Fusion transcripts and their genomic breakpoints in polyadenylated and ribosomal RNA–minus RNA sequencing data

Background Fusion genes are typically identified by RNA sequencing (RNA-seq) without elucidating the causal genomic breakpoints. However, non–poly(A)-enriched RNA-seq contains large proportions of intronic reads that also span genomic breakpoints. Results We have developed an algorithm, Dr. Disco, that searches for fusion transcripts by taking an entire reference genome into account as search space. This includes exons but also introns, intergenic regions, and sequences that do not meet splice junction motifs. Using 1,275 RNA-seq samples, we investigated to what extent genomic breakpoints can be extracted from RNA-seq data and their implications regarding poly(A)-enriched and ribosomal RNA–minus RNA-seq data. Comparison with whole-genome sequencing data revealed that most genomic breakpoints are not, or minimally, transcribed while, in contrast, the genomic breakpoints of all 32 TMPRSS2-ERG–positive tumours were present at RNA level. We also revealed tumours in which the ERG breakpoint was located before ERG, which co-existed with additional deletions and messenger RNA that incorporated intergenic cryptic exons. In breast cancer we identified rearrangement hot spots near CCND1 and in glioma near CDK4 and MDM2 and could directly associate this with increased expression. Furthermore, in all datasets we find fusions to intergenic regions, often spanning multiple cryptic exons that potentially encode neo-antigens. Thus, fusion transcripts other than classical gene-to-gene fusions are prominently present and can be identified using RNA-seq. Conclusion By using the full potential of non–poly(A)-enriched RNA-seq data, sophisticated analysis can reliably identify expressed genomic breakpoints and their transcriptional effects.

The Prognostic and Predictive Value of ESR1 Fusion Gene Transcripts in Primary Breast Cancer

Background: In breast cancer (BC), recurrent fusion genes of estrogen receptor alpha (ESR1) and AKAP12, ARMT1 and CCDC170 have been reported. In these gene fusions the ligand binding domain of ESR1 has been replaced by the transactivation domain of the fusion partner constitutively activating the receptor. As a result, these gene fusions can drive tumor growth hormone independently as been shown in preclinical models, but the clinical value of these fusions have not been reported. Here, we studied the prognostic and predictive value of different frequently reported ESR1 fusion transcripts in primary BC. Methods: We evaluated 732 patients with primary BC (131 ESR1-negative and 601 ESR1-positive cases), including two ER-positive BC patient cohorts: one cohort of 322 patients with advanced disease who received first-line endocrine therapy (ET) (predictive cohort), and a second cohort of 279 patients with lymph node negative disease (LNN) who received no adjuvant systemic treatment (prognostic cohort). Fusion gene transcript levels were measured by reverse transcriptase quantitative PCR. The presence of the different fusion transcripts was associated, in uni- and multivariable Cox regression analysis taking along current clinic-pathological characteristics, to progression free survival (PFS) during first-line endocrine therapy in the predictive cohort, and disease- free survival (DFS) and overall survival (OS) in the prognostic cohort.Results: The ESR1-CCDC170 fusion transcript was present in 27.6% of the ESR1-positive BC subjects and in 2.3% of the ESR1-negative cases. In the predictive cohort, none of the fusion transcripts were associated with response to first-line ET. In the prognostic cohort, the median DFS and OS were respectively 37 and 93 months for patients with an ESR1-CCDC170 exon 8 gene fusion transcript and respectively 91 and 212 months for patients without this fusion transcript. In a multivariable analysis, this ESR1-CCDC170 fusion transcript was an independent prognostic factor for DFS (HR) (95% confidence interval (CI): 1.8 (1.2–2.8), P=0.005) and OS (HR (95% CI: 1.7 (1.1–2.7), P=0.023). Conclusions: Our study shows that in primary BC only ESR1-CCDC170 exon 8 gene fusion transcript carries prognostic value. None of the ESR1 fusion transcripts, which are considered to have constitutive ER activity, was predictive for outcome in BC with advanced disease treated with endocrine treatment.

