scholarly journals Self-controlled Sequencing Suggests that Somatic Mutations of Signaling, Transcription and Tumor Suppression Genes are a Precondition for AML Transformation in MDS

Author(s):  
Feng Xu ◽  
Ling-Yun Wu ◽  
Juan Guo ◽  
Qi He ◽  
Zheng Zhang ◽  
...  

Abstract Background The transformation biology of secondary AML from MDS is still not fully understood. Here, we performed a large cohort of paired self-controlled sequences including target, whole-exome and single cell sequencing to search AML transformation-related mutations (TRMs). Methods 39 target genes from paired samples from 72 patients with MDS who had undergone AML transformation were analyzed by next generation target sequencing. Whole exome and single-cell RNA sequencing were used to verify the dynamics of transformation. Results The target sequencing results showed that sixty-four out of the 72 (88.9%) patients presented presumptive TRMs involving activated signaling, transcription factors, or tumor suppressors. Of the 64 patients, most of TRMs (62.5%, 40 cases) emerged at the leukemia transformation point. All three of the remaining eight patients analyzed by paired whole exome sequencing showed TRMs which are not included in the reference targets. No patient with MDS developed into AML only by acquiring mutations involved in epigenetic modulation or RNA splicing. Single-cell sequencing in one pair sample indicated that the activated cell signaling route was related to TRMs which take place prior to phenotypic development. Of note, target sequencing defined TRMs were limited to a small set of seven genes (in the order: NRAS/KRAS, CEBPA, TP53, FLT3, CBL, PTPN11 and RUNX1, accounted for nearly 90.0% of the TRMs). Conclusions Somatic mutations involving in signaling, transcription factors, or tumor suppressors appeared to be a precondition for AML transformation from MDS. The TRMs may be considered as new therapy targets.

2021 ◽  
Author(s):  
Xiao Li ◽  
Chun-Kang Chang ◽  
Feng Xu ◽  
Ling-Yun Wu ◽  
Juan Guo ◽  
...  

The transformation biology of secondary AML from MDS is still not fully understood. Here, we performed a large cohort of paired sequences including target, whole-exome and single cell sequencing to search AML transformation- related mutations (TRM). The results showed that fifty-five out of the 64 (85.9%) patients presented presumptive TRM involving activated signaling, transcription factors, or tumor suppressors. Most of TRM (63.6%, 35 cases) emerged at the leukemia transformation point. All five of the remaining nine patients analyzed by paired whole exome sequencing showed TRM which are not included in the reference targets. Single-cell sequencing indicated that the activated cell signaling route was related to TRM which take place prior to phenotypic development. Of note, defined TRM was limited to a small set of genes (less than ten, in the order: NRAS/KRAS, CEBPA, TP53, FLT3, RUNX1, CBL, PTPN11 and WT1, accounted for 91.0% of the mutations). In conclusion, somatic mutations involving in activated signaling, transcription factors, or tumor suppressors appeared to be a precondition for AML transformation from myelodysplastic syndromes. The TRM may be considered as new therapy targets.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1943-1943 ◽  
Author(s):  
Lili Wang ◽  
Dylan Kotliar ◽  
Jean Fan ◽  
Shuqiang Li ◽  
Jonna Grimsby ◽  
...  

