Clonal Architecture Research Articles

Single-Cell Analysis Reveals Transcriptomic Features of Drug-Tolerant Persisters and Stromal Adaptation in a Patient-Derived EGFR-Mutated Lung Adenocarcinoma Xenograft Model.

Targeted therapies require life-long treatment, as drug discontinuation invariably leads to tumor recurrence. Recurrence is mainly driven by minor subpopulations of drug-tolerant persister (DTP) cells that survive the cytotoxic drug effect. In lung cancer, DTP studies have mainly been conducted with cell line models. We conducted an invivo DTP study using a lung adenocarcinoma patient-derived xenograft tumor driven by an EGFR mutation. Daily treatment of tumor-bearing mice for 5 to 6 weeks with the EGFR inhibitor erlotinib markedly shrunk tumors and generated DTPs, which were analyzed by whole exome, bulk population transcriptome, and single-cell RNA sequencing. The DTP tumors maintained the genomic clonal architecture of untreated baseline (BL) tumors but had reduced proliferation. Single-cell RNA sequencing identified a rare (approximately 4%) subpopulation of BL cells (DTP-like) with transcriptomic similarity to DTP cells and intermediate activity of pathways that are up-regulated in DTPs. Furthermore, the predominant transforming growth factor-β activated cancer-associated fibroblast (CAF) population in BL tumors was replaced by a CAF population enriched for IL6 production. Invitro experiments indicate that these populations interconvert depending on the levels of transforming growth factor-β versus NF-κB signaling, which is modulated by tyrosine kinase inhibitor presence. The DTPs had signs of increased NF-κB and STAT3 signaling, which may promote their survival. The DTPs may arise from a specific preexisting subpopulation of cancer cells with partial activation of specific drug resistance pathways. Tyrosine kinase inhibitor treatment induces DTPs revealing greater activation of these pathways while converting the major preexisting CAF population into a new state that may further promote DTP survival.

ViCloD, an interactive web tool for visualizing B cell repertoires and analyzing intraclonal diversities: application to human B-cell tumors.

High throughput sequencing of adaptive immune receptor repertoire (AIRR-seq) has provided numerous human immunoglobulin (IG) sequences allowing specific B cell receptor (BCR) studies such as the antigen-driven evolution of antibodies (soluble forms of the membrane-bound IG part of the BCR). AIRR-seq data allows researchers to examine intraclonal differences caused primarily by somatic hypermutations in IG genes and affinity maturation. Exploring this essential adaptive immunity process could help elucidate the generation of antibodies with high affinity or broadly neutralizing activities. Retracing their evolutionary history could also clarify how vaccines or pathogen exposition drive the humoral immune response, and unravel the clonal architecture of B cell tumors. Computational methods are necessary for large-scale analysis of AIRR-seq properties. However, there is no efficient and interactive tool for analyzing intraclonal diversity, permitting users to explore adaptive immune receptor repertoires in biological and clinical applications. Here we present ViCloD, a web server for large-scale visual analysis of repertoire clonality and intraclonal diversity. ViCloD uses preprocessed data in the format defined by the Adaptive Immune Receptor Repertoire (AIRR) Community. Then, itperforms clonal grouping and evolutionary analyses, producing a collection of useful plots for clonal lineage inspection. The web server presents diverse functionalities, including repertoire navigation, clonal abundance analysis, and intraclonal evolutionary tree reconstruction. Users can download the analyzed data in different table formats and save the generated plots as images. ViCloD is a simple, versatile, and user-friendly tool that can help researchers and clinicians to analyze B cell intraclonal diversity. Moreover, its pipeline is optimized to process hundreds of thousands of sequences within a few minutes, allowing an efficient investigation of large and complex repertoires.

Single cell analysis in head and neck cancer reveals potential immune evasion mechanisms during early metastasis

Profiling tumors at single-cell resolution provides an opportunity to understand complexities underpinning lymph-node metastases in head and neck squamous-cell carcinoma. Single-cell RNAseq (scRNAseq) analysis of cancer-cell trajectories identifies a subpopulation of pre-metastatic cells, driven by actionable pathways including AXL and AURK. Blocking these two proteins blunts tumor invasion in patient-derived cultures. Furthermore, scRNAseq analyses of tumor-infiltrating CD8 + T-lymphocytes show two distinct trajectories to T-cell dysfunction, corroborated by their clonal architecture based on single-cell T-cell receptor sequencing. By determining key modulators of these trajectories, followed by validation using external datasets and functional experiments, we uncover a role for SOX4 in mediating T-cell exhaustion. Finally, interactome analyses between pre-metastatic tumor cells and CD8 + T-lymphocytes uncover a putative role for the Midkine pathway in immune-modulation and this is confirmed by scRNAseq of tumors from humanized mice. Aside from specific findings, this study demonstrates the importance of tumor heterogeneity analyses in identifying key vulnerabilities during early metastasis.

RcCAE: a convolutional autoencoder method for detecting intra-tumor heterogeneity and single-cell copy number alterations.

