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.

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.

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.

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.

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.

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.

Genetic and genomic analyses of RNA polymerase II-pausing factor in regulation of mammalian transcription and cell growth.

Many mammalian genes are occupied by paused RNA polymerase II (pol II) in the promoter-proximal region on both sides of the transcription start site. However, the impact of pol II pausing on gene expression and cell biology is not fully understood. In this study, we used a Cre-Lox system to conditionally knock out the b subunit of mouse negative elongation factor (Nelf-b), a key pol II-pausing factor, in mouse embryonic fibroblasts. We found that Nelf-b was associated with the promoter-proximal region of the majority of expressed genes, yet genetic ablation of Nelf-b only affected the steady-state mRNA levels of a small percentage of the Nelf-b-associated genes. Interestingly, Nelf-b deletion also increased levels of transcription start site upstream transcripts at multiple negative elongation factor-associated genes. The direct target genes of Nelf-b were highly enriched with those involved in the control of cell growth and cell death. Correspondingly, Nelf-b knock-out mouse embryonic fibroblasts exhibited slower progression from quiescence to proliferation, as well as in a cycling cell population. Furthermore, Nelf-b deletion also resulted in increased apoptosis. Thus, the genetic and genomic studies provide new physiological and molecular insight into Nelf-mediated pol II pausing.

Combining clinical, pathology, and gene expression data to predict recurrence of hepatocellular carcinoma.

BACKGROUND & AIMS: In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS: We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS: Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS: We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses.

Non-housekeeping genes expressed in human trabecular meshwork cell cultures.

PURPOSE: To identify non-housekeeping genes definitively expressed in the human trabecular meshwork (TM). METHODS: Microarray gene expression data on TM cultured cells from four studies were compared. Genes that were queried in at least three studies and assessed to be expressed in at least three studies were considered definitively expressed genes of the human TM. Housekeeping genes were removed from this set of genes. The non-housekeeping TM gene profile was analyzed for pathway enrichment and microRNA targeting, using bioinformatics tools. The results were compared with results of previous non-array based studies. RESULTS: Nine hundred and sixty-two genes were identified as non-housekeeping TM expressed genes. Analysis of these by Kyoto Encyclopedia of Genes and Genomes led to identification of two enriched biologic pathways that achieved a highly significant Bonferroni p-value (p≤0.01): focal adhesion and extracellular matrix (ECM)-receptor interaction. Many of the genes were previously implicated in TM-related functions and the TM-associated disease glaucoma; however, some are novel. MicroRNAs known to be expressed in the trabecular meshwork were predicted to target some of the genes. Ten genes identified here, ALDH1A1 (aldehyde dehydrogenase 1 family, member A1), CDH11 (cadherin 11, type 2, OB-cadherin), CXCR7 (chemokine (C-X-C motif) receptor 7), CHI3L1 (chitinase 3-like 1), FGF2 (fibroblast growth factor 2), GNG11 (guanine nucleotide binding protein [G protein], gamma 11), IGFBP5 (insulin-like growth factor binding protein 5), PTPRM (protein tyrosine phosphatase, receptor type, M), RGS5 (regulator of G-protein signaling 5), and TUSC3 (tumor suppressor candidate 3), were also reported as TM expressed genes in three earlier non-microarray based studies. CONCLUSIONS: A transcriptome consisting of 962 non-housekeeping genes definitively expressed in the human TM was identified. Multiple genes and microRNAs are proposed for further study for a better understanding of TM physiology.

Gene expression profiling of human whole blood samples with the Illumina WG-DASL assay.

