Primary Founder Mutations in the PRKDC Gene Increase Tumor Mutation Load in Colorectal Cancer

The clonal composition of a malignant tumor strongly depends on cellular dynamics influenced by the asynchronized loss of DNA repair mechanisms. Here, our aim was to identify founder mutations leading to subsequent boosts in mutation load. The overall mutation burden in 591 colorectal cancer tumors was analyzed, including the mutation status of DNA-repair genes. The number of mutations was first determined across all patients and the proportion of genes having mutation in each percentile was ranked. Early mutations in DNA repair genes preceding a mutational expansion were designated as founder mutations. Survival analysis for gene expression was performed using microarray data with available relapse-free survival. Of the 180 genes involved in DNA repair, the top five founder mutations were in PRKDC (n = 31), ATM (n = 26), POLE (n = 18), SRCAP (n = 18), and BRCA2 (n = 15). PRKDC expression was 6.4-fold higher in tumors compared to normal samples, and higher expression led to longer relapse-free survival in 1211 patients (HR = 0.72, p = 4.4 × 10−3). In an experimental setting, the mutational load resulting from UV radiation combined with inhibition of PRKDC was analyzed. Upon treatments, the mutational load exposed a significant two-fold increase. Our results suggest PRKDC as a new key gene driving tumor heterogeneity.

Genomic evidence for inbreeding depression and purging of deleterious genetic variation in Indian tigers

Increasing habitat fragmentation leads to wild populations becoming small, isolated, and threatened by inbreeding depression. However, small populations may be able to purge recessive deleterious alleles as they become expressed in homozygotes, thus reducing inbreeding depression and increasing population viability. We used whole-genome sequences from 57 tigers to estimate individual inbreeding and mutation load in a small–isolated and two large–connected populations in India. As expected, the small–isolated population had substantially higher average genomic inbreeding (FROH = 0.57) than the large–connected (FROH = 0.35 and FROH = 0.46) populations. The small–isolated population had the lowest loss-of-function mutation load, likely due to purging of highly deleterious recessive mutations. The large populations had lower missense mutation loads than the small–isolated population, but were not identical, possibly due to different demographic histories. While the number of the loss-of-function alleles in the small–isolated population was lower, these alleles were at higher frequencies and homozygosity than in the large populations. Together, our data and analyses provide evidence of 1) high mutation load, 2) purging, and 3) the highest predicted inbreeding depression, despite purging, in the small–isolated population. Frequency distributions of damaging and neutral alleles uncover genomic evidence that purifying selection has removed part of the mutation load across Indian tiger populations. These results provide genomic evidence for purifying selection in both small and large populations, but also suggest that the remaining deleterious alleles may have inbreeding-associated fitness costs. We suggest that genetic rescue from sources selected based on genome-wide differentiation could offset any possible impacts of inbreeding depression.

A Network-Centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers

One of the key concepts employed in cancer driver gene identification is that of mutual exclusivity (ME); a driver mutation is less likely to occur in case of an earlier mutation that has common functionality in the same molecular pathway. Several ME tests have been proposed recently, however the current protocols to evaluate ME tests have two main limitations. Firstly the evaluations are mostly with respect to simulated data and secondly the evaluation metrics lack a network-centric view. The latter is especially crucial as the notion of common functionality can be achieved through searching for interaction patterns in relevant networks. We propose a network-centric framework to evaluate the pairwise significances found by statistical ME tests. It has three main components. The first component consists of metrics employed in the network-centric ME evaluations. Such metrics are designed so that network knowledge and the reference set of known cancer genes are incorporated in ME evaluations under a careful definition of proper control groups. The other two components are designed as further mechanisms to avoid confounders inherent in ME detection on top of the network-centric view. To this end, our second objective is to dissect the side effects caused by mutation load artifacts where mutations driving tumor subtypes with low mutation load might be incorrectly diagnosed as mutually exclusive. Finally, as part of the third main component, the confounding issue stemming from the use of nonspecific interaction networks generated as combinations of interactions from different tissues is resolved through the creation and use of tissue-specific networks in the proposed framework. The data, the source code and useful scripts are available at: https://github.com/abu-compbio/NetCentric.