Intra-tumor heterogeneity (ITH) is one of the major confounding factors that result in cancer relapse, and deciphering ITH is essential for personalized therapy. Single-cell DNA sequencing (scDNA-seq) now enables profiling of single-cell copy number alterations (CNAs) and thus aids in high-resolution inference of ITH. Here, we introduce an integrated framework called rcCAE to accurately infer cell subpopulations and single-cell CNAs from scDNA-seq data. A convolutional autoencoder (CAE) is employed in rcCAE to learn latent representation of the cells as well as distill copy number information from noisy read counts data. This unsupervised representation learning via the CAE model makes it convenient to accurately cluster cells over the low-dimensional latent space, and detect single-cell CNAs from enhanced read counts data. Extensive performance evaluations on simulated datasets show that rcCAE outperforms the existing CNA calling methods, and is highly effective in inferring clonal architecture. Furthermore, evaluations of rcCAE on two real datasets demonstrate that it is able to provide a more refined clonal structure, of which some details are lost in clonal inference based on integer copy numbers.

Abstract P4-02-04: Serial monitoring of circulating tumor cells and circulating tumor DNA in metastatic lobular breast cancer identifies intra-tumor heterogeneity and precision and immuno-oncology biomarkers of therapeutic importance

Abstract Clinical decisions on precision and immuno-oncology therapies are based on predictive biomarkers commonly obtained from a single metastatic biopsy or archived primary tumor tissue. Circulating genomic biomarkers offer a minimally invasive approach to monitor intra-patient tumor heterogeneity and detect in real-time the clinically-relevant evolving clonal architecture. Although currently underutilized, we hypothesize that single-cell DNA next generation sequencing (scNGS) of circulating tumor cells (CTC) is a particularly well-suited method to complement biomarker information obtained from tissue and cell-free circulating tumor DNA (ctDNA). In this study we analyzed 113 individual CTC, 21 ctDNA, and 15 white blood cells (WBC) samples, from 15 CTC-positive lobular breast cancer patients, four of whom had CTC available at both metastatic baseline and after progression on a variety of therapies chosen at their physician’s discretion. Clinical NGS data from 15 tumor tissue biopsies obtained using a ~1700-gene DNA panel and whole transcriptome sequencing were available for comparison. CTC were enriched with the CellSearch® system and isolated as single cells with the DEPArray™ system. Whole genome amplified CTC and WBC, as well as ctDNA underwent scNGS with the Oncomine Comprehensive Assay covering ~500 genes and 1.1Mb of genomic space to detect mutations, copy number alterations, tumor mutation burden (TMB) and microsatellite instability (MSI). 99.1% of single cells and 95.2% of ctDNA samples were informative, with a mean sequencing depth of 664x. Using our previously developed, CTC-based precision medicine reporting platform, MI-CTCSeq, CTC in 9 of 15 patients (60%) had mutations that were actionable by FDA-approved targeted therapies including in the oncogenes PIK3CA and FGFR2 and HER2. 3 of these 9 patients (33%) harbored actionable alterations not shared between all 3 analyte types (tissue, CTC and ctDNA). These included 3 actionable mutations found in CTC and ctDNA only, 1 in tissue and ctDNA only, and 1 in ctDNA only. However, 2 of those ctDNA mutations were identified near the limit of detection and with a priori knowledge of their presence from tissue or CTC. Further, 1 patient with plentiful CTC had no detectable ctDNA and one patient’s tissue biopsy was inadequate for sequencing while both liquid biopsy analytes were abundant. 13 patients (87%) displayed intra-patient, inter-CTC genomic heterogeneity of putative driver mutations. 1 of 4 (25%) patients with CTC available in >1 timepoint displayed fluctuations in their CTC subclonal makeup between timepoints. Data from this patient’s 2 tissue biopsies, 3 ctDNA samples, and 27 individual CTC over 4 timepoints combined to reveal in unprecedented detail inter-metastatic lesion and inter-CTC heterogeneity and tumor evolution in response to endocrine and immunotherapy selective pressures. ScNGS of CTC helped provide an additional level of detail not appreciated by sequencing of the other two analyte types. In another patient, CTC were composed of 2 subclones which were indistinguishable by ctDNA, 1 of which appears to have not been sampled by the tissue biopsy. Using a novel method, we enabled detection of single-cell CTC TMB and MSI. CTC TMB scores (dichotomized as above/below 10 mutations/Mb) were 100% concordant with those measured in the corresponding tissue biopsies. Further, in a novel observation, we detected intra patient, inter-CTC heterogeneity of TMB and MSI, which has potential implications for immunotherapy response and development of resistance. Taken together, these data support the non-invasive biomarker interrogation and monitoring by liquid biopsy that incorporates CTC scNGS and complements tissue in informing precision and immuno-oncology approaches. This may have important implications for appropriate treatment selection and identification of therapeutic resistance mechanisms. Citation Format: Andi Cani, Emily Dolce, Alissa Turnbull, Kevin Hu, Chia-Jen Liu, Elizabeth Darga, Dan Robinson, Yi-Mi Wu, Dafydd G. Thomas, Costanza Paoletti, Scott Tomlins, James Rae, Aaron Udager, Arul Chinnaiyan, Erin F. Cobain, Daniel F. Hayes. Serial monitoring of circulating tumor cells and circulating tumor DNA in metastatic lobular breast cancer identifies intra-tumor heterogeneity and precision and immuno-oncology biomarkers of therapeutic importance [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-02-04.

