Joint analysis of single-cell and bulk tissue sequencing data to infer intratumor heterogeneity

Many computational methods have been developed to discern intratumor heterogeneity (ITH) using DNA sequence data from bulk tumor samples. These methods share an assumption that two mutations arise from the same subclone if they have similar mutant allele-frequencies (MAFs), and thus it is difficult or impossible to distinguish two subclones with similar MAFs. Single-cell DNA sequencing (scDNA-seq) data can be very informative for ITH inference. However, due to the difficulty of DNA amplification, scDNA-seq data are often very noisy. A promising new study design is to collect both bulk and single-cell DNA-seq data and jointly analyze them to mitigate the limitations of each data type. To address the analytic challenges of this new study design, we propose a computational method named BaSiC (B ulk tumor a nd Si ngle C ell), to discern ITH by jointly analyzing DNA-seq data from bulk tumor and single cells. We demonstrate that BaSiC has comparable or better performance than the methods using either data type. We further evaluate BaSiC using bulk tumor and single-cell DNA-seq data from a breast cancer patient and several leukemia patients.     

Hunting down the dominating subclone of cancer stem cells as a potential new therapeutic target in multiple myeloma: An artificial intelligence perspective

The development of single-cell subclones, which can rapidly switch from dormant to dominant subclones, occur in the natural pathophysiology of multiple myeloma(MM) but is often "pressed" by the standard treatment of MM. These emerging subclones present a challenge, providing reservoirs for chemoresistant mutations. Technological advancement is required to track MM subclonal changes, as understanding MM's mechanism of evolution at the cellular level can prompt the development of new targeted ways of treating this disease. Current methods to study the evolution of subclones in MM rely on technologies capable of phenotypically and genotypically characterizing plasma cells, which include immunohistochemistry, flow cytometry, or cytogenetics. Still, all of these technologies may be limited by the sensitivity for picking up rare events. In contrast, more incisive methods such as RNA sequencing, comparative genomic hybridization, or whole-genome sequencing are not yet commonly used in clinical practice. Here we introduce the epidemiological diagnosis and prognosis of MM and review current methods for evaluating MM subclone evolution, such as minimal residual disease/multiparametric flow cytometry/next-generation sequencing, and their respective advantages and disadvantages. In addition, we propose our new single-cell method of evaluation to understand MM's mechanism of evolution at the molecular and cellular level and to prompt the development of new targeted ways of treating this disease, which has a broad prospect.     

SCYN: single cell CNV profiling method using dynamic programming

Background

All diseases containing genetic material undergo genetic evolution and give rise to heterogeneity including cancer and infection. Although these illnesses are biologically very different, the ability for phylogenetic retrodiction based on the genomic reads is common between them and thus tree-based principles and assumptions are shared. Just as the different frequencies of tumor genomic variants presupposes the existence of multiple tumor clones and provides a handle to computationally infer them, we postulate that the different variant frequencies in viral reads offers the means to infer multiple co-infecting sublineages.

Results

We present a common methodological framework to infer the phylogenomics from genomic data, be it reads of SARS-CoV-2 of multiple COVID-19 patients or bulk DNAseq of the tumor of a cancer patient. We describe the Concerti computational framework for inferring phylogenies in each of the two scenarios.To demonstrate the accuracy of the method, we reproduce some known results in both scenarios. We also make some additional discoveries.

Conclusions

Concerti successfully extracts and integrates information from multi-point samples, enabling the discovery of clinically plausible phylogenetic trees that capture the heterogeneity known to exist both spatially and temporally. These models can have direct therapeutic implications by highlighting “birth” of clones that may harbor resistance mechanisms to treatment, “death” of subclones with drug targets, and acquisition of functionally pertinent mutations in clones that may have seemed clinically irrelevant. Specifically in this paper we uncover new potential parallel mutations in the evolution of the SARS-CoV-2 virus. In the context of cancer, we identify new clones harboring resistant mutations to therapy.

