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Cancer development is a dynamic process during which the successive accumulation of mutations results in cells with increasingly malignant characteristics. Here, we show the clonal evolution pattern in myelodysplastic syndrome (MDS) patients receiving supportive care, with or without lenalidomide (follow-up 2.5-11 years). Whole-exome and targeted deep sequencing at multiple time points during the disease course reveals that both linear and branched evolutionary patterns occur with and without disease-modifying treatment. The application of disease-modifying therapy may create an evolutionary bottleneck after which more complex MDS, but also unrelated clones of haematopoietic cells, may emerge. In addition, subclones that acquired an additional mutation associated with treatment resistance (TP53) or disease progression (NRAS, KRAS) may be detected months before clinical changes become apparent. Monitoring the genetic landscape during the disease may help to guide treatment decisions.
A thorough analysis of clonal evolution commonly requires integration of diverse sources of data (e.g., karyotyping, next-generation sequencing, and clinical information). Subsequent to actual reconstruction of clonal evolution, detailed analysis and interpretation of the results are essential. Often, however, only few tumor samples per patient are available. Thus, information on clonal development and therapy effect may be incomplete. Furthermore, analysis of biallelic events-considered of high relevance with respect to disease course-can commonly only be realized by time-consuming analysis of the raw results and even raw sequencing data.
Therapy-related myeloid neoplasms (t-MN) may occur as a late effect of cytotoxic therapy for a primary malignancy or autoimmune diseases in susceptible individuals. We studied the development of somatic mutations in t-MN, using a collection of follow-up samples from 14 patients with a primary hematologic malignancy, who developed a secondary leukemia (13 t-MN and 1 t-acute lymphoblastic leukemia), at a median latency of 73 months (range 18-108) from primary cancer diagnosis.Using Sanger and next generation sequencing (NGS) approaches we identified 8 mutations (IDH1 R132H, ASXL1 Y591*, ASXL1 S689*, ASXL1 R693*, SRSF2 P95H, SF3B1 K700E, SETBP1 G870R and TP53 Y220C) in seven of thirteen t-MN patients (54%), whereas the t-ALL patient had a t(4,11) translocation, resulting in the KMT2A/AFF1 fusion gene. These mutations were then tracked backwards in marrow samples preceding secondary leukemia occurrence, using pyrosequencing and a NGS protocol that allows the detection of low variant allele frequencies (≥0.1%).Somatic mutations were detectable in the BM harvested at the primary diagnosis, prior to any cytotoxic treatment in three patients, while they were not detectable and apparently acquired by the t-MN clone in five patients.These data show that clonal evolution in t-MN is heterogeneous, with some somatic mutations preceding cytotoxic treatment and possibly favoring leukemic development.
Germinal centers (GCs) are the primary sites of clonal B cell expansion and affinity maturation, directing the production of high-affinity antibodies. This response is a central driver of pathogenesis in autoimmune diseases, such as systemic lupus erythematosus (SLE), but the natural history of autoreactive GCs remains unclear. Here, we present a novel mouse model where the presence of a single autoreactive B cell clone drives the TLR7-dependent activation, expansion, and differentiation of other autoreactive B cells in spontaneous GCs. Once tolerance was broken for one self-antigen, autoreactive GCs generated B cells targeting other self-antigens. GCs became independent of the initial clone and evolved toward dominance of individual clonal lineages, indicating affinity maturation. This process produced serum autoantibodies to a breadth of self-antigens, leading to antibody deposition in the kidneys. Our data provide insight into the maturation of the self-reactive B cell response, contextualizing the epitope spreading observed in autoimmune disease.
