LncRNA MIAT correlates with immune infiltrates and drug reactions in hepatocellular carcinoma

Long non-coding RNAs in cancer: multifaceted roles and potential targets for immunotherapy

Cancer remains a major global health concern with high mortality rates mainly due to late diagnosis and poor prognosis. Long non-coding RNAs (lncRNAs) are emerging as key regulators of gene expression in human cancer, functioning through various mechanisms including as competing endogenous RNAs (ceRNAs) and indirectly regulating miRNA expression. LncRNAs have been found to have both oncogenic and tumor-suppressive roles in cancer, with the former promoting cancer cell proliferation, migration, invasion, and poor prognosis. Recent research has shown that lncRNAs are expressed in various immune cells and are involved in cancer cell immune escape and the modulation of the tumor microenvironment, thus highlighting their potential as targets for cancer immunotherapy. Targeting lncRNAs in cancer or immune cells could enhance the anti-tumor immune response and improve cancer immunotherapy outcomes. However, further research is required to fully understand the functional roles of lncRNAs in cancer and the immune system and their potential as targets for cancer immunotherapy. This review offers a comprehensive examination of the multifaceted roles of lncRNAs in human cancers, with a focus on their potential as targets for cancer immunotherapy. By exploring the intricate mechanisms underlying lncRNA-mediated regulation of cancer cell proliferation, invasion, and immune evasion, we provide insights into the diverse therapeutic applications of these molecules.

LINC00887 regulates malignant progression and T-cell chemotaxis in clear cell renal cell carcinoma by activating CD70 via recruitment of SPI1

BACKGROUND

LINC00887 has been mentioned in several articles regarding its involvement in various cancers like nasopharyngeal carcinoma, lung cancer and glioma. However, the mechanism of LINC00887 in the malignant progression of clear cell renal cell carcinoma (ccRCC) is still unclear. The topic of our study is mainly centered on exploring how LINC00887 exactly affects ccRCC malignant progression.

METHODS

The bioinformatics method predicted the downstream TF and target genes of LINC00887 by the "LncRNA-transcription factor (TF)-Gene" triplet model. RNA immunoprecipitation, chromatin immunoprecipitation analysis, and Dual-luciferase reporter assay determined the regulatory relationship between LINC00887 and its downstream genes. The LINC00887 expression and its downstream gene expression in ccRCC cells were examined by qRT-PCR and Western blot. The effect of LINC00887-SPI1-CD70 modulation axis on proliferative transfer, cell stemness and T cell chemotaxis of ccRCC cells was examined in cellular and animal experiments.

RESULTS

Our research demonstrated an upregulation of LINC00887 in ccRCC, which facilitated tumor growth and stemness in vivo. In addition, LINC00887 could upregulate the CD70 expression by recruiting transcriptional factor SPI1. The results of in vitro experiments illustrated that the LINC00887-SPI1-CD70 regulatory axis facilitated ccRCC malignant progression by promoting cell stemness and hindering T-cell chemotaxis.

CONCLUSION

LINC00887, by recruiting SPI1, activated CD70 transcription, thereby propelling malignant progression and cell stemness and suppressing T cell chemotaxis in ccRCC. Based on our findings, we believed that the LINC00887-SPI1-CD70 regulatory axis had the potential to be a critical breakthrough for treating ccRCC.

The sorafenib resistance-related gene signature predicts prognosis and indicates immune activity in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related death worldwide. Most patients with advanced HCC acquire sorafenib resistance. Drug resistance reflects the heterogeneity of tumors and is the main cause of tumor recurrence and death.We identified and validated sorafenib resistance related-genes (SRGs) as prognostic biomarkers for HCC. We obtained SRGs from the Gene Expression Omnibus and selected four key SRGs using the least absolute shrinkage and selection operator, random forest, and Support Vector Machine-Recursive feature elimination machine learning algorithms. Samples from the The Cancer Genome Atlas (TCGA)-HCC were segregated into two groups by consensus clustering. Following difference analysis, 19 SRGs were obtained through univariate Cox regression analysis, and a sorafenib resistance model was constructed for risk stratification and prognosis prediction. In multivariate Cox regression analysis, the risk score was an independent predictor of overall survival (OS). Patients classified as high-risk were more sensitive to other chemotherapy drugs and showed a higher expression of the common immune checkpoints. Additionally, the expression of drug-resistance genes was verified in the International Cancer Genome Consortium cohort. A nomogram model with a risk score was established, and its prediction performance was verified by calibration chart analysis of the TCGA-HCC cohort. We conclude that there is a significant correlation between sorafenib resistance and the tumor immune microenvironment in HCC. The risk score could be used to identify a reliable prognostic biomarker to optimize the therapeutic benefits of chemotherapy and immunotherapy, which can be helpful in the clinical decision-making for HCC patients.

The current status and future of PD-L1 in liver cancer

The application of immunotherapy in tumor, especially immune checkpoint inhibitors (ICIs), has played an important role in the treatment of advanced unresectable liver cancer. However, the efficacy of ICIs varies greatly among different patients, which has aroused people's attention to the regulatory mechanism of programmed death ligand-1 (PD-L1) in the immune escape of liver cancer. PD-L1 is regulated by multiple levels and signaling pathways in hepatocellular carcinoma (HCC), including gene variation, epigenetic inheritance, transcriptional regulation, post-transcriptional regulation, and post-translational modification. More studies have also found that the high expression of PD-L1 may be the main factor affecting the immunotherapy of liver cancer. However, what is the difference of PD-L1 expressed by different types of cells in the microenvironment of HCC, and which type of cells expressed PD-L1 determines the effect of tumor immunotherapy remains unclear. Therefore, clarifying the regulatory mechanism of PD-L1 in liver cancer can provide more basis for liver cancer immunotherapy and combined immune treatment strategy. In addition to its well-known role in immune regulation, PD-L1 also plays a role in regulating cancer cell proliferation and promoting drug resistance of tumor cells, which will be reviewed in this paper. In addition, we also summarized the natural products and drugs that regulated the expression of PD-L1 in HCC.

Expression patterns and functional analysis of porcine lnc-34015

Long noncoding RNAs (lncRNAs) play important roles in immune regulation in humans and animals. The lnc-34015 was discovered to be critical for the development of muscles, based on the muscle transcriptome of pigs; however, the underlying molecular mechanism requires better understanding. Here, the sequence characteristics of lnc-34015 were analyzed and a competitive endogenous RNA regulatory network of lncRNA was predicted. The developmental expression trend and tissue expression profiles of lnc-34015 were investigated using quantitative polymerase chain reaction. The lnc-34015 sequence is overlapped with introns 11 and 12 of CWF19L1, while CWF19L1, PKD2L1, and CHUK were identified as cis-regulatory genes of lnc-34015. Bioinformatics analyses revealed that lnc-34015 binds to 15 microRNAs (miRNAs), including miR-3646, miR-377-3p, and miR-190b-3p, to regulate downstream gene expression. GO and KEGG enrichment results show that lnc-34015 was mainly involved in cell proliferation, stress response, transcriptional regulation, and alternative splicing. The expression trend of lnc-34015 in muscle was similar to that of target genes and opposite to that of miRNAs. The expression of lnc-34015 was significantly higher in the porcine small intestine and IPEC-J2 cells. Our findings suggest that lnc-34015 regulates CHUK, ZBTB20, and XIAP gene expression by competing with endogenous RNAs to regulate porcine inflammatory responses.

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.