Abstract Cancer cell phenotype is controlled by both genetic composition and gene expression. Recent large-scale cancer sequencing studies have revealed extensive intratumoral genetic heterogeneity and have demonstrated its potential impact on clonal evolution and clinical outcome. The most direct approach to uncovering the impact of genetic heterogeneity on cellular phenotype requires integration of genetic and transcriptomic profiles of single cells. Currently, however, RNA and DNA cannot be reliably isolated from the same cell. Here, we demonstrate the feasibility for linking single-cell somatic mutation data with cellular transcriptional heterogeneity through a targeted RNA-based approach. By leveraging a microfluidic platform (Fluidigm BioMarkTMHD system) to perform multiplexed targeted amplification of RNA derived from hundreds of single cells, we have generated a versatile approach for the integrated detection of somatic mutations in relation to specific gene transcripts. We focused on a series of chronic lymphocytic leukemia (CLL) B cells that were previously characterized by bulk whole-exome (WES) and RNA-sequencing (RNA-Seq). We developed 2 classes of assays. First, we generated multiplexed nested quantitative RT-PCR assays of 96 genes with known involvement in CLL biology. Second, to simultaneously detect patient-specific somatic mutations in the same cell, we devised multiplexed pre-amplification primers targeting transcribed regions containing somatic point mutations. These regions were then amplified using paired nested primers, for detection of the wild-type or mutant alleles. We focused on those somatic mutations with detectable expression in bulk CLL RNA (> 5 FPKM by RNA-seq). When applied to either artificial oligonucleotide templates or bulk patient cDNA, these paired wild-type and mutant allele detection assays reliably demonstrated consistent differences in DCT values of >6 cycles. In total, we designed expression assays for 96 genes and 46 mutation detection applied to 5 CLL samples (median of 9 assays/sample, range 6-13). We examined up to 384 single cells from each of 5 samples and from normal CD19+ B cells. Based on expression of housekeeping genes ACTB and B2M, we observed viable expression in 1951 of 2112 cells (92.4%). We could clearly discern that expression of the 96 genes was heterogeneous across 354 single CLL-B cells and could discriminate CLL from 174 normal B cells by principal component analysis. 32 out of 46 (70%) mutation detection assays successfully distinguished between wild-type and mutant alleles and the mutant allele was consistently observed in the originating CLL cells, but not in unrelated CLL or non-leukemic B cells. Our RNA-based estimates of allele frequency agreed with single-cell targeted DNA-based detection of somatic mutations conducted for 3 of 5 CLL samples as well as with frequencies estimated from bulk WES-based cancer cell fraction (CCF) measurements. We applied our integrated assay design to 2 CLL samples known to harbor mutations in the putative CLL driver SF3B1: Patient 1 with bulk CCF of 17% (G742D) and Patient 2 with 87% (K700E). Mutation of this critical spliceosome component broadly changes RNA splicing profiles although the functional impact of these alternative splice variants on CLL biology remains unknown. We generated multiplex assays for SF3B1 mutation detection and for expression of mutation-associated alternative splice variants. Consistent with the bulk-sequencing results, we detected 50 of 373 (13.4%) single CLL cells from Patient 1 with SF3B1 mutation. Moreover, the subset of cells with SF3B1 mutation demonstrated high expression of splice variants relative to wild-type cells (GCC2 and MAP3K7, p< 0.000001). This SF3B1 mutated subclone also displayed reduced expression of RNA splicing factors (BTAF1, DDX17, SNW1, SRSF3, U2SURP; all p<0.05), cell cycle regulators (CDC27, PDS5A; p<0.015) and an inflammatory pathway gene (MALT1p=0.039), suggesting involvement of SF3B1 mutation in these biological processes. Analysis of Patient 2 is ongoing. Taken together, our study demonstrates the feasibility of linking genotype with gene expression at the RNA level. Furthermore, these analyses reveal the potential for single cell RNA-based analysis to directly uncover the effects of driver mutations on the leukemia cell phenotype. Disclosures Brown: Sanofi, Onyx, Vertex, Novartis, Boehringer, GSK, Roche/Genentech, Emergent, Morphosys, Celgene, Janssen, Pharmacyclics, Gilead: Consultancy.


Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 70-70
Author(s):  
Sarra L Ryan ◽  
Vikki Rand ◽  
Claire Schwab ◽  
Heather Morrison ◽  
Elizabeth Matheson ◽  
...  

