Integrated analysis of lymphocyte infiltration-associated lncRNA for ovarian cancer via TCGA, GTEx and GEO datasets

Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review

In recent years, the role of bioinformatics and computational biology together with omics techniques and transcriptomics has gained tremendous importance in biomedicine and healthcare, particularly for the identification of biomarkers for precision medicine and drug discovery. Differential gene expression (DGE) analysis is one of the most used techniques for RNA-sequencing (RNA-seq) data analysis. This tool, which is typically used in various RNA-seq data processing applications, allows the identification of differentially expressed genes across two or more sample sets. Functional enrichment analyses can then be performed to annotate and contextualize the resulting gene lists. These studies provide valuable information about disease-causing biological processes and can help in identifying molecular targets for novel therapies. This review focuses on differential gene expression (DGE) analysis pipelines and bioinformatic techniques commonly used to identify specific biomarkers and discuss the advantages and disadvantages of these techniques.

DC-Derived CXCL10 Promotes CTL Activation to Suppress Ovarian Cancer

This study investigates the role of dendritic cells (DCs), with a focus on their CXCL10 marker gene, in the activation of cytotoxic T lymphocytes (CTLs) within the ovarian cancer microenvironment and its impact on disease progression. Utilizing scRNA-seq data and immune infiltration analysis, we identified a diminished DC presence in ovarian cancer. Gene analysis pinpointed CXCL10 as a key regulator in OV progression via its influence on DCs and CTLs. Prognostic analysis and in vitro experiments substantiated this role. Our findings reveal that DC-derived CXCL10 significantly affects CTL activation and proliferation. Reduced CXCL10 levels hinder CTL cytotoxicity, promoting ovarian cancer cell migration and invasion. Experimental studies using animal models have provided further evidence that the capacity of CTLs to suppress tumor development is significantly diminished when treated with DCs that have low expression of CXCL10. Dendritic cell-derived CXCL10 emerges as a pivotal factor in restraining ovarian cancer growth and metastasis through the activation of cytotoxic T lymphocytes. This study sheds light on the crucial interplay within the ovarian cancer microenvironment, offering potential therapeutic targets for ovarian cancer treatment.

EM-transcriptomic signature predicts drug response in advanced stages of high-grade serous ovarian carcinoma based on ascites-derived primary cultures

Introduction: High-grade serous ovarian carcinoma (HGSOC) remains a medical challenge despite considerable improvements in the treatment. Unfortunately, over 75% of patients have already metastasized at the time of diagnosis. Advances in understanding the mechanisms underlying how ascites cause chemoresistance are urgently needed to derive novel therapeutic strategies. This study aimed to identify the molecular markers involved in drug sensitivity and highlight the use of ascites as a potential model to investigate HGSOC treatment options. Methods: After conducting an in silico analysis, eight epithelial-mesenchymal (EM)-associated genes related to chemoresistance were identified. To evaluate differences in EM-associated genes in HGSOC samples, we analyzed ascites-derived HGSOC primary cell culture (AS), tumor (T), and peritoneal nodule (NP) samples. Moreover, in vitro experiments were employed to measure tumor cell proliferation and cell migration in AS, following treatment with doxorubicin (DOX) and cisplatin (CIS) and expression of these markers. Results: Our results showed that AS exhibits a mesenchymal phenotype compared to tumor and peritoneal nodule samples. Moreover, DOX and CIS treatment leads to an invasive-intermediate epithelial-to-mesenchymal transition (EMT) state of the AS by different EM-associated marker expression. For instance, the treatment of AS showed that CDH1 and GATA6 decreased after CIS exposure and increased after DOX treatment. On the contrary, the expression of KRT18 has an opposite pattern. Conclusion: Taken together, our study reports a comprehensive investigation of the EM-associated genes after drug exposure of AS. Exploring ascites and their associated cellular and soluble components is promising for understanding the HGSOC progression and treatment response at a personalized level.

The Prognosis and Immunotherapy Prediction Model of Ovarian Serous Cystadenocarcinoma Patient was Constructed Based on Cuproptosis-Related LncRNA

Cuproptosis can serve as potential prognostic predictors in patients with cancer. However, the role of this relationship in ovarian serous cystadenocarcinoma (OV) remains unclear. 376 OV tumor samples were obtained from the Cancer Genome Atlas (TCGA) database, and long non-coding RNAs (lncRNAs) related to cuproptosis were obtained through correlation analysis. The risk assessment model was further constructed by univariate Cox regression analysis and LASSO Cox regression. Bioinformatics was used to analyze the regulatory effect of relevant risk assessment models on tumor mutational burden (TMB) and immune microenvironment. We obtained 5 lncRNAs (AC025287.2, AC092718.4, AC112721.2, LINC00996, and LINC01639) and incorporated them into the Cox proportional hazards model. Kaplan-Meier (KM) curve analysis of the prognosis found that the high-risk group was associated with a poorer prognosis. The receiver operating characteristic (ROC) curve showed stronger predictive power compared to other clinicopathological features. Immune infiltration analysis showed that high-risk scores were inversely correlated with CD8+ T cells, CD4+ T cells, macrophages, NK cells, and B cells. Functional enrichment analysis found that they may act via the extracellular matrix (ECM)-interacting proteins and other pathways. We successfully constructed a reliable cuproptosis-related lncRNA model for the prognosis of OV.

Long noncoding RNA FTX promotes epithelial-mesenchymal transition of epithelial ovarian cancer through modulating miR-7515/TPD52 and activating Met/Akt/mTOR

Overexpressed long noncoding RNA FTX is associated with low survival rate of epithelial ovarian cancer (EOC) patients, and enhances tumor infiltration. Thus, we aim to illuminate the undefined underlying mechanisms. Real-time quantitative polymerase chain reaction was applied to detect the expressions of FTX, miR-7515, miR-342-3p, miR-940, miR-150-5p, miR-205-5p and tumor protein D52 (TPD52). Cell counting kit-8 and transwell assays were utilized to explore the cell viability, migration or invasion of EOC cells. Western blot was conducted to measure the expressions of E-cadherin, N-cadherin, Met, phosphorylated (p)-Met, Akt, p-Akt, mTOR and p-mTOR. LncBase and TargetScan predicted the binding of miR-7515 with FTX, and the binding of TPD52 with miR-7515, respectively. The two bindings were further validated by dual luciferase reporter assay. As a result, FTX sponged miR-7515 and miR-7515 targeted to TPD52. FTX was overexpressed in four EOC cell lines. Overexpressed FTX enhanced the cell viability, migration or invasion of EOC cells, elevated N-cadherin and TPD52 expressions, phosphorylated Met/Akt/mTOR, and inhibited E-cadherin expression. All these influences were subsequently reversed by miR-7515 mimic. Collectively, FTX regulates miR-7515/TPD52 to facilitate the migration, invasion or epithelial-mesenchymal transition of EOC through activating Met/Akt/mTOR signaling pathway.

Elsayed A, López-Berestein G, Amero P, Rodríguez-Aguayo C. An Overview of the Immune Modulatory Properties of Long Non-Coding RNAs and Their Potential Use as Therapeutic Targets in Cancer

Long non-coding RNAs (lncRNAs) play pivotal roles in regulating immune responses, immune cell differentiation, activation, and inflammatory processes. In cancer, they are gaining prominence as potential therapeutic targets due to their ability to regulate immune checkpoint molecules and immune-related factors, suggesting avenues for bolstering anti-tumor immune responses. Here, we explore the mechanistic insights into lncRNA-mediated immune modulation, highlighting their impact on immunity. Additionally, we discuss their potential to enhance cancer immunotherapy, augmenting the effectiveness of immune checkpoint inhibitors and adoptive T cell therapies. LncRNAs as therapeutic targets hold the promise of revolutionizing cancer treatments, inspiring further research in this field with substantial clinical implications.

