Genome Gene Expression Profiling Research Articles

The genetic and epigenetic basis of distinct melanoma types.

Melanoma represents the deadliest skin cancer. Recent therapeutic developments, including targeted and immune therapies have revolutionized clinical management and improved patient outcome. This progress was achieved by rigorous molecular and functional studies followed by robust clinical trials. The identification of key genomic alterations and gene expression profiles have propelled the understanding of distinct characteristics within melanoma subtypes. The aim of this review is to summarize and highlight the main genetic and epigenetic findings of melanomas and highlight their pathological and therapeutic importance.

Bioinformatics Analysis Identifies IL6ST as a Potential Tumor Suppressor Gene for Triple-Negative Breast Cancer.

Improved insight into the molecular mechanisms of triple-negative breast cancer (TNBC) is required to predict prognosis and develop a new therapeutic strategy for targeted genes. The aim of this study was to identify genes significantly associated with TNBC and further analyze their prognostic significance. The Cancer Genome Atlas (TCGA) TNBC database and gene expression profiles of GSE76275 from Gene Expression Omnibus (GEO) were used to explore differentially co-expressed genes in TNBC compared with those in normal tissues and non-TNBC breast cancer tissues. Differential gene expression and weighted gene co-expression network analyses identified 24 differentially co-expressed genes. Functional annotation suggested that these genes were primarily enriched in processes such as metabolism, membrane, and protein binding. The protein-protein interaction (PPI) network further identified ten hub genes, five of which (MAPT, CBS, SOX11, IL6ST, and MEX3A) were confirmed to be differentially expressed in an independent dataset (GSE38959). Moreover, CBS and MEX3A expression was upregulated, whereas IL6ST expression was downregulated in TNBC tissues compared to that in other breast cancer subtypes. Furthermore, lower expression of IL6ST was associated with worse overall survival in patients with TNBC. Thus, IL6ST might play an important role in TNBC progression and could serve as a tumor suppressor gene for diagnosis and treatment.

Genetic Analysis of Multiple Myeloma Identifies Cytogenetic Alterations Implicated in Disease Complexity and Progression.

Simple SummaryMultiple myeloma (MM) is the second most common hematological neoplasia with a high incidence in elderly populations. The disease is characterized by a severe chaos of genomic abnormality. Comprehensive examinations of myeloma cytogenetics are needed for better understanding of MM and potential application to the development of novel therapeutic regiments. Here we utilized gene expression profiling and CytoScan HD genomic arrays to investigate molecular alterations in myeloma leading to disease progression and poor clinical outcomes. We demonstrates that genetic abnormalities within MM patients exhibit unique protein network signatures that can be exploited for implementation of existing therapies targeting key pathways and the development of novel therapeutics.Multiple myeloma (MM) is a genetically heterogeneous disease characterized by genomic chaos making it difficult to distinguish driver from passenger mutations. In this study, we integrated data from whole genome gene expression profiling (GEP) microarrays and CytoScan HD high-resolution genomic arrays to integrate GEP with copy number variations (CNV) to more precisely define molecular alterations in MM important for disease initiation, progression and poor clinical outcome. We utilized gene expression arrays from 351 MM samples and CytoScan HD arrays from 97 MM samples to identify eight CNV events that represent possible MM drivers. By integrating GEP and CNV data we divided the MM into eight unique subgroups and demonstrated that patients within one of the eight distinct subgroups exhibited common and unique protein network signatures that can be utilized to identify new therapeutic interventions based on pathway dysregulation. Data also point to the central role of 1q gains and the upregulated expression of ANP32E, DTL, IFI16, UBE2Q1, and UBE2T as potential drivers of MM aggressiveness. The data presented here utilized a novel approach to identify potential driver CNV events in MM, the creation of an improved definition of the molecular basis of MM and the identification of potential new points of therapeutic intervention.