     

Characterizing mutational heterogeneity in a glioblastoma patient with double recurrence

Human cancers are driven by the acquisition of somatic mutations. Separating the driving mutations from those that are random consequences of general genomic instability remains a challenge. New sequencing technology makes it possible to detect mutations that are present in only a minority of cells in a heterogeneous tumor population. We sought to leverage the power of ultra-deep sequencing to study various levels of tumor heterogeneity in the serial recurrences of a single glioblastoma multiforme patient. Our goal was to gain insight into the temporal succession of DNA base-level lesions by querying intra- and inter-tumoral cell populations in the same patient over time. We performed targeted "next-generation" sequencing on seven samples from the same patient: two foci within the primary tumor, two foci within an initial recurrence, two foci within a second recurrence, and normal blood. Our study reveals multiple levels of mutational heterogeneity. We found variable frequencies of specific EGFR, PIK3CA, PTEN, and TP53 base substitutions within individual tumor regions and across distinct regions within the same tumor. In addition, specific mutations emerge and disappear along the temporal spectrum from tumor at the time of diagnosis to second recurrence, demonstrating evolution during tumor progression. Our results shed light on the spatial and temporal complexity of brain tumors. As sequencing costs continue to decline and deep sequencing technology eventually moves into the clinic, this approach may provide guidance for treatment choices as we embark on the path to personalized cancer medicine.     

Evolutionary dynamics of two related malignant plasma cell lines

Cancer is the consequence of sequential acquisition of mutations within somatic cells. Mutations alter the relative reproductive fitness of cells, enabling the population to evolve in time as a consequence of selection. Cancer therapy itself can select for or against specific subclones. Given the large population of tumor cells, subclones inevitably emerge and their fate will depend on the evolutionary dynamics that define the interactions between such clones. Using a combination of in vitro studies and mathematical modeling, we describe the dynamic behavior of two cell lines isolated from the same patient at different time points of disease progression and show how the two clones relate to one another. We provide evidence that the two clones coexisted at the time of initial presentation. The dominant clone presented with biopsy-proven cardiac AL amyloidosis. Initial therapy selected for the second clone that expanded leading to a change in the diagnosis to multiple myeloma. The evolutionary dynamics relating the two cell lines are discussed and a hypothesis is generated in regard to the mechanism of one of the phenotypic characteristics that is shared by these two cell lines.Key words: multiple myeloma, amyloidosis, chemotherapy, clonal evolution, selection     

Integrated Analysis of Tumor Samples Sheds Light on Tumor Heterogeneity

The heterogeneity of tumor samples is a major challenge in the analysis of high-throughput profiling of tumor biopsies and cell lines. The measured aggregate signals of multigenerational progenies often represent an average of several tumor subclones with varying genomic aberrations and different gene expression levels. The goal of the present study was to integrate copy number analyses from SNP-arrays and karyotyping, gene expression profiling, and pathway analyses to detect heterogeneity, identify driver mutations, and explore possible mechanisms of tumor evolution. We showed the heterogeneity of the studied samples, characterized the global copy number alteration profiles, and identified genes whose copy number status and expression levels were aberrant. In particular, we identified a recurrent association between two BRAF^V600E and BRAF^V600K mutations and changes in DKK1 gene expression levels, which might indicate an association between the BRAF and WNT pathways. These findings show that the integrated approaches used in the present study can robustly address the challenging issue of tumor heterogeneity in high-throughput profiling.     

The origin and evolution of mutations in acute myeloid leukemia

Most mutations in cancer genomes are thought to be acquired after the initiating event, which may cause genomic instability and drive clonal evolution. However, for acute myeloid leukemia (AML), normal karyotypes are common, and genomic instability is unusual. To better understand clonal evolution in AML, we sequenced the genomes of M3-AML samples with a known initiating event (PML-RARA) versus the genomes of normal karyotype M1-AML samples and the exomes of hematopoietic stem/progenitor cells (HSPCs) from healthy people. Collectively, the data suggest that most of the mutations found in AML genomes are actually random events that occurred in HSPCs before they acquired the initiating mutation; the mutational history of that cell is "captured" as the clone expands. In many cases, only one or two additional, cooperating mutations are needed to generate the malignant founding clone. Cells from the founding clone can acquire additional cooperating mutations, yielding subclones that can contribute to disease progression and/or relapse.     

