HCG18/miR-34a-5p/HMMR axis accelerates the progression of lung adenocarcinoma

AGTR1: a potential biomarker associated with the occurrence and prognosis of lung adenocarcinoma

Introduction

Lung adenocarcinoma, a disease with complex pathogenesis, high mortality and poor prognosis, is one of the subtypes of lung cancer. Hence, it is very crucial to find novel biomarkers as diagnostic and therapeutic targets for LUAD.

Methods

GSE10072 was used for DEGs and WGCNA, and the intersection genes were subjected to enrichment analysis through Metascape and GSEA. Key genes were screened by three machine learning methods. Further, the reliability of key genes was identified by ROC, COX regression analysis and qRT-PCR. CIBERSORT and Spearman analysis were used for understanding the relationships of LUAD, immunity and key genes. In addition, ceRNA networks and potential drugs of key genes were constructed and predicted.

Results

After overlapping 631 DEGs and key module genes, 623 intersection genes were obtained. Subsequently, DUOX1, CD36, AGTR1, FHL5 and SSR4 were further selected using three machine learning methods. Reliability analysis demonstrated that AGTR1 possesses important predictive value for the occurrence and prognosis of LUAD. The enrichment analysis showed that AGTR1 was significantly enriched in the GPCR-related pathways. Immune infiltration analysis showed that the development of LUAD was related to the changes of immune cells such as M2 macrophages and neutrophils, which were regulated by AGTR1. Further, AGTR1 is also involved in regulating immune chemokines, checkpoints and immune regulatory factors such as PECAM1, ADARB1, SPP1 and ENO1, all of them playing important roles in immune cell regulation, tumor cell proliferation and migration. Further, the drug-gene interaction network screened out 13 potential drugs such as Benazepril, Valsartan, Eprosartan, and so on.

Discussion

AGTR1 is a potential biomarker for the occurrence and progression of LUAD, closely related to tumor immunity, proliferation and migration. It can serve as a new target for the diagnosis and treatment of LUAD.

The microRNA-34 Family and Its Functional Role in Lung Cancer

Lung cancer is one of the most common malignant tumors in humans and the leading cause of cancer-related deaths worldwide. The microRNA-34 (miR-34) family is dysregulated in various human cancers and is an important family of tumor suppressor genes among microRNAs. The miR-34 family is downregulated in lung cancer. It inhibits cell proliferation, metastasis, and invasion, arrests the cell cycle, and induces apoptosis or senescence by negatively regulating many oncogenes. It is commonly used to detect and treat lung cancer. This study describes the regulatory role of the miR-34 family in lung cancer and the associated research advances in treatment.

LncRNA HCG18 affects aortic dissection through the miR-103a-3p/HMGA2 axis by modulating proliferation and apoptosis of vascular smoothing muscle cells

BACKGROUND

Aortic Dissection (AD) is a vascular disease with a high mortality rate and limited treatment strategies. The current research analyzed the function and regulatory mechanism of lncRNA HCG18 in AD.

METHODS

HCG18, miR-103a-3p, and HMGA2 levels in the aortic tissue of AD patients were examined by RT-qPCR. After transfection with relevant plasmids, the proliferation of rat aortic Vascular Smoothing Muscle Cells (VSMCs) was detected by CCK-8 and colony formation assay, Bcl-2 and Bax was measured by Western blot, and apoptosis was checked by flow cytometry. Then, the targeting relationship between miR-103a-3p and HCG18 or HMGA2 was verified by bioinformation website analysis and dual luciferase reporter assay. Finally, the effect of HCG18 was verified in an AD rat model induced by β-aminopropionitrile.

RESULTS

HCG18 and HMGA2 were upregulated and miR-103a-3p was downregulated in the aortic tissues of AD patients. Downregulating HCG18 or upregulating miR-103a-3p enhanced the proliferation of VSMCs and limited cell apoptosis. HCG18 promoted HMGA2 expression by competing with miR-103a-3p and restoring HMGA2 could impair the effect of HCG18 downregulation or miR-103a-3p upregulation in mediating the proliferation and apoptosis of VSMCs. In addition, down-regulation of HCG18 could improve the pathological injury of the aorta in AD rats.

CONCLUSION

HCG18 reduces proliferation and induces apoptosis of VSMCs through the miR-103a-3p/HMGA2 axis, thus aggravating AD.

HMMR triggers immune evasion of hepatocellular carcinoma by inactivation of phagocyte killing

Hepatocellular carcinoma (HCC) acquires an immunosuppressive microenvironment, leading to unbeneficial therapeutic outcomes. Hyaluronan-mediated motility receptor (HMMR) plays a crucial role in tumor progression. Here, we found that aberrant expression of HMMR could be a predictive biomarker for the immune suppressive microenvironment of HCC, but the mechanism remains unclear. We established an HMMR-/- liver cancer mouse model to elucidate the HMMR-mediated mechanism of the dysregulated "don't eat me" signal. HMMR knockout inhibited liver cancer growth and induced phagocytosis. HMMRhigh liver cancer cells escaped from phagocytosis via sustaining CD47 signaling. Patients with HMMRhighCD47high expression showed a worse prognosis than those with HMMRlowCD47low expression. HMMR formed a complex with FAK/SRC in the cytoplasm to activate NF-κB signaling, which could be independent of membrane interaction with CD44. Notably, targeting HMMR could enhance anti-PD-1 treatment efficiency by recruiting CD8+ T cells. Overall, our data revealed a regulatory mechanism of the "don't eat me" signal and knockdown of HMMR for enhancing anti-PD-1 treatment.

Differential expression and clinical significance of long non-coding RNAs in the development and progression of lung adenocarcinoma

With the development of gene testing technology, we have found many different genes, and lncRNA is one of them. LncRNAs refer to a non-protein coding RNA molecule with a length of more than 200bp, which is one of the focuses of research on human malignant diseases such as LUAD. LncRNAs act as an oncogene or inhibitor to regulate the occurrence and progression of tumors. The differential expression of LncRNAs promotes or inhibits the progression of lung adenocarcinoma by affecting cell proliferation, metastasis, invasion, and apoptosis, thus affecting the prognosis and survival rate of patients. Therefore, LncRNAs can be used as a potential target for diagnosis and treatment of cancer. The early diagnosis of the disease was made through the detection of tumor markers. Because lung adenocarcinoma is not easy to diagnose in the early stage and tumor markers are easy to ignore, LncRNAs play an important role in the diagnosis and treatment of lung adenocarcinoma. The main purpose of this article is to summarize the known effects of LncRNAs on lung adenocarcinoma, the effect of differential expression of LncRNAs on the progression of lung adenocarcinoma, and related signal transduction pathways. And to provide a new idea for the future research of lung adenocarcinoma-related LncRNAs.

PM2.5 regulates the progression of lung adenocarcinoma through the axis of HCG18, miR-195 and ATG14

Relevant studies have indicated the association of HCG18 with tumour occurrence and progression. In this study, we observed that PM2.5 can enhance the growth of lung adenocarcinoma cells by modulating the expression of HCG18. Further investigations, including overexpression and knockout experiments, elucidated that HCG18 suppresses miR-195, which in turn upregulates the expression of ATG14, resulting in the upregulation of autophagy. Consequently, exposure to PM2.5 leads to elevated HCG18 expression in lung tissues, which in turn increases Atg14 expression and activates autophagy pathways through inhibition of miR-195, thereby contributing to oncogenesis.