Upregulation of ubiquitin-conjugating enzyme E2T (UBE2T) predicts poor prognosis and promotes hepatocellular carcinoma progression

ABSTRACT Reportedly, ubiquitin-conjugating enzyme E2T (UBE2T) is closely related to the progression of several malignancies. This work is aimed to probe the role of UBE2T in the progression of hepatocellular carcinoma (HCC) patients. The microarray analysis was executed to screen the differentially expressed genes (DEGs) in HCC tissues. The Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA2) databases, PCR and immunohistochemistry were utilized to validate the dysregulation of UBE2T in HCC. Kaplan-Meier analysis was employed to determine the relationship between UBE2T expression and the prognosis of HCC patients. PCR was carried out to detect UBE2T protein expression in HCC cell lines. Cell Counting Kit-8 (CCK-8) assay and 5-bromo-2ʹ-deoxyuridine (BrdU) experiments were conducted to examine the proliferation of HCC cells. Scratch healing and Transwell experiments were conducted to examine the migration of HCC cells. Bioinformatics analysis and dual-luciferase reporter gene experiments predicted and validated the targeting relationship with miR-212-5p and UBE2T. We found that UBE2T expression was remarkably up-modulated in HCC tissues and cell lines, and its high expression was linked to a worse prognosis in HCC patients. UBE2T overexpression enhanced HCC cell proliferation and migration. Additionally, UBE2T was verified as a downstream target of miR-212-5p. In conclusion, UBE2T overexpression is markedly linked to unfavorable prognosis in HCC patients. UBE2T, regulated by miR-212-5p, significantly enhances the malignant phenotypes of HCC cells, which can be used as a target for HCC diagnosis and prognosis.

Expression and prognostic analyses of the insulin-like growth factor 2 mRNA binding protein family in human pancreatic cancer

BackgroundDespite advances in early diagnosis and treatment, cancer remains the leading cause of mortality worldwide. The insulin-like growth factor 2 mRNA binding protein (IGF2BP) family has been reported to be involved in a variety of human malignant tumours. However, little is known about their expression and prognostic value in human pancreatic cancer. Therefore, we performed a detailed cancer versus normal differential analysis.MethodsThe Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases were used to analyse the mRNA expression levels of the IGF2BP family in various cancers, including pancreatic cancer. Then, the LinkedOmics and GEPIA databases were used to assess the relation between the expression levels of IGF2BPs and overall survival (OS). Then, univariate and multivariate Cox regression analyses were performed, and subgroups based on grade and stage were analysed. The signalling pathways associated with IGF2BP2 and IGF2BP3 were then investigated via gene set enrichment analysis (GSEA).ResultsIGF2BP2 and IGF2BP3 were associated with each subset of OS based on grade and stage. Further clinical correlation analysis of IGF2BP2 and IGF2BP3 confirmed that IGF2BP2 and IGF2BP3 are fundamental factors in promoting pancreatic cancer progression.ConclusionIGF2BP2 and IGF2BP3 are key factors in promoting the progression of pancreatic cancer and are closely related to overall survival.

Cancer Stem Cell Markers in Relation to Patient Survival Outcomes: Lessons for Integrative Diagnostics and Next-Generation Anticancer Drug Development.

Solid tumors display a complex biology that requires a multipronged treatment strategy. Most anticancer interventions, including chemotherapy, are currently unable to prevent treatment resistance and relapse. In general, therapeutics target cancer cells and overlook the tumor microenvironment (TME) and the presence of cancer stem cells (CSCs) with self-renewal and tumorigenic abilities. CSCs have been postulated to play key roles in tumor initiation, progression, therapy resistance, and metastasis. Hence, CSC markers have been suggested as diagnostics to forecast cancer prognosis as well as molecular targets for new-generation cancer treatments, especially in resistant disease. We report here original findings on expression and prognostic significance of CSC markers in several cancers. We examined and compared the transcriptional expression of CSC markers (ABCB1, ABCG2, ALDH1A1, CD24, CD44, CD90, CD133, CXCR4, EPCAM, ICAM1, and NES) in tumor tissues versus the adjacent normal tissues using publicly available databases, The Cancer Genome Atlas and Gene Expression Profiling Interactive Analysis. We found that CSC transcriptional markers were, to a large extent, expressed in higher abundance in solid tumors such as colon, lung, pancreatic, and esophageal cancers. On the other hand, no CSC marker in our analysis was expressed in the same pattern in all cancers, while individual CSC marker expression, alone, was not significantly associated with overall patient survival. Innovation in next-generation cancer therapeutics and diagnostics ought to combine CSC markers as well as integrative diagnostics that pool knowledge from CSCs and other TME components and cancer cells.