Single-center, observational study of AML/MDS-EB with IDH1/2 mutations: genetic profile, immunophenotypes, mutational kinetics and outcomes

ABSTRACTObjectiveIDH1/2 mutations, intervening in epigenetic procedures, are frequently encountered in acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS). Knowledge of the genetics, immunophenotypes, and mutational kinetics of IDH1/2-mutated AML can contribute to the understanding of AML clonal architecture and inform therapeutics and monitoring.MethodsWe retrospectively analyzed 50 IDH1/2-mutated AML/MDS-EB cases of our institution, to identify recurrent co-mutations, immunophenotypes, patterns of co-variance of IDH1/2 allele burdens with those of recurrent co-mutations, frequency of persistent IDH1/2 mutation as clonal hematopoiesis of indeterminate potential (CHIP) in remission and response to hypomethylating agents.ResultsMost frequently co-mutated genes were DNMT3A, SRSF2 and NPM1. Most cases with co-existent IDH1/2 and NPM1 mutations (11/13) showed an ‘APL-like’ immunophenotype (CD34-HLADR-). Allele burdens of mutated IDH1/2 were identical to mutated SRSF2 allele burdens at diagnosis and remission, but not always to mutated NPM1 allele burden in remission. We show persistence of significant mutIDH1/2 allele burden in approximately one-fourth of patients with deep remissions. IDH1/2 mutations were significantly more frequent among responders to first-line HMA-based regimens than among non-responders, in patients treated for myeloid neoplasms with excess blasts.ConclusionsIDH1/2 mutations are most frequently accompanied by DNMT3A, SRSF2 and NPM1 mutations. NPM1-IDH1/2 mutated AML has a mature phenotype possibly amenable to differentiation therapies. IDH1/2 and SRSF2 mutations probably arise at the same developmental stage of the disease, as their allele burdens covariate. IDH1/2 mutation represents CHIP in a substantial proportion of cases and is therefore no reliable residual disease marker. The preferential presence of IDH1/2 mutations among HMA-responders could inform therapeutic decisions if confirmed in larger series.

Next-CLL, a New Next-Generation Sequencing–Based Method for Assessment of IGHV Gene Mutational Status in Chronic Lymphoid Leukemia

Current guidelines for patients with chronic lymphocytic leukemia (CLL) recommend mutation status determination of the clonotypic IGHV gene before treatment initiation to guide the choice of first-line therapy. Currently, commercially available next-generation sequencing (NGS) solutions have technical constraints, as they necessitate at least a 2×300 bp sequencing, which restricts their use for routine practice. The cost of the commercial kits also represents an important drawback. We present a new method called Next-CLL, a ready-to-use strategy to evaluate IGHV gene mutation status using any NGS device (including 2×150 bp sequencers) in routine diagnostic laboratories. The performance of Next-CLL was validated on genomic DNA and cDNA obtained from 80 patients with CLL at diagnosis. Next-CLL identified a productive clone in 100% of cases, whereas PCR with Sanger sequencing led to a 12.5% failure rate. Next-CLL had 100% concordance with the reference technique for IGHV gene identification and allowed assessment of the IGHV mutation status from the leader sequence, following international guidelines. Comparing a large retrospective series of samples, analyzed by using Sanger sequencing (n=773) or Next-CLL (n = 352), showed no bias in IGHV usage or mutational status, further validating our strategy in the real-life setting. Next-CLL represents a straightforward workflow for IGHV analysis in routine practice to assess clonal architecture and prognosis of patients with CLL.

Breakdown of clonal cooperative architecture in multispecies biofilms and the spatial ecology of predation

Biofilm formation, including adherence to surfaces and secretion of extracellular matrix, is common in the microbial world, but we often do not know how interaction at the cellular spatial scale translates to higher-order biofilm community ecology. Here we explore an especially understudied element of biofilm ecology, namely predation by the bacterium Bdellovibrio bacteriovorus. This predator can kill and consume many different Gram-negative bacteria, including Vibrio cholerae and Escherichia coli. V.cholerae can protect itself from predation within densely packed biofilm structures that it creates, whereas E.coli biofilms are highly susceptible to B.bacteriovorus. We explore how predator-prey dynamics change when V.cholerae and E.coli are growing in biofilms together. We find that in dual-species prey biofilms, E.coli survival under B.bacteriovorus predation increases, whereas V.cholerae survival decreases. E.coli benefits from predator protection when it becomes embedded within expanding groups of highly packed V.cholerae. But we also find that the ordered, highly packed, and clonal biofilm structure of V.cholerae can be disrupted if V.cholerae cells are directly adjacent to E.coli cells at the start of biofilm growth. When this occurs, the two species become intermixed, and the resulting disordered cell groups do not block predator entry. Because biofilm cell group structure depends on initial cell distributions at the start of prey biofilm growth, the surface colonization dynamics have a dramatic impact on the eventual multispecies biofilm architecture, which in turn determines to what extent both species survive exposure to B.bacteriovorus.

