Glioma IL13Rα2 is associated with mesenchymal signature gene expression and poor patient prognosis

A major challenge for successful immunotherapy against glioma is the identification and characterization of validated targets. We have taken a bioinformatics approach towards understanding the biological context of IL-13 receptor α2 (IL13Rα2) expression in brain tumors, and its functional significance for patient survival. Querying multiple gene expression databases, we show that IL13Rα2 expression increases with glioma malignancy grade, and expression for high-grade tumors is bimodal, with approximately 58% of WHO grade IV gliomas over-expressing this receptor. By several measures, IL13Rα2 expression in patient samples and low-passage primary glioma lines most consistently correlates with the expression of signature genes defining mesenchymal subclass tumors and negatively correlates with proneural signature genes as defined by two studies. Positive associations were also noted with proliferative signature genes, whereas no consistent associations were found with either classical or neural signature genes. Probing the potential functional consequences of this mesenchymal association through IPA analysis suggests that IL13Rα2 expression is associated with activation of proinflammatory and immune pathways characteristic of mesenchymal subclass tumors. In addition, survival analyses indicate that IL13Rα2 over-expression is associated with poor patient prognosis, a single gene correlation ranking IL13Rα2 in the top ~1% of total gene expression probes with regard to survival association with WHO IV gliomas. This study better defines the functional consequences of IL13Rα2 expression by demonstrating association with mesenchymal signature gene expression and poor patient prognosis. It thus highlights the utility of IL13Rα2 as a therapeutic target, and helps define patient populations most likely to respond to immunotherapy in present and future clinical trials.

GFAP Mutations in Astrocytes Impair Oligodendrocyte Progenitor Proliferation and Myelination in an hiPSC Model of Alexander Disease

Alexander disease (AxD) is a leukodystrophy that primarily affects astrocytes and is caused by mutations in the astrocytic filament gene GFAP. While astrocytes are thought to have important roles in controlling myelination, AxD animal models do not recapitulate critical myelination phenotypes and it is therefore not clear how AxD astrocytes contribute to leukodystrophy. Here, we show that AxD patient iPSC-derived astrocytes recapitulate key features of AxD pathology such as GFAP aggregation. Moreover, AxD astrocytes inhibit proliferation of human iPSC-derived oligodendrocyte progenitor cells (OPCs) in co-culture and reduce their myelination potential. CRISPR/Cas9-based correction of GFAP mutations reversed these phenotypes. Transcriptomic analyses of AxD astrocytes and postmortem brains identified CHI3L1 as a key mediator of AxD astrocyte-induced inhibition of OPC activity. Thus, this iPSC-based model of AxD not only recapitulates patient phenotypes not observed in animal models, but also reveals mechanisms underlying disease pathology and provides a platform for assessing therapeutic interventions.

Subtypes of HPV-Positive Head and Neck Cancers Are Associated with HPV Characteristics, Copy Number Alterations, PIK3CA Mutation, and Pathway Signatures

PURPOSE

There is substantial heterogeneity within human papillomavirus (HPV)-associated head and neck cancer (HNC) tumors that predispose them to different outcomes; however, the molecular heterogeneity in this subgroup is poorly characterized due to various historical reasons.

EXPERIMENTAL DESIGN

We performed unsupervised gene expression clustering on deeply annotated (transcriptome and genome) HPV(+) HNC samples from two cohorts (84 total primary tumors), including 18 HPV(-) HNC samples, to discover subtypes and characterize the differences between subgroups in terms of their HPV characteristics, pathway activity, whole-genome somatic copy number alterations, and mutation frequencies.

RESULTS

We identified two distinct HPV(+) subtypes (namely HPV-KRT and HPV-IMU). HPV-KRT is characterized by elevated expression of genes in keratinocyte differentiation and oxidation-reduction process, whereas HPV-IMU has strong immune response and mesenchymal differentiation. The differences in expression are likely connected to the differences in HPV characteristics and genomic changes. HPV-KRT has more genic viral integration, lower E2/E4/E5 expression levels, and higher ratio of spliced to full-length HPV oncogene E6 than HPV-IMU; the subgroups also show differences in copy number alterations and mutations, in particular the loss of chr16q in HPV-IMU and gain of chr3q and PIK3CA mutation in HPV-KRT.