LTF Regulates the Immune Microenvironment of Prostate Cancer Through JAK/STAT3 Pathway

BackgroundThe study of the immune microenvironment in prostate cancer (PRAD) has brought new opportunities for the current traditional treatment regimens. Therefore, our goal is to develop a universal immunodiagnostic marker to improve patient survival.MethodsBioinformatics analysis: We collected 591 samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts and evaluated the abundance and distribution of immune cell members in the PRAD expression profile matrix in the mixed cell population by CIBERSORT, ESTIMATE, single-sample gene set enrichment analysis (ssGSEA), and other methods. The target genes related to PRAD immune microenvironment and tumor mutation load were obtained by overlap analysis and verified by pan-cancer analysis. Cell experiment: The cell transfection scheme was designed, and the experiment was divided into three groups: overexpressing lactoferrin (LTF) group, empty plasmid group, and control group. After obtaining cells in each group, the gene and protein expression levels of LTF and signal transduction of signal transducer and activator of transcription 3 (STAT3) and granulocyte-macrophage colony-stimulating factor (GM-CSF) in the above three groups were detected by real-time PCR and Western blot, respectively. Finally, the level of GM-CSF secretion in the three groups was detected by ELISA.ResultsMacrophages, resting mast cells, and plasma cells play an important role in PRAD immune microenvironment. In addition, high tumor mutation load [tumor mutational burden (TMB)] was positively correlated with lymph node metastasis in patients with PRAD. As the core gene of the PRAD immune microenvironment, the low expression of LTF in PRAD promotes the occurrence of immunodeficiency, PRAD, and the enrichment of the Janus kinase (JAK)/STAT3 signal pathway. Through cell experiments, it was found that the content of LTF mRNA and protein increased significantly, while the content of STAT3 and GM-CSF mRNA and protein decreased significantly in the overexpressed LTF group. The level of GM-CSF in the supernatant of cell culture was significantly decreased in the overexpression group of LTF.ConclusionThe core gene we proposed is one of the most promising biomarkers to improve the overall survival rate of PRAD and provides an important theoretical basis for the study of the mechanism of the LTF-mediated JAK/STAT3 pathway in PRAD.

Landscape of Immune-Related Markers and Potential Therapeutic Targets in Soft Tissue Sarcoma

Soft tissue sarcomas, depending on the subtype and grade, frequently recur and become metastatic after localized treatment. There is now great interest in applying immunotherapy to sarcomas to immuno-profile the different subtypes and immune monitor for prognosis. Our group previously showed that key immunotherapy target genes are present in sarcomas. Here, we extend our findings by demonstrating that sarcomas with a relatively high mutational load are likely to be more sensitive to immunotherapy compared to sarcomas with a lower mutation load. We also show that sarcomas with a higher mutation load are associated with the expression of key immune-related genes. We found that CD8+ T cells are present in sarcoma subtypes and that PD-L2 is highly expressed. These findings further define potential mechanisms behind the immunotherapy response of specific sarcoma subtypes and can be used to develop more optimal treatments in the future.

