cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14916327
title: Comprehensive analysis of lncRNA-miRNA-mRNA regulatory networks for microbiota-mediated colorectal cancer associated with immune cell infiltration

description: Recent findings have identified microbiota as crucial participants in many disease conditions, including cancers. Competing endogenous RNA (ceRNA) is regarded as a candidate mechanism involving relevant biological processes. We therefore constructed a ceRNA network using the TCGA and GEO database, to determine the potential mechanisms of microbiota-mediated colorectal carcinogenesis and progression. We found a total of 75 lncRNAs, 8 miRNAs, and 9 mRNAs in the probiotics-mediated ceRNA network and a total of 49 lncRNAs, 4 miRNAs, and 3 mRNA in the pathobiont-mediated ceRNA network, which could induce the microbiota-mediated carcinogenesis and progression. The GO and KEGG analysis indicated that the ceRNA network is mainly enriched in the metabolic process, and two unique pathways (the p53 signaling pathway and microRNA in cancer), respectively. A four-gene signature (FRMD6-AS2, DIRC3, LIFR-AS1, and MRPL23-AS1) was suggested as an independent prognostic factor. Four lncRNAs (LINC00355, KCNQ1OT1, LINC00491, and HOTAIR) were associated with poor survival. Three small molecule candidate anticancer drugs (Pentoxyverine, Rimexolone, and Doxylamine) were identified. A four-gene signature (FAM129A, BCL2, PMAIP1, and RPS6) is significantly correlated with immune infiltration level. This study provides a promising biomarker reservoir to explore the mechanism by which microbiota regulate the ceRNA network involving the immune response, and further participate in colorectal carcinogenesis and progression.
DOI: 10.6084/m9.figshare.14916327.v1
title: Comprehensive analysis of lncRNA-miRNA-mRNA regulatory networks for microbiota-mediated colorectal cancer associated with immune cell infiltration

description: Recent findings have identified microbiota as crucial participants in many disease conditions, including cancers. Competing endogenous RNA (ceRNA) is regarded as a candidate mechanism involving relevant biological processes. We therefore constructed a ceRNA network using the TCGA and GEO database, to determine the potential mechanisms of microbiota-mediated colorectal carcinogenesis and progression. We found a total of 75 lncRNAs, 8 miRNAs, and 9 mRNAs in the probiotics-mediated ceRNA network and a total of 49 lncRNAs, 4 miRNAs, and 3 mRNA in the pathobiont-mediated ceRNA network, which could induce the microbiota-mediated carcinogenesis and progression. The GO and KEGG analysis indicated that the ceRNA network is mainly enriched in the metabolic process, and two unique pathways (the p53 signaling pathway and microRNA in cancer), respectively. A four-gene signature (FRMD6-AS2, DIRC3, LIFR-AS1, and MRPL23-AS1) was suggested as an independent prognostic factor. Four lncRNAs (LINC00355, KCNQ1OT1, LINC00491, and HOTAIR) were associated with poor survival. Three small molecule candidate anticancer drugs (Pentoxyverine, Rimexolone, and Doxylamine) were identified. A four-gene signature (FAM129A, BCL2, PMAIP1, and RPS6) is significantly correlated with immune infiltration level. This study provides a promising biomarker reservoir to explore the mechanism by which microbiota regulate the ceRNA network involving the immune response, and further participate in colorectal carcinogenesis and progression.
DOI: 10.6084/m9.figshare.16611933
title: High expression of ladinin-1 (LAD1) predicts adverse outcomes: a new candidate docetaxel resistance gene for prostatic cancer (PCa)

description: Docetaxel resistance is one of the major obstacles that undermine the treatment outcome of PCa. Exploring molecular mechanisms associated with docetaxel resistance could provide insights into the formulation of novel strategies enhancing the efficacy of PCa treatment. Ladinin-1 (LAD1) is an anchoring filament protein in basement membranes, which contributes to the association of the epithelial cells with the underlying mesenchyme. LAD1 has been implicated in the progression of different cancers. However, its role in PCa remains to be investigated. In the present study, we found that LAD1 was highly expressed in docetaxel-resistant PCa cells, while its expression was significantly suppressed in tumor samples after docetaxel treatment. Moreover, the expression level of LAD1 in PCa tissues was significantly higher than that of normal tissue, and high expression level of LAD1 was significantly associated with adverse outcomes of PCa patients. Finally, high expression of LAD1 in PCa tissue was also correlated with the expression level of genes involving in tumor cell proliferation and invasive behaviors. Collectively, our data suggest that LAD1 may serve as a potential prognostic factor in PCa patients.
DOI: 10.6084/m9.figshare.16611933.v2
title: High expression of ladinin-1 (LAD1) predicts adverse outcomes: a new candidate docetaxel resistance gene for prostatic cancer (PCa)