Long non‑coding RNA lung cancer‑associated transcript 1 regulates ferroptosis via microRNA‑34a‑5p‑mediated GTP cyclohydrolase 1 downregulation in lung cancer cells

Ferroptosis, a recently discovered type of programmed cell death triggered by excessive accumulation of iron‑dependent lipid peroxidation, is linked to several malignancies, including non‑small cell lung cancer. Long non‑coding RNAs (lncRNAs) are involved in ferroptosis; however, data on their role and mechanism in cancer therapy remains limited. Therefore, the aim of the present study was to identify ferroptosis‑associated mRNAs and lncRNAs in A549 lung cancer cells treated with RAS‑selective lethal 3 (RSL3) and ferrostatin‑1 (Fer‑1) using RNA sequencing. The results demonstrated that lncRNA lung cancer‑associated transcript 1 (LUCAT1) was significantly upregulated in lung adenocarcinoma and lung squamous cell carcinoma tissues. Co‑expression analysis of differentially expressed mRNAs and lncRNAs suggested that LUCAT1 has a crucial role in ferroptosis. LUCAT1 expression was markedly elevated in A549 cells treated with RSL3, which was prevented by co‑incubation with Fer‑1. Functionally, overexpression of LUCAT1 facilitated cell proliferation and reduced the occurrence of ferroptosis induced by RSL3 and Erastin, while inhibition of LUCAT1 expression reduced cell proliferation and increased ferroptosis. Mechanistically, downregulation of LUCAT1 resulted in the downregulation of both GTP cyclohydrolase 1 (GCH1) and ferroptosis suppressor protein 1 (FSP1). Furthermore, inhibition of LUCAT1 expression upregulated microRNA (miR)‑34a‑5p and then downregulated GCH1. These results indicated that inhibition of LUCAT1 expression promoted ferroptosis by modulating the downregulation of GCH1, mediated by miR‑34a‑5p. Therefore, the combination of knocking down LUCAT1 expression with ferroptosis inducers may be a promising strategy for lung cancer treatment.

Exploring HMMR as a therapeutic frontier in breast cancer treatment, its interaction with various cell cycle genes, and targeting its overexpression through specific inhibitors

Among women, breast carcinoma is one of the most complex cancers, with one of the highest death rates worldwide. There have been significant improvements in treatment methods, but its early detection still remains an issue to be resolved. This study explores the multifaceted function of hyaluronan-mediated motility receptor (HMMR) in breast cancer progression. HMMR's association with key cell cycle regulators (AURKA, TPX2, and CDK1) underscores its pivotal role in cancer initiation and advancement. HMMR's involvement in microtubule assembly and cellular interactions, both extracellularly and intracellularly, provides critical insights into its contribution to cancer cell processes. Elevated HMMR expression triggered by inflammatory signals correlates with unfavorable prognosis in breast cancer and various other malignancies. Therefore, recognizing HMMR as a promising therapeutic target, the study validates the overexpression of HMMR in breast cancer and various pan cancers and its correlation with certain proteins such as AURKA, TPX2, and CDK1 through online databases. Furthermore, the pathways associated with HMMR were explored using pathway enrichment analysis, such as Gene Ontology, offering a foundation for the development of effective strategies in breast cancer treatment. The study further highlights compounds capable of inhibiting certain pathways, which, in turn, would inhibit the upregulation of HMMR in breast cancer. The results were further validated via MD simulations in addition to molecular docking to explore protein-protein/ligand interaction. Consequently, these findings imply that HMMR could play a pivotal role as a crucial oncogenic regulator, highlighting its potential as a promising target for the therapeutic intervention of breast carcinoma.

hsa-miR-34a-5p enhances temozolomide anti-tumoral effects on glioblastoma: in-silico and in-vitro study

Glioblastoma multiform (GBM) is a commonly diagnosed brain neoplasm with a poor prognosis. Accumulating evidence has highlighted the significance of microRNA (miR) dysregulation in tumor development and progression. This study investigated the effect of hsa-miR-34a-5p and its combination with temozolomide on GBM, the related molecular mechanisms, and the signaling pathway using in-silico and in-vitro approaches. The in-silico tumor bulk and single-cell RNA sequencing analyses were done on TCGA-GTEx, CGGA, GSE13276, GSE90603, and GSE182109 datasets. After selecting the A172 cell line, hsa-miR-34a-5p mimics were transfected, and the cell viability, migration, cell cycle, clonogenicity, and apoptosis of studied groups were studied using MTT, scratch, flow cytometry, colony formation, and Annexin V/PI assays. The mRNA expression of CASP9, CASP3, CASP8, MMP2, CD44, CDK6, CDK4, CCND1, RAF1, MAP2K1, MET, SRC, and CD274 was studied using qRT-PCR method. hsa-miR-34a-5p downregulated RAF1 expression, as the signaling factor of the MAPK pathway. The combined treatment significantly downregulated the expression of MET, SRC, and MAP2K1, leading to the inhibition of the MET/MAPK pathway compared to temozolomide. Besides exerting anti-tumoral effects on the cell viability, migration, cell cycle, apoptosis, and clonogenicity of A172 cells, its combination with temozolomide enhanced temozolomide anti-tumoral effect. Compared to temozolomide, the combined treatment significantly decreased CDK4, CDK6, CCND1, and MMP2 expression. hsa-miR-34a-5p targets RAF1, as the signaling factor of the MAPK pathway, and potentiates the temozolomide anti-tumoral effect on A172 cells.

The role of lncRNA HCG18 in human diseases

A substantial number of long noncoding RNAs (lncRNAs) have been identified as potent regulators of human disease. Human leukocyte antigen complex group 18 (HCG18) is a new type of lncRNA that has recently been proven to play an important role in the occurrence and development of various diseases. Studies have found that abnormal expression of HCG18 is closely related to the clinicopathological characteristics of many diseases. More importantly, HCG18 was also found to promote disease progression by affecting a series of cell biological processes. This article mainly discusses the expression characteristics, clinical characteristics, biological effects and related regulatory mechanisms of HCG18 in different human diseases, providing a scientific theoretical basis for its early clinical application.

LncRNA HCG18 affects diabetic cardiomyopathy and its association with miR-9-5p/IGF2R axis

This paper aimed to investigate the role of lncRNA HCG18 (HCG18) in the progression of diabetic cardiomyopathy (DCM) and potential mechanisms. Streptozocin (STZ) was used to induce DCM model in rats, which was confirmed by blood glucose concentration, body weight, and HE staining. Myocardial apoptosis was detected by TUNEL. H9c2 cardiomyocytes were used to construct cell models of DCM through treatment of high glucose. The results showed that HCG18 was overexpressed in STZ induced DCM rat model and high glucose induced H9c2 cardiomyocytes. Si-HCG18 significantly increased cell viability, reduced cell apoptosis, attenuated activities of myocardial enzymes and enhanced activities of antioxidant enzymes in STZ induced DM model and high glucose induced H9c2 cardiomyocytes, while the results of upregulation of HCG18, in high glucose induced H9c2 cardiomyocytes, were opposite with that of si-HCG18. MiR-9-5p was a target of HCG18, and which was down-regulated in cardiomyocytes of DCM. The overexpression of miR-9-5p could neutralize the high glucose induced cardiomyocyte injury, and the silence of miR-9-5p could reverse the effect of si-HCG18 on high glucose induced cardiomyocytes. MiR-9-5p could directly target to IGF2R, and IGF2R was overexpressed in cardiomyocytes of DCM. Up-regulation of IGF2R can reverse the protective effect of si-HCG18 on cardiomyocytes. Taken together, HCG18 is significantly increased in cardiomyocytes of DCM. Down-regulation of HCG18 can improve cardiomyocyte injury through miR-9-5p/IGF2R axis in DCM.

