The Sub-Clonal Complexity of STIL-TAL1 T-ALL

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3788-3788
Author(s):  
Caroline L Furness ◽  
Marcela B Mansur ◽  
Victoria J Weston ◽  
Sarah Jenkinson ◽  
Frederik W van Delft ◽  
...  

Abstract Introduction The STIL-TAL1 fusion is found in 16% cases of paediatric and adolescent T-ALL, making it one of the most common T-ALL subgroups. Our study considers this leukaemia subtype in the context of a complex ecosystem that is diverse, evolving and subject to selective pressures. We used single cell methods to understand the order of co-operating mutational events and the clonal evolution of mutations in genes that are re-iteratively targeted, such as PTEN. Methods Diagnostic DNA from five STIL-TAL1 positive T-ALL cases was exome sequenced using Agilent SureSelect Human all Exon kit plus Illumina paired end sequencing. Driver copy number alterations and NOTCH1/PTEN exon 7 mutation status had been identified in a previous study and candidate driver mutations for inclusion in single cell experiments were validated by sequencing or Q-PCR using custom assays. Where more than one mutation was present within the same exon of a candidate driver gene, cloning experiments were carried out to verify the independent mutation sequences. Material from xenograft transplants was available in three of the five cases to assess their clonal heterogeneity in the leukaemia initiating cell compartment. Single cell multiplex Q-PCR was used to examine the single cell genetics of the pre-defined mutation events. Briefly, single cells were sorted and lysed prior to multiplex specific (DNA) target amplification and Q-PCR using the 96.96 dynamic microfluidic array and the BioMark HD (Fluidigm, UK). Copy number assays for the 1p33 deletion and custom assays for the patient specific STIL-TAL1 fusion breakpoints were used to confirm that the 1p33 deletion leading to this gene fusion was a clonal event. Results The only aberrant events common to all five samples were CKDN2A copy number loss and the 1p33 deletion that results in the STIL-TAL1 fusion. Exome sequencing revealed further mutations in known T-ALL drivers including NOTCH1, PTEN and PHF6 as well as candidate driver mutations in FREM2, PIK3CD, RPL14, BMPR1A and CDH18. Both NOTCH1 and PTEN demonstrated re-iterative inactivation and this was investigated in detail for PTEN. Case 1 had multiple PTEN exon 7 mutations and sub-clonal copy number loss. Case 2 had parallel frameshift mutations in PTEN exons 5 and 7. Case 3 contained an exon 8 mutation and multiple PTEN exon 7 mutations. In this case the three most frequent PTEN exon 7 indels were validated and tracked in a single cell multiplex Q-PCR experiment. This revealed a branching sub-clonal genetic architecture (see figure 1) in which all malignant cells at the proposed apex of the branching architecture harboured the STIL-TAL1 fusion and CDKN2A deletion with copy number losses of 4p, 6q and FREM2 and PTEN mutations occurring as sub-clonal events. PTEN indels 2 and 3 were found co-localised in the same sub-clone. Preliminary analysis of the paired mouse xenograft bone marrow did not detect PTEN exon 7 indels 1 – 3 in 84 single cells. However, bulk Sanger Sequencing analysis did identify the PTEN exon 8 mutation in the mouse. Ongoing work is in progress to determine whether single cells of the xenograft carry alternative PTEN exon 7 mutations detected in the diagnostic sample exome data and to characterise in which diagnostic sub-clone the PTEN exon 8 mutation resides. Conclusions This study demonstrates how exome sequencing and single cell multiplex Q-PCR can be used as complementary tools to understand the sub-clonal complexity of STIL-TAL1 T-ALL. PTEN inactivation is sub-clonal by single cell analysis, demonstrating the parallel evolution of multiple independent PTEN inactivated sub-clones, highlighting PTEN inactivation as a key event in this T-ALL subgroup. In a wider cohort of 20 patients collected by our group at least 50% had PTEN inactivation as assessed by sequencing of exon 7 and copy number data alone. Results indicate a strong evolutionary pressure selecting for mutational events that result in inactivation of the PTEN-PI3Kinase pathway. These events occur via multiple mechanisms, including copy number loss and truncating mutations, which are not limited to the known T-ALL hotspot in exon 7. Current work is focussing on using a similar approach to examine the clonal evolution of NOTCH1 mutations in STIL-TAL1 T-ALL samples in diagnostic and xenograft samples of cases 4 and 5. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii408-iii408
Author(s):  
Marina Danilenko ◽  
Masood Zaka ◽  
Claire Keeling ◽  
Stephen Crosier ◽  
Rafiqul Hussain ◽  
...  