Construction of Immune Infiltration-Related LncRNA Signatures Based on Machine Learning for the Prognosis in Colon Cancer

Colon cancer is one of the malignant tumors with high morbidity, lethality, and prevalence across global human health. Molecular biomarkers play key roles in its prognosis. In particular, immune-related lncRNAs (IRL) have attracted enormous interest in diagnosis and treatment, but less is known about their potential functions. We aimed to investigate dysfunctional IRL and construct a risk model for improving the outcomes of patients. Nineteen immune cell types were collected for identifying house-keeping lncRNAs (HKLncRNA). GSE39582 and TCGA-COAD were treated as the discovery and validation datasets, respectively. Four machine learning algorithms (LASSO, Random Forest, Boruta, and Xgboost) and a Gaussian mixture model were utilized to mine the optimal combination of lncRNAs. Univariate and multivariate Cox regression was utilized to construct the risk score model. We distinguished the functional difference in an immune perspective between low- and high-risk cohorts calculated by this scoring system. Finally, we provided a nomogram. By leveraging the microarray, sequencing, and clinical data for immune cells and colon cancer patients, we identified the 221 HKLncRNAs with a low cell type-specificity index. Eighty-seven lncRNAs were up-regulated in the immune compared to cancer cells. Twelve lncRNAs were beneficial in improving performance. A risk score model with three lncRNAs (CYB561D2, LINC00638, and DANCR) was proposed with robust ROC performance on an independent dataset. According to immune-related analysis, the risk score is strongly associated with the tumor immune microenvironment. Our results emphasized IRL has the potential to be a powerful and effective therapy for enhancing the prognostic of colon cancer.

LncRNA miR663AHG represses the development of colon cancer in a miR663a-dependent manner

The MIR663AHG gene encodes both miR663AHG and miR663a. While miR663a contributes to the defense of host cells against inflammation and inhibits colon cancer development, the biological function of lncRNA miR663AHG has not been previously reported. In this study, the subcellular localization of lncRNA miR663AHG was determined by RNA-FISH. miR663AHG and miR663a were measured by qRT-PCR. The effects of miR663AHG on the growth and metastasis of colon cancer cells were investigated in vitro and in vivo. CRISPR/Cas9, RNA pulldown, and other biological assays were used to explore the underlying mechanism of miR663AHG. We found that miR663AHG was mainly distributed in the nucleus of Caco2 and HCT116 cells and the cytoplasm of SW480 cells. The expression level of miR663AHG was positively correlated with the level of miR663a (r = 0.179, P = 0.015) and significantly downregulated in colon cancer tissues relative to paired normal tissues from 119 patients (P < 0.008). Colon cancers with low miR663AHG expression were associated with advanced pTNM stage (P = 0.021), lymph metastasis (P = 0.041), and shorter overall survival (hazard ratio = 2.026; P = 0.021). Experimentally, miR663AHG inhibited colon cancer cell proliferation, migration, and invasion. The growth of xenografts from RKO cells overexpressing miR663AHG was slower than that of xenografts from vector control cells in BALB/c nude mice (P = 0.007). Interestingly, either RNA-interfering or resveratrol-inducing expression changes of miR663AHG or miR663a can trigger negative feedback regulation of transcription of the MIR663AHG gene. Mechanistically, miR663AHG could bind to miR663a and its precursor pre-miR663a, and prevent the degradation of miR663a target mRNAs. Disruption of the negative feedback by knockout of the MIR663AHG promoter, exon-1, and pri-miR663A-coding sequence entirely blocked these effects of miR663AHG, which was restored in cells transfected with miR663a expression vector in rescue experiment. In conclusion, miR663AHG functions as a tumor suppressor that inhibits the development of colon cancer through its cis-binding to miR663a/pre-miR663a. The cross talk between miR663AHG and miR663a expression may play dominant roles in maintaining the functions of miR663AHG in colon cancer development.

Diagnostic value of non-coding RNAs in ovarian cancer

The type of primary tumour of the ovary ranks first among all organs in the body. Although the incidence of malignant ovarian tumour ranks third among gynaecological malignancies, it is the most fatal type. A lack of effective diagnostic methods for early ovarian cancer remains, and the efficacy of advanced ovarian cancer is often unsatisfactory; the five-year survival rate of stage III-IV is less than 30%. Non-coding RNA is RNA that does not have protein-coding potential and was once considered as 'junk DNA'. However, increasing number of studies have shown that the disorder of non-coding RNA is related to a variety of diseases, including the occurrence and development of tumours. We summarised the dysregulated non-coding RNAs (miRNAs, circRNAs, and lncRNAs) reported currently in ovarian cancer and their functional mechanisms, and the clinical value of different types of ncRNAs as diagnostic or predictive markers for ovarian cancer, providing further evidence for non-coding RNAs to be considered as biomarkers of ovarian cancer.

N6-methyladenosine methylation regulator FTO promotes oxidative stress and induces cell apoptosis in ovarian cancer

Aims: This study aimed to reveal the possible molecular mechanism of n6-methyladenosine (m6A) methylation regulator FTO in the biological activities of ovarian cancer (OC) based on The Cancer Genome Atlas, Genotype-Tissue Expression and Gene Expression Omnibus databases. Materials & methods: A risk score model was constructed to predict the prognosis of patients with OC. The key m6A methylation regulator was screened out based on OC-related microarray datasets. Results: 22 m6A methylation regulators were differentially expressed and interacted with each other in OC. FTO, a key m6A methylation regulator, was singled out. In vivo experiments verified that FTO promoted oxidative stress and apoptosis of OC cells to inhibit tumor growth in nude mice. Conclusion: This study highlighted the tumor-suppressive mechanism of m6A methylation regulator FTO in OC.

Does the LHPP gene share a common biological function in pancancer progression?

Although emerging evidence has revealed that LHPP, a histidine phosphatase protein, suppresses the progression of different cancers, a pan-cancer analysis still remains unavailable. Therefore, we first utilized different bioinformatics tools to explore the tumor inhibitory role of LHPP protein across 33 tumor types based on the TCGA project. Additionally, HGC-27 gastric cancer cells were used to evaluate the biological functions of LHPP after stable transfection with lentiviruses. Consequently, LHPP mRNA and protein expression were down-regulated in the most cancer tissues corresponding to normal tissues. The data showed that patients with higher LHPP performance had a better prognosis of overall survival (OS) and disease-free survival (DFS) in brain glioma and renal carcinoma. In addition, we found that enhancement of LHPP expression attenuated the proliferation, migration and invasion of gastric cancer cells. The expression levels of cell-cycle-related and EMT-related molecules, such as CDK4, CyclinD1, Vimentin and Snail, were clearly reduced. Moreover, a genetic alteration analysis showed that the most frequent mutation types in LHPP protein was amplification. The patients without LHPP mutation showed a better tendency of prognosis in UCEC, STAD and COAD. Cancer-associated fibroblast infiltration was also observed in head and neck squamous cell carcinoma, stomach adenocarcinoma and testicular germ cell tumors. In summary, our pancancer analysis among various tumor types could provide a comprehensive understanding of LHPP biological function in the progression of malignant diseases and promote the development of novel therapeutic targets.

