Publications by authors named "Zhongming Zhao"

376 Publications

The allergy mediator histamine confers resistanceto immunotherapy in cancer patients via activationof the macrophage histamine receptor H1.

Cancer Cell 2021 Nov 18. Epub 2021 Nov 18.

Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. Electronic address:

Reinvigoration of antitumor immunity remains an unmet challenge. Our retrospective analyses revealed that cancer patients who took antihistamines during immunotherapy treatment had significantly improved survival. We uncovered that histamine and histamine receptor H1 (HRH1) are frequently increased in the tumor microenvironment and induce T cell dysfunction. Mechanistically, HRH1-activated macrophages polarize toward an M2-like immunosuppressive phenotype with increased expression of the immune checkpoint VISTA, rendering T cells dysfunctional. HRH1 knockout or antihistamine treatment reverted macrophage immunosuppression, revitalized T cell cytotoxic function, and restored immunotherapy response. Allergy, via the histamine-HRH1 axis, facilitated tumor growth and induced immunotherapy resistance in mice and humans. Importantly, cancer patients with low plasma histamine levels had a more than tripled objective response rate to anti-PD-1 treatment compared with patients with high plasma histamine. Altogether, pre-existing allergy or high histamine levels in cancer patients can dampen immunotherapy responses and warrant prospectively exploring antihistamines as adjuvant agents for combinatorial immunotherapy.
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http://dx.doi.org/10.1016/j.ccell.2021.11.002DOI Listing
November 2021

Single-cell RNA sequencing reveals a strong connection between upregulation and oncolytic HSV infection in tumor tissue.

Mol Ther Oncolytics 2021 Dec 20;23:330-341. Epub 2021 Oct 20.

Center for Nuclear Receptors and Cell Signaling, Department of Biology and Biochemistry, University of Houston, Houston, TX 77204, USA.

The oncolytic effect of virotherapy derives from the intrinsic capability of the applied virus in selectively infecting and killing tumor cells. Although oncolytic viruses of various constructions have been shown to efficiently infect and kill tumor cells , the efficiency of these viruses to exert the same effect on tumor cells within tumor tissues has not been extensively investigated. Here we report our studies using single-cell RNA sequencing to comprehensively analyze the gene expression profile of tumor tissues following herpes simplex virus 2-based oncolytic virotherapy. Our data revealed the extent and cell types within the tumor microenvironment that could be infected by the virus. Moreover, we observed changes in the expression of cellular genes, including antiviral genes, in response to viral infection. One notable gene found to be upregulated significantly in oncolytic virus-infected tumor cells was , which is desirable for optimal virus replication. These results not only help reveal the precise infection status of the oncolytic virus but also provide insight that may lead to the development of new strategies to further enhance the therapeutic efficacy of oncolytic virotherapy.
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http://dx.doi.org/10.1016/j.omto.2021.10.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573104PMC
December 2021

Comprehensive characterization of tumor immune landscape following oncolytic virotherapy by single-cell RNA sequencing.

Cancer Immunol Immunother 2021 Oct 30. Epub 2021 Oct 30.

Center for Nuclear Receptors and Cell Signaling, Department of Biology and Biochemistry, University of Houston, Houston, TX, 77204, USA.

An important mechanism of oncolytic virotherapy in ameliorating cancer immunotherapy is by inducing significant changes in the immune landscape in the tumor microenvironment (TME). Despite this notion and the potential therapeutic implications, a comprehensive analysis of the immune changes in carcinomas induced by virotherapy has not yet been elucidated. We conducted single-cell RNA sequencing analysis on carcinomas treated with an HSV-2-based oncolytic virus to characterize the immunogenic changes in the TME. We specifically analyzed and compared the immune cell composition between viral treated and untreated tumors. We also applied CellChat to analyze the complex interactions among the infiltrated immune cells. Our data revealed significant infiltration of B cells in addition to other important immune cells, including CD4, CD8, and NK cells following virotherapy. Further analysis identified distinct subset compositions of the infiltrated immune cells and their activation status upon virotherapy. The intensive interactions among the infiltrated immune cells as revealed by CellChat analysis may further shape the immune landscape in favor of generating antitumor immunity. Our findings will facilitate the design of new strategies in incorporating immunotherapy into virotherapy for clinical translation. Moreover, the significant infiltration of B cells makes it suitable for combining virotherapy with immune checkpoint inhibitors.
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http://dx.doi.org/10.1007/s00262-021-03084-2DOI Listing
October 2021

Erratum: Rodriguez et al. Substance P Antagonism as a Novel Therapeutic Option to Enhance Efficacy of Cisplatin in Triple Negative Breast Cancer and Protect PC12 Cells against Cisplatin-Induced Oxidative Stress and Apoptosis. 2021, , 3871.

Cancers (Basel) 2021 Oct 15;13(20). Epub 2021 Oct 15.

Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.

One contributor's name was missing in the original version of the authorship of the paper [...].
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http://dx.doi.org/10.3390/cancers13205178DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8533910PMC
October 2021

Artificial image objects for classification of breast cancer biomarkers with transcriptome sequencing data and convolutional neural network algorithms.

Breast Cancer Res 2021 Oct 10;23(1):96. Epub 2021 Oct 10.

Nevada Institute of Personalized Medicine, University of Nevada Las Vegas, Las Vegas, NV, 89154, USA.

Background: Transcriptome sequencing has been broadly available in clinical studies. However, it remains a challenge to utilize these data effectively for clinical applications due to the high dimension of the data and the highly correlated expression between individual genes.

Methods: We proposed a method to transform RNA sequencing data into artificial image objects (AIOs) and applied convolutional neural network (CNN) algorithms to classify these AIOs. With the AIO technique, we considered each gene as a pixel in an image and its expression level as pixel intensity. Using the GSE96058 (n = 2976), GSE81538 (n = 405), and GSE163882 (n = 222) datasets, we created AIOs for the subjects and designed CNN models to classify biomarker Ki67 and Nottingham histologic grade (NHG).

