Transcriptome analysis of human gastric cancer

Long noncoding RNA GATA2AS influences human erythropoiesis by transcription factor and chromatin landscape modulation

ABSTRACT

Long noncoding RNAs (lncRNAs) are extensively expressed in eukaryotic cells and have been revealed to be important for regulating cell differentiation. Many lncRNAs have been found to regulate erythroid differentiation in the mouse. However, given the low sequence conservation of lncRNAs between mouse and human, our understanding of lncRNAs in human erythroid differentiation remains incomplete. lncRNAs are often transcribed opposite to protein coding genes and regulate their expression. Here, we characterized a human erythrocyte-expressed lncRNA, GATA2AS, which is transcribed opposite to erythroid transcription regulator GATA2. GATA2AS is a 2080-bp long, primarily nucleus-localized noncoding RNA that is expressed in erythroid progenitor cells and decreases during differentiation. Knockout of GATA2AS in human HUDEP2 erythroid progenitor cells using CRISPR-Cas9 genome editing to remove the transcription start site accelerated erythroid differentiation and dysregulated erythroblast gene expression. We identified GATA2AS as a novel GATA2 and HBG activator. Chromatin isolation by RNA purification showed that GATA2AS binds to thousands of genomic sites and colocalizes at a subset of sites with erythroid transcription factors including LRF and KLF1. RNA pulldown and RNA immunoprecipitation confirmed interaction between GATA2AS and LRF and KLF1. Chromatin immunoprecipitation sequencing (ChIP-seq) showed that knockout of GATA2AS reduces binding of these transcription factors genome wide. Assay for transposase-accessible chromatin sequencing (ATAC-seq) and H3K27ac ChIP-seq showed that GATA2AS is essential to maintain the chromatin regulatory landscape during erythroid differentiation. Knockdown of GATA2AS in human primary CD34+ cells mimicked results in HUDEP2 cells. Overall, our results implicate human-specific lncRNA GATA2AS as a regulator of erythroid differentiation by influencing erythroid transcription factor binding and the chromatin regulatory landscape.

Prognostic analysis of uveal melanoma based on the characteristic genes of M2-type macrophages in the tumor microenvironment

Uveal melanoma arises from stromal melanocytes and is the most prevalent primary intraocular tumor in adults. It poses a significant diagnostic and therapeutic challenge due to its high malignancy and early onset of metastases. In recent years, there has been a growing interest in the role of diverse immune cells in tumor cell development and metastasis. Using The Cancer Genome Atlas and the gene expression omnibus databases, and the CIBERSORT method, we investigated the topography of intra-tumor immune infiltration in uveal melanoma in this research. We evaluated the prognosis of uveal melanoma patients using the M2 macrophage immune cell infiltration score in conjunction with clinical tumor patient data. We built a prognostic model based on the distinctive genes of M2 macrophages and combined it with patients' clinical data in the database; we ran a survival prognostic analysis to authenticate the model's accuracy. The functional study revealed the importance of macrophage-associated genes in the development of uveal melanoma. Moreover, the reliability of our prediction model was verified by combining tumor mutational load, immune checkpoint, and drug sensitivity, respectively. Our study provides a reference for the follow-up study of uveal melanoma.

Construction of a novel prognostic-predicting model correlated to ovarian cancer

Background: Ovarian cancer (OC) is one of the most lethal gynecological cancers worldwide. The pathogenesis of the disease and outcomes prediction of OC patients remain largely unclear. The present study aimed to explore the key genes and biological pathways in ovarian carcinoma development, as well as construct a prognostic model to predict patients’ overall survival (OS).

Results: We identified 164 up-regulated and 80 down-regulated differentially expressed genes (DEGs) associated with OC. Gene Ontology (GO) term enrichment showed DEGs mainly correlated with spindle microtubes. For Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, cell cycle was mostly enriched for the DEGs. The protein–protein interaction (PPI) network yielded 238 nodes and 1284 edges. Top three modules and ten hub genes were further filtered and analyzed. Three candidiate drugs targeting for therapy were also selected. Thirteen OS-related genes were selected and an eight-mRNA model was present to stratify patients into high- and low-risk groups with significantly different survival.

Conclusions: The identified DEGs and biological pathways may provide new perspective on the pathogenesis and treatments of OC. The identified eight-mRNA signature has significant clinical implication for outcome prediction and tailored therapy guidance for OC patients.

