an out-of-frame chimera. The breaks then occur in one or both protein-coding regions forming a stop codon in the chimeric transcript shortly after the fusion point. Though the latter genetic events and mechanisms at first awoke little research interest, careful investigations have established them as neither rare nor inconsequential. In the present work, we review and discuss the truncation of genes in neoplastic cells resulting from chromosomal rearrangements, especially from seemingly balanced translocations.

Integrative analysis of synovial sarcoma transcriptome reveals different types of transcriptomic changes

Background: Synovial sarcoma (SS) is a rare and aggressive cancer that can come from distinct soft tissue types including muscle and ligaments. However, the transcriptomic landscape of SS is still poorly understood. This study aimed to systematically dissect the changes in SS transcriptome from different perspectives.

Methods: We performed deep total RNA sequencing on ten paired Synovial sarcoma and tumor-adjacent tissues to systematically dissect the transcriptomic profile of SS in terms of gene expression, alternative splicing, gene fusion, and circular RNAs.

Results: A total of 2,309 upregulated and 1,977 downregulated genes were identified between SS and tumor-adjacent tissues. Those upregulated genes could lead to the upregulation of the cell cycle, ribosome, and DNA replication pathways, while the downregulated genes may result in the downregulation of a set of metabolic biological processes and signaling pathways. Moreover, 2,511 genes (including 21 splicing factors) were differentially alternative spliced, indicating that the deregulation of alternative splicing could be one important factor that contributes to tumorigenesis. Additionally, we identified the known gene fusions of SS18-SSX1/SSX2 as well as 11 potentially novel gene fusions. Interestingly, 49 circular RNAs were differentially expressed and their parental genes could function in muscle contraction and muscle system processes.

Conclusions: Collectively, our comprehensive dissection of the transcriptomic changes of SS from both transcriptional and post-transcriptional levels provides novel insights into the biology and underlying molecular mechanism of SS.

BCL6-SPECC1L: A Novel Fusion Gene in Nasopharyngeal Carcinoma

Background: Nasopharyngeal carcinomas (NPCs) are malignant tumors originating from the lining epithelium of the nasopharynx. Fusion genes have been confirmed to play important roles in the occurrence and development of various malignant tumors, but the role of fusion genes in NPC is poorly understood. We aimed to explore new fusion genes that promote the occurrence and development of NPC. Methods: RNA-seq was used to search for interchromosomal translocations in 18 NPC tissues. Polymerase chain reaction (PCR) and Sanger sequencing were applied to verify the presence of BCL6-SPECC1L (BS); quantitative PCR (qPCR) and Western blotting were used to measure the expression level of BCL-6 in NPC cells; MTT and in vivo tumorigenesis assays were applied to evaluate the cell proliferation ability; immunofluorescence assays were used to determine the cellular localization of BCL6 and BS; and a luciferase reporter assay was performed to evaluate the ability of BCL6 and BS to inhibit transcription. Results: BS was present in 5.34% (11/206) of primary NPC biopsies and 2.13% (1/47) of head and neck cancer biopsies. The expression of BCL6 was downregulated in NPC, and silencing of endogenous BCL6 promoted NPC cell proliferation in vitro. Overexpression of BCL6 but not BS inhibited the growth of NPC cells in vivo and in vitro. Mechanistically, BCL6 localized in the nucleus can inhibit the G1/S transition to suppress the growth of NPC cells. However, after the fusion of BCL6 and SPECC1L, the product cannot localize to the nucleus, and the transcriptional inhibitory function of BCL6 is abolished, eventually abolishing its tumor suppressor effect and leading to the development of NPC. Conclusion: BS is a novel fusion gene in NPC that may play an important role in the occurrence and development of this cancer. The clinical significance of the BS fusion gene needs further elucidation.

Gene Duplication and Gene Fusion Are Important Drivers of Tumourigenesis during Cancer Evolution

Chromosomal rearrangement and genome instability are common features of cancer cells in human. Consequently, gene duplication and gene fusion events are frequently observed in human malignancies and many of the products of these events are pathogenic, representing significant drivers of tumourigenesis and cancer evolution. In certain subsets of cancers duplicated and fused genes appear to be essential for initiation of tumour formation, and some even have the capability of transforming normal cells, highlighting the importance of understanding the events that result in their formation. The mechanisms that drive gene duplication and fusion are unregulated in cancer and they facilitate rapid evolution by selective forces akin to Darwinian survival of the fittest on a cellular level. In this review, we examine current knowledge of the landscape and prevalence of gene duplication and gene fusion in human cancers.

