Submegabase copy number variations arise during cerebral cortical neurogenesis as revealed by single-cell whole-genome sequencing.

Somatic copy number variations (CNVs) exist in the brain, but their genesis, prevalence, forms, and biological impact remain unclear, even within experimentally tractable animal models. We combined a transposase-based amplification (TbA) methodology for single-cell whole-genome sequencing with a bioinformatic approach for filtering unreliable CNVs (FUnC), developed from machine learning trained on lymphocyte V(D)J recombination. TbA-FUnC offered superior genomic coverage and removed >90% of false-positive CNV calls, allowing extensive examination of submegabase CNVs from over 500 cells throughout the neurogenic period of cerebral cortical development in Mus musculus Thousands of previously undocumented CNVs were identified. Half were less than 1 Mb in size, with deletions 4× more common than amplification events, and were randomly distributed throughout the genome. However, CNV prevalence during embryonic cortical development was nonrandom, peaking at midneurogenesis with levels triple those found at younger ages before falling to intermediate quantities. These data identify pervasive small and large CNVs as early contributors to neural genomic mosaicism, producing genomically diverse cellular building blocks that form the highly organized, mature brain.

Gene expression signature of Gleason score is associated with prostate cancer outcomes in a radical prostatectomy cohort.

Prostate cancer (PCa) is a leading cause of cancer-related mortality worldwide. Gleason score (GS) is one of the best predictors of PCa aggressiveness, but additional tumor biomarkers may improve its prognostic accuracy. We developed a gene expression signature of GS to enhance the prediction of PCa outcomes. Elastic net was used to construct a gene expression signature by contrasting GS 8-10 vs. ≤6 tumors in The Cancer Genome Atlas (TCGA) dataset. The constructed signature was then evaluated for its ability to predict recurrence and metastatic-lethal (ML) progression in a Fred Hutchinson (FH) patient cohort (N=408; NRecurrence=109; NMLprogression=27). The expression signature included transcripts representing 49 genes. In the FH cohort, a 25% increase in the signature was associated with a hazard ratio (HR) of 1.51 (P=2.7×10-5) for recurrence. The signature's area under the curve (AUC) for predicting recurrence and ML progression was 0.68 and 0.76, respectively. Compared to a model with age at diagnosis, pathological stage and GS, the gene expression signature improved the AUC for recurrence (3%) and ML progression (6%). Higher levels of the signature were associated with increased expression of genes in cell cycle-related pathways and decreased expression of genes in androgen response, estrogen response, oxidative phosphorylation, and apoptosis. This gene expression signature based on GS may improve the prediction of recurrence as well as ML progression in PCa patients after radical prostatectomy.

Gene expression panel predicts metastatic-lethal prostate cancer outcomes in men diagnosed with clinically localized prostate cancer.

Prognostic biomarkers are needed to distinguish patients with clinically localized prostate cancer (PCa) who are at high risk of metastatic progression. The tumor transcriptome may reveal its aggressiveness potential and have utility for predicting adverse patient outcomes. Genomewide gene expression levels were measured in primary tumor samples of 383 patients in a population-based discovery cohort, and from an independent clinical validation dataset of 78 patients. Patients were followed for ≥ 5 years after radical prostatectomy to ascertain outcomes. Area under the receiver-operating characteristic curve (AUC), partial AUC (pAUC, 95% specificity), and P-value criteria were used to detect and validate the differentially expressed transcripts. Twenty-three differentially expressed transcripts in patients with metastatic-lethal compared with nonrecurrent PCa were validated (P < 0.05; false discovery rate < 0.20) in the independent dataset. The addition of each validated transcript to a model with Gleason score showed that 17 transcripts significantly improved the AUC (range: 0.83-0.88; all P-values < 0.05). These differentially expressed mRNAs represent genes with diverse cellular functions related to tumor aggressiveness. This study validated 23 gene transcripts for predicting metastatic-lethal PCa in patients surgically treated for clinically localized disease. Several of these mRNA biomarkers have clinical potential for identifying the subset of PCa patients with more aggressive tumors who would benefit from closer monitoring and adjuvant therapy.

Bevacizumab May Differentially Improve Ovarian Cancer Outcome in Patients with Proliferative and Mesenchymal Molecular Subtypes.