Long noncoding RNA MIAT regulates TP53 ubiquitination and expedites prostate adenocarcinoma progression by recruiting TBL1X

Despite recent advances in cancer immunotherapy, their efficacy for treating patients with prostate adenocarcinoma (PRAD) is low due to complex immune evasion mechanisms. However, the function of long non-coding RNA (lncRNAs) in immune evasion has not been fully clarified. This study aimed to expound the role of myocardial infarction-associated transcript (MIAT), a lncRNA significantly upregulated in three PRAD-associated datasets, in immune evasion and try to reveal the potential mechanism. MIAT was highly expressed in PRAD tissues and predicted poor prognosis, and suppression of MIAT inhibited the malignant biological behavior of PRAD cells. Moreover, the depletion of MIAT promoted the immune response of CD8+ T cells and hampered the immune evasion of PRAD cells. In addition, MIAT downregulated TP53 protein expression by recruiting transducin beta-like protein 1X (TBL1X) for ubiquitination modification. Silencing of TP53 or overexpression of TBL1X was enough to abate the tumor suppressive effects of MIAT knockdown in vitro and in vivo. Our results provide evidence for a novel regulation mechanism of CD8+ T cells in PRAD and MIAT may serve as a potential therapeutic target in PRAD.

DISCERN: deep single-cell expression reconstruction for improved cell clustering and cell subtype and state detection

BACKGROUND

Single-cell sequencing provides detailed insights into biological processes including cell differentiation and identity. While providing deep cell-specific information, the method suffers from technical constraints, most notably a limited number of expressed genes per cell, which leads to suboptimal clustering and cell type identification.

RESULTS

Here, we present DISCERN, a novel deep generative network that precisely reconstructs missing single-cell gene expression using a reference dataset. DISCERN outperforms competing algorithms in expression inference resulting in greatly improved cell clustering, cell type and activity detection, and insights into the cellular regulation of disease. We show that DISCERN is robust against differences between batches and is able to keep biological differences between batches, which is a common problem for imputation and batch correction algorithms. We use DISCERN to detect two unseen COVID-19-associated T cell types, cytotoxic CD4+ and CD8+ Tc2 T helper cells, with a potential role in adverse disease outcome. We utilize T cell fraction information of patient blood to classify mild or severe COVID-19 with an AUROC of 80% that can serve as a biomarker of disease stage. DISCERN can be easily integrated into existing single-cell sequencing workflow.

CONCLUSIONS

Thus, DISCERN is a flexible tool for reconstructing missing single-cell gene expression using a reference dataset and can easily be applied to a variety of data sets yielding novel insights, e.g., into disease mechanisms.

A New Understanding of Long Non-Coding RNA in Hepatocellular Carcinoma-From m6A Modification to Blood Biomarkers

With recent advancements in biological research, long non-coding RNAs (lncRNAs) with lengths exceeding 200 nucleotides have emerged as pivotal regulators of gene expression and cellular phenotypic modulation. Despite initial skepticism due to their low sequence conservation and expression levels, their significance in various biological processes has become increasingly apparent. We provided an overview of lncRNAs and discussed their defining features and modes of operation. We then explored their crucial function in the hepatocarcinogenesis process, elucidating their complex involvement in hepatocellular carcinoma (HCC). The influential role of lncRNAs within the HCC tumor microenvironment is emphasized, illustrating their potential as key modulators of disease dynamics. We also investigated the significant influence of N6-methyladenosine (m6A) modification on lncRNA function in HCC, enhancing our understanding of both their roles and their upstream regulators. Additionally, the potential of lncRNAs as promising biomarkers was discussed in liver cancer diagnosis, suggesting a novel avenue for future research and clinical application. Finally, our work underscored the dual potential of lncRNAs as both contributors to HCC pathogenesis and innovative tools for its diagnosis. Existing challenges and prospective trajectories in lncRNA research are also discussed, emphasizing their potential in advancing liver cancer research.

MIAT shuttled by tumor-secreted exosomes promotes paclitaxel resistance in esophageal cancer cells by activating the TAF1/SREBF1 axis

Chemoresistance remains a major obstacle to the treatment of esophageal cancer (EC). Exosome-mediated transfer of long noncoding RNAs (lncRNAs) has recently been unveiled to correlate with the regulation of drug resistance in EC. This study aimed to investigate the physiological mechanisms by which exosome-encapsulated lncRNA myocardial infarction-associated transcript (MIAT) derived from tumor cells might mediate the paclitaxel (PTX) resistance of EC cells. First, MIAT was experimentally determined to be upregulated in PTX nonresponders and PTX-resistant EC cells. Silencing of MIAT in PTX-resistant EC cells decreased cell viability and enhanced apoptosis, corresponding to a reduced half-maximal inhibitory concentration (IC50 ) value. Next, exosomes were isolated from EC109 and EC109/T cells, and EC109 cells were cocultured with EC109/T-cell-derived exosomes. Accordingly, MIAT was revealed to be transmitted through exosomes from EC109/T cells to EC109 cells. Tumor-derived exosomes carrying MIAT increased the IC50 value of PTX and suppressed apoptosis in EC109 cells to promote PTX resistance. Furthermore, MIAT promoted the enrichment of TATA-box binding protein-associated Factor 1 (TAF1) in the promoter region of sterol regulatory element binding transcription factor 1 (SREBF1), as shown by a chromatin immunoprecipitation assay. This might be the mechanism by which MIAT could promote PTX resistance. Finally, in vivo experiments further confirmed that the knockdown of MIAT attenuated the resistance of EC cells to PTX. Collectively, these results indicate that tumor-derived exosome-loaded MIAT activates the TAF1/SREBF1 axis to induce PTX resistance in EC cells, providing a potential therapeutic target for overcoming PTX resistance in EC.

Regulation of T cell differentiation and function by long noncoding RNAs in homeostasis and cancer

Long noncoding RNAs (lncRNAs) increase in genomes of complex organisms and represent the largest group of RNA genes transcribed in mammalian cells. Previously considered only transcriptional noise, lncRNAs comprise a heterogeneous class of transcripts that are emerging as critical regulators of T cell-mediated immunity. Here we summarize the lncRNA expression landscape of different T cell subsets and highlight recent advances in the role of lncRNAs in regulating T cell differentiation, function and exhaustion during homeostasis and cancer. We discuss the different molecular mechanisms of lncRNAs and highlight lncRNAs that can serve as novel targets to modulate T cell function or to improve the response to cancer immunotherapies by modulating the immunosuppressive tumor microenvironment.

2,5-dimethylcelecoxib alleviated NK and T-cell exhaustion in hepatocellular carcinoma via the gastrointestinal microbiota-AMPK-mTOR axis

BACKGROUND

2,5-dimethylcelecoxib (DMC), a derivative of celecoxib, is an inhibitor of microsomal prostaglandin E synthase-1 (mPGES-1). Our previous studies have demonstrated that DMC inhibits the expression of programmed death-ligand 1 on hepatocellular carcinoma (HCC) cells to prevent tumor progression. However, the effect and mechanism of DMC on HCC infiltrating immune cells remain unclear.

METHODS

In this study, single-cell-based high-dimensional mass cytometry was performed on the tumor microenvironment of HCC mice treated with DMC, celecoxib and MK-886 (a known mPGES-1 inhibitor). Moreover, 16S ribosomal RNA sequencing was employed to analyze how DMC improved the tumor microenvironment of HCC by remodeling the gastrointestinal microflora.

RESULTS

We found that (1) DMC significantly inhibited the growth of HCC and improved the prognosis of the mice, and this depended on the stronger antitumor activity of natural killer (NK) and T cells; (2) compared with celecoxib and MK-886, DMC significantly enhanced the cytotoxic and stem-like potential, and inhibited exhaustion of NK and T cells; (3) mechanistically, DMC inhibited the expression of programmed cell death protein-1 and upregulated interferon-γ expression of NK and T cells via the gastrointestinal microbiota (Bacteroides acidifaciens, Odoribacter laneus, and Odoribacter splanchnicus)-AMPK-mTOR axis.

CONCLUSIONS

Our study uncovers the role of DMC in improving the tumor microenvironment of HCC, which not only enriches the relationship between the mPGES-1/prostaglandin E2 pathway and the antitumor function of NK and T cells, but also provide an important strategic reference for multitarget or combined immunotherapy of HCC.Cite Now.