Clonal Evolution of a Case of Treatment Refractory Maxillary Sinus Carcinoma

Background

Maxillary sinus carcinoma (MSC) is a rare cancer of the head and neck region. Patients are treated with surgery, radiation therapy, and chemotherapy and the treatment regimen is based on patient’s age, general health condition, disease stage, and its extent of spread. There is very little information available on the genetics of this disease. DNA content based flow sorting of tumor cells followed by array comparative genomic hybridization allows for high definition global assessment of distinct clonal changes within tumor populations.

Methods

We applied this technique to primary and metastatic samples collected from a patient with radio- and chemotherapy refractory maxillary sinus carcinoma to gauge the progression of this disease.

Results

A clonal KIT amplicon was present in aneuploid populations sorted from the primary tumor and in divergent subclones arising in metastatic foci found in the brain, lung, and jejunum. The evolution of these subclones was associated with distinct genetic aberrations and DNA ploidies.

Conclusion

The information presented here paves the path to understanding the development and progression of this disease.     

Statistical tests for intra-tumour clonal co-occurrence and exclusivity

Tumour progression is an evolutionary process in which different clones evolve over time, leading to intra-tumour heterogeneity. Interactions between clones can affect tumour evolution and hence disease progression and treatment outcome. Intra-tumoural pairs of mutations that are overrepresented in a co-occurring or clonally exclusive fashion over a cohort of patient samples may be suggestive of a synergistic effect between the different clones carrying these mutations. We therefore developed a novel statistical testing framework, called GeneAccord, to identify such gene pairs that are altered in distinct subclones of the same tumour. We analysed our framework for calibration and power. By comparing its performance to baseline methods, we demonstrate that to control type I errors, it is essential to account for the evolutionary dependencies among clones. In applying GeneAccord to the single-cell sequencing of a cohort of 123 acute myeloid leukaemia patients, we find 1 clonally co-occurring and 8 clonally exclusive gene pairs. The clonally exclusive pairs mostly involve genes of the key signalling pathways.     

Evolutionary dynamics of two related malignant plasma cell lines

Cancer is the consequence of sequential acquisition of mutations within somatic cells. Mutations alter the relative reproductive fitness of cells, enabling the population to evolve in time as a consequence of selection. Cancer therapy itself can select for or against specific subclones. Given the large population of tumor cells, subclones inevitably emerge and their fate will depend on the evolutionary dynamics that define the interactions between such clones. Using a combination of in vitro studies and mathematical modeling, we describe the dynamic behavior of two cell lines isolated from the same patient at different time points of disease progression and show how the two clones relate to one another. We provide evidence that the two clones coexisted at the time of initial presentation. The dominant clone presented with biopsy proven cardiac AL amyloidosis. Initial therapy selected for the second clone that expanded leading to a change in the diagnosis to multiple myeloma. The evolutionary dynamics relating the two cell lines are discussed and a hypothesis is generated in regard to the mechanism of one of the phenotypic characteristics that is shared by these two cell lines.     

Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm

Tumor heterogeneity presents a challenge for inferring clonal evolution and driver gene identification. Here, we describe a method for analyzing the cancer genome at a single-cell nucleotide level. To perform our analyses, we first devised and validated a high-throughput whole-genome single-cell sequencing method using two lymphoblastoid cell line single cells. We then carried out whole-exome single-cell sequencing of 90 cells from a JAK2-negative myeloproliferative neoplasm patient. The sequencing data from 58 cells passed our quality control criteria, and these data indicated that this neoplasm represented a monoclonal evolution. We further identified essential thrombocythemia (ET)-related candidate mutations such as SESN2 and NTRK1, which may be involved in neoplasm progression. This pilot study allowed the initial characterization of the disease-related genetic architecture at the single-cell nucleotide level. Further, we established a single-cell sequencing method that opens the way for detailed analyses of a variety of tumor types, including those with high genetic complex between patients.     