Purpose: Recent progress in understanding the molecular biology of epithelial ovarian cancer has not yet translated into individualized treatment for these women or improvements in their disease outcome. Gene expression has been utilized to identify distinct molecular subtypes, but there have been no reports investigating whether or not molecular subtyping is predictive of response to bevacizumab in ovarian cancer.Experimental Design: DASL gene expression arrays were performed on FFPE tissue from patients enrolled on the ICON7 trial. Patients were stratified into four TCGA molecular subtypes. Associations between molecular subtype and the efficacy of randomly assigned therapy with bevacizumab were assessed.Results: Molecular subtypes were assigned as follows: 122 immunoreactive (34%), 96 proliferative (27%), 73 differentiated (20%), and 68 mesenchymal (19%). In univariate analysis patients with tumors of proliferative subtype obtained the greatest benefit from bevacizumab with a median PFS improvement of 10.1 months [HR, 0.55 (95% CI, 0.34-0.90), P = 0.016]. For the mesenchymal subtype, bevacizumab conferred a nonsignificant improvement in PFS of 8.2 months [HR 0.78 (95% CI, 0.44-1.40), P = 0.41]. Bevacizumab conferred modest improvements in PFS for patients with immunoreactive subtype (3.8 months; P = 0.08) or differentiated subtype (3.7 months; P = 0.61). Multivariate analysis demonstrated significant PFS improvement in proliferative subtype patients only [HR, 0.45 (95% CI, 0.27-0.74), P = 0.0015].Conclusions: Ovarian carcinoma molecular subtypes with the poorest survival (proliferative and mesenchymal) derive a comparably greater benefit from treatment that includes bevacizumab. Validation of our findings in an independent cohort could enable the use of bevacizumab for those patients most likely to benefit, thereby reducing side effects and healthcare cost. Clin Cancer Res; 23(14); 3794-801. ©2017 AACR.

Novel Gene Expression Signature Predictive of Clinical Recurrence After Radical Prostatectomy in Early Stage Prostate Cancer Patients.

BACKGROUND: Current clinical tools have limited accuracy in differentiating patients with localized prostate cancer who are at risk of recurrence from patients with indolent disease. We aimed to identify a gene expression signature that jointly with clinical variables could improve upon the prediction of clinical recurrence after RP for patients with stage T2 PCa. METHODS: The study population includes consented patients who underwent a radical retropubic prostatectomy (RP) and bilateral pelvic lymph node dissection at the University of Southern California in the PSA-era (1988-2008). We used a nested case-control study of 187 organ-confined patients (pT2N0M0): 154 with no recurrence ("controls") and 33 with clinical recurrence ("cases"). RNA was obtained from laser capture microdissected malignant glands representative of the overall Gleason score of each patient. Whole genome gene expression profiles (29,000 transcripts) were obtained using the Whole Genome DASL HT platform (Illumina, Inc). A gene expression signature of PCa clinical recurrence was identified using stability selection with elastic net regularized logistic regression. Three existing datasets generated with the Affymetrix Human Exon 1.0ST array were used for validation: Mayo Clinic (MC, n = 545), Memorial Sloan Kettering Cancer Center (SKCC, n = 150), and Erasmus Medical Center (EMC, n = 48). The areas under the ROC curve (AUCs) were obtained using repeated fivefold cross-validation. RESULTS: A 28-gene expression signature was identified that jointly with key clinical variables (age, Gleason score, pre-operative PSA level, and operation year) was predictive of clinical recurrence (AUC of clinical variables only was 0.67, AUC of clinical variables, and 28-gene signature was 0.99). The AUC of this gene signature fitted in each of the external datasets jointly with clinical variables was 0.75 (0.72-0.77) (MC), 0.90 (0.86-0.94) (MSKCC), and 0.82 (0.74-0.91) (EMC), whereas the AUC for clinical variables only in each dataset was 0.72 (0.70-0.74), 0.86 (0.82-0.91), and 0.76 (0.67-0.85), respectively. CONCLUSIONS: We report a novel gene-expression based classifier identified using agnostic approaches from whole genome expression profiles that can improve upon the accuracy of clinical indicators to stratify early stage localized patients at risk of clinical recurrence after RP. Prostate 76:1239-1256, 2016. © 2016 Wiley Periodicals, Inc.

