Protocol to study the inheritance and propagation of non-genetically encoded states using barcode decay lineage tracing

Here, we present a protocol to perform barcode decay lineage tracing followed by single-cell transcriptome analysis (BdLT-Seq). We describe steps for BdLT-Seq experimental design, building barcoded episome reporters, performing episome transfection, and barcode retrieval. We then describe procedures for sequencing library construction while providing options for sample multiplexing and data analysis. This BdLT-Seq technique enables the assessment of clonal evolution in a directional manner while preserving isogeneity, thus allowing the comparison of non-genetic molecular features between isogenic cell lineages. For complete details on the use and execution of this protocol, please refer to Shlyakhtina et al. (2023).1.

Clonal hematopoiesis of indeterminate potential in persons with HIV

BACKGROUND

Clonal hematopoiesis of indeterminate potential (CHIP) has been associated with older age, inflammation and with risk of coronary artery disease (CAD). We aimed to characterize the burden of CHIP, and to explore the association between CHIP, inflammatory markers, and CAD in older persons with HIV (PWH).

METHODS

From the Copenhagen Comorbidity in HIV Infection (COCOMO) study, we included 190 individuals older than 55 years of age. We defined CHIP as variant allele fraction at least 2%. CAD was categorized according to the most severe coronary artery lesion on coronary computed tomography (CT) angiography as no coronary atherosclerosis; any atherosclerosis defined as at least 1% stenosis and obstructive CAD defined as at least 50% stenosis.

RESULTS

In the entire population (median age 66 years, 87% men), we identified a total of 62 mutations distributed among 49 (26%) participants. The three most mutated genes were DNMT3A , TET2 , and ASXL1 , accounting for 49, 25, and 16% of mutations, respectively. Age and sex were the only variables associated with CHIP. IL-1β, IL-1Ra, IL-2, IL-6, IL-10, soluble CD14, soluble CD163 and TNF-α were not associated with CHIP, and CHIP was not associated with any atherosclerosis or with obstructive CAD in adjusted analyses.

CONCLUSION

In older, well treated, Scandinavian PWH, more than one in four had at least one CHIP mutation. We did not find evidence of an association between CHIP and inflammatory markers or between CHIP and CAD. CHIP is an unlikely underlying mechanism to explain the association between inflammation and CAD in treated HIV disease.

Joint analysis of mutational and transcriptional landscapes in human cancer reveals key perturbations during cancer evolution

BACKGROUND

Tumors are able to acquire new capabilities, including traits such as drug resistance and metastasis that are associated with unfavorable clinical outcomes. Single-cell technologies have made it possible to study both mutational and transcriptomic profiles, but as most studies have been conducted on model systems, little is known about cancer evolution in human patients. Hence, a better understanding of cancer evolution could have important implications for treatment strategies.

RESULTS

Here, we analyze cancer evolution and clonal selection by jointly considering mutational and transcriptomic profiles of single cells acquired from tumor biopsies from 49 lung cancer samples and 51 samples with chronic myeloid leukemia. Comparing the two profiles, we find that each clone is associated with a preferred transcriptional state. For metastasis and drug resistance, we find that the number of mutations affecting related genes increases as the clone evolves, while changes in gene expression profiles are limited. Surprisingly, we find that mutations affecting ligand-receptor interactions with the tumor microenvironment frequently emerge as clones acquire drug resistance.

CONCLUSIONS

Our results show that lung cancer and chronic myeloid leukemia maintain a high clonal and transcriptional diversity, and we find little evidence in favor of clonal sweeps. This suggests that for these cancers selection based solely on growth rate is unlikely to be the dominating driving force during cancer evolution.

Mutations, Bottlenecks, and Clonal Sweeps: How Environmental Carcinogens and Genomic Changes Shape Clonal Evolution during Tumor Progression

The transition from a single, initiated cell to a full-blown malignant tumor involves significant genomic evolution. Exposure to carcinogens-whether directly mutagenic or not-can drive progression toward malignancy, as can stochastic acquisition of cancer-promoting genetic events. Mouse models using both carcinogens and germline genetic manipulations have enabled precise inquiry into the evolutionary dynamics that take place as a tumor progresses from benign to malignant to metastatic stages. Tumor progression is characterized by changes in somatic point mutations and copy-number alterations, even though any single tumor can itself have a high or low burden of genomic alterations. Further, lineage-tracing, single-cell analyses and CRISPR barcoding have revealed the distinct clonal dynamics within benign and malignant tumors. Application of these tools in a range of mouse models can shed unique light on the patterns of clonal evolution that take place in both mouse and human tumors.

Modeling stress-induced responses: plasticity in continuous state space and gradual clonal evolution

Mathematical models of cancer and bacterial evolution have generally stemmed from a gene-centric framework, assuming clonal evolution via acquisition of resistance-conferring mutations and selection of their corresponding subpopulations. More recently, the role of phenotypic plasticity has been recognized and models accounting for phenotypic switching between discrete cell states (e.g., epithelial and mesenchymal) have been developed. However, seldom do models incorporate both plasticity and mutationally driven resistance, particularly when the state space is continuous and resistance evolves in a continuous fashion. In this paper, we develop a framework to model plastic and mutational mechanisms of acquiring resistance in a continuous gradual fashion. We use this framework to examine ways in which cancer and bacterial populations can respond to stress and consider implications for therapeutic strategies. Although we primarily discuss our framework in the context of cancer and bacteria, it applies broadly to any system capable of evolving via plasticity and genetic evolution.

Case report: Cytopenias in VEXAS syndrome - a WHO 2022 based approach in a single-center cohort

VEXAS syndrome is an acquired autoinflammatory disease characterized in most cases by cytopenias and macrocytic anemia. Dyshematopoiesis is a frequent finding in chronic inflammatory conditions and therefore, cytopenias are not easily classified in VEXAS patients. Here we report a series of 7 patients affected by VEXAS associated cytopenias, treated at our center. The use of NGS, together with morphological assays, integrated with the WHO 2022 criteria, allowed to identify three subsets of VEXAS associated cytopenias: ICUS (idiopathic cytopenia of uncertain significance), CCUS (clonal cytopenia of uncertain significance) at high risk of clonal evolution, and MDS. This approach could help to better understand the nature of VEXAS associated cytopenias and to guide the use of specific targeted treatments in order to achieve long lasting responses.

