Most cancers carry a substantial deleterious load due to Hill-Robertson interference

Spontaneous single-nucleotide substitutions and microsatellite mutations have distinct distributions of fitness effects

The fitness effects of new mutations determine key properties of evolutionary processes. Beneficial mutations drive evolution, yet selection is also shaped by the frequency of small-effect deleterious mutations, whose combined effect can burden otherwise adaptive lineages and alter evolutionary trajectories and outcomes in clonally evolving organisms such as viruses, microbes, and tumors. The small effect sizes of these important mutations have made accurate measurements of their rates difficult. In microbes, assessing the effect of mutations on growth can be especially instructive, as this complex phenotype is closely linked to fitness in clonally evolving organisms. Here, we perform high-throughput time-lapse microscopy on cells from mutation-accumulation strains to precisely infer the distribution of mutational effects on growth rate in the budding yeast, Saccharomyces cerevisiae. We show that mutational effects on growth rate are overwhelmingly negative, highly skewed towards very small effect sizes, and frequent enough to suggest that deleterious hitchhikers may impose a significant burden on evolving lineages. By using lines that accumulated mutations in either wild-type or slippage repair-defective backgrounds, we further disentangle the effects of two common types of mutations, single-nucleotide substitutions and simple sequence repeat indels, and show that they have distinct effects on yeast growth rate. Although the average effect of a simple sequence repeat mutation is very small (~0.3%), many do alter growth rate, implying that this class of frequent mutations has an important evolutionary impact.

Non-hypermutator cancers access driver mutations through reversals in germline mutational bias

Cancer is an evolutionary disease driven by mutations in asexually-reproducing somatic cells. In asexual microbes, bias reversals in the mutation spectrum can speed adaptation by increasing access to previously undersampled beneficial mutations. By analyzing tumors from 20 tissues, along with normal tissue and the germline, we demonstrate this effect in cancer. Non-hypermutated tumors reverse the germline mutation bias and have consistent spectra across tissues. These spectra changes carry the signature of hypoxia, and they facilitate positive selection in cancer genes. Hypermutated and non-hypermutated tumors thus acquire driver mutations differently: hypermutated tumors by higher mutation rates and non-hypermutated tumors by changing the mutation spectrum to reverse the germline mutation bias.

Synergistic epistasis among cancer drivers can rescue early tumors from the accumulation of deleterious passengers

Epistasis among driver mutations is pervasive and explains relevant features of cancer, such as differential therapy response and convergence towards well-characterized molecular subtypes. Furthermore, a growing body of evidence suggests that tumor development could be hampered by the accumulation of slightly deleterious passenger mutations. In this work, we combined empirical epistasis networks, computer simulations, and mathematical models to explore how synergistic interactions among driver mutations affect cancer progression under the burden of slightly deleterious passengers. We found that epistasis plays a crucial role in tumor development by promoting the transformation of precancerous clones into rapidly growing tumors through a process that is analogous to evolutionary rescue. The triggering of epistasis-driven rescue is strongly dependent on the intensity of epistasis and could be a key rate-limiting step in many tumors, contributing to their unpredictability. As a result, central genes in cancer epistasis networks appear as key intervention targets for cancer therapy.

Phased genomics reveals hidden somatic mutations and provides insight into fruit development in sweet orange

Although revisiting the discoveries and implications of genetic variations using phased genomics is critical, such efforts are still lacking. Somatic mutations represent a crucial source of genetic diversity for breeding and are especially remarkable in heterozygous perennial and asexual crops. In this study, we focused on a diploid sweet orange (Citrus sinensis) and constructed a haplotype-resolved genome using high fidelity (HiFi) reads, which revealed 10.6% new sequences. Based on the phased genome, we elucidate significant genetic admixtures and haplotype differences. We developed a somatic detection strategy that reveals hidden somatic mutations overlooked in a single reference genome. We generated a phased somatic variation map by combining high-depth whole-genome sequencing (WGS) data from 87 sweet orange somatic varieties. Notably, we found twice as many somatic mutations relative to a single reference genome. Using these hidden somatic mutations, we separated sweet oranges into seven major clades and provide insight into unprecedented genetic mosaicism and strong positive selection. Furthermore, these phased genomics data indicate that genomic heterozygous variations contribute to allele-specific expression during fruit development. By integrating allelic expression differences and somatic mutations, we identified a somatic mutation that induces increases in fruit size. Applications of phased genomics will lead to powerful approaches for discovering genetic variations and uncovering their effects in highly heterozygous plants. Our data provide insight into the hidden somatic mutation landscape in the sweet orange genome, which will facilitate citrus breeding.

Paralog dispensability shapes homozygous deletion patterns in tumor genomes

Genomic instability is a hallmark of cancer, resulting in tumor genomes having large numbers of genetic aberrations, including homozygous deletions of protein coding genes. That tumor cells remain viable in the presence of such gene loss suggests high robustness to genetic perturbation. In model organisms and cancer cell lines, paralogs have been shown to contribute substantially to genetic robustness-they are generally more dispensable for growth than singletons. Here, by analyzing copy number profiles of > 10,000 tumors, we test the hypothesis that the increased dispensability of paralogs shapes tumor genome evolution. We find that genes with paralogs are more likely to be homozygously deleted and that this cannot be explained by other factors known to influence copy number variation. Furthermore, features that influence paralog dispensability in cancer cell lines correlate with paralog deletion frequency in tumors. Finally, paralogs that are broadly essential in cancer cell lines are less frequently deleted in tumors than non-essential paralogs. Overall, our results suggest that homozygous deletions of paralogs are more frequently observed in tumor genomes because paralogs are more dispensable.