Genetic suppression reveals DNA repair-independent antagonism between BRCA1 and COBRA1 in mammary gland development.

The breast cancer susceptibility gene BRCA1 is well known for its function in double-strand break (DSB) DNA repair. While BRCA1 is also implicated in transcriptional regulation, the physiological significance remains unclear. COBRA1 (also known as NELF-B) is a BRCA1-binding protein that regulates RNA polymerase II (RNAPII) pausing and transcription elongation. Here we interrogate functional interaction between BRCA1 and COBRA1 during mouse mammary gland development. Tissue-specific deletion of Cobra1 reduces mammary epithelial compartments and blocks ductal morphogenesis, alveologenesis and lactogenesis, demonstrating a pivotal role of COBRA1 in adult tissue development. Remarkably, these developmental deficiencies due to Cobra1 knockout are largely rescued by additional loss of full-length Brca1. Furthermore, Brca1/Cobra1 double knockout restores developmental transcription at puberty, alters luminal epithelial homoeostasis, yet remains deficient in homologous recombination-based DSB repair. Thus our genetic suppression analysis uncovers a previously unappreciated, DNA repair-independent function of BRCA1 in antagonizing COBRA1-dependent transcription programme during mammary gland development.

Translational Initiation at a Non-AUG Start Codon for Human and Mouse Negative Elongation Factor-B.

Negative elongation factor (NELF), a four-subunit protein complex in metazoan, plays an important role in regulating promoter-proximal pausing of RNA polymerase II (RNAPII). Genetic studies demonstrate that the B subunit of mouse NELF (NELF-B) is critical for embryonic development and homeostasis in adult tissue. We report here that both human and mouse NELF-B proteins are translated from a non-AUG codon upstream of the annotated AUG. This non-AUG codon sequence is conserved in mammalian NELF-B but not NELF-B orthologs of lower metazoan. The full-length and a truncated NELF-B that starts at the first AUG codon both interact with the other three NELF subunits. Furthermore, these two forms of NELF-B have a similar impact on the transcriptomics and proliferation of mouse embryonic fibroblasts. These results strongly suggest that additional amino acid sequence upstream of the annotated AUG is dispensable for the essential NELF function in supporting cell growth in vitro. The majority of mouse adult tissues surveyed express the full-length NELF-B protein, and some contain a truncated NELF-B protein with the same apparent size as the AUG-initiated version. This result raises the distinct possibility that translational initiation of mouse NELF-B is regulated in a tissue-dependent manner.

Expression of cell cycle-regulated genes and prostate cancer prognosis in a population-based cohort.

BACKGROUND: Prostate cancer (PCa) is clinically and biologically heterogeneous, making it difficult to predict at detection whether it will take an indolent or aggressive disease course. Cell cycle-regulated genes may be more highly expressed in actively dividing cells, with transcript levels reflecting tumor growth rate. Here, we evaluated expression of cell cycle genes in relation to PCa outcomes in a population-based cohort. METHODS: Gene expression data were generated from tumor tissues obtained at radical prostatectomy for 383 population-based patients (12.3-years average follow-up). The overall mean and individual transcript levels of 30 selected cell cycle genes was compared between patients with no evidence of recurrence (73%) and those who recurred (27%) or died (7%) from PCa. RESULTS: The multivariate adjusted hazard ratio (HR) for a change from the 25th to 75th percentile of mean gene expression level (range 8.02-10.05) was 1.25 (95%CI 0.96-1.63; P = 0.10) for PCa recurrence risk, and did not vary substantially by Gleason score, TMPRSS2-ERG fusion status, or family history of PCa. For lethal PCa, the HR for a change (25th to 75th percentile) in mean gene expression level was 2.04 (95%CI 1.26-3.31; P = 0.004), adjusted for clinicopathological variables. The ROC curve for mean gene expression level alone (AUC = 0.740) did not perform as well as clinicopathological variables alone (AUC = 0.803) for predicting lethal PCa, and the addition of mean gene expression to clinicopathological variables did not substantially improve prediction (AUC = 0.827; P = 0.18). Higher TK1 expression was strongly associated with both recurrent (P = 6.7 × 10(-5)) and lethal (P = 6.4 × 10(-6)) PCa. CONCLUSIONS: Mean expression level for 30 selected cell cycle-regulated genes was unrelated to recurrence risk, but was associated with a twofold increase in risk of lethal PCa. However, gene expression had less discriminatory accuracy than clinical variables alone for predicting lethal events. Transcript levels for several genes in the panel were significantly overexpressed in lethal versus non-recurrent PCa.