description: Docetaxel resistance is one of the major obstacles that undermine the treatment outcome of PCa. Exploring molecular mechanisms associated with docetaxel resistance could provide insights into the formulation of novel strategies enhancing the efficacy of PCa treatment. Ladinin-1 (LAD1) is an anchoring filament protein in basement membranes, which contributes to the association of the epithelial cells with the underlying mesenchyme. LAD1 has been implicated in the progression of different cancers. However, its role in PCa remains to be investigated. In the present study, we found that LAD1 was highly expressed in docetaxel-resistant PCa cells, while its expression was significantly suppressed in tumor samples after docetaxel treatment. Moreover, the expression level of LAD1 in PCa tissues was significantly higher than that of normal tissue, and high expression level of LAD1 was significantly associated with adverse outcomes of PCa patients. Finally, high expression of LAD1 in PCa tissue was also correlated with the expression level of genes involving in tumor cell proliferation and invasive behaviors. Collectively, our data suggest that LAD1 may serve as a potential prognostic factor in PCa patients.
DOI: 10.6084/m9.figshare.14704805
title: Long non-coding RNA TINCR promotes hepatocellular carcinoma proliferation and invasion via STAT3 signaling by direct interacting with T-cell protein tyrosine phosphatase (TCPTP)

description: The long non-coding RNAs (lncRNAs) participate in modulating numerous important cancer phenotypes via formation of RNA-protein complex. TINCR (terminal differentiation-induced lncRNA) modulates cancer cell behavior in many human malignancies, such as hepatocellular carcinoma (HCC). Herein, we proposed to investigate the underlying mechanism by which TINCR regulates HCC progression via formation of RNA-protein. RNA pulldown, LC-MS/MS, bioinformatics analysis, and RNA immunoprecipitation (RIP) assays were employed to identify TINCR-interacting protein TCPTP in HCC cells. The siRNAs for TINCR and TCPTP were transfected into HCC cells. The plasmids encoding full length or the 1–360 nt deletion of TINCR were generated and applied to cell transfection. The CCK-8, colony formation, EdU, wound healing along with transwell assays were employed to examine cell proliferation, apoptosis, migration, and infiltration. Real-time PCR, as well as western blot assays were employed to assess the levels of STAT3 phosphorylation and its target genes. We identified 1–360 nt region of TINCR, which directly bound with the phosphatase domain of TCPTP to inhibit its tyrosine phosphatase activity. Then, the results showed that the increasing of cell growth, migration, infiltration, and the reducing of apoptosis in TINCR-knockdown HCC cells was remarkably reversed with TCPTP silence. Additionally, Δ1-360 TINCR overexpression did not affect HCC cell growth, apoptosis, migration, infiltration, and STAT3 target genes expression. Our data revealed that TINCR directly bound TCPTP and suppressed the dephosphorylation of STAT3, thus promoting STAT3 activation and its downstream target genes in HCC progression and tumorigenicity. Highlights LncRNA TINCR interacted with protein TCPTP LncRNA TINCR maintained STAT3 phosphorylation LncRNA TINCR affected STAT3 signaling in HCC Abbreviations: lncRNAs: long non-coding RNAs; TINCR: terminal differentiation-induced lncRNA; TCPTP: T cell protein tyrosine phosphatase; siRNA: small-interfering RNA; HCC: hepatocellular carcinoma; nt: nucleotide; LC-MS/MS: Liquid Chromatography - Tandem Mass Spectrometry; RIP: RNA immunoprecipitation; ANOVA: analysis of variance; EdU: 5-ethynyl-2’-deoxyuridine; real-time PCR: real-time polymerase chain reaction; CCK-8: cell counting kit-8; aa: amino acids; STAT3: signal transducer and activator of transcription 3
DOI: 10.6084/m9.figshare.14704805.v1
title: Long non-coding RNA TINCR promotes hepatocellular carcinoma proliferation and invasion via STAT3 signaling by direct interacting with T-cell protein tyrosine phosphatase (TCPTP)