Measurable Residual Disease and Clonal Evolution in Acute Myeloid Leukemia from Diagnosis to Post-Transplant Follow-Up: The Role of Next-Generation Sequencing

It has now been ascertained that acute myeloid leukemias-as in most type of cancers-are mixtures of various subclones, evolving by acquiring additional somatic mutations over the course of the disease. The complexity of leukemia clone architecture and the phenotypic and/or genotypic drifts that can occur during treatment explain why more than 50% of patients-in hematological remission-could relapse. Moreover, the complexity and heterogeneity of clone architecture represent a hindrance for monitoring measurable residual disease, as not all minimal residual disease monitoring methods are able to detect genetic mutations arising during treatment. Unlike with chemotherapy, which imparts a relatively short duration of selective pressure on acute myeloid leukemia clonal architecture, the immunological effect related to allogeneic hematopoietic stem cell transplant is prolonged over time and must be overcome for relapse to occur. This means that not all molecular abnormalities detected after transplant always imply inevitable relapse. Therefore, transplant represents a critical setting where a measurable residual disease-based strategy, performed during post-transplant follow-up by highly sensitive methods such as next-generation sequencing, could optimize and improve treatment outcome. The purpose of our review is to provide an overview of the role of next-generation sequencing in monitoring both measurable residual disease and clonal evolution in acute myeloid leukemia patients during the entire course of the disease, with special focus on the transplant phase.

Next-generation sequencing shows the genomic features of ovarian clear cell cancer and compares the genetic architectures of high-grade serous ovarian cancer and clear cell carcinoma in ovarian and endometrial tissues.

Ovarian clear cell carcinoma (OCCC) is a special histological type of epithelial ovarian cancer (EOC) that is not derived from epithelial cells of the ovarian or fallopian tube as the most common type of ovarian cancer, high-grade serous ovarian carcinoma (HGSOC), but is closely related to endometriosis and similar to endometrial clear cell carcinoma (ECCC) at morphologic and phenotypic features. However, limited data was shown in OCCC genomic features and compared with that in OCCC, HGSOC and ECCC. Herein, we utilized next-generation sequencing analysis of a panel of 1,021 genes to profile the mutational alterations in 34 OCCC and compared them to those from HGSOC (402 cases) and ECCC (30 cases). In result, the ARID1A and PIK3CA are high-frequency mutations of OCCC. Clonal architectures showed that all the mutations of genes occur in the later stage in the OCCC progress, whereas KRAS mutation is the earlier event compared with mutation of ARID1A or PIK3CA, which usually occurs in a group of ARID1A or PIK3CA mutations. The mutation frequency of main driver genes is similar between OCCC and ECCC, while TP53 is the main mutation in HGSOC and ECCC. Shared mutational signatures between OCCC and ECCC tissues with commonly observed a C>T change indicated a common carcinogens-exposed between these two carcinomas, but HGSOC and ECCC have common and distinct mutational signatures across cohorts respectively. In addition, we identified some novel CNV gains in NF1, ASXL1, TCF7L2, CREBBP and LRP1B and loss in ATM, FANCM, RB1 and FLT in OCCC. Our study offered a new perspective for OCCC tumorigenesis from two organs, the ovary and uterus, at genomic architectures and revealed novel CNV events for helping to provide theoretical support for OCCC treatment.

Decision level integration of unimodal and multimodal single cell data with scTriangulate

Decisively delineating cell identities from uni- and multimodal single-cell datasets is complicated by diverse modalities, clustering methods, and reference atlases. We describe scTriangulate, a computational framework to mix-and-match multiple clustering results, modalities, associated algorithms, and resolutions to achieve an optimal solution. Rather than ensemble approaches which select the “consensus”, scTriangulate picks the most stable solution through coalitional iteration. When evaluated on diverse multimodal technologies, scTriangulate outperforms alternative approaches to identify high-confidence cell-populations and modality-specific subtypes. Unlike existing integration strategies that rely on modality-specific joint embedding or geometric graphs, scTriangulate makes no assumption about the distributions of raw underlying values. As a result, this approach can solve unprecedented integration challenges, including the ability to automate reference cell-atlas construction, resolve clonal architecture within molecularly defined cell-populations and subdivide clusters to discover splicing-defined disease subtypes. scTriangulate is a flexible strategy for unified integration of single-cell or multimodal clustering solutions, from nearly unlimited sources.

OGC P04 Spatial sampling of Barrett's oesophagus reveals that tumour heterogeneity is not a useful predictor of progression to cancer

Abstract Background Intra-tumour heterogeneity has been well-described in oesophageal adenocarcinoma and Barrett's oesophagus (BE) segments also consist of multiple clones (groups of cells which share mutations). In BE there is some suggestion that the number of individual genetic clones within the segment and the diversity of the segment can be predictors of progression to cancer. However, this was with pre- whole genome sequencing (WGS) methods. In this study we consider the detailed spatial maps of ten patients with different disease trajectories, using WGS, to determine the heterogeneity and correlate it with their progression. Methods We performed WGS (50x) on 35 high-quality, frozen, endoscopic biopsies taken spatially from ten cases (8 males, 2 females, median age 75 (range 31–83). This included 4 long-term non-dysplastic (ND) patients with long BE segments and 6 patients with dysplasia. We used the copy number and purity information (from Battenberg) and the somatic mutation clustering information (from DPClust) to infer the clonal and subclonal architecture of individual biopsies and looked at the spatial relationship between biopsies within the segment. Results In both ND and dysplastic BE we saw cells with unrelated patterns of mutations, or clones, implying completely separate origins for different parts of the segments. This suggests independent or parallel evolution. There was a higher burden of shared (truncal) mutations in the dysplastic biopsies (p=0.049), indicating a more recent clonal sweep with some clones being outcompeted. Dysplastic samples had more subclonal copy number aberrations and more clonal driver mutations. In addition, most of the driver gene alterations in the dysplastic trees occurred early, whereas CDKN2A, the p16 locus, was the only truncal mutation found on the ND clone trees. We did not find the number of clones or the diversity of the segment to differ between the two groups. Conclusions Each individual patient showed complex, distinct genomic features and evolutionary trajectories. Some cases arose from a single ancestral clone, while others had few shared mutational variants suggesting multiple clones. Importantly, in this sample of cases we did not see any trend that the clonal diversity or number of clones correlated with progression to cancer. This is different to previous studies and highlights the importance of multiple sampling to determine the propensity for cancer progression even if the samples look similar histologically.

