RNA Sequencing Based Whole Transcriptome Analysis Detected Precisely All Fusion Transcripts in Leukemias

Abstract Introduction: Fusion transcript is a chimeric RNA encoded by a fusion gene or by two different genes by subsequent trans-splicing. Detection of fusion transcripts is an integral part of routine diagnostics of hematological malignancies. However, most of previous analytical methods couldn't detect all fusion transcripts in leukemia. In this study, we developed accurate fusion transcript detection methood using whole transcriptome sequencing, fusion gene detection software and expression analysis. Methods: RNA sequencing (RNA-seq) for whole transcriptome was performed in 11 patients with hematological malignancies (4 AML, 2 APL, 2 ALL, and 3 CML) having fusion transcripts detected by multiplex RT-PCR (HemaVision, DNA Diagnostic, Risskov, Denmark). Library were prepared with 1 ug of total RNA for each sample by TruSeq mRNA Sample Prep kit (Illumina, San Diego, USA). The libraries were quantified using qPCR according to the qPCR Quantification Protocol Guide (KAPA Library Quantificatoin kits for Illumina Sequecing platforms) and qualified using the TapeStation D1000 ScreenTape (Agilent Technologies, Santa Clara, USA). Indexed libraries were then sequenced using the HiSeq2500 platform (Illumina). The data obtained from the sequencing was analyzed using STAR-Fusion (v1.2.0). Novel fusion transcripts were confirmed by conventional sequencing. Results: Using STAR-Fusion, average number of fusion candidates per sample was 949.8 (range, 286-1752). To exclude false positive results and obtain true positive results, we developed the following filtering algorithm. First filtering criterion is to have more than 5 junction reads, the second is to detect more than one number of spanning reads, and the third criterion is to be in-frame fusion, which type of fusion can actually synthesize intact protein. Fusion candidates remaining after applying the above three filtering criteria were 1-3 per sample. All known fusion transcripts (PML--RARA, RUNX--RUNX1T1, CBFB--MYH11, KMT2A--MLLT3, BCR--ABL1, DEK--NUP214, ETV6--RUNX1) by multiplex RT-PCR were also detected in RNA-seq. In addition, 10 novel fusion transcripts (IGKV4-1--IGKC, IGLV1-47--IGLC2, HBA2--HBB, DEFA3--MBNL1, HBB--HBA2, MPO--HBA2, HBS1L--AHI1, HBB--HBA2, IGKV4-1--IGKC, SS18L1--ADRM1) were detected and among them, 6 fusions were confirmed by conventional sequencing. Conclusions: Whole transcriptome sequencing and optimized filtering algorithms successfully detected all known fusion transcripts and various novel fusions. Disclosures No relevant conflicts of interest to declare.

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

Blood Advances ◽

10.1182/bloodadvances.2020003007 ◽

2020 ◽

Vol 4 (21) ◽

pp. 5393-5401

Author(s):

Anna Stengel ◽

Rabia Shahswar ◽

Torsten Haferlach ◽

Wencke Walter ◽

Stephan Hutter ◽

...

Keyword(s):

Transcriptome Sequencing ◽

Residual Disease ◽

Fusion Transcript ◽

Whole Genome Sequencing Data ◽

Control Group ◽

Complex Karyotype ◽

Sequencing Data ◽

Fusion Transcripts ◽

Whole Transcriptome Sequencing ◽

Whole Transcriptome

Abstract 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.

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Whole Transcriptome Sequencing In Refractory T-Cell Acute Lymphoblastic Leukemia

Blood ◽

10.1182/blood.v122.21.350.350 ◽

2013 ◽

Vol 122 (21) ◽

pp. 350-350

Author(s):

Valentina Gianfelici ◽

Sabina Chiaretti ◽

Zeynep Kalender Atak ◽

Fulvia Brugnoletti ◽

Messina Monica ◽

...