Higher Incidence of Co-Expression of BCR-ABL Fusion Transcripts in an Eastern Indian Population

Background Chronic myeloid leukaemia (CML) is a hematopoietic stem cell disorder, caused by a balanced reciprocal translocation (t(9;22) (q34;q11))that lead to the formation of BCR (Break point Cluster Region)-ABL (Abelson) fusion transcripts known as Philadelphia (Ph) chromosome. Prevalence of BCR-ABL fusion transcripts in Indian CML population is poorly understood and few studies have been reported from India. The aim of present study was to determine the frequencies as well as prognostic effects of the three fusion transcripts i.e. b2a2, b3a2 and e1a2 in an Indian population. Methods RNA was isolated from total 123 sample 27 bone marrow (BM) sample and 96 Peripheral blood (PB) sample of CML patient followed by cDNA synthesis. Real-time quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was performed using TaqMan→ assay (ABI, CA, USA) to monitor BCR-ABL transcript. Results Ph' chromosome was observed in 103 patients whereas it was not detected in 20 cases. qRT-PCR revealed that the b3a2 fusion transcripts was the most common transcript in CML patients (63.41%) while b2a2 fusion transcript was present in 16.26% cases. Co-expression of b3a2+b2a2 fusion transcript was observed in 0.81% cases whereas co-expression of b3a2+e1a2 fusion transcript was found in 1.63% cases. There was no co-relation observed between b3a2 fusion transcript and platelet count. The fusion transcript b2a2 was observed in relatively younger patients compared to b3a2 fusion transcript. Although this correlation was not statistically significant. Conclusion The co-expression of BCR-ABL fusion transcripts was higher (63.41% aggregate of b3a2) in the present population in contrast to other populations reported. This finding was consistent with the frequency data reported from Sudan.

Transcript-targeted analysis reveals isoform alterations and double-hop fusions in breast cancer

Although transcriptome alteration is an essential driver of carcinogenesis, the effects of chromosomal structural alterations on the cancer transcriptome are not yet fully understood. Short-read transcript sequencing has prevented researchers from directly exploring full-length transcripts, forcing them to focus on individual splice sites. Here, we develop a pipeline for Multi-Sample long-read Transcriptome Assembly (MuSTA), which enables construction of a transcriptome from long-read sequence data. Using the constructed transcriptome as a reference, we analyze RNA extracted from 22 clinical breast cancer specimens. We identify a comprehensive set of subtype-specific and differentially used isoforms, which extended our knowledge of isoform regulation to unannotated isoforms including a short form TNS3. We also find that the exon–intron structure of fusion transcripts depends on their genomic context, and we identify double-hop fusion transcripts that are transcribed from complex structural rearrangements. For example, a double-hop fusion results in aberrant expression of an endogenous retroviral gene, ERVFRD-1, which is normally expressed exclusively in placenta and is thought to protect fetus from maternal rejection; expression is elevated in several TCGA samples with ERVFRD-1 fusions. Our analyses provide direct evidence that full-length transcript sequencing of clinical samples can add to our understanding of cancer biology and genomics in general.

Benchmarking of Whole Genome Sequencing (WGS) and Whole Transcriptome Sequencing (WTS) As Diagnostic Tools for the Genetic Characterization of Acute Myeloid Leukemia (AML) and Acute Lymphoblastic Leukemia (ALL) in Adults