Demystifying emerging bulk RNA-Seq applications: the application and utility of bioinformatic methodology

Significant innovations in next-generation sequencing techniques and bioinformatics tools have impacted our appreciation and understanding of RNA. Practical RNA sequencing (RNA-Seq) applications have evolved in conjunction with sequence technology and bioinformatic tools advances. In most projects, bulk RNA-Seq data is used to measure gene expression patterns, isoform expression, alternative splicing and single-nucleotide polymorphisms. However, RNA-Seq holds far more hidden biological information including details of copy number alteration, microbial contamination, transposable elements, cell type (deconvolution) and the presence of neoantigens. Recent novel and advanced bioinformatic algorithms developed the capacity to retrieve this information from bulk RNA-Seq data, thus broadening its scope. The focus of this review is to comprehend the emerging bulk RNA-Seq-based analyses, emphasizing less familiar and underused applications. In doing so, we highlight the power of bulk RNA-Seq in providing biological insights.

Role of chimeric transcript formation in the pathogenesis of birth defects

Chimeric transcripts are formed by chromosomal aberrations. Little is known about the role of chimeric transcripts in the pathogenesis of birth defects. We reanalyzed RNA-seq data in alignment map files from the peripheral blood of 56 patients in whom the diagnoses could not be confirmed by standard exome analysis and transcriptome analysis to screen for chimeric transcripts using a dedicated software, ChimPipe. Chimeric analysis led to a diagnosis in two of the 56 patients: (a) the first patient had a chimeric transcript spanning the causative gene ZEB2 and the GTDC1 gene in its neighboring locus. RNA-seq revealed reads spanning exon 5 of ZEB2 and exon 7 of GTDC1. Whole genome sequencing revealed a 436-kb deletion spanning intron 4 of ZEB2 and intron 7 of GTDC1 and the diagnosis of Mowat-Wilson syndrome was made. (b) The second patient had a chimeric transcript spanning the causative gene KCNK9 and the TRAPPC9 gene in its neighboring locus. RNA-seq revealed reads spanning exon 21 of TRAPPC9 and exon 1 of KCNK9. Whole genome sequencing revealed a 186-kb deletion spanning intron 20 of TRAPPC9 and intron 1 of KCNK9 in this patient. KCNK9 gene is a maternally expressed imprinted gene. The diagnosis of Birk-Barel syndrome was made. Thus, both patients had chimeric transcripts that were directly involved in the pathogenesis of the birth defects. The approach reported herein, of detecting chimeric transcripts from RNA-seq data, is unique in that the approach does not rely on any prior information on the presence of genomic deletion.

Interstitial Deletions Generating Fusion Genes

A fusion gene is the physical juxtaposition of two different genes resulting in a structure consisting of the head of one gene and the tail of the other. Gene fusion is often a primary neoplasia-inducing event in leukemias, lymphomas, solid malignancies as well as benign tumors. Knowledge about fusion genes is crucial not only for our understanding of tumorigenesis, but also for the diagnosis, prognostication, and treatment of cancer. Balanced chromosomal rearrangements, in particular translocations and inversions, are the most frequent genetic events leading to the generation of fusion genes. In the present review, we summarize the existing knowledge on chromosome deletions as a mechanism for fusion gene formation. Such deletions are mostly submicroscopic and, hence, not detected by cytogenetic analyses but by array comparative genome hybridization (aCGH) and/or high throughput sequencing (HTS). They are found across the genome in a variety of neoplasias. As tumors are increasingly analyzed using aCGH and HTS, it is likely that more interstitial deletions giving rise to fusion genes will be found, significantly impacting our understanding and treatment of cancer.

KDM3B-ETF1 fusion gene downregulates LMO2 via the WNT/β-catenin signaling pathway, promoting metastasis of invasive ductal carcinoma

Breast cancer is the most common malignancy for women, with invasive ductal carcinoma being the largest subtype of breast cancers, accounting for 75-80% of cases. However, the underlying mechanism of invasive ductal carcinoma remains unclear. In this study, we investigate the possible effects KDM3B-ETF1 fusion gene has on breast cancer cell metastasis, invasion and its downstream signaling mediators as revealed from RNA sequence data analysis. As predicted, KDM3B-ETF1 expression was increased in breast cancer tissues and cells. Overexpression of KDM3B-ETF1 in cancer cell lines promoted the growth and invasion of breast cancer cells, while KDM3B-ETF1 knockdown showed the opposite effects on malignant cell growth and invasion both in vivo and in vitro as evidenced by cell counting kit-8, Transwell assay and tumor xenograft in nude mice. On the contrary, LIM Domain Only 2 (LMO2) expression was significantly reduced in breast cancer tissues and cells. According to chromatin immunoprecipitation and Western blot analysis, KDM3B-ETF1 targets LMO2 and reduced the expression of LMO2, leading to an increase in WNT/β-catenin signaling pathway and thus promoting invasion. In conclusion, fusion gene KDM3B-ETF1 inhibits LMO2, activates the Wnt/β-catenin signaling pathway that leads to increased breast cancer cell invasion and metastasis, providing a novel insight into developing therapeutic strategies. These results provide novel insights into the molecular mechanism of invasive ductal carcinomas, which may lead to potential therapeutic targets.