Results: With fivefold cross-validation, we accomplished a classification accuracy and AUC of 0.821 ± 0.023 and 0.891 ± 0.021 for Ki67 status. For NHG, the weighted average of categorical accuracy was 0.820 ± 0.012, and the weighted average of AUC was 0.931 ± 0.006. With GSE96058 as training data and GSE81538 as testing data, the accuracy and AUC for Ki67 were 0.826 ± 0.037 and 0.883 ± 0.016, and that for NHG were 0.764 ± 0.052 and 0.882 ± 0.012, respectively. These results were 10% better than the results reported in the original studies. For Ki67, the calls generated from our models had a better power for prediction of survival as compared to the calls from trained pathologists in survival analyses.

Conclusions: We demonstrated that RNA sequencing data could be transformed into AIOs and be used to classify Ki67 status and NHG with CNN algorithms. The AIO method could handle high-dimensional data with highly correlated variables, and there was no need for variable selection. With the AIO technique, a data-driven, consistent, and automation-ready model could be developed to classify biomarkers with RNA sequencing data and provide more efficient care for cancer patients.
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http://dx.doi.org/10.1186/s13058-021-01474-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504079PMC
October 2021

Unsupervised Feature Selection Using an Integrated Strategy of Hierarchical Clustering with Singular Value Decomposition: An Integrative Biomarker Discovery Method with Application to Acute Myeloid Leukemia.

IEEE/ACM Trans Comput Biol Bioinform 2021 Sep 8;PP. Epub 2021 Sep 8.

Here we propose a novel unsupervised feature selection by combining hierarchical feature clustering with singular value decomposition (SVD). The proposed algorithm first generates several feature clusters by adopting hierarchical clustering on the feature space and then applies SVD to each of these feature clusters to identify the feature that contributes most to the SVD-entropy. The proposed feature selection method selects an optimal feature subset that not only minimizes the mutual dependency among the selected features but also maximizes mutual dependency of the selected features against their nearest neighbor non-selected features. Each of the selected features also contributes the maximum SVD-entropy among all features of the same feature cluster. The experimental results demonstrate that proposed algorithm performs well against state-of-the-art methods of feature selection in terms of various evaluation criteria. The superiority of the proposed algorithm is demonstrated through analysis of Acute Myeloid Leukemia (AML) multi-omics data that consist of five datasets: gene expression, exon expression, methylation, microRNA, and pathway activity dataset (paradigm IPLs) from The Cancer Genome Atlas (TCGA). Our analysis pinpoints a candidate gene-marker, EREG for AML with an integrative omics evidence. EREG is targeted by two top ranked microRNAs, hsa-miR-1286 and hsa-miR-1976 in the datasets.
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http://dx.doi.org/10.1109/TCBB.2021.3110989DOI Listing
September 2021

siRNA Mediate RNA Interference Concordant with Early On-Target Transient Transcriptional Interference.

Genes (Basel) 2021 08 23;12(8). Epub 2021 Aug 23.

Ingham Institute, School of Psychiatry, University of NSW, Sydney, NSW 2170, Australia.

Exogenous siRNAs are commonly used to regulate endogenous gene expression levels for gene function analysis, genotype-phenotype association studies and for gene therapy. Exogenous siRNAs can target mRNAs within the cytosol as well as nascent RNA transcripts within the nucleus, thus complicating siRNA targeting specificity. To highlight challenges in achieving siRNA target specificity, we targeted an overlapping gene set that we found associated with a familial form of multiple synostosis syndrome type 4 (SYSN4). In the affected family, we found that a previously unknown non-coding gene was disrupted and the adjacent gene was downregulated. Moreover, a conserved long-range enhancer for was found located within which in turn overlapped another gene which we named . In fibroblast cell lines, is transcribed at much higher levels in the opposite (convergent) direction to . siRNA targeting of resulted in post transcriptional gene silencing (PTGS/RNAi) of that peaked at 72 h together with a rapid early increase in the level of both and that peaked and waned after 24 h. These findings indicated the following sequence of events: Firstly, the siRNA designed to target mRNA for RNAi in the cytosol had also caused an early and transient transcriptional interference of in the nucleus; Secondly, the resulting interference of transcription increased the transcription of ; Thirdly, the increased transcription of increased the transcription of . These findings have implications for the design and application of RNA and DNA targeting technologies including siRNA and CRISPR. For example, we used siRNA targeting of to successfully restore levels in the gene therapy of SYNS4 family fibroblasts in culture. To confidently apply gene targeting technologies, it is important to first determine the transcriptional interference effects of the targeting reagent and the targeted gene.
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http://dx.doi.org/10.3390/genes12081290DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8393430PMC
August 2021

Whole-Genome Differentially Hydroxymethylated DNA Regions among Twins Discordant for Cardiovascular Death.

Genes (Basel) 2021 07 29;12(8). Epub 2021 Jul 29.

Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.

Epigenetics is a mechanism underlying cardiovascular disease. It is unknown whether DNA hydroxymethylation is prospectively associated with the risk for cardiovascular death independent of germline and common environment. Male twin pairs middle-aged in 1969-1973 and discordant for cardiovascular death through December 31, 2014, were included. Hydroxymethylation was quantified in buffy coat DNA collected in 1986-1987. The 1893 differentially hydroxymethylated regions (DhMRs) were identified after controlling for blood leukocyte subtypes and age among 12 monozygotic (MZ) pairs (Benjamini-Hochberg False Discovery Rate < 0.01), of which the 102 DhMRs were confirmed with directionally consistent log-fold changes and < 0.01 among additional 7 MZ pairs. These signature 102 DhMRs, independent of the germline, were located on all chromosomes except for chromosome 21 and the Y chromosome, mainly within/overlapped with intergenic regions and introns, and predominantly hyper-hydroxymethylated. A binary linear classifier predicting cardiovascular death among 19 dizygotic pairs was identified and equivalent to that generated from MZ via the 2D transformation. Computational bioinformatics discovered pathways, phenotypes, and DNA motifs for these DhMRs or their subtypes, suggesting that hydroxymethylation was a pathophysiological mechanism underlying cardiovascular death that might be influenced by genetic factors and warranted further investigations of mechanisms of these signature regions in vivo and in vitro.
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http://dx.doi.org/10.3390/genes12081183DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8392630PMC
July 2021

EmptyNN: A neural network based on positive and unlabeled learning to remove cell-free droplets and recover lost cells in scRNA-seq data.