Deciphering intratumor heterogeneity using cancer genome analysis

Intratumor heterogeneity within individual cancer tissues underlies the numerous phenotypes of cancer. Tumor subclones ultimately affect therapeutic outcomes due to their distinct molecular features. Drug-resistant subclones are present at a low frequency in tissues at the time of biopsy, but can also arise as a result of acquired somatic mutations. A number of different approaches have been utilized to understand the nature of intratumor heterogeneity. Clonal analysis using whole exome or genome sequencing data can help monitor subclones in the context of tumor progression. Multiregional biopsies permit the molecular characterization of subclones within tumors. Deep sequencing has also provided researchers with the ability to measure the low allele fraction variant within a small number of cells. Ultimately, single-cell sequencing will enable the identification of every minor population within a tumor microenvironment. In the clinical context, the ability to identify and monitor the subclonal architecture of a tumor is valuable for the development of precise cancer therapeutic methods.     

BK virus-transformed inbred hamster brain cells: status of viral DNA in subclones.

We have recently reported that viral DNA sequences in inbred LSH hamster brain cells transformed by the GS variant of BK virus (LSH-BR-BK) are present predominantly in a free form (Beth et al., J. Virol. 40:276-284, 1981). In this report, we confirm that the presence of viral DNA sequences in these cells is not due to virus production, since viral capsid proteins were not detected by immunoprecipitation. Furthermore, we examined the status of viral DNA in 15 subclones of this cell line and detected free and integrated viral DNA sequences in only 5 of the subclones. The other 10 subclones contained exclusively integrated viral DNA sequences, as shown by the blot hybridization of high-molecular-weight cell DNA which was uncleaved or digested with HincII, for which there are no sites in viral DNA. The arrangement of viral DNA in these clones was further analyzed by cleavage of cellular DNA with HpaII and HindIII. Mitomycin (0.03 microgram/ml) treatment of subclones containing only integrated sequences resulted in the appearance of free viral DNA sequences in some of these cells. This result supports the postulation that free viral DNA in LSH-BR-BK cells is made up of excision products of observed tandemly repeated integrated sequences. In addition to the large T- and small t-antigens, LSH-BR-BK and all of its 15 subclones contained two antigen species which were larger than large T and one species which was smaller than small t. The number of tumor antigens in the LSH- BR-BK cell line and its subclones with a large copy number in a free form was not more than in the subclones with low copy number and integrated DNA. This suggests that free viral DNA is not a template for tumor antigen production in transformed cells.     

p53 tumor suppressor gene mutations in fibroblast-like synoviocytes from erosion synovium and non-erosion synovium in rheumatoid arthritis

Abnormalities in the p53 tumor suppressor gene have been detected in rheumatoid arthritis (RA) and could contribute to the pathogenesis of chronic disease. To determine whether synoviocytes from invasive synovium in RA have an increased number of mutations compared with non-erosion synoviocytes, p53 cDNA subclones from fibroblast-like synoviocytes (FLS) derived from erosion and non-erosion sites of the same synovium were examined in patients requiring total joint replacement. Ten erosion FLS lines and nine non-erosion FLS lines were established from nine patients with RA. Exons 5-10 from 209 p53 subclones were sequenced (114 from erosion FLS, 95 from non-erosion FLS). Sixty percent of RA FLS cell lines and 8.6% of the p53 subclones isolated from FLS contained p53 mutations. No significant differences were observed between the erosion and non-erosion FLS with regard to the frequency or type of p53 mutation. The majority of the mutations were missense transition mutations, which are characteristic of oxidative damage. In addition, paired intact RA synovium and cultured FLS from the same joints were evaluated for p53 mutations. Matched synovium and cultured synoviocytes contained p53 mutations, although there was no overlap in the specific mutations identified in the paired samples. Clusters of p53 mutations in subclones were detected in some FLS, including one in codon 249, which is a well-recognized 'hot spot' associated with cancer. Our data are consistent with the hypothesis that p53 mutations are randomly induced by genotoxic exposure in small numbers of RA synoviocytes localized to erosion and non-erosion regions of RA synovium. The determining factor for invasiveness might be proximity to bone or cartilage rather than the presence of a p53 mutation.     