description: The long non-coding RNAs (lncRNAs) participate in modulating numerous important cancer phenotypes via formation of RNA-protein complex. TINCR (terminal differentiation-induced lncRNA) modulates cancer cell behavior in many human malignancies, such as hepatocellular carcinoma (HCC). Herein, we proposed to investigate the underlying mechanism by which TINCR regulates HCC progression via formation of RNA-protein. RNA pulldown, LC-MS/MS, bioinformatics analysis, and RNA immunoprecipitation (RIP) assays were employed to identify TINCR-interacting protein TCPTP in HCC cells. The siRNAs for TINCR and TCPTP were transfected into HCC cells. The plasmids encoding full length or the 1–360 nt deletion of TINCR were generated and applied to cell transfection. The CCK-8, colony formation, EdU, wound healing along with transwell assays were employed to examine cell proliferation, apoptosis, migration, and infiltration. Real-time PCR, as well as western blot assays were employed to assess the levels of STAT3 phosphorylation and its target genes. We identified 1–360 nt region of TINCR, which directly bound with the phosphatase domain of TCPTP to inhibit its tyrosine phosphatase activity. Then, the results showed that the increasing of cell growth, migration, infiltration, and the reducing of apoptosis in TINCR-knockdown HCC cells was remarkably reversed with TCPTP silence. Additionally, Δ1-360 TINCR overexpression did not affect HCC cell growth, apoptosis, migration, infiltration, and STAT3 target genes expression. Our data revealed that TINCR directly bound TCPTP and suppressed the dephosphorylation of STAT3, thus promoting STAT3 activation and its downstream target genes in HCC progression and tumorigenicity. Highlights LncRNA TINCR interacted with protein TCPTP LncRNA TINCR maintained STAT3 phosphorylation LncRNA TINCR affected STAT3 signaling in HCC Abbreviations: lncRNAs: long non-coding RNAs; TINCR: terminal differentiation-induced lncRNA; TCPTP: T cell protein tyrosine phosphatase; siRNA: small-interfering RNA; HCC: hepatocellular carcinoma; nt: nucleotide; LC-MS/MS: Liquid Chromatography - Tandem Mass Spectrometry; RIP: RNA immunoprecipitation; ANOVA: analysis of variance; EdU: 5-ethynyl-2’-deoxyuridine; real-time PCR: real-time polymerase chain reaction; CCK-8: cell counting kit-8; aa: amino acids; STAT3: signal transducer and activator of transcription 3
DOI: 10.6084/m9.figshare.16611933.v1
title: High expression of ladinin-1 (LAD1) predicts adverse outcomes: a new candidate docetaxel resistance gene for prostatic cancer (PCa)

description: Docetaxel resistance is one of the major obstacles that undermine the treatment outcome of PCa. Exploring molecular mechanisms associated with docetaxel resistance could provide insights into the formulation of novel strategies enhancing the efficacy of PCa treatment. Ladinin-1 (LAD1) is an anchoring filament protein in basement membranes, which contributes to the association of the epithelial cells with the underlying mesenchyme. LAD1 has been implicated in the progression of different cancers. However, its role in PCa remains to be investigated. In the present study, we found that LAD1 was highly expressed in docetaxel-resistant PCa cells, while its expression was significantly suppressed in tumor samples after docetaxel treatment. Moreover, the expression level of LAD1 in PCa tissues was significantly higher than that of normal tissue, and high expression level of LAD1 was significantly associated with adverse outcomes of PCa patients. Finally, high expression of LAD1 in PCa tissue was also correlated with the expression level of genes involving in tumor cell proliferation and invasive behaviors. Collectively, our data suggest that LAD1 may serve as a potential prognostic factor in PCa patients.
DOI: 10.6084/m9.figshare.16570709
title: Expression of N<sup>6</sup>-methyladenosine (m<sup>6</sup>A) regulators correlates with immune microenvironment characteristics and predicts prognosis in diffuse large cell lymphoma (DLBCL)