Integration of lncRNAs, Protein-Coding Genes and Pathology Images for Detecting Metastatic Melanoma

Melanoma is a lethal skin disease that develops from moles. This study aimed to integrate multimodal data to predict metastatic melanoma, which is highly aggressive and difficult to treat. The proposed EnsembleSKCM method evaluated the prediction performances of long noncoding RNAs (lncRNAs), protein-coding messenger genes (mRNAs) and pathology images (images) for metastatic melanoma. Feature selection was used to screen for metastatic biomarkers in the lncRNA and mRNA datasets. The integrated EnsembleSKCM model was built based on the weighted results of the lncRNA-, mRNA- and image-based models. EnsembleSKCM achieved 0.9444 in the prediction accuracy of metastatic melanoma and outperformed the single-modal prediction models based on the lncRNA, mRNA and image data. The experimental data suggest the importance of integrating the complementary information from the three data modalities. WGCNA was used to analyze the relationship of molecular-level features and image features, and the results show connections between them. Another cohort was used to validate our prediction.

Database Mining Detected a Cuproptosis-Related Prognostic Signature and a Related Regulatory Axis in Breast Cancer

Background

Breast cancer is the frequent cause of disease burden related to cancer among women. It affects one in 20 women globally and up to one in eight women in high-income countries. Cuproptosis is a copper-induced modality of mitochondrial cell death that is involved in tumor proliferation and metastasis.

Methods

To construct a prognostic cuproptosis-related signature, LASSO Cox regression analysis was employed. Additionally, ceRNA was developed with an aim of exploring the possible lncRNA-miRNA-mRNA regulatory axis in breast cancer.

Results

The expression of FDX1, DLD, DLAT, LIAS, LIPT1, GLS MTF1, and PDHA1 was downregulated, while CDKN2A expression level was elevated in breast cancer in contrast with normal tissue. We furthermore reviewed the genetic mutation landscape of genes linked to cuproptosis in breast cancer. Prognosis analysis revealed poor OS and RFS rates in breast cancer patients with elevated levels of CDKN2A and PDHA1 and low levels of MTF1, DLD, LIPT1, and FDX1. We then constructed a cuproptosis-related signature with six genes (DKN2A, MTF1, PDHA1, DLD, LIPT1, and FDX1) for breast cancer, which predicted the OS rate with an accuracy that ranged from medium to high. Further analysis demonstrated a significant correlation between the cuproptosis-related prognostic signature and pTNM stage, MSI score, drug sensitivity, TMB score, and immune cell infiltration. Moreover, we identified the lncRNA XIST/miR-92b-3p/MTF1 regulatory axis for breast cancer.

Conclusion

Multiomics approaches were used to create a cuproptosis-related signature with six genes (DKN2A, MTF1, PDHA1, DLD, LIPT1, and FDX1) for breast cancer. We discovered the lncRNA XIST/miR-92b-3p/MTF1 regulatory axis for breast cancer, which has not yet been investigated previously.

Quantitative Proteomics Based on iTRAQ Reveal that Nitidine Chloride Induces Apoptosis by Activating JNK/c-Jun Signaling in Hepatocellular Carcinoma Cells

The aim of the present study was to investigate the cytotoxic effects and underlying molecular mechanisms of nitidine chloride (NC) in hepatocellular carcinoma cells via quantitative proteomics. MTT assays were used to detect the inhibitory effects of NC in Bel-7402 liver cancer cells, and the number of apoptotic cells was measured by flow cytometry. Quantitative proteomics technology based on iTRAQ was used to discover differential expressed proteins after NC treatment, and bioinformatic techniques were further used to screen potential targets of NC. Molecular docking was applied to evaluate the docking activity of NC with possible upstream proteins, and their expression was detected at the mRNA and protein levels by quantitative reverse transcription PCR and western blotting. NC inhibited the proliferation of Bel-7402 cells after 24 h of treatment and stimulated apoptosis in vitro. The proteomics experiment showed that NC triggers mitochondrial damage in HCC cells and transcription factor AP-1 (c-Jun) may be a potential target of NC (fold change = 4.36 ± 0.23). Molecular docking results revealed the highest docking score of NC with c-Jun N-terminal kinase (JNK), one of the upstream proteins of c-Jun. Moreover, the mRNA and protein expression of c-Jun and JNK were significantly increased after NC treatment (p < 0.05). These findings indicate that NC significantly induced mitochondrial damage in HCC cells, and induced apoptosis by activating JNK/c-Jun signaling.

Upregulation of Metallothionein 1 G (MT1G) Negatively Regulates Ferroptosis in Clear Cell Renal Cell Carcinoma by Reducing Glutathione Consumption

Ferroptosis is characterized by lipid peroxidation and iron accumulation, closely associated with clear cell renal cell carcinoma (ccRCC). It is of great significance for prognostic prediction and treatment of ccRCC to find biomarkers related to ferroptosis. We conducted several bioinformatic analyses using the transcriptome data and clinical information derived from online databases. Firstly, we identified the differentially expressed target genes in ccRCC. Then, t test and COX analysis were used to determine whether it was an independent prognostic factor combined with clinical information. String and gene set enrichment analysis (GSEA) were used to predict its function. Finally, we used ccRCC cells: 769-P and KAKI-1 in vitro to verify the regulation of target genes on cell proliferation apoptosis, iron metabolism, and GSH metabolism, which were used to judge the effect of target genes on ferroptosis. The study showed that MT1G is downregulated in ccRCC tissues compared with normal renal tissues. However, the ccRCC patients with higher expression relatively had higher malignancy and advanced stages. MT1G is an independent adverse factor for the prognosis of ccRCC. The protein interaction network analysis and GSEA showed that MT1G was closely related to GSH metabolism-related proteins (GSR) and lipid oxidation-related proteins (PLA2G2A). Samples with high expression of MT1G were enriched in “glutathione metabolism,” “oxidative phosphorylation,” and “proteasome,” whose function was involved in GSH metabolism and lipid peroxidation. The term associated with the occurrence and development of tumors included “P53 signaling pathway.” Furthermore, in vitro experiments showed that MT1G partially blocked ferroptosis induced by erastin and sorafenib-induced ccRCC cell lines (769-P and CAKI-1). The mechanism may be that MT1G affects ferroptosis by regulating GSH consumption in ccRCC cells. MT1G may be a negative regulator of ferroptosis in ccRCC cells and a biomarker of poor prognosis.

A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma

Background and purpose: Radioresistance remains a major reason of radiotherapeutic failure in esophageal squamous cell carcinoma (ESCC). Our study is to screen the immune-related long non-coding RNA (ir-lncRNAs) of radiation-resistant ESCC (rr-ESCC) via Gene Expression Omnibus (GEO) database and to construct a prognostic risk model.

Methods: Microarray data (GSE45670) related to radioresistance of ESCC was downloaded from GEO. Based on pathologic responses after chemoradiotherapy, patients were divided into a non-responder (17 samples) and responder group (11 samples), and the difference in expression profiles of ir-lncRNAs were compared therein. Ir-lncRNA pairs were constructed for the differentially expressed lncRNAs as prognostic variables, and the microarray dataset (GSE53625) was downloaded from GEO to verify the effect of ir-lncRNA pairs on the long-term survival of ESCC. After modelling, patients are divided into high- and low-risk groups according to prognostic risk scores, and the outcomes were compared within groups based on the COX proportional hazards model. The different expression of ir-lncRNAs were validated using ECA 109 and ECA 109R cell lines via RT-qPCR.

Results: 26 ir-lncRNA genes were screened in the GSE45670 dataset with differential expression, and 180 ir-lncRNA pairs were constructed. After matching with ir-lncRNA pairs constructed by GSE53625, six ir-lncRNA pairs had a significant impact on the prognosis of ESCC from univariate analysis model, of which three ir-lncRNA pairs were significantly associated with prognosis in multivariate COX analysis. These three lncRNA pairs were used as prognostic indicators to construct a prognostic risk model, and the predicted risk scores were calculated. With a median value of 2.371, the patients were divided into two groups. The overall survival (OS) in the high-risk group was significantly worse than that in the low-risk group (p < 0.001). The 1-, 2-, and 3-year prediction performance of this risk-model was 0.666, 0.702, and 0.686, respectively. In the validation setting, three ir-lncRNAs were significantly up-regulated, while two ir-lncRNAs were obviouly down-regulated in the responder group.