Patterns (N Y) 2021 Aug 20;2(8):100311. Epub 2021 Jul 20.

Therapeutic Innovation Center, Baylor College of Medicine, Houston, TX 77030, USA.

Droplet-based single-cell RNA sequencing (scRNA-seq) has significantly increased the number of cells profiled per experiment and revolutionized the study of individual transcriptomes. However, to maximize the biological signal, robust computational methods are needed to distinguish cell-free from cell-containing droplets. Here, we introduce a novel cell-calling algorithm called EmptyNN, which trains a neural network based on positive-unlabeled learning for improved filtering of barcodes. For benchmarking purposes, we leveraged cell hashing and genetic variation to provide ground truth. EmptyNN accurately removed cell-free droplets while recovering lost cell clusters, and achieved an area under the receiver operating characteristics of 94.73% and 96.30%, respectively. Comparisons to current state-of-the-art cell-calling algorithms demonstrated the superior performance of EmptyNN. EmptyNN was further applied to a single-nucleus RNA sequencing (snRNA-seq) dataset and showed good performance. Therefore, EmptyNN represents a powerful tool to enhance both scRNA-seq and snRNA-seq quality control analyses.
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http://dx.doi.org/10.1016/j.patter.2021.100311DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8369248PMC
August 2021

Artificial image objects for classification of schizophrenia with GWAS-selected SNVs and convolutional neural network.

Patterns (N Y) 2021 Aug 30;2(8):100303. Epub 2021 Jun 30.

Nevada Institute of Personalized Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA.

In this article, we propose a new approach to analyze large genomics data. We considered individual genetic variants as pixels in an image and transformed a collection of variants into an artificial image object (AIO), which could be classified as a regular image by CNN algorithms. Using schizophrenia as a case study, we demonstrate the principles and their applications with 3 datasets. With 4,096 SNVs, the CNN models achieved an accuracy of 0.678 ± 0.007 and an AUC of 0.738 ± 0.008 for the diagnosis phenotype. With 44,100 SNVs, the models achieved class-specific accuracies of 0.806 ± 0.032 and 0.820 ± 0.049, and AUCs of 0.930 ± 0.017 and 0.867 ± 0.040 for the bottom and top classes stratified by the patient's polygenic risk scores. These results suggest that, once transformed to images, large genomics data can be analyzed effectively with image classification algorithms.
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http://dx.doi.org/10.1016/j.patter.2021.100303DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8369164PMC
August 2021

Angiogenic gene networks are dysregulated in opioid use disorder: evidence from multi-omics and imaging of postmortem human brain.

Mol Psychiatry 2021 Aug 12. Epub 2021 Aug 12.

Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA.

Opioid use disorder (OUD) is a public health crisis in the U.S. that causes over 50 thousand deaths annually due to overdose. Using next-generation RNA sequencing and proteomics techniques, we identified 394 differentially expressed (DE) coding and long noncoding (lnc) RNAs as well as 213 DE proteins in Brodmann Area 9 of OUD subjects. The RNA and protein changes converged on pro-angiogenic gene networks and cytokine signaling pathways. Four genes (LGALS3, SLC2A1, PCLD1, and VAMP1) were dysregulated in both RNA and protein. Dissecting these DE genes and networks, we found cell type-specific effects with enrichment in astrocyte, endothelial, and microglia correlated genes. Weighted-genome correlation network analysis (WGCNA) revealed cell-type correlated networks including an astrocytic/endothelial/microglia network involved in angiogenic cytokine signaling as well as a neuronal network involved in synaptic vesicle formation. In addition, using ex vivo magnetic resonance imaging, we identified increased vascularization in postmortem brains from a subset of subjects with OUD. This is the first study integrating dysregulation of angiogenic gene networks in OUD with qualitative imaging evidence of hypervascularization in postmortem brain. Understanding the neurovascular effects of OUD is critical in this time of widespread opioid use.
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http://dx.doi.org/10.1038/s41380-021-01259-yDOI Listing
August 2021

Fostering precision psychiatry through bioinformatics.

Braz J Psychiatry 2021 Aug 9. Epub 2021 Aug 9.

Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston (UTHealth), Houston, TX, USA.

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http://dx.doi.org/10.1590/1516-4446-2021-2083DOI Listing
August 2021

An integrative study of genetic variants with brain tissue expression identifies viral etiology and potential drug targets of multiple sclerosis.

Mol Cell Neurosci 2021 09 17;115:103656. Epub 2021 Jul 17.

Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, USA. Electronic address:

Multiple sclerosis (MS) is a neuroinflammatory disorder leading to chronic disability. Brain lesions in MS commonly arise in normal-appearing white matter (NAWM). Genome-wide association studies (GWAS) have identified genetic variants associated with MS. Transcriptome alterations have been observed in case-control studies of NAWM. We developed a Cross-Dataset Evaluation (CDE) function for our network-based tool, Edge-Weighted Dense Module Search of GWAS (EW_dmGWAS). We applied CDE to integrate publicly available MS GWAS summary statistics of 41,505 cases and controls with collectively 38 NAWM expression samples, using the human protein interactome as the reference network, to investigate biological underpinnings of MS etiology. We validated the resulting modules with colocalization of GWAS and expression quantitative trait loci (eQTL) signals, using GTEx Consortium expression data for MS-relevant tissues: 14 brain tissues and 4 immune-related tissues. Other network assessments included a drug target query and functional gene set enrichment analysis. CDE prioritized a MS NAWM network containing 55 unique genes. The gene list was enriched (p-value = 2.34 × 10) with GWAS-eQTL colocalized genes: CDK4, IFITM3, MAPK1, MAPK3, METTL12B and PIK3R2. The resultant network also included drug signatures of FDA-approved medications. Gene set enrichment analysis revealed the top functional term "intracellular transport of virus", among other viral pathways. We prioritize critical genes from the resultant network: CDK4, IFITM3, MAPK1, MAPK3, METTL12B and PIK3R2. Enriched drug signatures suggest potential drug targets and drug repositioning strategies for MS. Finally, we propose mechanisms of potential MS viral onset, based on prioritized gene set and functional enrichment analysis.
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http://dx.doi.org/10.1016/j.mcn.2021.103656DOI Listing
September 2021