Whole Genome DNA Methylation and Gene Expression Profiling of Oropharyngeal Cancer Patients in North-Eastern India: Identification of Epigenetically Altered Gene Expression Reveals Potential Biomarkers.

Oropharyngeal cancer is a subtype of head and neck squamous cell carcinoma that is associated with unique risk exposures like consumption of smokeless tobacco and areca nut and is highly prevalent in the northeastern region of India, especially Meghalaya. However, the underlying epigenetic and transcriptomic changes in this cancer type is yet to be delineated. We have undertaken a study on genome wide somatic alterations in the DNA methylation and transcriptome in oropharyngeal cancer patients from this region using genome wide techniques in paired tumors and adjacent normal tissues. By using integrative approaches, we have identified 194 epigenetically silenced and 241 epigenetically overexpressed genes in the tumor tissue of these patients. Pathways that are significantly enriched by these genes include the pathways of immune systems, such as the interleukin signaling pathways and Toll-like receptor signaling pathway. Also, osteoclast differentiation pathway was found to be epigenetically upregulated. The pathways enriched by the epigenetically downregulated genes were found to be predominantly those involved in xenobiotic metabolism and keratinization. Two major transcription factors – SPI1 and RUNX1 were identified as epigenetically dysregulated, which further modulates 129 downstream genes. Comparison of our observations with the head and neck cancer data from TCGA revealed distinct DNA methylation and gene expression landscapes which might be specific for oropharyngeal cancer. HPV DNA sequences were not detected in any of the tumor samples in RNA-Seq data. The results obtained in this study might provide improved understanding of the disease.

BUB1B promotes hepatocellular carcinoma progression via activation of the mTORC1 signaling pathway.

Background and AimsAccumulating studies identified that BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) is integrally involved in the initiation and development of tumors. Nevertheless, the precise biological role and underlying mechanisms of BUB1B in hepatocellular carcinoma (HCC) remain indistinct.MethodTo figure out the role of BUB1B in HCC, we first assessed its expression using The Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases. We then verified BUB1B expression in HCC tissues, nontumor tissues, and HCC cell lines through western blotting, quantitative reverse transcription‐polymerase chain reaction, and immunohistochemistry. To explore the specific function of BUB1B in HCC in vivo and in vitro, we performed the flow cytometry, Cell Counting Kit‐8, 5‐ethynyl‐2′‐deoxyuridine incorporation, colony formation, Transwell, wound‐healing, subcutaneous tumor growth, and metastasis assays. Additionally, we identified the BUB1B‐regulated pathways involved in HCC by using gene set enrichment analysis.ResultsOur data displayed that higher BUB1B expression was detected in HCC tissues and HCC cell lines. The overexpression of BUB1B was positively correlated with adverse clinicopathological characteristics. Survival analyses showed that lower recurrence‐free and overall survival rates were correlated with the overexpression of BUB1B in patients with HCC. Moreover, the malignancy of HCC was facilitated by BUB1B both in vivo and in vitro. Lastly, the results were confirmed by western blots, which showed that BUB1B upregulated mTORC1 signaling pathway in HCC. Meanwhile, the oncogenic effect of BUB1B will be impaired when the mTORC1 signaling pathway was inhibited by rapamycin.ConclusionWe highlighted that BUB1B played an oncogenic role in HCC and was identified as a possible clinical prognostic factor and a potential novel therapeutic target for HCC.

Identification of Prostate Cancer-Related Circular RNA Through Bioinformatics Analysis.