CDC6 may serve as an indicator of lung adenocarcinoma prognosis and progression based on TCGA and GEO data mining and experimental analyses

Lung adenocarcinoma (LUAD) is one of the most lethal types of cancer worldwide, and accurately predicting patient prognosis is an important challenge. Gene prediction models, which are known for their simplicity and efficiency, have the potential to be used for prognostic predictions. However, the availability of models with true clinical value is limited. The present study integrated tissue sequencing and the clinical information of patients with LUAD from The Cancer Genome Atlas and Gene Expression Omnibus databases using bioinformatics. This comprehensive approach enabled the identification of 252 differentially expressed genes. Subsequently, univariate and multivariate Cox analyses were performed using these genes, and 14 and 3 genes [including cell division cycle 6 (CDC6), hyaluronan mediated motility receptor and STIL centriolar assembly protein] were selected for the construction of two prognostic models. Notably, the 3‑gene prognostic model exhibited a comparable predictive ability to that of the 14‑gene model. Functionally, pathway enrichment analysis revealed that CDC6 played a role in regulating the cell cycle and promoting tumor staging. To further investigate the relevance of CDC6, in vitro experiments involving the downregulation of CDC6 expression were conducted, which resulted in significant inhibition of tumor cell migration, invasion and proliferation. Moreover, in vivo experiments demonstrated that downregulating CDC6 expression significantly reduced the burden and metastasis of in situ lung tumors in mice. These findings suggested that CDC6 may be a critical gene involved in the development and prognosis of LUAD. In summary, the present study successfully constructed a simple yet accurate prognostic prediction model consisting of 3 genes. Additionally, the functional importance of CDC6 as a key gene in the model was identified. These findings lay a crucial foundation for further exploration of prognostic prediction models and a deeper understanding of the functional mechanisms of CDC6. Notably, these results have potential clinical implications for improving personalized treatment and prognosis evaluation for patients with LUAD.

Identification and validation of a 4-extracellular matrix gene signature associated with prognosis and immune infiltration in lung adenocarcinoma

Background

The extracellular matrix (ECM) plays a crucial role in the development and tumor microenvironment of lung adenocarcinoma (LUAD). This study aimed to establish a risk score of ECM-related genes in LUAD and explore the association between the risk score and patient survival as well as immune cell infiltration, somatic mutations, and therapy response.

Methods

Gene expression data from The Cancer Genome Atlas (TGCA) and eight Gene Expression Omnibus (GEO) databases were used to analyze and identify differentially expressed genes (DEGs). Prognostic ECM-related genes were identified and utilized to formulate a prognostic signature. A nomogram was constructed using TCGA dataset and validated in two GEO datasets. Differences between high- and low-risk patients were analyzed for function enrichment, immune cell infiltration, somatic mutations, and therapy response. Finally, Quantitative real-time PCR (qRT-PCR) was used to detect the mRNA expression of DEGs in LUAD.

Results

A risk score based on four ECM-related genes, ANOS1, CD36, COL11A1, and HMMR, was identified as an independent prognostic factor for overall survival (OS) compared to other clinical variables. Subsequently, a nomogram incorporating the risk score and TNM staging was developed using the TCGA dataset. Internal and external validation of the nomogram, conducted through calibration plots, C-index, time-dependent receiver operating characteristics (ROC), integrated discrimination improvement (IDI), and decision curve analyses (DCA), demonstrated the excellent discriminatory ability and clinical practicability of this nomogram. The risk score correlated with the distribution of function enrichment, immune cell infiltration, and immune checkpoint expression. More somatic mutations occurred in the high-risk group. The risk score also demonstrated a favorable ability to predict immunotherapy response and drug sensitivity.

Conclusion

A novel signature based on four ECM-related genes is developed to help predict LUAD prognosis. This signature correlates with tumor immune microenvironment and can predict the response to different therapies in LUAD patients.

Molecular mechanisms of HCG18 in the sorafenib resistance of hepatocellular carcinoma

Sorafenib has been approved for advance hepatocellular carcinoma (HCC), however, drug resistance often occurred. Therefore, it is of great significance to clarify the underlying mechanisms of sorafenib resistance and to find out the effective strategies to overcome sorafenib resistance. The expression of HCG18 was detected by qPCR, MTT, colony formation, flow cytometry and TUNEL assay were used to explore the function of HCG18 on sorafenib resistance in HCC. RNA pull-down, RNA immunoprecipitation, immunofluorescence labeling, luciferase reporter assay, western blot and qPCR were used to investigate the mechanism of HCG18 regulating sorafenib resistance in HCC. Our results showed that HCG18 was significantly increased in HCC, which resulted in shorter 5-year survival for patients with HCC. Sorafenib can induce the expression of HCG18, suggesting HCG18 might be involved in sorafenib resistance in HCC. Further analysis showed that knockdown of HCG18 can reduce viability and increase apoptosis of HCC cells. Mechanistically, HCG18 can bind to USP15, further regulated the protein stability of p65, TAB2 and TAB3, and nuclear location of p65, which finally modulated the NF-κB signaling. Our findings showed that HCG18 played an important role in sorafenib resistance in HCC. And knockdown of HCG18 can promote the sensitivity of HCC cells to sorafenib, inferring that targeting HCG18 might be an effective strategy to overcome sorafenib resistance in HCC.

Identification of epithelial-mesenchymal transition-related biomarkers in lung adenocarcinoma using bioinformatics and lab experiments

BACKGROUND

Lung adenocarcinoma accounts for approximately 40% of lung cancer cases and poses a serious threat to human health. Therefore, there is an urgent need to identify central biomarkers in lung adenocarcinoma.

METHODS

We first identified the EMT-associated genes in LUAD based on the TCGA cohort. Then we screened these 90 EMT-associated genes using univariate Cox regression analysis and LASSO regression analysis to develop a prognostic gene signature in the training set. The predictive performance of the gene signature was assessed in the validation set and multiple external test sets using the ROC cure, C index and log-rank tests. RT-PCR, western blot, wound healing assays, and siRNA methods were further used to investigate the role of PLEK2 in tumor behaviors.

RESULTS

Eight genes (CCNB1, PLEK2, DERL3, C1QTNF6, DLGAP5, HMMR, GJB3, and SPOCK1) were eventually selected to develop an eight-gene signature. The 5-year AUC of the gene signature has a robust predictive ability both for predicting overall survival (0.774, 0.756, and 0.669 in the external test sets, respectively), and for progression free survival (0.774, 0.746, and 0.755 in the external test sets, respectively). C-index of the gene signature was 0.961 ± 0.005, 0.916 ± 0.011, and 0.868 ± 0.234 in the external test sets, respectively. Four genes (C1QTNF6, DLGAP5, HMMR, and PLEK2) were identified as key genes in LUAD progression, which were upregulated in the cancerous tissue compared with in the normal tissue (P < 0.001), and correlated with an unwanted prognosis in lung cancer (P < 0.05). PLEK2 was used as an example to explore its effect on LUAD progression in vitro using RT-PCR, western blot, CCK8, si-RNA and wound healing assay. Silencing of PLEK2 was shown to reduce proliferative and migrated ability of lung cancer cells via prohibition of autophagy.

CONCLUSIONS

This study developed a novel EMT-related gene signature benefiting precision medicine, and identified four pivotal genes which can serve as therapeutic targets in LUAD. Four key genes can serve as molecular targets for patients with LUAD; silencing of PLEK2 was shown to reduce proliferative and migrated ability of lung cancer cells via prohibition of autophagy.

