ChimerDB 4.0: an updated and expanded database of fusion genes

Integrating Optical Genome Mapping and Whole Genome Sequencing in Somatic Structural Variant Detection

Structural variants drive tumorigenesis by disrupting normal gene function through insertions, inversions, translocations, and copy number changes, including deletions and duplications. Detecting structural variants is crucial for revealing their roles in tumor development, clinical outcomes, and personalized therapy. Presently, most studies rely on short-read data from next-generation sequencing that aligns back to a reference genome to determine if and, if so, where a structural variant occurs. However, structural variant discovery by short-read sequencing is challenging, primarily because of the difficulty in mapping regions of repetitive sequences. Optical genome mapping (OGM) is a recent technology used for imaging and assembling long DNA strands to detect structural variations. To capture the structural variant landscape more thoroughly in the human genome, we developed an integrated pipeline that combines Bionano OGM and Illumina whole-genome sequencing and applied it to samples from 29 pediatric B-ALL patients. The addition of OGM allowed us to identify 511 deletions, 506 insertions, 93 duplications/gains, and 145 translocations that were otherwise missed in the short-read data. Moreover, we identified several novel gene fusions, the expression of which was confirmed by RNA sequencing. Our results highlight the benefit of integrating OGM and short-read detection methods to obtain a comprehensive analysis of genetic variation that can aid in clinical diagnosis, provide new therapeutic targets, and improve personalized medicine in cancers driven by structural variation.

Integrated analysis of transcriptome and genome variations in pediatric T cell acute lymphoblastic leukemia: data from north Indian tertiary care center

INTRODUCTION

T-cell acute lymphoblastic leukemia (T-ALL) is a genetically heterogeneous disease with poor prognosis and inferior outcome. Although multiple studies have been perform on genomics of T-ALL, data from Indian sub-continent is scarce.

METHODS

In the current study we aimed to identify the genetic variability of T-ALL in an Indian cohort of pediatric (age ≤ 12 years) T-ALL patients (n = 25) by whole transcriptome sequencing along with whole exome sequencing and correlated the findings with clinical characteristics and disease outcome.

RESULTS

The median age was 7 years (range 3 -12 years). RNA sequencing revealed a definitive fusion event in 14 cases (56%) (including a novel fusions) with STIL::TAL1 in 4 (16%), followed by NUP21::ABL1, TCF7::SPI1, ETV6::HDAC8, LMO1::RIC3, DIAPH1::JAK2, SETD2::CCDC12 and RCBTB2::LPAR6 in 1 (4%) case each. Significant aberrant expression was noted in RAG1 (64%), RAG2 (80%), MYCN (52%), NKX3-1 (52%), NKX3-2 (32%), TLX3 (28%), LMO1 (20%) and MYB (16%) genes. WES data showed frequent mutations in NOTCH1 (35%) followed by WT1 (23%), FBXW7 (12%), KRAS (12%), PHF6 (12%) and JAK3 (12%). Nearly 88.2% of cases showed a deletion of CDKN2A/CDKN2B/MTAP genes. Clinically significant association of a better EFS and OS (p=0.01) was noted with RAG2 over-expression at a median follow up of 22 months, while a poor EFS (p=0.041) and high relapse rate (p=0.045) was observed with MYB over-expression.

CONCLUSION

Overall, the present study demonstrates the frequencies of transcriptomic and genetic alterations from Indian cohort of pediatric T-ALL and is a salient addition to current genomics data sets available in T-ALL.

CTAT-LR-fusion: accurate fusion transcript identification from long and short read isoform sequencing at bulk or single cell resolution

Gene fusions are found as cancer drivers in diverse adult and pediatric cancers. Accurate detection of fusion transcripts is essential in cancer clinical diagnostics, prognostics, and for guiding therapeutic development. Most currently available methods for fusion transcript detection are compatible with Illumina RNA-seq involving highly accurate short read sequences. Recent advances in long read isoform sequencing enable the detection of fusion transcripts at unprecedented resolution in bulk and single cell samples. Here we developed a new computational tool CTAT-LR-fusion to detect fusion transcripts from long read RNA-seq with or without companion short reads, with applications to bulk or single cell transcriptomes. We demonstrate that CTAT-LR-fusion exceeds fusion detection accuracy of alternative methods as benchmarked with simulated and real long read RNA-seq. Using short and long read RNA-seq, we further apply CTAT-LR-fusion to bulk transcriptomes of nine tumor cell lines, and to tumor single cells derived from a melanoma sample and three metastatic high grade serous ovarian carcinoma samples. In both bulk and in single cell RNA-seq, long isoform reads yielded higher sensitivity for fusion detection than short reads with notable exceptions. By combining short and long reads in CTAT-LR-fusion, we are able to further maximize detection of fusion splicing isoforms and fusion-expressing tumor cells. CTAT-LR-fusion is available at https://github.com/TrinityCTAT/CTAT-LR-fusion/wiki.