Novel Molecular Insights into Leukemic Evolution of Myeloproliferative Neoplasms: A Single Cell Perspective.

Myeloproliferative neoplasms (MPNs) are clonal disorders originated by the serial acquisition of somatic mutations in hematopoietic stem/progenitor cells. The major clinical entities are represented by polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF), that are caused by driver mutations affecting JAK2, MPL or CALR. Disease progression is related to molecular and clonal evolution. PV and ET can progress to secondary myelofibrosis (sMF) but can also evolve to secondary acute myeloid leukemia (sAML). PMF is associated with the highest frequency of leukemic transformation, which represents the main cause of death. sAML is associated with a dismal prognosis and clinical features that differ from those of de novo AML. The molecular landscape distinguishes sAML from de novo AML, since the most frequent hits involve TP53, epigenetic regulators, spliceosome modulators or signal transduction genes. Single cell genomic studies provide novel and accurate information about clonal architecture and mutation acquisition order, allowing the reconstruction of clonal dynamics and molecular events that accompany leukemic transformation. In this review, we examine our current understanding of the genomic heterogeneity in MPNs and how it affects disease progression and leukemic transformation. We focus on molecular events elicited by somatic mutations acquisition and discuss the emerging findings coming from single cell studies.

GEN-10 WHOLE GENOME LANDSCAPE OF GLIOBLASTOMA, IDH-WILD TYPE

Abstract Introduction: Glioblastoma, IDH-wild type (GBM) is the most common malignant brain tumor with a dismal prognosis. Although its coding region is well-analyzed, little is yet known about the landscape of whole-genome in GBM. Here, we analyzed whole-genome sequencing data from large cohorts to completely uncover the genetic aberrations in GBM. Methods: We analyzed 281 whole-genome sequencing data of patients with GBM, of which 152 cases are from our cohort with deep coverage (×120) and 129 cases are from a public database. Results: The median numbers of somatic mutations and structural variants (SVs) per case are 3.0/Mb and 62.5, respectively. While a complex SV is rare in other malignant brain tumors such as IDH-mutant glioma (35% of samples), a large proportion of GBM cases (85%) have complex SV with ≥10 breakpoints. CDKN2A/B homozygous deletions (HDs) are usually comprised of a simple deletion in IDH-mutant glioma whereas about a quarter of CDKN2A/B HDs in GBM are induced by complex SVs. In addition, 30.5% of extrachromosomal DNA (ecDNA) involves multiple chromosomes. Taken together, complex SVs could play a key role in the initiation and progression of GBM. Our deep WGS enables us to delineate a fine view of clonal architecture, where mutational signature varies between clonal and subclonal mutations. The majority of clonal mutations consist of the clock-like signature, whereas subclonal mutations have a relatively low proportion of the clock-like signature. Instead, several other signatures including the APOBEC signature significantly increase in subclones, presuming that various mutational processes along with the clock-like signature contribute to the GBM pathogenesis in its progression phase. Conclusions: GBM evolves through exploiting complex structural variants involving multiple driver genes and the accumulation of genetic mutations caused by distinct mechanisms depending on its developmental stage.

Genomic evolution during locoregional recurrence in colorectal cancer determined by whole-exome sequencing: a retrospective observational study

Objective: The genomic landscapes of metastatic colorectal cancer (mCRC) have been extensively studied; however, the genetic mechanisms underlying the locoregional recurrence (LR) of CRC remain unclear. The objective of our study was to investigate genomic evolution during LR in CRC using high-throughput sequencing. Methods: Twenty-three CRC patients with matched primary and LR tissues were recruited from Nanfang Hospital and Zhejiang Cancer Hospital between January 2011 and December 2018. The last date of follow-up was March 2020. Tissue samples were analyzed by whole-exome sequencing and the genomic profiles were depicted by single nucleotide variation, mutational signature, copy number variation, clonal architecture, and other features. The evolutionary process was speculated with comparison of the genetic variations between primary and LR lesions. The disseminating clusters from primary to LR lesions were identified by variant allele frequency dynamics. Furthermore, the early-recurrent biomarker was explored by comparing the indel signature between early- and late-recurrent patients. The study was approved by the Institutional Review Board of Nanfang Hospital of Southern Medical University (approval No. 2020010) on September 11, 2020. Results: The results highlighted distinct origins of LR between patients with high microsatellite instability and microsatellite stability. LR lesions evolved independently in patients with high microsatellite instability, while LR lesions were highly clonally related to the primary lesions in patients with microsatellite stability. Late-acquired variations in LR lesions encompassed a wide range of driver genes involved in histone methylation, DNA replication, T cell activation, PDCD1 gain, and LMNA loss. Furthermore, clonal analysis of the disseminating cells identified a dominant polyclonal seeding pattern during LR. The indel signature ID4 was associated with significantly shorter disease-free survival in patients with relapsed CRC according to a public dataset. Conclusion: These findings pose a challenge for the development of new approaches targeting the interactions of multiple clones in the establishment of LR and in terms of optimizing the clinical management of susceptible patients.