Integrative Analysis Revealed LINC00847 as a Potential Target of Tumor Immunotherapy

Lung cancer is the second most commonly diagnosed cancer and the leading cause of cancer-related death. Lung adenocarcinoma (LUAD) is the most common form of lung cancer and has a low 5-year survival rate. Therefore, much more research is needed to identify cancer biomarkers, promote biomarker-driven therapy and improve treatment outcomes. LncRNAs have been reported to participate in various physiological and pathological processes, especially in cancer, and thus have attracted much attention. In this study, lncRNAs were screened from the single-cell RNA-seq dataset CancerSEA. Among them, four lncRNAs (HCG18, NNT-AS1 and LINC00847 and CYTOR) were closely associated with the prognosis of LUAD patients according to Kaplan-Meier analysis. Further study explored the correlations between these four lncRNAs and immune cell infiltration in cancer. In LUAD, LINC00847 was positively correlated with the immune infiltration of B cells, CD8 T cells, and dendritic cells. LINC00847 decreased the expression of PD-L1, immune checkpoint blockade (ICB) immunotherapy-related gene, which suggests that LINC00847 is a potential new target for tumor immunotherapy.

HMMR alleviates endoplasmic reticulum stress by promoting autophagolysosomal activity during endoplasmic reticulum stress-driven hepatocellular carcinoma progression

BACKGROUND

The mechanism of hepatitis B virus (HBV)-induced carcinogenesis remains an area of interest. The accumulation of hepatitis B surface antigen in the endoplasmic reticulum (ER) of hepatocytes stimulates persistent ER stress. Activity of the unfolded protein response (UPR) pathway of ER stress may play an important role in inflammatory cancer transformation. How the protective UPR pathway is hijacked by cells as a tool for malignant transformation in HBV-related hepatocellular carcinoma (HCC) is still unclear. Here, we aimed to define the key molecule hyaluronan-mediated motility receptor (HMMR) in this process and explore its role under ER stress in HCC development.

METHODS

An HBV-transgenic mouse model was used to characterize the pathological changes during the tumor progression. Proteomics and transcriptomics analyses were performed to identify the potential key molecule, screen the E3 ligase, and define the activation pathway. Quantitative real-time PCR and Western blotting were conducted to detect the expression of genes in tissues and cell lines. Luciferase reporter assay, chromatin immunoprecipitation, coimmunoprecipitation, immunoprecipitation, and immunofluorescence were employed to investigate the molecular mechanisms of HMMR under ER stress. Immunohistochemistry was used to clarify the expression patterns of HMMR and related molecules in human tissues.

RESULTS

We found sustained activation of ER stress in the HBV-transgenic mouse model of hepatitis-fibrosis-HCC. HMMR was transcribed by c/EBP homologous protein (CHOP) and degraded by tripartite motif containing 29 (TRIM29) after ubiquitination under ER stress, which caused the inconsistent expression of mRNA and protein. Dynamic expression of TRIM29 in the HCC progression regulated the dynamic expression of HMMR. HMMR could alleviate ER stress by increasing autophagic lysosome activity. The negative correlation between HMMR and ER stress, positive correlation between HMMR and autophagy, and negative correlation between ER stress and autophagy were verified in human tissues.

CONCLUSIONS

This study identified the complicated role of HMMR in autophagy and ER stress, that HMMR controls the intensity of ER stress by regulating autophagy in HCC progression, which could be a novel explanation for HBV-related carcinogenesis.

The effectiveness of blood-activating and stasis-transforming traditional Chinese medicines (BAST) in lung cancer progression-a comprehensive review

ETHNOPHARMACOLOGICAL RELEVANCE

Blood-activating and stasis-transforming traditional Chinese medicines (BAST) are a class of herbs that have the effect of dilating blood vessels and dispersing stagnation. Modern pharmaceutical research has demonstrated that they are capable of improving hemodynamics and micro-flow, resist thrombosis and promote blood flow. BAST contain numerous active ingredients, which can theoretically regulate multiple targets at the same time and have a wide range of pharmacological effects in the treatment of diseases including human cancers. Clinically, BAST have minimal side effects and can be used in combination with Western medicine to improve patients' quality of life, lessen adverse effects and minimize the risk of recurrence and metastasis of cancers.

AIM OF THE REVIEW

We aimed to summarize the research progression of BAST on lung cancer in the past five years and present a prospect for the future. Particularly, this review further analyzes the effects and molecular mechanisms that BAST inhibit the invasion and metastasis of lung cancer.

MATERIALS AND METHODS

Relevant studies about BSAT were collected from PubMed and Web of science.

RESULTS

Lung cancer is one of the malignant tumors with the highest mortality rate. Most patients with lung cancer are diagnosed at an advanced stage and are highly susceptible to metastasis. Recent studies have shown that BAST, a class of traditional Chinese medicine (TCM) with the function of opening veins and dispersing blood stasis, significantly improve hemodynamics and microcirculation, prevent thrombosis and promote blood flow, and thereby inhibiting the invasion and metastasis of lung cancer. In the current review, we analyzed 51 active ingredients extracted from BAST. It was found that BAST and their active ingredients contribute to the prevention of invasion and metastasis of lung cancer through multiple mechanisms, such as regulation of EMT process, specific signaling pathway and metastasis-related genes, tumor blood vessel formation, immune microenvironment and inflammatory response of tumors.

CONCLUSIONS

BSAT and its active ingredients have showed promising anticancer activity and significantly inhibit the invasion and metastasis of lung cancer. A growing number of studies have realized their potential clinical significance in the therapy of lung cancer, which will provide substantial evidences for the development of new TCM for lung cancer therapy.

Construction of an m6A-related lncRNA model for predicting prognosis and immunotherapy in patients with lung adenocarcinoma

N6-methyladenosine (m6A)-related lncRNAs could be involved in the development of multiple tumors with an unknown role in lung adenocarcinoma (LUAD). Hence, gene expression data and clinical data of LUAD patients were acquired from The Cancer Genome Atlas Database. The prognostic m6A-related lncRNAs were identified through differential lncRNA expression analysis and Spearman's correlation analysis. The least absolute shrinkage and selection operator regression was used to establish the prognostic risk model, so as to evaluate and validate the predictive performance with survival analysis and receiver operating characteristic curve analysis. The expression of immune checkpoints, immune cell infiltration and drug sensitivity of patients in different risk groups were analyzed separately. A total of 19 prognostic m6A-related lncRNAs were identified to set up the prognostic risk model. The patients were divided into high- and low-risk groups based on the median value of the risk scores. Compared with the patients in the low-risk group, the prognosis of the patients in the high-risk group was relatively worse. The receiver operating characteristic curves indicated that this model had excellent sensitivity and specificity. Multivariate Cox regression analysis demonstrated that the risk score could be supposed as an independent prognostic risk factor. We highlighted that the risk scores were correlated with immune cell infiltration and drug sensitivity for constructing a prognostic risk model in LUAD patients based on m6A-related lncRNAs.

Guidelines on lung adenocarcinoma prognosis based on immuno-glycolysis-related genes

OBJECTIVES

This study developed a new model for risk assessment of immuno-glycolysis-related genes for lung adenocarcinoma (LUAD) patients to predict prognosis and immunotherapy efficacy.