Identification of a Musashi2 translocation as a novel oncogene in myeloid leukemia

Myeloid leukemias, diseases marked by aggressiveness and poor outcomes, are frequently triggered by oncogenic translocations. In the case of chronic myelogenous leukemia (CML) the BCR-ABL fusion initiates chronic phase disease with second hits allowing progression to blast crisis. Although Gleevec has been transformative for CML, blast crisis CML remains relatively drug resistant. Here we show that MSI2-HOXA9, a translocation with an unknown role in cancer, can serve as a second hit in driving bcCML. Compared to BCR-ABL, BCR-ABL/MSI2-HOXA9 led to a more aggressive disease in vivo with decreased latency, increased lethality and a differentiation blockade that is a hallmark of blast crisis. Domain mapping revealed that the MSI2 RNA binding domain RRM1 had a preferential impact on growth and lethality of bcCML relative to RRM2 or the HOXA9 domain. Mechanistically, MSI2-HOXA9 triggered global downstream changes with a preferential upregulation of mitochondrial components. Consistent with this, BCR-ABL/MSI2-HOXA9 cells exhibited a significant increase in mitochondrial respiration. These data suggest that MSI2-HOXA9 acts, at least in part, by increasing expression of the mitochondrial polymerase Polrmt and augmenting mitochondrial function and basal respiration in blast crisis. Collectively, our findings demonstrate for the first time that translocations involving the stem and developmental signal MSI2 can be oncogenic, and suggest that MSI, which we found to be a frequent partner for an array of translocations, could also be a driver mutation across solid cancers.

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

Dissolution of oncofusion transcription factor condensates for cancer therapy

Cancer-associated chromosomal rearrangements can result in the expression of numerous pathogenic fusion proteins. The mechanisms by which fusion proteins contribute to oncogenesis are largely unknown, and effective therapies for fusion-associated cancers are lacking. Here we comprehensively scrutinized fusion proteins found in various cancers. We found that many fusion proteins are composed of phase separation-prone domains (PSs) and DNA-binding domains (DBDs), and these fusions have strong correlations with aberrant gene expression patterns. Furthermore, we established a high-throughput screening method, named DropScan, to screen drugs capable of modulating aberrant condensates. One of the drugs identified via DropScan, LY2835219, effectively dissolved condensates in reporter cell lines expressing Ewing sarcoma fusions and partially rescued the abnormal expression of target genes. Our results indicate that aberrant phase separation is likely a common mechanism for these PS-DBD fusion-related cancers and suggest that modulating aberrant phase separation is a potential route to treat these diseases.

Discovering chromatin dysregulation induced by protein-coding perturbations at scale

Although population-scale databases have expanded to millions of protein-coding variants, insight into variant mechanisms has not kept pace. We present PROD-ATAC, a high-throughput method for discovering the effects of protein-coding variants on chromatin. A pooled library of variants is expressed in a disease-agnostic cell line, and single-cell ATAC resolves each variant's effect on chromatin. Using PROD-ATAC, we characterized the effects of >100 oncofusions (a class of cancer-causing chimeric proteins) and controls and revealed that pioneer activity is a common feature of fusions spanning an enormous range of fusion frequencies. Further, fusion-induced dysregulation can be context-agnostic as observed mechanisms often overlapped with cancer and cell-type specific prior knowledge. We also showed that gain-of-function pioneering is common among oncofusions. This work provides a global view of fusion-induced chromatin. We uncovered convergent mechanisms among disparate oncofusions and shared modes of dysregulation across different cancers. PROD-ATAC is generalizable to any set of protein-coding variants.

Genome-wide Detection of Chimeric Transcripts in Early-stage Non-small Cell Lung Cancer

BACKGROUND/AIM

Lung cancer remains the main culprit in cancer-related mortality worldwide. Transcript fusions play a critical role in the initiation and progression of multiple cancers. Treatment approaches based on specific targeting of discovered driver events, such as mutations in EGFR, and fusions in NTRK, ROS1, and ALK genes led to profound improvements in clinical outcomes. The formation of chimeric proteins due to genomic rearrangements or at the post-transcriptional level is widespread and plays a critical role in tumor initiation and progression. Yet, the fusion landscape of lung cancer remains underexplored.

MATERIALS AND METHODS

We used the JAFFA pipeline to discover transcript fusions in early-stage non-small cell lung cancer (NSCLC). The set of detected fusions was further analyzed to identify recurrent events, genes with multiple partners and fusions with high predicted oncogenic potential. Finally, we used a generalized linear model (GLM) to establish statistical associations between fusion occurrences and clinicopathological variables. RNA sequencing was used to discover and characterize transcript fusions in 270 NSCLC samples selected from the Glans-Look specimen repository. The samples were obtained during the early stages of disease prior to the initiation of chemo- or radiotherapy.

RESULTS

We identified a set of 792 fusions where 751 were novel, and 33 were recurrent. Four of the 33 recurrent fusions were significantly associated with clinicopathological variables. Several of the fusion partners were represented by well-established oncogenes ERBB4, BRAF, FGFR2, and MET.

CONCLUSION

The data presented in this study allow researchers to identify, select, and validate promising candidates for targeted clinical interventions.

Whole exome sequencing of well-differentiated liposarcoma and dedifferentiated liposarcoma in older woman: a case report

Background

Common kinds of soft tissue sarcomas (STS) include well-differentiated liposarcoma (WDLPS) and dedifferentiated liposarcoma (DDLPS). In this case, we present a comprehensive clinical profile of a patient who underwent multiple recurrences during the progression from WDLPS to DDLPS.

