Mutational signatures association with replication timing in normal cells reveals similarities and differences with matched cancer tissues

Neuronal somatic mutations are increased in multiple sclerosis lesions

Neuroinflammation underpins neurodegeneration and clinical progression in multiple sclerosis (MS), but knowledge of processes linking these disease mechanisms remains incomplete. Here we investigated somatic single-nucleotide variants (sSNVs) in the genomes of 106 single neurons from post-mortem brain tissue of ten MS cases and 16 controls to determine whether somatic mutagenesis is involved. We observed an increase of 43.9 sSNVs per year in neurons from chronic MS lesions, a 2.5 times faster rate than in neurons from normal-appearing MS and control tissues. This difference was equivalent to 1,291 excess sSNVs in lesion neurons at 70 years of age compared to controls. We performed mutational signature analysis to investigate mechanisms underlying neuronal sSNVs and identified a signature characteristic of lesions with a strong, age-associated contribution to sSNV counts. This research suggests that neuroinflammation is mutagenic in the MS brain, potentially contributing to disease progression.

Quantifying cell divisions along evolutionary lineages in cancer

Cell division drives somatic evolution but is challenging to quantify. We developed a framework to count cell divisions with DNA replication-related mutations in polyguanine homopolymers. Analyzing 505 samples from 37 patients, we studied the milestones of colorectal cancer evolution. Primary tumors diversify at ~250 divisions from the founder cell, while distant metastasis divergence occurs significantly later, at ~500 divisions. Notably, distant but not lymph node metastases originate from primary tumor regions that have undergone surplus divisions, tying subclonal expansion to metastatic capacity. Then, we analyzed a cohort of 73 multifocal lung cancers and showed that the cell division burden of the tumors' common ancestor distinguishes independent primary tumors from intrapulmonary metastases and correlates with patient survival. In lung cancer too, metastatic capacity is tied to more extensive proliferation. The cell division history of human cancers is easily accessible using our simple framework and contains valuable biological and clinical information.

Landscape of human protein-coding somatic mutations across tissues and individuals

Although somatic mutations are fundamentally important to human biology, disease, and aging, many outstanding questions remain about their rates, spectrum, and determinants in apparently healthy tissues. Here, we performed high-coverage exome sequencing on 265 samples from 14 GTEx donors sampled for a median of 17.5 tissues per donor (spanning 46 total tissues). Using a novel probabilistic method tailored to the unique structure of our data, we identified 8,470 somatic variants. We leverage our compendium of somatic mutations to quantify the burden of deleterious somatic variants among tissues and individuals, identify molecular features such as chromatin accessibility that exhibit significantly elevated somatic mutation rates, provide novel biological insights into mutational mechanisms, and infer developmental trajectories based on patterns of multi-tissue somatic mosaicism. Our data provides a high-resolution portrait of somatic mutations across genes, tissues, and individuals.

Replication timing alterations are associated with mutation acquisition during breast and lung cancer evolution

During each cell cycle, the process of DNA replication timing is tightly regulated to ensure the accurate duplication of the genome. The extent and significance of alterations in this process during malignant transformation have not been extensively explored. Here, we assess the impact of altered replication timing (ART) on cancer evolution by analysing replication-timing sequencing of cancer and normal cell lines and 952 whole-genome sequenced lung and breast tumours. We find that 6%-18% of the cancer genome exhibits ART, with regions with a change from early to late replication displaying an increased mutation rate and distinct mutational signatures. Whereas regions changing from late to early replication contain genes with increased expression and present a preponderance of APOBEC3-mediated mutation clusters and associated driver mutations. We demonstrate that ART occurs relatively early during cancer evolution and that ART may have a stronger correlation with mutation acquisition than alterations in chromatin structure.