CONCLUSIONS

Our characterization of two subtypes of HPV(+) HNC tumors provides valuable molecular level information that point to two main carcinogenic paths. Together, these results shed light on stratifications of the HPV(+) HNCs and will help to guide personalized care for HPV(+) HNC patients. Clin Cancer Res; 22(18); 4735-45. ©2016 AACR.

COHCAP: an integrative genomic pipeline for single-nucleotide resolution DNA methylation analysis

COHCAP (City of Hope CpG Island Analysis Pipeline) is an algorithm to analyze single-nucleotide resolution DNA methylation data produced by either an Illumina methylation array or targeted bisulfite sequencing. The goal of the COHCAP algorithm is to identify CpG islands that show a consistent pattern of methylation among CpG sites. COHCAP is currently the only DNA methylation package that provides integration with gene expression data to identify a subset of CpG islands that are most likely to regulate downstream gene expression, and it can generate lists of differentially methylated CpG islands with ∼50% concordance with gene expression from both cell line data and heterogeneous patient data. For example, this article describes known breast cancer biomarkers (such as estrogen receptor) with a negative correlation between DNA methylation and gene expression. COHCAP also provides visualization for quality control metrics, regions of differential methylation and correlation between methylation and gene expression. This software is freely available at https://sourceforge.net/projects/cohcap/.

S100B promotes glioma growth through chemoattraction of myeloid-derived macrophages

PURPOSE

S100B is member of a multigenic family of Ca(2+)-binding proteins, which is overexpressed by gliomas. Recently, we showed that low concentrations of S100B attenuated microglia activation through the induction of Stat3. We hypothesized that overexpression of S100B in gliomas could promote tumor growth by modulating the activity of tumor-associated macrophages (TAM).

EXPERIMENTAL DESIGN

We stably transfected GL261 glioma cell lines with constructs that overexpressed (S100B(high)) or underexpressed (S100B(low)) S100B and compared their growth characteristics to intracranial wild-type (S100B(wt)) tumors.

RESULTS

Downregulation of S100B in gliomas had no impact on cell division in vitro but abrogated tumor growth in vivo. Interestingly, compared to S100B(low) tumors, S100B(wt) and S100B(high) intracranial gliomas exhibited higher infiltration of TAMs, stronger inflammatory cytokine expression, and increased vascularity. To identify the potential mechanisms involved, the expression of the S100B receptor, receptor for advanced glycation end products (RAGE), was evaluated in gliomas. Although S100B expression induced RAGE in vivo, RAGE ablation in mice did not significantly inhibit TAM infiltration into gliomas, suggesting that other pathways were involved in this process. To evaluate other mechanisms responsible for TAM chemoattraction, we then examined chemokine pathways and found that C-C motif ligand 2 (CCL2) was upregulated in S100B(high) tumors. Furthermore, analysis of The Cancer Genome Atlas's glioma data bank showed a positive correlation between S100B and CCL2 expression in human proneural and neural glioma subtypes, supporting our finding.

CONCLUSIONS

These observations suggest that S100B promotes glioma growth by TAM chemoattraction through upregulation of CCL2 and introduces the potential utility of S100B inhibitors for glioma therapy.

Identification of a common mesenchymal stromal progenitor for the adult haematopoietic niche

Microenvironment cues received by haematopoietic stem cells (HSC) are important in regulating the choice between self-renewal and differentiation. On the basis of the differential expression of cell-surface markers, here we identify a mesenchymal stromal progenitor hierarchy, where CD45⁻Ter119⁻CD31⁻CD166⁻CD146⁻Sca1⁺(Sca1⁺) progenitors give rise to CD45⁻Ter119⁻CD31⁻CD166⁻CD146⁺(CD146⁺) intermediate and CD45⁻Ter119⁻CD31⁻CD166⁺CD146⁻(CD166⁺) mature osteo-progenitors. All three progenitors preserve HSC long-term multi-lineage reconstitution capability in vitro; however, their in vivo fates are different. Post-transplantation, CD146⁺ and CD166⁺ progenitors form bone only. While Sca1⁺ progenitors produce CD146⁺, CD166⁺ progenitors, osteocytes and CXCL12-producing stromal cells. Only Sca1⁺ progenitors are capable of homing back to the marrow post-intravenous infusion. Ablation of Sca1⁺ progenitors results in a decrease of all three progenitor populations as well as haematopoietic stem/progenitor cells. Moreover, suppressing production of KIT-ligand in Sca1⁺ progenitors inhibits their ability to support HSCs. Our results indicate that Sca1⁺ progenitors, through the generation of both osteogenic and stromal cells, provide a supportive environment for hematopoiesis.