Cancer is considered an outcome of decades-long clonal evolution fueled by acquisition of somatic genomic abnormalities (SGAs). Non-steroidal anti-inflammatory drugs (NSAIDs) have been shown to reduce cancer risk, including risk of progression from Barrett's esophagus (BE) to esophageal adenocarcinoma (EA). However, the cancer chemopreventive mechanisms of NSAIDs are not fully understood. We hypothesized that NSAIDs modulate clonal evolution by reducing SGA acquisition rate. We evaluated thirteen individuals with BE. Eleven had not used NSAIDs for 6.2±3.5 (mean±standard deviation) years and then began using NSAIDs for 5.6±2.7 years, whereas two had used NSAIDs for 3.3±1.4 years and then discontinued use for 7.9±0.7 years. 161 BE biopsies, collected at 5-8 time points over 6.4-19 years, were analyzed using 1Million-SNP arrays to detect SGAs. Even in the earliest biopsies there were many SGAs (284±246 in 10/13 and 1442±560 in 3/13 individuals) and in most individuals the number of SGAs changed little over time, with both increases and decreases in SGAs detected. The estimated SGA rate was 7.8 per genome per year (95% support interval [SI], 7.1-8.6) off-NSAIDs and 0.6 (95% SI 0.3-1.5) on-NSAIDs. Twelve individuals did not progress to EA. In ten we detected 279±86 SGAs affecting 53±30 Mb of the genome per biopsy per time point and in two we detected 1,463±375 SGAs affecting 180±100 Mb. In one individual who progressed to EA we detected a clone having 2,291±78 SGAs affecting 588±18 Mb of the genome at three time points in the last three of 11.4 years of follow-up. NSAIDs were associated with reduced rate of acquisition of SGAs in eleven of thirteen individuals. Barrett's cells maintained relative equilibrium level of SGAs over time with occasional punctuations by expansion of clones having massive amount of SGAs.
Astrocytomas often recur after surgical resection, but the underlying mechanism remains enigmatic. Elucidation of clonal evolution in primary and relapse tumors may provide important information on tumor progression. Here, we examined genetic factors underlying recurrence in a patient with astrocytoma initially diagnosed with World Health Organization (WHO) grade II astrocytoma, who then relapsed with glioblastoma (WHO grade IV) complicated with local anaplastic astrocytoma (WHO grade III). We performed genomic DNA sequencing and data analysis of paired tumor tissue specimens and a peripheral blood sample (control), and used expands software for subclone analysis. A germline NOTCH1 missense mutation was identified in the peripheral blood sample, the primary tumor and the relapse tumor; in addition, we identified a tumor protein p53 (TP53) heterozygous nonsense mutation in the primary tumor and a TP53 homozygous nonsense mutation and an IDH1 heterozygous missense mutation in the relapse tumor. Clonal evolution trees indicated higher heterogeneity in the relapse tumor. Although germline mutations might contribute to the driving force of the primary tumor, aggressive chemotherapy and radiation may apply selective pressure for tumor clonal evolution; furthermore, a total loss of function of gatekeeping genes (TP53) may result in impaired DNA repair and catastrophic chromosomal aberrations.
Tumors frequently arise as a result of an acquired genomic instability and the subsequent evolution of neoplastic populations with variable genomes. A barrier to the study of the somatic genetics of human solid tumors in vivo is the presence of admixtures of non-neoplastic cells with normal genomes in patient samples. These can obscure the presence of somatic aberrations including mutations, homozygous deletions, and breakpoints in biopsies of interest. Furthermore, clinical samples frequently contain multiple neoplastic populations that cannot be distinguished by morphology. Consequently, it is difficult to determine whether mutations detected in a sample of interest are concurrent in a single clonal population or if they occur in distinct cell populations in the same sample. The advent of targeted therapies increases the selection for preexisting populations. However the asymmetric distribution of therapeutic targets in clonal populations provides a mechanism for the rapid evolution of resistant disease. Thus, there is a need to not only isolate tumor from normal cells, but to also enrich distinct populations of clonal neoplastic cells in order to apply genome technologies to identify clinically relevant genomic aberrations that drive disease in patients in vivo. To address this we have applied single and multiparameter DNA content based flow assays to the study of solid tumors. Our work has identified examples of clonal resistance to effective therapies. This includes androgen withdrawal in advanced prostate cancer. In addition we demonstrate examples of co-existing clonal populations with highly aberrant genomes and ploidies in a wide variety of solid tumors. We propose that clonal analysis of tumors, based on flow cytometry and high resolution genome analyses of purified neoplastic populations, provides a unique approach to the study of therapeutic responses and the evolution of resistance.