Conclusion: Ir-lncRNAs may be involved in the biological regulation of radioresistance in patients with ESCC; and the prognostic risk-model, established by three ir-lncRNAs pairs has important clinical value in predicting the prognosis of patients with rr-ESCC.

LINC00665 affects the malignant biological behavior of ovarian cancer via the miR-148b-3p/KLF5

This study investigated the expression and clinical significance of long intergenic noncoding RNA 00665 (LINC00665) in ovarian cancer (OC), as well as its effect on the malignant biological behavior of OC cells. The expression of LINC00665, miR-148b-3p, and Krüppel-like factor 5 (KLF5) in OC tissues and cells were determined by RT-qPCR. Western blot was used to detect the protein expression of KLF5. The expression patterns of LINC00665 in nuclear and cytoplasm fractions were undertaken using RT-qPCR. In addition, CCK-8 assay, clone formation assay, transwell, scratch test, and flow cytometry were respectively used to detect the cell activity, proliferation, invasiveness, healing of cells, and apoptosis rate of OC cells. Furthermore, the interactions between LINC00665 and miR-148b-3p and between miR-148b-3p and KLF5 were verified by the luciferase reporter assay, and the correlations among these three genes were analyzed. LINC00665 expression was upregulated both in OC cell lines and tissues. Si-LINC00665 inhibited cell proliferation, invasion, and migration and induced apoptosis to a certain extent. The subcellular fraction assay revealed LINC00665 to be located mainly in the cytoplasm. miR-148b-3p was a target of LINC00665, and KLF5 was directly targeted by miR-148b-3p. Si-LINC00665 inhibited KLF5 expression, miR-148b-3p inhibitor promoted KLF5 expression, and si-KLF5 inhibited LINC00665 expression. Interestingly, the expression of LINC00665 was reversely associated with miR-148b-3p expression but positively correlated with KLF5. Furthermore, miR-148b-3p expression was negatively correlated with KLF5. In addition, si-KLF5 inhibited the malignant biological behavior of OC cells, whereas miR-148b-3p inhibitor had the opposite effect. Most importantly, the si-LINC00665 could reverse the promotion effect of the miR-148b-3p inhibitor on the malignant biological behavior of OC cells. LINC00665 can be used as an effective prognostic indicator of OC, which has the potential to be a new therapeutic target.

Risk coefficient model of necroptosis-related lncRNA in predicting the prognosis of patients with lung adenocarcinoma

Model algorithms were used in constructing the risk coefficient model of necroptosis-related long non-coding RNA in identifying novel potential biomarkers in the prediction of the sensitivity to chemotherapeutic agents and prognosis of patients with lung adenocarcinoma (LUAD). Clinic and transcriptomic data of LUAD were obtained from The Cancer Genome Atlas. Differently expressed necroptosis-related long non-coding RNAs got identified by performing both the univariate and co-expression Cox regression analyses. Subsequently, the least absolute shrinkage and selection operator technique was adopted in constructing the nrlncRNA model. We made a comparison of the areas under the curve, did the count of the values of Akaike information criterion of 1-year, 2-year, as well as 3-year receiver operating characteristic curves, after which the cut-off value was determined for the construction of an optimal model to be used in identifying high risk and low risk patients. Genes, tumor-infiltrating immune cells, clinical correlation analysis, and chemotherapeutic agents data of both the high-risk and low-risk subgroups were also performed. We identified 26 DEnrlncRNA pairs, which were involved in the Cox regression model constructed. The curve areas under survival periods of 1 year, 2 years, and 3 years of patients with LUAD were 0.834, 0.790, and 0.821, respectively. The cut-off value set was 2.031, which was used in the identification of either the high-risk or low-risk patients. Poor outcomes were observed in patients belonging to the high-risk group. The risk score was the independent predictor of the LUAD outcome (p < 0.001). The expression levels of immune checkpoint and infiltration of specific immune cells were anticipated by the gene risk model. The high-risk group was found to be highly sensitive to docetaxel, erlotinib, cisplatin, and paclitaxel. The model established through nrlncRNA pairs irrespective of the levels of expression could give a prediction on the LUAD patients’ prognosis and assist in identifying the patients who might gain more benefit from chemotherapeutic agents.

An Integrative Analysis Revealing ZFHX4-AS1 as a Novel Prognostic Biomarker Correlated with Immune Infiltrates in Ovarian Cancer

Ovarian cancer (OC) is the main cause of deaths worldwide in female reproductive system malignancies. Growing studies have indicated that eRNAs could regulate cellular activities in various tumors. Yet the potential roles of eRNAs in OC progression have not been elucidated. Thus, comprehensive assays were needed to screen the critical eRNAs and to explore their possible function in OC. We used Kaplan–Meier methods to identify survival-associated eRNAs in OC based on TCGA datasets. The levels of ZFHX4-AS1 were examined using TCGA datasets. Further exploration was carried out based on the following assays: clinical and survival assays, GO terms, and KEGG assays. TIMER was applied to delve into the relationships between ZFHX4-AS1 and tumor immune infiltration. In this research, we observed 71 survival-related eRNAs in OC patients. ZFHX4-AS1 was highly expressed in OC specimens and predicted a poor prognosis of OC patients. In addition, high ZFHX4-AS1 expression was positively related to the advanced stages of OC specimens. Multivariate assays revealed that ZFHX4-AS1 was an independent prognostic factor for overall survival of OC patients. KEGG analysis indicated that ZFHX4-AS1 may play a regulatory effect on TGF-beta signaling, PI3K-Akt signaling, and proteoglycans in cancer. The pan-cancer validation indicated that ZFHX4-AS1 was related to survival in eight tumors, namely, UCEC, STAD, SARC, OV, ACC, KICH, KIRC, and BLCA. The expression of ZFHX4-AS1 was correlated with the levels of B cells, T cell CD8+, neutrophil, macrophage, and myeloid dendritic cells. Simultaneously, ZFHX4-AS1 may be a prognostic biomarker and a distinctly immunotherapy-related eRNA in OC.

Identification of NAD+ Metabolism-Derived Gene Signatures in Ovarian Cancer Prognosis and Immunotherapy

Background: Nicotinamide adenine dinucleotide (NAD⁺) has emerged as a critical regulator of cell signaling and survival pathways, affecting tumor initiation and progression. In this study it was investigated whether circulating NAD⁺ metabolism-related genes (NMRGs) could be used to predict immunotherapy response in ovarian cancer (OC) patients.

Method: In this study, NMRGs were comprehensively examined in OC patients, three distinct NMRGs subtypes were identified through unsupervised clustering, and an NAD⁺-related prognostic model was generated based on LASSO Cox regression analysis and generated a risk score (RS). ROC curves and an independent validation cohort were used to assess the model’s accuracy. A GSEA enrichment analysis was performed to investigate possible functional pathways. Furthermore, the role of RS in the tumor microenvironment, immunotherapy, and chemotherapy was also investigated.

Result: We found three different subgroups based on NMRGs expression patterns. Twelve genes were selected by LASSO regression to create a prognostic risk signature. High-RS was founded to be linked to a worse prognosis. In Ovarian Cancer Patients, RS is an independent prognostic marker. Immune infiltrating cells were considerably overexpressed in the low-RS group, as immune-related functional pathways were significantly enriched. Furthermore, immunotherapy prediction reveal that patients with low-RS are more sensitive to immunotherapy.