BACKGROUND: Microarray-based gene expression analysis of peripheral whole blood is a common strategy in the development of clinically relevant biomarker panels for a variety of human diseases. However, the results of such an analysis are often plagued by decreased sensitivity and reliability due to the effects of relatively high levels of globin mRNA in whole blood. Globin reduction assays have been shown to overcome such effects, but they require large amounts of total RNA and may induce distinct gene expression profiles. The Illumina whole genome DASL assay can detect gene expression levels using partially degraded RNA samples and has the potential to detect rare transcripts present in highly heterogeneous whole blood samples without the need for globin reduction. We assessed the utility of the whole genome DASL assay in an analysis of peripheral whole blood gene expression profiles. RESULTS: We find that gene expression detection is significantly increased with the use of whole genome DASL compared to the standard IVT-based direct hybridization. Additionally, globin-probe negative whole genome DASL did not exhibit significant improvements over globin-probe positive whole genome DASL. Globin reduction further increases the detection sensitivity and reliability of both whole genome DASL and IVT-based direct hybridization with little effect on raw intensity correlations. Raw intensity correlations between total RNA and globin reduced RNA were 0.955 for IVT-based direct hybridization and 0.979 for whole genome DASL. CONCLUSIONS: Overall, the detection sensitivity of the whole genome DASL assay is higher than the IVT-based direct hybridization assay, with or without globin reduction, and should be considered in conjunction with globin reduction methods for future blood-based gene expression studies.

Genome-wide expression assay comparison across frozen and fixed postmortem brain tissue samples.

BACKGROUND: Gene expression assays have been shown to yield high quality genome-wide data from partially degraded RNA samples. However, these methods have not yet been applied to postmortem human brain tissue, despite their potential to overcome poor RNA quality and other technical limitations inherent in many assays. We compared cDNA-mediated annealing, selection, and ligation (DASL)- and in vitro transcription (IVT)-based genome-wide expression profiling assays on RNA samples from artificially degraded reference pools, frozen brain tissue, and formalin-fixed brain tissue. RESULTS: The DASL-based platform produced expression results of greater reliability than the IVT-based platform in artificially degraded reference brain RNA and RNA from frozen tissue-based samples. Although data associated with a small sample of formalin-fixed RNA samples were poor when obtained from both assays, the DASL-based platform exhibited greater reliability in a subset of probes and samples. CONCLUSIONS: Our results suggest that the DASL-based gene expression-profiling platform may confer some advantages on mRNA assays of the brain over traditional IVT-based methods. We ultimately consider the implications of these results on investigations of neuropsychiatric disorders.

Gene-expression signature of vascular invasion in hepatocellular carcinoma.

BACKGROUND & AIMS: Vascular invasion is a major predictor of tumor recurrence after surgical treatments for hepatocellular carcinoma (HCC). While macroscopic vascular invasion can be detected by radiological techniques, pre-operative detection of microscopic vascular invasion, which complicates 30-40% of patients with early tumors, remains elusive. METHODS: A total of 214 patients with hepatocellular carcinoma who underwent resection were included in the study. By using genome-wide gene-expression profiling of 79 hepatitis C-related hepatocellular carcinoma samples (training set), a gene-expression signature associated with vascular invasion was defined. The signature was validated in formalin-fixed paraffin-embedded tissues obtained from an independent set of 135 patients with various etiologies. RESULTS: A 35-gene signature of vascular invasion was defined in the training set, predicting vascular invasion with an accuracy of 69%. The signature was independently associated with the presence of vascular invasion (OR 3.38, 95% CI 1.48-7.71, p=0.003) along with tumor size (diameter greater than 3 cm, OR 2.66, 95% CI 1.17-6.05, p=0.02). In the validation set, the signature discarded the presence of vascular invasion with a negative predictive value of 0.77, and significantly improved the diagnostic power of tumor size alone (p=0.045). CONCLUSIONS: The assessment of a gene-expression signature obtained from resected biopsied tumor specimens improved the diagnosis of vascular invasion beyond clinical variable-based prediction. The signature may aid in candidate selection for liver transplantation, and guide the design of clinical trials with experimental adjuvant therapies.

Distinct pigmentary and melanocortin 1 receptor-dependent components of cutaneous defense against ultraviolet radiation.