Abstract Medulloblastomas harbor clinically-significant intra-tumoral heterogeneity for key biomarkers (e.g. MYC/MYCN, β-catenin). Recent studies have characterized transcriptional heterogeneity at the single-cell level, however the underlying genomic copy number and mutational architecture remains to be resolved. We therefore sought to establish the intra-tumoural genomic heterogeneity of medulloblastoma at single-cell resolution. Copy number patterns were dissected by whole-genome sequencing in 1024 single cells isolated from multiple distinct tumour regions within 16 snap-frozen medulloblastomas, representing the major molecular subgroups (WNT, SHH, Group3, Group4) and genotypes (i.e. MYC amplification, TP53 mutation). Common copy number driver and subclonal events were identified, providing clear evidence of copy number evolution in medulloblastoma development. Moreover, subclonal whole-arm and focal copy number alterations covering important genomic loci (e.g. on chr10 of SHH patients) were detected in single tumour cells, yet undetectable at the bulk-tumor level. Spatial copy number heterogeneity was also common, with differences between clonal and subclonal events detected in distinct regions of individual tumours. Mutational analysis of the cells allowed dissection of spatial and clonal heterogeneity patterns for key medulloblastoma mutations (e.g. CTNNB1, TP53, SMARCA4, PTCH1) within our cohort. Integrated copy number and mutational analysis is underway to establish their inter-relationships and relative contributions to clonal evolution during tumourigenesis. In summary, single-cell analysis has enabled the resolution of common mutational and copy number drivers, alongside sub-clonal events and distinct patterns of clonal and spatial evolution, in medulloblastoma development. We anticipate these findings will provide a critical foundation for future improved biomarker selection, and the development of targeted therapies.


Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3834-3834
Author(s):  
Christoph Niemöller ◽  
Sabine Bleul ◽  
Nadja Blagitko-Dorfs ◽  
Christine Greil ◽  
Kenichi Yoshida ◽  
...  

Abstract INTRODUCTION: We recently described the first case of the evolution of inv(16) AML on the background of a clonal hematopoiesis due to a germline CBL mutation (defining the CBL syndrome), and we identified possibly cooperating mutations by exome sequencing (Becker et al. Blood 2014;123:1883-6). Among the mutated genes was PTPRT, encoding a protein tyrosine phosphatase that inhibits STAT3 activity and is commonly mutated in cancer (reviewed by Zhao et al. Oncogene 2015;34:3885-94). Here, we investigated the co-occurrence of mutated PTPRT with other mutated genes by single cell genotyping in order gain insights into the clonal architecture and sequence of mutation acquisition. METHODS: Exome sequencing of the bulk specimens was previously described; germline or somatic origin of mutations was verified in skin fibroblasts (Becker et al. Blood 2014;123:1883-6). For single cell genotyping, Ficoll-enriched bone marrow aspirates were DAPI stained, and single cells were placed into each well of a PCR plate using a MoFlo high speed cell sorter (Beckman Coulter). Genomic DNA was amplified by whole genome amplification (WGA) using the REPLI-g Mini Kit (Qiagen) according to a modified protocol, and subjected to PCR and Sanger sequencing of the respective mutation loci. As WGA can lead to allele dropout (ADO), we also sequenced single nucleotide polymorphisms (SNPs), that were identified by CytoScan HD array (Affymetrix) to be heterozygous in the sample and that were located nearby the respective mutation loci. RESULTS: Exome sequencing allows prediction of a possible clonal architecture based on the variant allele frequencies (VAFs). VAFs of the mutations identified in the AML were as follows: KIF14 p.V341I (VAF 51%), TMEM125 p.D113N (51%), MIOX p.W225R (46%), CAND1 p.E584* (39%), NID2 p.D319N (38%), ARF3 p.N101S (36%), PRSS16 p.R491C (36%), PTPRT p.T844M (33%), DOCK6 p.R1872_K1873insP (33%), ADAM12 p.A222V (21%), CMIP p.T323M (15%) and MYOCD p.D283N (7%); due to its germline nature, all leukemic cells harbored the CBL p.D390V mutation. In order to verify the co-occurrence of mutations in a clone and thus the clonal architecture, we performed single cell genotyping of the mutations in PTPRT as well as CAND1 and DOCK6. CAND1 and DOCK6 were selected in addition to PTPRT since their comparable VAFs did not allow identifying the sequence of acquisition. Moreover, CAND1 and DOCK6 were affected by likely deleterious mutations and were previously found mutated in AML. To control for ADO, we included the heterozygous SNPs rs2867061 (PTPRT), rs1252402 (C AND1), and rs12980863 (DOCK6) in our analyses. We analyzed 19 single cells for the 6 mutations and SNPs. This resulted in 102 successful sequencing reactions, and yielded informative results for at least 2 mutations in 12 cells and for all 3 mutations in 5 cells. Based on the concurrent presence of the wild-type allele at the mutation locus and ADO at the SNP site, 18 mutation analyses were judged to be inconclusive. Overall, our analyses confirmed that the mutations in CAND1, PTPRT and DOCK6 occurred together in the same clone. Moreover, based on the identification of cells with the presence of both CAND1 and DOCK6 mutations but presence or absence of PTPRT mutations, respectively, we concluded that PTPRT mutations were acquired after the mutations in DOCK6 and CAND1. CONCLUSION: Single cell genotyping verified the co-occurrence of PTPRT, CAND1 and DOCK6 mutations in the same AML clone and revealed a clonal hierarchy, as the PTPRT mutation was acquired after the mutations in CAND1 and DOCK6. These insights into the clonal architecture and evolution had not been possible solely based on exome sequencing and suggest that the sequential expression of mutated PTPRT may cooperate with mutated CBL and inv(16) at a late stage of AML development. Disclosures No relevant conflicts of interest to declare.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 5264-5264
Author(s):  
Carla AL Assaf ◽  
Els Lierman ◽  
Timothy Devos ◽  
Johan Billiet ◽  
Carlos Graux ◽  
...  