Keyword(s):

T Cell ◽

Lymphoblastic Leukemia ◽

Rna Seq ◽

Fusion Transcripts ◽

Whole Transcriptome Sequencing ◽

Cell Acute Lymphoblastic Leukemia ◽

Conventional Cytogenetics ◽

Thymus Cells ◽

Whole Transcriptome

Abstract T-cell acute lymphoblastic leukemia (T-ALL) is a malignancy of the lymphoblasts committed to the T-cell lineage. Despite the therapeutic improvements witnessed over the years, ∼25% of children and ∼50% of adults still show a poor long-term outcome. While many recurrent oncogenic lesions have been identified through the characterization of chromosomal aberrations and candidate gene sequencing, several observations indicate that additional genetic alterations, not evident by conventional cytogenetics, might influence leukemogenesis and treatment outcome. Improvement of our knowledge in the identification and characterization of new oncogenic genome variations is expected to lead to a better prognostic classification and should also allow the design of tailored therapeutic strategies. To get further insights into the molecular pathogenesis of T-ALL and to identify novel markers for risk stratification and treatment improvement, we performed whole transcriptome sequencing (RNA-seq) on 18 refractory T-ALL cases sampled at diagnosis (median age 37.5 years, range 11-55). A pool of normal thymus cells was used as negative control. Next generation sequencing libraries were constructed from the mRNA fraction, followed by paired-end sequencing on a HiSeq2000 (Illumina). Sequence reads were aligned to the reference genome and were processed to identify gene expression levels, gene fusion transcripts and single nucleotide variations (SNVs). We first determined accurate gene expression levels from the RNA-seq data and used them to classify patients into T-ALL subtypes. Next, we applied the deFuse algorithm to detect fusion transcripts. Fusion transcripts detected also in normal thymus cells were filtered out, as well as fusions involving ribosomal genes. After applying these filters, we obtained 407 fusion transcripts (average: 22.6/sample, range: 0-84) predominantly involving genes localized on the same chromosome and mostly generated by deletion (306/407). Novel candidate fusion transcripts were confirmed by RT-PCR and Sanger sequencing. The SET-NUP214 fusion was identified in 2 cases, as well as 2 novel fusion transcripts involving the T-cell receptor (TCR) genes and not detected by conventional cytogenetics: the first fusion resulted in a chromosomal rearrangement between HOXA-AS4 and TRBC2 (also accompanied by overexpression of the HOXA genes) and the second between TRAC and SOX8 (associated with SOX8 overexpression). Interestingly, we also found out-of-frame fusion transcripts leading to the potential inactivation of tumor suppressor genes, such as PTEN-FAS and MAST3-C19orf10. Finally, we performed SNV calling on our dataset. After removing the most common polymorphisms, we obtained 1,483 protein-altering SNVs (missense, nonsense mutations and mutations affecting splicing), ranging between 30 and 131 per sample, with 85 genes that contain a protein-altering mutation in at least 3 of the 18 samples (i.e. 16% of cohort). Members or modulators of NOTCH and JAK/STAT pathways were the most recurrently mutated, each accounting for ∼38% of cases. In particular, 7/18 samples showed previously reported lesions in the NOTCH1 (n=5) and FBXW7 (n=1) genes but also in novel candidates as NOTCH2 (n=1), NOTCH3 (n=1) and SPEN (n=1). Interestingly, 1 patient showed 2 different mutations in the exon 26 of NOTCH1, while in 2 samples NOTCH1 mutation was associated with mutations in NOTCH2 or NOTCH3. Similarly, the JAK/STAT pathway was affected in 7/18 samples, including JAK1 (n=2), JAK3 (n=5), TYK2 (n=1) but also the novel candidates STAT5A (n=2) and STAT6 (n=1). Four of the 5 JAK3-positive patients showed also a mutation in another gene of the same pathway, such as JAK1 (n=1), STAT5A (n=2) and STAT6 (n=1). Thus, mutational screening of both the NOTCH and JAK/STAT pathway shows that mutations can occur simultaneously and suggests that more than one lesion is required for leukemic transformation. In conclusion, RNA-seq appears as a promising tool to dissect the heterogeneity of T-ALL and to identify targets that might be useful for tailored therapeutic interventions. Further investigations are ongoing to determine the recurrence and specificity of these lesions, and their potential in inducing a refractory phenotype. Finally, in vitro experiments will be carried out to investigate the transforming capability of specific lesions and the targettability of the recurrently impaired pathways. Disclosures: No relevant conflicts of interest to declare.

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The Diverse Landscape of Fusion Transcripts in 25 Different Hematological Entities

Blood ◽

10.1182/blood-2020-137518 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 16-17

Author(s):

Claudia Haferlach ◽

Wencke Walter ◽

Manja Meggendorfer ◽

Constance Baer ◽

Anna Stengel ◽

...