We discuss the molecular evolution of gliosarcoma, a mesenchymal type of glioblastoma (GBM), using the case of a 37-yr-old woman who developed two recurrences and an extracranial metastasis. She was initially diagnosed with isocitrate dehydrogenase (IDH) wild-type gliosarcoma in the frontal lobe and treated with surgery followed by concurrent radiotherapy with temozolomide. Five months later the tumor recurred in the left frontal lobe, outside the initially resected area, and was treated with further surgery and radiotherapy. Six months later the patient developed a second left frontal recurrence and was again treated with surgery and radiotherapy. Six weeks later, further recurrence was observed in the brain and bone, and biopsy confirmed metastases in the pelvic bones. To understand the clonal relationships between the four tumor instances and the origin of metastasis, we performed whole-genome sequencing of the intracranial tumors and the tumor located in the right iliac bone. We compared their mutational and copy-number profiles and inferred the clonal phylogeny. The tumors harbored shared alterations in GBM driver genes, including mutations in TP53, NF1, and RB1, and CDKN2A deletion. Whole-genome doubling was identified in the first recurrence and the extracranial metastasis. Comparisons of the metastatic to intracranial tumors highlighted a high similarity in molecular profile but contrasting evidence regarding the origin of the metastasis. Subclonal reconstruction suggested a parallel evolution of the recurrent tumors, and that the metastatic tumor was largely derived from the first recurrence. We conclude that metastasis in glioma can be a late event in tumorigenesis.
Colorectal cancer (CRC) is the third most frequently diagnosed cancer worldwide, where ~50% of patients develop metastasis, despite current improved management. Genomic characterisation of metastatic CRC, and elucidating the effects of therapy on the metastatic process, are essential to help guide precision medicine. Multi-region whole-exome sequencing was performed on 191 sampled tumour regions of patient-matched therapy-naïve and treated CRC primary tumours (n = 92 tumour regions) and metastases (n = 99 tumour regions), in 30 patients. Somatic variants were analysed to define the origin, composition, and timing of seeding in the metastatic progression of therapy-naïve and treated metastatic CRC. High concordance, with few genomic differences, was observed between primary CRC and metastases. Most cases supported a late dissemination model, via either monoclonal or polyclonal seeding. Polyclonal seeding appeared more common in therapy-naïve metastases than in treated metastases. Whereby, treatment prompted for the selection of distinct resistant clones, through monoclonal seeding to distant metastatic sites. Overall, this study reinforces the importance of early clinical detection and surgical excision of the CRC tumour, whilst further highlighting the clinical challenges for metastatic CRC with increased intratumour heterogeneity (either due to early dissemination or polyclonal metastatic spread) and the underlying risk of future therapeutic resistance in treated patients.
The transmissible agent causing canine transmissible venereal tumor (CTVT) is thought to be the tumor cell itself. To test this hypothesis, we analyzed genetic markers including major histocompatibility (MHC) genes, microsatellites, and mitochondrial DNA (mtDNA) in naturally occurring tumors and matched blood samples. In each case, the tumor is genetically distinct from its host. Moreover, tumors collected from 40 dogs in 5 continents are derived from a single neoplastic clone that has diverged into two subclades. Phylogenetic analyses indicate that CTVT most likely originated from a wolf or an East Asian breed of dog between 200 and 2500 years ago. Although CTVT is highly aneuploid, it has a remarkably stable genotype. During progressive growth, CTVT downmodulates MHC antigen expression. Our findings have implications for understanding genome instability in cancer, natural transplantation of allografts, and the capacity of a somatic cell to evolve into a transmissible parasite.
Clonal evolution of a tumor ecosystem depends on different selection pressures that are principally immune and treatment mediated. We integrate RNA-seq, DNA sequencing, TCR-seq and SNP array data across multiple regions of liver cancer specimens to map spatio-temporal interactions between cancer and immune cells. We investigate how these interactions reflect intra-tumor heterogeneity (ITH) by correlating regional neo-epitope and viral antigen burden with the regional adaptive immune response. Regional expression of passenger mutations dominantly recruits adaptive responses as opposed to hepatitis B virus and cancer-testis antigens. We detect different clonal expansion of the adaptive immune system in distant regions of the same tumor. An ITH-based gene signature improves single-biopsy patient survival predictions and an expression survey of 38,553 single cells across 7 regions of 2 patients further reveals heterogeneity in liver cancer. These data quantify transcriptomic ITH and how the different components of the HCC ecosystem interact during cancer evolution.