Clonal Hematopoiesis of Indeterminate Potential (CHIP) and Incident Type 2 Diabetes Risk

OBJECTIVE

Clonal hematopoiesis of indeterminate potential (CHIP) is an aging-related accumulation of somatic mutations in hematopoietic stem cells, leading to clonal expansion. CHIP presence has been implicated in atherosclerotic coronary heart disease (CHD) and all-cause mortality, but its association with incident type 2 diabetes (T2D) is unknown. We hypothesized that CHIP is associated with elevated risk of T2D.

RESEARCH DESIGN AND METHODS

CHIP was derived from whole-genome sequencing of blood DNA in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) prospective cohorts. We performed analysis for 17,637 participants from six cohorts, without prior T2D, cardiovascular disease, or cancer. We evaluated baseline CHIP versus no CHIP prevalence with incident T2D, including associations with DNMT3A, TET2, ASXL1, JAK2, and TP53 variants. We estimated multivariable-adjusted hazard ratios (HRs) and 95% CIs with adjustment for age, sex, BMI, smoking, alcohol, education, self-reported race/ethnicity, and combined cohorts' estimates via fixed-effects meta-analysis.

RESULTS

Mean (SD) age was 63.4 (11.5) years, 76% were female, and CHIP prevalence was 6.0% (n = 1,055) at baseline. T2D was diagnosed in n = 2,467 over mean follow-up of 9.8 years. Participants with CHIP had 23% (CI 1.04, 1.45) higher risk of T2D than those with no CHIP. Specifically, higher risk was for TET2 (HR 1.48; CI 1.05, 2.08) and ASXL1 (HR 1.76; CI 1.03, 2.99) mutations; DNMT3A was nonsignificant (HR 1.15; CI 0.93, 1.43). Statistical power was limited for JAK2 and TP53 analyses.

CONCLUSIONS

CHIP was associated with higher incidence of T2D. CHIP mutations located on genes implicated in CHD and mortality were also related to T2D, suggesting shared aging-related pathology.

Somatic evolution of marine transmissible leukemias in the common cockle, Cerastoderma edule

Transmissible cancers are malignant cell lineages that spread clonally between individuals. Several such cancers, termed bivalve transmissible neoplasia (BTN), induce leukemia-like disease in marine bivalves. This is the case of BTN lineages affecting the common cockle, Cerastoderma edule, which inhabits the Atlantic coasts of Europe and northwest Africa. To investigate the evolution of cockle BTN, we collected 6,854 cockles, diagnosed 390 BTN tumors, generated a reference genome and assessed genomic variation across 61 tumors. Our analyses confirmed the existence of two BTN lineages with hemocytic origins. Mitochondrial variation revealed mitochondrial capture and host co-infection events. Mutational analyses identified lineage-specific signatures, one of which likely reflects DNA alkylation. Cytogenetic and copy number analyses uncovered pervasive genomic instability, with whole-genome duplication, oncogene amplification and alkylation-repair suppression as likely drivers. Satellite DNA distributions suggested ancient clonal origins. Our study illuminates long-term cancer evolution under the sea and reveals tolerance of extreme instability in neoplastic genomes.

Eltrombopag with or without Tacrolimus for relapsed/refractory acquired aplastic anaemia: a prospective randomized trial

This trial compared eltrombopag (EPAG)+tacrolimus and EPAG monotherapy in patients with refractory/relapsed acquired aplastic anaemia (AA). Patients with refractory/relapsed AA were randomly assigned to receive either EPAG+tacrolimus or EPAG monotherapy at a ratio of 2:1. Patient response, safety, clonal evolution and survival were compared. In total, 114 patients were included in the analysis, with 76 patients receiving EPAG+tacrolimus and 38 receiving EPAG only. With a median follow-up of 18 (6-24) months, the overall response rate (ORR) for patients treated with EPAG+tacrolimus and EPAG alone was 38.2% vs. 31.6% (P = 0.490) at the 3rd month, 61.8% vs. 39.5% (P = 0.024) at the 6th month, 64.5% vs. 47.1% (P = 0.097) at the 12th month, and 60.5% vs. 34.2% (P = 0.008) at the last follow-up. The rate of each adverse event, overall survival curves (P = 0.635) and clonal evolution rate (P = 1.000) were comparable between the groups. A post hoc subgroup analysis showed that EPAG+tacrolimus could have advantage over EPAG monotherapy in terms of the ORR at the 6th month (P = 0.030)/last follow-up (P = 0.013) and the cumulative relapse-free survival (RFS) curves (P = 0.048) in patients <60 years old.

Potential value of high-throughput single-cell DNA sequencing of Juvenile myelomonocytic leukemia: report of two cases

Juvenile myelomonocytic leukemia (JMML) is a rare myeloproliferative disease of early childhood that develops due to mutations in the genes of the RAS-signaling pathway. Next-generation high throughput sequencing (NGS) enables identification of various secondary molecular genetic events that can facilitate JMML progression and transformation into secondary acute myeloid leukemia (sAML). The methods of single-cell DNA sequencing (scDNA-seq) enable overcoming limitations of bulk NGS and exploring genetic heterogeneity at the level of individual cells, which can help in a better understanding of the mechanisms leading to JMML progression and provide an opportunity to evaluate the response of leukemia to therapy. In the present work, we applied a two-step droplet microfluidics approach to detect DNA alterations among thousands of single cells and to analyze clonal dynamics in two JMML patients with sAML transformation before and after hematopoietic stem cell transplantation (HSCT). At the time of diagnosis both of our patients harbored only "canonical" mutations in the RAS signaling pathway genes detected by targeted DNA sequencing. Analysis of samples from the time of transformation JMML to sAML revealed additional genetic events that are potential drivers for disease progression in both patients. ScDNA-seq was able to measure of chimerism level and detect a residual tumor clone in the second patient after HSCT (sensitivity of less than 0.1% tumor cells). The data obtained demonstrate the value of scDNA-seq to assess the clonal evolution of JMML to sAML, response to therapy and engraftment monitoring.

cloneRate: fast estimation of single-cell clonal dynamics using coalescent theory

MOTIVATION

While evolutionary approaches to medicine show promise, measuring evolution itself is difficult due to experimental constraints and the dynamic nature of body systems. In cancer evolution, continuous observation of clonal architecture is impossible, and longitudinal samples from multiple timepoints are rare. Increasingly available DNA sequencing datasets at single-cell resolution enable the reconstruction of past evolution using mutational history, allowing for a better understanding of dynamics prior to detectable disease. There is an unmet need for an accurate, fast, and easy-to-use method to quantify clone growth dynamics from these datasets.