Keyword(s):

Drug Targets ◽

Hematological Malignancies ◽

Conflicts Of Interest ◽

Fusion Gene ◽

Fusion Transcript ◽

Whole Genome Sequencing Data ◽

Regulatory Sequences ◽

Sequencing Data ◽

Fusion Event ◽

Fusion Transcripts

Background: Genomic alterations are a hallmark of hematological malignancies and comprise small nucleotide variants, copy number alterations and structural variants (SV). SV lead to the co-localization of remote genomic material resulting in 2 different scenarios: 1. breakpoints are located within 2 genes leading to a chimeric fusion gene and a fusion transcript, 2. breakpoints are located outside of genes, frequently placing one nearby gene under the influence of the regulatory sequences of the partner, leading to a deregulated - usually increased - transcription. Aim: The frequency of fusion transcripts was determined across hematological entities in order to 1) identify recurrent partner genes across entities, 2) evaluate the specificity of fusion transcripts and genes involved in fusions for distinct entities. Cohort and Methods: Whole transcriptome sequencing (WTS) was performed in 3,549 patients in 25 different hematological entities (table). 101 bp paired-end reads were produced on a NovaSeq 6000 system (Illumina, San Diego, CA) with a yield between 35 and 125 million paired reads per sample. Potential fusions were called using 3 different callers (Arriba, STAR-Fusion, Manta), only fusions called by at least 2 callers, validated by whole genome sequencing (data available for all cases) and with at least one protein coding partner were kept for further analyses. Reciprocal fusion transcripts were counted as one fusion event. Results: In total 1,309 fusion transcripts were identified in 932 of 3,549 (26.3%) patients. 221 patients showed > 1 fusion (2 fusions: 150, 3: 36, >3: 35). 806 distinct fusion transcripts were divided into recurrent fusions (n=50) and unique fusions, i.e. found only in 1 case (n=756). Out of 932 patients with at least 1 fusion, 541 (58%) patients harbored a minimum of one recurrent fusion. The proportion of patients harboring any or a recurrent fusion varied substantially between different entities with high frequencies for both in CML (96.5%/96.5%), B-lineage ALL (53.1%/41.3%), AML (42.8%/31.2%), and T-lineage ALL (35.3%/12.6%). In several myeloid entities low fusion frequencies were observed (e.g. PMF, MDS/MPN-U, MDS, figure A). No fusion transcripts were detected in ET. Strikingly, fusions were detected in a substantial proportion of cases with lymphoid neoplasms but only very few occurred recurrently (e.g. T-PLL: 47.8%/4.3%, FL: 39.3%/4.9%, figure A). With regard to age, only patients with AML and T-ALL harboring recurrent fusions were significantly younger than corresponding cases without recurrent fusions (59 vs 71 yrs, p<0.0001; 35 vs 38 yrs, p=0.02). Only in AML patients with unique fusions were older (70 vs 66 yrs, p=0.02), while no age differences were observed between cases with and without unique fusions in other entities. 23/50 (46%) of the recurrent fusions were specific for one entity (12 in myeloid, 11 in lymphatic entities), while the other 54% (27/50) were observed in 2 to 7 different entities. Of these 27 recurrent fusions, only 16 fusions were shared between myeloid and lymphatic entities, while 10 were restricted to myeloid and one fusion to lymphatic entities (figure B). In total 1,270 different genes were involved in the 806 distinct fusions, indicating a broad spectrum of potential functional impact. 54 genes were involved only in recurrent fusions, 27 genes in both recurrent and unique fusions, while 1,189 genes were solely involved in unique fusions. Four genes involved in recurrent fusions and 32 genes involved in unique fusions are FDA approved drug targets (Human Protein Atlas). Only 16% (199/1270) of the genes were involved in more than one fusion: 3 genes (ETV6, KMT2A, RUNX1) in 14 fusions, 2 genes (ABL1, BCR) in 11 fusions, 16 genes in 4 to 10 fusions, 38 genes in 3 fusions, 140 in 2 fusions. Several genes frequently involved in fusions in hematological malignancies (e.g. ABL1, ETV6, KMT2A) and 78/1189 genes only involved in unique fusions were also reported to be partners in fusions in non-hematological malignancies. Conclusions: As known, in CML and acute several leukemias a high proportion of patients harbor fusions of which many occur recurrently, suggesting a substantial pathogenic impact and, thus, requiring detection in a diagnostic work-up. In BCR-ABL1 negative chronic myeloid malignancies few fusions were observed while lymphoma patients carry frequently non-recurrent fusions with so far unknown impact on pathogenesis and prognosis. Disclosures No relevant conflicts of interest to declare.

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Molecular Heterogeneity of the FIP1L1-PDGFRA Fusion Gene in Chronic Eosinophilic Leukemia (CEL) and Systemic Mastocytosis with Eosinophilia (SME): A Study of 43 Cases.