How the environment of the niche regulates haematopoietic stem cells (HSC) is unclear. Here, the authors identify a mesenchymal stromal progenitor hierarchy and identify Sca1+ cells as common progenitors for mesenchymal stromal cells in the adult niche that provide a supportive environment for hematopoiesis.

Prognostic and therapeutic significance of ribonucleotide reductase small subunit M2 in estrogen-negative breast cancers

Background

Ribonucleotide reductase (RR) is an essential enzyme involved in DNA synthesis. We hypothesized that RR subunit M2 (RRM2) might be a novel prognostic and predictive biomarker for estrogen receptor (ER)-negative breast cancers.

Methods

Individual and pooled survival analyses were conducted on six independent large-scale breast cancer microarray data sets; and findings were validated on a human breast tissue set (ZJU set).

Results

Gene set enrichment analysis revealed that RRM2-high breast cancers were significantly enriched for expression of gene sets that increased in proliferation, invasiveness, undifferentiation, embryonic stem/progenitor-like phenotypes, and poor patient survival (p < 0.01). Independent and pooled analyses verified that increased RRM2 mRNA levels were associated with poor patient outcome in a dose-dependent manner. The prognostic power of RRM2 mRNA was comparable to multiple gene signatures, and it was superior to TNM stage. In ER-negative breast cancers, RRM2 showed more prognostic power than that in ER-positive breast cancers. Further analysis indicated that RRM2 was a more accurate prognostic biomarker for ER-negative breast cancers than the pathoclinical indicators and uPA. A new RR inhibitor, COH29, could significantly enhance the chemosensitivity to doxorubicin in ER-negative MDA-MB-231 cells, but not in ER-positive MCF-7 cells.

Conclusion

RRM2 appears to be a promising prognostic biomarker and therapeutic target for ER-negative breast cancer patients.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2407-14-664) contains supplementary material, which is available to authorized users.

The histone demethylase jumonji coordinates cellular senescence including secretion of neural stem cell-attracting cytokines

Jumonji domain-containing protein 3 (JMJD3/KDM6B) demethylates lysine 27 on histone H3 (H3K27me3), a repressive epigenetic mark controlling chromatin organization and cellular senescence. To better understand the functional consequences of JMJD3 its expression was investigated in brain tumor cells. Querying patient expression profile databases confirmed JMJD3 overexpression in high-grade glioma. Immunochemical staining of two glioma cell lines, U251 and U87, indicated intrinsic differences in JMJD3 expression levels that were reflected in changes in cell phenotype and variations associated with cellular senescence, including senescence-associated β-galactosidase (SA-β-gal) activity and the senescence-associated secretory phenotype (SASP). Overexpressing wild-type JMJD3 (JMJD3wt) activated SASP-associated genes, enhanced SA-β-gal activity, and induced nuclear blebbing. Conversely, overexpression of a catalytically inactive dominant negative mutant JMJD3 (JMJD3mut) increased proliferation. In addition, a large number of transcripts were identified by RNA-seq as altered in JMJD3 overexpressing cells, including cancer- and inflammation-related transcripts as defined by Ingenuity Pathway Analysis. These results suggest that expression of the SASP in the context of cancer undermines normal tissue homeostasis and contributes to tumorigenesis and tumor progression. These studies are therapeutically relevant because inflammatory cytokines have been linked to homing of neural stem cells and other stem cells to tumor loci.

IMPLICATIONS

This glioma study brings together actions of a normal epigenetic mechanism (JMJD3 activity) with dysfunctional activation of senescence-related processes, including secretion of SASP proinflammatory cytokines and stem cell tropism toward tumors.