Case presentation

A 62-year-old Asian female underwent retroperitoneal resection of a large tumor 11 years ago, the initial pathology revealed a fibrolipoma-like lesion. Over the next six years, the patient underwent three resections for recurrence of abdominal tumors. Postoperative histology shows mature adipose tissue with scattered "adipoblast"-like cells with moderate-to-severe heterogeneous spindle cells, pleomorphic cells, or tumor giant cells. Immunohistochemistry (IHC) demonstrated positive staining for MDM2 and CDK4, confirming that the abdominal tumor was WDLPS and gradually progressing to DDLPS. Post-operative targeted sequencing and IHC confirmed the POC1B::ROS1 fusion gene in DDLPS. Whole-exome sequencing (WES) revealed that WDLPS and DDLPS shared similar somatic mutations and copy number variations (CNVs), whereas DDLPS had more mutated genes and a higher and more concentrated amplification of the chromosome 12q region. Furthermore, somatic mutations in DDLPS were significantly reduced after treatment with CDK4 inhibitors, while CNVs remained elevated.

Conclusion

Due to the high likelihood of recurrence of liposarcoma, various effective treatments should be taken into consideration even if surgery is the primary treatment for recurrent liposarcoma. To effectively control the course of the disease following surgery, combination targeted therapy may be a viable alternative to chemotherapy and radiotherapy in the treatment of liposarcoma.

Systematic discovery of gene fusions in pediatric cancer by integrating RNA-seq and WGS

BACKGROUND

Gene fusions are important cancer drivers in pediatric cancer and their accurate detection is essential for diagnosis and treatment. Clinical decision-making requires high confidence and precision of detection. Recent developments show RNA sequencing (RNA-seq) is promising for genome-wide detection of fusion products but hindered by many false positives that require extensive manual curation and impede discovery of pathogenic fusions.

METHODS

We developed Fusion-sq to overcome existing disadvantages of detecting gene fusions. Fusion-sq integrates and "fuses" evidence from RNA-seq and whole genome sequencing (WGS) using intron-exon gene structure to identify tumor-specific protein coding gene fusions. Fusion-sq was then applied to the data generated from a pediatric pan-cancer cohort of 128 patients by WGS and RNA sequencing.

RESULTS

In a pediatric pan-cancer cohort of 128 patients, we identified 155 high confidence tumor-specific gene fusions and their underlying structural variants (SVs). This includes all clinically relevant fusions known to be present in this cohort (30 patients). Fusion-sq distinguishes healthy-occurring from tumor-specific fusions and resolves fusions in amplified regions and copy number unstable genomes. A high gene fusion burden is associated with copy number instability. We identified 27 potentially pathogenic fusions involving oncogenes or tumor-suppressor genes characterized by underlying SVs, in some cases leading to expression changes indicative of activating or disruptive effects.

CONCLUSIONS

Our results indicate how clinically relevant and potentially pathogenic gene fusions can be identified and their functional effects investigated by combining WGS and RNA-seq. Integrating RNA fusion predictions with underlying SVs advances fusion detection beyond extensive manual filtering. Taken together, we developed a method for identifying candidate gene fusions that is suitable for precision oncology applications. Our method provides multi-omics evidence for assessing the pathogenicity of tumor-specific gene fusions for future clinical decision making.

Characterization and evaluation of gene fusions as a measure of genetic instability and disease prognosis in prostate cancer

BACKGROUND

Prostate cancer (PCa) is one of the most prevalent cancers worldwide. The clinical manifestations and molecular characteristics of PCa are highly variable. Aggressive types require radical treatment, whereas indolent ones may be suitable for active surveillance or organ-preserving focal therapies. Patient stratification by clinical or pathological risk categories still lacks sufficient precision. Incorporating molecular biomarkers, such as transcriptome-wide expression signatures, improves patient stratification but so far excludes chromosomal rearrangements. In this study, we investigated gene fusions in PCa, characterized potential novel candidates, and explored their role as prognostic markers for PCa progression.

METHODS

We analyzed 630 patients in four cohorts with varying traits regarding sequencing protocols, sample conservation, and PCa risk group. The datasets included transcriptome-wide expression and matched clinical follow-up data to detect and characterize gene fusions in PCa. With the fusion calling software Arriba, we computationally predicted gene fusions. Following detection, we annotated the gene fusions using published databases for gene fusions in cancer. To relate the occurrence of gene fusions to Gleason Grading Groups and disease prognosis, we performed survival analyses using the Kaplan-Meier estimator, log-rank test, and Cox regression.

RESULTS

Our analyses identified two potential novel gene fusions, MBTTPS2,L0XNC01::SMS and AMACR::AMACR. These fusions were detected in all four studied cohorts, providing compelling evidence for the validity of these fusions and their relevance in PCa. We also found that the number of gene fusions detected in a patient sample was significantly associated with the time to biochemical recurrence in two of the four cohorts (log-rank test, p-value < 0.05 for both cohorts). This was also confirmed after adjusting the prognostic model for Gleason Grading Groups (Cox regression, p-values < 0.05).