BackgroundProstate cancer (PCa) is one of the most common malignant tumors worldwide. Accumulating evidence has suggested that circular RNAs (circRNAs) are involved in the development and progression of various cancers, and they show great potential as novel biomarkers. However, the underlying mechanisms and specific functions of most circRNAs in PCa remain unknown. Here, we aimed to identify circRNAs with potential roles in PCa from the PCa expression profile.MethodsWe used data downloaded from the Gene Expression Omnibus to identify circRNAs that were differentially expressed between PCa samples and adjacent non-tumor samples. Relative expression levels of identified circRNAs were validated by quantitative real-time PCR. Micro (mi)RNA response elements were predicted by the CircInteractome database, and miRNA target genes were predicted by miRDB, miRTarBase, and TargetScan databases. Gene ontology (GO) enrichment analysis and pathway analysis revealed the potential biological and functional roles of these target genes. A circRNA–miRNA–mRNA interaction network was constructed by Cytoscape. The interaction between circRNAs and miRNAs in PCa was thoroughly reviewed in the PubMed. Finally, the mRNA expression of these genes was validated by the Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases. The expression of proteins encoded by these genes was further validated by the Human protein Atlas (HPA) database.ResultsA total of 60 circRNAs that were differentially expressed between PCa and healthy samples were screened, of which 15 were annotated. Three circRNAs (hsa_circ_0024353, hsa_circ_0085494, hsa_circ_0031408) certified the criteria were studied. The results of quantitative real-time PCR demonstrated that the expression of hsa_circ_0024353 was significantly downregulated in PC-3 cells when compared with RWPE-1 cells, while the expression of hsa_circ_0031408 and hsa_circ_0085494 was significantly upregulated in PC-3 cells when compared with RWPE-1 cells. GO and Kyoto Encyclopedia of Genes and Genomes analyses found that target genes were mainly enriched in metabolic processes and pathways involving phosphoinositide 3-kinase-Akt signaling, hypoxia-inducible factor-1 signaling, p53 signaling, and the cell cycle. A total of 11 miRNA target genes showing differential expression between PCa and healthy samples were selected, and their mRNA and protein expression were validated by GEPIA and HPA databases, respectively. Of these, PDE7B, DMRT2, and TGFBR3 were identified as potentially playing a role in PCa progression. Finally, three circRNA–miRNA–mRNA interaction axes were predicted by bioinformatics: hsa_circ_0024353–hsa-miR-940–PDE7B, hsa_circ_0024353–hsa-miR-1253–DMRT2, and hsa_circ_0085494–hsa-miR-330-3p–TGFBR3.ConclusionThis study identified three circRNA–miRNA–mRNA interaction axes that might provide novel insights into the potential mechanisms underlying PCa development.

Genomics of Peripheral T-Cell Lymphoma and Its Implications for Personalized Medicine.

Peripheral T-cell lymphoma (PTCL) is a rare, heterogenous group of mature T-cell neoplasms that comprise 10–15% of non-Hodgkin lymphoma cases in the United States. All subtypes of PTCL, except for ALK+ anaplastic T-cell lymphoma, are associated with poor prognosis, with median overall survival (OS) rates of 1–3 years. The diagnosis of PTCL is mainly based on clinical presentation, morphologic features, and immunophenotypes. Recent advances in genome sequencing and gene expression profiling have given new insights into the pathogenesis and molecular biology of PTCL. An enhanced understanding of its genomic landscape holds the promise of refining the diagnosis, prognosis, and management of PTCL. In this review, we examine recently discovered genetic abnormalities identified by molecular profiling in 3 of the most common types of PTCL: RHOAG17V and epigenetic regulator mutations in angioimmunoblastic T-cell lymphoma, ALK expression and JAK/STAT3 pathway mutations in anaplastic T-cell lymphoma, and T-follicular helper phenotype and GATA3/TBX21 expression in PTCL-not otherwise specified. We also discuss the implications of these abnormalities for clinical practice, new/potential targeted therapies, and the role of personalized medicine in the management of PTCL.