An integrated deep learning and dynamic programming method for predicting tumor suppressor genes, oncogenes, and fusion from PDB structures

Mutations in proto-oncogenes (ONGO) and the loss of regulatory function of tumor suppression genes (TSG) are the common underlying mechanism for uncontrolled tumor growth. While cancer is a heterogeneous complex of distinct diseases, finding the potentiality of the genes related functionality to ONGO or TSG through computational studies can help develop drugs that target the disease. This paper proposes a classification method that starts with a preprocessing stage to extract the feature map sets from the input 3D protein structural information. The next stage is a deep convolutional neural network stage (DCNN) that outputs the probability of functional classification of genes. We explored and tested two approaches: in Approach 1, all filtered and cleaned 3D-protein-structures (PDB) are pooled together, whereas in Approach 2, the primary structures and their corresponding PDBs are separated according to the genes' primary structural information. Following the DCNN stage, a dynamic programming-based method is used to determine the final prediction of the primary structures' functionality. We validated our proposed method using the COSMIC online database. For the ONGO vs TSG classification problem the AUROC of the DCNN stage for Approach 1 and Approach 2 DCNN are 0.978 and 0.765, respectively. The AUROCs of the final genes' primary structure functionality classification for Approach 1 and Approach 2 are 0.989, and 0.879, respectively. For comparison, the current state-of-the-art reported AUROC is 0.924. Our results warrant further study to apply the deep learning models to humans' (GRCh38) genes, for predicting their corresponding probabilities of functionality in the cancer drivers.

LongGF: computational algorithm and software tool for fast and accurate detection of gene fusions by long-read transcriptome sequencing

BACKGROUND

Long-read RNA-Seq techniques can generate reads that encompass a large proportion or the entire mRNA/cDNA molecules, so they are expected to address inherited limitations of short-read RNA-Seq techniques that typically generate < 150 bp reads. However, there is a general lack of software tools for gene fusion detection from long-read RNA-seq data, which takes into account the high basecalling error rates and the presence of alignment errors.

RESULTS

In this study, we developed a fast computational tool, LongGF, to efficiently detect candidate gene fusions from long-read RNA-seq data, including cDNA sequencing data and direct mRNA sequencing data. We evaluated LongGF on tens of simulated long-read RNA-seq datasets, and demonstrated its superior performance in gene fusion detection. We also tested LongGF on a Nanopore direct mRNA sequencing dataset and a PacBio sequencing dataset generated on a mixture of 10 cancer cell lines, and found that LongGF achieved better performance to detect known gene fusions over existing computational tools. Furthermore, we tested LongGF on a Nanopore cDNA sequencing dataset on acute myeloid leukemia, and pinpointed the exact location of a translocation (previously known in cytogenetic resolution) in base resolution, which was further validated by Sanger sequencing.

CONCLUSIONS

In summary, LongGF will greatly facilitate the discovery of candidate gene fusion events from long-read RNA-Seq data, especially in cancer samples. LongGF is implemented in C++ and is available at https://github.com/WGLab/LongGF .

Molecular pathogenesis and prognostication of "low-grade'' and "high-grade" endometrial stromal sarcoma

Endometrial stromal sarcomas (ESS) are a heterogeneous group of rare mesenchymal cancers. Considerable knowledge has been gained in recent years about the molecular characteristics of these cancers, which helps to classify them in a more meaningful manner leading to improved diagnosis, prognostication, and treatment. According to this classification, ESS is now grouped as low‐ or high‐grade. ESS may have overlapping clinical presentation, morphology, and immunohistochemical profile. Their genetic characteristics allow subdivision of many of them depending on which pathogenetically important fusion genes they carry, but clearly much more needs to be unraveled in this regard. We here provide an overview of the molecular pathogenetic knowledge gained so far on low‐ and high‐grade ESS.

Identification of novel fusion transcripts in meningioma

INTRODUCTION

Meningiomas are the most common primary intracranial tumor. Recent next generation sequencing analyses have elaborated the molecular drivers of this disease. We aimed to identify and characterize novel fusion genes in meningiomas.