Identification of ribosomal protein family as immune-cell-related biomarkers of NAFLD by bioinformatics and experimental analyses

Background

Immune cells play an integral role in the development and progression of non-alcoholic fatty liver disease (NAFLD). This study was to identify immune-cell-related biomarkers for the diagnosis and treatment of NAFLD.

Methods and findings

First, we introduced human liver transcriptome data from the GEO database (GSE48452 and GSE126848) and performed a weighted gene co-expression network analysis (WGCNA) to screen out the modules related to immune cell infiltration and to identify immune-cell-related differentially expressed genes (ICR-DEGs) associated with NAFLD progression. Further, the protein-protein interaction (PPI) network of ICR-DEGs was established to obtain hub genes and subsequently, the expression trend analysis was conducted to identify immune-cell-related biomarkers of NAFLD. Finally, the mRNA expression of biomarkers was validated in a NAFLD mouse model induced by high-fat diet (HFD) feeding. In total, we identified 66 ICR-DEGs and 13 hub genes associated with NAFLD. Among them, 9 hub genes (CD247, CD74, FCGR2B, IL2RB, INPP5D, MRPL16, RPL35, RPS3A, RPS8) were correlated with the infiltrating immune cells by the Pearson correlation analysis. Subsequently, 4 immune-cell-related biomarkers (RPL35, RPS3A, RPS8, and MRPL16) with the same expression trends in GSE48452 and GSE126848 datasets were identified. These biomarkers were enriched in immune-related pathways and had a good ability to distinguish between NASH and healthy samples. Moreover, we constructed a competing endogenous RNA (ceRNA) network of biomarkers and predicted twenty potential therapeutic drugs targeting RPS3A such as taxifolin and sitagliptin. Finally, experimental validation indicated that the hepatic mRNA expression of Rpl35, Rps3A, and Rps8 was significantly decreased in NAFLD mice.

Conclusions

This study identified four ribosomal protein genes (RPL35, RPS3A, RPS8, and MRPL16) as immune-cell-related biomarkers of NAFLD, which may actively participate in the immune processes during NAFLD progression and could serve as potential targets for the diagnosis and treatment of NAFLD.

The role of LncRNAs in tumor immunotherapy

Cancer immunotherapy is a major breakthrough in the history of tumor therapy in the last decade. Immune checkpoint inhibitors blocking CTLA-4/B7 or PD-1/PD-L1 pathways have greatly prolonged the survival of patients with different cancers. Long non-coding RNAs (lncRNAs) are abnormally expressed in tumors and play an important role in tumor immunotherapy through immune regulation and immunotherapy resistance. In this review, we summarized the mechanisms of lncRNAs in regulating gene expression and well-studied immune checkpoint pathways. The crucial regulatory function of immune-related lncRNAs in cancer immunotherapy was also described. Further understanding of the underlying mechanisms of these lncRNAs is of great importance to the development of taking lncRNAs as novel biomarkers and therapeutic targets for immunotherapy.

IncRNA MIAT Accelerates Keloid Formation by miR-411-5p/JAG1 Axis

The long non-coding RNA (lncRNA) myocardial infarction-associated transcript (MIAT) regulates the biological functions of many kinds of cells. The aim of this study is to explore the mechanism of MIAT and how it affects keloid progression. The expressions of MIAT, JAG1, and miR-411-5p in keloid tissues and keloid fibroblasts (KEL FIBs) were quantified by conducting Western blot and quantitative reverse transcription polymerase chain reaction analyses. The influences of MIAT, JAG1, and miR-411-5p on the abilities of KEL FIBs to proliferate, migrate, and invade were assessed by means of the CCK-8, wound healing, and Transwell experiments. To determine the binding relationship among MIAT, JAG1, and miR-411-5p, we performed luciferase reporter and RIP experiments. In keloid tissues and KEL FIBs, MIAT and JAG1 were upregulated while miR-411-5p was downregulated. Knocking-down MIAT or JAG1 significantly inhibited proliferation, migration and invasion. On the contrary, suppressing miR-411-5p expression produced an opposite effect. With regard to mechanisms, MIAT sponged miR-411-5p, which targeted JAG1. MIAT accelerates keloid formation by modulating the miR-411-5p/JAG1 axis.

Prognostic and immunological role of sulfatide-related lncRNAs in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver. Long non-coding RNAs (lncRNAs) play important roles in the occurrence and development of HCC through multiple pathways. Our previous study reported the specific molecular mechanism for sulfatide regulation of integrin αV expression and cell adhesion in HCC cells through lncRNA AY927503. Next, it is necessary to identify more sulfatide-related lncRNAs, explore their clinical signifcance, and determine new targeted treatment strategies.

Methods

Microarrays were used to screen a complete set of lncRNAs with different expression profiles in sulfatide-treated cells. Sulfatide-related lncRNAs expression data and corresponding HCC patient survival information were obtained from the The Cancer Genome Atlas (TCGA) database, and the prognosis prediction model was constructed based on Cox regression analysis. Methylated RNA immunoprecipitation with next generation sequencing (MeRIP-seq) was used to detemine the effect of sulfatide on lncRNAs m6A modification. Tumor Immune Estimation Resource (TIMER) and Gene set nnrichment analysis (GSEA) were utilized to enrich the immune and functional pathways of sulfatide-related lncRNAs.

Results

A total of 85 differentially expressed lncRNAs (|Fold Change (FC)|>2, P<0.05) were screened in sulfatide-treated HCC cells. As a result, 24 sulfatide-related lncRNAs were highly expressed in HCC tissues, six of which were associated with poor prognosis in HCC patients. Based on thses data, a sulfatide-related lncRNAs prognosis assessment model for HCC was constructed. According to this risk score analysis, the overall survival (OS) curve showed that the OS of high-risk patients was significantly lower than that of low-risk patients (P<0.05). Notably, the expression difference in sulfatide-related lncRNA NRSN2-AS1 may be related to sulfatide-induced RNA m6A methylation. In addition, the expression level of NRSN2-AS1 was significantly positively correlated with immune cell infiltration in HCC and participated in the peroxisome and Peroxisome proliferator-activated receptor (PPAR) signaling pathways.

Conclusions

In conclusion, sulfatide-related lncRNAs might be promising prognostic and therapeutic targets for HCC.

The LncRNA signature associated with cuproptosis as a novel biomarker of prognosis in immunotherapy and drug screening for clear cell renal cell carcinoma

Cuproptosis is a new form of cell death, the second form of metal ion-induced cell death defined after ferroptosis. Recently, cuproptosis has been suggested to be associated with tumorigenesis. However, the relationship between cuproptosis and patient prognosis in clear cell renal cell carcinoma (ccRCC) in the context of immunotherapy remains unknown. The aim of this study was to investigate the correlation between cuproptosis-related long non-coding RNA (lncRNA) and ccRCC in terms of immunity as well as prognosis. Clinical information on lncRNAs associated with differences in cuproptosis genes in ccRCC and normal tissues was collected from The Cancer Genome Atlas (TCGA) dataset. Univariate Cox regression was used to screen lncRNAs. A total of 11 lncRNAs closely associated with cuproptosis were further screened and established using the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression, and the samples were randomly divided into training and test groups. A risk prognostic model was constructed using the training group, and the model was validated using the test group. We investigated the predictive ability of the prognostic risk model in terms of clinical prognosis, tumor mutation, immune escape, immunotherapy, tumor microenvironment, immune infiltration levels, and tumor drug treatment of ccRCC. Using the median risk score, patients were divided into low and high-risk groups. Kaplan-Meier curves showed that the overall survival (OS) of patients in the high-risk group was significantly worse than low-risk group (p < 0.001). Receiver operating characteristic (ROC) curves further validated the reliability of our model. The model consistently and accurately predicted prognosis at 1, 3, and 5 years, with an AUC above 0.7. Tumor cell genes generally precede morphological abnormalities; therefore, the model we constructed can effectively compensate for the traditional method of evaluating the prognosis of patients with renal cancer, and our model was also clinically meaningful in predicting ccRCC staging. In addition, lower model risk scores determined by mutational load indicated a good chance of survival. The high-risk group had greater recruitment of immune cells, while the anti-immune checkpoint immunotherapy was less efficacious overall than that of the low-risk group. Tumor and immune-related pathways were enriched, and anti-tumor agents were selected to improve the survival of ccRCC. This prognostic risk model is based on the levels of cuproptosis-associated lncRNAs and provides a new perspective in the clinical assessment and precise treatment of ccRCC.