Blood-based multi-tissue gene expression inference with Bayesian ridge regression

Gene expression profiling is widely used in basic and cancer research but still not feasible in many clinical applications because tissues, such as brain samples, are difficult and not ethnical to collect. Gene expression in uncollected tissues can be computationally inferred using genotype and expression quantitative trait loci. No methods can infer unmeasured gene expression of multiple tissues with single tissue gene expression profile as input. Here, we present a Bayesian ridge regression-based method (B-GEX) to infer gene expression profiles of multiple tissues from blood gene expression profile. For each gene in a tissue, a low-dimensional feature vector was extracted from whole blood gene expression profile by feature selection. We used GTEx RNAseq data of 16 tissues to train inference models to capture the cross-tissue expression correlations between each target gene in a tissue and its preselected feature genes in peripheral blood. We compared B-GEX with least square regression, LASSO regression and ridge regression. B-GEX outperforms the other three models in most tissues in terms of mean absolute error, Pearson correlation coefficient and root-mean-squared error. Moreover, B-GEX infers expression level of tissue-specific genes as well as those of non-tissue-specific genes in all tissues. Unlike previous methods, which require genomic features or gene expression profiles of multiple tissues, our model only requires whole blood expression profile as input. B-GEX helps gain insights into gene expressions of uncollected tissues from more accessible data of blood. B-GEX is available at https://github.com/xuwenjian85/B-GEX. Supplementary data are available at Bioinformatics online.

Upregulated Expression of TUBA1C Predicts Poor Prognosis and Promotes Oncogenesis in Pancreatic Ductal Adenocarcinoma via Regulating the Cell Cycle

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant disease and has the worst prognosis and survival rate. TUBA1C is a microtubule component implicated in multiple cancers, however, the clinical significance and biological functions of TUBA1C in the progression of PDAC remain unexplored.Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) data were employed to detect the TUBA1C mRNA expression and the relation between TUBA1C expression and overall survival (OS) in PDAC. Then, bioinformatic analysis was employed to determine the potential pathway and genes related to TUBA1C. Human pancreatic cancer tissue and adjacent non-tumor tissues samples were detected by immunochemistry (IHC) staining, and the correlation between TUBA1C expression and the clinicopathological features were investigated. Meanwhile, TUBA1C expression in PDAC cell lines was evaluated by western blotting. Furthermore, functional assays including cell viability, apoptosis, cell cycle, transwell assay, wound healing assay, and a xenograft tumor model were performed to determine the oncogenic role of TUBA1C in PDAC, respectively.Results: TUBA1C was overexpressed in the PDAC tissues and cells. IHC analysis showed that the TUBA1C overexpression was associated with short OS. Bioinformatic analysis indicated that TUBA1C overexpression was mainly associated with cell cycle regulation. The downregulation of TUBA1C significantly suppressed cell proliferation, induced cell apoptosis and cycle arrest, and inhibited invasion and migration in PDAC cells. Furthermore, TUBA1C downregulation also inhibited tumor growth in vivo.Conclusion: These findings suggested that TUBA1C downregulation suppressed PDAC aggressiveness via cell cycle pathway and that TUBA1C may serve as a potential prognostic marker for PDAC therapy.

Identification of hub genes associated with outcome of clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is one of the most common tumor types of the urinary system. Bioinformatics tools have been used to identify new biomarkers of ccRCC and to explore the mechanisms underlying development and progression of ccRCC. The present study analyzed the differentially expressed genes (DEGs) associated with RCC using data obtained from Gene Expression Omnibus datasets and GEO2R software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of these DEGs was performed and analyzed using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes to identify the hub genes, defined as the genes with the highest degree of interrelation. Subsequently, differential expression and survival analyses of hub genes was performed using The Cancer Genome Atlas database and Gene Expression Profiling Interactive Analysis (GEPIA) online tool. Using GEO2R, 1,650 DEGs were identified, including 743 upregulated and 907 downregulated genes. GO and KEGG pathway analyses indicated that the upregulated DEGs were primarily involved in blood vessel and vasculature development, whereas downregulated DEGs were primarily involved in organic acid metabolic processes and carboxylic acid metabolic processes. Subsequently, important modules were identified in the PPI network using Cytoscape's Molecular Complex Detection. The 15 most connected hub genes were identified among DEGs, including glycine decarboxylase (GLDC), enolase 2 (ENO2) and topoisomerase II alpha. GEPIA revealed the association between expression levels of hub genes and survival. Specifically, GLDC and ENO2 were associated with the prognosis of patients with RCC and thus, the effects of GLDC and ENO2 involvement in renal cancer were investigated in vitro. GLDC and ENO2 affected the proliferation and apoptosis of renal cancer cells. These hub genes may reveal a new mechanism underlying development or progression of RCC and identify new markers for its diagnosis and prognosis.