RESULTS

We derived methods based on coalescent theory for estimating the net growth rate of clones using either reconstructed phylogenies or the number of shared mutations. We applied and validated our analytical methods for estimating the net growth rate of clones, eliminating the need for complex simulations used in previous methods. When applied to hematopoietic data, we show that our estimates may have broad applications to improve mechanistic understanding and prognostic ability. Compared to clones with a single or unknown driver mutation, clones with multiple drivers have significantly increased growth rates (median 0.94 versus 0.25 per year; P = 1.6×10-6). Further, stratifying patients with a myeloproliferative neoplasm (MPN) by the growth rate of their fittest clone shows that higher growth rates are associated with shorter time to MPN diagnosis (median 13.9 versus 26.4 months; P = 0.0026).

AVAILABILITY AND IMPLEMENTATION

We developed a publicly available R package, cloneRate, to implement our methods (Package website: https://bdj34.github.io/cloneRate/). Source code: https://github.com/bdj34/cloneRate/.

A Leukemic Target with a Thousand Faces: The Mitochondria

In the era of personalized medicine greatly improved by molecular diagnosis and tailor-made therapies, the survival rate of acute myeloid leukemia (AML) at 5 years remains unfortunately low. Indeed, the high heterogeneity of AML clones with distinct metabolic and molecular profiles allows them to survive the chemotherapy-induced changes, thus leading to resistance, clonal evolution, and relapse. Moreover, leukemic stem cells (LSCs), the quiescent reservoir of residual disease, can persist for a long time and activate the recurrence of disease, supported by significant metabolic differences compared to AML blasts. All these points highlight the relevance to develop combination therapies, including metabolism inhibitors to improve treatment efficacy. In this review, we summarized the metabolic differences in AML blasts and LSCs, the molecular pathways related to mitochondria and metabolism are druggable and targeted in leukemia therapies, with a distinct interest for Venetoclax, which has revolutionized the therapeutic paradigms of several leukemia subtype, unfit for intensive treatment regimens.

Clonal architecture and evolutionary history of Waldenström's macroglobulinemia at the single-cell level

To provide insight into the subclonal architecture and co-dependency patterns of the alterations in Waldenström's macroglobulinemia (WM), we performed single-cell mutational and protein profiling of eight patients. A custom panel was designed to screen for mutations and copy number alterations at the single-cell level in samples taken from patients at diagnosis (n=5) or at disease progression (n=3). Results showed that in asymptomatic WM at diagnosis, MYD88L265P was the predominant clonal alteration; other events, if present, were secondary and subclonal to MYD88L265P. In symptomatic WM, clonal diversity was more evident, uncovering combinations of alterations that synergized to promote clonal expansion and dominance. At disease progression, a dominant clone was observed, sometimes accompanied by other less complex minor clones, which could be consistent with a clonal selection process. Clonal diversity was also reduced, probably due to the effect of treatment. Finally, we combined protein expression with mutational analysis to map somatic genotype with the immunophenotype. Our findings provide a comprehensive view of the clonality of tumor populations in WM and how clonal complexity can evolve and impact disease progression.

Single-cell profiling in multiple myeloma: insights, problems, and promises

In a short time, single-cell platforms have become the norm in many fields of research, including multiple myeloma (MM). In fact, the large amount of cellular heterogeneity in MM makes single-cell platforms particularly attractive because bulk assessments can miss valuable information about cellular subpopulations and cell-to-cell interactions. The decreasing cost and increasing accessibility of single-cell platform, combined with breakthroughs in obtaining multiomics data for the same cell and innovative computational programs for analyzing data, have allowed single-cell studies to make important insights into MM pathogenesis; yet, there is still much to be done. In this review, we will first focus on the types of single-cell profiling and the considerations for designing a single-cell profiling experiment. Then, we will discuss what have learned from single-cell profiling about myeloma clonal evolution, transcriptional reprogramming, and drug resistance, and about the MM microenvironment during precursor and advanced disease.

Mutations observed in somatic evolution reveal underlying gene mechanisms

Highly sensitive DNA sequencing techniques have allowed the discovery of large numbers of somatic mutations in normal tissues. Some mutations confer a competitive advantage over wild-type cells, generating expanding clones that spread through the tissue. Competition between mutant clones leads to selection. This process can be considered a large scale, in vivo screen for mutations increasing cell fitness. It follows that somatic missense mutations may offer new insights into the relationship between protein structure, function and cell fitness. We present a flexible statistical method for exploring the selection of structural features in data sets of somatic mutants. We show how this approach can evidence selection of specific structural features in key drivers in aged tissues. Finally, we show how drivers may be classified as fitness-enhancing and fitness-suppressing through different patterns of mutation enrichment. This method offers a route to understanding the mechanism of protein function through in vivo mutant selection.

Clonal evolution and stereotyped sequences of human IgE lineages in aeroallergen-specific immunotherapy

BACKGROUND

Allergic disease reflects specific inflammatory processes initiated by interaction between allergen and allergen-specific IgE. Specific immunotherapy (SIT) is an effective long-term treatment option, but the mechanisms by which SIT provides desensitization are not well understood.

OBJECTIVE

Our aim was to characterize IgE sequences expressed by allergen-specific B cells over a 3-year longitudinal study of patients with aeroallergies who were undergoing SIT.