Activating signaling mutations are common in acute leukemia with KMT2A (previously MLL) rearrangements (KMT2A-R). These mutations are often subclonal and their biological impact remains unclear. Using a retroviral acute myeloid mouse leukemia model, we demonstrate that FLT3 ITD , FLT3 N676K , and NRAS G12D accelerate KMT2A-MLLT3 leukemia onset. Further, also subclonal FLT3 N676K mutations accelerate disease, possibly by providing stimulatory factors. Herein, we show that one such factor, MIF, promotes survival of mouse KMT2A-MLLT3 leukemia initiating cells. We identify acquired de novo mutations in Braf, Cbl, Kras, and Ptpn11 in KMT2A-MLLT3 leukemia cells that favored clonal expansion. During clonal evolution, we observe serial genetic changes at the Kras G12D locus, consistent with a strong selective advantage of additional Kras G12D . KMT2A-MLLT3 leukemias with signaling mutations enforce Myc and Myb transcriptional modules. Our results provide new insight into the biology of KMT2A-R leukemia with subclonal signaling mutations and highlight the importance of activated signaling as a contributing driver.
Targeted cancer therapies have revolutionized treatment but their efficacies are limited by the development of resistance driven by clonal evolution within tumors. We developed "CAPTURE", a single-cell barcoding approach to comprehensively trace clonal dynamics and capture live lineage-coupled resistant cells for in-depth multi-omics analysis and functional exploration. We demonstrate that heterogeneous clones, either preexisting or emerging from drug-tolerant persister cells, dominated resistance to vemurafenib in BRAFV600E melanoma. Further integrative studies uncovered diverse resistance mechanisms. This includes a previously unrecognized and clinically relevant mechanism, chromosome 18q21 gain, which leads to vulnerability of the cells to BCL2 inhibitor. We also identified targetable common dependencies of captured resistant clones, such as oxidative phosphorylation and E2F pathways. Our study provides new therapeutic insights into overcoming therapy resistance in BRAFV600E melanoma and presents a platform for exploring clonal evolution dynamics and vulnerabilities that can be applied to study treatment resistance in other cancers.
The human papillomavirus (HPV) genome is integrated into host DNA in most HPV-positive cancers, but the consequences for chromosomal integrity are unknown. Continuous long-read sequencing of oropharyngeal cancers and cancer cell lines identified a previously undescribed form of structural variation, "heterocateny," characterized by diverse, interrelated, and repetitive patterns of concatemerized virus and host DNA segments within a cancer. Unique breakpoints shared across structural variants facilitated stepwise reconstruction of their evolution from a common molecular ancestor. This analysis revealed that virus and virus-host concatemers are unstable and, upon insertion into and excision from chromosomes, facilitate capture, amplification, and recombination of host DNA and chromosomal rearrangements. Evidence of heterocateny was detected in extrachromosomal and intrachromosomal DNA. These findings indicate that heterocateny is driven by the dynamic, aberrant replication and recombination of an oncogenic DNA virus, thereby extending known consequences of HPV integration to include promotion of intratumoral heterogeneity and clonal evolution.
The vast majority of mutations in the exome of cancer cells are passengers, which do not affect the reproductive rate of the cell. Passengers can provide important information about the evolutionary history of an individual cancer, and serve as a molecular clock. Passengers can also become targets for immunotherapy or confer resistance to treatment. We study the stochastic expansion of a population of cancer cells describing the growth of primary tumors or metastatic lesions. We first analyze the process by looking forward in time and calculate the fixation probabilities and frequencies of successive passenger mutations ordered by their time of appearance. We compute the likelihood of specific evolutionary trees, thereby informing the phylogenetic reconstruction of cancer evolution in individual patients. Next, we derive results looking backward in time: for a given subclonal mutation we estimate the number of cancer cells that were present at the time when that mutation arose. We derive exact formulas for the expected numbers of subclonal mutations of any frequency. Fitting this formula to cancer sequencing data leads to an estimate for the ratio of birth and death rates of cancer cells during the early stages of clonal expansion.