Deleterious protein-coding variants in diverse cattle breeds of the world

The domestication of wild animals has resulted in a reduction in effective population sizes, which can affect the deleterious mutation load of domesticated breeds. In addition, artificial selection contributes to the accumulation of deleterious mutations because of an increased rate of inbreeding among domesticated animals. Since founder population sizes and artificial selection differ between cattle breeds, their deleterious mutation load can vary. We investigated this question by using whole-genome data from 432 animals belonging to 54 worldwide cattle breeds. Our analysis revealed a negative correlation between genomic heterozygosity and nonsynonymous-to-silent diversity ratio, which suggests a higher proportion of single nucleotide variants (SNVs) affecting proteins in low-diversity breeds. Our results also showed that low-diversity breeds had a larger number of high-frequency (derived allele frequency (DAF) > 0.51) deleterious SNVs than high-diversity breeds. An opposite trend was observed for the low-frequency (DAF ≤ 0.51) deleterious SNVs. Overall, the number of high-frequency deleterious SNVs was larger in the genomes of taurine cattle breeds than of indicine breeds, whereas the number of low-frequency deleterious SNVs was larger in the genomes of indicine cattle than in those of taurine cattle. Furthermore, we observed significant variation in the counts of deleterious SNVs within taurine breeds. The variations in deleterious mutation load between taurine and indicine breeds could be attributed to the population sizes of the wild progenitors before domestication, whereas the variations observed within taurine breeds could be due to differences in inbreeding level, strength of artificial selection, and/or founding population size. Our findings imply that the incidence of genetic diseases can vary between cattle breeds.

Drop of Prevalence after Population Expansion: A lower prevalence for recessive disorders in a random mating population is a transient phenomenon during and after a growth phase

Despite increasing data from population-wide sequencing studies, the risk for recessive disorders in consanguineous partnerships is still heavily debated. An important aspect that has not sufficiently been investigated theoretically, is the influence of inbreeding on mutation load and incidence rates when the population sizes change. We therefore developed a model to study these dynamics for a wide range of growth and mating conditions. In the phase of population expansion and shortly afterwards, our simulations show that there is a drop of diseased individuals at the expense of an increasing mutation load for random mating, while both parameters remain almost constant in highly consanguineous partnerships. This explains the empirical observation in present times that a high degree of consanguinity is associated with an increased risk of autosomal recessive disorders. However, it also states that the higher frequency of severe recessive disorders with developmental delay in inbred populations is a transient phenomenon before a mutation-selection balance is reached again.

Genomic background selection to reduce the mutation load after random mutagenesis

Random mutagenesis is a standard procedure to increase allelic variation in a crop species, especially in countries where the use of genetically modified crops is limited due to legal constraints. The chemical mutagen EMS is used in many species to induce random mutations throughout the genome with high mutation density. The major drawback for functional analysis is a high background mutation load in a single plant that must be eliminated by subsequent backcrossing, a time and resource-intensive activity. Here, we demonstrate that genomic background selection combined with marker-assisted selection is an efficient way to select individuals with reduced background mutations within a short period. We identified BC1 plants with a significantly higher share of the recurrent parent genome, thus saving one backcross generation. Furthermore, spring rapeseed as the recurrent parent in a backcrossing program could accelerate breeding by reducing the generation cycle. Our study depicts the potential for reducing the background mutation load while accelerating the generation cycle in EMS-induced winter oilseed rape populations by integrating genomic background selection.

Multi-omics approach identifies novel age-, time- and treatment-related immunopathological signatures in MIS-C and pediatric COVID-19

Pediatric COVID-19 (pCOVID-19) is rarely severe, however a minority of SARS-CoV-2-infected children may develop MIS-C, a multisystem inflammatory syndrome with significant morbidity. In this longitudinal multi-institutional study, we used multi-omics to identify novel time- and treatment-related immunopathological signatures in children with COVID-19 (n=105) and MIS-C (n=76). pCOVID-19 was characterized by enhanced type I IFN responses, and MIS-C by type II IFN- and NF-κB dependent responses, matrisome activation, and increased levels of Spike protein. Reduced levels of IL-33 in pCOVID-19, and of CCL22 in MIS-C suggested suppression of Th2 responses. Expansion of TRBV11-2 T-cell clonotypes in MIS-C was associated with inflammation and signatures of T-cell activation, and was reversed by glucocorticoids. The association of MIS-C with the combination of HLA A*02, B*35, C*04 alleles suggests genetic susceptibility. MIS-C B cells showed higher mutation load. Use of IVIG was identified as a confounding factor in the interpretation of autoantibody levels.