Co-delivery of novel bispecific and trispecific engagers by an amplicon vector augments the therapeutic effect of an HSV-based oncolytic virotherapy.

J Immunother Cancer 2021 07;9(7)

Center for Nuclear Receptors and Cell Signaling, Department of Biology and Biochemistry, University of Houston, Houston, Texas, USA

Background: Although oncolytic virotherapy has shown substantial promises as a new treatment modality for many malignancies, further improvement on its therapeutic efficacy will likely bring more clinical benefits. One plausible way of enhancing the therapeutic effect of virotherapy is to enable it with the ability to concurrently engage the infiltrating immune cells to provide additional antitumor mechanisms. Here, we report the construction and evaluation of two novel chimeric molecules (bispecific chimeric engager proteins, BiCEP and trispecific chimeric engager protein, TriCEP) that can engage both natural killer (NK) and T cells with tumor cells for enhanced antitumor activities.

Methods: BiCEP was constructed by linking orthopoxvirus major histocompatibility complex class I-like protein, which can selectively bind to NKG2D with a high affinity to a mutant form of epidermal growth factor (EGF) that can strongly bind to EGF receptor. TriCEP is similarly constructed except that it also contains a modified form of interleukin-2 that can only function as a tethered form. As NKG2D is expressed on both NK and CD8 T cells, both of which can thus be engaged by BiCEP and TriCEP.

Results: Both BiCEP and TriCEP showed the ability to engage NK and T cells to kill tumor cells in vitro. Coadministration of BiCEP and TriCEP with an oncolytic herpes simplex virus enhanced the overall antitumor effect. Furthermore, single-cell RNA sequencing analysis revealed that TriCEP not only engaged NK and T cells to kill tumor cells, it also promotes the infiltration and activation of these important immune cells.

Conclusions: These novel chimeric molecules exploit the ability of the oncolytic virotherapy in altering the tumor microenvironment with increased infiltration of important immune cells such as NK and T cells for cancer immunotherapy. The ability of BiCEP and TriCEP to engage both NK and T cells makes them an ideal choice for arming an oncolytic virotherapy.
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http://dx.doi.org/10.1136/jitc-2021-002454DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8261877PMC
July 2021

Genome-Wide Correlation of DNA Methylation and Gene Expression in Postmortem Brain Tissues of Opioid Use Disorder Patients.

Int J Neuropsychopharmacol 2021 11;24(11):879-891

Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.

Background: Opioid use disorder (OUD) affects millions of people, causing nearly 50 000 deaths annually in the United States. While opioid exposure and OUD are known to cause widespread transcriptomic and epigenetic changes, few studies in human samples have been conducted. Understanding how OUD affects the brain at the molecular level could help decipher disease pathogenesis and shed light on OUD treatment.

Methods: We generated genome-wide transcriptomic and DNA methylation profiles of 22 OUD subjects and 19 non-psychiatric controls. We applied weighted gene co-expression network analysis to identify genetic markers consistently associated with OUD at both transcriptomic and methylomic levels. We then performed functional enrichment for biological interpretation. We employed cross-omics analysis to uncover OUD-specific regulatory networks.

Results: We found 6 OUD-associated co-expression gene modules and 6 co-methylation modules (false discovery rate <0.1). Genes in these modules are involved in astrocyte and glial cell differentiation, gliogenesis, response to organic substance, and response to cytokine (false discovery rate <0.05). Cross-omics analysis revealed immune-related transcription regulators, suggesting the role of transcription factor-targeted regulatory networks in OUD pathogenesis.

Conclusions: Our integrative analysis of multi-omics data in OUD postmortem brain samples suggested complex gene regulatory mechanisms involved in OUD-associated expression patterns. Candidate genes and their upstream regulators revealed in astrocyte, and glial cells could provide new insights into OUD treatment development.
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http://dx.doi.org/10.1093/ijnp/pyab043DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8598308PMC
November 2021

An Integrative Transcriptomic and Methylation Approach for Identifying Differentially Expressed Circular RNAs Associated with DNA Methylation Change.

Biomedicines 2021 Jun 8;9(6). Epub 2021 Jun 8.

Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.

Recently, accumulating evidence has supported that circular RNA (circRNA) plays important roles in tumorigenesis by regulating gene expression at transcriptional and post-transcriptional levels. Expression of circRNAs can be epigenetically silenced by DNA methylation; however, the underlying regulatory mechanisms of circRNAs by DNA methylation remains largely unknown. We explored this regulation in hepatocellular carcinoma (HCC) using genome-wide DNA methylation and RNA sequencing data of the primary tumor and matched adjacent normal tissues from 20 HCC patients. Our pipeline identified 1012 upregulated and 747 downregulated circRNAs (collectively referred to as differentially expressed circRNAs, or DE circRNAs) from HCC RNA-seq data. Among them, 329 DE circRNAs covered differentially methylated sites (adjusted -value < 0.05, |ΔM| > 0.5) in circRNAs' interior and/or flanking regions. Interestingly, the corresponding parental genes of 46 upregulated and 31 downregulated circRNAs did not show significant expression change in the HCC tumor versus normal samples. Importantly, 34 of the 77 DE circRNAs (44.2%) had significant correlation with DNA methylation change in HCC (Spearman's rank-order correlation, -value < 0.05), suggesting that aberrant DNA methylation might regulate circular RNA expression in HCC. Our study revealed genome-wide differential circRNA expression in HCC. The significant correlation with DNA methylation change suggested that epigenetic regulation might act on both mRNA and circRNA expression. The specific regulation in HCC and general view in other cancer or disease requires further investigation.
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http://dx.doi.org/10.3390/biomedicines9060657DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8227141PMC
June 2021

Genome-wide CRISPR screens reveal cyclin C as synthetic survival target of BRCA2.

