scholarly journals Clonal status of actionable driver events and the timing of mutational processes in cancer evolution

2015 ◽  
Vol 7 (283) ◽  
pp. 283ra54-283ra54 ◽  
Author(s):  
Nicholas McGranahan ◽  
Francesco Favero ◽  
Elza C. de Bruin ◽  
Nicolai Juul Birkbak ◽  
Zoltan Szallasi ◽  
...  
Keyword(s):  
Targeted Therapy ◽  
Tumor Cells ◽  
Mitogen Activated Protein Kinase ◽  
Driver Mutations ◽  
Intratumor Heterogeneity ◽  
Tumor Evolution ◽  
Cancer Genes ◽  
Cancer Evolution ◽  
Signaling Axis ◽  
Mutational Processes

Deciphering whether actionable driver mutations are found in all or a subset of tumor cells will likely be required to improve drug development and precision medicine strategies. We analyzed nine cancer types to determine the subclonal frequencies of driver events, to time mutational processes during cancer evolution, and to identify drivers of subclonal expansions. Although mutations in known driver genes typically occurred early in cancer evolution, we also identified later subclonal “actionable” mutations, including BRAF (V600E), IDH1 (R132H), PIK3CA (E545K), EGFR (L858R), and KRAS (G12D), which may compromise the efficacy of targeted therapy approaches. More than 20% of IDH1 mutations in glioblastomas, and 15% of mutations in genes in the PI3K (phosphatidylinositol 3-kinase)–AKT–mTOR (mammalian target of rapamycin) signaling axis across all tumor types were subclonal. Mutations in the RAS–MEK (mitogen-activated protein kinase kinase) signaling axis were less likely to be subclonal than mutations in genes associated with PI3K-AKT-mTOR signaling. Analysis of late mutations revealed a link between APOBEC-mediated mutagenesis and the acquisition of subclonal driver mutations and uncovered putative cancer genes involved in subclonal expansions, including CTNNA2 and ATXN1. Our results provide a pan-cancer census of driver events within the context of intratumor heterogeneity and reveal patterns of tumor evolution across cancers. The frequent presence of subclonal driver mutations suggests the need to stratify targeted therapy response according to the proportion of tumor cells in which the driver is identified.

scholarly journals Use of signals of positive and negative selection to distinguish cancer genes and passenger genes

2020 ◽  
Author(s):  
László Bányai ◽  
Mária Trexler ◽  
Krisztina Kerekes ◽  
Orsolya Csuka ◽  
László Patthy
Keyword(s):  
Negative Selection ◽  
Cancer Genomics ◽  
Tumor Evolution ◽  
Cancer Genes ◽  
Cancer Evolution ◽  
Human Genes ◽  
Strong Negative Selection ◽  
Selection For ◽  
Inactivating Mutations

AbstractA major goal of cancer genomics is to identify all genes that play critical roles in carcinogenesis. Most approaches focused on genes that are positively selected for mutations that drive carcinogenesis and neglected the role of negative selection. Some studies have actually concluded that negative selection has no role in cancer evolution. In the present work we have re-examined the role of negative selection in tumor evolution through the analysis of the patterns of somatic mutations affecting the coding sequences of human genes. Our analyses have confirmed that tumor suppressor genes are positively selected for inactivating mutations. Oncogenes, however, were found to display signals of both negative selection for inactivating mutations and positive selection for activating mutations. Significantly, we have identified numerous human genes that show signs of strong negative selection during tumor evolution, suggesting that their functional integrity is essential for the growth and survival of tumor cells.

scholarly journals The Impact of Variant Allele Frequency in EGFR Mutated NSCLC Patients on Targeted Therapy

2021 ◽  
Vol 11 ◽  
Author(s):  
Alex Friedlaender ◽  
Petros Tsantoulis ◽  
Mathieu Chevallier ◽  
Claudio De Vito ◽  
Alfredo Addeo
Keyword(s):  
Targeted Therapy ◽  
Allele Frequency ◽  
Kinase Inhibitors ◽  
Survival Rates ◽  
Allelic Frequency ◽  
Exact Estimate ◽  
Egfr Mutations ◽  
Tumor Evolution ◽  
Cancer Evolution ◽  
The Impact