Childhood acute lymphoblastic leukemia (ALL) can often be traced to a pre-leukemic clone carrying a prenatal genetic lesion. Postnatally acquired mutations then drive clonal evolution toward overt leukemia. The enzymes RAG1-RAG2 and AID, which diversify immunoglobulin-encoding genes, are strictly segregated in developing cells during B lymphopoiesis and peripheral mature B cells, respectively. Here we identified small pre-BII cells as a natural subset with increased genetic vulnerability owing to concurrent activation of these enzymes. Consistent with epidemiological findings on childhood ALL etiology, susceptibility to genetic lesions during B lymphopoiesis at the transition from the large pre-BII cell stage to the small pre-BII cell stage was exacerbated by abnormal cytokine signaling and repetitive inflammatory stimuli. We demonstrated that AID and RAG1-RAG2 drove leukemic clonal evolution with repeated exposure to inflammatory stimuli, paralleling chronic infections in childhood.
Abnormal numerical and structural chromosome content is frequently found in human cancer. To test the role of aneuploidy in tumor initiation and progression, we generated mice with random aneuploidies by transient induction of polo-like kinase 4 (Plk4), a master regulator of centrosome number. Short-term chromosome instability (CIN) from transient Plk4 induction resulted in formation of aggressive T-cell lymphomas in mice with heterozygous inactivation of one p53 allele and accelerated tumor development in the absence of p53. Transient CIN increased the frequency of lymphoma-initiating cells with a specific karyotype profile, including trisomy of chromosomes 4, 5, 14, and 15 occurring early in tumorigenesis. Tumor development in mice with chronic CIN induced by an independent mechanism (through inactivation of the spindle assembly checkpoint) gradually trended toward a similar karyotypic profile, as determined by single-cell whole-genome DNA sequencing. Overall, we show how transient CIN generates cells with random aneuploidies from which ones that acquire a karyotype with specific chromosome gains are sufficient to drive cancer formation, and that distinct CIN mechanisms can lead to similar karyotypic cancer-causing outcomes.
Cancer results from an evolutionary process that typically yields multiple clones with varying sets of mutations within the same tumor. Accurately modeling this process is key to understanding and predicting cancer evolution. Here, we introduce clone to mutation (CloMu), a flexible and low-parameter tree generative model of cancer evolution. CloMu uses a two-layer neural network trained via reinforcement learning to determine the probability of new mutations based on the existing mutations on a clone. CloMu supports several prediction tasks, including the determination of evolutionary trajectories, tree selection, causality and interchangeability between mutations, and mutation fitness. Importantly, previous methods support only some of these tasks, and many suffer from overfitting on data sets with a large number of mutations. Using simulations, we show that CloMu either matches or outperforms current methods on a wide variety of prediction tasks. In particular, for simulated data with interchangeable mutations, current methods are unable to uncover causal relationships as effectively as CloMu. On breast cancer and leukemia cohorts, we show that CloMu determines similarities and causal relationships between mutations as well as the fitness of mutations. We validate CloMu's inferred mutation fitness values for the leukemia cohort by comparing them to clonal proportion data not used during training, showing high concordance. In summary, CloMu's low-parameter model facilitates a wide range of prediction tasks regarding cancer evolution on increasingly available cohort-level data sets.
Clonal expansion is a process in which a single organism reproduces asexually, giving rise to a diversifying population. It is pervasive in nature, from within-host pathogen evolution to emergent infectious disease outbreaks. Standard phylogenetic tools rely on full-length genomes of individual pathogens or population consensus sequences (phased genotypes).
An increasingly recognized resistance mechanism to androgen receptor (AR)-directed therapy in prostate cancer involves epithelial plasticity, in which tumor cells demonstrate low to absent AR expression and often have neuroendocrine features. The etiology and molecular basis for this 'alternative' treatment-resistant cell state remain incompletely understood. Here, by analyzing whole-exome sequencing data of metastatic biopsies from patients, we observed substantial genomic overlap between castration-resistant tumors that were histologically characterized as prostate adenocarcinomas (CRPC-Adeno) and neuroendocrine prostate cancer (CRPC-NE); analysis of biopsy samples from the same individuals over time points to a model most consistent with divergent clonal evolution. Genome-wide DNA methylation analysis revealed marked epigenetic differences between CRPC-NE tumors and CRPC-Adeno, and also designated samples of CRPC-Adeno with clinical features of AR independence as CRPC-NE, suggesting that epigenetic modifiers may play a role in the induction and/or maintenance of this treatment-resistant state. This study supports the emergence of an alternative, 'AR-indifferent' cell state through divergent clonal evolution as a mechanism of treatment resistance in advanced prostate cancer.
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