METHODS

LUAD samples and data obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases are used as training and test columns, respectively. Twenty-two (22) immuno-glycolysis-related genes were screened, the patients diagnosed with LUAD were divided into two molecular subtypes by consensus clustering of these genes. The initial prognosis model was developed using the multiple regression analysis method and Receiver Operating characteristic (ROC) analysis was used to verify its predictive potential. Gene set enrichment analysis (GSEA) showed the immune activities and pathways in different risk populations, we calculated immune checkpoints, immune escape, immune phenomena (IPS), and tumor mutation burden (TMB) based on TCGA datasets. Finally, the relationship between the model and drug sensitivity was analyzed.

RESULTS

Fifteen (15) key differentially expressed genes (DEGs) with prognostic value were screened and a new prognostic model was constructed. Four hundred and forty-three (443) samples were grouped into two different risk cohorts based on median model risk values. It was observed that survival rates in high-risk groups were significantly low. ROC curves were used to evaluate the model's accuracy in determining the survival time and clinical outcome of LUAD patients. Cox analysis of various clinical factors proved that the risk score has great potential as an independent prognostic factor. The results of immunological analysis can reveal the immune infiltration and the activity of related functions in different pathways in the two risk groups, and immunotherapy was more effective in low-risk patients. Most chemotherapeutic agents are more sensitive to low-risk patients, making them more likely to benefit.

CONCLUSION

A novel prognostic model for LUAD patients was established based on IGRG, which could more accurately predict the prognosis and an effective immunotherapy approach for patients.

Construction and validation of a prognostic model based on ten signature cell cycle-related genes for early-stage lung squamous cell carcinoma

BACKGROUND

We performed a bioinformatics analysis to screen for cell cycle-related differentially expressed genes (DEGs) and constructed a model for the prognostic prediction of patients with early-stage lung squamous cell carcinoma (LSCC).

METHODS

From a gene expression omnibus (GEO) database, the GSE157011 dataset was randomly divided into an internal training group and an internal testing group at a 1:1 ratio, and the GSE30219, GSE37745, GSE42127, and GSE73403 datasets were merged as the external validation group. We performed single-sample gene set enrichment analysis (ssGSEA), univariate Cox analysis, and difference analysis, and identified 372 cell cycle-related genes. Additionally, we combined LASSO/Cox regression analysis to construct a prognostic model. Then, patients were divided into high-risk and low-risk groups according to risk scores. The internal testing group, discovery set, and external verification set were used to assess model reliability. We used a nomogram to predict patient prognoses based on clinical features and risk values. Clinical relevance analysis and the Human Protein Atlas (HPA) database were used to verify signature gene expression.

RESULTS

Ten cell cycle-related DEGs (EIF2B1, FSD1L, FSTL3, ORC3, HMMR, SETD6, PRELP, PIGW, HSD17B6, and GNG7) were identified and a model based on the internal training group constructed. From this, patients in the low-risk group had a higher survival rate when compared with the high-risk group. Time-dependent receiver operating characteristic (tROC) and Cox regression analyses showed the model was efficient and accurate. Clinical relevance analysis and the HPA database showed that DEGs were significantly dysregulated in LSCC tissue.

CONCLUSION

Our model predicted the prognosis of early-stage LSCC patients and demonstrated potential applications for clinical decision-making and individualized therapy.

The regulatory role of LncRNA HCG18 in various cancers

As a member of long non-coding RNAs (lncRNAs), LncRNA HLA complex group 18 (HCG18) has recently become the focus of cancer research. As outlined in this review, LncRNA HCG18 has been reported to be dysregulated in various cancers development and appears to be activated in a variety of tumors, including clear cell renal cell carcinoma (ccRCC), colorectal cancer (CRC), gastric cancer (GC), hepatocellular carcinoma (HCC), laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC), lung adenocarcinoma (LUAD), nasopharyngeal cancer (NPC), osteosarcoma (OS), and prostate cancer (PCa). Furthermore, the expression of lncRNA HCG18 decreased in bladder cancer (BC) and papillary thyroid cancer (PTC). Overall, the presence of these differential expressions suggests the clinical value of HCG18 in cancer therapy. Additionally, lncRNA HCG18 influences various biological processes of cancer cells. This review summarizes the molecular mechanisms of HCG18 in cancer development, highlights reported the abnormal expression of HCG18 found in various cancer types, and aims to discuss the potential of HCG18 as a target for cancer therapy.

HMMR promotes prostate cancer proliferation and metastasis via AURKA/mTORC2/E2F1 positive feedback loop

Although dysregulated HMMR is linked to prostate cancer (PCa) prognosis, the precise mechanisms remain unclear. Here, we sought to elucidate the role of HMMR in PCa progression as well as underlying mechanism. Herein, we found that upregulation of HMMR frequently observed in PCa samples and was associated with poor prognosis. Additionally, HMMR significantly promoted PCa proliferation and metastasis through gain- and loss-of function approaches in vitro and in vivo. Mechanistically, HMMR may interact with AURKA and elevated AURKA protein level through inhibiting ubiquitination-mediated degradation, which subsequently activated mTORC2/AKT pathway to ensure the reinforcement of PCa progression. Moreover, upregulated E2F1 caused from sustained activation of mTORC2/AKT pathway in turn function as transcription factor to promote HMMR transcription, thereby forming a positive feedback loop to trigger PCa progression. Importantly, administration of the mTOR inhibitor partially antagonised HMMR-mediated PCa progression in vivo. In summary, we not only reveal a novel possible post-translation mechanism mediated by HMMR involved in AURKA regulation, but also describe a positive feedback loop that contributes to PCa deterioration, suggesting HMMR may serve as a potential promising therapeutic target in PCa.

Hsa_circ_0005273 acts as a sponge of miR-509-3p to promote the malignant behaviors of breast cancer by regulating HMMR expression

BACKGROUND

Breast cancer (BC) is a common malignant tumor that threatens the health of women worldwide. Hsa_circ_0005273 has been identified as a carcinogenic factor in some solid tumors, including BC. However, the molecular mechanism of circ_0005273 in BC is poorly defined.

METHODS

The expression of circ_0005273, miR-509-3p, and hyaluronan-mediated motility receptor (HMMR) mRNA in BC was detected by quantitative real-time polymerase chain reaction. Cell proliferation, migration, invasion, and apoptosis were detected by 5-ethynyl-2'-deoxyuridine, transwell, and flow cytometry assays. The glycolysis level was detected via specific kits. Western blot was used to detect protein expression. Binding between miR-509-3p and circ_0005273 or HMMR was also verified by dual-luciferase reporter, RNA pull-down, and RNA immunoprecipitation assays. Xenograft tumor model was used to detect tumor changes in mice, and immunohistochemistry assay was employed to detect Ki-67 abundance.

RESULTS

Circ_0005273 was increased in BC tissues and cells. Circ_0005273 knockdown might inhibit BC cell proliferation, migration, invasion, glutamine metabolism, and induce apoptosis. Circ_0005273 was a miR-509-3p, and the repression role of circ_0005273 absence on BC cell development was weakened by miR-509-3p inhibitor or HMMR overexpression. Circ_0005273 up-regulated the expression of HMMR by sponging miR-509-3p. Additionally, circ_0005273 silencing might hinder tumor growth in vivo.

