A pair of datasets for microRNA expression profiling to examine the use of careful study design for assigning arrays to samples.

We set out to demonstrate the logistic feasibility of careful experimental design for microarray studies and its level of scientific benefits for improving the accuracy and reproducibility of data inference. Towards this end, we conducted a study of microRNA expression using endometrioid endometrial tumours (n=96) and serous ovarian tumours (n=96) that were primary, untreated, and collected from 2000 to 2012 at Memorial Sloan Kettering Cancer Center. The same set of tumour tissue samples were profiled twice using the Agilent microRNA microarrays: once under an ideal experimental condition with balanced array-to-sample allocation and uniform handling; a second time by mimicking typical practice, with arrays assigned in the order of sample collection and processed by two technicians in multiple batches. This paper provides a detailed description of the generation and validation of this unique dataset pair so that the research community can re-use it to investigate other statistical questions regarding microarray study design and data analysis, and to address biological questions on the relevance of microRNA expression in gynaecologic cancer.

Mutational cooperativity linked to combinatorial epigenetic gain of function in acute myeloid leukemia.

Specific combinations of acute myeloid leukemia (AML) disease alleles, including FLT3 and TET2 mutations, confer distinct biologic features and adverse outcome. We generated mice with mutations in Tet2 and Flt3, which resulted in fully penetrant, lethal AML. Multipotent Tet2(-/-);Flt3(ITD) progenitors (LSK CD48(+)CD150(-)) propagate disease in secondary recipients and were refractory to standard AML chemotherapy and FLT3-targeted therapy. Flt3(ITD) mutations and Tet2 loss cooperatively remodeled DNA methylation and gene expression to an extent not seen with either mutant allele alone, including at the Gata2 locus. Re-expression of Gata2 induced differentiation in AML stem cells and attenuated leukemogenesis. TET2 and FLT3 mutations cooperatively induce AML, with a defined leukemia stem cell population characterized by site-specific changes in DNA methylation and gene expression.

Blocking and randomization to improve molecular biomarker discovery.

Randomization and blocking have the potential to prevent the negative impacts of nonbiologic effects on molecular biomarker discovery. Their use in practice, however, has been scarce. To demonstrate the logistic feasibility and scientific benefits of randomization and blocking, we conducted a microRNA study of endometrial tumors (n = 96) and ovarian tumors (n = 96) using a blocked randomization design to control for nonbiologic effects; we profiled the same set of tumors for a second time using no blocking or randomization. We assessed empirical evidence of differential expression in the two studies. We performed simulations through virtual rehybridizations to further evaluate the effects of blocking and randomization. There was moderate and asymmetric differential expression (351/3,523, 10%) between endometrial and ovarian tumors in the randomized dataset. Nonbiologic effects were observed in the nonrandomized dataset, and 1,934 markers (55%) were called differentially expressed. Among them, 185 were deemed differentially expressed (185/351, 53%) and 1,749 not differentially expressed (1,749/3,172, 55%) in the randomized dataset. In simulations, when randomization was applied to all samples at once or within batches of samples balanced in tumor groups, blocking improved the true-positive rate from 0.95 to 0.97 and the false-positive rate from 0.02 to 0.002; when sample batches were unbalanced, randomization was associated with the true-positive rate (0.92) and the false-positive rate (0.10) regardless of blocking. Normalization improved the detection of true-positive markers but still retained sizeable false-positive markers. Randomization and blocking should be used in practice to more fully reap the benefits of genomics technologies.

Quantitative assessment of intragenic receptor tyrosine kinase deletions in primary glioblastomas: their prevalence and molecular correlates.