description: This study conducted a comprehensive analysis of the clinical significance of N<sup>6</sup>-methyladenosine (m<sup>6</sup>A) regulators and their relationship with immune microenvironment characteristics in diffuse large cell lymphoma (DLBCL). Consensus clustering was performed to molecularly discriminate DLBCL subtypesbased on m<sup>6</sup>A regulators’ expression. Using the Cox and Lasso regression algorithm, survival-associated m<sup>6</sup>A regulators were identified, and a m<sup>6</sup>A-based prognostic signature was established. The influence of m<sup>6</sup>A risk on immune cell infiltration, immune checkpoint genes, cancer immunity cycle, and immunotherapeutic response was evaluated. Potential molecular pathways related to m<sup>6</sup>A risk were investigated using gene set enrichment analysis. The m<sup>6</sup>A regulators showed satisfactory performance in distinguishing DLBCL subgroups with distinct clinical traits and outcomes. A six m<sup>6</sup>A regulator-based prognostic signature was established and validated as an independent predictor, which separated patients into low- and high-risk groups. High-risk m<sup>6</sup>A indicated worse survival. The B cells naïve, T cells gamma delta, and NK cells resting were the three most affected immune cells by m<sup>6</sup>A risk. Up-regulated (PDCD1 and KIR3DL1) and down-regulated (TIGIT, IDO1, and BTLA) immune checkpoint genes in the high-risk group were identified. The m<sup>6</sup>A risk was found to influence several steps in the cancer immunity cycle. Patients with high-risk m<sup>6</sup>A were more likely to benefit from immunotherapy. Biological function enrichment analysis revealed that high-risk m<sup>6</sup>A to be tended related to malignant tumor characteristics, while low-risk m<sup>6</sup>A showed trend to be related to defensive response processes. Collectively, the m<sup>6</sup>A-based prognostic signature could be a practical prognostic predictor for DLBCL and immune microenvironment characteristics affected by m<sup>6</sup>A may be part of the mechanism.
DOI: 10.6084/m9.figshare.15133880
title: Identification of prognostic markers by weighted gene co‐expression network analysis in non-small cell lung cancer

description: Non-small cell lung cancer (NSCLC) is one of the fatal tumors and is associated with a poor prognosis. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to quantify the proportions of 22 types of immune cells. Weighted gene co-expression network analysis (WGCNA) was established from the GSE37745 data, and key modules correlating most with CD8<sup>+</sup> T cell infiltration were determined. Genes that manifested a high module connectivity in the key module were identified as hub genes. Three bioinformatics online databases were used to evaluate hub gene expression levels in tumor and normal tissues. Finally, survival analysis was conducted for these hub genes. In this study, we chose four hub genes (<i>AURKB, CDC20, TPX2</i> and <i>KIF2C</i>) based on the comprehensive bioinformatics analyses. All hub genes were overexpressed in tumor tissue, and high expression of <i>AURKB, CDC20, TPX2</i>, and <i>KIF2C</i> correlated with the poor prognosis of these patients. In vitro experiments confirmed that <i>CDC20</i> knockdown inhibited cell proliferation and growth. The above results indicated that AURKB, CDC20, TPX2, and KIF2C are potential CD8<sup>+</sup> T cell infiltration-related biomarkers and therapeutic targets.
DOI: 10.6084/m9.figshare.16570709.v2
title: Expression of N<sup>6</sup>-methyladenosine (m<sup>6</sup>A) regulators correlates with immune microenvironment characteristics and predicts prognosis in diffuse large cell lymphoma (DLBCL)

description: This study conducted a comprehensive analysis of the clinical significance of N<sup>6</sup>-methyladenosine (m<sup>6</sup>A) regulators and their relationship with immune microenvironment characteristics in diffuse large cell lymphoma (DLBCL). Consensus clustering was performed to molecularly discriminate DLBCL subtypesbased on m<sup>6</sup>A regulators’ expression. Using the Cox and Lasso regression algorithm, survival-associated m<sup>6</sup>A regulators were identified, and a m<sup>6</sup>A-based prognostic signature was established. The influence of m<sup>6</sup>A risk on immune cell infiltration, immune checkpoint genes, cancer immunity cycle, and immunotherapeutic response was evaluated. Potential molecular pathways related to m<sup>6</sup>A risk were investigated using gene set enrichment analysis. The m<sup>6</sup>A regulators showed satisfactory performance in distinguishing DLBCL subgroups with distinct clinical traits and outcomes. A six m<sup>6</sup>A regulator-based prognostic signature was established and validated as an independent predictor, which separated patients into low- and high-risk groups. High-risk m<sup>6</sup>A indicated worse survival. The B cells naïve, T cells gamma delta, and NK cells resting were the three most affected immune cells by m<sup>6</sup>A risk. Up-regulated (PDCD1 and KIR3DL1) and down-regulated (TIGIT, IDO1, and BTLA) immune checkpoint genes in the high-risk group were identified. The m<sup>6</sup>A risk was found to influence several steps in the cancer immunity cycle. Patients with high-risk m<sup>6</sup>A were more likely to benefit from immunotherapy. Biological function enrichment analysis revealed that high-risk m<sup>6</sup>A to be tended related to malignant tumor characteristics, while low-risk m<sup>6</sup>A showed trend to be related to defensive response processes. Collectively, the m<sup>6</sup>A-based prognostic signature could be a practical prognostic predictor for DLBCL and immune microenvironment characteristics affected by m<sup>6</sup>A may be part of the mechanism.
DOI: 10.6084/m9.figshare.15133880.v1
title: Identification of prognostic markers by weighted gene co‐expression network analysis in non-small cell lung cancer