Conclusion: For a patient with OC, NMRGs are promising biomarkers. Our prognostic signature has potential predictive value for OC prognosis and immunotherapy response. The results of this study may help improve our understanding of NMRG in OCs.

The Biological and Molecular Function of LINC00665 in Human Cancers

Long non-coding RNAs (lncRNAs) are more than 200 nucleotides in length and are implicated in the development of human cancers, without protein-coding function. Mounting evidence indicates that cancer initiation and progression are triggered by lncRNA dysregulation. Recently, a growing number of studies have found that LINC00665, a long intergenic non-protein coding RNA, may be associated with various cancers, including gastrointestinal tumors, gynecological tumors, and respiratory neoplasms. LINC00665 was reported to be significantly dysregulated in cancers and has an important clinical association. It participates in cell proliferation, migration, invasion, and apoptosis through different biological pathways. In this review, we summarize the current findings on LINC00665, including its biological roles and molecular mechanisms in various cancers. LINC00665 may be a potential prognostic biomarker and novel therapeutic target for cancers.

Identification of gene signatures for COAD using feature selection and Bayesian network approaches

The combination of TCGA and GTEx databases will provide more comprehensive information for characterizing the human genome in health and disease, especially for underlying the cancer genetic alterations. Here we analyzed the gene expression profile of COAD in both tumor samples from TCGA and normal colon tissues from GTEx. Using the SNR-PPFS feature selection algorithms, we discovered a 38 gene signatures that performed well in distinguishing COAD tumors from normal samples. Bayesian network of the 38 genes revealed that DEGs with similar expression patterns or functions interacted more closely. We identified 14 up-DEGs that were significantly correlated with tumor stages. Cox regression analysis demonstrated that tumor stage, STMN4 and FAM135B dysregulation were independent prognostic factors for COAD survival outcomes. Overall, this study indicates that using feature selection approaches to select key gene signatures from high-dimensional datasets can be an effective way for studying cancer genomic characteristics.

LINC00665: An Emerging Biomarker for Cancer Diagnostics and Therapeutics

Long intergenic noncoding RNA 00665 (LINC00665) is located on human chromosome 19q13.12. LINC00665 was upregulated in eighteen cancers and downregulated in two cancers. LINC00665 not only inhibits 25 miRNAs but also directly affects the stability of ten protein-coding genes. Notably, LINC00665 also encodes a micro-peptide CIP2A-BP that promotes triple-negative breast cancer progression. LINC00665 can participate in five signaling pathways to regulate cancer progression, including the Wnt/β-catenin signaling pathway, TGF-β signaling pathway, NF-κB signaling pathway, PI3K/AKT signaling pathway, and MAPK signaling pathway. Aberrant expression of LINC00665 in breast cancer, gastric cancer, and hepatocellular carcinoma can be used for disease diagnosis. In addition, aberrant expression of LINC00665 is closely associated with clinicopathological features and poor prognosis of various cancers. LINC00665 is closely associated with the effects of anticancer drugs, including gefitinib and cisplatin in non-small cell lung cancer, gemcitabine in cholangiocarcinoma, and cisplatin-paclitaxel in breast cancer. This work systematically summarizes the diagnostic and prognostic values of LINC00665 in various tumors, and comprehensively analyzes the molecular regulatory mechanism related to LINC00665, which is expected to provide clear guidance for future research.

The Role of Long Non-Coding RNAs in the Tumor Immune Microenvironment

Tumorigenesis is a complicated process caused by successive genetic and epigenetic alterations. The past decades demonstrated that the immune system affects tumorigenesis, tumor progression, and metastasis. Although increasing immunotherapies are revealed, only a tiny proportion of them are effective. Long non-coding RNAs (lncRNAs) are a class of single-stranded RNA molecules larger than 200 nucleotides and are essential in the molecular network of oncology and immunology. Increasing researches have focused on the connection between lncRNAs and cancer immunotherapy. However, the in-depth mechanisms are still elusive. In this review, we outline the latest studies on the functions of lncRNAs in the tumor immune microenvironment. Via participating in various biological processes such as neutrophil recruitment, macrophage polarization, NK cells cytotoxicity, and T cells functions, lncRNAs regulate tumorigenesis, tumor invasion, epithelial-mesenchymal transition (EMT), and angiogenesis. In addition, we reviewed the current understanding of the relevant strategies for targeting lncRNAs. LncRNAs-based therapeutics may represent promising approaches in serving as prognostic biomarkers or potential therapeutic targets in cancer, providing ideas for future research and clinical application on cancer diagnosis and therapies.

GMFG (glia maturation factor gamma) inhibits lung cancer growth by activating p53 signaling pathway

The tumor-promoting or tumor-suppressing functions of Glia maturation factor gamma (GMFG) were described in several cancers. However, how GMFG regulates lung cancer progression is elusive. Bioinformatics analysis was employed to analyze GMFG expression in lung adenocarcinoma (LUAD) and lung squamous cancer (LUSC) as well as its significance in prognosis prediction and diagnosis in lung cancer patients. CCK8 and colony formation assays were adopted to evaluate the impact of GMFG overexpressing and depleting on lung cancer cell proliferation. And in vivo experiments were implemented. Luciferase reporter assays were used to disclose the signaling pathway mediated by GMFG in lung cancer. GMFG expression was lower in LUSC and LUAD tissues compared with normal lung tissues based on TCGA and GTEx databases. Low GMFG expression was associated with lower overall survival and shorter disease specific survival compared high GMFG expression. In vitro loss and gain functions assays demonstrated that ectopically GMFG expression dampened the lung cancer cell proliferation while GMFG knockout escalated the cell proliferation. The promoting effect of GMFG knockout on lung cancer tumorgenesis was also observed in vivo. More interesting, GMFG overexpression reinforced the p53 signaling pathway in lung cancer cells, conversely GMFG deficiency disrupted p53 signaling pathway. In conclusion, we revealed that GMFG is fundamental to p53 signaling pathway to inhibit lung cancer progression, highlighting the importance of GMFG as a p53 inducer for lung cancer patient's diagnosis and therapy.

The Emerging Roles of LINC00665 in Human Cancers

Long non-coding RNAs (lncRNAs) are non-coding RNAs that have more than 200 nucleotides and can participate in the regulation of gene expression in various ways. An increasing number of studies have shown that the dysregulated expression of lncRNAs is related to the occurrence and progression of human cancers. LINC00665 is a novel lncRNA, which is abnormally expressed in various human cancers, such as lung cancer, breast cancer, prostate cancer, and glioma. LINC00665 functions in many biological processes of tumor cells, such as cell proliferation, migration, invasion, angiogenesis, and metabolism, and is related to the clinicopathological characteristics of cancer patients. LINC00665 can play biological functions as a ceRNA, directly binding and interacting with proteins, and as an upstream molecule regulating multiple signaling pathways. In this review, we comprehensively summarize the expression level, function, and molecular mechanisms of LINC00665 in different human cancers and emphasize that LINC00665 is a promising new diagnostic, prognostic biomarker, and therapeutic target.

Effect of LncRNA OIP5-AS1/microRNA-186-5p on isoflurane-induced cognitive dysfunction in aged rats

BACKGROUND

Post-operative recognition dysfunction (POCD) is a kind of central nervous system complication that appears after operative anesthesia. Recent studies on the mechanism of long non-coding RNA (lncRNA) in neurodegenerative diseases are abundant.

AIMS

The study aimed to explore the expression pattern and role of lncRNA OIP5-AS1 in POCD and to investigate its underlying mechanism in old rats.