Genetic variation at the melanocortin 1 receptor (MC1R) is an important risk factor for developing ultraviolet (UV) radiation-induced skin cancer, the most common form of cancer in humans. The underlying mechanisms by which the MC1R defends against UV-induced skin cancer are not known. We used neonatal mouse skin (which, like human skin, contains a mixture of melanocytes and keratinocytes) to study how pigment cells and Mc1r genotype affect the genome-level response to UV radiation. Animals without viable melanocytes (Kit(W-v)/Kit(W-v)) or animals lacking a functional Mc1r (Mc1r(e)/Mc1r(e)) were exposed to sunburn-level doses of UVB radiation, and the patterns of large-scale gene expression in the basal epidermis were compared to each other and to nonmutant animals. Our analysis revealed discrete Kit- and Mc1r-dependent UVB transcriptional responses in the basal epidermis. The Kit-dependent UVB response was characterized largely by an enrichment of oxidative and endoplasmic reticulum stress genes, highlighting a distinctive role for pigmented melanocytes in mediating antioxidant defenses against genotoxic stresses within the basal epidermal environment. By contrast, the Mc1r-dependent UVB response contained an abundance of genes associated with regulating the cell cycle and oncogenesis. To test the clinical relevance of these observations, we analyzed publicly available data sets for primary melanoma and melanoma metastases and found that the set of genes specific for the Mc1r-dependent UVB response was able to differentiate between different clinical subtypes. Our analysis also revealed that the classes of genes induced by UVB differ from those repressed by UVB with regard to their biological functions, their overall number, and their size. The findings described here offer new insights into the transcriptional nature of the UV response in the skin and provide a molecular framework for the underlying mechanisms by which melanocytes and the Mc1r independently mediate and afford protection against UV radiation.

Analysis of gene expression in stage I serous tumors identifies critical pathways altered in ovarian cancer.

OBJECTIVE: Despite recent advances in the conceptual understanding of the pathogenesis of ovarian cancer, it remains the foremost cause of death from gynecologic malignancies in developed countries. The main reason for such a high rate of mortality is the lack of sensitive and specific biomarkers and imaging techniques for early detection of ovarian cancer. Additional biological insights into early-stage ovarian carcinogenesis are needed to help speed the development of markers for early detection of ovarian cancer. The objective of this study was to characterize differentially expressed genes in high-grade stage I serous carcinoma of the ovary. METHODS: We analyzed gene expression in macrodissected formalin-fixed, paraffin-embedded samples from 5 high-grade stage I serous carcinomas and 5 stage I borderline tumors of the ovary using the Illumina Whole Genome DASL assay (cDNA-mediated annealing, selection, extension, and ligation) corresponding to 24,000 genes. Significance Analysis of Microarrays was performed to determine differentially expressed genes in stage I serous carcinoma, and class prediction analysis was performed to determine the predictive value of differentially expressed gene sets to correctly classify serous carcinoma from borderline tumors in 3 independent data sets. Altered transcription factor pathways and biological pathways unique to stage I serous carcinoma were identified through class comparison of differentially expressed genes. RESULTS: Unsupervised cluster analysis of gene expression correctly classified stage I serous carcinomas from serous borderline tumors. Supervised analysis identified several known, as well as novel, genes differentially expressed in stage I ovarian cancer. Using a differentially expressed gene set, class comparison prediction analysis correctly identified serous carcinomas from serous borderline tumors in 3 independent data sets at over 80% accuracy, sensitivity, and specificity. Pathway analysis demonstrated the significance of p53 and E2F pathways in serous carcinogenesis and significant involvements of cell cycle and immune response pathways in stage I serous epithelial ovarian cancer. CONCLUSION: We have identified differentially expressed genes associated with the carcinogenesis of high-grade stage I serous EOC. Furthermore, integrative analysis of biological and transcription pathway data contributed to the confirmation of important biological pathways and discovery of additional unique genes and pathways that may have potential importance in ovarian pathogenesis and biomarker development.

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.

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.

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.