CONCLUSIONS

Our gene fusion characterization workflow revealed two potential novel fusions specific for PCa. We found evidence that the number of gene fusions was associated with the prognosis of PCa. However, as the quantitative correlations were only moderately strong, further validation and assessment of clinical value is required before potential application.

Intracranial mesenchymal tumor with (novel) COX14::PTEN rearrangement

Mesenchymal tumors of the central nervous system (CNS) include numerous entities, with different pathological features and biological behavior. Mesenchymal non-meningothelial tumors are rare and comprise neoplasms that are exclusive to the CNS or show peculiar features when occurring in the CNS compared with other sites. Within this group there are three new entities, classified on the basis of specific molecular alterations and included in the 5th edition of the WHO Classification of CNS Tumors: primary intracranial sarcoma; DICER1-mutant; CIC-rearranged sarcoma; intracranial mesenchymal tumor, FET::CREB fusion-positive. These tumors often show variable morphology, making diagnosis very challenging, although the implementation of molecular techniques has led to better characterization and more precise identification of these entities. However, many molecular alterations have yet to be discovered and some recently reported CNS tumors are currently missing an appropriate classification. Herein, we report the case of a 43-year-old man who presented with an intracranial mesenchymal tumor. Histopathological examination showed a wide spectrum of peculiar morphological features and a non-specific immunohistochemical profile. Whole transcriptome sequencing revealed the presence of a novel genetic rearrangement involving COX14 and PTEN genes, which has never been reported before in any other neoplasm. The tumor did not cluster in any defined methylation class of the brain tumor classifier, but resulted in a calibrated score of 0.89 for the methylation class "Sarcoma, MPNST-like", when analyzed by the sarcoma classifier. Our study is the first to report about this tumor with unique pathological and molecular features, characterized by a novel rearrangement between COX14 and PTEN genes. Other studies are necessary in order to define it as a new entity or as a novel rearrangement involving recently described and incompletely characterized CNS mesenchymal tumors.

MALAT1 functions as a transcriptional promoter of MALAT1::GLI1 fusion for truncated GLI1 protein expression in cancer

BACKGROUND

The long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is a cancer biomarker. Furthermore, fusion of the MALAT1 gene with glioma-associated oncogene 1 (GLI1) is a diagnostic marker of plexiform fibromyxoma and gastroblastoma; however, the function of this fusion gene remains unexplored.

METHOD

In this study, we elucidate the structure and function of the MALAT1::GLI1 fusion gene. To this end, we determined a transcriptional start site (TSS) and promoter region for truncated GLI1 expression using rapid amplification of the 5' cDNA end and a luciferase reporter assay in cultured cells transfected with a plasmid harboring the MALAT1::GLI1 fusion gene.

RESULTS

We found that the TATA box, ETS1 motif, and TSS were located in MALAT1 and that MALAT1 exhibited transcriptional activity and induced expression of GLI1 from the MALAT1::GLI1 fusion gene. Truncated GLI1, lacking SUMOylation and SUFU binding sites and located in the nucleus, upregulated mRNA expression of GLI1 target genes in the hedgehog signaling pathway.

CONCLUSIONS

We demonstrate a distinct and alternative function of MALAT1 as a transcriptional promoter for expression of the MALAT1::GLI1 fusion gene. Our findings will aid future research on MALAT1 and its fusion gene partners.

Computational design of DNA binding domain-retained fusion proteins and virtual screening against FDA-approved drugs

Even though the transcription factors (TFs) are not regarded as good drug targets, mutated or dysregulated TFs can be a unique class of drug targets. Specifically, the TF fusion protein, which is the translated structural variants including TFs may affect downstream to promote tumorigenesis. To date, we lack the fusion protein sequence information and 3D structure information in identifying the potential drugs of fusion proteins. In this study, we predicted the 3D structures of 732 transcription factor fusion proteins (TFFPs). For the top five most frequent TFFPs, we performed the virtual screening across the FDA-approved drugs. Our study will provide an initial platform to develop novel therapeutic targets in the transcription factor fusion proteins.

SFyNCS detects oncogenic fusions involving non-coding sequences in cancer

Fusion genes are well-known cancer drivers. However, very few known oncogenic fusions involve non-coding sequences. We develop SFyNCS with superior performance to detect fusions of both protein-coding genes and non-coding sequences from transcriptomic sequencing data. We validate fusions using somatic structural variations detected from the genomes. This allows us to comprehensively evaluate various fusion detection and filtering strategies and parameters. We detect 165,139 fusions in 9,565 tumor samples across 33 tumor types in the Cancer Genome Atlas cohort. Among them, 72% of the fusions involve non-coding sequences and many are recurrent. We discover two long non-coding RNAs recurrently fused with various partner genes in 32% of dedifferentiated liposarcomas and experimentally validated the oncogenic functions in mouse model.

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

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

KEY POINTS

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

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

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

Establishment of experimental salivary gland cancer models using organoid culture and patient-derived xenografting

Purpose

Depending on its histological subtype, salivary gland carcinoma (SGC) may have a poor prognosis. Due to the scarcity of preclinical experimental models, its molecular biology has so far remained largely unknown, hampering the development of new treatment modalities for patients with these malignancies. The aim of this study was to generate experimental human SGC models of multiple histological subtypes using patient-derived xenograft (PDX) and organoid culture techniques.