The diagnostic and prognostic value of pseudogene SIGLEC17P in lung adenocarcinoma and a preliminary functional study

Among malignant tumors, lung adenocarcinoma (LUAD) is the leading cause of death worldwide. This study explored the diagnostic, prognostic value, and preliminary functional verification of sialic acid binding Ig like lectin 17, pseudogene (SIGLEC17P) in LUAD. Prognostic lncRNAs for LUAD were identified by The Cancer Genome Atlas and quantitative real-time PCR (qRT-PCR) was used to detect the expression of SIGLEC17P in LUAD and paracarcinoma tissues. Subsequently, lentiviral vectors were used to overexpress SIGLEC17P in A549 and H1299 cells. The effects of SIGLEC17P overexpression on the proliferation, migration, and invasiveness of LUAD cells (A549 and H1299) were evaluated by Cell Counting Kit-8, wound healing, and transwell migration assays, respectively. Bioinformatics analyses were performed to reveal the potential pathways in which SIGLEC17P is involved in LUAD. qRT-PCR results revealed low SIGLEC17P expression in LUAD tissues and a significant association with the N stage, T stage, and tumor node metastasis stage. Furthermore, the receiver operating characteristic curve demonstrated a reliable diagnostic value. The proliferation, migration, and invasion of LUAD cells were inhibited by overexpression of SIGLEC17P. Bioinformatics analyses suggested that SIGLEC17P might exert antioncogenic effects in LUAD through the mir-20-3p/ADH1B or mir-4476-5p/DPYSL axis. In summary, our results revealed that SIGLEC17P acts as a prognostic biomarker, independent prognostic factor, and potential therapeutic target for patients with LUAD.

Silencing lncRNA HCG18 regulates GPX4-inhibited ferroptosis by adsorbing miR-450b-5p to avert sorafenib resistance in hepatocellular carcinoma

Ferroptosis is potential to relieve drug resistance in hepatocellular carcinoma (HCC). Glutathione peroxidase 4 (GPX4) is a critical modulator of ferroptosis. This study discussed the mechanism of GPX4-inhibited ferroptosis in sorafenib resistance in HCC. HCG18 in HCC cells was detected. Sorafenib resistant (SR) cell line Huh7-SR cells were treated with sorafenib (0, 2.5, 5, 7.5, 10 μM). After silencing HCG18 in Huh7-SR cells, cell activity, proliferation and apoptosis were detected. The levels of iron, the concentration of MDA, GSH and lipid reactive oxygen species (ROS) were measured to evaluate the ferroptosis. The downstream mechanism of HCG18 was predicted and verified. Huh7-SR cells were infected with lentivirus sh-HCG18 to establish xenograft tumor model. HCG18 was elevated in HCC cells and associated with sorafenib resistance. Silencing HCG18 inhibited cell proliferation, promoted apoptosis, and impaired sorafenib resistance. Ferroptosis was inhibited in Huh7-SR cells, while silencing HCG18 inhibited sorafenib resistance by promoting ferroptosis. GPX4 overexpression averted the promotion of sh-HCG18 on ferroptosis, thereby reducing sorafenib resistance. HCG18 sponged miR-450b-5p to regulate GPX4. Collectively, Silencing HCG18 inhibits GPX4 by binding to miR-450b-5p, promotes GPX4-inhibited ferroptosis, and averts sorafenib resistance in HCC.

RNA and RNA Derivatives: Light and Dark Sides in Cancer Immunotherapy

Significance: Immunotherapy, which utilizes the patient's immune system to fight tumor cells, has been approved for the treatment of some types of advanced cancer. Recent Advances: The complexity and diversity of tumor immunity are responsible for the varying response rates toward current immunotherapy strategies and highlight the importance of exploring regulators in tumor immunotherapy. Several genetic factors have proved to be critical regulators of tumor immunotherapy. RNAs, including messenger RNAs and non-coding RNAs, play vital and diverse roles in tumorigenesis, metastasis, drug resistance, and immunotherapy response. RNA modifications, including N6-methyladenosine methylation, are involved in tumor immunity. Critical Issues: A critical issue is the lack of summary of the regulatory RNA molecules and their derivatives in mediating immune activities in human cancers that could provide potential applications for tumor immunotherapeutic strategy. Future Directions: This review summarizes the dual roles (the light and dark sides) of RNA and its derivatives in tumor immunotherapy and discusses the development of RNA-based therapies as novel immunotherapeutic strategies for cancer treatment. Antioxid. Redox Signal. 37, 1266-1290.

Bioinformatics Analysis and Validation of the Role of Lnc-RAB11B-AS1 in the Development and Prognosis of Hepatocellular Carcinoma

Lnc-RAB11B-AS1 is reported to be dysregulated in several types of cancers and can function as both an oncogene and tumor suppressor gene. To evaluate the potential role of lnc-RAB11B-AS1 in hepatocellular carcinoma (HCC), we investigated and evaluated its expression in HCC based on the data mining of a series of public databases, including TCGA, GEO, ICGC, HPA, DAVID, cBioPortal, GeneMIANA, TIMER, and ENCORI. The data showed downregulation of lnc-RAB11B-AS1 in HCC and was accompanied by the synchronous downregulation of the targeted RAB11B mRNA and its protein. Low expression of lnc-RAB11B-AS1 was associated with shorter overall survival (OS) and disease-free survival (DFS) of HCC patients, PD1/PD-L1 was correlated with low expression of RAB11B. Furthermore, Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed a correlation between immune cell change and non-alcoholic fatty liver disease. The above findings revealed that lnc-RAB11B-AS1 was down-regulated in HCC and closely associated with the clinical stage of the HCC patients, suggesting that lnc-RAB11B-AS1 could be a possible predictor for HCC and a potential new therapeutic target for the treatment of HCC.

Non-coding RNAs in hepatocellular carcinoma: Insights into regulatory mechanisms, clinical significance, and therapeutic potential

Hepatocellular carcinoma (HCC) is a complex and heterogeneous malignancy with high incidence and poor prognosis. In addition, owing to the lack of diagnostic and prognostic markers, current multimodal treatment options fail to achieve satisfactory outcomes. Tumor immune microenvironment (TIME), angiogenesis, epithelial-mesenchymal transition (EMT), invasion, metastasis, metabolism, and drug resistance are important factors influencing tumor development and therapy. The intercellular communication of these important processes is mediated by a variety of bioactive molecules to regulate pathophysiological processes in recipient cells. Among these bioactive molecules, non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), account for a large part of the human transcriptome, and their dysregulation affects the progression of HCC. The purpose of this review is to evaluate the potential regulatory mechanisms of ncRNAs in HCC, summarize novel biomarkers from somatic fluids (plasma/serum/urine), and explore the potential of some small-molecule modulators as drugs. Thus, through this review, we aim to contribute to a deeper understanding of the regulatory mechanisms, early diagnosis, prognosis, and precise treatment of HCC.