Detailed comparison of two popular variant calling packages for exome and targeted exon studies

The Genome Analysis Toolkit (GATK) is commonly used for variant calling of single nucleotide polymorphisms (SNPs) and small insertions and deletions (indels) from short-read sequencing data aligned against a reference genome. There have been a number of variant calling comparisons against GATK, but an equally comprehensive comparison for VarScan not yet been performed. More specifically, we compare (1) the effects of different pre-processing steps prior to variant calling with both GATK and VarScan, (2) VarScan variants called with increasingly conservative parameters, and (3) filtered and unfiltered GATK variant calls (for both the UnifiedGenotyper and the HaplotypeCaller). Variant calling was performed on three datasets (1 targeted exon dataset and 2 exome datasets), each with approximately a dozen subjects. In most cases, pre-processing steps (e.g., indel realignment and quality score base recalibration using GATK) had only a modest impact on the variant calls, but the importance of the pre-processing steps varied between datasets and variant callers. Based upon concordance statistics presented in this study, we recommend GATK users focus on “high-quality” GATK variants by filtering out variants flagged as low-quality. We also found that running VarScan with a conservative set of parameters (referred to as “VarScan-Cons”) resulted in a reproducible list of variants, with high concordance (>97%) to high-quality variants called by the GATK UnifiedGenotyper and HaplotypeCaller. These conservative parameters result in decreased sensitivity, but the VarScan-Cons variant list could still recover 84–88% of the high-quality GATK SNPs in the exome datasets. This study also provides limited evidence that VarScan-Cons has a decreased false positive rate among novel variants (relative to high-quality GATK SNPs) and that the GATK HaplotypeCaller has an increased false positive rate for indels (relative to VarScan-Cons and high-quality GATK UnifiedGenotyper indels). More broadly, we believe the metrics used for comparison in this study can be useful in assessing the quality of variant calls in the context of a specific experimental design. As an example, a limited number of variant calling comparisons are also performed on two additional variant callers.

The Novel Ribonucleotide Reductase Inhibitor COH29 Inhibits DNA Repair In Vitro

COH29 [N-(4-(3,4-dihydroxyphenyl)-5-phenylthiazol-2-yl)-3,4-dihydroxybenzamide], a novel antimetabolite drug developed at City of Hope Cancer Center, has anticancer activity that stems primarily from the inhibition of human ribonucleotide reductase (RNR). This key enzyme in deoxyribonucleotide biosynthesis is the target of established clinical agents such as hydroxyurea and gemcitabine because of its critical role in DNA replication and repair. Herein we report that BRCA-1-defective human breast cancer cells are more sensitive than wild-type BRCA-1 counterparts to COH29 in vitro and in vivo. Microarray gene expression profiling showed that COH29 reduces the expression of DNA repair pathway genes, suggesting that COH29 interferes with these pathways. It is well established that BRCA1 plays a role in DNA damage repair, especially homologous recombination (HR) repair, to maintain genome integrity. In BRCA1-defective HCC1937 breast cancer cells, COH29 induced more double-strand breaks (DSBs) and DNA-damage response than in HCC1937 + BRCA1 cells. By EJ5- and DR-green fluorescent protein (GFP) reporter assay, we found that COH29 could inhibit nonhomologous end joining (NHEJ) efficiency and that no HR activity was detected in HCC1937 cells, suggesting that repression of the NHEJ repair pathway may be involved in COH29-induced DSBs in BRCA1-deficient HCC1937 cells. Furthermore, we observed an accumulation of nuclear Rad51 foci in COH29-treated HCC1937 + BRCA1 cells, suggesting that BRCA1 plays a crucial role in repairing and recovering drug-induced DNA damage by recruiting Rad51 to damage sites. In summary, we describe here additional biologic effects of the RNR inhibitor COH29 that potentially strengthen its use as an anticancer agent.

Predicted functional RNAs within coding regions constrain evolutionary rates of yeast proteins

Functional RNAs (fRNAs) are being recognized as an important regulatory component in biological processes. Interestingly, recent computational studies suggest that the number and biological significance of functional RNAs within coding regions (coding fRNAs) may have been underestimated. We hypothesized that such coding fRNAs will impose additional constraint on sequence evolution because the DNA primary sequence has to simultaneously code for functional RNA secondary structures on the messenger RNA in addition to the amino acid codons for the protein sequence. To test this prediction, we first utilized computational methods to predict conserved fRNA secondary structures within multiple species alignments of Saccharomyces sensu strico genomes. We predict that as much as 5% of the genes in the yeast genome contain at least one functional RNA secondary structure within their protein-coding region. We then analyzed the impact of coding fRNAs on the evolutionary rate of protein-coding genes because a decrease in evolutionary rate implies constraint due to biological functionality. We found that our predicted coding fRNAs have a significant influence on evolutionary rates (especially at synonymous sites), independent of other functional measures. Thus, coding fRNA may play a role on sequence evolution. Given that coding regions of humans and flies contain many more predicted coding fRNAs than yeast, the impact of coding fRNAs on sequence evolution may be substantial in genomes of higher eukaryotes.