Methods

Tumor specimens from surgically resected SGCs were processed for the preparation of PDXs and patient-derived organoids (PDOs). Specimens from SGC PDXs were also processed for PDX-derived organoid (PDXO) generation. In vivo tumorigenicity was assessed using orthotopic transplantation of SGC organoids. The pathological characteristics of each model were compared to those of the original tumors using immunohistochemistry. RNA-seq was used to analyze the genetic traits of our models.

Results

Three series of PDOs, PDXs and PDXOs of salivary duct carcinomas, one series of PDOs, PDXs and PDXOs of mucoepidermoid carcinomas and PDXs of myoepithelial carcinomas were successfully generated. We found that PDXs and orthotopic transplants from PDOs/PDXOs showed similar histological features as the original tumors. Our models also retained their genetic traits, i.e., transcription profiles, genomic variants and fusion genes of the corresponding histological subtypes.

Conclusion

We report the generation of SGC PDOs, PDXs and PDXOs of multiple histological subtypes, recapitulating the histological and genetical characteristics of the original tumors. These experimental SGC models may serve as a useful resource for the development of novel therapeutic strategies and for investigating the molecular mechanisms underlying the development of these malignancies.

Bioinformatics-Driven Identification of p62 as A Crucial Oncogene in Liver Cancer

Liver hepatocellular carcinoma (LIHC) is the major form of liver cancer that is the fourth most common cause of cancer death worldwide. It has been reported that the multifunctional protein p62 (also known as SQSTM1) plays a cancer-promoting role in LIHC, but the detailed mechanisms underlying p62 interaction with LIHC remains unclear. To gain a comprehensive understanding of p62 interaction with LIHC in clinical settings, we performed bioinformatic analyses using various online algorithms derived from high throughput profiling. Our results indicate that p62 expression is significantly upregulated, partially due to its promoter demethylation, rather than p62 gene mutation, in LIHC. Mutation of TP53, CTNNB1, or ALB significantly correlates with, and mutation of AXIN1 reversely correlates with, the p62 expression level. Its upregulation occurs as early as liver cirrhosis, and go through all stages of the carcinogenesis. HCV infection makes a significant contribution to p62 upregulation in LIHC. We further identified p62-associated molecular signatures in LIHC, including many genes that are involved in antioxidant stress and metabolism, such as SRX1 and TXNRD1. Regarding to the clinical outcome, p62 expression level reversely correlates with the survival of LIHC patients (p<0.01). Importantly, we experimentally validated that p62 depletion in liver cancer cell lines downregulates the expression of SRX1 and TXNRD1 at both transcriptional and translational levels, and reduces cell proliferation. As the potential mechanisms underlying the tumor-promoting role of p62, we show that p62 upregulation is remarkably associated with reprogramming of pathways mediated by p53, Wnt/β-catenin, and Keap1-NRF2, which are crucial for oncogenesis in many contexts. Our findings provide a comprehensive insight into the interaction between p62 and LIHC, offering valuable information for understanding of LIHC pathogenesis.

Identification of human gene research articles with wrongly identified nucleotide sequences

Nucleotide sequence reagents underpin molecular techniques that have been applied across hundreds of thousands of publications. We have previously reported wrongly identified nucleotide sequence reagents in human research publications and described a semi-automated screening tool Seek & Blastn to fact-check their claimed status. We applied Seek & Blastn to screen >11,700 publications across five literature corpora, including all original publications in Gene from 2007 to 2018 and all original open-access publications in Oncology Reports from 2014 to 2018. After manually checking Seek & Blastn outputs for >3,400 human research articles, we identified 712 articles across 78 journals that described at least one wrongly identified nucleotide sequence. Verifying the claimed identities of >13,700 sequences highlighted 1,535 wrongly identified sequences, most of which were claimed targeting reagents for the analysis of 365 human protein-coding genes and 120 non-coding RNAs. The 712 problematic articles have received >17,000 citations, including citations by human clinical trials. Given our estimate that approximately one-quarter of problematic articles may misinform the future development of human therapies, urgent measures are required to address unreliable gene research articles.

Molecular fusion events in carcinogenic organisms: a bioinformatics study for the detection of fused proteins between viruses, bacteria and eukaryotes

Molecular fusion events have a prominent role in the initial steps of carcinogenesis. In this study, a bioinformatics analysis was performed between four organisms that are known to induce cancer development in humans: two viruses, Human Herpesvirus 4, and Human T-cell leukaemia virus, one bacterium, Helicobacter Pylori, and one trematode, Schistosoma mansoni. The annotated proteomes from these organisms were analysed using the SAFE software to identify protein fusion events, which may provide insight into protein function similarities and possible merging events during the course of evolution. Based on the results, five fused proteins with very similar functions were detected, whereas proteins with different functions that might act in the same molecular complex or biochemical pathway were not found. Thus, this study analysed the above four well-known cancer-related organisms with de novo bioinformatics programs and provided useful information on protein fusion events, hopefully leading to deeper understanding of carcinogenenesis.