CDK6 levels regulate quiescence exit in human hematopoietic stem cells.

Regulated blood production is achieved through the hierarchical organization of dormant hematopoietic stem cell (HSC) subsets that differ in self-renewal potential and division frequency, with long-term (LT)-HSCs dividing the least. The molecular mechanisms underlying this variability in HSC division kinetics are unknown. We report here that quiescence exit kinetics are differentially regulated within human HSC subsets through the expression level of CDK6. LT-HSCs lack CDK6 protein. Short-term (ST)-HSCs are also quiescent but contain high CDK6 protein levels that permit rapid cell cycle entry upon mitogenic stimulation. Enforced CDK6 expression in LT-HSCs shortens quiescence exit and confers competitive advantage without impacting function. Computational modeling suggests that this independent control of quiescence exit kinetics inherently limits LT-HSC divisions and preserves the HSC pool to ensure lifelong hematopoiesis. Thus, differential expression of CDK6 underlies heterogeneity in stem cell quiescence states that functionally regulates this highly regenerative system.

Negative elongation factor controls energy homeostasis in cardiomyocytes.

Negative elongation factor (NELF) is known to enforce promoter-proximal pausing of RNA polymerase II (Pol II), a pervasive phenomenon observed across multicellular genomes. However, the physiological impact of NELF on tissue homeostasis remains unclear. Here, we show that whole-body conditional deletion of the B subunit of NELF (NELF-B) in adult mice results in cardiomyopathy and impaired response to cardiac stress. Tissue-specific knockout of NELF-B confirms its cell-autonomous function in cardiomyocytes. NELF directly supports transcription of those genes encoding rate-limiting enzymes in fatty acid oxidation (FAO) and the tricarboxylic acid (TCA) cycle. NELF also shares extensively transcriptional target genes with peroxisome proliferator-activated receptor α (PPARα), a master regulator of energy metabolism in the myocardium. Mechanistically, NELF helps stabilize the transcription initiation complex at the metabolism-related genes. Our findings strongly indicate that NELF is part of the PPARα-mediated transcription regulatory network that maintains metabolic homeostasis in cardiomyocytes.

A panel of CpG methylation sites distinguishes human embryonic stem cells and induced pluripotent stem cells.

Whether human induced pluripotent stem cells (hiPSCs) are epigenetically identical to human embryonic stem cells (hESCs) has been debated in the stem cell field. In this study, we analyzed DNA methylation patterns in a large number of hiPSCs (n = 114) and hESCs (n = 155), and identified a panel of 82 CpG methylation sites that can distinguish hiPSCs from hESCs with high accuracy. We show that 12 out of the 82 CpG sites were subject to hypermethylation in part by DNMT3B. Notably, DNMT3B contributes directly to aberrant hypermethylation and silencing of the signature gene, TCERG1L. Overall, we conclude that DNMT3B is involved in a wave of de novo methylation during reprogramming, a portion of which contributes to the unique hiPSC methylation signature. These 82 CpG methylation sites may be useful as biomarkers to distinguish between hiPSCs and hESCs.

Transcriptome profiling of archived sectioned formalin-fixed paraffin-embedded (AS-FFPE) tissue for disease classification.