METHODS

We performed a secondary analysis of our RNA sequencing data of 145 primary meningioma from 140 patients to detect fusion genes. Semi-quantitative rt-PCR was performed to confirm transcription of the fusion genes in the original tumors. Whole exome sequencing was performed to identify copy number variations within each tumor sample. Comparative RNA seq analysis was performed to assess the clonality of the fusion constructs within the tumor.

RESULTS

We detected six fusion events (NOTCH3-SETBP1, NF2-SPATA13, SLC6A3-AGBL3, PHF19-FOXP2 in two patients, and ITPK1-FBP2) in five out of 145 tumor samples. All but one event (NF2-SPATA13) led to extremely short reading frames, making these events de facto null alleles. Three of the five patients had a history of childhood radiation. Four out of six fusion events were detected in expression type C tumors, which represent the most aggressive meningioma. We validated the presence of the RNA transcripts in the tumor tissue by semi-quantitative RT PCR. All but the two PHF19-FOXP2 fusions demonstrated high degrees of clonality.

CONCLUSIONS

Fusion genes occur infrequently in meningiomas and are more likely to be found in tumors with greater degree of genomic instability (expression type C) or in patients with history of cranial irradiation.

Fbxl17 is rearranged in breast cancer and loss of its activity leads to increased global O-GlcNAcylation

In cancer, many genes are mutated by genome rearrangement, but our understanding of the functional consequences of this remains rudimentary. Here we report the F-box protein encoded by FBXL17 is disrupted in the region of the gene that encodes its substrate-binding leucine rich repeat (LRR) domain. Truncating Fbxl17 LRRs impaired its association with the other SCF holoenzyme subunits Skp1, Cul1 and Rbx1, and decreased ubiquitination activity. Loss of the LRRs also differentially affected Fbxl17 binding to its targets. Thus, genomic rearrangements in FBXL17 are likely to disrupt SCFFbxl17-regulated networks in cancer cells. To investigate the functional effect of these rearrangements, we performed a yeast two-hybrid screen to identify Fbxl17-interacting proteins. Among the 37 binding partners Uap1, an enzyme involved in O-GlcNAcylation of proteins was identified most frequently. We demonstrate that Fbxl17 binds to UAP1 directly and inhibits its phosphorylation, which we propose regulates UAP1 activity. Knockdown of Fbxl17 expression elevated O-GlcNAcylation in breast cancer cells, arguing for a functional role for Fbxl17 in this metabolic pathway.

Landscape characterization of chimeric RNAs in colorectal cancer

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

Chimeric RNAs in cancer

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

GOLT1A-KISS1 fusion is associated with metastasis in adenoid cystic carcinomas

Genetic alterations can drive carcinogenesis. Numerous studies have shown that gene fusion is associated with cancer progression and could provide valuable biomarkers for clinical diagnosis or targets for cancer therapy. Adenoid cystic carcinoma (ACC) is a rare form of adenocarcinoma, characterized by frequent local recurrence and high rates of distant metastasis, ultimately resulting in low survival rates. Owing to the lack of effective therapeutic targets and limited biomarkers for diagnosis, a deeper understanding of the molecular basis of ACC is urgently needed. Here, we show that gene fusion is associated with ACC metastasis. We identified a metastasis suppressor KISS1 fused with a close-by gene, GOLT1A, in highly metastatic ACC cell lines and human specimens. Such fusion blocks KISS1 translation, but not transcription, by introducing 5' upstream open reading frames (uORFs) in the GOLT1A-KISS1 fusion transcript. Deletion of these uORFs rescued KISS1 expression and reduced invasion and migration of metastatic ACC cells. We also detected GOLT1A-KISS1 fusion transcripts in other types of highly metastatic cancer cell lines. Taken together, our results highlight the significance of this novel GOLT1A-KISS1 gene fusion in tumor metastasis and provide a valuable biomarker for clinical diagnosis and future therapeutic targeting of ACC.

Merging new-age biomarkers and nanodiagnostics for precision prostate cancer management

The accurate identification and stratified treatment of clinically significant early-stage prostate cancer have been ongoing concerns since the outcomes of large international prostate cancer screening trials were reported. The controversy surrounding clinical and cost benefits of prostate cancer screening has highlighted the lack of strategies for discriminating high-risk disease (that requires early treatment) from low-risk disease (that could be managed using watchful waiting or active surveillance). Advances in molecular subtyping and multiomics nanotechnology-based prostate cancer risk delineation can enable refinement of prostate cancer molecular taxonomy into clinically meaningful and treatable subtypes. Furthermore, the presence of intertumoural and intratumoural heterogeneity in prostate cancer warrants the development of novel nanodiagnostic technologies to identify clinically significant prostate cancer in a rapid, cost-effective and accurate manner. Circulating and urinary next-generation prostate cancer biomarkers for disease molecular subtyping and the newest complementary nanodiagnostic platforms for enhanced biomarker detection are promising tools for precision prostate cancer management. However, challenges in merging both aspects and clinical translation still need to be overcome.