Landscape of driver gene events, biomarkers, and druggable targets identified by whole-genome sequencing of glioblastomas

BACKGROUND

The survival of glioblastoma patients is poor. Median survival after diagnosis is 15 months, despite treatment involving surgical resection, radiotherapy, and/or temozolomide chemotherapy. Identification of novel targets and stratification strategies of glioblastoma patients to improve patient survival is urgently needed. Whole-genome sequencing (WGS) is the most comprehensive means to identify such DNA-level targets. We report a unique set of WGS samples along with comprehensive analyses of the glioblastoma genome and potential clinical impact of WGS.

METHODS

Our cohort consisted of 42 glioblastoma tumor tissue and matched whole-blood samples, which were whole-genome sequenced as part of the CPCT-02 study. Somatic single-nucleotide variants, small insertions/deletions, multi-nucleotide variants, copy-number alterations (CNAs), and structural variants were analyzed. These aberrations were harnessed to investigate driver genes, enrichments in CNAs, mutational signatures, fusion genes, and potential targeted therapies.

RESULTS

Tumor mutational burden (TMB) was similar to other WGS efforts (1-342 mutations per megabase pair). Mutational analysis in low TMB samples showed that the age-related CpG demethylation signature was dominant, while hyper- and ultramutated tumors had additional defective DNA mismatch repair signatures and showed microsatellite instability in their genomes. We detected chromothripsis in 24% of our cohort, recurrently on chromosomes 1 and 12. Recurrent noncoding regions only resulted in TERT promoter variants. Finally, we found biomarkers and potentially druggable changes in all but one of our tumor samples.

CONCLUSIONS

With high-quality WGS data and comprehensive methods, we identified the landscape of driver gene events and druggable targets in glioblastoma patients.

Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia

BACKGROUND

Considering the clinical and genetic characteristics, acute lymphoblastic leukemia (ALL) is a rather heterogeneous hematological neoplasm for which current standard diagnostics require various analyses encompassing morphology, immunophenotyping, cytogenetics, and molecular analysis of gene fusions and mutations. Hence, it would be desirable to rely on a technique and an analytical workflow that allows the simultaneous analysis and identification of all the genetic alterations in a single approach. Moreover, based on the results with standard methods, a significant amount of patients have no established abnormalities and hence, cannot further be stratified.

METHODS

We performed WTS and WGS in 279 acute lymphoblastic leukemia (ALL) patients (B-cell: n = 211; T-cell: n = 68) to assess the accuracy of WTS, to detect relevant genetic markers, and to classify ALL patients.

RESULTS

DNA and RNA-based genotyping was used to ensure correct WTS-WGS pairing. Gene expression analysis reliably assigned samples to the B Cell Precursor (BCP)-ALL or the T-ALL group. Subclassification of BCP-ALL samples was done progressively, assessing first the presence of chromosomal rearrangements by the means of fusion detection. Compared to the standard methods, 97% of the recurrent risk-stratifying fusions could be identified by WTS, assigning 76 samples to their respective entities. Additionally, read-through fusions (indicative of CDKN2A and RB1 gene deletions) were recurrently detected in the cohort along with 57 putative novel fusions, with yet untouched diagnostic potentials. Next, copy number variations were inferred from WTS data to identify relevant ploidy groups, classifying an additional of 31 samples. Lastly, gene expression profiling detected a BCR-ABL1-like signature in 27% of the remaining samples.

CONCLUSION

As a single assay, WTS allowed a precise genetic classification for the majority of BCP-ALL patients, and is superior to conventional methods in the cases which lack entity defining genetic abnormalities.

Fusion gene map of acute leukemia revealed by transcriptome sequencing of a consecutive cohort of 1000 cases in a single center

Fusion genes (FGs) are important genetic abnormalities in acute leukemias, but their variety and occurrence in acute leukemias remain to be systematically described. Whole transcriptome sequencing (WTS) provides a powerful tool for analyzing FGs. Here we report the FG map revealed by WTS in a consecutive cohort of 1000 acute leukemia cases in a single center, including 539 acute myeloid leukemia (AML), 437 acute lymphoblastic leukemia (ALL), and 24 mixed-phenotype acute leukemia (MPAL) patients. Bioinformatic analysis identified 792 high-confidence in-frame fusion events (296 distinct fusions) which were classified into four tiers. Tier A (pathogenic), B (likely pathogenic), and C (uncertain significance) FGs were identified in 61.8% cases of the total cohort (59.7% in AML, 64.5% in ALL, and 63.6% in MPAL). FGs involving protein kinase, transcription factor, and epigenetic genes were detected in 10.7%, 48.5%, and 15.1% cases, respectively. A considerable amount of novel FGs (82 in AML, 88 in B-ALL, 13 in T-ALL, and 9 in MPAL) was identified. This comprehensively described real map of FGs in acute leukemia revealed multiple FGs with clinical relevance that have not been previously recognized. WTS is a valuable tool and should be widely used in the routine diagnostic workup of acute leukemia.