BACKGROUND: Archived tissues from previously completed prospective trials represent invaluable resource for biomarker development. However, such specimens are often stored as sections on glass slides, in which RNA is severely degraded due to prolonged air exposure. We evaluated whether a proportion of archived sectioned formalin-fixed paraffin-embedded (AS-FFPE) tissues yield transcriptome profiles comparable to freshly cut (FC) FFPE tissues, which can be used for retrospective class prediction analysis. METHODS: Genome-wide transcriptome profiles of 6 to 7-year-old AS-FFPE tissue sections (generated from 5 to 16-year-old blocks) of 83 hepatocellular carcinoma (HCC) and 47 liver cirrhosis samples were generated by using whole-genome DASL assay (Illumina) and digital transcript counting (nCounter) assay (NanoString), and gene signature-based prediction of HCC subclasses and prognosis was compared with previously generated FC-FFPE profiles from the same tissue blocks. RESULTS: RNA quality and assay reproducibility of AS-FFPE RNA were comparable to intermediate to poor quality FC-FFPE samples (RNA Integrity Number: up to 2.50, R-square for technical replicates: up to 0.93). Analyzable transcriptome profiles were obtained in 64 (77%) HCC and 36 (77%) cirrhosis samples. Statistically more confident predictions based on random resampling-based method (nearest template prediction) were obtained in 37 (58%) HCC and 13 (36%) cirrhosis samples. Predictions made in FC-FFPE profiles were reproduced in 36 (97%) HCC and 11 (85%) cirrhosis AS-FFPE profiles. nCounter assay was tested in 24 cirrhosis samples, which yielded confident prediction in 15 samples (63%), of which 10 samples (67%) showed concordant predictions with FC-FFPE profiles. CONCLUSIONS: AS-FFPE tissues yielded poorer quality RNA and transcriptome profiles compared to FC-FFPE tissues. Statistically more confident class prediction was feasible in 37 of 83 HCC samples and 13 of 47 cirrhosis samples. These results suggest that AS-FFPE tissues can be regarded as a resource for retrospective transcriptome-based class prediction analysis when they are the only available materials.

Reduced lymphoid lineage priming promotes human hematopoietic stem cell expansion.

The hematopoietic system sustains regeneration throughout life by balancing self-renewal and differentiation. To stay poised for mature blood production, hematopoietic stem cells (HSCs) maintain low-level expression of lineage-associated genes, a process termed lineage priming. Here, we modulated expression levels of Inhibitor of DNA binding (ID) proteins to ask whether lineage priming affects self-renewal of human HSCs. We found that lentiviral overexpression of ID proteins in cord blood HSCs biases myeloerythroid commitment at the expense of lymphoid differentiation. Conversely, reducing ID2 expression levels increases lymphoid potential. Mechanistically, ID2 inhibits the transcription factor E47 to attenuate B-lymphoid priming in HSCs and progenitors. Strikingly, ID2 overexpression also results in a 10-fold expansion of HSCs in serial limiting dilution assays, indicating that early lymphoid transcription factors antagonize human HSC self-renewal. The relationship between lineage priming and self-renewal can be exploited to increase expansion of transplantable human HSCs and points to broader implications for other stem cell populations.

APOBEC3B upregulation and genomic mutation patterns in serous ovarian carcinoma.

Ovarian cancer is a clinically and molecularly heterogeneous disease. The driving forces behind this variability are unknown. Here, we report wide variation in the expression of the DNA cytosine deaminase APOBEC3B, with elevated expression in the majority of ovarian cancer cell lines (three SDs above the mean of normal ovarian surface epithelial cells) and high-grade primary ovarian cancers. APOBEC3B is active in the nucleus of several ovarian cancer cell lines and elicits a biochemical preference for deamination of cytosines in 5'-TC dinucleotides. Importantly, examination of whole-genome sequence from 16 ovarian cancers reveals that APOBEC3B expression correlates with total mutation load as well as elevated levels of transversion mutations. In particular, high APOBEC3B expression correlates with C-to-A and C-to-G transversion mutations within 5'-TC dinucleotide motifs in early-stage high-grade serous ovarian cancer genomes, suggesting that APOBEC3B-catalyzed genomic uracil lesions are further processed by downstream DNA "repair" enzymes including error-prone translesion polymerases. These data identify a potential role for APOBEC3B in serous ovarian cancer genomic instability.

Regulation of adipose oestrogen output by mechanical stress.