Long non-coding RNA ARHGAP5-AS1 inhibits migration of breast cancer cell via stabilizing SMAD7 protein

PURPOSE

Tumor metastasis is the main cause of death from breast cancer patients and cell migration plays a critical role in cancer metastasis. Recent studies have shown long non-coding RNAs (lncRNAs) play an essential role in the initiation and progression of cancer. In the present study, the role of an LncRNA, Rho GTPase Activating Protein 5- Antisense 1 (ARHGAP5-AS1) in breast cancer was investigated.

METHODS

RNA sequencing was performed to find out dysregulated LncRNAs in MDA-MB-231-LM2 cells. Transwell migration assays and F-actin staining were utilized to estimate cell migration ability. RNA pulldown assays and RNA immunoprecipitation were used to prove the interaction between ARHGAP5-AS1 and SMAD7. Western blot and immunofluorescence imaging were used to examine the protein levels. Dual luciferase reporter assays were performed to evaluate the activation of TGF-β signaling.

RESULTS

We analyzed the RNA-seq data of MDA-MB-231 and its highly metastatic derivative MDA-MB-231-LM2 cell lines (referred to as LM2) and identified a novel lncRNA (NR_027263) named as ARHGAP5-AS1, which expression was significantly downregulated in LM2 cells. Further functional investigation showed ARHGAP5-AS1 could inhibit cell migration via suppression of stress fibers in breast cancer cell lines. Afterwards, SMAD7 was further identified to interact with ARHGAP5-AS1 by its PY motif and thus its ubiquitination and degradation was blocked due to reduced interaction with E3 ligase SMURF1 and SMURF2. Moreover, ARHGAP5-AS1 could inhibit TGF-β signaling pathway due to its inhibitory role on SMAD7.

CONCLUSION

ARHGAP5-AS1 inhibits breast cancer cell migration via stabilization of SMAD7 protein and could serve as a novel biomarker and a potential target for breast cancer in the future.

Role of tesmin expression in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the most commonly diagnosed cancer and the most frequent cause of cancer-associated mortality worldwide. Tesmin (MTL5) is a 60 kDa protein which has cysteine rich motifs, characteristic of metallothioneins. Tesmin expression was first observed in germ cells during spermatogenesis. Increased tesmin expression in NSCLC has been described previously. Minichromosome maintenance proteins (MCMs) serve a critical role in replication and cell cycle progression, i.e. in NSCLC. The aim of the present study was to evaluate the localization and intensity of tesmin, MCM5 and MCM7 protein expression in NSCLC and their association with the clinicopathological data of patients. Archival paraffin blocks of 243 cases of NSCLC and 104 non-cancerous tissue samples from the surgical margin (control) were obtained from patients treated at the Clinic of Thoracic Surgery of Wroclaw Medical University (Wroclaw, Poland) between 2010 and 2016, and were used for tissue microarrays and immunohistochemical (IHC) experiments. Laser capture microdissection was used for the isolation of cancer cells from 36 frozen samples of NSCLC and 8 control samples, and subsequently, MTL5, MCM5 and MCM7 mRNA expression was detected separately by reverse transcription-quantitative PCR. Positive cytoplasmic and nuclear tesmin, as well as nuclear MCM5 and MCM7 IHC expression were observed in 95.1, 83.67, 95.51 and 100% of the NSCLC cases, respectively. MTL5, MCM5 and MCM7 mRNA expression was observed in 91.66% of the cancer cases for all genes. The statistical analysis revealed increased tesmin IHC expression in cancer cells compared with the control. A positive correlation was observed between the IHC expression of nuclear tesmin and MCM5 proteins (r=0.33; P<0.0001) and nuclear tesmin and MCM7 proteins (r=0.315; P<0.0001). In addition, a positive correlation between the mRNA expression levels of MTL5 and MCM5 (r=0.421; P<0.05), MTL5 and MCM7 (r=0.557; P<0.01) was demonstrated. The survival analysis revealed that the presence of IHC cytoplasmic tesmin expression was a positive prognostic marker in NSCLC (P=0.0524). Furthermore, in vitro experiments performed on the NCI-H1703 cell line revealed that silencing of MTL5 mRNA and tesmin caused the downregulation of the expression levels of MCM5 and MCM7 and decreased the number of cells in the G2 phase. A positive association among tesmin, MCM5 and MCM7 could indicate a possible role of tesmin in the proliferation of NSCLC cancer cells.

