Mitochondrial dysfunction plays critical roles in cancer development and related therapeutic response; however, exact molecular mechanisms remain unclear. Recently, alongside the discovery of mitochondrial-specific DNA methyltransferases, global and site-specific methylation of the mitochondrial genome has been described. Investigation of any functional consequences however remains unclear and debated due to insufficient evidence of the quantitative degree and frequency of mitochondrial DNA (mtDNA) methylation. This study uses WGBS to provide the first quantitative report of mtDNA methylation at single base pair resolution. The data show that mitochondrial genomes are extensively methylated predominantly at non-CpG sites. Importantly, these methylation patterns display notable differences between normal and cancer cells. Furthermore, knockdown of DNA methyltransferase enzymes resulted in a marked global reduction of mtDNA methylation levels, indicating these enzymes may be associated with the establishment and/or maintenance of mtDNA methylation. DNMT3B knockdown cells displayed a comparatively pronounced global reduction in mtDNA methylation with concomitant increases in gene expression, suggesting a potential functional link between methylation and gene expression. Together these results demonstrate reproducible, non-random methylation patterns of mtDNA and challenge the notion that mtDNA is lowly methylated. This study discusses key differences in methodology that suggest future investigations must allow for techniques that assess both CpG and non-CpG methylation.
Glioblastoma (GBM) are the most common tumors of the central nervous system and among the deadliest cancers in adults. GBM overall survival has not improved over the last decade despite optimization of therapeutic standard-of-care. While immune checkpoint inhibitors (ICI) have revolutionized cancer care, they unfortunately have little therapeutic success in GBM. Here, we elaborate on normal brain and GBM-associated immune landscapes. We describe the role of microglia and tumor-associated macrophages (TAMs) in immune suppression and highlight the impact of energy metabolism in immune evasion. We also describe the challenges and opportunities of immunotherapies in GBM and discuss new avenues based on harnessing the anti-tumor activity of myeloid cells, vaccines, chimeric antigen receptors (CAR)-T and -NK cells, oncolytic viruses, nanocarriers, and combination therapies.
Celiac disease is a chronic immune-mediated disorder with an important genetic component. To date, there are 57 independent association signals from 39 non-HLA loci, and a total of 66 candidate genes have been proposed. We aimed to scrutinize the functional implication of 45 of those genes by analyzing their expression in the disease tissue of celiac patients (at diagnosis/treatment) compared with non-celiac controls. Moreover, we investigated the SNP genotype effect in gene expression and performed coexpression analyses. Several genes showed differential expression among disease groups, most of them related to immune response. Multiple trans-eQTLs but only four cis-eQTLs were found, and surprisingly the genotype effect seems to be stimulus dependent as it differs among groups. Coexpression levels vary from higher to lower levels in active patients at diagnosis, treated patients and non-celiac controls respectively. A subset of 18 genes tightly correlated in both groups of patients but not in controls was identified. Interestingly, this subset of genes was influenced by the genotype of three SNPs. One of the SNPs, rs1018326 on chromosome two is on top of a known lincRNA whose function is not yet described, and whose expression seems to be upregulated in active disease when comparing biopsy pairs from the same individuals. Our results strongly suggest that the effects of disease-associated SNPs go far beyond the oversimplistic idea of transcriptional control at a nearby locus. Further investigations are needed to determine how each variant disrupts fine-tuning mechanisms in the genome that eventually lead to disease.
N6-methyladenosine (m6A) is the most common and abundant RNA modification. Recent studies have shown its importance in the regulation of several biological processes, including the immune response, and different approaches have been developed in order to map and quantify m6A marks. However, site specific detection of m6A methylation has been technically challenging, and existing protocols are long and tedious and often involve next-generation sequencing. Here, we describe a simple RT-QPCR based approach for the relative quantification of candidate m6A regions that takes advantage of the diminished capacity of BstI enzyme to retrotranscribe m6A residues. Using this technique, we have been able to confirm the recently described m6A methylation in the 3′UTR of SOCS1 and SOCS3 transcripts. Moreover, using the method presented here, we have also observed alterations in the relative levels of m6A in specific motifs of SOCS genes in celiac disease patients and in pancreatic β-cells exposed to inflammatory stimuli.