METHODS

Allergen-specific IgE-expressing clones were identified by using combinatorial single-chain variable fragment libraries and tracked in PBMCs and nasal biopsy samples over a 3-year period with antibody gene repertoire sequencing. The characteristics of private IgE-expressing clones were compared with those of stereotyped or "public" IgE responses to the grass pollen allergen Phleum pratense (Phl p) 2.

RESULT

Members of the same allergen-specific IgE lineages were observed in nasal biopsy samples and blood, and lineages detected at baseline persisted in blood and nasal biopsy samples after 3 years of SIT, including B cells that express IgE. Evidence of progressive class switch recombination to IgG subclasses was observed after 3 years of SIT. A common stereotyped Phl p 2-specific antibody heavy chain sequence was detected in multiple donors. The amino acid residues enriched in IgE-stereotyped sequences from seropositive donors were analyzed with machine learning and k-mer motif discovery. Stereotyped IgE sequences had lower overall rates of somatic hypermutation and antigen selection than did single-chain variable fragment-derived allergen-specific sequences or IgE sequences of unknown specificity.

CONCLUSION

Longitudinal tracking of rare circulating and tissue-resident allergen-specific IgE+ clones demonstrates persistence of allergen-specific IgE+ clones, progressive class switch recombination to IgG subtypes, and distinct maturation of a stereotyped Phl p 2 clonotype.

Multiparameter flow cytometry and ClonoSEQ correlation to evaluate precursor B-lymphoblastic leukemia measurable residual disease

Measurable residual disease (MRD) detection for precursor B-lymphoblastic leukemia (B-ALL) has become the standard of care. However, the testing methodology has not been standardized. We aim to correlate COG multiparameter flow cytometry (MFC) and ClonoSEQ techniques to assess the test characteristics, to study abnormal immunophenotype for B-ALL MRD, and to observe B-ALL clonal evolution and the impact of blinatumomab therapy on MFC testing. MFC and molecular reports were retrieved from electronic medical records and data was reviewed. Included in this study were 74 bone marrow samples collected from 31 B-ALL patients at our institution between January 2021 and March 2022. COG MFC and ClonoSEQ results were concordant in 59/74 samples (80%) with positive concordant results in 12 samples (16%) and negative concordant results in 47 samples (64%). Discordant results were seen in 15/74 samples (20%), with 14 samples (19%) showing ClonoSEQ + /MFC- results and only 1 sample (1%) showing MFC + /ClonoSEQ- result. ClonoSEQ + /MFC- cases had MRD values ranging from 1 to 1400 cells/million nucleated cells with 86% of cases showing MRD values of < 100 cells/million nucleated cells. Newly identified dominant sequences were detected using ClonoSEQ in 2/31 patients (6%) during follow-up. All 14 bone marrow samples from 8 patients, who had gone through blinatumomab immunotherapy, were MRD negative by MFC, but 3 cases were MRD positive by ClonoSEQ. Our results show strong correlation between COG MFC and ClonoSEQ (r = 0.96), and both methods are complementary. Clonal evolution may occur, and blinatumomab immunotherapy may impact MFC B-ALL MRD evaluation.

Clonal hematopoiesis and bone marrow inflammation

Clonal hematopoiesis (CH) occurs in hematopoietic stem cells with increased risks of progressing to hematologic malignancies. CH mutations are predominantly found in aged populations and correlate with an increased incidence of cardiovascular and other diseases. Increased lines of evidence demonstrate that CH mutations are closely related to the inflammatory bone marrow microenvironment. In this review, we summarize the recent advances in this topic starting from the discovery of CH and its mutations. We focus on the most commonly mutated and well-studied genes in CH and their contributions to the innate immune responses and inflammatory signaling, especially in the hematopoietic cells of bone marrow. We also aimed to discuss the interrelationship between inflammatory bone marrow microenvironment and CH mutations. Finally, we provide our perspectives on the challenges in the field and possible future directions to help understand the pathophysiology of CH.

The evolution of non-small cell lung cancer metastases in TRACERx

Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse.

Reconstructing Clonal Evolution-A Systematic Evaluation of Current Bioinformatics Approaches

The accurate reconstruction of clonal evolution, including the identification of newly developing, highly aggressive subclones, is essential for the application of precision medicine in cancer treatment. Reconstruction, aiming for correct variant clustering and clonal evolution tree reconstruction, is commonly performed by tedious manual work. While there is a plethora of tools to automatically generate reconstruction, their reliability, especially reasons for unreliability, are not systematically assessed. We developed clevRsim-an approach to simulate clonal evolution data, including single-nucleotide variants as well as (overlapping) copy number variants. From this, we generated 88 data sets and performed a systematic evaluation of the tools for the reconstruction of clonal evolution. The results indicate a major negative influence of a high number of clones on both clustering and tree reconstruction. Low coverage as well as an extreme number of time points usually leads to poor clustering results. An underlying branched independent evolution hampers correct tree reconstruction. A further major decline in performance could be observed for large deletions and duplications overlapping single-nucleotide variants. In summary, to explore the full potential of reconstructing clonal evolution, improved algorithms that can properly handle the identified limitations are greatly needed.

First passage time analysis of spatial mutation patterns reveals sub-clonal evolutionary dynamics in colorectal cancer

The signature of early cancer dynamics on the spatial arrangement of tumour cells is poorly understood, and yet could encode information about how sub-clones grew within the expanding tumour. Novel methods of quantifying spatial tumour data at the cellular scale are required to link evolutionary dynamics to the resulting spatial architecture of the tumour. Here, we propose a framework using first passage times of random walks to quantify the complex spatial patterns of tumour cell population mixing. First, using a simple model of cell mixing we demonstrate how first passage time statistics can distinguish between different pattern structures. We then apply our method to simulated patterns of mutated and non-mutated tumour cell population mixing, generated using an agent-based model of expanding tumours, to explore how first passage times reflect mutant cell replicative advantage, time of emergence and strength of cell pushing. Finally, we explore applications to experimentally measured human colorectal cancer, and estimate parameters of early sub-clonal dynamics using our spatial computational model. We infer a wide range of sub-clonal dynamics, with mutant cell division rates varying between 1 and 4 times the rate of non-mutated cells across our sample set. Some mutated sub-clones emerged after as few as 100 non-mutant cell divisions, and others only after 50,000 divisions. The majority were consistent with boundary driven growth or short-range cell pushing. By analysing multiple sub-sampled regions in a small number of samples, we explore how the distribution of inferred dynamics could inform about the initial mutational event. Our results demonstrate the efficacy of first passage time analysis as a new methodology in spatial analysis of solid tumour tissue, and suggest that patterns of sub-clonal mixing can provide insights into early cancer dynamics.