Isoforms of Base Excision Repair Enzymes Produced by Alternative Splicing

Transcripts of many enzymes involved in base excision repair (BER) undergo extensive alternative splicing, but functions of the corresponding alternative splice variants remain largely unexplored. In this review, we cover the studies describing the common alternatively spliced isoforms and disease-associated variants of DNA glycosylases, AP-endonuclease 1, and DNA polymerase beta. We also discuss the roles of alternative splicing in the regulation of their expression, catalytic activities, and intracellular transport.

Adaptive Huber Regression

Big data can easily be contaminated by outliers or contain variables with heavy-tailed distributions, which makes many conventional methods inadequate. To address this challenge, we propose the adaptive Huber regression for robust estimation and inference. The key observation is that the robustification parameter should adapt to the sample size, dimension and moments for optimal tradeoff between bias and robustness. Our theoretical framework deals with heavy-tailed distributions with bounded (1 + δ)-th moment for any δ > 0. We establish a sharp phase transition for robust estimation of regression parameters in both low and high dimensions: when δ ≥ 1, the estimator admits a sub-Gaussian-type deviation bound without sub-Gaussian assumptions on the data, while only a slower rate is available in the regime 0 < δ < 1 and the transition is smooth and optimal. In addition, we extend the methodology to allow both heavy-tailed predictors and observation noise. Simulation studies lend further support to the theory. In a genetic study of cancer cell lines that exhibit heavy-tailedness, the proposed methods are shown to be more robust and predictive.

Bioinformatical identification of key pathways and genes in human hepatocellular carcinoma after CSN5 depletion

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. It has been previously reported that CSN5 depletion is an effective method in human HCC. In the current study, we aimed to uncover gene signatures and key pathways during HCC. Gene expression profiles of GSE26485 were downloaded from GEO database. Totally, 101 differentially expressed genes (DEGs) were up-regulated and 146 ones were down-regulated. Biological processes (BP) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) analysis showed that the DEGs were mainly enriched in regulation of cell growth, oxidation-reduction process, mitotic cytokinesis, negative regulation of macroautophagy, endosome organization, lysosome, biosynthesis of antibiotics, small cell lung cancer and glutathione metabolism and so on (P < 0.05). Protein-protein interaction (PPI) network, Kaplan-Meier, log-rank method, western blot, immunohistochemistry and encyclopedia of DNA elements (ENCODE) analysis showed that CSN5 depletion took effects through down-regulation of SMAD5-related pathways which include EXO1, CENPA and NCAPG, resulting in the inactivation of H3K4me3 and H3K36me3. Those genes represent the promising targets for therapeutic intervention in HCC patients.

The potential value of CDV3 in the prognosis evaluation in Hepatocellular carcinoma

CDV3 is correlated with tumorigenesis and may affect some biological process in cancer. In this study, we explore the role of CDV3 in HCC. According to the TCGA data base, CDV3 is over-expressed in HCC tissues. Up-regulation of CDV3 is correlated with lower over-all survival rate in HCC patients. In HCC samples from our hospital, CDV3 is also enriched in cancer tissues and CDV3 expression associated with HCC pathological T stage. What is more, higher CDV3 expression could forecast poor survival rate in HCC patients. In conclusion, CDV3 is a biomarker of HCC and could be a potential therapeutic target.

McTwo: a two-step feature selection algorithm based on maximal information coefficient

BACKGROUND

High-throughput bio-OMIC technologies are producing high-dimension data from bio-samples at an ever increasing rate, whereas the training sample number in a traditional experiment remains small due to various difficulties. This "large p, small n" paradigm in the area of biomedical "big data" may be at least partly solved by feature selection algorithms, which select only features significantly associated with phenotypes. Feature selection is an NP-hard problem. Due to the exponentially increased time requirement for finding the globally optimal solution, all the existing feature selection algorithms employ heuristic rules to find locally optimal solutions, and their solutions achieve different performances on different datasets.

