A pilot study to troubleshoot quality control metrics when assessing circulating miRNA expression data reproducibility across study sites.

BACKGROUND: Given the growing interest in using microRNAs (miRNAs) as biomarkers of early disease, establishment of robust protocols and platforms for miRNA quantification in biological fluids is critical. OBJECTIVE: The goal of this multi-center pilot study was to evaluate the reproducibility of NanoString nCounter™ technology when analyzing the abundance of miRNAs in plasma and cystic fluid from patients with pancreatic lesions. METHODS: Using sample triplicates analyzed across three study sites, we assessed potential sources of variability (RNA isolation, sample processing/ligation, hybridization, and lot-to-lot variability) that may contribute to suboptimal reproducibility of miRNA abundance when using nCounter™, and evaluated expression of positive and negative controls, housekeeping genes, spike-in genes, and miRNAs. RESULTS: Positive controls showed a high correlation across samples from each site (median correlation coefficient, r> 0.9). Most negative control probes had expression levels below background. Housekeeping and spike-in genes each showed a similar distribution of expression and comparable pairwise correlation coefficients of replicate samples across sites. A total of 804 miRNAs showed a similar distribution of pairwise correlation coefficients between replicate samples (p= 0.93). After normalization and selecting miRNAs with expression levels above zero in 80% of samples, 55 miRNAs were identified; heatmap and principal component analysis revealed similar expression patterns and clustering in replicate samples. CONCLUSIONS: Findings from this pilot investigation suggest the nCounter platform can yield reproducible results across study sites. This study underscores the importance of implementing quality control procedures when designing multi-center evaluations of miRNA abundance.

Mitochondrial DNA sequence variation and risk of glioma.

BACKGROUND: Malignant gliomas are the most common primary adult brain tumors, with a poor prognosis and ill-defined etiology. Mitochondrial DNA (mtDNA) sequence variation has been linked with certain cancers; however, research on glioma is lacking. METHODS: We examined the association of common (minor allele frequency ≥ 5%) germline mtDNA variants and haplogroups with glioma risk in 1,566 glioma cases and 1,017 controls from a US case-control study, and 425 glioma cases and 1,534 matched controls from the UK Biobank cohort (UKB). DNA samples were genotyped using the UK Biobank array that included a set of common and rare mtDNA variants. Risk associations were examined separately for glioblastoma (GBM) and lower grade tumors (non-GBM). RESULTS: In the US study, haplogroup W was inversely associated with glioma when compared with haplogroup H (OR = 0.43, 95%CI: 0.23-0.79); this association was not demonstrated in the UKB (OR = 1.07, 95%CI: 0.47-2.43). In the UKB, the variant m.3010G > A was significantly associated with GBM (OR = 1.32; 95%CI: 1.01-1.73; p = 0.04), but not non-GBM (1.23; 95%CI: 0.78-1.95; p = 0.38); no similar association was observed in the US study. In the US study, the variant m.14798 T > C, was significantly associated with non-GBM (OR = 0.72; 95%CI: 0.53-0.99), but not GBM (OR = 0.86; 95%CI: 0.66-1.11), whereas in the UKB, a positive association was observed between this variant and GBM (OR = 1.46; 95%CI: 1.06-2.02) but not non-GBM (OR = 0.92; 95%CI: 0.52-1.63). None of these associations were significant after adjustment for multiple testing. CONCLUSION: The association of inherited mtDNA variation, including rare and singleton variants, with glioma risk merits further study.

Mitochondrial DNA sequence variation and risk of meningioma.

BACKGROUND: Risk factors for meningioma include female gender, African American race, high body mass index (BMI), and exposure to ionizing radiation. Although genome-wide association studies (GWAS) have identified two nuclear genome risk loci for meningioma (rs12770228 and rs2686876), the relation between mitochondrial DNA (mtDNA) sequence variants and meningioma is unknown. METHODS: We examined the association of 42 common germline mtDNA variants (minor allele frequency ≥ 5%), haplogroups, and genes with meningioma in 1080 controls and 478 meningioma cases from a case-control study conducted at medical centers in the southeastern United States. Associations were examined separately for meningioma overall and by WHO grade (n = 409 grade I and n = 69 grade II/III). RESULTS: Overall, meningioma was significantly associated with being female (OR 2.85; 95% CI 2.21-3.69), self-reported African American race (OR 2.38, 95% CI 1.41-3.99), and being overweight (OR 1.48; 95% CI 1.11-1.97) or obese (OR 1.70; 95% CI 1.25-2.31). The variant m.16362T > C (rs62581341) in the mitochondrial control region was positively associated with grade II/III meningiomas (OR 2.33; 95% CI 1.14-4.77), but not grade I tumors (OR 0.99; 95% CI 0.64-1.53). Haplogroup L, a marker for African ancestry, was associated with meningioma overall (OR 2.92; 95% CI 1.01-8.44). However, after stratifying by self-reported race, this association was only apparent among the few self-reported Caucasians with this haplogroup (OR 6.35; 95% CI 1.56-25.9). No other mtDNA variant, haplogroup, or gene was associated with meningioma. CONCLUSION: Common mtDNA variants and major mtDNA haplogroups do not appear to have associations with the odds of developing meningioma.