Linked-read Sequencing Analysis Reveals Tumor-specific Genome Variation Landscapes in Neurofibromatosis Type 2 (NF2) Patients

HYPOTHESIS

We hypothesize that genomic variants including deletions, insertions, inversions, and tandem duplications beyond the changes in tumor suppressor NF2 gene affect gene expression of tumor-specific pathways in vestibular schwannomas (VS) patients with Neurofibromatosis type 2 (NF2), thus contributing to their clinical behavior.

BACKGROUND

Genomic variation could reconfigure transcription in NF2 transformation process. Therefore, genome-wide high-resolution characterization of structural variants (SV) landscapes in NF2 tumors can expand our understanding of the genes regulating the clinical phenotypes in NF2-associated VS.

METHODS

We performed whole-genome haplotype-specific structural variation analysis using synthetic linked reads generated through microfluidics-based barcoding of high molecular weight DNA followed by high-coverage Illumina paired-end whole-genome sequencing from 10 patients' tumors of different growth rates and their matching blood samples.

RESULTS

NF2 tumor-specific deletions and large SVs were detected and can be classified based on their association with tumor growth rates. Through detailed annotation of these mutations, we uncover common alleles affected by these deletions and large SVs that can be associated with signaling pathways implicated in cell proliferation and tumorigenesis.

CONCLUSION

The genomic variation landscape of NF2-related VS was investigated through whole-genome linked-read sequencing. Large SVs, in addition to deletions, were identified and may serve as modulators of clinical behavior.

A New Era of Prostate Cancer Precision Medicine

Prostate cancer is the second most common male cancer affecting Western society. Despite substantial advances in the exploration of prostate cancer biomarkers and treatment strategies, men are over diagnosed with inert prostate cancer, while there is also a substantial mortality from the invasive disease. Precision medicine is the management of treatment profiles across different cancers predicting therapies for individual cancer patients. With strategies including individual genomic profiling and targeting specific cancer pathways, precision medicine for prostate cancer has the potential to impose changes in clinical practices. Some of the recent advances in prostate cancer precision medicine comprise targeting gene fusions, genome editing tools, non-coding RNA biomarkers, and the promise of liquid tumor profiling. In this review, we will discuss these recent scientific advances to scale up these approaches and endeavors to overcome clinical barriers for prostate cancer precision medicine.

Diagnosis of fusion genes using targeted RNA sequencing

Fusion genes are a major cause of cancer. Their rapid and accurate diagnosis can inform clinical action, but current molecular diagnostic assays are restricted in resolution and throughput. Here, we show that targeted RNA sequencing (RNAseq) can overcome these limitations. First, we establish that fusion gene detection with targeted RNAseq is both sensitive and quantitative by optimising laboratory and bioinformatic variables using spike-in standards and cell lines. Next, we analyse a clinical patient cohort and improve the overall fusion gene diagnostic rate from 63% with conventional approaches to 76% with targeted RNAseq while demonstrating high concordance for patient samples with previous diagnoses. Finally, we show that targeted RNAseq offers additional advantages by simultaneously measuring gene expression levels and profiling the immune-receptor repertoire. We anticipate that targeted RNAseq will improve clinical fusion gene detection, and its increasing use will provide a deeper understanding of fusion gene biology.

Rapid and accurate detection of fusion genes is important in cancer diagnostics. Here, the authors demonstrate that targeted RNA sequencing provides fast, sensitive and quantitative gene fusion detection and overcomes the limitations of approaches currently in clinical use.

AtFusionDB: a database of fusion transcripts in Arabidopsis thaliana

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.