Abstract Abstract 70 Intrachromosomal amplification of chromosome 21 (iAMP21) represents a distinct cytogenetic subgroup of BCP-ALL, in which patients experience a high-risk of relapse on standard treatment protocols. The abnormal chromosome 21 defining iAMP21 has a heterogeneous, complex profile at the genomic level. This complexity has made it difficult to elucidate target genes or the initiating mechanism giving rise to iAMP21 using standard genomic approaches. In this study, detailed genomic and mutational analysis has highlighted potential novel targets in the development of iAMP21 BCP-ALL. DNA was available from 45 iAMP21 patient samples. Patient 1 was a 10 year old female; her diagnostic karyotype was 47,XX,+10,der(21)dup(21)(q?)r(21)(q?). Fluorescence in situ hybridization detected multiple copies of RUNX1, thus defining iAMP21. SNP 6.0 arrays indicated the characteristic genomic profile of chromosome 21, comprising a ∼30Mb (from 17–47Mb) region of copy number gain/amplification. Many of the breakpoints occurred within the Down Syndrome Critical Region (DSCR), specifically within the gene, DSCAM at 41.4Mb, and a telomeric deletion was identified with a breakpoint within the gene, TSPEAR at 45.9Mb. Chromosome 7 abnormalities were frequent, with one deletion including IKZF1 at 50.3Mb. The IKZF1, ETV6 and RB1 deletions seen by SNP 6.0 arrays were confirmed by Multiplex Ligation Probe-dependent Amplification (MLPA) and quantitative PCR. Whole-exome sequencing of the diagnostic and remission DNA of patient 1 identified 44 somatic mutations; 21 were computationally predicted to be potentially damaging to the function of the protein. The variant frequency of the individual somatic mutations ranged from 1.1% − 65.2%, indicating heterogeneity within the iAMP21 genome. The majority of the variants were detected at a frequency of <10%, emphasising the importance of in depth coverage for the detection of mutations. A number (n=8) were confirmed by direct Sanger sequencing. Novel somatic mutations were identified in the B-cell development (ENPEP) and histone modification (SMYD3, RPL24, SIN3B) pathways. Genomic abnormalities in components of these pathways have been previously associated with BCP-ALL development. Six of the potentially-damaging mutations occurred within 3 genes: SIM2, SYNJ1, UMODL1, located within the DSCR, which have been implicated in the development of Down syndrome. We have previously demonstrated that Down syndrome-ALL and iAMP21 BCP-ALL share common genetic abnormalities: gain of an X chromosome and a high incidence of P2RY8-CRLF2 fusion. Furthermore, we identified a mutation in NF1, a component of the Ras signalling pathway. The mutation (P1496S) occurred in the kinase-binding domain at a variant frequency of 27%. Activation of the Ras signalling pathway was confirmed by pERK expression shown by Western blot analysis. This is the first report of deregulation of the Ras signalling pathway in iAMP21 BCP-ALL. Additional studies using a combination of target-enrichment strategies and massively parallel deep-sequencing identified NRAS and KRAS mutations in 18 of the remaining 44 iAMP21 patients. These mutations were frequently identified in hotspot regions: NRAS G12D, KRAS G13D. Dual mutations were identified in both NRAS and KRAS in two patients, suggesting a cooperative effect of Ras signalling pathway defects. In conclusion, genomic analysis and whole exome sequencing of a single patient has identified novel mutations: ENPEP and SMYD3, RPL24, SIN3B; in the B-cell development and histone modification pathways, respectively, indicating the involvement of pathways in iAMP21 patients that are common to other BCP-ALL subtypes. Although previously reported at a high level in high-risk childhood BCP-ALL, the involvement of the Ras signalling pathway was observed for the first time in iAMP21 BCP-ALL, through the identification of a NF1 mutation in patient 1. The involvement of the Ras signalling pathway in 41% of iAMP21 patients was confirmed by the finding of NRAS and KRAS mutations in a larger iAMP21 cohort. The novel identification of 3 mutated genes (SIM2, SYNJ1, UMODL1) and breakpoints within 2 others (DSCAM, TSPEAR) located within the DSCR reinforces common features between Down syndrome-ALL and iAMP21 BCP-ALL, which may further our understanding of the increased leukemia risk of Down syndrome individuals. Disclosures: Schnittger: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Grossmann:MLL Munich Leukemia Laboratory: Employment. Kohlmann:MLL Munich Leukemia Laboratory: Employment.