Engineering and optimization of an allosteric biosensor protein for peroxisome proliferator-activated receptor γ ligands

The peroxisome proliferator-activated receptor gamma (PPARγ or PPARG) belongs to the nuclear receptor superfamily, and is a potential drug target for a variety of diseases. In this work, we constructed a series of bacterial biosensors for the identification of functional PPARγ ligands. These sensors entail modified Escherichia coli cells carrying a four-domain fusion protein, comprised of the PPARγ ligand binding domain (LBD), an engineered mini-intein domain, the E. coli maltose binding protein (MBD), and a thymidylate synthase (TS) reporter enzyme. E. coli cells expressing this protein exhibit hormone ligand-dependent growth phenotypes. Unlike our published estrogen (ER) and thyroid receptor (TR) biosensors, the canonical PPARγ biosensor cells displayed pronounced growth in the absence of ligand. They were able to distinguish agonists and antagonists, however, even in the absence of agonist. To improve ligand sensitivity of this sensor, we attempted to engineer and optimize linker peptides flanking the PPARγ LBD insertion point. Truncation of the original linkers led to decreased basal growth and significantly enhanced ligand sensitivity of the PPARγ sensor, while substitution of the native linkers with optimized G(4)S (Gly-Gly-Gly-Gly-Ser) linkers further increased the sensitivity. Our studies demonstrate that the properties of linkers, especially the C-terminal linker, greatly influence the efficiency and fidelity of the allosteric signal induced by ligand binding. Our work also suggests an approach to increase allosteric behavior in this multidomain sensor protein, without modification of the functional LBD.

Global expression of molecular transporters in the human vaginal tract: implications for HIV chemoprophylaxis

Background

Pre-exposure chemoprophylaxis (PrECP) using antiretroviral agents is a promising strategy for the prevention of sexual HIV transmission in women. Molecular transporters in the human vaginal tract (VT) may play a pivotal role in determining drug disposition and, consequently, pharmacodynamic outcomes in these efforts. Little is known, however, on the expression of these transporters in vaginal tissues, representing a critical knowledge gap.

Methodology/Principal Findings

Our study analyzed the genome-wide transcriptome in 44 vaginal tissue samples from 6 reproductive-age women undergoing gynecologic surgeries. The analysis revealed that, unexpectedly, a large number (43%) of gene isoforms corresponding to membrane transporters were over-expressed (above the median expression level) in all samples. A subset of 12 highly expressed membrane transporters was identified and contained 10 members (83%) of the solute carrier superfamily. The largest difference in membrane transporter gene expression was observed across subjects, but more subtle differential expression also was found along the anterior-posterior axis of the VT. Cross-validation of the microarray analyses with measurements RT-qPCR demonstrated high concordance between these data sets. Immunofluorescence labeling of membrane transporter proteins in vaginal tissues was highly dependent on tissue/cell types.

Conclusions/Significance

Antiretroviral PrECP drugs currently under evaluation are substrates for molecular transporters that were commonly expressed, but fell into both over- or under-expressed categories in all samples, suggesting a complex role for carrier-mediated processes in determining the disposition of these xenobiotics in vaginal tissues. These findings hold important implications for the successful development of products, either oral or intravaginal, for female-controlled HIV PrECP.

BD-Func: a streamlined algorithm for predicting activation and inhibition of pathways

BD-Func (BiDirectional FUNCtional enrichment) is an algorithm that calculates functional enrichment by comparing lists of pre-defined genes that are known to be activated versus inhibited in a pathway or by a regulatory molecule. This paper shows that BD-Func can correctly predict cell line alternations and patient characteristics with accuracy comparable to popular algorithms, with a significantly faster run-time. BD-Func can compare scores for individual samples across multiple groups as well as provide predictive statistics and receiver operating characteristic (ROC) plots to quantify the accuracy of the signature associated with a binary phenotypic variable. BD-Func facilitates collaboration and reproducibility by encouraging users to share novel molecular signatures in the BD-Func discussion group, which is where the novel progesterone receptor and LBH589 signatures from this paper can be found. The novel LBH589 signature presented in this paper also serves as a case study showing how a custom signature using cell line data can accurately predict activity in vivo. This software is available to download at https://sourceforge.net/projects/bdfunc/.