A new method of cryopreserving colorectal carcinoma cells for patient derived xenograft model generation

Patient derived xenograft (PDX) models provide an efficient way to study anti-tumor drug efficacy. In this respect, it is essential to study the optimal method needed to cryopreserve the starting cells obtained from tumor samples for PDX model generation. Cryopreservation of cells prior to xenografting is necessary for cross-verification of results obtained by xenografting and also for practical planning of experiments. In the present work, we studied the cryopreservation of colorectal carcinoma (CRC) cells isolated from patient tumor samples for generating their patient derived xenograft models. CRC therapeutics study is essential for early stage intervention and treatment of the disease. CRC cell lines do not ideally depict the molecular characteristics of patient CRC tumor samples. This necessitates the generation of CRC PDX models for drug discovery. We show that CRC cells isolated from patient tumor samples have comparable recovery, viability and growth with both conventional cryopreservation methods as well as Fibulas BioFlash Drive™. However, xenograft tumor formation was much more effective with Fibulas BioFlash Drive™ cryopreserved cells than with cells cryopreserved with conventional methods. Therefore, we put forward an effective way to cryopreserve primary cells obtained from patient tumor samples for PDX model generation in this study.     

The life history of 21 breast cancers

Cancer evolves dynamically as clonal expansions supersede one another driven by shifting selective pressures, mutational processes, and disrupted cancer genes. These processes mark the genome, such that a cancer's life history is encrypted in the somatic mutations present. We developed algorithms to decipher this narrative and applied them to 21 breast cancers. Mutational processes evolve across a cancer's lifespan, with many emerging late but contributing extensive genetic variation. Subclonal diversification is prominent, and most mutations are found in just a fraction of tumor cells. Every tumor has a dominant subclonal lineage, representing more than 50% of tumor cells. Minimal expansion of these subclones occurs until many hundreds to thousands of mutations have accumulated, implying the existence of long-lived, quiescent cell lineages capable of substantial proliferation upon acquisition of enabling genomic changes. Expansion of the dominant subclone to an appreciable mass may therefore represent the final rate-limiting step in a breast cancer's development, triggering diagnosis.     

Analysis of multiple basal cell carcinomas (BCCs) arising in one individual highlights genetic tumor heterogeneity and identifies novel driver mutations

Basal cell carcinoma (BCC) is the most common human cancer, especially in individuals with light skin phototypes (i.e., Fitzpatrick I-II skin type). Many affected develop multiple BCCs during their lifetime. It is not uncommon to observe elderly patients with >5 BCCs. In this study, we explored whether for patients diagnosed with multiple BCCs, analyzing the genomic mutations in one tumor could be sufficient to derive meaningful molecular/genetic conclusions regarding the other BCC tumors. Following the Genome Analysis Toolkit (GATK) best practices we have completed the study of 6 BCCs that occurred in an 83-year-old Caucasian male due to sun exposure. We have analyzed exome sequencing data of each BCC tumor and matched normal skin samples. We identified that BCCs from the same patient shared some of the key driver mutations, but they also displayed significant intertumoral heterogeneity. This finding may in part explain the different clinical progression/evolution of BCCs observed in the same patient. This work also highlights the value of characterizing multiple BCCs in one individual to identify patient-specific genetic events with a potential link to other malignancies and implications for personalized medicine.     

Cell migration patterns and ongoing somatic mutations in the progression of follicular lymphoma