Regulation of temozolomide resistance via lncRNAs: Clinical and biological properties of lncRNAs in gliomas (Review)

Gliomas are a primary types of intracranial malignancies and are characterized by a poor prognosis due to aggressive recurrence profiles. Temozolomide (TMZ) is an auxiliary alkylating agent that is extensively used in conjunction with surgical resection and forms the mainstay of clinical treatment strategies for gliomas. However, the frequent occurrence of TMZ resistance in clinical practice limits its therapeutic efficacy. Accumulating evidence has demonstrated that long non‑coding RNAs (lncRNAs) can play key and varied roles in glioma progression. lncRNAs have been reported to inhibit glioma progression by targeting various signaling pathways. In addition, the differential expression of lncRNAs has also been found to mediate the resistance of glioma to several chemotherapeutic agents, particularly to TMZ. The present review article therefore summarizes the findings of previous studies in an aim to report the significance and function of lncRNAs in regulating the chemoresistance of gliomas. The present review may provide further insight into the clinical treatment of gliomas.

Comprehensive exploration of tumor immune microenvironment feature and therapeutic response in colorectal cancer based on a novel immune-related long non-coding RNA prognostic signature

Colorectal cancer (CRC) is one of the most common malignant tumors with a high incidence rate and mortality. LncRNA is an important regulator of the immune system. It is of great significance to study immune-related lncRNAs (IR-lncRNAs) for CRC. In this study, we screened IR-lncRNAs differentially expressed in normal and CRC tissues, and Univariate Cox regression and the Least Absolute Shrinkage and Selection Operator were applied to construct IR-lncRNA prognostic signature in TCGA training dataset, and its predictive capability for the prognosis of CRC patients was verified in GSE39582 validation dataset. The novel signature was identified as an independent predictor of prognosis in CRC patients. In addition, the signature could accurately predict the feature of the immune microenvironment and therapeutic response in CRC patients. The CMap database was adopted to screen for small molecule candidate drugs that can reverse and treat high-risk CRC patients. Finally, the expression of six IR-lncRNAs were verified by qRT-PCR in clinical specimens from our patient cohort. In conclusion, we construct an IR-lncRNA prognostic signature, which is a powerful biomarker of CRC and can accurately predict the prognosis, immune microenvironment feature, and therapeutic response of CRC patients.

Construction, bioinformatics analysis, and validation of competitive endogenous RNA networks in ulcerative colitis

Background: Ulcerative colitis (UC) is a common chronic disease of the digestive system. Recently, competitive endogenous RNAs (ceRNAs) have been increasingly used to reveal key mechanisms for the pathogenesis and treatment of UC. However, the role of ceRNA in UC pathogenesis has not been fully clarified. This study aimed to explore the mechanism of the lncRNA-miRNA-mRNA ceRNA network in UC and identify potential biomarkers and therapeutic targets.

Materials and Methods: An integrative analysis of mRNA, microRNA (miRNA), and long non-coding RNA (lncRNA) files downloaded from the Gene Expression Omnibus (GEO) was performed. Differentially expressed mRNA (DE-mRNAs), miRNA (DE-miRNAs), and lncRNA (DE-lncRNAs) were investigated between the normal and UC groups by the limma package. A weighted correlation network analysis (WGCNA) was used to identify the relative model for constructing the ceRNA network, and, concurrently, miRWalk and DIANA-LncBase databases were used for target prediction. Consecutively, the Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) pathway, and Reactome pathway enrichment analyses, protein-protein interaction (PPI) network, Cytohubba, and ClueGO were performed to identify hub genes. Additionally, we examined the immune infiltration characteristics of UC and the correlation between hub genes and immune cells using the immuCellAI database. Finally, the expression of potential biomarkers of ceRNA was validated via qRT-PCR in an experimental UC model induced by dextran sulfate sodium (DSS).

Result: The ceRNA network was constructed by combining four mRNAs, two miRNAs, and two lncRNAs, and the receiver operating characteristic (ROC) analysis showed that two mRNAs (CTLA4 and STAT1) had high diagnostic accuracy (area under the curve [AUC] > 0.9). Furthermore, CTLA4 up-regulation was positively correlated with the infiltration of immune cells. Finally, as a result of this DSS-induced experimental UC model, CTLA4, MIAT, and several associate genes expression were consistent with the results of previous bioinformatics analysis, which proved our hypothesis.

Conclusion: The investigation of the ceRNA network in this study could provide insight into UC pathogenesis. CTLA4, which has immune-related properties, can be a potential biomarker in UC, and MIAT/miR-422a/CTLA4 ceRNA networks may play important roles in UC.

Identification of m6A- and ferroptosis-related lncRNA signature for predicting immune efficacy in hepatocellular carcinoma

Background

N6-methyladenosine (m6A) methylation and ferroptosis assist long noncoding RNAs (lncRNAs) in promoting immune escape in hepatocellular carcinoma (HCC). However, the predictive value of m6A- and ferroptosis-related lncRNAs (mfrlncRNAs) in terms of immune efficacy remains unknown.

Method

A total of 365 HCC patients with complete data from The Cancer Genome Atlas (TCGA) database were used as the training cohort, and half of them were randomly selected as the validation cohort. A total of 161 HCC patients from the International Cancer Genome Consortium (ICGC) database were used as external validation (ICGC cohort).

Results

We first identified a group of specific lncRNAs associated with both m6A regulators and ferroptosis-related genes and then constructed prognosis-related mfrlncRNA pairs. Based on this, the mfrlncRNA signature was constructed using the least absolute shrinkage and selection operator (LASSO) analysis and Cox regression. Notably, the risk score of patients was proven to be an independent prognostic factor and was better than the TNM stage and tumor grade. Moreover, patients with high-risk scores had lower survival rates, higher infiltration of immunosuppressive cells (macrophages and Tregs), lower infiltration of cytotoxic immune cells (natural killer cells), poorer immune efficacy (both immunophenoscore and score of tumor immune dysfunction and exclusion), higher IC₅₀, and enrichment of the induced Treg pathway, which confirmed that the mfrlncRNA signature contributed to survival prediction and risk stratification of patients with HCC.

Conclusions

The mfrlncRNA signature, which has great prognostic value, provides new clues for identifying “cold” and “hot” tumors and might have crucial implications for individualized therapy to improve the survival rate of patients with HCC.

Noncoding RNA-mediated molecular bases of chemotherapy resistance in hepatocellular carcinoma

Despite the significant progress in decreasing the occurrence and mortality of hepatocellular carcinoma (HCC), it remains a public health issue worldwide on the basis of its late presentation and tumor recurrence. To date, apart from surgical interventions, such as surgical resection, liver transplantation and locoregional ablation, current standard antitumor protocols include conventional cytotoxic chemotherapy. However, due to the high chemoresistance nature, most current therapeutic agents show dismal outcomes for this refractory malignancy, leading to disease relapse. Nevertheless, the molecular mechanisms involved in chemotherapy resistance remain systematically ambiguous. Herein, HCC is hierarchically characterized by the formation of primitive cancer stem cells (CSCs), progression of epithelial-mesenchymal transition (EMT), unbalanced autophagy, delivery of extracellular vesicles (EVs), escape of immune surveillance, disruption of ferroptosis, alteration of the tumor microenvironment and multidrug resistance-related signaling pathways that mediate the multiplicity and complexity of chemoresistance. Of note, anecdotal evidence has corroborated that noncoding RNAs (ncRNAs) extensively participate in the critical physiological processes mentioned above. Therefore, understanding the detailed regulatory bases that underlie ncRNA-mediated chemoresistance is expected to yield novel insights into HCC treatment. In the present review, a comprehensive summary of the latest progress in the investigation of chemotherapy resistance concerning ncRNAs will be elucidated to promote tailored individual treatment for HCC patients.