Adipose stromal cells are the primary source of local oestrogens in adipose tissue, aberrant production of which promotes oestrogen receptor-positive breast cancer. Here we show that extracellular matrix compliance and cell contractility are two opposing determinants for oestrogen output of adipose stromal cells. Using synthetic extracellular matrix and elastomeric micropost arrays with tunable rigidity, we find that increasing matrix compliance induces transcription of aromatase, a rate-limiting enzyme in oestrogen biosynthesis. This mechanical cue is transduced sequentially by discoidin domain receptor 1, c-Jun N-terminal kinase 1, and phosphorylated JunB, which binds to and activates two breast cancer-associated aromatase promoters. In contrast, elevated cell contractility due to actin stress fibre formation dampens aromatase transcription. Mechanically stimulated stromal oestrogen production enhances oestrogen-dependent transcription in oestrogen receptor-positive tumour cells and promotes their growth. This novel mechanotransduction pathway underlies communications between extracellular matrix, stromal hormone output, and cancer cell growth within the same microenvironment.

The transcriptional architecture of early human hematopoiesis identifies multilevel control of lymphoid commitment.

Understanding how differentiation programs originate from the gene-expression 'landscape' of hematopoietic stem cells (HSCs) is crucial for the development of new clinical therapies. We mapped the transcriptional dynamics underlying the first steps of commitment by tracking transcriptome changes in human HSCs and eight early progenitor populations. We found that transcriptional programs were extensively shared, extended across lineage-potential boundaries and were not strictly lineage affiliated. Elements of stem, lymphoid and myeloid programs were retained in multilymphoid progenitors (MLPs), which reflected a hybrid transcriptional state. By functional single cell analysis, we found that the transcription factors Bcl-11A, Sox4 and TEAD1 (TEF1) governed transcriptional networks in MLPs, which led to B cell specification. Overall, we found that integrated transcriptome approaches can be used to identify previously unknown regulators of multipotency and show additional complexity in lymphoid commitment.

FOXC1 in human trabecular meshwork cells is involved in regulatory pathway that includes miR-204, MEIS2, and ITGß1.

Forkhead box C1 (FOXC1) is a transcription factor that affects eye development. FOXC1 is implicated in the etiology of glaucoma because mutations in the gene are among the causes of Axenfeld-Rieger syndrome which is often accompanied by glaucoma. Glaucoma is the second leading cause of blindness. It is a complex disorder whose genetic basis in most patients remains unknown. Microarrays expression analysis was performed to identify genes in human trabecular meshwork (TM) primary cultures that are affected by FOXC1 and genes that may have roles in glaucoma. This represents the first genome wide analysis of FOXC1 target genes in any tissue. FOXC1 knock down by siRNAs affected the expression of 849 genes. Results on selected genes were confirmed by real time PCR, immunoblotting, and dual luciferase reporter assays. Observation of MEIS2 as a FOXC1 target and consideration of FOXC1 as a potential target of miR-204 prompted testing the effect of this micro RNA on expression of FOXC1 and several genes identified by array analysis as FOXC1 target genes. It was observed that miR-204 caused decreased expression of FOXC1 and the FOXC1 target genes CLOCK, PLEKHG5, ITGß1, and MEIS2 in the TM cultures. Expression of CLOCK, PLEKHG5, ITGß1 has not previously been reported to be affected by miR-204. The data suggest existence of a complex regulatory pathway in the TM part of which includes interactions between FOXC1, miR-204, MEIS2, and ITGß1. All these molecules are known to have TM relevant functions, and the TM is strongly implicated in the etiology of glaucoma.

MicroRNA paraffin-based studies in osteosarcoma reveal reproducible independent prognostic profiles at 14q32.

BACKGROUND: Although microRNAs (miRNAs) are implicated in osteosarcoma biology and chemoresponse, miRNA prognostic models are still needed, particularly because prognosis is imperfectly correlated with chemoresponse. Formalin-fixed, paraffin-embedded tissue is a necessary resource for biomarker studies in this malignancy with limited frozen tissue availability. METHODS: We performed miRNA and mRNA microarray formalin-fixed, paraffin-embedded assays in 65 osteosarcoma biopsy and 26 paired post-chemotherapy resection specimens and used the only publicly available miRNA dataset, generated independently by another group, to externally validate our strongest findings (n = 29). We used supervised principal components analysis and logistic regression for survival and chemoresponse, and miRNA activity and target gene set analysis to study miRNA regulatory activity. RESULTS: Several miRNA-based models with as few as five miRNAs were prognostic independently of pathologically assessed chemoresponse (median recurrence-free survival: 59 months versus not-yet-reached; adjusted hazards ratio = 2.90; P = 0.036). The independent dataset supported the reproducibility of recurrence and survival findings. The prognostic value of the profile was independent of confounding by known prognostic variables, including chemoresponse, tumor location and metastasis at diagnosis. Model performance improved when chemoresponse was added as a covariate (median recurrence-free survival: 59 months versus not-yet-reached; hazard ratio = 3.91; P = 0.002). Most prognostic miRNAs were located at 14q32 - a locus already linked to osteosarcoma - and their gene targets display deregulation patterns associated with outcome. We also identified miRNA profiles predictive of chemoresponse (75% to 80% accuracy), which did not overlap with prognostic profiles. CONCLUSIONS: Formalin-fixed, paraffin-embedded tissue-derived miRNA patterns are a powerful prognostic tool for risk-stratified osteosarcoma management strategies. Combined miRNA and mRNA analysis supports a possible role of the 14q32 locus in osteosarcoma progression and outcome. Our study creates a paradigm for formalin-fixed, paraffin-embedded-based miRNA biomarker studies in cancer.