CONCLUSION

Circ_0005273 knockdown might repress BC cell malignant behaviors by regulating the miR-509-3p/HMMR axis, which might provide a potential therapeutic target for BC.

lncRNA-disease association prediction based on the weight matrix and projection score

With the development of medical science, long noncoding RNA (lncRNA), originally considered as a noise gene, has been found to participate in a variety of biological activities. Several recent studies have shown the involvement of lncRNA in various human diseases, such as gastric cancer, prostate cancer, lung cancer, and so forth. However, obtaining lncRNA-disease relationship only through biological experiments not only costs manpower and material resources but also gains little. Therefore, developing effective computational models for predicting lncRNA-disease association relationship is extremely important. This study aimed to propose an lncRNA-disease association prediction model based on the weight matrix and projection score (LDAP-WMPS). The model used the relatively perfect lncRNA-miRNA relationship data and miRNA-disease relationship data to predict the lncRNA-disease relationship. The integrated lncRNA similarity matrix and the integrated disease similarity matrix were established by fusing various methods to calculate the similarity between lncRNA and disease. This study improved the existing weight algorithm, applied it to the lncRNA-miRNA-disease triple network, and thus proposed a new lncRNA-disease weight matrix calculation method. Combined with the improved projection algorithm, the lncRNA-miRNA relationship and miRNA-disease relationship were used to predict the lncRNA-disease relationship. The simulation results showed that under the Leave-One-Out-Cross-Validation framework, the area under the receiver operating characteristic curve of LDAP-WMPS could reach 0.8822, which was better than the latest result. Taking adenocarcinoma and colorectal cancer as examples, the LDAP-WMPS model was found to effectively infer the lncRNA-disease relationship. The simulation results showed good prediction performance of the LDAP-WMPS model, which was an important supplement to the research of lncRNA-disease association prediction without lncRNA-disease relationship data.

Potentials of lncRNA-miRNA-mRNA networks as biomarkers for laryngeal squamous cell carcinoma

Chemoresistance, radioresistance, and facile spreading of laryngeal squamous cell carcinoma (LSCC) make the practically clinical treatment invalid. Such dismal outcome mainly originates from the lack of effective biomarkers which are highly desirable to understand the pathogenesis of LSCC, and strives to find promising novel biomarkers to improve early screening, effective treatment, and prognosis evaluation in LSCC. Recently, long non-coding RNAs (lncRNAs), a kind of non-coding RNAs longer than 200 nucleotides, can participate in the process of tumorigenesis and progression through many regulatory modalities, such as epigenetic transcriptional regulation and post-transcriptional regulation. Meanwhile, microRNAs (miRNAs, miRs), essentially involved in the post-transcriptional regulation of gene expression, are aberrantly expressed in cancer-related genomic regions or susceptible sites. An increasing number of studies have shown that lncRNAs are important regulators of miRNAs expression in LSCC, and that miRNAs can also target to regulate the expression of lncRNAs, and they can target to regulate downstream messenger RNAs (mRNAs) transcriptionally or post-transcriptionally, thereby affecting various physiopathological processes of LSCC. Complex cross-regulatory networks existing among lncRNAs, miRNAs, and mRNAs can regulate the tumorigenesis and development of LSCC. Such networks may become promising biomarkers and potential therapeutic targets in the research field of LSCC. In this review, we mainly summarize the latest research progress on the regulatory relationships among lncRNAs, miRNAs, and downstream mRNAs, and highlight the potential applications of lncRNA-miRNA-mRNA regulatory networks as biomarkers for the early diagnosis, epithelial-mesenchymal transition (EMT) process, chemoresistance, radioresistance, and prognosis of LSCC, aiming to provide important clues for understanding the pathogenesis of LSCC and developing new diagnostic and therapeutic strategies.

Analysis of prognostic model based on immunotherapy related genes in lung adenocarcinoma

Lung cancer is one of the most common malignant tumors, and ranks high in the list of mortality due to cancers. Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Despite progress in the diagnosis and treatment of lung cancer, the prognosis of these patients remains dismal. Therefore, it is crucial to identify the predictors and treatment targets of lung cancer to provide appropriate treatments and improve patient prognosis. In this study, the gene modules related to immunotherapy were screened by weighted gene co-expression network analysis (WGCNA). Using unsupervised clustering, patients in The Cancer Genome Atlas (TCGA) were divided into three clusters based on the gene expression. Next, gene clustering was performed on the prognosis-related differential genes, and a six-gene prognosis model (comprising PLK1, HMMR, ANLN, SLC2A1, SFTPB, and CYP4B1) was constructed using least absolute shrinkage and selection operator (LASSO) analysis. Patients with LUAD were divided into two groups: high-risk and low-risk. Significant differences were found in the survival, immune cell infiltration, Tumor mutational burden (TMB), immune checkpoints, and immune microenvironment between the high- and low-risk groups. Finally, the accuracy of the prognostic model was verified in the Gene Expression Omnibus (GEO) dataset in patients with LUAD (GSE30219, GSE31210, GSE50081, GSE72094).

Tumor-promoting roles of HMMR in lung adenocarcinoma

Searching for differential genes in lung adenocarcinoma (LUAD) is vital for research. Hyaluronan mediated motility receptor (HMMR) promotes malignant progression of cancer patients. However, the molecular regulators of HMMR-mediated LUAD onset are unknown. This work aimed to study the relevance of HMMR to proliferation, migration and invasion of LUAD cells. Let-7c-5p and HMMR levels in LUAD cells and HLF-a cells were assessed, and their correlation was also detected. Their interaction was determined by dual-luciferase experiments and qRT-PCR. Cell proliferation, migration and invasion potentials in vitro were validated through cell counting kit-8 (CCK-8), colony formation, scratch healing, and transwell assays. The expression of HMMR was examined by qRT-PCR and western blot and the expression of let-7c-5p was assayed by qRT-PCR. It was found that HMMR level was increased in LUAD and negatively correlated with let-7c-5p level. Let-7c-5p directly targeted HMMR to repress LUAD cell proliferation, migration and invasion. The above data illustrated that the let-7c-5p/HMMR axis may provide certain therapeutic value for LUAD patients.

MKL-1-induced PINK1-AS overexpression contributes to the malignant progression of hepatocellular carcinoma via ALDOA-mediated glycolysis

Aldolase A (ALDOA), an important metabolic enzyme in the glycolytic pathway, plays an important role in regulating tumour metabolism. In this study, we investigated the expression pattern of ALDOA in hepatocellular carcinoma (HCC) and its biological role in tumour progression. Bioinformatics analysis, western blot (WB) and RT-qPCR were performed to detect the relative expression of ALDOA in HCC tissues and cell lines. A loss-of-function approach was used to investigate the biological function of ALDOA. The role of ALDOA on glycolysis was assessed by WB, glucose and lactate assay kits and a nude mouse xenograft model. Luciferase reporter experiment, chromatin immunoprecipitation and WB were performed to elucidate the underlying molecular. The expression level of ALODA was up-regulated in HCC tissues and cell lines. High ALDOA levels were associated with poorer patient overall survival. Mechanistic studies suggest that ALDOA is a direct target of miR-34a-5p, which can inhibit glycolysis in hepatocellular carcinoma cells by targeting the 3'UTR of ALDOA. PINK1 antisense RNA (PINK1-AS) competitively sponged miR-34a-5p to increase ALDOA expression by antagonizing miR-34a-5p-mediated ALDOA inhibition. MKL-1 acted as a transcription factor to promote the expression of PINK1-AS and ALDOA, thus promoting the deterioration of HCC cells. This study shows that high expression of ALDOA contributes to the development and poor prognosis of hepatocellular carcinoma and will be a target and potential prognostic biomarker for the treatment of HCC.

Establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes

Lung adenocarcinoma (LUAD) is the most widely known histological subtype of lung cancer. Its classification is significant for the characteristic evaluation of patients. The aim of this research is to assess the categorization of LUAD and its risk model based on necroptosis and to investigate its potential regulatory mechanisms for diagnosing and treating LUAD. According to the expression profile data along with the clinical information related to LUAD from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we constructed a consistency matrix through consistency clustering, and used the ConsensusClusterPlus as the measurement distance to cluster and subtype the samples, and performed gene set enrichment analysis and immune infiltration analysis. Least absolute shrinkage and selection operator (Lasso) regression was utilized for obtaining prognostic significant necroptosis phenotype-related genes. Finally, we measured each patient's riskscore (RS) and build a risk model, and predicted the effect of immunotherapy for different groups of risk factors in the model. Three molecular subtypes of LUAD were obtained by cluster analysis of necroptosis-related genes in LUAD samples. Compared with C1, C3 had a better prognosis and higher immune cell infiltration. The prognosis of the C1 subtype was poor and had a high clinical grade. The proportion of Stage II, Stage III, and Stage IV was much more in comparison with that of the other two subtypes. TP53 gene had a high mutation frequency in the C1 subtype. Gene Set Enrichment Analysis (GSEA) indicated that the aberrant pathways in the C1 and C3 subtypes mainly included some cell cycle-related pathways. In addition, seven genes were identified as related genes of necroptosis phenotype affecting prognosis. High RS had a poor prognosis, while low RS had a good prognosis. The RS was verified to have a strong ability to predict survival. LUAD can be classified by the genes linked with cell necrosis and apoptosis. The difference among various types is helpful to deepen the understanding of LUAD. In addition, a risk model was constructed based. In conclusion, this study provides potential detection targets and treatment methods for LUAD from a new perspective.

A scoping review on the significance of programmed death-ligand 1-inhibiting microRNAs in non-small cell lung treatment: A single-cell RNA sequencing-based study

Background

The programmed death-ligand 1 (PD-L1)/PD-1 axis is one of the well-established inhibitory axes in regulating immune responses. Besides the significance of tumor-intrinsic PD-L1 expression in immune evasion, its oncogenic role has been implicated in various malignancies, like non-small cell lung cancer (NSCLC). As small non-coding RNAs, microRNAs (miRs) have pivotal roles in cancer biology. The current study aimed to systematically review the current knowledge about the significance of PD-L1-inhibiting miRs in NSCLC inhibition and their underlying mechanisms.

Materials and methods

We conducted the current scoping review based on the PRISMA-ScR statement. We systematically searched Embase, Scopus, Web of Science, PubMed, Ovid, EBSCO, ProQuest, Cochrane Library, African Index Medicus, and Pascal-Francis up to 4 April 2021. We also performed in silico tumor bulk RNA sequencing and single-cell RNA sequencing to further the current knowledge of the non-coding RNA-mediated tumor-intrinsic PD-L1 regulation and the PD-L1/PD-1 axis in NSCLC.

Results

The ectopic expression of hsa-miR-194-5p, hsa-miR-326, hsa-miR-526b-3p, hsa-miR-34a-5p, hsa-miR-34c-5p, hsa-miR-138-5p, hsa-miR-377-3p, hsa-let-7c-5p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, and hsa-miR-197-3p, as PD-L1-inhibiting miR, inhibits NSCLC development. These PD-L1-inhibiting miRs can substantially regulate the cell cycle, migration, clonogenicity, invasion, apoptosis, tumor chemosensitivity, and host anti-tumoral immune responses. Based on single-cell RNA sequencing results, PD-L1 inhibition might liberate the tumor-infiltrated CD8+ T-cells and dendritic cells (DCs)-mediated anti-tumoral immune responses via disrupting the PD-L1/PD-1 axis.

Conclusion

Given the promising preclinical results of these PD-L1-inhibiting miRs in inhibiting NSCLC development, their ectopic expression might improve NSCLC patients' prognosis; however, further studies are needed to translate this approach into clinical practice.

Identify miRNA-mRNA regulation pairs to explore potential pathogenesis of lung adenocarcinoma

PURPOSE

MicroRNA (miRNA) function via base-pairing with complementary sequences within mRNA molecules. This study aims to identify critical miRNA-mRNA regulation pairs contributing to lung adenocarcinoma (LUAD) pathogenesis.

PATIENTS AND METHODS

MiRNA and mRNA microarray and RNA-sequencing datasets were downloaded from gene expression omnibus (GEO) and the cancer genome atlas (TCGA) databases. Differential miRNAs (DE-miRNAs) and mRNAs (DE-mRNAs) were screened by the GEO2R tool and R packages. DAVID, DIANA, and Hiplot tools were used to perform gene enrichment analysis. The pairs of miRNA-mRNA were screened from the experimentally validated miRNA-target interactions databases (miRTarBase and TarBase). External validation was carried out in 30 pairs of LUAD tissues by quantitative reverse transcription and polymerase chain reaction (qRT-PCR). The diagnostic value of the miRNA-mRNA regulation pairs was evaluated by receiver operating characteristic curve (ROC) and decision curve analysis (DCA). Biological function assay was were also performed to confirm the function of miRNA-mRNA axis in LUAD progression. The study also performed the clinical, survival and tumor-associated phenotypic analysis of miRNA-mRNA pairs.

RESULTS

A total of 7 miRNA and 13 mRNA expression datasets from GEO were analyzed, and 11 DE-miRNAs (5 down-regulated and 6 up-regulated in LUAD tissues) and 128 DE-mRNAs (30 up-regulated and 98 down-regulated in LUAD tissues) were identified. The pairs of miR-1-3p(down) and CENPF(up) and miR-126-5p(down) and UGT8(up) were verified in the external validation cohort (30 LUAD vs. 30 NC) using qRT-PCR. Areas under the ROC curve of the two miRNA-mRNA regulation pairs panel were 0.973 in TCGA-LUAD and 0.771 in the external validation. The DCA also showed that the miRNA-mRNA regulation pairs had an excellent diagnostic performance distinguishing LUAD from normal controls. The expression of the regulation pairs is different in different ages, TNM stages, and gender. The overexpression of miR-1-3p and miR-126-5p significantly inhibited the proliferation and migration of LUAD cells. Correlation analysis showed that CENPF correlated with prognosis and tumor immunity.

CONCLUSIONS

The research identified potential miRNA-mRNA regulation pairs, providing a new idea for exploring the genesis and development of LUAD.

Recognition of driver genes with potential prognostic implications in lung adenocarcinoma based on H3K79me2

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The efficacy of H3K79me2 on gene expression regulation is affirmed in LUAD.

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An open-source algorithm for identifying LUAD-related driver genes is presented.

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12 H3K79me2-targeted driver genes with clinical values are verified by qPCR.

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The regions with obvious H3K79me2 signals changes on driver genes are pinpointed.

Lung adenocarcinoma is a malignancy with a low overall survival and a poor prognosis. Studies have shown that lung adenocarcinoma progression relates to locus-specific/global changes in histone modifications. To explore the relationship between histone modification and gene expression changes, we focused on 11 histone modifications and quantitatively analyzed their influences on gene expression. We found that, among the studied histone modifications, H3K79me2 displayed the greatest impact on gene expression regulation. Based on the Shannon entropy, 867 genes with differential H3K79me2 levels during tumorigenesis were identified. Enrichment analyses showed that these genes were involved in 16 common cancer pathways and 11 tumors and were target-regulated by trans-regulatory elements, such as Tp53 and WT1. Then, an open-source computational framework was presented (https://github.com/zlq-imu/Identification-of-potential-LUND-driver-genes). Twelve potential driver genes were extracted from the genes with differential H3K79me2 levels during tumorigenesis. The expression levels of these potential driver genes were significantly increased/decreased in tumor cells, as assayed by RT–qPCR. A risk score model comprising these driver genes was further constructed, and this model was strongly negatively associated with the overall survival of patients in different datasets. The proportional hazards assumption and outlier test indicated that this model could robustly distinguish patients with different survival rates. Immune analyses and responses to immunotherapeutic and chemotherapeutic agents showed that patients in the high and low-risk groups may have distinct tendencies for clinical selection. Finally, the regions with clear H3K79me2 signal changes on these driver genes were accurately identified. Our research may offer potential molecular biomarkers for lung adenocarcinoma treatment.