Comprehensive Analyses of Stromal-Immune Score-Related Competing Endogenous RNA Networks In Colon Adenocarcinoma

Although recent clinical investigations emphasize the roles of myriad diversities of RNAs in stromal and immune components in the tumor microenvironment, especially in colon adenocarcinoma, however, analyses of “competing endogenous RNAs (ceRNA)” network in association with stromal and immune scores have yet to be determined. This study was conducted to explore the regulatory mechanisms of a stromal-immune score-based ceRNA network in colon adenocarcinoma. Stromal and immune scores of colon adenocarcinoma tumor samples were calculated by using the ESTIMATE algorithm. Differential expression analysis between samples with high/low stromal and immune scores was performed, followed by functional annotation for the overlapping DEmRNAs. The ceRNA network was constructed by differential expression analysis, prediction of RNA-RNA interaction, and correlation with clinicopathological parameters of the patients, which were further verified by external datasets and experiments. Colon adenocarcinoma patients having higher immune scores exhibited prolonged overall survival. RNA dataset analyses from TCGA revealed aberrant expressions of a total of 2052 mRNAs, 108 lncRNAs, and 70 miRNAs between high and low stromal/immune groups. Functional annotation mapped the differentially overexpressed mRNAs for immune-associated GO terms. To construct the ceRNA network, a total of 48 lncRNAs, 40 miRNAs, and 199 mRNAs were sorted out. A dysregulated ceRNA network consisting of 6 lncRNAs, 11 miRNAs, and 39 mRNAs was constructed by comparing RNA expressions between cancer as well as adjacent normal tissues. The ceRNA regulatory axis “MIAT/miR-532-3p/STC1” was regarded as a potential hit by the comprehensive analysis. The RT-qPCR assay showed upregulation of MIAT and STC1 while downregulation of hsa-miR-532-3p expression in cancer. Thus, our study highlights the potential role of a stromal-immune score-based ceRNA network in the colon adenocarcinoma microenvironment. The ceRNA axis MIAT/miR-532-3p/STC1 could serve as a promising therapeutic target for colon adenocarcinoma.

Identification of A Risk Signature Based on Lactic Acid Metabolism-Related LncRNAs in Patients With Esophageal Squamous Cell Carcinoma

Lactic acid, formerly thought of as a byproduct of glycolysis or a metabolic waste produced, has now been identified as a key regulator of cancer growth, maintenance, and progression. However, the results of investigations on lactic acid metabolism-related long non-coding RNAs (LRLs) in esophageal squamous cell carcinoma (ESCC) remain inconclusive. In this study, univariate Cox regression analysis was carried out in the TCGA cohort, and 9 lncRNAs were shown to be significantly associated with prognosis. Least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox regression analysis were then used in the GEO cohort. 6 LRLs were identified as independent prognostic factors for ESCC patients used to construct a prognostic risk-related signature subsequently. Two groups were formed based on the middle value of risk scores: a low-risk group and a high-risk group. Following that, we conducted Kaplan-Meier survival analysis, which revealed that the high-risk group had a lower survival probability than the low-risk group in both GEO and TCGA cohorts. On multivariate Cox regression analysis, the prognostic signature was shown to be independent prognostic factor, and it was found to be a better predictor of the prognosis of ESCC patients than the currently widely used grading and staging approaches. The established nomogram can be conveniently applied in the clinic to predict the 1-, 3-, and 5- year survival rates of patients. There was a significant link found between the 6 LRLs-based prognostic signature and immune-cell infiltration, tumor microenvironment (TME), tumor somatic mutational status, and chemotherapeutic treatment sensitivity in the study population. Finally, we used GTEx RNA-seq data and qRT-PCR experiments to verify the expression levels of 6 LRLs. In conclusion, we constructed a prognostic signature which could predict the prognosis and immunotherapy response of ESCC patients.

A Glycolysis-Related Gene Signature Correlates With the Characteristics of the Tumor Immune Microenvironment and Predicts Prognosis in Patients With Hepatocellular Carcinoma

Aim: To develop a glycolysis-related gene signature that correlated with the characteristics of the tumor immune microenvironment and had good predictive power for overall survival (OS) in hepatocellular carcinoma (HCC).

Methods: Gene expression profiles, RNA sequencing data, clinical characteristics and survival information for 407 patients with HCC and 58 healthy controls were downloaded from the TCGA database. GSEA 4.1.0 software was used to evaluate the glycolysis-related pathways enriched in HCC compared to normal liver tissue. Univariate Cox, Least Absolute Shrinkage, Selection Operator, and two-step multivariate Cox analyses were used to construct a glycolysis-related gene signature for prognostic prediction. The glycolysis-related gene signature was combined with clinical characteristics to generate a nomogram. Tumor-infiltrating immune cell profiles and PD-L1 protein expression in HCC tissues were investigated.

Results: The gene expression profiles of HCC tissues were enriched in glycolysis-related pathways. A glycolysis-related gene signature was used to categorize patients as high-risk or low-risk, where high-risk patients had significantly worse OS. Receiver operating characteristic curves confirmed the predictive capability of the glycolysis-related gene signature for OS (AUC >0.80). There was a significant difference in M0 macrophage (p = 0.017), dendritic cell (p = 0.043), B cell (p = 0.0018), CD4 T cell (p = 0.003), Treg (p = 0.01) and mast cell (p = 0.02) content and PD-L1 protein expression (p = 0.019) between HCC tissues in patients in the high-risk and low-risk groups.

Conclusion: We established a glycolysis-related gene signature for OS in HCC that was predictive in training and test TCGA cohorts and correlated with the characteristics of the HCC tumor immune microenvironment. The glycolysis-related gene signature may guide clinical decision-making concerning patient selection for immunotherapy in HCC.

A Novel Pyroptotic and Inflammatory Gene Signature Predicts the Prognosis of Cutaneous Melanoma and the Effect of Anticancer Therapies

Purpose

The purpose of this study was to construct a gene signature comprising genes related to both inflammation and pyroptosis (GRIPs) to predict the prognosis of patients with cutaneous melanoma patients and the efficacy of immunotherapy, chemotherapy, and targeted therapy in these patients.

Methods

Gene expression profiles were collected from The Cancer Genome Atlas. Weighted gene co-expression network analysis was performed to identify GRIPs. Univariable Cox regression and Lasso regression further selected key prognostic genes. Multivariable Cox regression was used to construct a risk score, which stratified patients into high- and low-risk groups. Areas under the ROC curves (AUCs) were calculated, and Kaplan-Meier analyses were performed for the two groups, following validation in an external cohort from Gene Expression Omnibus (GEO). A nomogram including the GRIP signature and clinicopathological characteristics was developed for clinical use. Gene set enrichment analysis illustrated differentially enriched pathways. Differences in the tumor microenvironment (TME) between the two groups were assessed. The efficacies of immune checkpoint inhibitors (ICIs), chemotherapeutic agents, and targeted agents were predicted for both groups. Immunohistochemical analyses of the GRIPs between the normal and CM tissues were performed using the Human Protein Atlas data. The qRT-PCR experiments validated the expression of genes in CM cell lines, Hacat, and PIG1 cell lines.

Results

A total of 185 GRIPs were identified. A novel gene signature comprising eight GRIPs (TLR1, CCL8, EMP3, IFNGR2, CCL25, IL15, RTP4, and NLRP6) was constructed. The signature had AUCs of 0.714 and 0.659 for predicting 3-year overall survival (OS) in the TCGA entire and GEO validation cohorts, respectively. Kaplan-Meier analyses revealed that the high-risk group had a poorer prognosis. Multivariable Cox regression showed that the GRIP signature was an independent predictor of OS with higher accuracy than traditional clinicopathological features. The nomogram showed good accuracy and reliability in predicting 3-year OS (AUC = 0.810). GSEA and TME analyses showed that the high-risk group had lower levels of pyroptosis, inflammation, and immune response, such as lower levels of CD8+ T-cell infiltration, CD4+ memory-activated T-cell infiltration, and ICI. In addition, low-risk patients whose disease expressed PD-1 or CTLA-4 were likely to respond better to ICIs, and several chemotherapeutic and targeted agents. Immunohistochemical analysis confirmed the distinct expression of five out of the eight GRIPs between normal and CM tissues.

Conclusion

Our novel 8-GRIP signature can accurately predict the prognosis of patients with CM and the efficacies of multiple anticancer therapies. These GRIPs might be potential prognostic biomarkers and therapeutic targets for CM.