A Human Embryonic Stem Cell Model of Aβ-Dependent Chronic Progressive Neurodegeneration

We describe the construction and phenotypic analysis of a human embryonic stem cell model of progressive Aβ-dependent neurodegeneration (ND) with potential relevance to Alzheimer’s disease (AD). We modified one allele of the normal APP locus to directly express a secretory form of Aβ40 or Aβ42, enabling expression from this edited allele to bypass the normal amyloidogenic APP processing pathway. Following neuronal differentiation, edited cell lines specifically accumulate intracellular aggregated/oligomeric Aβ, exhibit a synaptic deficit, and have an abnormal accumulation of endolysosomal vesicles. Edited cultures progress to a stage of overt ND. All phenotypes appear at earlier culture times for Aβ42 relative to Aβ40. Whole transcriptome RNA-Seq analysis identified 23 up and 70 down regulated genes (differentially expressed genes) with similar directional fold change but larger absolute values in the Aβ42 samples suggesting common underlying pathogenic mechanisms. Pathway/annotation analysis suggested that down regulation of extracellular matrix and cilia functions is significantly overrepresented. This cellular model could be useful for uncovering mechanisms directly linking Aβ to neuronal death and as a tool to screen for new therapeutic agents that slow or prevent human ND.

Genomic analyses of germline and somatic variation in high-grade serous ovarian cancer

BACKGROUND

High-grade serous ovarian cancers (HGSCs) display a high degree of complex genetic alterations. In this study, we identified germline and somatic genetic alterations in HGSC and their association with relapse-free and overall survival. Using a targeted capture of 557 genes involved in DNA damage response and PI3K/AKT/mTOR pathways, we conducted next-generation sequencing of DNA from matched blood and tumor tissue from 71 HGSC participants. In addition, we performed the OncoScan assay on tumor DNA from 61 participants to examine somatic copy number alterations (SCNA).

RESULTS

Approximately one-third of tumors had loss-of-function (LOF) germline (18/71, 25.4%) or somatic (7/71, 9.9%) variants in the DNA homologous recombination repair pathway genes BRCA1, BRCA2, CHEK2, MRE11A, BLM, and PALB2. LOF germline variants also were identified in other Fanconi anemia genes and in MAPK and PI3K/AKT/mTOR pathway genes. Most tumors harbored somatic TP53 variants (65/71, 91.5%). Using the OncoScan assay on tumor DNA from 61 participants, we identified focal homozygous deletions in BRCA1, BRCA2, MAP2K4, PTEN, RB1, SLX4, STK11, CREBBP, and NF1. In total, 38% (27/71) of HGSC patients harbored pathogenic variants in DNA homologous recombination repair genes. For patients with multiple tissues from the primary debulking or from multiple surgeries, the somatic mutations were maintained with few newly acquired point mutations suggesting that tumor evolution was not through somatic mutations. There was a significant association of LOF variants in homologous recombination repair pathway genes and high-amplitude somatic copy number alterations. Using GISTIC analysis, we identified NOTCH3, ZNF536, and PIK3R2 in these regions that were significantly associated with an increase in cancer recurrence and a reduction in overall survival.

CONCLUSIONS

From 71 patients with HGCS, we performed targeted germline and tumor sequencing and provided a comprehensive analysis of these 557 genes. We identified germline and somatic genetic alterations including somatic copy number alterations and analyzed their associations with relapse-free and overall survival. This single-site long-term follow-up study provides additional information on genetic alterations related to occurrence and outcome of HGSC. Our findings suggest that targeted treatments based on both variant and SCNA profile potentially could improve relapse-free and overall survival.

On comparing two structured RNA multiple alignments

We present a method, called BlockMatch, for aligning two blocks, where a block is an RNA multiple sequence alignment with the consensus secondary structure of the alignment in Stockholm format. The method employs a quadratic-time dynamic programming algorithm for aligning columns and column pairs of the multiple alignments in the blocks. Unlike many other tools that can perform pairwise alignment of either single sequences or structures only, BlockMatch takes into account the characteristics of all the sequences in the blocks along with their consensus structures during the alignment process, thus being able to achieve a high-quality alignment result. We apply BlockMatch to phylogeny reconstruction on a set of 5S rRNA sequences taken from fifteen bacteria species. Experimental results showed that the phylogenetic tree generated by our method is more accurate than the tree constructed based on the widely used ClustalW tool. The BlockMatch algorithm is implemented into a web server, accessible at http://bioinformatics.njit.edu/blockmatch. A jar file of the program is also available for download from the web server.