Nucleic Acids Res 2021 07;49(13):7476-7491

Department of Experimental Radiation Oncology, Unit 1052, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.

Poly (ADP-ribose) polymerase inhibitor (PARPi)-based therapies initially reduce tumor burden but eventually lead to acquired resistance in cancer patients with BRCA1 or BRCA2 mutation. To understand the potential PARPi resistance mechanisms, we performed whole-genome CRISPR screens to discover genetic alterations that change the gene essentiality in cells with inducible depletion of BRCA2. We identified that several RNA Polymerase II transcription Mediator complex components, especially Cyclin C (CCNC) as synthetic survival targets upon BRCA2 loss. Total mRNA sequencing demonstrated that loss of CCNC could activate the transforming growth factor (TGF)-beta signaling pathway and extracellular matrix (ECM)-receptor interaction pathway, however the inhibition of these pathways could not reverse cell survival in BRCA2 depleted CCNC-knockout cells, indicating that the activation of these pathways is not required for the resistance. Moreover, we showed that the improved survival is not due to restoration of homologous recombination repair although decreased DNA damage signaling was observed. Interestingly, loss of CCNC could restore replication fork stability in BRCA2 deficient cells, which may contribute to PARPi resistance. Taken together, our data reveal CCNC as a critical genetic determinant upon BRCA2 loss of function, which may help the development of novel therapeutic strategies that overcome PARPi resistance.
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http://dx.doi.org/10.1093/nar/gkab540DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8287926PMC
July 2021

Association of CXCR6 with COVID-19 severity: delineating the host genetic factors in transcriptomic regulation.

Hum Genet 2021 Sep 21;140(9):1313-1328. Epub 2021 Jun 21.

Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St. Suite 600, Houston, TX, 77030, USA.

The coronavirus disease 2019 (COVID-19) is an infectious disease that mainly affects the host respiratory system with ~ 80% asymptomatic or mild cases and ~ 5% severe cases. Recent genome-wide association studies (GWAS) have identified several genetic loci associated with the severe COVID-19 symptoms. Delineating the genetic variants and genes is important for better understanding its biological mechanisms. We implemented integrative approaches, including transcriptome-wide association studies (TWAS), colocalization analysis, and functional element prediction analysis, to interpret the genetic risks using two independent GWAS datasets in lung and immune cells. To understand the context-specific molecular alteration, we further performed deep learning-based single-cell transcriptomic analyses on a bronchoalveolar lavage fluid (BALF) dataset from moderate and severe COVID-19 patients. We discovered and replicated the genetically regulated expression of CXCR6 and CCR9 genes. These two genes have a protective effect on lung, and a risk effect on whole blood, respectively. The colocalization analysis of GWAS and cis-expression quantitative trait loci highlighted the regulatory effect on CXCR6 expression in lung and immune cells. In the lung-resident memory CD8 T (T) cells, we found a 2.24-fold decrease of cell proportion among CD8 T cells and lower expression of CXCR6 in the severe patients than moderate patients. Pro-inflammatory transcriptional programs were highlighted in the T cellular trajectory from moderate to severe patients. CXCR6 from the 3p21.31 locus is associated with severe COVID-19. CXCR6 tends to have a lower expression in lung T cells of severe patients, which aligns with the protective effect of CXCR6 from TWAS analysis.
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http://dx.doi.org/10.1007/s00439-021-02305-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8216591PMC
September 2021

Cell-type deconvolution analysis identifies cancer-associated myofibroblast component as a poor prognostic factor in multiple cancer types.

Oncogene 2021 Jul 17;40(28):4686-4694. Epub 2021 Jun 17.

Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.

Cancer-associated fibroblasts (CAFs) constitute a prominent component of the tumor microenvironment and play critical roles in cancer progression and drug resistance. Although recent studies indicate CAFs may consist of several CAF subtypes, the breadth of CAF heterogeneity and functional roles of CAF subtypes in cancer progression remain unclear. In this study, we implemented a cell-type deconvolutional approach to comprehensively characterize cell-type alternations across 18 cancer types from The Cancer Genome Atlas (TCGA). Pan-cancer survival analysis using deconvoluted CAF subtypes revealed myofibroblastic CAF (myCAF) composition as a poor prognostic factor in nine cancer types. Patients with higher myCAF compositions tend to have worse response to six antineoplastic drugs predicted by a lncRNA-based Elastic Net prediction model (LENP). In addition, integrative mutational analysis identified 14 and 413 genes associated with the differentiation degree of myCAF and inflammatory CAF (iCAF), respectively, with significant enrichment of genes involved in fibroblast and extracellular matrix (ECM)-related pathways. In summary, our findings systematically illustrated the complex roles of CAF subtypes in patient prognosis and drug response, and identified putative driver genes in CAF-subtype differentiation. These results provided novel therapeutic perspectives for targeting CAF subtypes in tumor microenvironment and arranging treatment scheme based on the CAF compositions in different cancer types.
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http://dx.doi.org/10.1038/s41388-021-01870-xDOI Listing
July 2021

Identification of microRNAs and gene regulatory networks in cleft lip common in humans and mice.

Hum Mol Genet 2021 Sep;30(19):1881-1893

Department of Diagnostic & Biomedical Sciences, School of Dentistry, The University of Texas Health Science Center at Houston, Houston, TX 77054, USA.