EGFR mutations represent the most common currently targetable oncogenic driver in non-small cell lung cancer. There has been tremendous progress in targeting this alteration over the course of the last decade, and third generation tyrosine kinase inhibitors offer previously unseen survival rates among these patients. Nonetheless, a better understanding is still needed, as roughly a third of patients do not respond to targeted therapy and there is an important heterogeneity among responders. Allelic frequency, or the variant EGFR allele frequency, corresponds to the fraction of sequencing reads harboring the mutation. The allelic fraction is influenced by the proportion of tumor cells in the sample, the presence of copy number alterations but also, most importantly, by the proportion of cells within the tumor that carry the mutation. Mutations that occur early in tumor evolution, often called clonal or truncal, have a higher allelic frequency than late, subclonal mutations, and are more often drivers of cancer evolution and attractive therapeutic targets. Most, but not all, EGFR mutations are clonal. Although an exact estimate of clonal proportion is hard to derive computationally, the allelic frequency is readily available to clinicians and could be a useful surrogate. We hypothesized that tumors with low allelic frequency of the EGFR mutation will respond less favorably to targeted treatment.

scholarly journals Analysis of Mutations and Dysregulated Pathways Unravels Carcinogenic Effect and Clinical Actionability of Mutational Processes

2021 ◽  
Vol 9 ◽  
Author(s):  
Zedong Jiang ◽  
Gaoming Liao ◽  
Yiran Yang ◽  
Yujia Lan ◽  
Liwen Xu ◽  
...  
Keyword(s):  
Somatic Mutations ◽  
Strand Break ◽  
Driver Mutations ◽  
Cancer Genes ◽  
Carcinogenic Effect ◽  
Cancer Subtypes ◽  
Recurrent Mutations ◽  
Clinical Benefits ◽  
Mutational Processes ◽  
Mutational Process

Somatic mutations accumulate over time in cancer cells as a consequence of mutational processes. However, the role of mutational processes in carcinogenesis remains poorly understood. Here, we infer the causal relationship between mutational processes and somatic mutations in 5,828 samples spanning 34 cancer subtypes. We found most mutational processes cause abundant recurrent mutations in cancer genes, while exceptionally ultraviolet exposure and altered activity of the error-prone polymerase bring a large number of recurrent non-driver mutations. Furthermore, some mutations are specifically induced by a certain mutational process, such as IDH1 p.R132H which is mainly caused by spontaneous deamination of 5-methylcytosine. At the pathway level, clock-like mutational processes extensively trigger mutations to dysregulate cancer signal transduction pathways. In addition, APOBEC mutational process destroys DNA double-strand break repair pathway, and bladder cancer patients with high APOBEC activity, though with homologous recombination proficient, show a significantly longer overall survival with platinum regimens. These findings help to understand how mutational processes act on the genome to promote carcinogenesis, and further, presents novel insights for cancer prevention and treatment, as our results showing, APOBEC mutagenesis and HRD synergistically contributed to the clinical benefits of platinum-based treatment.

scholarly journals Mutational likeliness and entropy help to identify driver mutations and their functional role in cancer

2018 ◽  
Author(s):  
Giorgio Mattiuz ◽  
Salvatore Di Giorgio ◽  
Lorenzo Tofani ◽  
Antonio Frandi ◽  
Francesco Donati ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Somatic Mutations ◽  
Driver Mutations ◽  
Cancer Evolution ◽  
Loss Of Function ◽  
Driver Genes ◽  
Cancer Driver ◽  
Cancer Genomes ◽  
Passenger Mutations ◽  
Mutational Processes

AbstractAlterations in cancer genomes originate from mutational processes taking place throughout oncogenesis and cancer progression. We show that likeliness and entropy are two properties of somatic mutations crucial in cancer evolution, as cancer-driver mutations stand out, with respect to both of these properties, as being distinct from the bulk of passenger mutations. Our analysis can identify novel cancer driver genes and differentiate between gain and loss of function mutations.

scholarly journals Use of signals of positive and negative selection to distinguish cancer genes and passenger genes

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
László Bányai ◽  
Maria Trexler ◽  
Krisztina Kerekes ◽  
Orsolya Csuka ◽  
László Patthy
Keyword(s):  
Negative Selection ◽  
Cancer Genomics ◽  
Tumor Evolution ◽  
Cancer Genes ◽  
Cancer Evolution ◽  
Human Genes ◽  
Strong Negative Selection ◽  
Selection For ◽  
Inactivating Mutations