RESULTS

This work describes a feature selection algorithm based on a recently published correlation measurement, Maximal Information Coefficient (MIC). The proposed algorithm, McTwo, aims to select features associated with phenotypes, independently of each other, and achieving high classification performance of the nearest neighbor algorithm. Based on the comparative study of 17 datasets, McTwo performs about as well as or better than existing algorithms, with significantly reduced numbers of selected features. The features selected by McTwo also appear to have particular biomedical relevance to the phenotypes from the literature.

CONCLUSION

McTwo selects a feature subset with very good classification performance, as well as a small feature number. So McTwo may represent a complementary feature selection algorithm for the high-dimensional biomedical datasets.

Role of downregulation of galectin-9 in the tumorigenesis of gastric cancer

Galectin-9 (Gal-9), a member of the β-galactoside-binding galectin family, plays a role in immune response, apoptosis, cell proliferation and cell death. Recent studies have shown that abnormal expression of Gal-9 is involved in certain primary cancers. The present study is the first investigation of the role of Gal-9 gene expression in clinically diagnosed primary gastric cancer tissues. Gal-9 mRNA expression was assessed in 44 clinically diagnosed frozen primary cancer tissue samples using quantitative PCR (qPCR). Analysis of the qPCR data revealed a significant reduction (>2-fold decreased) of Gal-9 gene expression in gastric cancer tissues in 77% (34/44) of patients. In patients with gastric cancer, although no statistically significant difference was found between adjacent (<2 cm away from the cancer tissue) and normal tissues (>5 cm away from the cancer tissue), a >2-fold reduction in Gal-9 expression was observed in the adjacent tissues of 34% of the patients. Compared to matched normal or adjacent tissues, the gene expression of Gal-9 was significantly decreased in tumor tissues (p<0.001). The correlation of Gal-9 expression and clinicopathological features in gastric cancer was analyzed according to the TNM classification system using AJCC stage grouping. In patients with gastric cancer, clinical staging, tumor pathological stage (pT stage), tumor cell differentiation, lymph node metastasis and survival rate were found to be associated with Gal-9 expression. However, no significant association was found between Gal-9 expression and distant metastasis (p>0.05). No significant difference was found between patients of different genders, levels of cell differentiation, distant metastasis status or different survival time of patients. Compared to normal tissues, >2-fold reduction of Tim-3 expression in gastric cancer tissues occurred in 59% of patients, but no correlation was found between Gal-9 and Tim-3 in gastric cancer. These results strongly suggest that Gal-9 is involved in tumorigenesis of gastric cancer.

Discovery of widespread GTP-binding motifs in genomic DNA and RNA

Biological RNAs that bind small molecules have been implicated in a variety of regulatory and catalytic processes. Inspired by these examples, we used in vitro selection to search a pool of genome-encoded RNA fragments for naturally occurring GTP aptamers. Several aptamer classes were identified, including one (the "G motif") with a G-quadruplex structure. Further analysis revealed that most RNA and DNA G-quadruplexes bind GTP. The G motif is abundant in eukaryotes, and the human genome contains ~75,000 examples with dissociation constants comparable to the GTP concentration of a eukaryotic cell (~300 μM). G-quadruplexes play roles in diverse cellular processes, and our findings raise the possibility that GTP may play a role in the function of these elements. Consistent with this possibility, the sequence requirements of several classes of regulatory G-quadruplexes parallel those of GTP binding.

Galectin-9 in tumor biology: a jack of multiple trades

Galectin family members have been shown to exert multiple roles in the context of tumor biology. Several recent findings support a similar multi-faceted role for galectin-9. Galectin-9 expression is frequently altered in cancer as compared to normal tissues. In addition, an increasing amount of evidence suggests that galectin-9 is involved in several aspects of tumor progression, including tumor cell adhesion and survival, immune escape and angiogenesis. Also, galectin-9 shows potential as a prognostic marker and a therapeutic target for several malignancies. In this review we summarize both the established and the emerging roles of galectin-9 in tumor biology and discuss the potential application of galectin-9 in anti-cancer therapy.

A two-phase case-control study for colorectal cancer genetic susceptibility: candidate genes from chromosomal regions 9q22 and 3q22

Background:

Colorectal cancer (CRC) is the second cause of cancer-related death in the Western world. Much of the CRC genetic risk remains unidentified and may be attributable to a large number of common, low-penetrance genetic variants. Genetic linkage studies in CRC families have reported additional association with regions 9q22–31, 3q21–24, 7q31, 11q, 14q and 22q. There are several plausible candidate genes for CRC susceptibility within the aforementioned linkage regions including PTCH1, XPA and TGFBR1 in 9q22–31, and EPHB1 and MRAS in 3q21–q24.