Whole transcriptome sequencing detects a large number of novel fusion transcripts in patients with AML and MDS

Fusion transcripts are frequent genetic abnormalities in myeloid malignancies and are often the basis for risk stratification, minimal residual disease (MRD) monitoring, and targeted therapy. We comprehensively analyzed the fusion transcript landscape in 572 acute myeloid leukemia (AML) and 630 myelodysplastic syndrome (MDS) patients by whole transcriptome sequencing (WTS). Totally, 274 fusion events (131 unique fusions) were identified in 210/572 AML patients (37%). In 16/630 MDS patients, 16 fusion events (15 unique fusions) were detected (3%). In AML, 141 cases comprised entity-defining rearrangements (51% of all detected fusions) and 21 (8%) additional well-known fusions, all detected by WTS (control group). In MDS, only 1 fusion was described previously (NRIP1-MECOM, n = 2). Interestingly, a high number of so-far unreported fusions were found (41% [112/274] in AML, 88% [14/16] in MDS), all validated by cytogenetic and/or whole genome sequencing data. With 1 exception (CTDSP1-CFLAR, n = 2), all novel fusions were observed in 1 patient each. In AML, cases with novel fusions showed concomitantly a high frequency of TP53 mutations (67%) and of a complex karyotype (71%), which was also observed in MDS, but less pronounced (TP53, 26%; complex karyotype, 21%). A functional annotation of genes involved in novel fusions revealed many functional relevant genes (eg, transcription factors; n = 28 in AML, n = 2 in MDS) or enzymes (n = 42 in AML, n = 9 in MDS). Taken together, new genomic alterations leading to fusion transcripts were much more common in AML than in MDS. Any novel fusions might be of use for developing markers (eg, for MRD monitoring), particularly in cases without an entity-defining abnormality.

Algorithm-Based Meta-Analysis Reveals the Mechanistic Interaction of the Tumor Suppressor LIMD1 With Non-Small-Cell Lung Carcinoma

Non-small-cell lung carcinoma (NSCLC) is the major type of lung cancer, which is among the leading causes of cancer-related deaths worldwide. LIMD1 was previously identified as a tumor suppressor in lung cancer, but their detailed interaction in this setting remains unclear. In this study, we have carried out multiple genome-wide bioinformatic analyses for a comprehensive understanding of LIMD1 in NSCLC, using various online algorithm platforms that have been built for mega databases derived from both clinical and cell line samples. Our results indicate that LIMD1 expression level is significantly downregulated at both mRNA and protein levels in both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), with a considerable contribution from its promoter methylation rather than its gene mutations. The Limd1 gene undergoes mutation only at a low rate in NSCLC (0.712%). We have further identified LIMD1-associated molecular signatures in NSCLC, including its natural antisense long non-coding RNA LIMD1-AS1 and a pool of membrane trafficking regulators. We have also identified a subgroup of tumor-infiltrating lymphocytes, especially neutrophils, whose tumor infiltration levels significantly correlate with LIMD1 level in both LUAD and LUSC. However, a significant correlation of LIMD1 with a subset of immune regulatory molecules, such as IL6R and TAP1, was only found in LUAD. Regarding the clinical outcomes, LIMD1 expression level only significantly correlates with the survival of LUAD (p<0.01) but not with that of LUSC (p>0.1) patients. These findings indicate that LIMD1 plays a survival role in LUAD patients at least by acting as an immune regulatory protein. To further understand the mechanisms underlying the tumor-suppressing function of LIMD1 in NSCLC, we show that LIMD1 downregulation remarkably correlates with the deregulation of multiple pathways that play decisive roles in the oncogenesis of NSCLC, especially those mediated by EGFR, KRAS, PIK3CA, Keap1, and p63, in both LUAD and LUSC, and those mediated by p53 and CDKN2A only in LUAD. This study has disclosed that LIMD1 can serve as a survival prognostic marker for LUAD patients and provides mechanistic insights into the interaction of LIMD1 with NSCLC, which provide valuable information for clinical applications.

CRTC1/MAML2 directs a PGC-1α-IGF-1 circuit that confers vulnerability to PPARγ inhibition

Mucoepidermoid carcinoma (MEC) is a life-threatening salivary gland cancer that is driven primarily by a transcriptional coactivator fusion composed of cyclic AMP-regulated transcriptional coactivator 1 (CRTC1) and mastermind-like 2 (MAML2). The mechanisms by which the chimeric CRTC1/MAML2 (C1/M2) oncoprotein rewires gene expression programs that promote tumorigenesis remain poorly understood. Here, we show that C1/M2 induces transcriptional activation of the non-canonical peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PGC-1α) splice variant PGC-1α4, which regulates peroxisome proliferator-activated receptor gamma (PPARγ)-mediated insulin-like growth factor 1 (IGF-1) expression. This mitogenic transcriptional circuitry is consistent across cell lines and primary tumors. C1/M2-positive tumors exhibit IGF-1 pathway activation, and small-molecule drug screens reveal that tumor cells harboring the fusion gene are selectively sensitive to IGF-1 receptor (IGF-1R) inhibition. Furthermore, this dependence on autocrine regulation of IGF-1 transcription renders MEC cells susceptible to PPARγ inhibition with inverse agonists. These results yield insights into the aberrant coregulatory functions of C1/M2 and identify a specific vulnerability that can be exploited for precision therapy.