Multicomponent Analysis in Head and Neck Squamous Cancer: Based on Genome, Epigenome and Transcriptome

In recent years, with the rapid development and application of a series of high-throughput proteomics technologies such as gene chip, high-throughput sequencing, and mass spectrometry, people have a more comprehensive and systematic understanding of diseases (including tumors) at genome, transcriptome, proteome and metabolome levels. The research papers on genome sequencing and gene expression profiling of head and neck tumors are increasing year by year, which provides a lot of basic data for revealing the pathogenesis of tumors and excavating new biomarkers. Although there are some articles on the joint analysis of multi-genomics, most of them are based on the speculation of coding amino acid mutations based on gene expression patterns and gene mutations. In this study, our analysis revealed four distinct head and neck squamous cancer (HNSC) subtypes through genome, epigenome and transcriptome data, which provides the possibility for molecular pathological diagnosis, subtyping, invasion and metastasis, chemoradiotherapy resistance and tumor heterogeneity of head and neck tumors. Funding: The work was supported by The Natural Science Youth Founds of Jiangxi Province (no.2016BAB215249), The Natural Science Foundation of Fujian Province (no. 2015J01512), The Middle- and Young-Aged Key Personnel Projects of Fujian Provincial Health and Family Planning Commission, China (no. 2015-ZQN-JC-39). Declaration of Interest: The authors declare that they have no competing interests. Ethical Approval: It is considered by the Ethic Committee of the Quanzhou First Hospital Affiliated to Fujian Medical University, The experimental design and scheme of this study fully considered the principle of safety and fairness, this study does not cause harm or risk to the study subjects. The subjects will be based on the principle of voluntariness, the right to know is guaranteed, protect the interests and privacy of research subjects to the maximum extent, There is no conflict of interest between the research results and the research content. Ethics Committee agrees the program to carry out as planned (No. [2019] 109).

Comparative Gene Expression Profiling of Tobacco-Associated HPV-Positive versus Negative Oral Squamous Carcinoma Cell Lines.

Background: HPV-positive oral squamous cell carcinomas (OSCCs) are specific biological and clinical entities, characterized by a more favorable prognosis compared to HPV-negative OSCCs and occurring generally in non-smoking and non-drinking younger individuals. However, poor information is available on the molecular and the clinical behavior of HPV-positive oral cancers occurring in smoking/drinking subjects. Thus, this study was designed to compare, at molecular level, two OSCC cell lines, both derived from drinking and smoking individuals and differing for presence/absence of HPV infection.Methods: HPV-negative UPCI-SCC-131 and HPV16-positive UPCI-SCC-154 cell lines were compared by whole genome gene expression profiling and subsequently studied for activation of Wnt/βCatenin signaling pathway by the expression of several Wnt-target genes, βCatenin intracellular localization, stem cell features and miRNA let-7e. Gene expression data were validated in head and neck squamous cell carcinoma (HNSCC) public datasets.Results: Gene expression analysis identified Wnt/βCatenin pathway as the unique signaling pathway more active in HPV-negative compared to HPV-positive OSCC cells and this observation was confirmed upon evaluation of several Wnt-target genes (i.e., Cyclin D1, Cdh1, Cdkn2a, Cd44, Axin2, c-Myc and Tcf1). Interestingly, HPV-negative OSCC cells showed higher levels of total βCatenin and its active form, increase of its nuclear accumulation and more prominent stem cell traits. Furthermore, miRNA let-7e was identified as potential upstream regulator responsible for the downregulation of Wnt/βCatenin signaling cascade since its silencing in UPCI-SCC-154 cell resulted in upregulation of Wnt-target genes. Finally, the analysis of two independent gene expression public datasets of human HNSCC cell lines and tumors confirmed that Wnt/βCatenin pathway is more active in HPV-negative compared to HPV-positive tumors derived from individuals with smoking habit.Conclusions: These data suggest that lack of HPV infection is associated with more prominent activation of Wnt/βCatenin signaling pathway and gain of stem-like traits in tobacco-related OSCCs.