Methods:

CRC cases and matched controls were from EPICOLON, a prospective, multicentre, nationwide Spanish initiative, composed of two independent phases. Phase 1 corresponded to 515 CRC cases and 515 controls, whereas phase 2 consisted of 901 CRC cases and 909 controls. Genotyping was performed for 172 single-nucleotide polymorphisms (SNPs) in 84 genes located within regions 9q22–31 and 3q21–q24.

Results:

None of the 172 SNPs analysed in our study could be formally associated with CRC risk. However, rs1444601 (TOPBP1) and rs13088006 (CDV3) in region 3q22 showed interesting results and may have an effect on CRC risk.

Conclusions:

TOPBP1 and CDV3 genetic variants on region 3q22 may modulate CRC risk. Further validation and meta-analysis should be undertaken in larger CRC cohorts.

Overexpression of Bax inhibitor-1 (BI-1) induces cell transformation in NIH3T3 cells

BI-1 (Bax inhibitor-1), an apoptosis-inhibiting gene belonging to the Bcl-2 protein family, plays an important role in mitochondrial apoptosis pathway to suppress Bax-induced apoptosis. To investigate the potential role of BI-1 in promoting cell growth and tumorigenesis, in the present study we overexpressed the BI-1 gene in NIH3T3 cells using the lentivirus-mediated gene expression system. Our in vitro studies showed that NIH3T3 cells overexpressing BI-1 displayed a significantly higher growth rate and formed more and larger colonies than the control cells. In addition, our in vivo studies indicated that the lenti-BI-1-infected cells formed obvious tumours, while no tumours were formed by the control cells after subcutaneously injected into nude mice. These results strongly suggested that the BI-1 gene might play a crucial role in neoplastic genesis and development.

Structural basis for binding of RNA and cofactor by a KsgA methyltransferase

Among methyltransferases, KsgA and the reaction it catalyzes are conserved throughout evolution. However, the specifics of substrate recognition by the enzyme remain unknown. Here we report structures of Aquifex aeolicus KsgA, in its ligand-free form, in complex with RNA, and in complex with both RNA and S-adenosylhomocysteine (SAH, reaction product of cofactor S-adenosylmethionine), revealing critical structural information on KsgA-RNA and KsgA-SAH interactions. Moreover, the structures show how conformational changes that occur upon RNA binding create the cofactor-binding site. There are nine conserved functional motifs (motifs I-VIII and X) in KsgA. Prior to RNA binding, motifs I and VIII are flexible, each exhibiting two distinct conformations. Upon RNA binding, the two motifs become stabilized in one of these conformations, which is compatible with the binding of SAH. Motif X, which is also stabilized upon RNA binding, is directly involved in the binding of SAH.

Gene characterization index: assessing the depth of gene annotation

Background

We introduce the Gene Characterization Index, a bioinformatics method for scoring the extent to which a protein-encoding gene is functionally described. Inherently a reflection of human perception, the Gene Characterization Index is applied for assessing the characterization status of individual genes, thus serving the advancement of both genome annotation and applied genomics research by rapid and unbiased identification of groups of uncharacterized genes for diverse applications such as directed functional studies and delineation of novel drug targets.

Methodology/Principal Findings

The scoring procedure is based on a global survey of researchers, who assigned characterization scores from 1 (poor) to 10 (extensive) for a sample of genes based on major online resources. By evaluating the survey as training data, we developed a bioinformatics procedure to assign gene characterization scores to all genes in the human genome. We analyzed snapshots of functional genome annotation over a period of 6 years to assess temporal changes reflected by the increase of the average Gene Characterization Index. Applying the Gene Characterization Index to genes within pharmaceutically relevant classes, we confirmed known drug targets as high-scoring genes and revealed potentially interesting novel targets with low characterization indexes. Removing known drug targets and genes linked to sequence-related patent filings from the entirety of indexed genes, we identified sets of low-scoring genes particularly suited for further experimental investigation.

Conclusions/Significance

The Gene Characterization Index is intended to serve as a tool to the scientific community and granting agencies for focusing resources and efforts on unexplored areas of the genome. The Gene Characterization Index is available from http://cisreg.ca/gci/.