The Gallus gallus RJF reference genome reveals an MHCY haplotype organized in gene blocks that contain 107 loci including 45 specialized, polymorphic MHC class I loci, 41 C-type lectin-like loci, and other loci amid hundreds of transposable elements

MHCY is a second major histocompatibility complex-like gene region in chickens originally identified by the presence of major histocompatibility complex class I-like and class II-like gene sequences. Up to now, the MHCY gene region has been poorly represented in genomic sequence data. A high density of repetitive sequence and multiple members of several gene families prevented the accurate assembly of short-read sequence data for MHCY. Identified here by single-molecule real-time sequencing sequencing of BAC clones for the Gallus gallus Red Jungle Fowl reference genome are 107 MHCY region genes (45 major histocompatibility complex class I-like, 41 c-type-lectin-like, 8 major histocompatibility complex class IIβ, 8 LENG9-like, 4 zinc finger protein loci, and a single only zinc finger-like locus) located amid hundreds of retroelements within 4 contigs representing the region. Sequences obtained for nearby ribosomal RNA genes have allowed MHCY to be precisely mapped with respect to the nucleolar organizer region. Gene sequences provide insights into the unusual structure of the MHCY class I molecules. The MHCY class I loci are polymorphic and group into 22 types based on predicted amino acid sequences. Some MHCY class I loci are full-length major histocompatibility complex class I genes. Others with altered gene structure are considered gene candidates. The amino acid side chains at many of the polymorphic positions in MHCY class I are directed away rather than into the antigen-binding groove as is typical of peptide-binding major histocompatibility complex class I molecules. Identical and nearly identical blocks of genomic sequence contribute to the observed multiplicity of identical MHCY genes and the large size (&gt;639 kb) of the Red Jungle Fowl MHCY haplotype. Multiple points of hybridization observed in fluorescence in situ hybridization suggest that the Red Jungle Fowl MHCY haplotype is made up of linked, but physically separated genomic segments. The unusual gene content, the evidence of highly similar duplicated segments, and additional evidence of variation in haplotype size distinguish polymorphic MHCY from classical polymorphic major histocompatibility complex regions.

HPV genotyping by L1 amplicon sequencing of archived invasive cervical cancer samples: a pilot study

BACKGROUND

Human papillomavirus (HPV) is the primary cause of invasive cervical cancer (ICC). The prevalence of various HPV genotypes, ranging from oncogenically low- to high-risk, may be influenced by geographic and demographic factors, which could have critical implications for the screening and prevention of HPV infection and ICC incidence. However, many technical factors may influence the identification of high-risk genotypes associated with ICC in different populations.

METHODS

We used high-throughput sequencing of a single amplicon within the HPV L1 gene to assess the influence of patient age, race/ethnicity, histological subtype, sample type, collection date, experimental factors, and computational parameters on the prevalence of HPV genotypes detected in archived DNA (n = 34), frozen tissue (n = 44), and formalin-fixed paraffin-embedded (FFPE) tissue (n = 57) samples collected in the Los Angeles metropolitan area.

RESULTS

We found that the percentage of off-target human reads and the concentration of DNA amplified from each sample varied by HPV genotype and by archive type. After accounting for the percentage of human reads and excluding samples with especially low levels of amplified DNA, the HPV prevalence was 95% across all ICC samples: HPV16 was the most common genotype (in 56% of all ICC samples), followed by HPV18 (in 21%). Depending upon the genotyping parameters, the prevalence of HPV58 varied up to twofold in our cohort. In archived DNA and frozen tissue samples, we detected previously established differences in HPV16 and HPV18 frequencies based on histological subtype, but we could not reproduce those findings using our FFPE samples.

CONCLUSIONS

In this pilot study, we demonstrate that sample collection, preparation, and analysis methods can influence the detection of certain HPV genotypes and must be carefully considered when drawing any biological conclusions based on HPV genotyping data from ICC samples.

Critical Differential Expression Assessment for Individual Bulk RNA-Seq Projects

Finding the right balance of quality and quantity can be important, and it is essential that project quality does not drop below the level where important main conclusions are missed or misstated. We use knock-out and over-expression studies as a simplification to test recovery of a known causal gene in RNA-Seq cell line experiments. When single-end RNA-Seq reads are aligned with STAR and quantified with htseq-count, we found potential value in testing the use of the Generalized Linear Model (GLM) implementation of edgeR with robust dispersion estimation more frequently for either single-variate or multi-variate 2-group comparisons (with the possibility of defining criteria less stringent than |fold-change| > 1.5 and FDR < 0.05). When considering a limited number of patient sample comparisons with larger sample size, there might be some decreased variability between methods (except for DESeq1). However, at the same time, the ranking of the gene identified using immunohistochemistry (for ER/PR/HER2 in breast cancer samples from The Cancer Genome Atlas) showed as possible shift in performance compared to the cell line comparisons, potentially highlighting utility for standard statistical tests and/or limma-based analysis with larger sample sizes. If this continues to be true in additional studies and comparisons, then that could be consistent with the possibility that it may be important to allocate time for potential methods troubleshooting for genomics projects. Analysis of public data presented in this study does not consider all experimental designs, and presentation of downstream analysis is limited. So, any estimate from this simplification would be an underestimation of the true need for some methods testing for every project. Additionally, this set of independent cell line experiments has a limitation in being able to determine the frequency of missing a highly important gene if the problem is rare (such as 10% or lower). For example, if there was an assumption that only one method can be tested for "initial" analysis, then it is not completely clear to the extent that using edgeR-robust might perform better than DESeq2 in the cell line experiments. Importantly, we do not wish to cause undue concern, and we believe that it should often be possible to define a gene expression differential expression workflow that is suitable for some purposes for many samples. Nevertheless, at the same time, we provide a variety of measures that we believe emphasize the need to critically assess every individual project and maximize confidence in published results.

Genomic Analyses of Germline and Somatic Variation in High-Grade Serous Ovarian Cancer

Background High-grade serous ovarian cancers (HGSCs) display a high degree of complex genetic alterations. In this study, we identified germline and somatic genetic alterations in HGSC and their association with relapse-free and overall survival. Using a targeted capture of 577 genes involved in DNA damage response and PI3K/AKT/mTOR pathways, we conducted next-generation sequencing of DNA from matched blood and tumor tissue from 71 HGSC participants. In addition, we performed the OncoScan assay on tumor DNA from 61 participants to examine somatic copy number alterations. Results Approximately one-third of tumors had loss-of-function germline (18/71, 25.4%) or somatic (7/71, 9.9%) variants in the DNA homologous recombination repair pathway genes BRCA1, BRCA2, CHEK2, MRE11A, BLM , and PALB2 . Loss-of-function germline variants also were identified in other Fanconi anemia genes and in MAPK and PI3K/AKT/mTOR pathway genes. Most tumors harbored somatic TP53 variants (65/71, 91.5%). Using the OncoScan assay on tumor DNA from 61 participants, we identified focal homozygous deletions in BRCA1, BRCA2, MAP2K4, PTEN, RB1, SLX4, STK11, CREBBP , and NF1 . In total, 38% (27/71) of HGSC patients harbored pathogenic variants in DNA homologous recombination repair genes. For patients with multiple tissues from the primary debulking or from multiple surgeries, the somatic mutations were maintained with few newly acquired point mutations suggesting that tumor evolution was not through somatic mutations. There was a significant association of loss-of-function variants in homologous recombination repair pathway genes and high-amplitude somatic copy number alterations. Using GISTIC analysis, we identified NOTCH3, ZNF536 , and PIK3R2 in these regions that were significantly associated with an increase in cancer recurrence and a reduction in overall survival. Conclusions From 71 patients with HGCS, we performed targeted germline and tumor sequencing and provided a comprehensive analysis of these 577 genes. We identified germline and somatic genetic alterations including somatic copy number alterations and analyzed their associations with relapse-free and overall survival. This single-site long-term follow-up study provides additional information on genetic alterations related to occurrence and outcome of HGSC. Our findings suggest that targeted treatments based on both variant and SCNA profile potentially could improve relapse-free and overall survival.