Tandem CAR-T cells targeting CD70 and B7-H3 exhibit potent preclinical activity against multiple solid tumors.

Purpose: Given that heterogeneous expression and variants of antigens on solid tumors are responsible for relapse after chimeric antigen receptor (CAR)-T cell therapy, we hypothesized that combinatorial targeting two tumor-associated antigens would lessen this problem and enhance the antitumor activity of T cells.Methods: The co-expression level of CD70 and B7-H3 was analyzed in multiple tumor tissue samples. Further, two putative antigens were identified in The Cancer Genome Atlas and Gene Expression Profiling Interactive Analysis database. Two CD70 targeted CARs with different antigen binding domain, truncated CD27 and CD70 specific single-chain antibody fragment (scFv), were designed to screen a more suitable target-antigen binding moiety. Accordingly, we designed a bivalent tandem CAR (TanCAR) and further assessed the anti-tumor efficacy of TanCAR-T cells in vitro and in vivo.Results: Our results indicated that co-expression of CD70 and B7-H3 was observed on multiple tumor types including kidney, breast, esophageal, liver, colon cancer, glioma as well as melanoma. The CD70 targeted CAR-T cells with binding moiety of CD70 specific scFv exhibit a higher affinity and antitumor effect against CD70+ tumor cells. TanCAR-T cells induced enhanced ability of cytolysis and cytokine release over unispecific CAR-T cells when encountering tumor cells expressing two target-antigens. Further, low doses of TanCAR-T cells could also effectively control the lung cancer and melanoma xenografts and improved overall survival of the treated animals.Conclusion: TanCAR-T cells targeting CD70 and B7-H3 exhibit enhanced antitumor functionality and improve the problem of antigenic heterogeneity and variant in the treatment against solid tumor and melanoma.

Integrated Analysis of DNA Copy Number Changes and Gene Expression Identifies Key Genes in Gastric Cancer.

This study was aimed at identifying differentially expressed genes (DEGs) with copy number changes in gastric cancer (GC) pathogenesis. Microarray data GSE33429, including array-based comparative genomic hybridization and gene expression profiles, were obtained. DEGs were screened between GC and adjacent noncancerous tissues. Genes located at Minimum Common Regions (MCRs) were identified, and overlapped genes between DEGs and genes with amplification or deletion were identified. Gene Ontology function and pathway enrichment analysis of DEGs were performed. A protein-protein interaction network for DEGs was built, and significant modules were mined from the network. Functional annotation of genes in modules was also performed. A total of 677 up- and 583 downregulated DEGs were identified, including 37 overexpressed genes located at gained MCRs and 28 downregulated genes located at deleted MCRs. In significant modules, upregulated genes with amplification, including DSN1 (MIS12 kinetochore complex component), MAPRE1 (microtubule-associated protein, RP/EB family, member 1), TPX2 (microtubule-associated), UBE2C (ubiquitin-conjugating enzyme E2C), and MYBL2 (v-myb avian myeloblastosis viral oncogene homolog-like 2), were associated with cell cycle, but downregulated genes with deletion, including UGT2B15 (UDP glucuronosyltransferase 2 family, polypeptide B15), UGT2B17 (UDP glucuronosyltransferase 2 family, polypeptide B17), ADH1B (alcohol dehydrogenase 1B), and ADH1A (alcohol dehydrogenase 1A), were related to metabolism. The identified genes DSN1, MAPRE1, TPX2, UBE2C, and MYBL2 located at gained MCRs and UGT2B15, UGT2B17, ADH1B, and ADH1A located at deleted MCRs may play an important role in GC progression through regulating cell cycle and metabolism.