Time-resolved, integrated analysis of clonally evolving genomes

Clonal genome evolution is a key feature of asexually reproducing species and human cancer development. While many studies have described the landscapes of clonal genome evolution in cancer, few determine the underlying evolutionary parameters from molecular data, and even fewer integrate theory with data. We derived theoretical results linking mutation rate, time, expansion dynamics, and biological/clinical parameters. Subsequently, we inferred time-resolved estimates of evolutionary parameters from mutation accumulation, mutational signatures and selection. We then applied this framework to predict the time of speciation of the marbled crayfish, an enigmatic, globally invasive parthenogenetic freshwater crayfish. The results predict that speciation occurred between 1986 and 1990, which is consistent with biological records. We also used our framework to analyze whole-genome sequencing datasets from primary and relapsed glioblastoma, an aggressive brain tumor. The results identified evolutionary subgroups and showed that tumor cell survival could be inferred from genomic data that was generated during the resection of the primary tumor. In conclusion, our framework allowed a time-resolved, integrated analysis of key parameters in clonally evolving genomes, and provided novel insights into the evolutionary age of marbled crayfish and the progression of glioblastoma.

Stem cell mutations, associated cancer risk, and consequences for regenerative medicine

Mutation accumulation in stem cells has been associated with cancer risk. However, the presence of numerous mutant clones in healthy tissues has raised the question of what limits cancer initiation. Here, we review recent developments in characterizing mutation accumulation in healthy tissues and compare mutation rates in stem cells during development and adult life with corresponding cancer risk. A certain level of mutagenesis within the stem cell pool might be beneficial to limit the size of malignant clones through competition. This knowledge impacts our understanding of carcinogenesis with potential consequences for the use of stem cells in regenerative medicine.

Oncogenic context shapes the fitness landscape of tumor suppression

Tumors acquire alterations in oncogenes and tumor suppressor genes in an adaptive walk through the fitness landscape of tumorigenesis. However, the interactions between oncogenes and tumor suppressor genes that shape this landscape remain poorly resolved and cannot be revealed by human cancer genomics alone. Here, we use a multiplexed, autochthonous mouse platform to model and quantify the initiation and growth of more than one hundred genotypes of lung tumors across four oncogenic contexts: KRAS G12D, KRAS G12C, BRAF V600E, and EGFR L858R. We show that the fitness landscape is rugged-the effect of tumor suppressor inactivation often switches between beneficial and deleterious depending on the oncogenic context-and shows no evidence of diminishing-returns epistasis within variants of the same oncogene. These findings argue against a simple linear signaling relationship amongst these three oncogenes and imply a critical role for off-axis signaling in determining the fitness effects of inactivating tumor suppressors.

Intra-FCY1: a novel system to identify mutations that cause protein misfolding

Protein misfolding is a common intracellular occurrence. Most mutations to coding sequences increase the propensity of the encoded protein to misfold. These misfolded molecules can have devastating effects on cells. Despite the importance of protein misfolding in human disease and protein evolution, there are fundamental questions that remain unanswered, such as, which mutations cause the most misfolding? These questions are difficult to answer partially because we lack high-throughput methods to compare the destabilizing effects of different mutations. Commonly used systems to assess the stability of mutant proteins in vivo often rely upon essential proteins as sensors, but misfolded proteins can disrupt the function of the essential protein enough to kill the cell. This makes it difficult to identify and compare mutations that cause protein misfolding using these systems. Here, we present a novel in vivo system named Intra-FCY1 that we use to identify mutations that cause misfolding of a model protein [yellow fluorescent protein (YFP)] in Saccharomyces cerevisiae. The Intra-FCY1 system utilizes two complementary fragments of the yeast cytosine deaminase Fcy1, a toxic protein, into which YFP is inserted. When YFP folds, the Fcy1 fragments associate together to reconstitute their function, conferring toxicity in media containing 5-fluorocytosine and hindering growth. But mutations that make YFP misfold abrogate Fcy1 toxicity, thus strains possessing misfolded YFP variants rise to high frequency in growth competition experiments. This makes such strains easier to study. The Intra-FCY1 system cancels localization of the protein of interest, thus can be applied to study the relative stability of mutant versions of diverse cellular proteins. Here, we confirm this method can identify novel mutations that cause misfolding, highlighting the potential for Intra-FCY1 to illuminate the relationship between protein sequence and stability.

Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors

In cancer, evolutionary forces select for clones that evade the immune system. Here we analyzed >10,000 primary tumors and 356 immune-checkpoint-treated metastases using immune dN/dS, the ratio of nonsynonymous to synonymous mutations in the immunopeptidome, to measure immune selection in cohorts and individuals. We classified tumors as immune edited when antigenic mutations were removed by negative selection and immune escaped when antigenicity was covered up by aberrant immune modulation. Only in immune-edited tumors was immune predation linked to CD8 T cell infiltration. Immune-escaped metastases experienced the best response to immunotherapy, whereas immune-edited patients did not benefit, suggesting a preexisting resistance mechanism. Similarly, in a longitudinal cohort, nivolumab treatment removes neoantigens exclusively in the immunopeptidome of nonimmune-edited patients, the group with the best overall survival response. Our work uses dN/dS to differentiate between immune-edited and immune-escaped tumors, measuring potential antigenicity and ultimately helping predict response to treatment.