The landscape of long noncoding RNA-involved and tumor-specific fusions across various cancers

The majority of the human genome encodes long noncoding RNA (lncRNA) genes, critical regulators of various cellular processes, which largely outnumber protein-coding genes. However, lncRNA-involved fusions have not been surveyed and characterized yet. Here, we present a systematic study of the lncRNA fusion landscape across cancer types and identify >30 000 high-confidence tumor-specific lncRNA fusions (using 8284 tumor and 6946 normal samples). Fusions positively correlated with DNA damage and cancer stemness and were specifically low in microsatellite instable (MSI)-High or virus-infected tumors. Moreover, fusions distribute differently among cancer molecular subtypes, but with shared enrichment in tumors that are microsatellite stable (MSS), with high somatic copy number alterations (SCNA), and with poor survival. Importantly, we find a potentially new mechanism, mediated by enhancer RNAs (eRNA), which generates secondary fusions that form densely connected fusion networks with many fusion hubs targeted by FDA-approved drugs. Finally, we experimentally validate functions of two tumor-promoting chimeric proteins derived from mRNA-lncRNA fusions, KDM4B-G039927 and EPS15L1-lncOR7C2-1. The EPS15L1 fusion protein may regulate (Gasdermin E) GSDME, critical in pyroptosis and anti-tumor immunity. Our study completes the fusion landscape in cancers, sheds light on fusion mechanisms, and enriches lncRNA functions in tumorigenesis and cancer progression.

Identification of a Novel CSNK2A1-PDGFRB Fusion Gene in a Patient with Myeloid Neoplasm with Eosinophilia

Platelet-derived growth factor receptor beta (PDGFRB) rearrangements play an important role in the pathogenesis of eosinophilia-associated myeloid/lymphoid neoplasms. Up to now, more than 70 PDGFRB fusions have been identified. Here, a novel PDGFRB fusion gene CSNK2A1-PDGFRB has been identified in myeloproliferative neoplasm (MPN) with eosinophilia by RNA-sequencing, which has been verified by reverse transcription polymerase chain reaction and Sanger sequencing. The new PDGFRB fusion partner gene CSNK2A1 encoded one of the two catalytic subunit of casein kinase II (CK2). To our knowledge, this is the first report on the involvement of CSNK2A1 in fusion genes, especially fusion with another kinase PDGFRB in MPN. In addition, the CSNK2A1-PDGFRB fusion retained the entire kinase domain of PDGFRB and response to imatinib at low concentration. The patient with CSNK2A1-PDGFRB was sensitive to imatinib treatment and acquired sustained complete remission.

Emerging oncogenic fusions other than ALK, ROS1, RET, and NTRK in NSCLC and the role of fusions as resistance mechanisms to targeted therapy

Recent evidence has shown that gene fusions caused by chromosomal rearrangements are frequent events in the initiation and during progression of solid tumors, including non-small cell lung cancers (NSCLCs). Since the discoveries of ALK and ROS1 fusions in 2007 and the subsequent successes of pharmacological targeting for these fusions, numerous efforts have identified additional oncogenic driver fusions in NSCLCs, especially in lung adenocarcinomas. In this review, we will summarize recent advances in this field focusing on novel oncogenic fusions other than ALK, ROS1, NTRK, and RET fusions, which are summarized in other articles in this thematic issue. These novel gene fusions include neuregulin-1 (NRG1) fusions, MET fusions, fusion genes involving fibroblast growth factor receptor (FGFR) family members, EGFR fusions, and other rare fusions. In addition, evidence has suggested that acquisition of gene fusions by cancer cells can be a molecular mechanism of acquired resistance to targeted therapies. Most of the current data are from analyses of resistance mechanisms to EGFR tyrosine kinase inhibitors in lung cancers with oncogenic EGFR mutations. However, a few recent studies suggest that gene fusions can also be a resistance mechanism to ALK-tyrosine kinase inhibitors in lung cancers with oncogenic ALK fusions. Detection, validation, and pharmacological inhibition of these fusion genes are becoming more important in the treatment of NSCLC patients.

Mining potentially actionable kinase gene fusions in cancer cell lines with the KuNG FU database

Inhibition of kinase gene fusions (KGFs) has proven successful in cancer treatment and continues to represent an attractive research area, due to kinase druggability and clinical validation. Indeed, literature and public databases report a remarkable number of KGFs as potential drug targets, often identified by in vitro characterization of tumor cell line models and confirmed also in clinical samples. However, KGF molecular and experimental information can sometimes be sparse and partially overlapping, suggesting the need for a specific annotation database of KGFs, conveniently condensing all the molecular details that can support targeted drug development pipelines and diagnostic approaches. Here, we describe KuNG FU (KiNase Gene FUsion), a manually curated database collecting detailed annotations on KGFs that were identified and experimentally validated in human cancer cell lines from multiple sources, exclusively focusing on in-frame KGF events retaining an intact kinase domain, representing potentially active driver kinase targets. To our knowledge, KuNG FU represents to date the largest freely accessible homogeneous and curated database of kinase gene fusions in cell line models.

Bioinformatics services for analyzing massive genomic datasets

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.

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

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