Research Progress on the Inflammatory Effects of Long Non-coding RNA in Traumatic Brain Injury

Globally, traumatic brain injury (TBI) is an acute clinical event and an important cause of death and long-term disability. However, the underlying mechanism of the pathophysiological has not been fully elucidated and the lack of effective treatment a huge burden to individuals, families, and society. Several studies have shown that long non-coding RNAs (lncRNAs) might play a crucial role in TBI; they are abundant in the central nervous system (CNS) and participate in a variety of pathophysiological processes, including oxidative stress, inflammation, apoptosis, blood-brain barrier protection, angiogenesis, and neurogenesis. Some lncRNAs modulate multiple therapeutic targets after TBI, including inflammation, thus, these lncRNAs have tremendous therapeutic potential for TBI, as they are promising biomarkers for TBI diagnosis, treatment, and prognosis prediction. This review discusses the differential expression of different lncRNAs in brain tissue during TBI, which is likely related to the physiological and pathological processes involved in TBI. These findings may provide new targets for further scientific research on the molecular mechanisms of TBI and potential therapeutic interventions.

Identification of Epithelial Mesenchymal Transition-Related lncRNAs Associated with Prognosis and Tumor Immune Microenvironment of Hepatocellular Carcinoma

Purpose. The long noncoding RNAs (lncRNAs) play the important role in tumor occurrence and progression, and the epithelial to mesenchymal transition (EMT) is the critical process for tumor migration. However, the role of EMT-related lncRNA in hepatocellular carcinoma (HCC) has not been elucidated. Methods. In this study, we selected the EMT-related lncRNAs in HCC by using data from The Cancer Genome Atlas database (TCGA). Two prognostic models of the overall survival (OS) and relapse-free survival (RFS) were constructed and validated through Cox regression model, Kaplan-Meier analysis, and the receiver-operating characteristic (ROC) curves. The unsupervised clustering analysis was utilized to investigate the association between EMT-lncRNAs with tumor immune microenvironment. ESTIMATE algorithm and gene set enrichment analysis (GSEA) were used to estimate tumor microenvironment and associated KEGG pathways. Results. Two EMT-related lncRNA prognostic models of OS and RFS were constructed. Kaplan-Meier curves showed the dismal prognosis of OS and RFS in the group with high-risk score. The ROC curves and AUC values in two prognostic models indicated the discriminative value in the training set and validation set. Patients with HCC were clustered into two subgroups according the unsupervised clustering analysis. Lnc-CCNY-1 was selected as the key lncRNA. GSVA analysis showed that lnc-CCNY-1 was negatively associated with peroxisome proliferator-activated receptor (PPAR) signaling pathway and positively correlated with CELL cycle pathway. Conclusion. Two EMT-related lncRNA prognostic models of OS and RFS were constructed to discriminate patients and predict prognosis of HCC. EMT-related lncRNAs may play a role on prognosis of HCC by influencing the immune microenvironment. Lnc-CCNY-1 was selected as the key EMT-related lncRNA for further exploration.

Computational Identification of Immune- and Ferroptosis-Related LncRNA Signature for Prognosis of Hepatocellular Carcinoma

Long non-coding RNAs (lncRNAs), which were implicated in many pathophysiological processes including cancer, were frequently dysregulated in hepatocellular carcinoma (HCC). Studies have demonstrated that ferroptosis and immunity can regulate the biological behaviors of tumors. Therefore, biomarkers that combined ferroptosis, immunity, and lncRNA can be a promising candidate bioindicator in clinical therapy of cancers. Many bioinformatics methods, including Pearson correlation analysis, univariate Cox proportional hazard regression analysis, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox proportional hazard regression analysis were applied to develop a prognostic risk signature of immune- and ferroptosis-related lncRNA (IFLSig). Finally, eight immune- and ferroptosis-related lncRNAs (IFLncRNA) were identified to develop and IFLSig of HCC patients. We found the prognosis of patients with high IFLSig will be worse, while the prognosis of patients with low IFLSig will be better. The results provide an efficient method of uniting critical clinical information with immunological characteristics, enabling estimation of the overall survival (OS). Such an integrative prognostic model with high predictive power would have a notable impact and utility in prognosis prediction and individualized treatment strategies.

LncRNA PTPRG-AS1 Promotes the Metastasis of Hepatocellular Carcinoma by Enhancing YWHAG

Objectives

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. LncRNA PTPRG-AS1 (PTPRG-AS1) has been confirmed to function as a regulator in various cancers, whose function during HCC tumorigenesis is still not clear now. Thus, we aim to dig out the biological function and its mechanisms of PTPRG-AS1 in HCC.

Methods

PTPRG-AS1 relative expression in tissues and cells was detected and analyzed using real-time quantitative PCR (qRT-PCR). Subcellular distribution of PTPRG-AS1 was examined by FISH experiments. The effects of PTPRG-AS1 in the growth of HCC were studied by in vitro CCK-8 experiments, transwell invasion experiments, and in vivo xenograft tumor experiments. Dual-Luciferase reporter assay was performed to verify the interaction between PTPRG-AS1 and miR-199a-3p or miR-199a-3p and its target gene, YWHAG.

Results

PTPRG-AS1 was upregulated in HCC tissues compared with adjacent normal tissues. We identified PTPRG-AS1 mainly localized in the cytoplasm of HCC cells. Downregulation of PTPRG-AS1 suppressed HCC progression, while overexpression of PTPRG-AS1 showed the opposite effects. Furthermore, PTPRG-AS1 served as a miR-199a-3p sponge and positively regulated YWHAG expression. Besides, PTPRG-AS1 could promote HCC through miR-199a-3p/YWHAG axis.

Conclusions

Taken together, we demonstrated PTPRG-AS1 may serve as a ceRNA and reversely regulates the expression of miR-199a-3p, thus facilitating HCC tumorigenesis and metastasis, which is expected to provide new clues for the treatment of HCC.

Expression, prognosis value, and immune infiltration of lncRNA ASB16-AS1 identified by pan-cancer analysis

Long non-coding RNA known as ASB16 antisense RNA1 (ASB16-AS1) has been proven to be an oncogene, and the relationship between ASB16-AS1 and immunity is still under studied. This study aims to explore the expression and prognostic potential of ASB16-AS1, and to visualize the relationship between ASB16-AS1 expression and immune infiltration in pan-cancer analysis. We clarified ASB16-AS1 expression patterns and its relationship with prognosis through multi-platform and multi-database sources. We also verified the function of ASB16-AS1 in liver hepatocellular carcinoma (LIHC). A  variety of immune cell content evaluation methods were used to mutually verify the correlation between ASB16-AS1 and immune infiltration. Finally, the relationships between ASB16-AS1 and molecular characteristics were further explored. In terms of comprehensive analysis, compared with non-tumor tissues, ASB16-AS1 was highly expressed in tumor tissues, and indicated the value of poor prognosis in multiple cancer types. Functional assays, such as counting kit-8 assay, transwell assay and scratch-wound assay verified that high ASB16-AS1 expression promoted tumor progression in LIHC. ASB16-AS1 was positively correlated with B cells, T cells CD4+ and T cells CD8+ in most cancer types, and negatively correlated with macrophages, dendritic cells and neutrophils in some cancer types. In addition, there were different interaction modes between ASB16-AS1 and molecular features, such as the relationship with oncogenic signaling pathways, showing that the high ASB16-AS1 expression was related to alterations in oncogenic signaling pathways. Our study emphasizes that ASB16-AS1 is a potential pan-cancer prognostic marker, whichs is associated with the immune infiltration in multiple cancer types.