2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Andrew P. Hutchins

AbstractRecent innovations in single cell sequencing-based technologies are shining a light on the heterogeneity of cellular populations in unprecedented detail. However, several cellular aspects are currently underutilized in single cell studies. One aspect is the expression and activity of transposable elements (TEs). TEs are selfish sequences of DNA that can replicate, and have been wildly successful in colonizing genomes. However, most TEs are mutated, fragmentary and incapable of transposition, yet they are actively bound by multiple transcription factors, host complex patterns of chromatin modifications, and are expressed in mRNAs as part of the transcriptome in both normal and diseased states. The contribution of TEs to development and cellular function remains unclear, and the routine inclusion of TEs in single cell sequencing analyses will potentially lead to insight into stem cells, development and human disease.


2019 ◽  
Author(s):  
Qiao Rui Xing ◽  
Chadi EL Farran ◽  
Yao Yi ◽  
Tushar Warrier ◽  
Pradeep Gautam ◽  
...  

SUMMARYWe developed ASTAR-Seq (Assay for Single-cell Transcriptome and Accessibility Regions) integrated with automated microfluidic chips, which allows for parallel sequencing of transcriptome and chromatin accessibility within the same single-cell. Using ASTAR-Seq, we profiled 192 mESCs cultured in serum+LIF and 2i medium, 424 human cell lines including BJ, K562, JK1, and Jurkat, and 480 primary cells undergoing erythroblast differentiation. Integrative analysis using Coupled NMF identified the distinct sub-populations and uncovered sets of regulatory regions and the respective target genes determining their distinctions. Analysis of epigenetic regulomes further unravelled the key transcription factors responsible for the heterogeneity observed.


2017 ◽  
Author(s):  
Sara Aibar ◽  
Carmen Bravo González-Blas ◽  
Thomas Moerman ◽  
Jasper Wouters ◽  
Vân Anh Huynh-Thu ◽  
...  

AbstractSingle-cell RNA-seq allows building cell atlases of any given tissue and infer the dynamics of cellular state transitions during developmental or disease trajectories. Both the maintenance and transitions of cell states are encoded by regulatory programs in the genome sequence. However, this regulatory code has not yet been exploited to guide the identification of cellular states from single-cell RNA-seq data. Here we describe a computational resource, called SCENIC (Single Cell rEgulatory Network Inference and Clustering), for the simultaneous reconstruction of gene regulatory networks (GRNs) and the identification of stable cell states, using single-cell RNA-seq data. SCENIC outperforms existing approaches at the level of cell clustering and transcription factor identification. Importantly, we show that cell state identification based on GRNs is robust towards batch-effects and technical-biases. We applied SCENIC to a compendium of single-cell data from the mouse and human brain and demonstrate that the proper combinations of transcription factors, target genes, enhancers, and cell types can be identified. Moreover, we used SCENIC to map the cell state landscape in melanoma and identified a gene regulatory network underlying a proliferative melanoma state driven by MITF and STAT and a contrasting network controlling an invasive state governed by NFATC2 and NFIB. We further validated these predictions by showing that two transcription factors are predominantly expressed in early metastatic sentinel lymph nodes. In summary, SCENIC is the first method to analyze scRNA-seq data using a network-centric, rather than cell-centric approach. SCENIC is generic, easy to use, and flexible, and allows for the simultaneous tracing of genomic regulatory programs and the mapping of cellular identities emerging from these programs. Availability: SCENIC is available as an R workflow based on three new R/Bioconductor packages: GENIE3, RcisTarget and AUCell. As scalable alternative to GENIE3, we also provide GRNboost, paving the way towards the network analysis across millions of single cells.


2021 ◽  
Author(s):  
Bo Yuan ◽  
Mengdi Wang ◽  
Xinran Wu ◽  
Peipei Cheng ◽  
Ran Zhang ◽  
...  