Blood ◽

10.1182/blood.v104.11.2428.2428 ◽

2004 ◽

Vol 104 (11) ◽

pp. 2428-2428 ◽

Cited By ~ 2

Author(s):

Christoph Walz ◽

Daniela Cilloni ◽

Simona Soverini ◽

Catherine Roche ◽

Emanuela Ottaviani ◽

...

Keyword(s):

Tyrosine Kinase ◽

Fusion Gene ◽

Systemic Mastocytosis ◽

Collaborative Study ◽

Fusion Transcript ◽

Pcr Analysis ◽

Molecular Heterogeneity ◽

Rt Pcr ◽

Fusion Transcripts ◽

Chronic Eosinophilic Leukemia

Abstract The FIP1L1-PDGFRA fusion gene results from a cytogenetically invisible interstitial chromosomal deletion on chromosome 4q12 and was recently identified as a recurrent molecular abnormality in patients with chronic eosinophilic leukemia (CEL) and systemic mastocytosis with eosinophilia (SME). The pathogenesis of FIP1L1-PDGFRA positive CEL/SME is similar to BCR-ABL positive chronic myeloid leukemia (CML) with constitutively increased tyrosine kinase activity of the fusion protein and excellent response to treatment with imatinib. The breakpoints within FIP1L1 are variable and a number of different exons are fused to a truncated PDGFRA exon 12. However, the numbers of sequenced fusion transcripts in single reports have been too small for a more detailed analysis of the anatomy and relative frequency of the different fusion transcripts. We therefore sought to collect data from FIP1L1-PDGFRA positive patients from several laboratories across Europe (France, Germany, Italy, UK) in a collaborative study within the workpackage "Minimal residual disease" of the European LeukemiaNet. A total number of 43 FIP1L1-PDGFRA positive cases were identified by RT-PCR. For yet unknown reasons a considerable number of cases were only found to be positive after nested RT-PCR despite adequate sample quality, high leukocyte counts and marked eosinophilia. Possible reasons might be a relatively low proportion of FIP1L1-PDGFRA positive cells, relatively low expression of the fusion transcript and/or relatively rapid fusion transcript degradation; although FIP1L1-PDGFRA was found to be expressed at a level comparable to the ABL control gene in RQ-PCR analysis of EOL-1 cell line. Sequence analysis revealed that all PDGFRA breakpoints fell exclusively within exon 12, thus retaining the entire kinase domain of PDGFRA in all cases. The truncated PDGFRA (p) exon 12 was fused to FIP1L1 (f) exons 9 to 13 (formerly described as 7a, 8, 8a, 9 and 10 - Cools et al., NEJM. 2003;348: 1201–1214): f9p12 (n=1; 2%), f10p12 (n = 10; 22%), f11p12 (n=15; 33%), f12p12 (n=7; 15%), f13p12 (n=10; 22%). An insertion of additional sequences of up to 107 bp was found in 24 patients (56%) leading to an open reading frame in all cases. These sequences were derived from introns of FIP1L1 in 14 cases, from FIP1L1 exon 13 in one case and from 4q33 in one case, the latter indicating a more complex rearrangement. Eight inserts of 2 – 6 bp could not be matched to known sequences because they were too short. An entirely identical fusion transcript resulting from an identical PDGFRA sequence fused to the same FIP1L1 exon without insert was found in 6 patients with a f12p12 fusion transcript and 4 patients with a f10p12 fusion transcript. We conclude that the combination of a great variability of breakpoints within FIP1L1 and PDGFRA plus the insertion of sequences which are variable in length and origin lead to unique FIP1L1-PDGFRA fusion sequences in the majority of patients. This carries important implications for strategies for molecular detection and development of RQ-PCR assays to determine response to imatinib or alternative tyrosine kinase inhibitors.

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Impact of RNA Extraction and Target Capture Methods on RNA Sequencing Using Formalin-Fixed, Paraffin Embedded Tissues

10.1101/656736 ◽

2019 ◽

Author(s):

Christopher A. Hilker ◽

Aditya V. Bhagwate ◽

Jin Sung Jang ◽

Jeffrey G Meyer ◽

Asha A. Nair ◽

...