Abstract Background Essential thrombocythemia (ET) is a myeloproliferative neoplasm featured by a sustained elevation of platelet count and a tendency for thrombosis and hemorrhage. Cytogenetic abnormalities are rare in ET. The most common molecular abnormality in ET is JAK2 V617F, found in approximately 50% of ET cases followed by MPL W515K/L, found in about 10% of cases. The molecular cause of the remaining ET cases is still largely unknown. As such, in a substantial fraction of ET cases, the underlying molecular cause is yet to be discovered. In a recent study by Hou et al., single cells derived from an ET JAK2 V617F-negative ET patient were sequenced using a method based on exome sequencing. Eight genes were identified as possible candidate drivers. However, their recurrence rate in ET was not established. Aims To establish the recurrence rate in JAK2 V617F-negative and MPL W515K/L-Negative ET of potential candidate driver mutations, as identified by Hou et al. Methods and Results We studied unfractionated blood or bone marrow samples from a series of 64 cases of JAK2 V617F-negative and MPL W515K/L-negative ET. In this series, we used PCR and Sanger sequencing to detect the following mutations: SESN2 P87S, TOP1MT S479L, ST13 Q349*, and DNAJC17 A292P, as they exhibited the highest scores in the study of Hou et al. In addition, we included NTRK1 N323S, a mutant tyrosine kinase. None of the mutations reported by Hou et al. was detected in our patients. However, we identified a novel acquired heterozygous mutation in TOP1MT (c.1400 A>G, p.N467S) which is predicted to be damaging by polyphen 2. This mutation was not detected in the germline DNA from the buccal swab of the patient. TOP1MT is a mitochondrial topoisomerase encoded by the genomic DNA. It is a type IB enzyme, which sustains the appropriate conformation of DNA during replication, transcription, recombination, and repair. This mutation might affect the interaction of TOP1MT with the DNA molecule as suggested by the results of in silico analysis from I-Tasser. p.N467S mutation causes the gain of a helix and the loss of a β strand which are in close proximity to the bound DNA molecule. We screened exon 11 of TOP1MT gene in 38 additional JAK2 V617F-negative MPL W515K/L-negative ET cases, but did not find any additional cases. Conclusions In this series of 102 cases of JAK2 V617F-negative and MPL W515K/L-negative ET, only one case was identified with a mutation of TOP1MT. Mutations of SESN2, ST13, DNAJC17, or NTRK1, four other candidate driver genes as identified by Hou et al., could not be identified in a series of 64 cases. The functional role of TOP1MT in the pathogenesis of ET remains to be established. The absence of the mutations, as proposed by Hou et al., in our cohort raises questions about their role as potential driver mutations in JAK2 V617F-negative and MPL W515K/L-negative ET. The quest for the full complement of driver mutations in ET therefore remains open. Reference Hou, Y., et al., Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm. Cell, 2012. 148(5): p. 873-85. Disclosures: No relevant conflicts of interest to declare.