The etiology of cleft lip with/without cleft palate (CL/P), one of the most frequent craniofacial birth defects worldwide, is complicated by contributions of both genetic and environmental factors. Understanding the etiology of these conditions is essential for developing preventive strategies. This study thus aims to identify regulatory networks of microRNAs (miRNAs), transcriptional factors (TFs) and non-TF genes associated with cleft lip (CL) that are conserved in humans and mice. Notably, we found that miR-27b, miR-133b, miR-205, miR-376b and miR-376c were involved in the regulation of CL-associated gene expression in both humans and mice. Among the candidate miRNAs, the overexpression of miR-27b, miR-133b and miR-205, but not miR-376b and miR-376c, significantly inhibited cell proliferation through suppression of CL-associated genes (miR-27b suppressed PAX9 and RARA; miR-133b suppressed FGFR1, PAX7, and SUMO1; and miR-205 suppressed PAX9 and RARA) in cultured human and mouse lip mesenchymal cells. Taken together, our results suggest that elevated expression of miR-27b, miR-133b and miR-205 may play a crucial role in CL through the suppression of genes associated with CL.
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http://dx.doi.org/10.1093/hmg/ddab151DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444451PMC
September 2021

Distinct Murine Pancreatic Transcriptomic Signatures during Chronic Pancreatitis Recovery.

Mediators Inflamm 2021 15;2021:5595464. Epub 2021 May 15.

Department of Surgery, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.

We have previously demonstrated that the pancreas can recover from chronic pancreatitis (CP) lesions in the cerulein-induced mouse model. To explore how pancreatic recovery is achieved at the molecular level, we used RNA-sequencing (seq) and profiled transcriptomes during CP transition to recovery. CP was induced by intraperitoneally injecting cerulein in C57BL/6 mice. Time-matched controls (CON) were given normal saline. Pancreata were harvested from mice 4 days after the final injections (designated as CP and CON) or 4 weeks after the final injections (designated as CP recovery (CPR) and control recovery (CONR)). Pancreatic RNAs were extracted for RNA-seq and quantitative (q) PCR validation. Using RNA-seq, we identified a total of 3,600 differentially expressed genes (DEGs) in CP versus CON and 166 DEGs in CPR versus CONR. There are 132 DEGs overlapped between CP and CPR and 34 DEGs unique to CPR. A number of selected pancreatic fibrosis-relevant DEGs were validated by qPCR. The top 20 gene sets enriched from DEGs shared between CP and CPR are relevant to extracellular matrix and cancer biology, whereas the top 10 gene sets enriched from DEGs specific to CPR are pertinent to DNA methylation and specific signaling pathways. In conclusion, we identified a distinct set of DEGs in association with extracellular matrix and cancer cell activities to contrast CP and CPR. Once during ongoing CP recovery, DEGs relevant to DNA methylation and specific signaling pathways were induced to express. The DEGs shared between CP and CPR and the DEGs specific to CPR may serve as the unique transcriptomic signatures and biomarkers for determining CP recovery and monitoring potential therapeutic responses at the molecular level to reflect pancreatic histological resolution.
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http://dx.doi.org/10.1155/2021/5595464DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8158417PMC
May 2021

Distinct effect of prenatal and postnatal brain expression across 20 brain disorders and anthropometric social traits: a systematic study of spatiotemporal modularity.

Brief Bioinform 2021 Nov;22(6)

Center for Precision Health, School of Biomedical Informatics, the University of Texas Health Science Center at Houston, 7000 Fannin St. Suite 600, Houston, TX 77030, USA.

Different spatiotemporal abnormalities have been implicated in different neuropsychiatric disorders and anthropometric social traits, yet an investigation in the temporal network modularity with brain tissue transcriptomics has been lacking. We developed a supervised network approach to investigate the genome-wide association study (GWAS) results in the spatial and temporal contexts and demonstrated it in 20 brain disorders and anthropometric social traits. BrainSpan transcriptome profiles were used to discover significant modules enriched with trait susceptibility genes in a developmental stage-stratified manner. We investigated whether, and in which developmental stages, GWAS-implicated genes are coordinately expressed in brain transcriptome. We identified significant network modules for each disorder and trait at different developmental stages, providing a systematic view of network modularity at specific developmental stages for a myriad of brain disorders and traits. Specifically, we observed a strong pattern of the fetal origin for most psychiatric disorders and traits [such as schizophrenia (SCZ), bipolar disorder, obsessive-compulsive disorder and neuroticism], whereas increased co-expression activities of genes were more strongly associated with neurological diseases [such as Alzheimer's disease (AD) and amyotrophic lateral sclerosis] and anthropometric traits (such as college completion, education and subjective well-being) in postnatal brains. Further analyses revealed enriched cell types and functional features that were supported and corroborated prior knowledge in specific brain disorders, such as clathrin-mediated endocytosis in AD, myelin sheath in multiple sclerosis and regulation of synaptic plasticity in both college completion and education. Our study provides a landscape view of the spatiotemporal features in a myriad of brain-related disorders and traits.
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http://dx.doi.org/10.1093/bib/bbab214DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8575009PMC
November 2021

DeepFun: a deep learning sequence-based model to decipher non-coding variant effect in a tissue- and cell type-specific manner.

Nucleic Acids Res 2021 07;49(W1):W131-W139

Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.

More than 90% of the genetic variants identified from genome-wide association studies (GWAS) are located in non-coding regions of the human genome. Here, we present a user-friendly web server, DeepFun (https://bioinfo.uth.edu/deepfun/), to assess the functional activity of non-coding genetic variants. This new server is built on a convolutional neural network (CNN) framework that has been extensively evaluated. Specifically, we collected chromatin profiles from ENCODE and Roadmap projects to construct the feature space, including 1548 DNase I accessibility, 1536 histone mark, and 4795 transcription factor binding profiles covering 225 tissues or cell types. With such comprehensive epigenomics annotations, DeepFun expands the functionality of existing non-coding variant prioritizing tools to provide a more specific functional assessment on non-coding variants in a tissue- and cell type-specific manner. By using the datasets from various GWAS studies, we conducted independent validations and demonstrated the functions of the DeepFun web server in predicting the effect of a non-coding variant in a specific tissue or cell type, as well as visualizing the potential motifs in the region around variants. We expect our server will be widely used in genetics, functional genomics, and disease studies.
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http://dx.doi.org/10.1093/nar/gkab429DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262726PMC
July 2021

DeepVISP: Deep Learning for Virus Site Integration Prediction and Motif Discovery.