Keyword(s):

Gene Expression ◽

Fusion Gene ◽

Rna Extraction ◽

Extraction Methods ◽

Rna Seq ◽

Gene Detection ◽

Formalin Fixed Paraffin ◽

Formalin Fixed Paraffin Embedded ◽

Whole Transcriptome ◽

Formalin Fixed

AbstractFormalin fixed paraffin embedded (FFPE) tissues are commonly used biospecimen for clinical diagnosis. However, RNA degradation is extensive when isolated from FFPE blocks making it challenging for whole transcriptome profiling (RNA-seq). Here, we examined RNA isolation methods, quality metrics, and the performance of RNA-seq using different approaches with RNA isolated from FFPE and fresh frozen (FF) tissues. We evaluated FFPE RNA extraction methods using six different tissues and five different methods. The reproducibility and quality of the prepared libraries from these RNAs were assessed by RNA-seq. We next examined the performance and reproducibility of RNA-seq for gene expression profiling with FFPE and FF samples using targeted (Kinome capture) and whole transcriptome capture based sequencing. Finally, we assessed Agilent SureSelect All-Exon V6+UTR capture and the Illumina TruSeq RNA Access protocols for their ability to detect known gene fusions in FFPE RNA samples. Although the overall yield of RNA varied among extraction methods, gene expression profiles generated by RNA-seq were highly correlated (>90%) when the input RNA was of sufficient quality (≥DV200 30%) and quantity (≥ 100 ng). Using gene capture, we observed a linear relationship between gene expression levels for shared genes that were captured using either All-Exon or Kinome kits. Gene expression correlations between the two capture-based approaches were similar using RNA from FFPE and FF samples. However, TruSeq RNA Access protocol provided significantly higher exon and junction reads when compared to the SureSelect All-Exon capture kit and was more sensitive for fusion gene detection. Our study established pre and post library construction QC parameters that are essential to reproducible RNA-seq profiling using FFPE samples. We show that gene capture based NGS sequencing is an efficient and highly reproducible strategy for gene expression measurements as well as fusion gene detection.

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Recurrent fusion transcripts detected by whole-transcriptome sequencing of 120 primary breast cancer samples

Genes Chromosomes and Cancer ◽

10.1002/gcc.22279 ◽

2015 ◽

Vol 54 (11) ◽

pp. 681-691 ◽

Cited By ~ 16

Author(s):

Jisun Kim ◽

Sehwan Kim ◽

Seyoon Ko ◽

Yong-ho In ◽

Hyeong-Gon Moon ◽

...

Keyword(s):

Breast Cancer ◽

Primary Breast Cancer ◽

Transcriptome Sequencing ◽

Fusion Transcripts ◽

Whole Transcriptome Sequencing ◽

Whole Transcriptome

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Three Novel AML Cases Harboring the Semi-Cryptic t(7;21)(p22;q22) Translocation Expressing RUNX1-USP42 Fusion Transcripts Associated with Diploidy/Tetraploidy and/or 5q Alterations: a Probably Underestimated Combination

Blood ◽

10.1182/blood.v116.21.2708.2708 ◽

2010 ◽

Vol 116 (21) ◽

pp. 2708-2708

Author(s):

Eric Jeandidier ◽

Carine Gervais ◽

Isabelle Radford-Weiss ◽

Catherine Gangneux ◽

Valerie Rimelen ◽

...

Keyword(s):