Isocitrate Dehydrogenase Mutations in Cancer: Mechanisms of Transformation and Metabolic Liability

Isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) are metabolic enzymes that interconvert isocitrate and 2-oxoglutarate (2OG). Gain-of-function mutations in IDH1 and IDH2 occur in a number of cancers, including acute myeloid leukemia, glioma, cholangiocarcinoma, and chondrosarcoma. These mutations cripple the wild-type activity of IDH and cause the enzymes to catalyze a partial reverse reaction in which 2OG is reduced but not carboxylated, resulting in production of the (R)-enantiomer of 2-hydroxyglutarate ((R)-2HG). (R)-2HG accumulation in IDH-mutant tumors results in profound dysregulation of cellular metabolism. The most well-characterized oncogenic effects of (R)-2HG involve the dysregulation of 2OG-dependent epigenetic tumor-suppressor enzymes. However, (R)-2HG has many other effects in IDH-mutant cells, some that promote transformation and others that induce metabolic dependencies. Herein, we review how cancer-associated IDH mutations impact epigenetic regulation and cellular metabolism and discuss how these effects can potentially be leveraged to therapeutically target IDH-mutant tumors.

Tissue-Predisposition to Cancer Driver Mutations

Driver mutations are considered the cornerstone of cancer initiation. They are defined as mutations that convey a competitive fitness advantage, and hence, their mutation frequency in premalignant tissue is expected to exceed the basal mutation rate. In old terms, that translates to "the survival of the fittest" and implies that a selective process underlies the frequency of cancer driver mutations. In that sense, each tissue is its own niche that creates a molecular selective pressure that may favor the propagation of a mutation or not. At the heart of this stands one of the biggest riddles in cancer biology: the tissue-predisposition to cancer driver mutations. The frequency of cancer driver mutations among tissues is non-uniform: for instance, mutations in APC are particularly frequent in colorectal cancer, and 99% of chronic myeloid leukemia patients harbor the driver BCR-ABL1 fusion mutation, which is rarely found in solid tumors. Here, we provide a mechanistic framework that aims to explain how tissue-specific features, ranging from epigenetic underpinnings to the expression of viral transposable elements, establish a molecular basis for selecting cancer driver mutations in a tissue-specific manner.

ssMutPA: single-sample mutation-based pathway analysis approach for cancer precision medicine

BACKGROUND

Single-sample pathway enrichment analysis is an effective approach for identifying cancer subtypes and pathway biomarkers, facilitating the development of precision medicine. However, the existing approaches focused on investigating the changes in gene expression levels but neglected somatic mutations, which play a crucial role in cancer development.

FINDINGS

In this study, we proposed a novel single-sample mutation-based pathway analysis approach (ssMutPA) to infer individualized pathway activities by integrating somatic mutation data and the protein-protein interaction network. For each sample, ssMutPA first uses local and global weighted strategies to evaluate the effects of genes from mutations according to the network topology and then calculates a single-sample mutation-based pathway enrichment score (ssMutPES) to reflect the accumulated effect of mutations of each pathway. To illustrate the performance of ssMutPA, we applied it to 33 cancer cohorts from The Cancer Genome Atlas database and revealed patient stratification with significantly different prognosis in each cancer type based on the ssMutPES profiles. We also found that the identified characteristic pathways with high overlap across different cancers could be used as potential prognosis biomarkers. Moreover, we applied ssMutPA to 2 melanoma cohorts with immunotherapy and identified a subgroup of patients who may benefit from therapy.

CONCLUSIONS

We provided evidence that ssMutPA could infer mutation-based individualized pathway activity profiles and complement the current individualized pathway analysis approaches focused on gene expression data, which may offer the potential for the development of precision medicine. ssMutPA is available at https://CRAN.R-project.org/package=ssMutPA.

Both cell autonomous and non-autonomous processes modulate the association between replication timing and mutation rate

Cancer somatic mutations are the product of multiple mutational and repair processes, some of which are tightly associated with DNA replication. Mutation rates (MR) are known to be higher in late replication timing (RT) regions, but different processes can affect this association. Systematic analysis of the mutational landscape of 2787 tumors from 32 tumor types revealed that approximately one third of the tumor samples show weak association between replication timing and mutation rate. Further analyses revealed that those samples have unique mutational signatures and are enriched with mutations in genes involved in DNA replication, DNA repair and chromatin structure. Surprisingly, analysis of differentially expressed genes between weak and strong RT-MR association groups revealed that tumors with weak association are enriched with genes associated with cell-cell communication and the immune system, suggesting a non-autonomous response to DNA damage.