METHODS

The old rats were exposed to isoflurane to mimic the POCD in the elderly, and their cognitive function was tested via Morris water maze (MWM) test. Enzyme linked immunosorbent assay was applied for the concentration detection of inflammation and oxidative stress-related factors. Luciferase reporter assay was done for the target gene analysis.

RESULTS

Downregulation of OIP5-AS1 was accompanied by isoflurane treatment in rats, overexpression of OIP5-AS1 induced the rats to spend more time in the target quadrant, and shorten escape latency time. OIP5-AS1 inhibited the release of TNF-α, IL-6 and IL-1β, GSH and superoxide dismutase, decreased the activation of caspase-3, but promoted malondialdehyde release. miR-186-5p was a target miRNA of OIP5-AS1, and exhibited high expression in rats after isoflurane exposure. miR-186-5p can abolish the beneficial role of OIP5-AS1 against cognitive impairment, inflammatory response, oxidative stress and neuron apoptosis.

CONCLUSION

OIP5-AS1 plays a neuroprotective role in elderly POCD rats through sponging miR-186-5p, and it is related to OIP5-AS1/miR-186-5p mediated inflammatory response, oxidative stress and neuron apoptosis.

LukS-PV Induces Apoptosis via the SET8-H4K20me1-PIK3CB Axis in Human Acute Myeloid Leukemia Cells

Evidence suggests that histone modification disorders are involved in leukemia pathogenesis. We previously reported that LukS-PV, a component of Panton-Valentine leukocidin (PVL), has antileukemia activities that can induce differentiation, increase apoptosis, and inhibit proliferation of acute myeloid leukemia (AML) cells. Furthermore, LukS-PV inhibited hepatoma progression by regulating histone deacetylation, speculating that LukS-PV may exert antileukemia activity by targeting histone modification regulators. In this study, the results showed that LukS-PV induced apoptosis by downregulating the methyltransferase SET8 and its target histone H4 monomethylated at Lys 20 (H4K20me1). Furthermore, chromatin immunoprecipitation sequencing and polymerase chain reaction identified the kinase PIK3CB as a downstream target gene for apoptosis mediated by SET8/H4K20me1. Finally, our results indicated that LukS-PV induced apoptosis via the PIK3CB-AKT-FOXO1 signaling pathway by targeting SET8. This study indicates that SET8 downregulation is one of the mechanisms by which LukS-PV induces apoptosis in AML cells, suggesting that SET8 may be a potential therapeutic target for AML. Furthermore, LukS-PV may be a drug candidate for the treatment of AML that targets epigenetic modifications.

Systematic Analysis and Identification of Dysregulated Panel lncRNAs Contributing to Poor Prognosis in Head-Neck Cancer

Head and neck cancer (HNC) is one of the most prevalent cancers worldwide, accounting for approximately 5% of all cancers. While the underlying molecules and their pathogenetic mechanisms in HNC have yet to be well elucidated, recent studies have shown that dysregulation of lncRNAs may disrupt the homeostasis of various biological pathways. However, the understanding of lncRNAs in HNC is still limited by the lack of expression profiling. In the present study, we employed a systematic strategy to identify a panel of lncRNA associated with HNC. A cancer-related lncRNA profile PCR array was screened to explore potential molecules specific for HNC. A total of 55 lncRNAs were found to be dysregulated in HNC cells when compared to normal keratinocytes. Further analysis of the prognostic significance using The Cancer Genome Atlas (TCGA) database revealed 15 lncRNAs highly correlated with overall survival in HNC patients. Additionally, clinical sample expression analysis of the TCGA-HNSC cohort revealed 16 highly dysregulated lncRNAs in HNC, resulting in a combined 31-lncRNA signature panel that could predict prognosis. Validation of these molecules confirmed the considerable level of altered expressions in HNC cells, with XIST, HOXA11-AS, TSIX, MALAT1, WT1-AS, and IPW being the most prominently dysregulated. We further selected a molecule from our panel (XIST) to confirm the validity of these lncRNAs in the regulation of cancer aggressiveness. Gene ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses demonstrated that XIST participated in various cancer-related functions, including cell proliferation and metastasis. XIST silencing with the RNAi technique substantially reduced invasion and migration in several HNC cell lines. Thus, our study defined a 31-lncRNA panel as prognostic signatures in HNC. These perspective results provide a knowledge foundation for further application of these molecules in precision medicine.

Identification and analysis of genes associated with epithelial ovarian cancer by integrated bioinformatics methods

Background

Though considerable efforts have been made to improve the treatment of epithelial ovarian cancer (EOC), the prognosis of patients has remained poor. Identifying differentially expressed genes (DEGs) involved in EOC progression and exploiting them as novel biomarkers or therapeutic targets is of great value.

Methods

Overlapping DEGs were screened out from three independent gene expression omnibus (GEO) datasets and were subjected to Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses. The protein-protein interactions (PPI) network of DEGs was constructed based on the STRING database. The expression of hub genes was validated in GEPIA and GEO. The relationship of hub genes expression with tumor stage and overall survival and progression-free survival of EOC patients was investigated using the cancer genome atlas data.

Results

A total of 306 DEGs were identified, including 265 up-regulated and 41 down-regulated. Through PPI network analysis, the top 20 genes were screened out, among which 4 hub genes, which were not researched in depth so far, were selected after literature retrieval, including CDC45, CDCA5, KIF4A, ESPL1. The four genes were up-regulated in EOC tissues compared with normal tissues, but their expression decreased gradually with the continuous progression of EOC. Survival curves illustrated that patients with a lower level of CDCA5 and ESPL1 had better overall survival and progression-free survival statistically.

Conclusion

Two hub genes, CDCA5 and ESPL1, identified as probably playing tumor-promotive roles, have great potential to be utilized as novel therapeutic targets for EOC treatment.

Screening and Identification of an Immune-Associated lncRNA Prognostic Signature in Ovarian Carcinoma: Evidence from Bioinformatic Analysis

Backgrounds

The dysregulated long noncoding RNAs (lncRNAs) have been described to be crucial regulators in the progression of ovarian carcinoma. The infiltration status of immune cells is also related to the clinical outcomes in ovarian carcinoma. The present research is aimed at constructing an immune-associated lncRNA signature with potential prognostic value for ovarian carcinoma patients.

Methods

We obtained 379 ovarian carcinoma cases with available clinical data and transcriptome data from The Cancer Genome Atlas database to evaluate the infiltration status of immune cells, thereby generating high and low immune cell infiltration groups. According to the expression of the immune-associated lncRNA signature, the risk score of each case was calculated. The high- and low-risk groups were classified using the median risk score as threshold.

Results

A total of 169 immune-associated lncRNAs that differentially expressed in ovarian carcinoma were included. According to the Lasso regression analysis and Cox univariate and multivariate analyses, 5 immune-associated lncRNAs, including AC134312.1, AL133467.1, CHRM3-AS2, LINC01722, and LINC02207, were identified as a predictive signature with significant prognostic value in ovarian carcinoma. The following Kaplan-Meier analysis, ROC analysis, and Cox univariate and multivariate analyses further suggested that the predicted signature may be an independent prognosticator for patients with ovarian carcinoma. The following gene set enrichment analysis showed that this 5 immune-associated lncRNAs signature was significantly related to the hedgehog pathway, basal cell carcinoma, Wnt signaling pathway, cytokine receptor interaction, antigen processing and presentation, and T cell receptor pathway.

Conclusion

: This study suggested a predictive model with 5 immune-associated lncRNAs that has an independent prognostic value for ovarian carcinoma patients.