Background: In AML and ALL the application of WHO classification and ELN guidelines requires a combination of cytogenetics and targeted sequencing for specific mutations to determine the diagnostic and prognostic subgroup. WGS and WTS have emerged as comprehensive techniques that allow the simultaneous analysis and identification of all genetic alterations in a single approach with possible turnaround times of 1 week. Aim: Evaluate the accuracy of WGS and WTS in providing all relevant genetic information in a clinical setting. Patients and Methods: The cohort comprised 738 AML, 293 BCP-ALL and 124 T-ALL. The diagnosis was established following WHO guidelines. WGS (100x, 2x151bp) and WTS (50 Mio reads, 2x101bp) were performed on a NovaSeq instrument. Variants were called with Strelka2, Manta and GATK using a tumor w/o normal pipeline, fusions with Arriba, STAR-Fusion and Manta. Results: The combination of WGS and WTS detected all chromosomal and molecular abnormalities in the AML and ALL cohorts relevant for disease stratification and prognostication as identified by chromosome banding analysis (CBA) and targeted panel sequencing (TPS). A very high concordance between CBA and WGS was revealed for the detection of balanced structural variants (SV) with the added benefit of WGS to also detect cytogenetically cryptic rearrangements (i.e.: ETV6-MN1, NUP98-KDM5A), which all were confirmed either by FISH or RT-PCR. Fusion calling by WTS identified 96% of the WHO subtype defining rearrangements and detected 20 additional fusion transcripts relevant for disease stratification (e.g. EP300-ZNF384, TCF3-HLF) including 9 fusion transcripts that led to prognostic reassignment or could serve as a potential treatment target. Breakpoints of unbalanced SV can occur in repetitive sequences of the genome, hampering the detection by WGS. However, adding copy number alteration (CNA) calls to the analyses allows also reliable identification of unbalanced SV. WGS outperformed CBA in cases with insufficient in vitro proliferation due to suboptimal pre-analytics (i.e. longer transport time) and identified 36 chromosomal aberrations in 12 cases with CBA not evaluable. WGS's independence of in vitro cell proliferation was most impactful in ALL: 40 T-ALL cases showed a normal karyotype according to CBA. WGS detected SVs in 16 (40%) and CNAs in 20 (50%) of these cases, confirming the normal karyotype for only 9 samples. In the BCP-ALL cohort, CNV analysis identified 29 low hypodiploid and 16 high hyperdiploid karyotypes, 6 of which were missed by CBA. Due to the higher resolution and unrestricted, genome-wide assessment, WGS detected relevant gene deletions (RB1, ERG, PAX5, CDKN2A, IKZF1, ETV6, BTG1) in 59% of ALL cases, providing additional diagnostic and prognostic information. In the AML cohort CBA and WGS detected 795 CNA concordantly. In addition WGS called 54 CNA with size 1-5 MB (below the detection limit of CBA), i.e. 3 BCOR deletions in inv(3)(q21q26) cases and 67 CNA with size > 5 MB, which were missed by CBA. 35 CNA were missed by WGS due to small clone sizes (median 6% as determined by FISH). WGS detected copy neutral loss of heterozygosity (CN-LOH) in AML most frequently on 21q (n=17), 4q (n=15), 13q (n=15), 11q (n=13) and in T-ALL on 9p (n=19), mostly encompassing CDKN2A/B deletions. Expression profiling provided additional diagnostic information for 57 ALL cases (41 BCR-ABL1-like, 16 DUX4 rearranged) that can only insufficiently be obtained by WGS or CBA. WGS reliably detected all gene mutations with a VAF > 15% (n = 647) identified by TPS encompassing especially all mutations in genes relevant for WHO diagnosis and prognostication. 26/171 mutations with a VAF < 15% were missed by WGS. Evaluation of WGS data for 121 genes recurrently mutated in hematologic neoplasms revealed an additional 2 mutations per sample on average (range: 0-9) which might qualify as targets for therapy. Conclusions: WGS and WTS provide all necessary genetic information to accurately determine the diagnostic and prognostic subgroup according to WHO and ELN guidelines in AML and ALL. Compared to today's gold standards, these novel methods provide a comprehensive genome wide characterization with higher resolution that directly identifies genes of impact, offering the basis for targeted treatment selection and monitoring of residual disease. Both can be implemented with automated analysis pipelines, consequently reducing time and error rates. Figure 1 Figure 1. Disclosures Haferlach: MLL Munich Leukemia Laboratory: Other: Part ownership. Kern: MLL Munich Leukemia Laboratory: Other: Part ownership. Haferlach: MLL Munich Leukemia Laboratory: Other: Part ownership.

Location of the t(4;14) Translocation Breakpoint Identifies a Subset of Newly-Diagnosed Multiple Myeloma Patients with Poor Prognosis