Detection of a MicroRNA molecular signature of ultraviolet radiation in the superficial regions of melanocytic nevi on sun-exposed skin

How melanocytes transform into melanoma cells remains largely unknown. However, prolonged ultraviolet radiation exposure is linked with melanoma, and the DNA of melanomas arising in chronically sun-exposed skin is characterized by an elevated number of pyrimidine transitions, mainly C>T (predominantly caused by ultraviolet B), and transversions of GC>TA or AT>CG (caused by ultraviolet A over indirect mechanisms). Since ultraviolet penetrates mostly only the superficial dermis, we sought to determine the extent to which superficial and deep melanocytes of nevi in sun-exposed skin differ in their miRNA expression and consider the changes as likely secondary to ultraviolet radiation-induced damage. The differentially expressed miRNAs were analyzed for known potential oncomiRs or linked to potential oncogenes or tumor suppressors. Superficial and deep melanocytes were microdissected from the nevi of 14 patients. The suspensions were processed for hybridization to a ribonucleotide protection system with 2280 total probes, including 2256 miRNA probes targeting 2083 human miRNAs. A comprehensive analysis of all human miRNAs registered in miRBase 11.0 was performed using the HTG Molecular Diagnostic database. Statistical analysis of these data yielded for 14 samples a statistically relevant profile of 39 miRNA species at FDR<0.1 that were differentially expressed between superficial and deep melanocytes. Ingenuity Pathway Analysis based on the expression data of these 39 miRNAs suggested the gene transcripts AR, MDM2, SMAD2/3, and YBX1 as the most probable miRNA targets, which were validated at the protein level. Our findings suggest that superficial ultraviolet radiation-damaged melanocytes can be differentiated from deep melanocytes on the basis of the expression of 39 miRNAs, the most probable gene transcript and protein targets of which are AR, MDM2, SMAD2/3, and YBX1, with YBX1 expression validating the best the molecular signature in immunohistochemical analysis.

Picky comprehensively detects high-resolution structural variants in nanopore long reads

Acquired genomic structural variants (SVs) are major hallmarks of cancer genomes, but they are challenging to reconstruct from short-read sequencing data. Here we exploited the long reads of the nanopore platform using our customized pipeline, Picky ( https://github.com/TheJacksonLaboratory/Picky ), to reveal SVs of diverse architecture in a breast cancer model. We identified the full spectrum of SVs with superior specificity and sensitivity relative to short-read analyses, and uncovered repetitive DNA as the major source of variation. Examination of genome-wide breakpoints at nucleotide resolution uncovered micro-insertions as the common structural features associated with SVs. Breakpoint density across the genome is associated with the propensity for interchromosomal connectivity and was found to be enriched in promoters and transcribed regions of the genome. Furthermore, we observed an over-representation of reciprocal translocations from chromosomal double-crossovers through phased SVs. We demonstrate that Picky analysis is an effective tool for comprehensive detection of SVs in cancer genomes from long-read data.

Multiple large inversions and breakpoint rewiring of gene expression in the evolution of the fire ant social supergene

Supergenes consist of co-adapted loci that segregate together and are associated with adaptive traits. In the fire ant Solenopsis invicta, two 'social' supergene variants regulate differences in colony queen number and other traits. Suppressed recombination in this system is maintained, in part, by a greater than 9 Mb inversion, but the supergene is larger. Has the supergene in S. invicta undergone multiple large inversions? The initial gene content of the inverted allele of a supergene would be the same as that of the wild-type allele. So, how did the inversion increase in frequency? To address these questions, we cloned one extreme breakpoint in the fire ant supergene. In doing so, we found a second large (greater than 800 Kb) rearrangement. Furthermore, we determined the temporal order of the two big inversions based on the translocation pattern of a third small fragment. Because the S. invicta supergene lacks evolutionary strata, our finding of multiple inversions may support an introgression model of the supergene. Finally, we showed that one of the inversions swapped the promoter of a breakpoint-adjacent gene, which might have conferred a selective advantage relative to the non-inverted allele. Our findings provide a rare example of gene alterations arising directly from an inversion event.

Blood-Based DNA Methylation Biomarkers for Type 2 Diabetes: Potential for Clinical Applications

Type 2 diabetes (T2D) is a leading cause of death and disability worldwide. It is a chronic metabolic disorder that develops due to an interplay of genetic, lifestyle, and environmental factors. The biological onset of the disease occurs long before clinical symptoms develop, thus the search for early diagnostic and prognostic biomarkers, which could facilitate intervention strategies to prevent or delay disease progression, has increased considerably in recent years. Epigenetic modifications represent important links between genetic, environmental and lifestyle cues and increasing evidence implicate altered epigenetic marks such as DNA methylation, the most characterized and widely studied epigenetic mechanism, in the pathogenesis of T2D. This review provides an update of the current status of DNA methylation as a biomarker for T2D. Four databases, Scopus, Pubmed, Cochrane Central, and Google Scholar were searched for studies investigating DNA methylation in blood. Thirty-seven studies were identified, and are summarized with respect to population characteristics, biological source, and method of DNA methylation quantification (global, candidate gene or genome-wide). We highlight that differential methylation of the TCF7L2, KCNQ1, ABCG1, TXNIP, PHOSPHO1, SREBF1, SLC30A8, and FTO genes in blood are reproducibly associated with T2D in different population groups. These genes should be prioritized and replicated in longitudinal studies across more populations in future studies. Finally, we discuss the limitations faced by DNA methylation studies, which include including interpatient variability, cellular heterogeneity, and lack of accounting for study confounders. These limitations and challenges must be overcome before the implementation of blood-based DNA methylation biomarkers into a clinical setting. We emphasize the need for longitudinal prospective studies to support the robustness of the current findings of this review.