Bone Marrow ◽

Chromosomal Abnormalities ◽

Conflicts Of Interest ◽

Fusion Transcript ◽

Fish Analysis ◽

Chimeric Transcript ◽

Rt Pcr ◽

Balanced Translocation ◽

Fusion Transcripts ◽

Cryptic Translocation

Abstract Abstract 2708 RUNX1 is implicated in numerous chromosomal abnormalities acquired in acute myeloid leukemia (AML). The most frequent one, the t(8;21) is associated with a particular morphology together with a favorable prognosis. This is not the case for other 21q abnormalities, that are much less frequent and for which the prognosis is quite different. Moreover, beside point mutations, conventional cytogenetics failed to detect some of chromosomal alterations involving RUNX1. Recently 3 cases of the rare and semi-cryptic t(7;21)(p22;q22) translocation expressing the RUNX1-USP42 fusion transcripts have been reported, demonstrating the recurrence of this abnormality in AML. We describe here 3 additional cases with the same translocation and fusion transcripts, associated to 5q alterations leading to EGR1 and CSF1R heterozygous losses. In all our patients, the t(7;21)(p22.1;q22.3) was initially detected by the systematic FISH evaluation of the blastic populations using ETO-AML1 Dual Fusion probe. Patient#1 bone marrow karyotype was characterized by a tetraploid clone (89,XXYY) with loss of chromosomes 15, 17 and 18 in addition to the t(7;21), and a unbalanced translocation der(5)t(5;13)(q23;q?) between long arms of chromosomes 5 and 13, resulting in a heterozygous loss of EGR1 and CSF1R. Patient #2 blood and bone marrow karyotypes revealed a diploid clone with a del(5)(q31q33) associated with the t(7;21). The FISH analysis confirmed EGR1 and CSF1R deletions. In patient #3, the bone marrow karyotype showed diploid/tetraploïd clones, both harboring the t(7;21)(p22;q22), confirmed by FISH experiments (WCP7, AML1 probes). In addition, a der(5)t(1;5)(q3?2;q21-23) was identified within the tetraploïd clone, resulting in the loss of EGR1 and CSF1R, confirmed by FISH. In all three cases a RUNX1-USP42 fusion transcript was detected using RT-PCR, as well as the reciprocal transcript. Sequence analysis of RT-PCR products showed that the breakpoints occurred exactly in the same introns of USP42 and RUNX1 as in the previously described cases. For patient #1 and #3 a chimeric transcript was found formed of the RUNX1 exon 7 fused to the USP42 exon 3. In patient #2, a shorter chimeric transcript arised from the fusion of the RUNX1 exon 5 to the exon 3 of USP42. As already noticed in the previous reports, an alternative splicing of the RUNX1 exon 6 has been detected in these three cases. The description of these 3 novel t(7;21) confirm the recurrence of this balanced translocation in AML, and shows that this chromosomal abnormality is often associated with diploid/tetraploid clones and/or 5q alterations. Special attention should be paid in karyotype analysis of AML with diploid or tetraploid clones harboring 5q alterations. In such cases RUNX1 rearrangements should be explored using FISH analysis, and RUNX1-USP42 fusion transcript should be searched by RT-PCR in positive cases. Prospective and retrospective studies of AML have now to be settled in order to assess the incidence and clinical relevance of this cryptic translocation. Disclosures: No relevant conflicts of interest to declare.

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533 Detection of recurrent novel fusion transcripts from whole transcriptome sequencing of 120 primary breast cancer

European Journal of Cancer ◽

10.1016/s0959-8049(14)70659-8 ◽

2014 ◽

Vol 50 ◽

pp. 173

Author(s):

J. Kim ◽

S.Y. Go ◽

S.W. Kim ◽

S. Lee ◽

H.S. Lee ◽

...

Keyword(s):

Breast Cancer ◽

Primary Breast Cancer ◽

Transcriptome Sequencing ◽

Fusion Transcripts ◽

Whole Transcriptome Sequencing ◽

Whole Transcriptome

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Genome-wide co-localization of RNA-DNA interactions and fusion RNA pairs

10.1101/472019 ◽

2018 ◽

Author(s):

Zhangming Yan ◽

Norman Huang ◽

Weixin Wu ◽

Weizhong Chen ◽

Yiqun Jiang ◽

...

Keyword(s):

Gene Pair ◽

Validation Cohort ◽

Fusion Gene ◽

Spatial Proximity ◽

Rna Seq ◽

Dna Interactions ◽

Normal Cells ◽

Fusion Transcripts ◽

Genome Wide ◽

Cancer Types

AbstractFusion transcripts are used as biomarkers in companion diagnoses. Although more than 15,000 fusion RNAs have been identified from diverse cancer types, few common features have been reported. Here, we compared 16,410 fusion transcripts detected in cancer (from a published cohort of 9,966 tumor samples of 33 cancer types) with genome-wide RNA-DNA interactions mapped in two normal, non-cancerous cell types (using iMARGI, an enhanced version of the MARGI [Mapping RNA-Genome Interactions assay]). Among the top 10 most significant RNA-DNA interactions in normal cells, 5 co-localized with the gene pairs that formed fusion RNAs in cancer. Furthermore, throughout the genome, the frequency of a gene pair to exhibit RNA-DNA interactions is positively correlated with the probability of this gene pair to present documented fusion transcripts in cancer. To test whether RNA-DNA interactions in normal cells are predictive of fusion RNAs, we analyzed these in a validation cohort of 96 lung cancer samples using RNA-seq. 37 out of 42 fusion transcripts in the validation cohort were found to exhibit RNA-DNA interactions in normal cells. Finally, by combining RNA-seq, single-molecule RNA FISH, and DNA FISH, we detected a cancer sample with EML4-ALK fusion RNA without forming the EML4-ALK fusion gene. Collectively, these data suggest a novel RNA-poise model, where spatial proximity of RNA and DNA could poise for the creation of fusion transcripts.

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