description: Non-small cell lung cancer (NSCLC) is one of the fatal tumors and is associated with a poor prognosis. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to quantify the proportions of 22 types of immune cells. Weighted gene co-expression network analysis (WGCNA) was established from the GSE37745 data, and key modules correlating most with CD8<sup>+</sup> T cell infiltration were determined. Genes that manifested a high module connectivity in the key module were identified as hub genes. Three bioinformatics online databases were used to evaluate hub gene expression levels in tumor and normal tissues. Finally, survival analysis was conducted for these hub genes. In this study, we chose four hub genes (<i>AURKB, CDC20, TPX2</i> and <i>KIF2C</i>) based on the comprehensive bioinformatics analyses. All hub genes were overexpressed in tumor tissue, and high expression of <i>AURKB, CDC20, TPX2</i>, and <i>KIF2C</i> correlated with the poor prognosis of these patients. In vitro experiments confirmed that <i>CDC20</i> knockdown inhibited cell proliferation and growth. The above results indicated that AURKB, CDC20, TPX2, and KIF2C are potential CD8<sup>+</sup> T cell infiltration-related biomarkers and therapeutic targets.
DOI: 10.6084/m9.figshare.16570709.v1
title: Expression of N<sup>6</sup>-methyladenosine (m<sup>6</sup>A) regulators correlates with immune microenvironment characteristics and predicts prognosis in diffuse large cell lymphoma (DLBCL)

description: This study conducted a comprehensive analysis of the clinical significance of N<sup>6</sup>-methyladenosine (m<sup>6</sup>A) regulators and their relationship with immune microenvironment characteristics in diffuse large cell lymphoma (DLBCL). Consensus clustering was performed to molecularly discriminate DLBCL subtypesbased on m<sup>6</sup>A regulators’ expression. Using the Cox and Lasso regression algorithm, survival-associated m<sup>6</sup>A regulators were identified, and a m<sup>6</sup>A-based prognostic signature was established. The influence of m<sup>6</sup>A risk on immune cell infiltration, immune checkpoint genes, cancer immunity cycle, and immunotherapeutic response was evaluated. Potential molecular pathways related to m<sup>6</sup>A risk were investigated using gene set enrichment analysis. The m<sup>6</sup>A regulators showed satisfactory performance in distinguishing DLBCL subgroups with distinct clinical traits and outcomes. A six m<sup>6</sup>A regulator-based prognostic signature was established and validated as an independent predictor, which separated patients into low- and high-risk groups. High-risk m<sup>6</sup>A indicated worse survival. The B cells naïve, T cells gamma delta, and NK cells resting were the three most affected immune cells by m<sup>6</sup>A risk. Up-regulated (PDCD1 and KIR3DL1) and down-regulated (TIGIT, IDO1, and BTLA) immune checkpoint genes in the high-risk group were identified. The m<sup>6</sup>A risk was found to influence several steps in the cancer immunity cycle. Patients with high-risk m<sup>6</sup>A were more likely to benefit from immunotherapy. Biological function enrichment analysis revealed that high-risk m<sup>6</sup>A to be tended related to malignant tumor characteristics, while low-risk m<sup>6</sup>A showed trend to be related to defensive response processes. Collectively, the m<sup>6</sup>A-based prognostic signature could be a practical prognostic predictor for DLBCL and immune microenvironment characteristics affected by m<sup>6</sup>A may be part of the mechanism.