Historical perspective of code clone refactorings in evolving software

Cloning in software is generally perceived as a threat to its maintenance and that is why it needs to be managed properly. Understanding clones from a historical perspective is essential for effective clone management. Analysis of code refactorings performed on clones in previous releases will help developers in taking decisions about clone refactoring in future releases. In this paper we perform a longitudinal study on the evolution of clone refactorings in various versions of five software systems. To perform a systematic study on clone refactoring evolution, we define clone evolution patterns for studying refactorings in a formal notation. Our results show that only a small proportion of code clones are refactored between the versions and most of the refactorings are inconsistent within clone classes. Moreover, clone refactorings may cause clone removal. Analysis of the source code of refactored clones reveals similar reasons of inconsistent refactorings and clone removal for five Java systems. This analysis will help in devising appropriate strategies for managing clone refactorings in software and hence provide foundation for devising better clone management tools.

Spatial epitope barcoding reveals clonal tumor patch behaviors

Intratumoral heterogeneity is a seminal feature of human tumors contributing to tumor progression and response to treatment. Current technologies are still largely unsuitable to accurately track phenotypes and clonal evolution within tumors, especially in response to genetic manipulations. Here, we developed epitopes for imaging using combinatorial tagging (EpicTags), which we coupled to multiplexed ion beam imaging (EpicMIBI) for in situ tracking of barcodes within tissue microenvironments. Using EpicMIBI, we dissected the spatial component of cell lineages and phenotypes in xenograft models of small cell lung cancer. We observed emergent properties from mixed clones leading to the preferential expansion of clonal patches for both neuroendocrine and non-neuroendocrine cancer cell states in these models. In a tumor model harboring a fraction of PTEN-deficient cancer cells, we observed a non-autonomous increase of clonal patch size in PTEN wild-type cancer cells. EpicMIBI facilitates in situ interrogation of cell-intrinsic and cell-extrinsic processes involved in intratumoral heterogeneity.

Targeted Next-Generation Sequencing Reveals Divergent Clonal Evolution in Components of Composite Pleomorphic Xanthoastrocytoma-Ganglioglioma

Composite pleomorphic xanthoastrocytoma-ganglioglioma (PXA-GG) is an extremely rare central nervous system neoplasm with 2 distinct but intermingled components. Whether this tumor represents a "collision tumor" of separate neoplasms or a monoclonal neoplasm with divergent evolution is poorly understood. Clinicopathologic studies and capture-based next generation sequencing were performed on extracted DNA from all available PXA-GG at 2 medical centers. Five PXA-GG were diagnosed in 1 male and 4 female patients ranging from 13 to 25 years in age. Four arose within the cerebral hemispheres; 1 presented in the cerebellar vermis. DNA was sufficient for analysis in 4 PXA components and 3 GG components. Four paired PXA and GG components harbored BRAF p.V600E hotspot mutations. The 4 sequenced PXA components demonstrated CDKN2A homozygous deletion by sequencing with loss of p16 (protein product of CDKN2A) expression by immunohistochemistry, which was intact in all assessed GG components. The PXA components also demonstrated more frequent copy number alterations relative to paired GG components. In one PXA-GG, shared chromosomal copy number alterations were identified in both components. Our findings support divergent evolution of the PXA and GG components from a common BRAF p.V600E-mutant precursor lesion, with additional acquisition of CDKN2A homozygous deletion in the PXA component as is typically seen in conventional PXA.

Systematic investigation of the prognostic impact of clonal status of somatic mutations across multiple cancer types

Tumors are genetically heterogeneous and many mutations are actually present in subclonal populations. The clonal status of mutations is valuable for accurate prognosis, clinical management. The aim of this study was to identify the clonal status of somatic mutations and systematically evaluate their prognostic values across various cancer types. We totally identified 227 clonal and 432 subclonal mutations contributed to prognosis and demonstrated the importance of clonal status in improving mutation-related clinical guidance. We further developed a customized multi-step approach to identify gene-specific prognostic patterns of clonal status at pan-cancer level and found some cancer-specific prognostic patterns. The 'subclonal-dependent risk' subpattern was one of the most common subpatterns, it usually accompanied by high genomic in-stability and high extent of intra-tumor heterogeneity and could be used to improve the accuracy of prognostic analysis. Our results revealed the importance of clonal status, especially subclonal mutation in clinical survival.

Gattaca: Base-Pair Resolution Mutation Tracking for Somatic Evolution Studies using Agent-based Models

Research over the past two decades has made substantial inroads into our understanding of somatic mutations. Recently, these studies have focused on understanding their presence in homeostatic tissue. In parallel, agent-based mechanistic models have emerged as an important tool for understanding somatic mutation in tissue; yet no common methodology currently exists to provide base-pair resolution data for these models. Here, we present Gattaca as the first method for introducing and tracking somatic mutations at the base-pair resolution within agent-based models that typically lack nuclei. With nuclei that incorporate human reference genomes, mutational context, and sequence coverage/error information, Gattaca is able to realistically evolve sequence data, facilitating comparisons between in silico cell tissue modeling with experimental human somatic mutation data. This user-friendly method, incorporated into each in silico cell, allows us to fully capture somatic mutation spectra and evolution.