Preprocessing and Quality Control Strategies for Illumina DASL Assay-Based Brain Gene Expression Studies with Semi-Degraded Samples.

Available statistical preprocessing or quality control analysis tools for gene expression microarray datasets are known to greatly affect downstream data analysis, especially when degraded samples, unique tissue samples, or novel expression assays are used. It is therefore important to assess the validity and impact of the assumptions built in to preprocessing schemes for a dataset. We developed and assessed a data preprocessing strategy for use with the Illumina DASL-based gene expression assay with partially degraded postmortem prefrontal cortex samples. The samples were obtained from individuals with autism as part of an investigation of the pathogenic factors contributing to autism. Using statistical analysis methods and metrics such as those associated with multivariate distance matrix regression and mean inter-array correlation, we developed a DASL-based assay gene expression preprocessing pipeline to accommodate and detect problems with microarray-based gene expression values obtained with degraded brain samples. Key steps in the pipeline included outlier exclusion, data transformation and normalization, and batch effect and covariate corrections. Our goal was to produce a clean dataset for subsequent downstream differential expression analysis. We ultimately settled on available transformation and normalization algorithms in the R/Bioconductor package lumi based on an assessment of their use in various combinations. A log2-transformed, quantile-normalized, and batch and seizure-corrected procedure was likely the most appropriate for our data. We empirically tested different components of our proposed preprocessing strategy and believe that our results suggest that a preprocessing strategy that effectively identifies outliers, normalizes the data, and corrects for batch effects can be applied to all studies, even those pursued with degraded samples.

Age-dependent brain gene expression and copy number anomalies in autism suggest distinct pathological processes at young versus mature ages.

Autism is a highly heritable neurodevelopmental disorder, yet the genetic underpinnings of the disorder are largely unknown. Aberrant brain overgrowth is a well-replicated observation in the autism literature; but association, linkage, and expression studies have not identified genetic factors that explain this trajectory. Few studies have had sufficient statistical power to investigate whole-genome gene expression and genotypic variation in the autistic brain, especially in regions that display the greatest growth abnormality. Previous functional genomic studies have identified possible alterations in transcript levels of genes related to neurodevelopment and immune function. Thus, there is a need for genetic studies involving key brain regions to replicate these findings and solidify the role of particular functional pathways in autism pathogenesis. We therefore sought to identify abnormal brain gene expression patterns via whole-genome analysis of mRNA levels and copy number variations (CNVs) in autistic and control postmortem brain samples. We focused on prefrontal cortex tissue where excess neuron numbers and cortical overgrowth are pronounced in the majority of autism cases. We found evidence for dysregulation in pathways governing cell number, cortical patterning, and differentiation in young autistic prefrontal cortex. In contrast, adult autistic prefrontal cortex showed dysregulation of signaling and repair pathways. Genes regulating cell cycle also exhibited autism-specific CNVs in DNA derived from prefrontal cortex, and these genes were significantly associated with autism in genome-wide association study datasets. Our results suggest that CNVs and age-dependent gene expression changes in autism may reflect distinct pathological processes in the developing versus the mature autistic prefrontal cortex. Our results raise the hypothesis that genetic dysregulation in the developing brain leads to abnormal regional patterning, excess prefrontal neurons, cortical overgrowth, and neural dysfunction in autism.