Intragenic deletion is the most common form of activating mutation among receptor tyrosine kinases (RTK) in glioblastoma. However, these events are not detected by conventional DNA sequencing methods commonly utilized for tumor genotyping. To comprehensively assess the frequency, distribution, and expression levels of common RTK deletion mutants in glioblastoma, we analyzed RNA from a set of 192 glioblastoma samples from The Cancer Genome Atlas for the expression of EGFRvIII, EGFRvII, EGFRvV (carboxyl-terminal deletion), and PDGFRAΔ8,9. These mutations were detected in 24, 1.6, 4.7, and 1.6 % of cases, respectively. Overall, 29 % (55/189) of glioblastomas expressed at least one RTK intragenic deletion transcript in this panel. For EGFRvIII, samples were analyzed by both quantitative real-time PCR (QRT-PCR) and single mRNA molecule counting on the Nanostring nCounter platform. Nanostring proved to be highly sensitive, specific, and linear, with sensitivity comparable or exceeding that of RNA seq. We evaluated the prognostic significance and molecular correlates of RTK rearrangements. EGFRvIII was only detectable in tumors with focal amplification of the gene. Moreover, we found that EGFRvIII expression was not prognostic of poor outcome and that neither recurrent copy number alterations nor global changes in gene expression differentiate EGFRvIII-positive tumors from tumors with amplification of wild-type EGFR. The wide range of expression of mutant alleles and co-expression of multiple EGFR variants suggests that quantitative RNA-based clinical assays will be important for assessing the relative expression of intragenic deletions as therapeutic targets and/or candidate biomarkers. To this end, we demonstrate the performance of the Nanostring assay in RNA derived from routinely collected formalin-fixed paraffin-embedded tissue.

Convergent evolutionary analysis identifies significant mutations in drug resistance targets of Mycobacterium tuberculosis.

Mycobacterium tuberculosis adapts to the environment by selecting for advantageous single-nucleotide polymorphisms (SNPs). We studied whether advantageous SNPs could be distinguished from neutral mutations within genes associated with drug resistance. A total of 1,003 clinical isolates of M. tuberculosis were related phylogenetically and tested for the distribution of SNPs in putative drug resistance genes. Drug resistance-associated versus non-drug-resistance-associated SNPs in putative drug resistance genes were compared for associations with single versus multiple-branch outcomes using the chi-square and Fisher exact tests. All 286 (100%) isolates containing isoniazid (INH) resistance-associated SNPs had multibranch distributions, suggestive of multiple ancestry and convergent evolution. In contrast, all 327 (100%) isolates containing non-drug-resistance-associated SNPs were monophyletic and thus showed no evidence of convergent evolution (P < 0.001). Convergence testing was then applied to SNPs at position 481 of the iniA (Rv0342) gene and position 306 of the embB gene, both potential drug resistance targets for INH and/or ethambutol. Mutant embB306 alleles showed multibranch distributions, suggestive of convergent evolution; however, all 44 iniA(H481Q) mutations were monophyletic. In conclusion, this study validates convergence analysis as a tool for identifying mutations that cause INH resistance and explores mutations in other genes. Our results suggest that embB306 mutations are likely to confer drug resistance, while iniA(H481Q) mutations are not. This approach may be applied on a genome-wide scale to identify SNPs that impact antibiotic resistance and other types of biological fitness.

Population genetics study of isoniazid resistance mutations and evolution of multidrug-resistant Mycobacterium tuberculosis.

The molecular basis for isoniazid resistance in Mycobacterium tuberculosis is complex. Putative isoniazid resistance mutations have been identified in katG, ahpC, inhA, kasA, and ndh. However, small sample sizes and related potential biases in sample selection have precluded the development of statistically valid and significant population genetic analyses of clinical isoniazid resistance. We present the first large-scale analysis of 240 alleles previously associated with isoniazid resistance in a diverse set of 608 isoniazid-susceptible and 403 isoniazid-resistant clinical M. tuberculosis isolates. We detected 12 mutant alleles in isoniazid-susceptible isolates, suggesting that these alleles are not involved in isoniazid resistance. However, mutations in katG, ahpC, and inhA were strongly associated with isoniazid resistance, while kasA mutations were associated with isoniazid susceptibility. Remarkably, the distribution of isoniazid resistance-associated mutations was different in isoniazid-monoresistant isolates from that in multidrug-resistant isolates, with significantly fewer isoniazid resistance mutations in the isoniazid-monoresistant group. Mutations in katG315 were significantly more common in the multidrug-resistant isolates. Conversely, mutations in the inhA promoter were significantly more common in isoniazid-monoresistant isolates. We tested for interactions among mutations and resistance to different drugs. Mutations in katG, ahpC, and inhA were associated with rifampin resistance, but only katG315 mutations were associated with ethambutol resistance. There was also a significant inverse association between katG315 mutations and mutations in ahpC or inhA and between mutations in kasA and mutations in ahpC. Our results suggest that isoniazid resistance and the evolution of multidrug-resistant strains are complex dynamic processes that may be influenced by interactions between genes and drug-resistant phenotypes.