Adv Sci (Weinh) 2021 05 8;8(9):2004958. Epub 2021 Mar 8.

Center for Precision Health School of Biomedical Informatics The University of Texas Health Science Center at Houston (UTHealth) Houston TX 77030 USA.

Approximately 15% of human cancers are estimated to be attributed to viruses. Virus sequences can be integrated into the host genome, leading to genomic instability and carcinogenesis. Here, a new deep convolutional neural network (CNN) model is developed with attention architecture, namely DeepVISP, for accurately predicting oncogenic virus integration sites (VISs) in the human genome. Using the curated benchmark integration data of three viruses, hepatitis B virus (HBV), human herpesvirus (HPV), and Epstein-Barr virus (EBV), DeepVISP achieves high accuracy and robust performance for all three viruses through automatically learning informative features and essential genomic positions only from the DNA sequences. In comparison, DeepVISP outperforms conventional machine learning methods by 8.43-34.33% measured by area under curve (AUC) value enhancement in three viruses. Moreover, DeepVISP can decode -regulatory factors that are potentially involved in virus integration and tumorigenesis, such as HOXB7, IKZF1, and LHX6. These findings are supported by multiple lines of evidence in literature. The clustering analysis of the informative motifs reveales that the representative k-mers in clusters could help guide virus recognition of the host genes. A user-friendly web server is developed for predicting putative oncogenic VISs in the human genome using DeepVISP.
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http://dx.doi.org/10.1002/advs.202004958DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097320PMC
May 2021

Rewired Pathways and Disrupted Pathway Crosstalk in Schizophrenia Transcriptomes by Multiple Differential Coexpression Methods.

Genes (Basel) 2021 04 29;12(5). Epub 2021 Apr 29.

Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.

Transcriptomic studies of mental disorders using the human brain tissues have been limited, and gene expression signatures in schizophrenia (SCZ) remain elusive. In this study, we applied three differential co-expression methods to analyze five transcriptomic datasets (three RNA-Seq and two microarray datasets) derived from SCZ and matched normal postmortem brain samples. We aimed to uncover biological pathways where internal correlation structure was rewired or inter-coordination was disrupted in SCZ. In total, we identified 60 rewired pathways, many of which were related to neurotransmitter, synapse, immune, and cell adhesion. We found the hub genes, which were on the center of rewired pathways, were highly mutually consistent among the five datasets. The combinatory list of 92 hub genes was generally multi-functional, suggesting their complex and dynamic roles in SCZ pathophysiology. In our constructed pathway crosstalk network, we found "Clostridium neurotoxicity" and "signaling events mediated by focal adhesion kinase" had the highest interactions. We further identified disconnected gene links underlying the disrupted pathway crosstalk. Among them, four gene pairs (, , , and ) were normally correlated in universal contexts. In summary, we systematically identified rewired pathways, disrupted pathway crosstalk circuits, and critical genes and gene links in schizophrenia transcriptomes.
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http://dx.doi.org/10.3390/genes12050665DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8146818PMC
April 2021

Investigating Cellular Trajectories in the Severity of COVID-19 and Their Transcriptional Programs Using Machine Learning Approaches.

Genes (Basel) 2021 04 24;12(5). Epub 2021 Apr 24.

Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.

Single-cell RNA sequencing of the bronchoalveolar lavage fluid (BALF) samples from COVID-19 patients has enabled us to examine gene expression changes of human tissue in response to the SARS-CoV-2 virus infection. However, the underlying mechanisms of COVID-19 pathogenesis at single-cell resolution, its transcriptional drivers, and dynamics require further investigation. In this study, we applied machine learning algorithms to infer the trajectories of cellular changes and identify their transcriptional programs. Our study generated cellular trajectories that show the COVID-19 pathogenesis of healthy-to-moderate and healthy-to-severe on macrophages and T cells, and we observed more diverse trajectories in macrophages compared to T cells. Furthermore, our deep-learning algorithm DrivAER identified several pathways (e.g., xenobiotic pathway and complement pathway) and transcription factors (e.g., MITF and GATA3) that could be potential drivers of the transcriptomic changes for COVID-19 pathogenesis and the markers of the COVID-19 severity. Moreover, macrophages-related functions corresponded more to the disease severity compared to T cells-related functions. Our findings more proficiently dissected the transcriptomic changes leading to the severity of a COVID-19 infection.
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http://dx.doi.org/10.3390/genes12050635DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145325PMC
April 2021

MicroRNA-138 suppresses glioblastoma proliferation through downregulation of CD44.

Sci Rep 2021 04 28;11(1):9219. Epub 2021 Apr 28.

Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, 6431 Fannin St., MSE R117B, Houston, TX, 77030, USA.

Tumor suppressive microRNAs (miRNAs) are increasingly implicated in the development of anti-tumor therapy by reprogramming gene network that are aberrantly regulated in cancer cells. This study aimed to determine the therapeutic potential of putative tumor suppressive miRNA, miR-138, against glioblastoma (GBM). Whole transcriptome and miRNA expression profiling analyses on human GBM patient tissues identified miR-138 as one of the significantly downregulated miRNAs with an inverse correlation with CD44 expression. Transient overexpression of miR-138 in GBM cells inhibited cell proliferation, cell cycle, migration, and wound healing capability. We unveiled that miR-138 negatively regulates the expression of CD44 by directly binding to the 3' UTR of CD44. CD44 inhibition by miR-138 resulted in an inhibition of glioblastoma cell proliferation in vitro through cell cycle arrest as evidenced by a significant induction of p27 and its translocation into nucleus. Ectopic expression of miR-138 also increased survival rates in mice that had an intracranial xenograft tumor derived from human patient-derived primary GBM cells. In conclusion, we demonstrated a therapeutic potential of tumor suppressive miR-138 through direct downregulation of CD44 for the treatment of primary GBM.
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http://dx.doi.org/10.1038/s41598-021-88615-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080729PMC
April 2021

White matter deficits in cocaine use disorder: convergent evidence from in vivo diffusion tensor imaging and ex vivo proteomic analysis.