Temporal and spatial characteristics of tumor evolution in a mouse model of oral squamous cell carcinoma

ObjectivesWe aimed to elucidate the temporal and spatial characteristics of tumor evolution in an oral squamous cell carcinoma (OSCC) mouse model with higher burden of lymphatic metastasis through high-throughput sequencing.MethodsThe OSCC model was established in 9 mice. DNA was extracted from the tumors of primary tongue lesions and disseminated tumor cells (DTCs) of submandibular gland lymph nodes and bone marrow, and then whole genome sequencing was performed. After bioinformatics analysis, somatic single-nucleotide variants (SSNVs) and copy number variations (CNVs) data were obtained. Based on SSNVs, clonal architecture and ancestor-descendant relationships among tumor cell subclones were elucidated.ResultsA total of 238 tumor-related SSNVs with 120 high-frequency mutated genes were obtained from 36 samples of 9 mice by whole-genome sequencing. The number of unique SSNVs in the primary lesion, submandibular lymph node and bone marrow was greater than the number of shared SSNVs. Furthermore, the primary lesion-originated subclones, which were identified by SSNVs, were also detected in submandibular lymph nodes in the early stage of oral carcinogenesis. Moreover, at different histopathological stages, unique subclones were also identified in DTCs isolated from lymph nodes.ConclusionTumor heterogeneity is significant in primary tumor cells and disseminated tumor cells. OSCC cells probably disseminate to lymph nodes in the early stage of oral carcinogenesis. OSCC is characterized by polyclonal dissemination, and the evolutionary trajectory of DTCs is potentially dominated by the tumor microenvironment.

The Impact of Clonal Hierarchy and Heterogeneity on Phenotypic Manifestations of Myelodysplastic Neoplasms.

Until recently, conventional prognostication of myelodysplastic neoplasms (MDS) was performed using the revised International Prognostic Scoring System (IPSS-R), with additional adverse prognoses conferred by select mutations. Nonetheless, the clonal diversity and dynamics of coexisting mutations have been shown to alter the prognosis and treatment response in patients with MDS. Often in the process of clonal evolution, various initial hits are preferentially followed by a specific spectrum of secondary alterations, shaping the phenotypic and biologic features of MDS. Our ability to recapitulate the clonal ontology of MDS is a necessary step toward personalized therapy and the conceptualization of a better classification system, which ideally would take into consideration all genomic aberrations and their inferred clonal architecture in individual cases. In this review, we summarize our current understanding of the molecular landscape of MDS and the role of mutational combinations, clonal burden, and clonal hierarchy in defining the clinical fate of the disease.

Germline SAMD9/9L MDS Predisposition Syndromes Are Characterized By Complex Clonal Architecture and Lineage-Specific Escape Mechanisms Including Somatic Genetic Rescue in T and B Lymphocytes

Inherited bone marrow failure (BMF) and MDS predisposition syndromes have an intrinsic defect resulting in loss and/or dysfunction of hematopoietic stem and progenitor cells (HSPC). HSPC clones can escape this process by acquiring gene- or genome-level genetic changes (compensatory mutations or uniparental disomies (UPD)) thereby increasing cellular fitness. This process, referred to as somatic genetic rescue (SGR) has been shown to occur in >70% of patients with gain-of-function mutations in SAMD9 and SAMD9L (SAMD9/9L) genes, which are a common cause of early onset BMF and pediatric MDS with monosomy 7. It is unknown how SGR arises and in which cells it originates. Furthermore, little is known about the epistatic interactions of various rescue events. We aimed to address these questions by utilizing a newly established single cell (sc)-proteogenomic platform that can simultaneously detect single nucleotide variants (SNVs) and copy number variation (CNVs) in addition to protein expression. We applied this technology to study clonal architecture and cellular origins of SGR lesions in a cohort of clinically annotated SAMD9/9L-mutated (SAMD9/9Lmut) patients. We also asked if monosomy 7, traditionally assessed by karyotyping, can be also detected in peripheral blood (PB) of affected patients. We first performed whole exome and panel sequencing to characterize 67 germline SAMD9/9Lmut patients. Guided by this data, we designed a sc-proteogenomic panel with 69 amplicons specific to variants in SAMD9/9L and leukemia driver genes, and 250 amplicons covering high-frequency SNVs on chromosome 7q. For validation of initial findings, we developed a second panel targeting full coding regions of SAMD9/9L genes, and additional 7p SNVs allowing for a precise delineation of uniparental isodisomy 7q (UPD7q). We included oligonucleotide-conjugated antibodies specific to major hematopoietic antigens, including CD19, CD3, CD11b, CD38 and CD34. Using this panel, we analyzed 22 samples (15 bone marrow (BM) and 7 PB) of 10 patients enrolled in local biobanking protocols. On average, 3,845 high-quality cells were genotyped per sample, and we robustly identified SNVs, monosomy 7 and UPD7q changes in single cells. Somatic rescue SAMD9/9Lmut were found only in clones with normal (diploid) chromosome 7, UPD7q (containing two wild type SAMD9/9L alleles after mitotic recombination event) was a stand-alone clone, while monosomy 7 (SAMD9/9Lmut lost) occurred alone or together with leukemia driver mutations. We also detected lesions that were previously missed using routine clinical sequencing in 3 patients (somatic SAMD9/9Lmut or UPD7q). Most patients had branching clonal architecture (i.e., independent monosomy 7, UPD7q, and somatic SAMD9/9Lmut), while linear trajectories were rare (i.e., monosomy 7 à + leukemia driver mutation). Serial assessment of 4 patients with stable hematology (3 with monosomy 7 and 1 with an additional somatic SAMD9/9Lmut) for a period of up to 4.8 years, revealed stable clonal populations without acquisition of additional driver mutations. Quantification of clones in paired BM and PB in 4 patients demonstrated equal frequencies of monosomy 7 and somatic SAMD9/9Lmut in both compartments, demonstrating the utility of this assay in surveillance. Our findings were confirmed by sorting BM cells into different lineages followed by sequencing, error-corrected sequencing, and ddPCR. Finally, analysis of protein expression data revealed that while monosomy 7 is present exclusively in cells with myeloid phenotype, the SGR events can arise in lymphocyte lineage only; 4 patients carried clones with somatic SAMD9/9Lmut in CD3+ lymphocytes, and 2 patients had UPD7q clones in either CD3+ or CD19+ lymphocytes. These findings provide clues why most of the SGR events in patients do not result in long-lasting clinical remission since the genetic rescue can be restricted only to certain hematopoietic lineages. In conclusion, single cell proteogenomic analysis is useful for the understanding the mechanisms of clonal evolution in SAMD9/9L syndromes. This method also offers the opportunity for less invasive surveillance of karyotype abnormalities from peripheral blood in patients who are at high risk for MDS progression.

