Genomic studies have provided key insights into how cancers develop, evolve, metastasize and respond to treatment. Cancers result from an interplay between mutation, selection and clonal expansions. ...In solid tumours, this Darwinian competition between subclones is also influenced by topological factors. Recent advances have made it possible to study cancers at the single cell level. These methods represent important tools to dissect cancer evolution and provide the potential to considerably change both cancer research and clinical practice. Here we discuss state-of-the-art methods for the isolation of a single cell, whole-genome and whole-transcriptome amplification of the cell's nucleic acids, as well as microarray and massively parallel sequencing analysis of such amplification products. We discuss the strengths and the limitations of the techniques, and explore single-cell methodologies for future cancer research, as well as diagnosis and treatment of the disease.
Subclonal reconstruction from bulk tumor DNA sequencing has become a pillar of cancer evolution studies, providing insight into the clonality and relative ordering of mutations and mutational ...processes. We provide an outline of the complex computational approaches used for subclonal reconstruction from single and multiple tumor samples. We identify the underlying assumptions and uncertainties in each step and suggest best practices for analysis and quality assessment. This guide provides a pragmatic resource for the growing user community of subclonal reconstruction methods.
Cancer progression is associated with genomic instability and an accumulation of gains and losses of DNA. The growing variety of tools for measuring genomic copy numbers, including various types of ...array-CGH, SNP arrays and high-throughput sequencing, calls for a coherent framework offering unified and consistent handling of single- and multi-track segmentation problems. In addition, there is a demand for highly computationally efficient segmentation algorithms, due to the emergence of very high density scans of copy number.
A comprehensive Bioconductor package for copy number analysis is presented. The package offers a unified framework for single sample, multi-sample and multi-track segmentation and is based on statistically sound penalized least squares principles. Conditional on the number of breakpoints, the estimates are optimal in the least squares sense. A novel and computationally highly efficient algorithm is proposed that utilizes vector-based operations in R. Three case studies are presented.
The R package copynumber is a software suite for segmentation of single- and multi-track copy number data using algorithms based on coherent least squares principles.
Age is the most important risk factor for cancer, as cancer incidence and mortality increase with age. However, how molecular alterations in tumours differ among patients of different age remains ...largely unexplored. Here, using data from The Cancer Genome Atlas, we comprehensively characterise genomic, transcriptomic and epigenetic alterations in relation to patients' age across cancer types. We show that tumours from older patients present an overall increase in genomic instability, somatic copy-number alterations (SCNAs) and somatic mutations. Age-associated SCNAs and mutations are identified in several cancer-driver genes across different cancer types. The largest age-related genomic differences are found in gliomas and endometrial cancer. We identify age-related global transcriptomic changes and demonstrate that these genes are in part regulated by age-associated DNA methylation changes. This study provides a comprehensive, multi-omics view of age-associated alterations in cancer and underscores age as an important factor to consider in cancer research and clinical practice.
Abstract
Ethanol is a ubiquitous environmental stressor that is toxic to all lifeforms. Here, we use the model eukaryote
Saccharomyces cerevisiae
to show that exposure to sublethal ethanol ...concentrations causes DNA replication stress and an increased mutation rate. Specifically, we find that ethanol slows down replication and affects localization of Mrc1, a conserved protein that helps stabilize the replisome. In addition, ethanol exposure also results in the recruitment of error-prone DNA polymerases to the replication fork. Interestingly, preventing this recruitment through mutagenesis of the PCNA/Pol30 polymerase clamp or deleting specific error-prone polymerases abolishes the mutagenic effect of ethanol. Taken together, this suggests that the mutagenic effect depends on a complex mechanism, where dysfunctional replication forks lead to recruitment of error-prone polymerases. Apart from providing a general mechanistic framework for the mutagenic effect of ethanol, our findings may also provide a route to better understand and prevent ethanol-associated carcinogenesis in higher eukaryotes.
Cancer arises through the accumulation of somatic mutations over time. An understanding of the sequence of events during this process should allow both earlier diagnosis and better prediction of ...cancer progression. However, the pathways of tumor evolution have not yet been comprehensively characterized. With the advent of whole genome sequencing, it is now possible to infer the evolutionary history of single tumors from the snapshot of their genome taken at diagnosis, giving new insights into the biology of tumorigenesis.