Myeloid Sarcoma Involving the Testis in Adults: Clonal Evolution of Acute Myeloid Leukemia

To describe the clinical, histologic, immunophenotypic, and genetic characteristics of myeloid sarcoma (MS) diagnosed in the testes of adults, 3 cases were identified, and information on their presentation, clinical features, treatment, and outcome was retrieved from the medical records. In addition, histologic, immunophenotypic, and molecular characteristics were reviewed. This showed that all patients had a previous history of acute myeloid leukemia (AML), in 2 cases diagnosed >10 years before the testicular lesions. In 1 case, there was bilateral involvement, while in 2, involvement was unilateral. The neoplastic cells showed evidence of cytogenetic/molecular clonal evolution in all cases, 1 of which also had significant immunophenotypic changes. A mutational profile including NPM1 p.Trp288Cysfs*12, IDH1 p.Arg132His NRAS p.Gly12Asp was seen in 2 of the 3 cases. Concurrent bone marrow involvement by a myeloid neoplasm was diagnosed in 2 patients, in 1, there was AML in the second 8% blasts. These patients progressed rapidly after MS and had a dismal outcome. The patient with no concurrent bone marrow disease had a favorable outcome. In conclusion, MS involving the testes of adults is a rare event, and it may represent the clonal evolution of AML.

B cell receptor repertoire kinetics after SARS-CoV-2 infection and vaccination

B cells are important in immunity to both severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection and vaccination, but B cell receptor (BCR) repertoire development in these contexts has not been compared. We analyze serial samples from 171 SARS-CoV-2-infected individuals and 63 vaccine recipients and find the global BCR repertoire differs between them. Following infection, immunoglobulin (Ig)G1/3 and IgA1 BCRs increase, somatic hypermutation (SHM) decreases, and, in severe disease, IgM and IgA clones are expanded. In contrast, after vaccination, the proportion of IgD/M BCRs increase, SHM is unchanged, and expansion of IgG clones is prominent. VH1-24, which targets the N-terminal domain (NTD) and contributes to neutralization, is expanded post infection except in the most severe disease. Infection generates a broad distribution of SARS-CoV-2-specific clones predicted to target the spike protein, while a more focused response after vaccination mainly targets the spike's receptor-binding domain. Thus, the nature of SARS-CoV-2 exposure differentially affects BCR repertoire development, potentially informing vaccine strategies.

Monitoring of Dynamic Changes and Clonal Evolution in Circulating Tumor DNA From Patients With IDH-Mutated Cholangiocarcinoma Treated With Isocitrate Dehydrogenase Inhibitors

PURPOSE

IDH mutations occur in about 30% of patients with cholangiocarcinoma. Analysis of mutations in circulating tumor DNA (ctDNA) can be performed by droplet digital polymerase chain reaction (ddPCR). The analysis of ctDNA is a feasible approach to detect IDH mutations.

METHODS

We isolated ctDNA from the blood of patients with IDH-mutated advanced cholangiocarcinoma collected at baseline, on therapy, and at progression to isocitrate dehydrogenase (IDH) inhibitors.

RESULTS

Of 31 patients with IDH1R132 (n = 26) or IDH2R172 mutations (n = 5) in the tumor, IDH mutations were detected in 84% of ctDNA samples analyzed by ddPCR and in 83% of ctDNA samples analyzed by next-generation sequencing (NGS). Patients with a low variant allele frequency of ctDNA detected by NGS at baseline had a longer median time to treatment failure compared to patients with high variant allele frequency of ctDNA (3.6 v 1.5 months; P = .008). Patients with a decrease in IDH-mutated ctDNA on therapy by ddPCR compared with no change/increase had a trend to a longer median survival (P = .07). Most frequent emergent alterations in ctDNA by NGS at progression were ARID1A (n = 3) and TP53 mutations (n = 3).

CONCLUSION

Detection of IDH mutations in ctDNA in patients with advanced cholangiocarcinoma is feasible, and dynamic changes in ctDNA can correspond with the clinical course and clonal evolution.

Clonal myelopoiesis promotes adverse outcomes in chronic kidney disease

We sought to determine the relationship between age-related clonal hematopoiesis (CH) and chronic kidney disease (CKD). CH, defined as mosaic chromosome abnormalities (mCA) and/or driver mutations was identified in 5449 (2.9%) eligible UK Biobank participants (n = 190,487 median age = 58 years). CH was negatively associated with glomerular filtration rate estimated from cystatin-C (eGFR.cys; β = -0.75, P = 2.37 × 10-4), but not with eGFR estimated from creatinine, and was specifically associated with CKD defined by eGFR.cys < 60 (OR = 1.02, P = 8.44 × 10-8). In participants without prevalent myeloid neoplasms, eGFR.cys was associated with myeloid mCA (n = 148, β = -3.36, P = 0.01) and somatic driver mutations (n = 3241, β = -1.08, P = 6.25 × 10-5) associated with myeloid neoplasia (myeloid CH), specifically mutations in CBL, TET2, JAK2, PPM1D and GNB1 but not DNMT3A or ASXL1. In participants with no history of cardiovascular disease or myeloid neoplasms, myeloid CH increased the risk of adverse outcomes in CKD (HR = 1.6, P = 0.002) compared to those without myeloid CH. Mendelian randomisation analysis provided suggestive evidence for a causal relationship between CH and CKD (P = 0.03). We conclude that CH, and specifically myeloid CH, is associated with CKD defined by eGFR.cys. Myeloid CH promotes adverse outcomes in CKD, highlighting the importance of the interaction between intrinsic and extrinsic factors to define the health risk associated with CH.