Follicular lymphoma (FL) constitutes the neoplastic equivalent of germinal center B-cells. Like its physiological counterpart, FL grows in (atypical) follicular structures, the formation of which is as yet poorly understood. Recent data indicate that in early tumour stages, neoplastic FL cells home to and colonise reactive germinal centers. Laser microdissection (LMD) and micromanipulation techniques now allow for the molecular genetic analysis of single cell mutation patterns in FL. The purpose of the present study was the analysis of the sequence and order of somatic mutations in FL, i.e. the influence of the germinal center microenvironment on the clonal evolution in different grades of FL. By generating phylogenetic trees as calculated from tumour cell sequences, the clonal evolution from a putative progenitor cell was elucidated and finally, the tumour cell migration pattern in disease progression was assessed by analyzing biopsies at different time points in relapsed tumours. Four patients suffering from FL were included in the study. A primary FL grade 1 showed clustering of genetically related subclones in distinct follicles. A moderate interfollicular exchange of tumour cells was detected. Three cases of FL grade 2 were found to show decreased subclonal clustering in follicles and an increase in the interfollicular migration. Accumulations of replacement mutations in antigen binding domains (CDR) and silent mutations in non-antigen binding domains (FR), respectively, indicating antigen influence on hypermutation were only found in the case of FL grade 1. Our conclusion is that the microenvironment in germinal centers exercises influence on clonal evolution and tumour cell distribution patterns in FL. With increasing histologic grade during disease progression, a reduced intraclonal diversity and selection of subclones also occurs outside the setting of transformation to high-grade lymphoma. Antigen-dependent hypermutations were only seen in FL grade 1, while in progressed FL, random mutation patterns and a decrease of clonal diversity were found.     

Molecular Genetics of Pre-B Acute Lymphoblastic Leukemia Sister Cell Lines during Disease Progression

For many years, immortalized tumor cell lines have been used as reliable tools to understand the function of oncogenes and tumor suppressor genes. Today, we know that tumors can comprise subclones with common and with subclone-specific genetic alterations. We sequenced DNA and RNA of sequential sister cell lines obtained from patients with pre-B acute lymphoblastic leukemia at different phases of the disease. All five pairs of cell lines carry alterations that are typical for this disease: loss of tumor suppressors (CDKN2A, CDKN2B), expression of fusion genes (ETV6-RUNX1, BCR-ABL1, MEF2D-BCL9) or of genes targeted by point mutations (KRAS A146T, NRAS G12C, PAX5 R38H). MEF2D-BCL9 and PAX R38H mutations in cell lines have hitherto been undescribed, suggesting that YCUB-4 (MEF2D-BCL9), PC-53 (PAX R38H) and their sister cell lines will be useful models to elucidate the function of these genes. All aberrations mentioned above occur in both sister cell lines, demonstrating that the sisters derive from a common ancestor. However, we also found mutations that are specific for one sister cell line only, pointing to individual subclones of the primary tumor as originating cells. Our data show that sequential sister cell lines can be used to study the clonal development of tumors and to elucidate the function of common and clone-specific mutations.     

Loss and Recovery of Genetic Diversity in Adapting Populations of HIV

The evolution of drug resistance in HIV occurs by the fixation of specific, well-known, drug-resistance mutations, but the underlying population genetic processes are not well understood. By analyzing within-patient longitudinal sequence data, we make four observations that shed a light on the underlying processes and allow us to infer the short-term effective population size of the viral population in a patient. Our first observation is that the evolution of drug resistance usually occurs by the fixation of one drug-resistance mutation at a time, as opposed to several changes simultaneously. Second, we find that these fixation events are accompanied by a reduction in genetic diversity in the region surrounding the fixed drug-resistance mutation, due to the hitchhiking effect. Third, we observe that the fixation of drug-resistance mutations involves both hard and soft selective sweeps. In a hard sweep, a resistance mutation arises in a single viral particle and drives all linked mutations with it when it spreads in the viral population, which dramatically reduces genetic diversity. On the other hand, in a soft sweep, a resistance mutation occurs multiple times on different genetic backgrounds, and the reduction of diversity is weak. Using the frequency of occurrence of hard and soft sweeps we estimate the effective population size of HIV to be ( confidence interval ). This number is much lower than the actual number of infected cells, but much larger than previous population size estimates based on synonymous diversity. We propose several explanations for the observed discrepancies. Finally, our fourth observation is that genetic diversity at non-synonymous sites recovers to its pre-fixation value within 18 months, whereas diversity at synonymous sites remains depressed after this time period. These results improve our understanding of HIV evolution and have potential implications for treatment strategies.