Single Cell Genotypic and Phenotypic Analysis of Measurable Residual Disease in Acute Myeloid Leukemia

Measurable residual disease (MRD) represents the critical population of leukemic cells which persists following anti-leukemic therapy. The presence of MRD has powerful prognostic relevance and represents the reservoir responsible for acute myeloid leukemia (AML) relapse. It is therefore critical to enumerate and molecularly characterize MRD clones in order to better risk stratify AML patients and guide further therapy aimed at preventing relapse and improving outcomes. Current MRD methods, including multi-color flow cytometry (MFC) analysis and bulk NGS sequencing, face challenges in both sensitivity and specificity and are insufficient to distinguish between pre-leukemic and leukemic clones. Consequently, the imperfect predictive value of these techniques hinders meaningful clinical intervention. To overcome these shortcomings associated with conventional methods of MRD detection, we developed a novel single-cell (sc) MRD assay with high sensitivity and specificity by combining precursor/blast population enrichment with integrated scDNA sequencing and immunophenotypic analysis. We reasoned that the MRD clones responsible for relapse largely reside in immature compartments. Enriched CD34+ and/or CD117+ progenitors from 5 unique patient samples were multiplexed followed by integrated single cell analysis on the MissionBio TapestriV2 scDNA+protein platform. We developed a novel computational approach to deconvolute multiplexed sequencing reads and accurately assign cells to individual patients via K-means clustering and UMAP dimension reduction of germline SNP allele frequencies. To demonstrate the sensitivity and specificity of our scMRD assay, 10,000, 1,000, 500, and 200 AML blasts from 3 patients harboring known pathologic mutations (NRAS/RUNX1, JAK2/IDH2, and IDH2 alone) were individually spiked into 10 million normal bone marrow cells to test a sensitivity threshold of 0.1%, 0.01%, 0.005%, and 0.002%. Samples were FACS-enriched for blasts, multiplexed, subjected to the TapestriV2 microfluidics platform, and sequenced. The expected pathologic mutations were reliably identified in patients at a threshold of 0.01%, but not in normal subjects, demonstrating that our assay is nearly 10-fold more sensitive than the current ELN MRD standard [Fig 1]. We then applied our assay to 30 banked post-induction MRD samples from 29 patients (median age 71 years old, 15 male/14 female) who had a diagnosis of AML [Fig 2]. Overall, genomic analysis was concordant in 22/30 (73%) samples between bulk NGS (at MRD stage) and scMRD. The mean VAF of mutations was higher by scMRD than bulk NGS, consistent with our hypothesis that mutations are enriched in immature compartments. 17 mutations were identified by scMRD but missed/unreported by bulk NGS, including RUNX1 (n=5), NPM1 (n=3), KRAS (n=2), IDH2 (n=2), WT-1 (n=2), JAK2, TP53 and SRSF2 mutations, 14 of which were present at relapse. Clonal architecture was illustrated by scMRD data with identification of pre-leukemic and leukemic clones. In 5 post-HSCT samples, scMRD readily distinguished between donor vs. host cells and showed higher host cell chimerism compared to conventional STR testing, suggesting that host cells have higher enrichment in immature cell types and represent an early indicator of relapse. Our scMRD assay also enabled single cell immunophenotypic analysis, and revealed concordant abnormal immunophenotype of leukemic blasts identified by MFC. More importantly, differential immunophenotypic states were identified when comparing pre-leukemic and leukemic clones (i.e. DNMT3A only vs co-mutant DNMT3/NPM1) within and between patients. These data show that integrated genomic/immunophenotypic analysis at the MRD timepoint can distinguish between clonal hematopoiesis and pre-leukemic/leukemic clones with a substantively higher likelihood of relapse. In conclusion, our scMRD assay not only enhances MRD detection, but also provides a molecular glimpse into the clonal architecture of pre-leukemic/leukemic cells surviving AML therapy. Larger studies are needed to comprehensively elucidate the clonal architecture of MRD and study the dynamics of clonal evolution by comparing clonal architecture and immunophenotype at diagnosis and relapse. Our study paves the road for identifying/eradicating high-risk MRD clones and preventing relapse through a better understanding of the molecular drivers of MRD. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Integrative Analysis of Blast Phase Chronic Myelomonocytic Leukemia Reveals Distinct Transformation Phenotypes Predictive of Drug Response