Longitudinal analyses of CLL in mice identify leukemia-related clonal changes including a Myc gain predicting poor outcome in patients

Chronic lymphocytic leukemia (CLL) is a B-cell malignancy mainly occurring at an advanced age with no single major genetic driver. Transgenic expression of TCL1 in B cells leads after a long latency to a CLL-like disease in aged Eµ-TCL1 mice suggesting that TCL1 overexpression is not sufficient for full leukemic transformation. In search for secondary genetic events and to elucidate the clonal evolution of CLL, we performed whole exome and B-cell receptor sequencing of longitudinal leukemia samples of Eµ-TCL1 mice. We observed a B-cell receptor stereotypy, as described in patients, confirming that CLL is an antigen-driven disease. Deep sequencing showed that leukemia in Eµ-TCL1 mice is mostly monoclonal. Rare oligoclonality was associated with inability of tumors to develop disease upon adoptive transfer in mice. In addition, we identified clonal changes and a sequential acquisition of mutations with known relevance in CLL, which highlights the genetic similarities and therefore, suitability of the Eµ-TCL1 mouse model for progressive CLL. Among them, a recurrent gain of chromosome 15, where Myc is located, was identified in almost all tumors in Eµ-TCL1 mice. Interestingly, amplification of 8q24, the chromosomal region containing MYC in humans, was associated with worse outcome of patients with CLL.

Invasion front dynamics of interactive populations in environments with barriers

Invading populations normally comprise different subpopulations that interact while trying to overcome existing barriers against their way to occupy new areas. However, the majority of studies so far only consider single or multiple population invasion into areas where there is no resistance against the invasion. Here, we developed a model to study how cooperative/competitive populations invade in the presence of a physical barrier that should be degraded during the invasion. For one dimensional (1D) environment, we found that a Langevin equation as [Formula: see text] describing invasion front position. We then obtained how [Formula: see text] and [Formula: see text] depend on population interactions and environmental barrier intensity. In two dimensional (2D) environment, for the average interface position movements we found a Langevin equation as [Formula: see text]. Similar to the 1D case, we calculate how [Formula: see text] and [Formula: see text] respond to population interaction and environmental barrier intensity. Finally, the study of invasion front morphology through dynamic scaling analysis showed that growth exponent, [Formula: see text], depends on both population interaction and environmental barrier intensity. Saturated interface width, [Formula: see text], versus width of the 2D environment (L) also exhibits scaling behavior. Our findings show revealed that competition among subpopulations leads to more rough invasion fronts. Considering the wide range of shreds of evidence for clonal diversity in cancer cell populations, our findings suggest that interactions between such diverse populations can potentially participate in the irregularities of tumor border.

Spatial patterns of tumour growth impact clonal diversification in a computational model and the TRACERx Renal study

Genetic intra-tumour heterogeneity fuels clonal evolution, but our understanding of clinically relevant clonal dynamics remain limited. We investigated spatial and temporal features of clonal diversification in clear cell renal cell carcinoma through a combination of modelling and real tumour analysis. We observe that the mode of tumour growth, surface or volume, impacts the extent of subclonal diversification, enabling interpretation of clonal diversity in patient tumours. Specific patterns of proliferation and necrosis explain clonal expansion and emergence of parallel evolution and microdiversity in tumours. In silico time-course studies reveal the appearance of budding structures before detectable subclonal diversification. Intriguingly, we observe radiological evidence of budding structures in early-stage clear cell renal cell carcinoma, indicating that future clonal evolution may be predictable from imaging. Our findings offer a window into the temporal and spatial features of clinically relevant clonal evolution.

[Treatment strategies for multiple myeloma based on molecular pathogenesis]

It is well documented that multiple myeloma (MM) originates in a single plasma cell transformed by chromosome 14q translocations or chromosomal hyperdiploidy and evolves with the accumulation of point mutations of driver genes and/or cytogenetic abnormalities. Furthermore, disease progression is accomplished by branching patterns of subclonal evolution from reservoir clones with a propagating potential and/or the emergence of minor clones, which already exist at premalignant stages and outcompete other clones through selective pressure mainly by therapeutic agents. Each subclone harbors novel mutations and distinct phenotypes, including drug sensitivities. Generally, mature clones are highly sensitive to proteasome inhibitors (PIs), whereas immature clones are resistant to PIs although could be eradicated by immunomodulatory drugs (IMiDs). The branching evolution is a result of the fitness of different clones to the microenvironment and their evasion of immune surveillance; therefore, IMiDs are effective for MM with this pattern of evolution. In contrast, ∼20% of MM evolve neutrally in the context of strong oncogenic drivers, including high-risk IgH translocations, and are relatively resistant to IMiDs. Treatment strategies considering the genomic landscape and the pattern of clonal evolution may further improve the treatment outcome of MM.

HLA associations, somatic loss of HLA expression, and clinical outcomes in immune aplastic anemia

Immune aplastic anemia (AA) features somatic loss of HLA class I allele expression on bone marrow cells, consistent with a mechanism of escape from T-cell-mediated destruction of hematopoietic stem and progenitor cells. The clinical significance of HLA abnormalities has not been well characterized. We examined the somatic loss of HLA class I alleles and correlated HLA loss and mutation-associated HLA genotypes with clinical presentation and outcomes after immunosuppressive therapy in 544 AA patients. HLA class I allele loss was detected in 92 (22%) of the 412 patients tested, in whom there were 393 somatic HLA gene mutations and 40 instances of loss of heterozygosity. Most frequently affected was HLA-B*14:02, followed by HLA-A*02:01, HLA-B*40:02, HLA-B*08:01, and HLA-B*07:02. HLA-B*14:02, HLA-B*40:02, and HLA-B*07:02 were also overrepresented in AA. High-risk clonal evolution was correlated with HLA loss, HLA-B*14:02 genotype, and older age, which yielded a valid prediction model. In 2 patients, we traced monosomy 7 clonal evolution from preexisting clones harboring somatic mutations in HLA-A*02:01 and HLA-B*40:02. Loss of HLA-B*40:02 correlated with higher blood counts. HLA-B*07:02 and HLA-B*40:01 genotypes and their loss correlated with late-onset of AA. Our results suggest the presence of specific immune mechanisms of molecular pathogenesis with clinical implications. HLA genotyping and screening for HLA loss may be of value in the management of immune AA. This study was registered at clinicaltrials.gov as NCT00001964, NCT00061360, NCT00195624, NCT00260689, NCT00944749, NCT01193283, and NCT01623167.