Pan-Cancer and Single-Cell Modeling of Genomic Alterations Through Gene Expression.

Cancer is a disease often characterized by the presence of multiple genomic alterations, which trigger altered transcriptional patterns and gene expression, which in turn sustain the processes of tumorigenesis, tumor progression, and tumor maintenance. The links between genomic alterations and gene expression profiles can be utilized as the basis to build specific molecular tumorigenic relationships. In this study, we perform pan-cancer predictions of the presence of single somatic mutations and copy number variations using machine learning approaches on gene expression profiles. We show that gene expression can be used to predict genomic alterations in every tumor type, where some alterations are more predictable than others. We propose gene aggregation as a tool to improve the accuracy of alteration prediction models from gene expression profiles. Ultimately, we show how this principle can be beneficial in intrinsically noisy datasets, such as those based on single-cell sequencing.

Integration of genome wide association study with gene expression profiling identifies ROR1 as a novel susceptibility gene for coronary artery disease

Objective To identify new susceptibility genes for coronary artery disease(CAD)by integrating genome wide association study and gene expression profiling. Methods On account of our data of genome wide association study(GWAS)on CAD, our integrative analysis of gene expression profiles and GWAS for CAD was conducted, and we obtained candidate genes and single nucleotide polymorphisms(SNPs)for a multicenter case-control genetic association study.Using a DNA ligase chain reaction-based genotyping method, we validated these candidate loci in two independent populations. Results Firstly, we selected 21 SNPs for 21 candidate genes.Using a DNA ligase chain reaction-based genotyping method, we validated these candidate loci in two independent populations, including population 1(495 cases and 492 control)and population 2(810 cases and 853 control). And we identified an intragenic SNP rs11208367(ROR1), which was significantly associated with CAD.Meta confluence analysis in combination of GWAS and two validation populations showed that the P value of rs11208367 was 2.00×10-4, which was still significant after Bonferroni multiple test correction(0.05/21=2.38×10-3). Conclusions The rs11208367 SNP of ROR1gene is significantly associated with CAD, indicating that ROR1is a novel susceptibility gene for CAD. Key words: Genomics; Coronary disease; Genetic predisposition to disease

Long noncoding RNA LINC00958 regulates cell sensitivity to radiotherapy through RRM2 by binding to microRNA-5095 in cervical cancer.

Long noncoding RNAs (lncRNAs) have been implicated in the regulation of resistance to radiotherapy in cervical cancer, which is a type of gynecological disease with high mortality in women around the world. Hence, our purpose is to delineate the involvement of LINC00958 in regulating cell sensitivity to radiotherapy in cervical cancer. LINC00958 expression in cervical cancer was assayed, followed by verification of the relationship among LINC00958, microRNA-5095 (miR-5095) and ribonucleotide reductase subunit M2 (RRM2). Hela cells were transduced with up-/downregulation of miR-5095 or RRM2, or LINC00958 silencing, respectively, and then treated with or without a 6 Gy dose of X-ray irradiation. Then the cell proliferation, apoptosis, survival fraction rate, as well as sensitivity to radiotherapy, were assessed. Finally, xenograft tumor in nude mice was established by transplanting Hela cells transfected with sh-LINC00958 and irradiated with 6 Gy of X-ray. High expression of LINC00958 was revealed in The Cancer Genome Atlas and Gene Expression Profiling Interactive Analysis, as well as in radiation-resistant patients, which was associated with lower sensitivity to radiotherapy in cervical cancer. Moreover, cervical cancer patients with higher LINC00958 expression exhibited a shorter overall survival according to Kaplan-Meier analysis. In addition, LINC00958 could regulate the expression of RRM2 by competing for miR-5095. A combination of radiotherapy with LINC00958 silencing, RRM2 downregulation or miR-5095 overexpression was found to inhibit cervical cancer cell proliferation and tumor growth, while promoting cell apoptosis both in vitro and in vivo. Collectively, our results suggest that LINC00958 could regulate RRM2 by competing to miR-5095, which regulates cell sensitivity to radiotherapy in cervical cancer.