Leveraging transcriptional dynamics to improve BRAF inhibitor responses in melanoma.

BACKGROUND: Melanoma is a heterogeneous tumour, but the impact of this heterogeneity upon therapeutic response is not well understood. METHODS: Single cell mRNA analysis was used to define the transcriptional heterogeneity of melanoma and its dynamic response to BRAF inhibitor therapy and treatment holidays. Discrete transcriptional states were defined in cell lines and melanoma patient specimens that predicted initial sensitivity to BRAF inhibition and the potential for effective re-challenge following resistance. A mathematical model was developed to maintain competition between the drug-sensitive and resistant states, which was validated in vivo. FINDINGS: Our analyses showed melanoma cell lines and patient specimens to be composed of >3 transcriptionally distinct states. The cell state composition was dynamically regulated in response to BRAF inhibitor therapy and drug holidays. Transcriptional state composition predicted for therapy response. The differences in fitness between the different transcriptional states were leveraged to develop a mathematical model that optimized therapy schedules to retain the drug sensitive population. In vivo validation demonstrated that the personalized adaptive dosing schedules outperformed continuous or fixed intermittent BRAF inhibitor schedules. INTERPRETATION: Our study provides the first evidence that transcriptional heterogeneity at the single cell level predicts for initial BRAF inhibitor sensitivity. We further demonstrate that manipulating transcriptional heterogeneity through personalized adaptive therapy schedules can delay the time to resistance. FUNDING: This work was funded by the National Institutes of Health. The funder played no role in assembly of the manuscript.

Drug and disease signature integration identifies synergistic combinations in glioblastoma.

Glioblastoma (GBM) is the most common primary adult brain tumor. Despite extensive efforts, the median survival for GBM patients is approximately 14 months. GBM therapy could benefit greatly from patient-specific targeted therapies that maximize treatment efficacy. Here we report a platform termed SynergySeq to identify drug combinations for the treatment of GBM by integrating information from The Cancer Genome Atlas (TCGA) and the Library of Integrated Network-Based Cellular Signatures (LINCS). We identify differentially expressed genes in GBM samples and devise a consensus gene expression signature for each compound using LINCS L1000 transcriptional profiling data. The SynergySeq platform computes disease discordance and drug concordance to identify combinations of FDA-approved drugs that induce a synergistic response in GBM. Collectively, our studies demonstrate that combining disease-specific gene expression signatures with LINCS small molecule perturbagen-response signatures can identify preclinical combinations for GBM, which can potentially be tested in humans.

Transient mitochondrial DNA double strand breaks in mice cause accelerated aging phenotypes in a ROS-dependent but p53/p21-independent manner.

We observed that the transient induction of mtDNA double strand breaks (DSBs) in cultured cells led to activation of cell cycle arrest proteins (p21/p53 pathway) and decreased cell growth, mediated through reactive oxygen species (ROS). To investigate this process in vivo we developed a mouse model where we could transiently induce mtDNA DSBs ubiquitously. This transient mtDNA damage in mice caused an accelerated aging phenotype, preferentially affecting proliferating tissues. One of the earliest phenotypes was accelerated thymus shrinkage by apoptosis and differentiation into adipose tissue, mimicking age-related thymic involution. This phenotype was accompanied by increased ROS and activation of cell cycle arrest proteins. Treatment with antioxidants improved the phenotype but the knocking out of p21 or p53 did not. Our results demonstrate that transient mtDNA DSBs can accelerate aging of certain tissues by increasing ROS. Surprisingly, this mtDNA DSB-associated senescence phenotype does not require p21/p53, even if this pathway is activated in the process.

Specific elimination of mutant mitochondrial genomes in patient-derived cells by mitoTALENs.

Mitochondrial diseases are commonly caused by mutated mitochondrial DNA (mtDNA), which in most cases coexists with wild-type mtDNA, resulting in mtDNA heteroplasmy. We have engineered transcription activator-like effector nucleases (TALENs) to localize to mitochondria and cleave different classes of pathogenic mtDNA mutations. Mitochondria-targeted TALEN (mitoTALEN) expression led to permanent reductions in deletion or point-mutant mtDNA in patient-derived cells, raising the possibility that these mitochondrial nucleases can be therapeutic for some mitochondrial diseases.