Knockdown of PNO1 inhibits esophageal cancer progression

The present study aimed to investigate the role of partner of NOB1 homolog (PNO1) in esophageal cancer (EC). The expression levels of PNO1 in EC were primarily analyzed using data obtained from databases. PNO1 expression was also knocked down in EC cells (Eca-109 and TE1) to determine the biological effects of PNO1 on tumorigenesis in vitro and in vivo. In addition, possible downstream targets of PNO1 in EC were identified. The expression levels of PNO1 were upregulated in the tumor tissues compared with that noted in normal tissues. Moreover, the knockdown (KD) of PNO1 suppressed cell proliferation, migration and invasion, and promoted cell apoptosis (P<0.05). Furthermore, the protein expression levels of AKT1, Twist, Myc, mTOR, matrix metalloproteinase 2 (MMP2), nuclear factor (NF)-κB p65 and β-catenin 1 (CTNNB1) were downregulated following the KD of PNO1 in Eca-109 cells (P<0.05). In addition, the overexpression of CTNNB1 reversed the effects of PNO1 KD in Eca-109 cells (P<0.05). In conclusion, the findings of the present study suggest that PNO1 promotes EC progression by regulating AKT1, Twist, Myc, mTOR, MMP2, NF-κB p65 and CTNNB1 expression.

Identification of a 5-Gene-Based Scoring System by WGCNA and LASSO to Predict Prognosis for Rectal Cancer Patients

Background

Although accumulating evidence suggested that a molecular signature panel may be more effective for the prognosis prediction than routine clinical characteristics, current studies mainly focused on colorectal or colon cancers. No reports specifically focused on the signature panel for rectal cancers (RC). Our present study was aimed at developing a novel prognostic signature panel for RC.

Methods

Sequencing (or microarray) data and clinicopathological details of patients with RC were retrieved from The Cancer Genome Atlas (TCGA-READ) or the Gene Expression Omnibus (GSE123390, GSE56699) database. A weighted gene coexpression network was used to identify RC-related modules. The least absolute shrinkage and selection operator analysis was performed to screen the prognostic signature panel. The prognostic performance of the risk score was evaluated by survival curve analyses. Functions of prognostic genes were predicted based on the interaction proteins and the correlation with tumor-infiltrating immune cells. The Human Protein Atlas (HPA) tool was utilized to validate the protein expression levels.

Results

A total of 247 differentially expressed genes (DEGs) were commonly identified using TCGA and GSE123390 datasets. Brown and yellow modules (including 77 DEGs) were identified to be preserved for RC. Five DEGs (ASB2, GPR15, PRPH, RNASE7, and TCL1A) in these two modules constituted the optimal prognosis signature panel. Kaplan-Meier curve analysis showed that patients in the high-risk group had a poorer prognosis than those in the low-risk group. Receiver operating characteristic (ROC) curve analysis demonstrated that this risk score had high predictive accuracy for unfavorable prognosis, with the area under the ROC curve of 0.915 and 0.827 for TCGA and GSE56699 datasets, respectively. This five-mRNA classifier was an independent prognostic factor. Its predictive accuracy was also higher than all clinical factor models. A prognostic nomogram was developed by integrating the risk score and clinical factors, which showed the highest prognostic power. ASB2, PRPH, and GPR15/TCL1A were predicted to function by interacting with CASQ2/PDK4/EPHA67, PTN, and CXCL12, respectively. TCL1A and GPR15 influenced the infiltration levels of B cells and dendritic cells, while the expression of PRPH was positively associated with the abundance of macrophages. HPA analysis supported the downregulation of PRPH, RNASE7, CASQ2, EPHA6, and PDK4 in RC compared with normal controls.

Conclusion

Our immune-related signature panel may be a promising prognostic indicator for RC.

Identification of HCG18 and MCM3AP-AS1 That Associate With Bone Metastasis, Poor Prognosis and Increased Abundance of M2 Macrophage Infiltration in Prostate Cancer

Background:

Bone metastasis is a leading cause of the high mortality rate of prostate cancer (PCa), but curative strategies remain lacking. Recent studies suggest long non-coding RNAs (lncRNAs) may be potential targets to develop drugs. However, PCa bone metastasis-specifically-related lncRNAs were rarely reported. This study aimed to identify crucial lncRNAs and reveal their function mechanisms.

Methods:

GSE32269 and GSE26964 microarray datasets, downloaded from the Gene Expression Omnibus database, were used to analyze differentially expressed genes (DEGs)/lncRNAs (DELs) and miRNAs (DEMs), respectively. Weighted gene co-expression network analysis was performed to screen PCa bone metastasis-associated modules. The co-expression and competing endogenous RNAs (ceRNAs) networks were constructed to identify hub lncRNAs. Univariate Cox regression analysis was conducted to determine their prognostic values. The correlation of lncRNAs with immune infiltrating cells was analyzed by using Tumor IMmune Estimation Resource. Therapeutic drugs were predicted by querying the Connectivity Map (CMap) and the Comparative Toxicogenomics Database (CTD).

Results:

A total of 18 DELs, 2,614 DEGs and 86 DEMs were screened between bone metastatic and primary PCa samples. Four modules enriched by DEGs were shown to be bone metastasis-associated. LncRNA HCG18 and MCM3AP-AS1 were identified to be important because they existed in both of the co-expression and ceRNA networks (forming the relationship pairs: HCG18/MCM3AP-AS1-KNTC1, MCM3AP-AS1-hsa-miR-508-3p-DTL and HCG18/MCM3AP-AS1-hsa-miR-127-3p-CDKN3). All the genes in these interaction pairs were significantly associated with overall survival of PCa patients. Also, HCG18, MCM3AP-AS1 and their target mRNAs were positively correlated with various tumor-infiltrated immune cells, especially increased M2 macrophages. Valproic acid and trichostatin A may be effective to treat PCa bone metastasis by targeting HCG18 and MCM3AP-AS1.

Conclusion:

HCG18 and MCM3AP-AS1 that regulate M2 macrophage infiltration may be important targets to treat PCa bone metastasis and improve prognosis.

Long non-coding RNA LINC00665 promotes gemcitabine resistance of Cholangiocarcinoma cells via regulating EMT and stemness properties through miR-424-5p/BCL9L axis

Gemcitabine is the first-line chemotherapy drug for cholangiocarcinoma (CCA), but acquired resistance has been frequently observed in CCA patients. To search for potential long noncoding RNAs (lncRNAs) involved in gemcitabine resistance, two gemcitabine resistant CCA cell lines were established and dysregulated lncRNAs were identified by lncRNA microarray. Long intergenic non-protein coding RNA 665 (LINC00665) were found to rank the top 10 upregulated lncRNAs in our study, and high LINC00665 expression was closely associated with poor prognosis and chemoresistance of CCA patients. Silencing LINC00665 in gemcitabine resistant CCA cells impaired gemcitabine tolerance, while enforced LINC00665 expression increased gemcitabine resistance of sensitive CCA cells. The gemcitabine resistant CCA cells showed increased EMT and stemness properties, and silencing LINC00665 suppressed sphere formation, migration, invasion and expression of EMT and stemness markers. In addition, Wnt/β-Catenin signaling was activated in gemcitabine resistant CCA cells, but LINC00665 knockdown suppressed Wnt/β-Catenin activation. B-cell CLL/lymphoma 9-like (BCL9L), the nucleus transcriptional regulators of Wnt/β-Catenin signaling, plays a key role in the nucleus translocation of β-Catenin and promotes β-Catenin-dependent transcription. In our study, we found that LINC00665 regulated BCL9L expression by acting as a molecular sponge for miR-424-5p. Moreover, silencing BCL9L or miR-424-5p overexpression suppressed gemcitabine resistance, EMT, stemness and Wnt/β-Catenin activation in resistant CCA cells. In conclusion, our results disclosed the important role of LINC00665 in gemcitabine resistance of CCA cells, and provided a new biomarker or therapeutic target for CCA treament.