Introduction: Blastic transformation of chronic myelomonocytic leukemia (CMML) is a common and terminal event. Blast phase CMML (BP-CMML) displays clinical and genetic heterogeneity, but its clonal evolution and transcriptional dynamics are poorly understood. Improved stratification would better characterize transformation phenotypes and identify opportunities for personalized therapy. Methods: Blasts/HSPCs were FACS sorted (SSCloCD45wk) from 43 BP-CMML patients and 7 age-matched healthy controls for bulk RNA-sequencing. Blast immunophenotype by flow cytometry was integrated with clinical metadata in an unsupervised Random Forest classifier. Clonal architecture was investigated using the Tapestri DNA+Protein single cell platform and a bespoke pipeline. Drug testing comprised Cell Titer Glo assay of primary BP-CMML cells. Results: BP-CMML blasts displayed 2090 differentially expressed genes vs control HSPCs. Upregulated genes (n=1424) included the AP-1 transcription factors (JUN, JUNB, JUND), ATF3, and ID1; and included 110 genes from our previous single cell RNA seq of BP-CMML, including CXCL8, HLX, LGALS1 and MKNK1. We sought genes/pathways upregulated in both bulk and single cell datasets, prioritizing by known function and availability of inhibitors. We identified 12 targets, including RAF mitogenic effectors (VEGFA, AKT, PI3K, MTOR), the pERK downstream effector MKNK1, HIF1A, STAT3/5 and NFKB. BP-CMML cells were consistently sensitive to AKT, MKNK1 and HIF1A inhibition, irrespective of genotype or prior therapy, with an additive effect at therapeutically relevant doses for combined AKT/MKNK1 inhibition. Observed heterogeneity between BP-CMML cases suggested distinct clinicopathological phenotypes. We integrated clinical metadata with blast immunophenotype (59 independent features) for unsupervised learning by Random Forest, then overlaid RNA-seq. This clearly separated 2 groups ("C1/C2"), with distinctive clinical and molecular features (eg C2 enriched for ASXL1 (p=0.004) and RUNX1 (p=0.044) mutations; C1 for NPM1 (p=0.031)), but no difference in survival. C2 displayed an immature, stem-like phenotype (higher expression of CD34, CD117 and enriched HSC transcriptional signature). C1 reflected a more mature myelomonocytic phenotype (higher CD123, CD13, CD135, CD56) with enrichment of monocytic/granulocytic gene signatures (Fig A). Amongst genes dysregulated in BP-CMML, 1213 and 402 were unique to C1 or C2, respectively. C1 was enriched for myeloid genes (CD14, S100A8/9, TLR4) and related pathways; C2 for ribosomal, mitogenic (MAP3K8) and FOS family. Genie3 highlighted distinct regulatory networks in C1 and C2, driven by myeloid differentiation (SPI1, TFEB, KLF4) and proto-oncogene (JUND, ATF3, ETV6) transcription factors, respectively. Intriguingly, they displayed different/opposing signatures for resistance to azacitidine (C2>C1; p=0.004), venetoclax (C1>C2; p=0.007) and cytarabine (C1>C2; p=0.0003). We validated for C1 absolute and relative (vs C2) ex vivo resistance to venetoclax, daunorubicin and cytarabine, but saw no difference in azacitidine response. Multiomic single cell genotyping (n=8) revealed patterns of clonal expansion linked to secondary genetic events, with all harboring acquired mutations in RAS pathway or IDH1/2. Concurrent profiling of 45 surface proteins uncovered subtype-specific differences in origin and extent of differentiation block arising from blasts. Dominant genetic clones in C2 were restricted to phenotypically primitive (CD34+117+) cells with little maturation beyond. By contrast, fully evolved clones in C1 were widely distributed from primitive to mature cells, indicating transformation initiating upstream with a 'leaky' differentiation block and continued multilineage contribution of blasts to the pool of maturing cells (Fig B). Conclusion: Integration of multimodal data reveals distinct CMML transformation phenotypes associated with unique transcriptional states and drug sensitivities, mirroring the refractoriness of BP-CMML to AML therapy. Subgroups share mitogenic gene expression and ex vivo sensitivity to AKT/MKNK1 inhibition as a promising novel combination therapy. Finally, we describe different routes of clonal evolution, confirming that BP-CMML blasts can retain extensive differentiation capacity to supplant multilevel hematopoiesis after transformation. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal