Synthetic Lethal and Resistance Interactions with BET Bromodomain Inhibitors in Triple-Negative Breast Cancer.

BET bromodomain inhibitors (BBDIs) are candidate therapeutic agents for triple-negative breast cancer (TNBC) and other cancer types, but inherent and acquired resistance to BBDIs limits their potential clinical use. Using CRISPR and small-molecule inhibitor screens combined with comprehensive molecular profiling of BBDI response and resistance, we identified synthetic lethal interactions with BBDIs and genes that, when deleted, confer resistance. We observed synergy with regulators of cell cycle progression, YAP, AXL, and SRC signaling, and chemotherapeutic agents. We also uncovered functional similarities and differences among BRD2, BRD4, and BRD7. Although deletion of BRD2 enhances sensitivity to BBDIs, BRD7 loss leads to gain of TEAD-YAP chromatin binding and luminal features associated with BBDI resistance. Single-cell RNA-seq, ATAC-seq, and cellular barcoding analysis of BBDI responses in sensitive and resistant cell lines highlight significant heterogeneity among samples and demonstrate that BBDI resistance can be pre-existing or acquired.

Increased HOXA5 expression provides a selective advantage for gain of whole chromosome 7 in IDH wild-type glioblastoma.

Glioblastoma is the most frequently occurring and invariably fatal primary brain tumor in adults. The vast majority of glioblastomas is characterized by chromosomal copy number alterations, including gain of whole chromosome 7 and loss of whole chromosome 10. Gain of whole chromosome 7 is an early event in gliomagenesis that occurs in proneural-like precursor cells, which give rise to all isocitrate dehydrogenase (IDH) wild-type glioblastoma transcriptional subtypes. Platelet-derived growth factor A (PDGFA) is one gene on chromosome 7 known to drive gliomagenesis, but, given its location near the end of 7p, there are likely several other genes located along chromosome 7 that select for its increased whole-chromosome copy number within glioblastoma cells. To identify other potential genes that could select for gain of whole chromosome 7, we developed an unbiased bioinformatics approach that identified homeobox A5 (HOXA5) as a gene whose expression correlated with gain of chromosome 7 and a more aggressive phenotype of the resulting glioma. High expression of HOXA5 in glioblastoma was associated with a proneural gene expression pattern and decreased overall survival in both human proneural and PDGF-driven mouse glioblastoma. Furthermore, HOXA5 overexpression promoted cellular proliferation and potentiated radioresistance. We also found enrichment of HOXA5 expression in recurrent human and mouse glioblastoma at first recurrence after radiotherapy. Overall, this study implicates HOXA5 as a chromosome 7-associated gene-level locus that promotes selection for gain of whole chromosome 7 and an aggressive phenotype in glioblastoma.

Assessing base-resolution DNA mechanics on the genome scale.

Intrinsic DNA properties including bending play a crucial role in diverse biological systems. A recent advance in a high-throughput technology called loop-seq makes it possible to determine the bendability of hundred thousand 50-bp DNA duplexes in one experiment. However, it's still challenging to assess base-resolution sequence bendability in large genomes such as human, which requires thousands of such experiments. Here, we introduce 'BendNet'-a deep neural network to predict the intrinsic DNA bending at base-resolution by using loop-seq results in yeast as training data. BendNet can predict the DNA bendability of any given sequence from different species with high accuracy. To explore the utility of BendNet, we applied it to the human genome and observed DNA bendability is associated with chromatin features and disease risk regions involving transcription/enhancer regulation, DNA replication, transcription factor binding and extrachromosomal circular DNA generation. These findings expand our understanding on DNA mechanics and its association with transcription regulation in mammals. Lastly, we built a comprehensive resource of genomic DNA bendability profiles for 307 species by applying BendNet, and provided an online tool to assess the bendability of user-specified DNA sequences (http://www.dnabendnet.com/).

A deep learning-based drug repurposing screening and validation for anti-SARS-CoV-2 compounds by targeting the cell entry mechanism.

The recent outbreak of Corona Virus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a severe threat to the global public health and economy, however, effective drugs to treat COVID-19 are still lacking. Here, we employ a deep learning-based drug repositioning strategy to systematically screen potential anti-SARS-CoV-2 drug candidates that target the cell entry mechanism of SARS-CoV-2 virus from 2635 FDA-approved drugs and 1062 active ingredients from Traditional Chinese Medicine herbs. In silico molecular docking analysis validates the interactions between the top compounds and host receptors or viral spike proteins. Using a SARS-CoV-2 pseudovirus system, we further identify several drug candidates including Fostamatinib, Linagliptin, Lysergol and Sophoridine that can effectively block the cell entry of SARS-CoV-2 variants into human lung cells even at a nanomolar scale. These efforts not only illuminate the feasibility of applying deep learning-based drug repositioning for antiviral agents by targeting a specified mechanism, but also provide a valuable resource of promising drug candidates or lead compounds to treat COVID-19.

Secuer: Ultrafast, scalable and accurate clustering of single-cell RNA-seq data.

Identifying cell clusters is a critical step for single-cell transcriptomics study. Despite the numerous clustering tools developed recently, the rapid growth of scRNA-seq volumes prompts for a more (computationally) efficient clustering method. Here, we introduce Secuer, a Scalable and Efficient speCtral clUstERing algorithm for scRNA-seq data. By employing an anchor-based bipartite graph representation algorithm, Secuer enjoys reduced runtime and memory usage over one order of magnitude for datasets with more than 1 million cells. Meanwhile, Secuer also achieves better or comparable accuracy than competing methods in small and moderate benchmark datasets. Furthermore, we showcase that Secuer can also serve as a building block for a new consensus clustering method, Secuer-consensus, which again improves the runtime and scalability of state-of-the-art consensus clustering methods while also maintaining the accuracy. Overall, Secuer is a versatile, accurate, and scalable clustering framework suitable for small to ultra-large single-cell clustering tasks.

Detection of differentially methylated CpG sites between tumor samples with uneven tumor purities.

MOTIVATION: Inference of differentially methylated (DM) CpG sites between two groups of tumor samples with different geno- or pheno-types is a critical step to uncover the epigenetic mechanism of tumorigenesis, and identify biomarkers for cancer subtyping. However, as a major source of confounding factor, uneven distributions of tumor purity between two groups of tumor samples will lead to biased discovery of DM sites if not properly accounted for. RESULTS: We here propose InfiniumDM, a generalized least square model to adjust tumor purity effect for differential methylation analysis. Our method is applicable to a variety of experimental designs including with or without normal controls, different sources of normal tissue contaminations. We compared our method with conventional methods including minfi, limma and limma corrected by tumor purity using simulated datasets. Our method shows significantly better performance at different levels of differential methylation thresholds, sample sizes, mean purity deviations and so on. We also applied the proposed method to breast cancer samples from TCGA database to further evaluate its performance. Overall, both simulation and real data analyses demonstrate favorable performance over existing methods serving similar purpose. AVAILABILITY AND IMPLEMENTATION: InfiniumDM is a part of R package InfiniumPurify, which is freely available from GitHub (https://github.com/Xiaoqizheng/InfiniumPurify). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The expression profiles and prognostic values of HSP70s in hepatocellular carcinoma.

BACKGROUND: The HSP70 family of heat shock protein plays a critical role in protein synthesis and transport to maintain protein homeostasis. Several studies have indicated that HSP70s are related to the development and occurrence of various cancers. METHODS: The relationship between the overall survival rate of hepatocellular carcinoma patients and the expression of 14 HSP70s from multiple databases, such as TCGA, ONCOMINE, cBioPortal was investigated. Western Blot and PCR were used to evaluate HSPA4 and HSPA14 expressions in various HCC cells to identify suitable cell lines for further experiments .Wound-healing assays, Transwell assays and EdU assays were used to verify the effects of HSPA4 and HSPA14 on the function of hepatocellular carcinoma cells, and statistical analysis was performed. RESULTS: Hepatocellular carcinoma tissues significantly expressed the 14 HSP70s compared to the normal samples. Besides, the high HSPA1A, HSPA1B, HSPA4, HSPA5, HSPA8, HSPA13, and HSPA14 expressions were inversely associated with the overall survival rate of patients, tumor grade, and cancer stage. A PPI regulatory network was constructed using the 14 HSP70s proteins with HSPA5 and HSPA8 at the network center. Univariate and multivariate analyses showed that HSPA4 and HSPA14 could be independent risk factors for the prognosis of hepatocellular carcinoma patients. Cell experiments have also confirmed that reducing HSPA4 and HSPA14 expressions can inhibit the invasion, metastasis, and proliferation of hepatocellular carcinoma cells. CONCLUSIONS: Therefore, the HSP70s significantly influence the occurrence and development of hepatocellular carcinoma. For instance, HSPA4 and HSPA14 can be novel therapeutic targets and prognostic biomarkers for hepatocellular carcinoma.

Deconvolution of heterogeneous tumor samples using partial reference signals.

Deconvolution of heterogeneous bulk tumor samples into distinct cellular populations is an important yet challenging problem, particularly when only partial references are available. A common approach to dealing with this problem is to deconvolve the mixed signals using available references and leverage the remaining signal as a new cell component. However, as indicated in our simulation, such an approach tends to over-estimate the proportions of known cell types and fails to detect novel cell types. Here, we propose PREDE, a partial reference-based deconvolution method using an iterative non-negative matrix factorization algorithm. Our method is verified to be effective in estimating cell proportions and expression profiles of unknown cell types based on simulated datasets at a variety of parameter settings. Applying our method to TCGA tumor samples, we found that proportions of pure cancer cells better indicate different subtypes of tumor samples. We also detected several cell types for each cancer type whose proportions successfully predicted patient survival. Our method makes a significant contribution to deconvolution of heterogeneous tumor samples and could be widely applied to varieties of high throughput bulk data. PREDE is implemented in R and is freely available from GitHub (https://xiaoqizheng.github.io/PREDE).

MicroRNA-10b expression predicts long-term survival in patients with solid tumor.

BACKGROUND: Numerous studies have evaluated the significance of the microRNA-10b (miR-10b) in the development and progression of many cancers. Their findings revealed that increased expression of miR-10b is associated with unfavorable prognosis in patients with cancer. RESULTS: A total of 1,834 patients from 19 studies were included in this study. A significantly shorter overall survival was observed in patients with increased expression of miR-10b (hazard ratio [HR] = 1.99, 95% confidence interval [CI]: 1.51-2.61). Statistical significance was also observed in subgroup meta-analysis stratified by the cancer type, cutoff value, analysis type, and sample size. Also, patients with a high expression level of miR-10b had a poorer disease-free survival rate (HR = 1.18, 95% CI: 1.05-1.33). In addition, the pooled odds ratios (ORs) showed that increased miR-10b was also associated with positive lymph node metastasis (OR = 2.09, 95% CI: 1.45-3.03), distant metastasis (OR = 2.40, 95% CI: 1.57-3.67), tumor size (OR = 3.86, 95% CI: 2.25-6.64), and poor clinical stage (OR = 5.02, 95% CI: 3.37-7.47). MATERIALS AND METHODS: A systematic literature search was conducted on a number of electronic databases, including PubMed, Embase, Web of Science, China National Knowledge Infrastructure, Springer, Google Scholar, and Gene expression omnibus. We retrieved the relevant articles to examine the association between the miR-10b expression levels and patients' prognosis. The meta-analysis was conducted using the RevMan 5.2 software and Stata SE12.0 software. CONCLUSIONS: High miR-10b expression was correlated with poor clinical outcome, which indicated the potential clinical use of miR-10b as a molecular biomarker for cancer, particularly in assessing prognosis for patients with cancers. Further studies should be performed to verify the clinical utility of miR-10b in human solid tumors.

Bisulfite-independent analysis of CpG island methylation enables genome-scale stratification of single cells.

Conventional DNA bisulfite sequencing has been extended to single cell level, but the coverage consistency is insufficient for parallel comparison. Here we report a novel method for genome-wide CpG island (CGI) methylation sequencing for single cells (scCGI-seq), combining methylation-sensitive restriction enzyme digestion and multiple displacement amplification for selective detection of methylated CGIs. We applied this method to analyzing single cells from two types of hematopoietic cells, K562 and GM12878 and small populations of fibroblasts and induced pluripotent stem cells. The method detected 21 798 CGIs (76% of all CGIs) per cell, and the number of CGIs consistently detected from all 16 profiled single cells was 20 864 (72.7%), with 12 961 promoters covered. This coverage represents a substantial improvement over results obtained using single cell reduced representation bisulfite sequencing, with a 66-fold increase in the fraction of consistently profiled CGIs across individual cells. Single cells of the same type were more similar to each other than to other types, but also displayed epigenetic heterogeneity. The method was further validated by comparing the CpG methylation pattern, methylation profile of CGIs/promoters and repeat regions and 41 classes of known regulatory markers to the ENCODE data. Although not every minor methylation differences between cells are detectable, scCGI-seq provides a solid tool for unsupervised stratification of a heterogeneous cell population.

Sabotaging of the oxidative stress response by an oncogenic noncoding RNA.

Overexpression of the multiple myeloma set domain (MMSET) Wolf-Hirschhorn syndrome candidate 1 gene, which contains an orphan box H/ACA class small nucleolar RNA, ACA11, in an intron, is associated with several cancer types, including multiple myeloma (MM). ACA11 and MMSET are overexpressed cotranscriptionally as a result of the t(4;14) chromosomal translocation in a subset of patients with MM. RNA sequencing of CD138+ tumor cells from t(4;14)-positive and -negative MM patient bone marrow samples revealed an enhanced oxidative phosphorylation mRNA signature. Supporting these data, ACA11 overexpression in a t(4;14)-negative MM cell line, MM1.S, demonstrated enhanced reactive oxygen species (ROS) levels. In addition, an enhancement of cell proliferation, increased soft agar colony size, and elevated ERK1/2 phosphorylation were observed. This ACA11-driven hyperproliferative phenotype depended on increased ROS levels as exogenously added antioxidants attenuate the increased proliferation. A major transcriptional regulator of the cellular antioxidant response, nuclear factor (erythroid-derived 2)-like 2 (NRF2), shuttled to the nucleus, as expected, in response to ACA11-driven increases in ROS; however, transcriptional up-regulation of some of NRF2's antioxidant target genes was abrogated in the presence of ACA11 overexpression. These data show for the first time that ACA11 promotes proliferation through inhibition of NRF2 function resulting in sustained ROS levels driving cancer cell proliferation.-Mahajan, N., Wu, H.-J., Bennett, R. L., Troche, C., Licht, J. D., Weber, J. D., Maggi, L. B., Jr., Tomasson, M. H. Sabotaging of the oxidative stress response by an oncogenic noncoding RNA.

Androgenetic haploid embryonic stem cells produce live transgenic mice.

Haploids and double haploids are important resources for studying recessive traits and have large impacts on crop breeding, but natural haploids are rare in animals. Mammalian haploids are restricted to germline cells and are occasionally found in tumours with massive chromosome loss. Recent success in establishing haploid embryonic stem (ES) cells in medaka fish and mice raised the possibility of using engineered mammalian haploid cells in genetic studies. However, the availability and functional characterization of mammalian haploid ES cells are still limited. Here we show that mouse androgenetic haploid ES (ahES) cell lines can be established by transferring sperm into an enucleated oocyte. The ahES cells maintain haploidy and stable growth over 30 passages, express pluripotent markers, possess the ability to differentiate into all three germ layers in vitro and in vivo, and contribute to germlines of chimaeras when injected into blastocysts. Although epigenetically distinct from sperm cells, the ahES cells can produce viable and fertile progenies after intracytoplasmic injection into mature oocytes. The oocyte-injection procedure can also produce viable transgenic mice from genetically engineered ahES cells. Our findings show the developmental pluripotency of androgenentic haploids and provide a new tool to quickly produce genetic models for recessive traits. They may also shed new light on assisted reproduction.

A computational strategy to adjust for copy number in tumor Hi-C data.

MOTIVATION: The Hi-C technology was designed to decode the three-dimensional conformation of the genome. Despite progress towards more and more accurate contact maps, several systematic biases have been demonstrated to affect the resulting data matrix. Here we report a new source of bias that can arise in tumor Hi-C data, which is related to the copy number of genomic DNA. To address this bias, we designed a chromosome-adjusted iterative correction method called caICB. Our caICB correction method leads to significant improvements when compared with the original iterative correction in terms of eliminating copy number bias. AVAILABILITY AND IMPLEMENTATION: The method is available at https://bitbucket.org/mthjwu/hicapp CONTACT: michor@jimmy.harvard.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Predicting tumor purity from methylation microarray data.

MOTIVATION: In cancer genomics research, one important problem is that the solid tissue sample obtained from clinical settings is always a mixture of cancer and normal cells. The sample mixture brings complication in data analysis and results in biased findings if not correctly accounted for. Estimating tumor purity is of great interest, and a number of methods have been developed using gene expression, copy number variation or point mutation data. RESULTS: We discover that in cancer samples, the distributions of data from Illumina Infinium 450 k methylation microarray are highly correlated with tumor purities. We develop a simple but effective method to estimate purities from the microarray data. Analyses of the Cancer Genome Atlas lung cancer data demonstrate favorable performance of the proposed method. AVAILABILITY AND IMPLEMENTATION: The method is implemented in InfiniumPurify, which is freely available at https://bitbucket.org/zhengxiaoqi/infiniumpurify. CONTACT: xqzheng@shnu.edu.cn or hao.wu@emory.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Formation of a functional maize centromere after loss of centromeric sequences and gain of ectopic sequences.

The maize (Zea mays) B centromere is composed of B centromere-specific repeats (ZmBs), centromere-specific satellite repeats (CentC), and centromeric retrotransposons of maize (CRM). Here we describe a newly formed B centromere in maize, which has lost CentC sequences and has dramatically reduced CRM and ZmBs sequences, but still retains the molecular features of functional centromeres, such as CENH3, H2A phosphorylation at Thr-133, H3 phosphorylation at Ser-10, and Thr-3 immunostaining signals. This new centromere is stable and can be transmitted to offspring through meiosis. Anti-CENH3 chromatin immunoprecipitation sequencing revealed that a 723-kb region from the short arm of chromosome 9 (9S) was involved in the formation of the new centromere. The 723-kb region, which is gene poor and enriched for transposons, contains two abundant DNA motifs. Genes in the new centromere region are still transcribed. The original 723-kb region showed a higher DNA methylation level compared with native centromeres but was not significantly changed when it was involved in new centromere formation. Our results indicate that functional centromeres may be formed without the known centromere-specific sequences, yet the maintenance of a high DNA methylation level seems to be crucial for the proper function of a new centromere.

Insights into salt tolerance from the genome of Thellungiella salsuginea.

Thellungiella salsuginea, a close relative of Arabidopsis, represents an extremophile model for abiotic stress tolerance studies. We present the draft sequence of the T. salsuginea genome, assembled based on ~134-fold coverage to seven chromosomes with a coding capacity of at least 28,457 genes. This genome provides resources and evidence about the nature of defense mechanisms constituting the genetic basis underlying plant abiotic stress tolerance. Comparative genomics and experimental analyses identified genes related to cation transport, abscisic acid signaling, and wax production prominent in T. salsuginea as possible contributors to its success in stressful environments.

Widespread long noncoding RNAs as endogenous target mimics for microRNAs in plants.

Target mimicry is a recently identified regulatory mechanism for microRNA (miRNA) functions in plants in which the decoy RNAs bind to miRNAs via complementary sequences and therefore block the interaction between miRNAs and their authentic targets. Both endogenous decoy RNAs (miRNA target mimics) and engineered artificial RNAs can induce target mimicry effects. Yet until now, only the Induced by Phosphate Starvation1 RNA has been proven to be a functional endogenous microRNA target mimic (eTM). In this work, we developed a computational method and systematically identified intergenic or noncoding gene-originated eTMs for 20 conserved miRNAs in Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa). The predicted miRNA binding sites were well conserved among eTMs of the same miRNA, whereas sequences outside of the binding sites varied a lot. We proved that the eTMs of miR160 and miR166 are functional target mimics and identified their roles in the regulation of plant development. The effectiveness of eTMs for three other miRNAs was also confirmed by transient agroinfiltration assay.

PsRobot: a web-based plant small RNA meta-analysis toolbox.

Small RNAs (smRNAs) in plants, mainly microRNAs and small interfering RNAs, play important roles in both transcriptional and post-transcriptional gene regulation. The broad application of high-throughput sequencing technology has made routinely generation of bulk smRNA sequences in laboratories possible, thus has significantly increased the need for batch analysis tools. PsRobot is a web-based easy-to-use tool dedicated to the identification of smRNAs with stem-loop shaped precursors (such as microRNAs and short hairpin RNAs) and their target genes/transcripts. It performs fast analysis to identify smRNAs with stem-loop shaped precursors among batch input data and predicts their targets using a modified Smith-Waterman algorithm. PsRobot integrates the expression data of smRNAs in major plant smRNA biogenesis gene mutants and smRNA-associated protein complexes to give clues to the smRNA generation and functional processes. Besides improved specificity, the reliability of smRNA target prediction results can also be evaluated by mRNA cleavage (degradome) data. The cross species conservation statuses and the multiplicity of smRNA target sites are also provided. PsRobot is freely accessible at http://omicslab.genetics.ac.cn/psRobot/.

Intratumoral microbiome is associated with gastric cancer prognosis and therapy efficacy.

The role of the intratumoral microbiome in gastric cancer (GC) has not been comprehensively assessed. Here, we explored the relationship between the microbial community and GC prognosis and therapy efficacy. Several cancer-associated microbial characteristics were identified, including increased α-diversity, differential ß-diversity, and decreased Helicobacter pylori abundance. After adjusting for clinical features, prognostic analysis revealed 2 phyla, 14 genera, and 5 species associated with the overall survival of patients with GC. Additionally, 2 phyla, 14 genera, and 6 species were associated with adjuvant chemotherapy (ACT) efficacy in patients with stage II - III GC. Furthermore, we classified GC microbiome structures into three microbial subtypes (MS1, MS2 and MS3) with distinguishing features. The MS1 subtype exhibited high immune activity and enrichment of microbiota related to immunotherapy and butyric acid-producing, as well as potential benefits in immunotherapy. MS2 featured the highest α-diversity and activation of the TFF pathway, MS3 was characterized by epithelial-mesenchymal transition and was associated with poor prognosis and reduced ACT efficacy. Collectively, the results of this study provide valuable insights into the microbial characteristics associated with GC prognosis and therapy efficacy.

CRISPR screens reveal convergent targeting strategies against evolutionarily distinct chemoresistance in cancer.

Resistance to chemotherapy has been a major hurdle that limits therapeutic benefits for many types of cancer. Here we systematically identify genetic drivers underlying chemoresistance by performing 30 genome-scale CRISPR knockout screens for seven chemotherapeutic agents in multiple cancer cells. Chemoresistance genes vary between conditions primarily due to distinct genetic background and mechanism of action of drugs, manifesting heterogeneous and multiplexed routes towards chemoresistance. By focusing on oxaliplatin and irinotecan resistance in colorectal cancer, we unravel that evolutionarily distinct chemoresistance can share consensus vulnerabilities identified by 26 second-round CRISPR screens with druggable gene library. We further pinpoint PLK4 as a therapeutic target to overcome oxaliplatin resistance in various models via genetic ablation or pharmacological inhibition, highlighting a single-agent strategy to antagonize evolutionarily distinct chemoresistance. Our study not only provides resources and insights into the molecular basis of chemoresistance, but also proposes potential biomarkers and therapeutic strategies against such resistance.