Identification of four methylation-driven genes as candidate biomarkers for monitoring single-walled carbon nanotube-induced malignant transformation of the lung

Long-term exposure to carbon nanotubes (CNTs) has been reported to induce malignant transformation. This study aimed to screen candidate biomarkers for monitoring occupational workers to prevent the development of lung cancer. mRNA (GSE56104) and methylation (GSE153246) profiles of lung epithelial BEAS-2B cells exposed to malignant transformation dose of single-walled CNTs or control medium were downloaded from Gene Expression Omnibus database. A total of 1513 differentially expressed genes (DEGs) and 912 differentially methylated genes (DMGs) were identified using LIMMA method. The weighted correlation network analysis identified blue and turquoise modules were associated with malignant transformation of BEAS-2B cells, 124 DMGs of which were overlapped with DEGs. The mRNA and methylation levels of four methylation-driven DEGs were validated in both lung adenocarcinoma (LUAD) and squamous cell carcinomas (LUSC) of The Cancer Genome Atlas dataset and they were associated with overall survival of LUAD patients. Downregulation of PXMP4 and MCOLN2, while upregulation of MET was confirmed in both LUSC and LUAD via Human Protein Atlas analysis. PXMP4 and MET protein levels were also supported in the proteomic analysis of LUAD. Receiver operating characteristic (ROC) curve analysis showed the combination of four genes may be the optimal biomarker for predicting lung cancer, with the area under ROC curve >0.9. Function analysis revealed BARX2 may interact with CCND1 to regulate cell cycle; MET and PXMP4/MCOLN2 may positively correlate with CCR5/IL-6 or GATA3/HLA-DPB1/HLA-DPA1 to involve immune regulation. In conclusion, these four methylation-driven genes may be candidate prognostic and diagnostic biomarkers for single-walled CNT-related lung cancer.

Immune-Related lncRNA to Construct Novel Signature and Predict the Immune Landscape of Human Hepatocellular Carcinoma

The signature composed of immune-related long noncoding ribonucleic acids (irlncRNAs) with no requirement of specific expression level seems to be valuable in predicting the survival of patients with hepatocellular carcinoma (HCC). Here, we retrieved raw transcriptome data from The Cancer Genome Atlas (TCGA), identified irlncRNAs by co-expression analysis, and recognized differently expressed irlncRNA (DEirlncRNA) pairs using univariate analysis. In addition, we modified Lasso penalized regression. Then, we compared the areas under curve, counted the Akaike information criterion (AIC) values of 5-year receiver operating characteristic curve, and identified the cut-off point to set up an optimal model for distinguishing the high- or low-disease-risk groups among patients with HCC. We then reevaluated them from the viewpoints of survival, clinic-pathological characteristics, tumor-infiltrating immune cells, chemotherapeutics efficacy, and immunosuppressed biomarkers. 36 DEirlncRNA pairs were identified, 12 of which were included in a Cox regression model. After regrouping the patients by the cut-off point, we could more effectively differentiate between them based on unfavorable survival outcome, aggressive clinic-pathological characteristics, specific tumor immune infiltration status, low chemotherapeutics sensitivity, and highly expressed immunosuppressed biomarkers. The signature established by paring irlncRNA regardless of expression levels showed a promising clinical prediction value.

Long non-coding RNAs: Emerging regulators for chemo/immunotherapy resistance in cancer stem cells

Cancer stem cells (CSCs) are a small subpopulation of tumor cells critical for tumor development. Their unique abilities, such as self-renewal, have resulted in tumor resistance to various cancer treatments, including traditional chemotherapy and latest immunotherapy. CSCs-targeting therapy is a promising treatment to overcome the therapeutic resistances to different tumors. However, despite their significance, the regulatory mechanism generating therapy-resistant CSCs is still obscure. Long non-coding RNAs (lncRNAs) are key regulators in various biological processes, including cell proliferation, apoptosis, migration, and invasion. Recent studies have revealed that lncRNAs play an important role in the therapeutic resistance of CSCs. Here we summarize the latest studies on the regulatory role of lncRNAs in sustaining the stemness of CSCs, and discuss the associated mechanisms behind these behavior changes in CSCs-related chemo- and immune-resistance. Future research implications are also discussed, shedding light on the potential CSCs-targeted strategies to break through the resistance of current therapies.

Long noncoding RNA: a dazzling dancer in tumor immune microenvironment

Long noncoding RNAs (lncRNAs) are a class of endogenous, non-protein coding RNAs that are highly linked to various cellular functions and pathological process. Emerging evidence indicates that lncRNAs participate in crosstalk between tumor and stroma, and reprogramming of tumor immune microenvironment (TIME). TIME possesses distinct populations of myeloid cells and lymphocytes to influence the immune escape of cancer, the response to immunotherapy, and the survival of patients. However, hitherto, a comprehensive review aiming at relationship between lncRNAs and TIME is missing. In this review, we focus on the functional roles and molecular mechanisms of lncRNAs within the TIME. Furthermore, we discussed the potential immunotherapeutic strategies based on lncRNAs and their limitations.

Three-gene prognostic biomarkers for seminoma identified by weighted gene co-expression network analysis

Testicular germ cell tumors (TGCTs) are common in young males, and seminoma accounts for a large proportion of TGCTs. However, there are limited records on the exploration of novel biomarkers for seminoma. Hence, we aimed to identify new biomarkers associated with overall survival in seminoma. mRNA-seq and clinical traits of TGCTs were downloaded from UCSC XENA and analyzed by weighted gene co-expression network analysis. After intersection with differentially expressed genes in GSE8607, common genes were subjected to protein-protein interaction (PPI) network construction and enrichment analyses. Then, the top 10 common genes were investigated by Kaplan–Meier (KM) survival analyses and univariate Cox regression analyses. Ultimately, TYROBP, CD68, and ITGAM were considered three prognostic biomarkers in seminoma. Based on correlation analysis between these genes and immune infiltrates, we suggest that the three biomarkers influence the survival of seminoma patients, possibly through regulating the infiltration of immune cells. In conclusion, our study demonstrated that TYROBP, CD68, and ITGAM could be regarded as prognostic biomarkers and therapeutic targets for seminoma patients.

Three Genes Predict Prognosis in Microenvironment of Ovarian Cancer

Ovarian cancer (OC) is the deadliest gynecological cancer in women. Immune cell infiltration has a critical role in regulating carcinogenesis and prognosis in OC. To identify prognostic genes relevant to the tumor microenvironment in OC, we investigated the association between OC and gene expression profiles. Results obtained with the ESTIMATE R tool showed that immune score and stromal score were correlated with lymphatic invasion, and high immune score predicted a favorable prognosis. A total of 342 common differentially expressed genes were identified according to the two scores; these genes were mainly involved in immune response, extracellular region, and serine-type endopeptidase activity. Three immune-related prognostic genes were selected by univariate and multivariate Cox regression analysis. We further established a prognostic model and validated the prognostic value of three hub genes in different databases; our results showed that this model could accurately predict survival and evaluate prognosis independent of clinical characteristics. Three hub genes have prognostic value in OC. TIMER analysis revealed that the three genes were correlated with different immune cells. Low levels of macrophage infiltration and high levels of CD4+ T cell infiltration were associated with favorable survival outcomes. Arm-level gain of GYPC was correlated with neutrophils and dendritic cells. These findings indicate that CXCR4, GYPC, and MMP12 modulate prognosis via effects on the infiltration of immune cells. Thus, these genes represent potential targets for immune therapy in OC.