The role of lncRNAs and circRNAs in the PD-1/PD-L1 pathway in cancer immunotherapy

Cancer immunotherapy has recently shown promising antitumor effects in various types of tumors. Among all immune checkpoints, the PD-1/PD-L1 pathway plays an important role in the immune evasion of tumor cells, making it a potent target in antitumor immunity. Accordingly, antibodies targeting the PD-1/PD-L1 pathway have been developed to attack tumor cells; however, resistance to immune therapy remains to be solved. Hence, identification of the underlying modulators of the PD-1/PD-L1 pathway is of significant importance to understand the mechanisms of antitumor immunotherapy. Long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) have been identified to regulate the PD-1/PD-L1 pathway, leading to participation in the immune response and immunotherapy. Therefore, this review focuses on the functions of lncRNAs and circRNAs in regulation of the PD-1/PD-L1 axis in tumorigenesis and tumor progression. We hope this review will stimulate research to supply more precise and effective cancer immune checkpoint therapies for a large number of tumors.

Long Non-coding RNAs: Mechanisms, Experimental, and Computational Approaches in Identification, Characterization, and Their Biomarker Potential in Cancer

Long non-coding RNAs are diverse class of non-coding RNA molecules >200 base pairs of length having various functions like gene regulation, dosage compensation, epigenetic regulation. Dysregulation and genomic variations of several lncRNAs have been implicated in several diseases. Their tissue and developmental specific expression are contributing factors for them to be viable indicators of physiological states of the cells. Here we present an comprehensive review the molecular mechanisms and functions, state of the art experimental and computational pipelines and challenges involved in the identification and functional annotation of lncRNAs and their prospects as biomarkers. We also illustrate the application of co-expression networks on the TCGA-LIHC dataset for putative functional predictions of lncRNAs having a therapeutic potential in Hepatocellular carcinoma (HCC).

A novel immune-related long non-coding RNA signature improves the prognosis prediction in the context of head and neck squamous cell carcinoma

The tumor immune microenvironment plays an important role in head and neck squamous cell carcinoma (HNSCC). Reliable prognostic signatures able to accurately predict the immune landscape and survival rate of HNSCC patients are crucial to ensure an individualized/effective treatment. Here, we used HNSCC transcriptomic and clinical data retrieved from The Cancer Genome Atlas and identified differentially expressed immune-related long non-coding RNAs (DEirlncRNAs). DEirlncRNA pairs were recognized using univariate analysis. Cox and Lasso regression analyses were used to determine the association between DEirlncRNA pairs and the patients’ overall survival and build the prediction model. Receiver operating characteristic curves and Kaplan–Meier survival curves were used to validate the prediction model. We then reevaluated the model based on the clinical factors, tumor-infiltrating immune cells, chemotherapeutic efficacy, and immunosuppression biomarkers. We built a risk score model based on 18 DEirlncRNA pairs, closely related to the overall survival of patients (hazard ratio: 1.376; 95% confidence interval: 1.302–1.453; P < 0.0001). Compared with two recently published lncRNA signatures, our DEirlncRNA pair signature had a higher area under the curve, indicating better prognostic performance. Additionally, the signature score positively correlated with aggressive HNSCC outcomes (low immunity score, significantly reduced CD8 + T cell infiltration, and low expression of immunosuppression biomarkers). However, high-risk patients might have high chemosensitivity. Overall, the lncRNAs signature established here shows promising clinical prediction and the effective disclosure of the tumor immune microenvironment in HNSCC patients; therefore, such signature might help distinguish patients that could benefit from immunotherapy.

Applications of single-cell sequencing in cancer research: progress and perspectives

Single-cell sequencing, including genomics, transcriptomics, epigenomics, proteomics and metabolomics sequencing, is a powerful tool to decipher the cellular and molecular landscape at a single-cell resolution, unlike bulk sequencing, which provides averaged data. The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions. In this review, we summarize emerging single-cell sequencing technologies and recent cancer research progress obtained by single-cell sequencing, including information related to the landscapes of malignant cells and immune cells, tumor heterogeneity, circulating tumor cells and the underlying mechanisms of tumor biological behaviors. Overall, the prospects of single-cell sequencing in facilitating diagnosis, targeted therapy and prognostic prediction among a spectrum of tumors are bright. In the near future, advances in single-cell sequencing will undoubtedly improve our understanding of the biological characteristics of tumors and highlight potential precise therapeutic targets for patients.

Identification of Prognostic Glycolysis-Related lncRNA Signature in Tumor Immune Microenvironment of Hepatocellular Carcinoma

Purpose: The purpose of this study was to construct a novel risk scoring model with prognostic value that could elucidate tumor immune microenvironment of hepatocellular carcinoma (HCC).

Samples and methods: Data were obtained through The Cancer Genome Atlas (TCGA) database. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox analysis were carried out to screen for glycolysis-related long noncoding RNAs (lncRNAs) that could provide prognostic value. Finally, we established a risk score model to describe the characteristics of the model and verify its prediction accuracy. The receiver operating characteristic (ROC) curves of 1, 3, and 5 years of overall survival (OS) were depicted with risk score and some clinical features. ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and CIBERSORT analysis were employed to reveal the characteristics of tumor immune microenvironment in HCC. The nomogram was drawn by screening indicators with high prognostic accuracy. The correlation of risk signature with immune infiltration and immune checkpoint blockade (ICB) therapy was analyzed. After enrichment of related genes, active behaviors and pathways in high-risk groups were identified and lncRNAs related to poor prognosis were validated in vitro. Finally, the impact of MIR4435-2HG upon ICB treatment was uncovered.

Results: After screening through multiple steps, four glycolysis-related lncRNAs were obtained. The risk score constructed with the four lncRNAs was found to significantly correlate with prognosis of samples. From the ROC curve of samples with 1, 3, and 5 years of OS, two indicators were identified with high prognostic accuracy and were used to draw a nomogram. Besides, the risk score significantly correlated with immune score, immune-related signature, infiltrating immune cells (i.e. B cells, etc.), and ICB key molecules (i.e. CTLA4,etc.). Gene enrichment analysis indicated that multiple biological behaviors and pathways were active in the high-risk group. In vitro validation results showed that MIR4435-2HG was highly expressed in the two cell lines, which had a significant impact on the OS of samples. Finally, we corroborated that MIR4435-2HG had intimate relationship with ICB therapy in hepatocellular carcinoma.

Conclusion: We elucidated the crucial role of risk signature in immune cell infiltration and immunotherapy, which might contribute to clinical strategies and clinical outcome prediction of HCC.

Suppression of Th17 cell differentiation via sphingosine-1-phosphate receptor 2 by cinnamaldehyde can ameliorate ulcerative colitis

Ulcerative colitis (UC) is chronic disease characterized by diffuse inflammation of the mucosa of the colon and rectum. Although the etiology is unknown, dysregulation of the intestinal mucosal immune system is closely related to UC. Cinnamaldehyde (CA) is a major active compound from cinnamon, is known as its anti-inflammatory and antibacterial. However, little research focused on its regulatory function on immune cells in UC. Therefore, we set out to explore the modulating effects of CA on immune cells in UC. We found that CA reduced the progression of colitis through controlling the production of proinflammatory cytokines and inhibiting the proportion of Th17 cells. Furthermore, the liquid chromatography-mass spectrometry (LC-MS) method was employed for analyzing and differentiating metabolites, data showed that sphingolipid pathway has a great influence on the effect of CA on UC. Meanwhile, sphingosine-1-phosphate receptor 2 (S1P2) and Rho-GTP protein levels were downregulated in colonic tissues after CA treatment. Moreover, in vitro assays showed that CA inhibited Th17 cell differentiation and downregulated of S1P2 and Rho-GTP signaling. Notably, we found that treatment with S1P2 antagonist (JTE-013) weakened the inhibitory effect of CA on Th17 cells. Furthermore, S1P2 deficiency (S1P2-/-) blocked the effect of CA on Th17 cell differentiation. In addition, CA can also improve inflammation via lncRNA H19 and MIAT. To sum up, this study provides clear evidence that CA can ameliorate ulcerative colitis through suppressing Th17 cells via S1P2 pathway and regulating lncRNA H19 and MIAT, which further supports S1P2 as a potential drug target for immunity-mediated UC.