Cancer develops as a result of somatic mutation and clonal selection, but quantitative measures of selection in cancer evolution are lacking. We adapted methods from molecular evolution and applied ...them to 7,664 tumors across 29 cancer types. Unlike species evolution, positive selection outweighs negative selection during cancer development. On average, <1 coding base substitution/tumor is lost through negative selection, with purifying selection almost absent outside homozygous loss of essential genes. This allows exome-wide enumeration of all driver coding mutations, including outside known cancer genes. On average, tumors carry ∼4 coding substitutions under positive selection, ranging from <1/tumor in thyroid and testicular cancers to >10/tumor in endometrial and colorectal cancers. Half of driver substitutions occur in yet-to-be-discovered cancer genes. With increasing mutation burden, numbers of driver mutations increase, but not linearly. We systematically catalog cancer genes and show that genes vary extensively in what proportion of mutations are drivers versus passengers.
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•Unlike the germline, somatic cells evolve predominantly by positive selection•Nearly all (∼99%) coding mutations are tolerated and escape negative selection•Exome-wide estimates of the total number of driver coding mutations per tumor•Half of the coding driver mutations occur outside of known cancer genes
Adapting an evolutionary genomics approach to cancer highlights a limited impact of negative selection on cancer genomes and significant variations in the proportion of coding driver mutations per tumor among different tumor types.
Cancer is a leading cause of death worldwide and, despite new targeted therapies and immunotherapies, many patients with advanced-stage- or high-risk cancers still die, owing to metastatic disease. ...Adoptive T-cell therapy, involving the autologous or allogeneic transplant of tumour-infiltrating lymphocytes or genetically modified T cells expressing novel T-cell receptors or chimeric antigen receptors, has shown promise in the treatment of cancer patients, leading to durable responses and, in some cases, cure. Technological advances in genomics, computational biology, immunology and cell manufacturing have brought the aspiration of individualised therapies for cancer patients closer to reality. This new era of cell-based individualised therapeutics challenges the traditional standards of therapeutic interventions and provides opportunities for a paradigm shift in our approach to cancer therapy. Invited speakers at a 2020 symposium discussed three areas-cancer genomics, cancer immunology and cell-therapy manufacturing-that are essential to the effective translation of T-cell therapies in the treatment of solid malignancies. Key advances have been made in understanding genetic intratumour heterogeneity, and strategies to accurately identify neoantigens, overcome T-cell exhaustion and circumvent tumour immunosuppression after cell-therapy infusion are being developed. Advances are being made in cell-manufacturing approaches that have the potential to establish cell-therapies as credible therapeutic options. T-cell therapies face many challenges but hold great promise for improving clinical outcomes for patients with solid tumours.
Tobacco smoking increases the risk of at least 17 classes of human cancer. We analyzed somatic mutations and DNA methylation in 5243 cancers of types for which tobacco smoking confers an elevated ...risk. Smoking is associated with increased mutation burdens of multiple distinct mutational signatures, which contribute to different extents in different cancers. One of these signatures, mainly found in cancers derived from tissues directly exposed to tobacco smoke, is attributable to misreplication of DNA damage caused by tobacco carcinogens. Others likely reflect indirect activation of DNA editing by APOBEC cytidine deaminases and of an endogenous clocklike mutational process. Smoking is associated with limited differences in methylation. The results are consistent with the proposition that smoking increases cancer risk by increasing the somatic mutation load, although direct evidence for this mechanism is lacking in some smoking-related cancer types.
The Life History of 21 Breast Cancers Nik-Zainal, Serena; Van Loo, Peter; Wedge, David C. ...
Cell,
05/2012, Letnik:
149, Številka:
5
Journal Article
Recenzirano
Odprti dostop
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.
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► Genome-wide analyses of mutations emerging through time in 21 breast cancers ► Minimal expansion of subclones occurs until thousands of mutations have accumulated ► Cancer-specific signatures of point mutations and genomic instability emerge late ► ERBB2 amplification begins early but continues to evolve over long molecular time
Newly developed algorithms allow the reconstruction of the genomic history of different breast cancers, tracing the temporal evolution of each tumor and the emergence of the dominant subclones that will eventually trigger diagnosis.
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