Lactate is a central metabolite in brain physiology but also contributes to tumor development. Glioblastoma (GB) is the most common and malignant primary brain tumor in adults, recognized by angiogenic and invasive growth, in addition to its altered metabolism. We show herein that lactate fuels GB anaplerosis by replenishing the tricarboxylic acid (TCA) cycle in absence of glucose. Lactate dehydrogenases (LDHA and LDHB), which we found spatially expressed in GB tissues, catalyze the interconversion of pyruvate and lactate. However, ablation of both LDH isoforms, but not only one, led to a reduction in tumor growth and an increase in mouse survival. Comparative transcriptomics and metabolomics revealed metabolic rewiring involving high oxidative phosphorylation (OXPHOS) in the LDHA/B KO group which sensitized tumors to cranial irradiation, thus improving mouse survival. When mice were treated with the antiepileptic drug stiripentol, which targets LDH activity, tumor growth decreased. Our findings unveil the complex metabolic network in which both LDHA and LDHB are integrated and show that the combined inhibition of LDHA and LDHB strongly sensitizes GB to therapy.
The Human Leucocyte Antigen (HLA) locus and other DNA sequence variants identified in Genome-Wide Association (GWA) studies explain around 50% of the heritability of celiac disease (CD). However, the pathogenesis of CD could be driven by other layers of genomic information independent from sequence variation, such as DNA methylation, and it is possible that allele-specific methylation explains part of the SNP associations. Since the DNA methylation landscape is expected to be different among cell types, we analyzed the methylome of the epithelial and immune cell populations of duodenal biopsies in CD patients and controls separately. We found a cell type-specific methylation signature that includes genes mapping to the HLA region, namely TAP1 and HLA-B. We also performed Immunochip SNP genotyping of the same samples and interrogated the expression of some of the affected genes. Our analysis revealed that the epithelial methylome is characterized by the loss of CpG island (CGI) boundaries, often associated to altered gene expression, and by the increased variability of the methylation across the samples. The overlap between differentially methylated positions (DMPs) and CD-associated SNPs or variants contributing to methylation quantitative trait loci (mQTLs) is minimal. In contrast, there is a notable enrichment of mQTLs among the most significant CD-associated SNPs. Our results support the notion that DNA methylation alterations constitute a genotype-independent event and confirm its role in the HLA region (apart from the well-known, DQ allele-specific effect). Finally, we find that a fraction of the CD-associated variants could exert its phenotypic effect through DNA methylation.
To identify candidate genes in celiac disease (CD), we reanalyzed the whole Immunochip CD cohort using a different approach that clusters individuals based on immunoancestry prior to disease association analysis, rather than by geographical origin. We detected 636 new associated SNPs (P<7.02 × 10) and identified 5 novel genomic regions, extended 8 others previously identified and also detected 18 isolated signals defined by one or very few significant SNPs. To test whether we could identify putative candidate genes, we performed expression analyses of several genes from the top novel region (chr2:134533564-136169524), from a previously identified locus that is now extended, and a gene marked by an isolated SNP, in duodenum biopsies of active and treated CD patients, and non-celiac controls. In the largest novel region, CCNT2 and R3HDM1 were constitutively underexpressed in disease, even after gluten removal. Moreover, several genes within this region were coexpressed in patients, but not in controls. Other novel genes like KIF21B, REL and SORD also showed altered expression in active disease. Apart from the identification of novel CD loci, these results suggest that ancestry-based stratified analysis is an efficient strategy for association studies in complex diseases.
Although the genetic contribution to colorectal cancer (CRC) has been studied in various populations, studies on the applicability of available genetic information in the Basque population are scarce. In total, 835 CRC cases and 940 controls from the Basque population were genotyped and genome-wide association studies were carried out. Mendelian Randomization analyses were used to discover the effect of modifiable risk factors and microbiota on CRC. In total, 25 polygenic risk score models were evaluated to assess their performance in CRC risk calculation. Moreover, 492 inflammatory bowel disease cases were used to assess whether that genetic information would not confuse both conditions. Five suggestive (p < 5 × 10−6) loci were associated with CRC risk, where genes previously associated with CRC were located (e.g., ABCA12, ATIC or ERBB4). Moreover, the analyses of CRC locations detected additional genes consistent with the biology of CRC. The possible contribution of cholesterol, BMI, Firmicutes and Cyanobacteria to CRC risk was detected by Mendelian Randomization. Finally, although polygenic risk score models showed variable performance, the best model performed correctly regardless of the location and did not misclassify inflammatory bowel disease cases. Our results are consistent with CRC biology and genetic risk models and could be applied to assess CRC risk in the Basque population.
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