2021 ◽  
Author(s):  
Xianbin Su ◽  
Linan Zhao ◽  
Yi Shi ◽  
Rui Zhang ◽  
Qi Long ◽  
...  

AbstractGenetic heterogeneity of tumor is closely related to clonal evolution, phenotypic diversity and treatment resistance. Such heterogeneity has been characterized in liver cancer at single-cell sub-chromosomal scale, and a more precise single-variant resolution analysis is lacking. Here we employed a strategy to analyze both the single-cell genomic mutations and transcriptomic changes in 5 patients with liver cancer. Target sequencing was done for a total of 480 single cells in a patient-specific manner. DNA copy number status of point mutations was obtained from single-cell mutational profiling. The clonal structures of liver cancers were then uncovered at single-variant resolution, and mutation combinations in single cells enabled reconstruction of their evolutionary history. A common origin but independent evolutionary fate was revealed for primary liver tumor and intrahepatic metastatic portal vein tumor thrombus. The mutational signature suggested early evolutionary process may be related to specific etiology like aristolochic acids. By parallel single-cell RNA-Seq, the transcriptomic phenotype was found to be related with genetic heterogeneity in liver cancer. We reconstructed the single-cell and single-variant resolution clonal evolutionary history of liver cancer, and dissection of both genetic and phenotypic heterogeneity provides knowledge for mechanistic understanding of liver cancer initiation and progression.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1043-1043
Author(s):  
Christiane Walter ◽  
Winfried Hofmann ◽  
Katarina Reinhardt ◽  
Dirk Reinhardt ◽  
Nils von Neuhoff

Abstract Introduction: Acute myeloid leukemia (AML) is one of the most frequent forms of leukemia in children younger than 15 years. The detection of several mutations in a blast population of pediatric AML (pAML) is supposed to be caused by a clonal evolution from a leukemic stem cell (LSC) to leukemic blasts. LSC are believed to be more resistant to chemotherapy, to be able to survive during treatment and to be responsible for the emergence of a relapse due to the persistence in the bone marrow (BM) niche. Since LSC and potential leukemic subclones are only present in small subpopulations, it has been a major technical challenge to particular analyse only the specific population. To acquire a better understanding of the underlying mechanisms of mutagenesis, clonal evolution and leukemogenesis, the aim of this study was to establish methods that allow the analysis and detection of mutations in single cells of a subpopulation known to contain HSC as well as LSC (CD34+CD38-). We especially focused on a pAML subgroup with mutations in Nucleophosmin (NPM1) and/or fms related tyrosine kinase 3 (Flt3). Methods and Results: We established methods to perform single cell sorting, whole genome amplification (WGA) using multiple displacement amplification (MDA) technology (Qiagen) and subsequent whole exome sequencing. The sorting efficiency was checked as Hoechst stained cells were sorted onto glas slides with 48 defined spots and the presence of single cells was checked under an inverse fluorescent microscope. Subsequently, single CD34+CD38- patient derived cells were sorted into 0,5ml low binding tubes containing 4µl PBS followed by WGA and whole exome sequencing. The mutational status of the sorted single cells from three patients suffering from pAML was analysed and compared to mutations detected at initial diagnosis in DNA from a bulk of BM cells. WGA from single CD34+CD38-PI- cells resulted in an amount of 29 to 31.7µg DNA from each of five single cells. The quality of the amplified DNA was sufficient for whole exome sequencing. A 4bp insertion in exon 12 of NPM1 reflecting a common NPM1 mutation (MutA) initially detected from a bulk of cells was identified in amplified DNA from single cells using whole exome sequencing in 2/3 patients. Internal tandem duplications in Flt3 indicated by mismatches in the alignment could be detected in amplified DNA from single cells of two patients. The detected ITD resemble those initially detected in DNA from a bulk of BM cells. Discussion and Conclusion: Single cell sequencing provides a useful tool to amend the detection of genetic aberrations from a bulk of cells and to confirm the presence of specific mutations in single cells from small subpopulations. It therefore helps to get further insights into the clonal evolution in pAML. Disclosures No relevant conflicts of interest to declare.


2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi219-vi219
Author(s):  
Cassandra Verheul ◽  
Federica Fabro ◽  
Ioannis Ntafoulis ◽  
Cecile Beerens ◽  
Youri Hoogstrate ◽  
...  