Introduction: The recombination of chromosomes 4 and 14 (t(4;14)) is a primary, predominantly clonal event in newly diagnosed multiple myeloma (ndMM) that is present in ~15% of patients. The translocation results in enhancer regions from the immunoglobulin heavy chain locus upregulating the expression of NSD2 and FGFR3 genes implicated in the disease biology of this subset of MM patients (Chesi et al. Blood. 1998, Keats et al, Leuk Lymph. 2006). The presence of t(4;14) translocation is a considered a biomarker of aggressive disease and is part of the Revised International Staging System (R-ISS) for clinical risk stratification. However, historically only ~40% of t(4;14) patients are high-risk based on the GEP70 gene expression signature. (Weinhold et al. Leukemia. 2016) Our previous analysis of a large cohort of ndMM patients described the genomic features of t(4;14) vs ndMM overall population demonstrating that only ~25% of t(4;14) patients died within 24 months of diagnosis and described biomarkers in this high-risk subset. This analysis identified both known and novel aberrations in ndMM, including some that were associated with high-risk t(4;14) (Ortiz et al Blood. 2019; 134 (Suppl_1):366). In this updated analysis, we provide a more robust analysis of the t(4;14) dataset and demonstrate the prognostic value of the NSD2 breakpoint location. Methods: We generated a large genomic dataset from t(4;14) ndMM patients with whole genome sequencing (WGS) and RNA-seq from a TOUL dataset (t(4;14) N=114) patients treated in routine practice), the IFM2009 trial (N=19), and the Myeloma Genome Project (MGP) (N=34) for discovery and validation. Gene expression, copy number aberration, single nucleotide variant and translocations were derived from RNAseq and WGS profiling of biopsies from patients aged less than 75 years who received transplant, and integrated with clinical information (including age, OS). Cytogenetic assessments from WGS were made by MANTA and used to identify translocation DNA breakpoint location. Results: In all datasets, three DNA breakpoint locations were identified, and based on their position with respect to the NSD2 gene named "no-disruption" (upstream of NSD2 gene), "early-disruption" (in the 5' UTR of NSD2 gene) and "late-disruption" (in the coding region of NSD2 gene). Using paired RNA-seq data, we identified IGH-NSD2 RNA fusion transcripts relative to the breakpoints that corresponded with previously described NSD2 isoforms. "No-disruption" and "early-disruption" breakpoints predominantly produced a fusion transcript (MB4-1) that retained the full coding sequence of the gene, while the "late-disruption" produced truncated fusion transcripts (MB4-2/3). We conducted survival analysis in our datasets based on both DNA breakpoint location and RNA fusion transcripts. This analysis demonstrated a significant difference in outcome between the patient samples with "no-disruption" and the "late-disruption" breakpoints that associated with good and poor OS, respectively (OS pval < 3e-4) in the discovery TOUL dataset. Patients with "late-disruption" had a median OS of 28.64 mo vs 59.18 mo for "early disruption" and 82.26 mo for those with "no disruption" (Figure). This association was replicated in an independent dataset (MGP N=33, replication pval<4.3e-5). The mOS difference of patients based on which fusion transcript they express is less than the difference based on breakpoint (mOS MB4-1 = 47.38 mo. vs. MB4-2/3 = 60.89 mo.). These analyses demonstrate that the breakpoint location has a stronger association with outcome than fusion transcript expression. Conclusion: From a large genomic dataset, we were able to discover and validate a clear association between the translocation breakpoints and survival outcome in t(4:14) ndMM patients. While prospective validation is needed before clinical application of our finding, molecular identification of high-risk t(4;14) patients using DNA breakpoint location may enable proper risk classification for this patient group at diagnosis, and would provide improved opportunities for risk-adjusted therapy and identification of a therapeutic target for this high-risk subpopulation. Ongoing work on mutations, copy number, and differential gene expression analyses between translocation breakpoint sub-groups and will be presented. Figure 1 Figure 1. Disclosures Stong: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Ortiz: Bristol Myers Squibb: Current Employment. Towfic: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Pierceall: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Flynt: Bristol Myers Squibb: Current Employment. Thakurta: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company, Patents & Royalties.

Full-length transcriptome analysis and identification of transcript structures in Eimeria necatrix from different developmental stages by single-molecule real-time sequencing

Background Eimeria necatrix is one of the most pathogenic parasites, causing high mortality in chickens. Although its genome sequence has been published, the sequences and complete structures of its mRNA transcripts remain unclear, limiting exploration of novel biomarkers, drug targets and genetic functions in E. necatrix. Methods Second-generation merozoites (MZ-2) of E. necatrix were collected using Percoll density gradients, and high-quality RNA was extracted from them. Single-molecule real-time (SMRT) sequencing and Illumina sequencing were combined to generate the transcripts of MZ-2. Combined with the SMRT sequencing data of sporozoites (SZ) collected in our previous study, the transcriptome and transcript structures of E. necatrix were studied. Results SMRT sequencing yielded 21,923 consensus isoforms in MZ-2. A total of 17,151 novel isoforms of known genes and 3918 isoforms of novel genes were successfully identified. We also identified 2752 (SZ) and 3255 (MZ-2) alternative splicing (AS) events, 1705 (SZ) and 1874 (MZ-2) genes with alternative polyadenylation (APA) sites, 4019 (SZ) and 2588 (MZ-2) fusion transcripts, 159 (SZ) and 84 (MZ-2) putative transcription factors (TFs) and 3581 (SZ) and 2039 (MZ-2) long non-coding RNAs (lncRNAs). To validate fusion transcripts, reverse transcription-PCR was performed on 16 candidates, with an accuracy reaching up to 87.5%. Sanger sequencing of the PCR products further confirmed the authenticity of chimeric transcripts. Comparative analysis of transcript structures revealed a total of 3710 consensus isoforms, 815 AS events, 1139 genes with APA sites, 20 putative TFs and 352 lncRNAs in both SZ and MZ-2. Conclusions We obtained many long-read isoforms in E. necatrix SZ and MZ-2, from which a series of lncRNAs, AS events, APA events and fusion transcripts were identified. Information on TFs will improve understanding of transcriptional regulation, and fusion event data will greatly improve draft versions of gene models in E. necatrix. This information offers insights into the mechanisms governing the development of E. necatrix and will aid in the development of novel strategies for coccidiosis control. Graphical Abstract