Abstract Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder characterized by deficits in social interactions and repetitive behaviors. Although hundreds of ASD risk genes, implicated in synaptic formation and transcriptional regulation, have been identified through human genetic studies, the East Asian ASD cohorts is still under-represented in the genome-wide genetic studies. Here we performed whole-exome sequencing on 369 ASD trios including probands and unaffected parents of Chinese origin. Using a joint-calling analytical pipeline based on GATK toolkits, we identified numerous de novo mutations including 55 high-impact variants and 165 moderate-impact variants, as well as de novo copy number variations containing known ASD-related genes. Importantly, combining with single-cell sequencing data from the developing human brain, we found that expression of genes with de novo mutations were specifically enriched in pre-, post-central gyrus (PRC, PC) and banks of superior temporal (BST) regions in the human brain. By further analyzing the brain imaging data with ASD and health controls, we found that the gray volume of the right BST in ASD patients significantly decreased comparing to health controls, suggesting the potential structural deficits associated with ASD. Finally, we found that there was decrease in the seed-based functional connectivity (FC) between BST/PC/PRC and sensory areas, insula, as well as frontal lobes in ASD patients. This work indicated that the combinatorial analysis with genome-wide screening, single-cell sequencing and brain imaging data would reveal brain regions contributing to etiology of ASD.


2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Yasunobu Nagata ◽  
Hideki Makishima ◽  
Cassandra M. Kerr ◽  
Bartlomiej P. Przychodzen ◽  
Mai Aly ◽  
...  

AbstractMyelodysplastic syndromes (MDS) arise in older adults through stepwise acquisitions of multiple somatic mutations. Here, analyzing 1809 MDS patients, we infer clonal architecture by using a stringent, the single-cell sequencing validated PyClone bioanalytic pipeline, and assess the position of the mutations within the clonal architecture. All 3,971 mutations are grouped based on their rank in the deduced clonal hierarchy (dominant and secondary). We evaluated how they affect the resultant morphology, progression, survival and response to therapies. Mutations of SF3B1, U2AF1, and TP53 are more likely to be dominant, those of ASXL1, CBL, and KRAS are secondary. Among distinct combinations of dominant/secondary mutations we identified 37 significant relationships, of which 12 affect clinical phenotypes, 5 cooperatively associate with poor prognosis. They also predict response to hypomethylating therapies. The clonal hierarchy has distinct ranking and the resultant invariant combinations of dominant/secondary mutations yield novel insights into the specific clinical phenotype of MDS.


2021 ◽  
Author(s):  
Vanita Berry ◽  
Alex Ionides ◽  
Nikolas Pontikos ◽  
Anthony T Moore ◽  
Roy A Quinlan ◽  
...  

Abstract Background: Lens development is orchestrated by transcription factors. Disease-causing variants in transcription factors and their developmental target genes are associated with congenital cataracts and other eye anomalies.Methods: Using whole exome sequencing, we identified disease-causing variants in two large British families and one isolated case with autosomal dominant congenital cataract. Bioinformatics analysis confirmed these disease-causing mutations as rare or novel variants, with a moderate to damaging pathogenicity score, with testing for segregation within the families using direct Sanger sequencing. Results: Family A had a missense variant (c.184G>A; p.V62M) in PAX6 and affected individuals presented with nuclear cataract. Family B had a frameshift variant (c.470-477dup; p.A160R*) in PITX3 that was also associated with nuclear cataract. A recurrent missense variant in HSF4 (c.341T>C; p.L114P) was associated with congenital cataract in a single isolated case. Conclusions: We have therefore identified novel variants in PAX6 and PITX3 that cause autosomal dominant congenital cataract.


2020 ◽  
Author(s):  
Yuan Gao ◽  
Jeff Gaither ◽  
Julia Chifman ◽  
Laura Kubatko

Although the role of evolutionary processes in cancer progression is widely accepted, increasing attention is being given to evolutionary mechanisms that can lead to differences in clinical outcome. Recent studies suggest that the temporal order in which somatic mutations accumulate during cancer progression is important. Single-cell sequencing provides a unique opportunity to examine the mutation order during cancer progression. However, the errors associated with single-cell sequencing complicate this task. We propose a new method for inferring the order in which somatic mutations arise within a tumor using noisy single-cell sequencing data that incorporates the errors that arise from the data collection process. Using simulation, we show that our method outperforms existing methods for identifying mutation order in most cases, especially when the number of cells is large. Our method also provides a means to quantify the uncertainty in the inferred mutation order along a fixed phylogeny. We apply our method to empirical data for colorectal and prostate cancer.


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