Transl Psychiatry 2021 04 29;11(1):252. Epub 2021 Apr 29.

Developmental Cognitive Neuroscience Lab (DCNL), Brain Institute, Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil.

White matter (WM) abnormalities in patients with cocaine use disorder (CUD) have been studied; however, the reported effects on the human brain are heterogenous and most results have been obtained from male participants. In addition, biological data supporting the imaging findings and revealing possible mechanisms underlying the neurotoxic effects of chronic cocaine use (CU) on WM are largely restricted to animal studies. To evaluate the neurotoxic effects of CU in the WM, we performed an in vivo diffusion tensor imaging assessment of male and female cocaine users (n = 75) and healthy controls (HC) (n = 58). Moreover, we performed an ex vivo large-scale proteomic analysis using liquid chromatography-tandem mass spectrometry in postmortem brains of patients with CUD (n = 8) and HC (n = 12). Compared with the HC, the CUD group showed significant reductions in global fractional anisotropy (FA) (p < 0.001), and an increase in global mean (MD) and radial diffusion (RD) (both p < 0.001). The results revealed that FA, RD, and MD alterations in the CUD group were widespread along the major WM tracts, after analysis using the tract-based special statistics approach. Global FA was negatively associated with years of CU (p = 0.0421) and female sex (p < 0.001), but not with years of alcohol or nicotine use. Concerning the fibers connecting the left to the right prefrontal cortex, Brodmann area 9 (BA9), the CUD group presented lower FA (p = 0.006) and higher RD (p < 0.001) values compared with the HC group. A negative association between the duration of CU in life and FA values in this tract was also observed (p = 0.019). Proteomics analyses in BA9 found 11 proteins differentially expressed between cocaine users and controls. Among these, were proteins related to myelination and neuroinflammation. In summary, we demonstrate convergent evidence from in vivo diffusion tensor imaging and ex vivo proteomics analysis of WM disruption in CUD.
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http://dx.doi.org/10.1038/s41398-021-01367-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8081729PMC
April 2021

Estrogen-related receptor α is involved in angiogenesis and skeletal muscle revascularization in hindlimb ischemia.

FASEB J 2021 05;35(5):e21480

Brown Foundation Institute of Molecular Medicine, McGovern Medical School, UTHealth, Houston, TX, USA.

Skeletal muscle ischemia is a major consequence of peripheral arterial disease (PAD) or critical limb ischemia (CLI). Although therapeutic options for resolving muscle ischemia in PAD/CLI are limited, the issue is compounded by poor understanding of the mechanisms driving muscle vascularization. We found that nuclear receptor estrogen-related receptor alpha (ERRα) expression is induced in murine skeletal muscle by hindlimb ischemia (HLI), and in cultured myotubes by hypoxia, suggesting a potential role for ERRα in ischemic response. To test this, we generated skeletal muscle-specific ERRα transgenic (TG) mice. In these mice, ERRα drives myofiber type switch from glycolytic type IIB to oxidative type IIA/IIX myofibers, which are typically associated with more vascular supply in muscle. Indeed, RNA sequencing and functional enrichment analysis of TG muscle revealed that "paracrine angiogenesis" is the top-ranked transcriptional program activated by ERRα in the skeletal muscle. Immunohistochemistry and angiography showed that ERRα overexpression increases baseline capillarity, arterioles and non-leaky blood vessel formation in the skeletal muscles. Moreover, ERRα overexpression facilitates ischemic neo-angiogenesis and perfusion recovery in hindlimb musculature of mice subjected to HLI. Therefore, ERRα is a hypoxia inducible nuclear receptor that is involved in skeletal muscle angiogenesis and could be potentially targeted for treating PAD/CLI.
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http://dx.doi.org/10.1096/fj.202001794RRDOI Listing
May 2021

Progression of prostate carcinoma is promoted by adipose stromal cell-secreted CXCL12 signaling in prostate epithelium.

NPJ Precis Oncol 2021 Mar 22;5(1):26. Epub 2021 Mar 22.

The Brown Foundation Institute of Molecular Medicine for the Prevention of Disease, The University of Texas Health Sciences Center at Houston, Houston, TX, USA.

Aggressiveness of carcinomas is linked with tumor recruitment of adipose stromal cells (ASC), which is increased in obesity. ASC promote cancer through molecular pathways not fully understood. Here, we demonstrate that epithelial-mesenchymal transition (EMT) in prostate tumors is promoted by obesity and suppressed upon pharmacological ASC depletion in HiMyc mice, a spontaneous genetic model of prostate cancer. CXCL12 expression in tumors was associated with ASC recruitment and localized to stromal cells expressing platelet-derived growth factor receptors Pdgfra and Pdgfrb. The role of this chemokine secreted by stromal cells in cancer progression was further investigated by using tissue-specific knockout models. ASC deletion of CXCL12 gene in the Pdgfr + lineages suppressed tumor growth and EMT, indicating stroma as the key source of CXCL12. Clinical sample analysis revealed that CXCL12 expression by peritumoral adipose stroma is increased in obesity, and that the correlating increase in Pdgfr/CXCL12 expression in the tumor is linked with decreased survival of patients with prostate carcinoma. Our study establishes ASC as the source of CXCL12 driving tumor aggressiveness and outlines an approach to treatment of carcinoma progression.
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http://dx.doi.org/10.1038/s41698-021-00160-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985375PMC
March 2021
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