Abstract INTRODUCTION The search for effective therapies for gliomas is progressively moving towards patient-specific medicine. In order to test patient-tailored therapies, it is vital to develop protocols for reliable establishment of patient-derived glioma cultures. We present a method for reliable culture establishment, with a 95% success rate in 114 consecutive high-grade samples. METHODS Cell cultures were established from either traditionally-resected tumor tissue or ultrasonic surgical aspirator (CUSA) derived tissue fragments, and expanded in serum-free culture, with selection of astrocytic populations if required. Cultures were started from single cells or small tumor fragments of 0.5-3mm (3D). Whole exome and RNA sequencing were carried out with the Illumina Novaseq and HiSeq platforms. Methylation profiling was performed with the Infinium MethylationEPIC array. Cultures and tumors were compared through analysis of single nucleotide polymorphisms and copy number profiles with the Infinium Global Screening Array. Intra-tumoral heterogeneity in cultures was investigated with single-cell transcriptomic sequencing (SORT-seq). We studied tumor-initiating potential by orthotopic injection of cultures in NOD-SCID mice. RESULTS Cultures started from single cells were established from CUSA material more efficiently (92%) than from traditional resection material (70%). 3D-derived cultures had a higher overall efficiency (95% for CUSA, 85% for traditional resection material). We confirmed high concordance in driver mutations, copy number and methylation profiles between tumors and derived cultures. Transcriptomics analysis, comparing tumors and derived cultures, revealed high consistency in gene expression distribution as demonstrated by correlation analysis (r=0.88). Singe-cell RNA-seq shows increased heterogeneity in CUSA derived-cultures, and decreased heterogeneity with passaging over time. Cultures faithfully produce tumors after orthotopic injection in NOD-SCID mice. CONCLUSION We present a highly successful method for the establishment of glioma cultures from patient material, with CUSA-derived cultures revealing greater heterogeneity. Cultures faithfully represent important molecular characteristics of parental tumors and can be used to test potential therapies in vitro.


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 2520-2520
Author(s):  
Parashar Dhapola ◽  
Mikael Sommarin ◽  
Mohamed Eldeeb ◽  
Amol Ugale ◽  
David Bryder ◽  
...  

Single-cell transcriptomics (scRNA-Seq) has accelerated the investigation of hematopoietic differentiation. Based on scRNA-Seq data, more refined models of lineage determination in stem- and progenitor cells are now available. Despite such advances, characterizing leukemic cells using single-cell approaches remains challenging. The conventional strategies of scRNA-Seq analysis map all cells on the same low dimensional space using approaches like tSNE and UMAP. However, when used for comparing normal and leukemic cells, such methods are often inadequate as the transcriptome of the leukemic cells has systematically diverged, resulting in irrelevant separation of leukemic subpopulations from their healthy counterpart. Here, we have developed a new computational approach bundled into a tool called Nabo (nabo.readthedocs.io) that has the capacity to directly compare cells that are otherwise unalignable. First, Nabo creates a shared nearest neighbor graph of the reference population, and the heterogeneity of this population is subsequently defined by performing clustering on the graph and calculating a low dimensional representation using t-SNE or UMAP. Nabo then calculates the similarity of incoming cells from a target population to each cell in the reference graph using a modified Canberra metric. The reference cells with higher similarity to the target cells obtain higher mapping scores. The built-in classifier is used to assign each target cell a reference cluster identity. We tested Nabo's accuracy on control datasets and found that Nabo's performance in terms of accuracy and robustness of projection is comparable to state-of-art methods. Moreover, Nabo is a generalized domain adaptation algorithm and hence can perform classification of target cells that are arbitrarily dissimilar to reference cells. Nabo could identify the cell-identity of sorted CD19+ B cells, CD14+ monocytes and CD56+ by projecting these unlabeled cells onto labelled peripheral blood mononuclear cells with an average specificity higher than 0.98. The general applicability of Nabo was demonstrated by successfully integrating pancreatic cells, sequenced in three different studies using different sequencing chemistries with comparable or better accuracy than existing methods. Also, it was conclusively demonstrated that Nabo can predict the identity of human HSPC subpopulations to the same accuracy as can be achieved by established cell-surface markers. Having Nabo at hand, we aimed to uncover the heterogeneity of hematopoietic cells from different stages of AML. Nabo showed that AML cells lacked the heterogeneity of normal CD34+ cells and were devoid of cells with HSC gene signature. A large patient-to-patient variability was found where leukemic cells mapped to distinct stages of myeloid progenitors. To ask whether this variability could reflect differences in leukemia-initiating cell identity, we induced leukemia in murine granulocyte-monocyte-lymphoid progenitors (GMLPs) using an inducible model for MLL-ENL-driven AML. On projection, more than 70% of MLL-ENL-activated cells mapped to a distinct Flt3+ subpopulation present within healthy GMLPs. Statistical validity of this projection was verified using two novel null models for testing cell projections: 1) ablated node model, wherein the mapping strength of target cells are evaluated after removal of high mapping score source nodes, and 2) high entropy features model, which rules out the background noise effect. By separating Flt3+ and Flt3- cells prior to activation of the fusion gene and performing in vitro replating assays, we could demonstrate that Flt3+ GMLPs contained 3-4 fold more leukemia-initiating cells (1/1.34 cells) than Flt3- GMLPs (1/4.89 cells), indicating that leukemia-initiating cells within GMLPs express Flt3. Taken together, Nabo represents a robust cell projection strategy for relevant analysis of scRNA-Seq data that permits an interpretable inference of cross-population relationships. Nabo is designed to compare disparate cellular populations by using the heterogeneity of one population as a point of reference allowing for cell-type specification even following perturbations that have resulted in large molecular changes to the cells of interest. As such, Nabo has critical implementation for delineation of leukemia heterogeneity and identification of leukemia-initiating cell population. Disclosures No relevant conflicts of interest to declare.