Development of locus specific sub-clone separation by fluorescence in situ hybridization in suspension in chronic lymphocytic leukemia

Intra-tumor genetic heterogeneity is a hallmark of cancer. The ability to monitor and analyze these sub-clonal cell populations can be considered key to successful treatment, particularly in the modern era of targeted therapies. Although advances in sequencing technologies have significantly improved our ability to analyze the mutational landscape of tumors, this utility is reduced when considering small, but clinically significant sub-clones, that is, those representing <10% of the tumor burden. We have developed a high-throughput method that utilizes a 17-probe labeled bacterial artificial chromosome contig to quantify sub-clonal populations of cells based on deletion of a single locus. Chronic lymphocytic leukemia (CLL) cells harboring deletion of the short arm of chromosome 17 (del17p), an important prognostic marker for CLL were used to demonstrate the technique. Sub-clones of del17p cells were quantified and isolated from heterogeneous CLL populations using fluorescence in situ hybridization in suspension (FISH-IS) and the locus specific probe set. Using the combination of FISH-IS with the locus-specific probe set enables automated analysis of tens of thousands of cells, accurately quantifying and isolating cells carrying a del17p. Based on the fluorescence intensity of 17p probes, 17p (TP53) deleted cells were identified and sorted using flow cytometric techniques, and enrichment was demonstrated using single nucleotide polymorphism analysis. The ability to separate sub-clones of cells based on genetic heterogeneity, independent of the clone size, highlights the potential application of this method not only in the diagnostic and prognostic setting, but also as an unbiased approach to enable further detailed genetic analysis of the sub-clone with deep sequencing approaches. © 2017 International Society for Advancement of Cytometry.

ChimeRScope: a novel alignment-free algorithm for fusion transcript prediction using paired-end RNA-Seq data

The RNA-Seq technology has revolutionized transcriptome characterization not only by accurately quantifying gene expression, but also by the identification of novel transcripts like chimeric fusion transcripts. The ‘fusion’ or ‘chimeric’ transcripts have improved the diagnosis and prognosis of several tumors, and have led to the development of novel therapeutic regimen. The fusion transcript detection is currently accomplished by several software packages, primarily relying on sequence alignment algorithms. The alignment of sequencing reads from fusion transcript loci in cancer genomes can be highly challenging due to the incorrect mapping induced by genomic alterations, thereby limiting the performance of alignment-based fusion transcript detection methods. Here, we developed a novel alignment-free method, ChimeRScope that accurately predicts fusion transcripts based on the gene fingerprint (as k-mers) profiles of the RNA-Seq paired-end reads. Results on published datasets and in-house cancer cell line datasets followed by experimental validations demonstrate that ChimeRScope consistently outperforms other popular methods irrespective of the read lengths and sequencing depth. More importantly, results on our in-house datasets show that ChimeRScope is a better tool that is capable of identifying novel fusion transcripts with potential oncogenic functions. ChimeRScope is accessible as a standalone software at (https://github.com/ChimeRScope/ChimeRScope/wiki) or via the Galaxy web-interface at (https://galaxy.unmc.edu/).

GFusion: an Effective Algorithm to Identify Fusion Genes from Cancer RNA-Seq Data

Fusion gene derived from genomic rearrangement plays a key role in cancer initiation. The discovery of novel gene fusions may be of significant importance in cancer diagnosis and treatment. Meanwhile, next generation sequencing technology provide a sensitive and efficient way to identify gene fusions in genomic levels. However, there are still many challenges and limitations remaining in the existing methods which only rely on unmapped reads or discordant alignment fragments. In this work we have developed GFusion, a novel method using RNA-Seq data, to identify the fusion genes. This pipeline performs multiple alignments and strict filtering algorithm to improve sensitivity and reduce the false positive rate. GFusion successfully detected 34 from 43 previously reported fusions in four cancer datasets. We also demonstrated the effectiveness of GFusion using 24 million 76 bp paired-end reads simulation data which contains 42 artificial fusion genes, among which GFusion successfully discovered 37 fusion genes. Compared with existing methods, GFusion presented higher sensitivity and lower false positive rate. The GFusion pipeline can be accessed freely for non-commercial purposes at: https://github.com/xiaofengsong/GFusion .