A major goal of cancer genomics is to identify all genes that play critical roles in carcinogenesis. Most approaches focused on genes positively selected for mutations that drive carcinogenesis and neglected the role of negative selection. Some studies have actually concluded that negative selection has no role in cancer evolution. We have re-examined the role of negative selection in tumor evolution through the analysis of the patterns of somatic mutations affecting the coding sequences of human genes. Our analyses have confirmed that tumor suppressor genes are positively selected for inactivating mutations, oncogenes, however, were found to display signals of both negative selection for inactivating mutations and positive selection for activating mutations. Significantly, we have identified numerous human genes that show signs of strong negative selection during tumor evolution, suggesting that their functional integrity is essential for the growth and survival of tumor cells.

scholarly journals Generation of Non-Small Cell Lung Cancer Patient-Derived Xenografts to Study Intratumor Heterogeneity

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2446
Author(s):  
Zoi Kanaki ◽  
Alexandra Voutsina ◽  
Athina Markou ◽  
Ioannis S. Pateras ◽  
Konstantinos Potaris ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Tumor Cells ◽  
Cell Lung Cancer ◽  
Genetic Alterations ◽  
Small Cell ◽  
Intratumor Heterogeneity ◽  
Molecular Characteristics ◽  
Tumor Evolution ◽  
Small Cell Lung

Recent advances in sequencing technologies have allowed the in-depth molecular study of tumors, even at the single cell level. Sequencing efforts have uncovered a previously unappreciated heterogeneity among tumor cells, which has been postulated to be the driving force of tumor evolution and to facilitate recurrence, metastasis, and drug resistance. In the current study, focused on early-stage operable non-small cell lung cancer, we used tumor growth in patient-derived xenograft (PDX) models in mice as a fast-forward tumor evolution process to investigate the molecular characteristics of tumor cells that grow in mice, as well as the parameters that affect the grafting efficiency. We found that squamous cell carcinomas grafted significantly more efficiently compared with adenocarcinomas. Advanced stage, patient age and primary tumor size were positively correlated with grafting. Additionally, we isolated and characterized circulating tumor cells (CTC) from patients’ peripheral blood and found that the presence of CTCs expressing epithelial-to-mesenchymal (EMT) markers correlated with the grafting potential. Interestingly, exome sequencing of the PDX tumor identified genetic alterations in DNA repair and genome integrity genes that were under-represented in the human primary counterpart. In conclusion, through the generation of a PDX biobank of NSCLC, we identified the clinical and molecular properties of tumors that affected growth in mice.

scholarly journals Universal patterns of selection in cancer and somatic tissues

2017 ◽  
Author(s):  
Iñigo Martincorena ◽  
Keiran M. Raine ◽  
Moritz Gerstung ◽  
Kevin J. Dawson ◽  
Kerstin Haase ◽  
...  
Keyword(s):  
Positive Selection ◽  
Negative Selection ◽  
Clonal Selection ◽  
Purifying Selection ◽  
Driver Mutations ◽  
Base Substitution ◽  
List Type ◽  
Cancer Genes ◽  
Cancer Evolution ◽  
Mutation Burden

ABSTRACTCancer develops as a result of somatic mutation and clonal selection, but quantitative measures of selection in cancer evolution are lacking. We applied methods from evolutionary genomics to 7,664 human cancers across 29 tumor 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 only detected for truncating mutations in essential genes in haploid regions. This allows exome-wide enumeration of all driver 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 identify novel cancer genes and show that genes vary extensively in what proportion of mutations are drivers versus passengers.HIGHLIGHTSUnlike the germline, somatic cells evolve predominantly by positive selectionNearly all (∼99%) coding mutations are tolerated and escape negative selectionFirst exome-wide estimates of the total number of driver coding mutations per tumor1-10 coding driver mutations per tumor; half occurring outside known cancer genes

scholarly journals Chromatin accessibility of primary human cancers ties regional mutational processes with tissues of origin