Clonal architecture predicts clinical outcomes and drug sensitivity in acute myeloid leukemia

The impact of clonal heterogeneity on disease behavior or drug response in acute myeloid leukemia remains poorly understood. Using a cohort of 2,829 patients, we identify features of clonality associated with clinical features and drug sensitivities. High variant allele frequency for 7 mutations (including NRAS and TET2) associate with dismal prognosis; elevated GATA2 variant allele frequency correlates with better outcomes. Clinical features such as white blood cell count and blast percentage correlate with the subclonal abundance of mutations such as TP53 and IDH1. Furthermore, patients with cohesin mutations occurring before NPM1, or transcription factor mutations occurring before splicing factor mutations, show shorter survival. Surprisingly, a branched pattern of clonal evolution is associated with superior clinical outcomes. Finally, several mutations (including NRAS and IDH1) predict drug sensitivity based on their subclonal abundance. Together, these results demonstrate the importance of assessing clonal heterogeneity with implications for prognosis and actionable biomarkers for therapy.

Capturing cancer evolution using genetically engineered mouse models (GEMMs)

Initiating from a single cell, cancer undergoes clonal evolution, leading to a high degree of intratumor heterogeneity (ITH). The arising genetic heterogeneity between cancer cells is influenced by exogenous and endogenous forces that shape the composition of clones within tumors. Preclinical mouse models have provided a valuable tool for understanding cancer, helping to build a fundamental understanding of tumor initiation, progression, and metastasis. Until recently, genetically engineered mouse models (GEMMS) of cancer had lacked the genetic diversity found in human tumors, in which evolution may be driven by long-term carcinogen exposure and DNA damage. However, advances in sequencing technology and in our understanding of the drivers of genetic instability have given us the knowledge to generate new mouse models, offering an approach to functionally explore mechanisms of tumor evolution.

Spatial and temporal intratumour heterogeneity has potential consequences for single biopsy-based neuroblastoma treatment decisions

Intratumour heterogeneity is a major cause of treatment failure in cancer. We present in-depth analyses combining transcriptomic and genomic profiling with ultra-deep targeted sequencing of multiregional biopsies in 10 patients with neuroblastoma, a devastating childhood tumour. We observe high spatial and temporal heterogeneity in somatic mutations and somatic copy-number alterations which are reflected on the transcriptomic level. Mutations in some druggable target genes including ALK and FGFR1 are heterogeneous at diagnosis and/or relapse, raising the issue whether current target prioritization and molecular risk stratification procedures in single biopsies are sufficiently reliable for therapy decisions. The genetic heterogeneity in gene mutations and chromosome aberrations observed in deep analyses from patient courses suggest clonal evolution before treatment and under treatment pressure, and support early emergence of metastatic clones and ongoing chromosomal instability during disease evolution. We report continuous clonal evolution on mutational and copy number levels in neuroblastoma, and detail its implications for therapy selection, risk stratification and therapy resistance.

Mapping the evolution of T cell states during response and resistance to adoptive cellular therapy

To elucidate mechanisms by which T cells eliminate leukemia, we study donor lymphocyte infusion (DLI), an established immunotherapy for relapsed leukemia. We model T cell dynamics by integrating longitudinal, multimodal data from 94,517 bone marrow-derived single T cell transcriptomes in addition to chromatin accessibility and single T cell receptor sequencing from patients undergoing DLI. We find that responsive tumors are defined by enrichment of late-differentiated T cells before DLI and rapid, durable expansion of early differentiated T cells after treatment, highly similar to "terminal" and "precursor" exhausted subsets, respectively. Resistance, in contrast, is defined by heterogeneous T cell dysfunction. Surprisingly, early differentiated T cells in responders mainly originate from pre-existing and novel clonotypes recruited to the leukemic microenvironment, rather than the infusion. Our work provides a paradigm for analyzing longitudinal single-cell profiling of scenarios beyond adoptive cell therapy and introduces Symphony, a Bayesian approach to infer regulatory circuitry underlying T cell subsets, with broad relevance to exhaustion antagonists across cancers.

Multiscale heterogeneity in gastric adenocarcinoma evolution is an obstacle to precision medicine

BACKGROUND

Cancer is a somatic evolutionary disease and adenocarcinomas of the stomach and gastroesophageal junction (GC) may serve as a two-dimensional model of cancer expansion, in which tumor subclones are not evenly mixed during tumor progression but rather spatially separated and diversified. We hypothesize that precision medicine efforts are compromised when clinical decisions are based on a single-sample analysis, which ignores the mechanisms of cancer evolution and resulting intratumoral heterogeneity. Using multiregional whole-exome sequencing, we investigated the effect of somatic evolution on intratumoral heterogeneity aiming to shed light on the evolutionary biology of GC.

METHODS

The study comprised a prospective discovery cohort of 9 and a validation cohort of 463 GCs. Multiregional whole-exome sequencing was performed using samples form 45 primary tumors and 3 lymph node metastases (range 3-10 tumor samples/patient) of the discovery cohort.

RESULTS

In total, the discovery cohort harbored 16,537 non-synonymous mutations. Intratumoral heterogeneity of somatic mutations and copy number variants were present in all tumors of the discovery cohort. Of the non-synonymous mutations, 53-91% were not present in each patient's sample; 399 genes harbored 2-4 different non-synonymous mutations in the same patient; 175 genes showed copy number variations, the majority being heterogeneous, including CD274 (PD-L1). Multi-sample tree-based analyses provided evidence for branched evolution being most complex in a microsatellite instable GC. The analysis of the mode of evolution showed a high degree of heterogeneity in deviation from neutrality within each tumor. We found evidence of parallel evolution and evolutionary trajectories: different mutations of SMAD4 aligned with different subclones and were found only in TP53 mutant GCs.

CONCLUSIONS

Neutral and non-neutral somatic evolution shape the mutational landscape in GC along its lateral expansions. It leads to complex spatial intratumoral heterogeneity, where lymph node metastases may stem from different areas of the primary tumor, synchronously. Our findings may have profound effects on future patient management. They illustrate the risk of mis-interpreting tumor genetics based on single-sample analysis and open new avenues for an evolutionary classification of GC, i.e., the discovery of distinct evolutionary trajectories which can be utilized for precision medicine.