2021 ◽  
Vol 11 ◽  
Author(s):  
Qingke Duan ◽  
Chao Tang ◽  
Zhao Ma ◽  
Chuangui Chen ◽  
Xiaobin Shang ◽  
...  

Gastroesophageal junction (GEJ) cancer is a tumor that occurs at the junction of stomach and esophagus anatomically. GEJ cancer frequently metastasizes to lymph nodes, however the heterogeneity and clonal evolution process are unclear. This study is the first of this kind to use single cell DNA sequencing to determine genomic variations and clonal evolution related to lymph node metastasis. Multiple Annealing and Looping Based Amplification Cycles (MALBAC) and bulk exome sequencing were performed to detect single cell copy number variations (CNVs) and single nucleotide variations (SNVs) respectively. Four GEJ cancer patients were enrolled with two (Pt.3, Pt.4) having metastatic lymph nodes. The most common mutation we found happened in the TTN gene, which was reported to be related with the tumor mutation burden in cancers. Significant intra-patient heterogeneity in SNVs and CNVs were found. We identified the SNV subclonal architecture in each tumor. To study the heterogeneity of CNVs, the single cells were sequenced. The number of subclones in the primary tumor was larger than that in lymph nodes, indicating the heterogeneity of primary site was higher. We observed two patterns of multi-station lymph node metastasis: one was skip metastasis and the other was to follow the lymphatic drainage. Taken together, our single cell genomic analysis has revealed the heterogeneity and clonal evolution in GEJ cancer.


2020 ◽  
Vol 10 ◽  
Author(s):  
Wenyang Zhou ◽  
Fan Yang ◽  
Zhaochun Xu ◽  
Meng Luo ◽  
Pingping Wang ◽  
...  

2020 ◽  
Vol 117 (46) ◽  
pp. 28784-28794
Author(s):  
Sisi Chen ◽  
Paul Rivaud ◽  
Jong H. Park ◽  
Tiffany Tsou ◽  
Emeric Charles ◽  
...  

Single-cell measurement techniques can now probe gene expression in heterogeneous cell populations from the human body across a range of environmental and physiological conditions. However, new mathematical and computational methods are required to represent and analyze gene-expression changes that occur in complex mixtures of single cells as they respond to signals, drugs, or disease states. Here, we introduce a mathematical modeling platform, PopAlign, that automatically identifies subpopulations of cells within a heterogeneous mixture and tracks gene-expression and cell-abundance changes across subpopulations by constructing and comparing probabilistic models. Probabilistic models provide a low-error, compressed representation of single-cell data that enables efficient large-scale computations. We apply PopAlign to analyze the impact of 40 different immunomodulatory compounds on a heterogeneous population of donor-derived human immune cells as well as patient-specific disease signatures in multiple myeloma. PopAlign scales to comparisons involving tens to hundreds of samples, enabling large-scale studies of natural and engineered cell populations as they respond to drugs, signals, or physiological change.


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