2021 ◽  
Author(s):  
Oliver Ocsenas ◽  
Jüri Reimand
Keyword(s):  
Human Cancer ◽  
Replication Timing ◽  
Chromatin Accessibility ◽  
Cancer Genes ◽  
Cancer Evolution ◽  
Normal Cells ◽  
Cancer Genomes ◽  
Localized Mutagenesis ◽  
Passenger Mutations ◽  
Mutational Processes

Regional mutagenesis in cancer genomes associates with DNA replication timing (RT) and chromatin accessibility (CA) of normal cells, however human cancer epigenomes remain uncharacterized in this context. Here we model megabase-scale mutation frequencies in 2517 cancer genomes with 773 CA and RT profiles of cancers and normal cells. We find that CA profiles of matching cancers, rather than normal cells, predict regional mutagenesis and mutational signatures, indicating that most passenger mutations follow the epigenetic landscapes of transformed cells. Carcinogen-induced and unannotated signatures show the strongest associations with epigenomes. Associations with normal cells in melanomas, lymphomas and SBS1 signatures suggest earlier occurrence of mutations in cancer evolution. Frequently mutated regions unexplained by CA and RT are enriched in cancer genes and developmental pathways, reflecting contributions of localized mutagenesis and positive selection. These results underline the complex interplay of mutational processes, genome function and evolution in cancer and tissues of origin.

scholarly journals Pervasive conditional selection of driver mutations and modular epistasis networks in cancer

2022 ◽  
Author(s):  
Jaime Iranzo ◽  
George Gruenhagen ◽  
Jorge Calle-Espinosa ◽  
Eugene V. Koonin
Keyword(s):  
Cancer Genomics ◽  
Mutual Exclusion ◽  
Driver Mutations ◽  
Tumor Evolution ◽  
Cancer Genes ◽  
Cancer Subtypes ◽  
Cancer Driver ◽  
Conditional Selection ◽  
Tcga Dataset ◽  
Complex Scenario

Cancer driver mutations often display mutual exclusion or co-occurrence, underscoring the key role of epistasis in carcinogenesis. However, estimating the magnitude of epistatic interactions and their quantitative effect on tumor evolution remains a challenge. We developed a method to quantify COnditional SELection on the Excess of Nonsynonymous Substitutions (Coselens) in cancer genes. Coselens infers the number of drivers per gene in different partitions of a cancer genomics dataset using covariance-based mutation models and determines whether coding mutations in a gene affect selection for drivers in any other gene. Using Coselens, we identified 296 conditionally selected gene pairs across 16 cancer types in the TCGA dataset. Conditional selection accounts for 25-50% of driver substitutions in tumors with >2 drivers. Conditionally co-selected genes form modular networks, whose structures challenge the traditional interpretation of within-pathway mutual exclusivity and across-pathway synergy, suggesting a more complex scenario, where gene-specific across-pathway interactions shape differentiated cancer subtypes.

scholarly journals Clonal approaches to understanding the impact of mutations on hematologic disease development

Blood ◽  
2019 ◽  
Vol 133 (13) ◽  
pp. 1436-1445 ◽  
Author(s):  
Jyoti Nangalia ◽  
Emily Mitchell ◽  
Anthony R. Green
Keyword(s):  
Somatic Mutations ◽  
Clonal Selection ◽  
Single Cells ◽  
Driver Mutations ◽  
Great Promise ◽  
Tumor Evolution ◽  
Disease Development ◽  
Hematopoietic Tissue ◽  
The Impact

Abstract Interrogation of hematopoietic tissue at the clonal level has a rich history spanning over 50 years, and has provided critical insights into both normal and malignant hematopoiesis. Characterization of chromosomes identified some of the first genetic links to cancer with the discovery of chromosomal translocations in association with many hematological neoplasms. The unique accessibility of hematopoietic tissue and the ability to clonally expand hematopoietic progenitors in vitro has provided fundamental insights into the cellular hierarchy of normal hematopoiesis, as well as the functional impact of driver mutations in disease. Transplantation assays in murine models have enabled cellular assessment of the functional consequences of somatic mutations in vivo. Most recently, next-generation sequencing–based assays have shown great promise in allowing multi-“omic” characterization of single cells. Here, we review how clonal approaches have advanced our understanding of disease development, focusing on the acquisition of somatic mutations, clonal selection, driver mutation cooperation, and tumor evolution.

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