Global phylogeny of Mycobacterium tuberculosis based on single nucleotide polymorphism (SNP) analysis: insights into tuberculosis evolution, phylogenetic accuracy of other DNA fingerprinting systems, and recommendations for a minimal standard SNP set.

We analyzed a global collection of Mycobacterium tuberculosis strains using 212 single nucleotide polymorphism (SNP) markers. SNP nucleotide diversity was high (average across all SNPs, 0.19), and 96% of the SNP locus pairs were in complete linkage disequilibrium. Cluster analyses identified six deeply branching, phylogenetically distinct SNP cluster groups (SCGs) and five subgroups. The SCGs were strongly associated with the geographical origin of the M. tuberculosis samples and the birthplace of the human hosts. The most ancestral cluster (SCG-1) predominated in patients from the Indian subcontinent, while SCG-1 and another ancestral cluster (SCG-2) predominated in patients from East Asia, suggesting that M. tuberculosis first arose in the Indian subcontinent and spread worldwide through East Asia. Restricted SCG diversity and the prevalence of less ancestral SCGs in indigenous populations in Uganda and Mexico suggested a more recent introduction of M. tuberculosis into these regions. The East African Indian and Beijing spoligotypes were concordant with SCG-1 and SCG-2, respectively; X and Central Asian spoligotypes were also associated with one SCG or subgroup combination. Other clades had less consistent associations with SCGs. Mycobacterial interspersed repetitive unit (MIRU) analysis provided less robust phylogenetic information, and only 6 of the 12 MIRU microsatellite loci were highly differentiated between SCGs as measured by GST. Finally, an algorithm was devised to identify two minimal sets of either 45 or 6 SNPs that could be used in future investigations to enable global collaborations for studies on evolution, strain differentiation, and biological differences of M. tuberculosis.

Role of embB codon 306 mutations in Mycobacterium tuberculosis revisited: a novel association with broad drug resistance and IS6110 clustering rather than ethambutol resistance.

Mutations at position 306 of embB (embB306) have been proposed as a marker for ethambutol resistance in Mycobacterium tuberculosis; however, recent reports of embB306 mutations in ethambutol-susceptible isolates caused us to question the biological role of this mutation. We tested 1,020 clinical M. tuberculosis isolates with different drug susceptibility patterns and of different geographical origins for associations between embB306 mutations, drug resistance patterns, and major genetic group. One hundred isolates (10%) contained a mutation in embB306; however, only 55 of these mutants were ethambutol resistant. Mutations in embB306 could not be uniquely associated with any particular type of drug resistance and were found in all three major genetic groups. A striking association was observed between these mutations and resistance to any drug (P < 0.001), and the association between embB306 mutations and resistance to increasing numbers of drugs was highly significant (P < 0.001 for trend). We examined the association between embB306 mutations and IS6110 clustering (as a proxy for transmission) among all drug-resistant isolates. Mutations in embB306 were significantly associated with clustering by univariate analysis (odds ratio, 2.44; P = 0.004). In a multivariate model that also included mutations in katG315, katG463, gyrA95, and kasA269, only mutations in embB306 (odds ratio, 2.14; P = 0.008) and katG315 (odds ratio, 1.99; P = 0.015) were found to be independently associated with clustering. In conclusion, embB306 mutations do not cause classical ethambutol resistance but may predispose M. tuberculosis isolates to the development of resistance to increasing numbers of antibiotics and may increase the ability of drug-resistant isolates to be transmitted between subjects.