Platelet-derived growth factor receptors (PDGFRs) fusion genes involvement in hematological malignancies

PURPOSE

To investigate oncogenic platelet-derived growth factor receptor(PDGFR) fusion genes involvement in hematological malignancies, the advances in the PDGFR fusion genes diagnosis and development of PDGFR fusions inhibitors.

METHODS

Literature search was done using terms "PDGFR and Fusion" or "PDGFR and Myeloid neoplasm" or 'PDGFR and Lymphoid neoplasm' or "PDGFR Fusion Diagnosis" or "PDGFR Fusion Targets" in databases including PubMed, ASCO.org, and Medscape.

RESULTS

Out of the 36 fusions detected, ETV6(TEL)-PDGFRB and FIP1L1-PDGFRA fusions were frequently detected, 33 are as a result of chromosomal translocation, FIP1L1-PDGFRA and EBF1-PDGFRB are the result of chromosomal deletion and CDK5RAP2- PDGFRΑ is the result of chromosomal insertion. Seven of the 34 rare fusions have detectable reciprocals.

CONCLUSION

RNA aptamers are promising therapeutic target of PDGFRs and diagnostic tools of PDGFRs fusion genes. Also, PDGFRs have variable prospective therapeutic strategies including small molecules, RNA aptamers, and interference therapeutics as well as development of adaptor protein Lnk mimetic drugs.

GeneBreak: detection of recurrent DNA copy number aberration-associated chromosomal breakpoints within genes

Development of cancer is driven by somatic alterations, including numerical and structural chromosomal aberrations. Currently, several computational methods are available and are widely applied to detect numerical copy number aberrations (CNAs) of chromosomal segments in tumor genomes. However, there is lack of computational methods that systematically detect structural chromosomal aberrations by virtue of the genomic location of CNA-associated chromosomal breaks and identify genes that appear non-randomly affected by chromosomal breakpoints across (large) series of tumor samples. 'GeneBreak' is developed to systematically identify genes recurrently affected by the genomic location of chromosomal CNA-associated breaks by a genome-wide approach, which can be applied to DNA copy number data obtained by array-Comparative Genomic Hybridization (CGH) or by (low-pass) whole genome sequencing (WGS). First, 'GeneBreak' collects the genomic locations of chromosomal CNA-associated breaks that were previously pinpointed by the segmentation algorithm that was applied to obtain CNA profiles. Next, a tailored annotation approach for breakpoint-to-gene mapping is implemented. Finally, dedicated cohort-based statistics is incorporated with correction for covariates that influence the probability to be a breakpoint gene. In addition, multiple testing correction is integrated to reveal recurrent breakpoint events. This easy-to-use algorithm, 'GeneBreak', is implemented in R ( www.cran.r-project.org) and is available from Bioconductor ( www.bioconductor.org/packages/release/bioc/html/GeneBreak.html).

GeneBreak: detection of recurrent DNA copy number aberration-associated chromosomal breakpoints within genes

Development of cancer is driven by somatic alterations, including numerical and structural chromosomal aberrations. Currently, several computational methods are available and are widely applied to detect numerical copy number aberrations (CNAs) of chromosomal segments in tumor genomes. However, there is lack of computational methods that systematically detect structural chromosomal aberrations by virtue of the genomic location of CNA-associated chromosomal breaks and identify genes that appear non-randomly affected by chromosomal breakpoints across (large) series of tumor samples. 'GeneBreak' is developed to systematically identify genes recurrently affected by the genomic location of chromosomal CNA-associated breaks by a genome-wide approach, which can be applied to DNA copy number data obtained by array-Comparative Genomic Hybridization (CGH) or by (low-pass) whole genome sequencing (WGS). First, 'GeneBreak' collects the genomic locations of chromosomal CNA-associated breaks that were previously pinpointed by the segmentation algorithm that was applied to obtain CNA profiles. Next, a tailored annotation approach for breakpoint-to-gene mapping is implemented. Finally, dedicated cohort-based statistics is incorporated with correction for covariates that influence the probability to be a breakpoint gene. In addition, multiple testing correction is integrated to reveal recurrent breakpoint events. This easy-to-use algorithm, 'GeneBreak', is implemented in R ( www.cran.r-project.org) and is available from Bioconductor ( www.bioconductor.org/packages/release/bioc/html/GeneBreak.html).