Identifying a 6-Gene Prognostic Signature for Lung Adenocarcinoma Based on Copy Number Variation and Gene Expression Data

The occurrence of lung adenocarcinoma (LUAD) is a complicated process, involving the genetic and epigenetic changes of proto-oncogenes and oncogenes. The objective of this study was to establish new predictive signatures of lung adenocarcinoma based on copy number variations (CNVs) and gene expression data. Next-generation sequencing was implemented to obtain gene expression and CNV information. According to univariate, multivariate survival Cox regression analysis, and LASSO analysis, the expression profiles of lung adenocarcinoma patients were screened and a risk score formula was established and experimentally validated in a local cohort. The model was evaluated by three independent cohorts (TCGA-LUAD, GSE31210, and GSE30219), and then validated by clinical samples from LUAD patients. A total of 844 CNV-related differentially expressed genes (CNV-related DEGs) were identified. These genes are significantly associated with the imbalance of various oxidative stress pathways. A CNV-associated-six gene signature was dramatically linked to overall survival in lung adenocarcinoma samples from both training and validation groups. Functional enrichment analysis further revealed involvement of genes in p53 signaling pathway and cell cycle as well as the mismatch repair pathway. Risk score is an independent marker considering clinical parameters and had better prediction in clinical subpopulation. The same signature also classified tumor tissues of clinical patients with CNV detected from their corresponding nontumorous tissues with an accuracy of 0.92. In conclusion, we identified a new class of 6 CNV-related gene markers that may act as efficient prognostic predictors of lung adenocarcinoma, thus contributing to individualized treatment decisions in patients.

The Oncogenic and Tumor Suppressive Long Non-Coding RNA-microRNA-Messenger RNA Regulatory Axes Identified by Analyzing Multiple Platform Omics Data from Cr(VI)-Transformed Cells and Their Implications in Lung Cancer

Chronic exposure to hexavalent chromium (Cr(VI)) causes lung cancer in humans, however, the underlying mechanism has not been well understood. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are commonly studied non-coding RNAs. miRNAs function mainly through interaction with the 3'-untranslated regions of messenger RNAs (mRNAs) to down-regulate gene expression. LncRNAs have been shown to function as competing endogenous RNAs (ceRNAs) to sponge miRNAs and regulate gene expression. It is now well accepted that lncRNAs and miRNAs could function as oncogenes or tumor suppressors. Dysregulations of lncRNAs and miRNAs have been shown to play important roles in cancer initiation, progression, and prognosis. To explore the mechanism of Cr(VI) lung carcinogenesis, we performed lncRNA, mRNA, and miRNA microarray analysis using total RNAs from our previously established chronic Cr(VI) exposure malignantly transformed and passage-matched control human bronchial epithelial BEAS-2B cells. Based on the differentially expressed lncRNAs, miRNAs, and mRNAs between the control (BEAS-2B-Control) and Cr(VI)-transformed (BEAS-Cr(VI)) cells and by using the lncRNA-miRNA interaction and miRNA target prediction algorithms, we identified three oncogenic (HOTAIRM1/miR-182-5p/ERO1A, GOLGA8B/miR-30d-5p/RUNX2, and PDCD6IPP2/miR-23a-3p/HOXA1) and three tumor suppressive (ANXA2P1/miR-20b-5p/FAM241A (C4orf32), MIR99AHG/miR-218-5p/GPM6A, and SH3RF3-AS1/miR-34a-5p/HECW2) lncRNA-miRNA-mRNA regulatory axes. Moreover, the relevance of these three oncogenic and three tumor suppressive lncRNA-miRNA-mRNA regulatory axes in lung cancer was explored by analyzing publicly available human lung cancer omics datasets. It was found that the identified three oncogenic lncRNA-miRNA-mRNA regulatory axes (HOTAIRM1/miR-182-5p/ERO1A, GOLGA8B/miR-30d-5p/RUNX2, and PDCD6IPP2/miR-23a-3p/HOXA1) and the three tumor suppressive lncRNA-miRNA-mRNA regulatory axes (ANXA2P1/miR-20b-5p/FAM241A (C4orf32), MIR99AHG/miR-218-5p/GPM6A, and SH3RF3-AS1/miR-34a-5p/HECW2) have significant diagnostic and prognosis prediction values in human lung cancer. In addition, our recent studies showed that Cr(VI)-transformed cells display cancer stem cell (CSC)-like properties. Further bioinformatics analysis identified the oncogenic lncRNA-miRNA-mRNA regulatory axes as the potential regulators of cancer stemness. In summary, our comprehensive analysis of multiple platform omics datasets obtained from Cr(VI)-transformed human bronchial epithelial cells identified several oncogenic and tumor suppressive lncRNA-miRNA-mRNA regulatory axes, which may play important roles in Cr(VI) carcinogenesis and lung cancer in general.

Identification of an autophagy-related 12-lncRNA signature and evaluation of NFYC-AS1 as a pro-cancer factor in lung adenocarcinoma

Objective: To develop an autophagy-related lncRNA-based risk signature and corresponding nomogram to predict overall survival (OS) for LUAD patients and investigate the possible meaning of screened factors.

Methods: Differentially expressed lncRNAs and autophagy genes were screened between normal and LUAD tumor samples from the TCGA LUAD dataset. Univariate and multivariate Cox regression analyses were performed to construct the lncRNA-based risk signature and nomogram incorporating clinical information. Then, the accuracy and sensitivity were confirmed by the AUC of ROC curves in both training and validation cohorts. qPCR, immunoblot, shRNA, and ectopic expression were used to verify the positive regulation of NFYC-AS1 on BIRC6. CCK-8, immunofluorescence, and flow cytometry were used to confirm the influence of NFYC-AS1 on cell proliferation, autophagy, and apoptosis via BIRC6.

Results: A 12-lncRNA risk signature and a nomogram combining related clinical information were constructed. Furthermore, the abnormal increase of NFYC-AS1 may promote LUAD progression through the autophagy-related gene BIRC6.

Conclusion: 12-lncRNA signature may function as a predictive marker for LUAD patients, and NFYC-AS1 along with BIRC6 may function as carcinogenic factors in a combinatorial manner.

A novel prognostic signature of metastasis-associated genes and personalized therapeutic strategy for lung adenocarcinoma patients

Lung adenocarcinoma (LUAD) is a highly invasive and metastatic malignant tumor with high morbidity and mortality. This study aimed to construct a prognostic signature for LUAD patients based on metastasis-associated genes (MAGs). RNA expression profiles were downloaded from the Cancer Genome Atlas (TCGA) database. RRA method was applied to identify differentially expressed MAGs. A total of 192 significantly robust MAGs were determined among seven GEO datasets. MAGs were initially selected through the Lasso Cox regression analysis and 6 MAGs were included to construct a prognostic signature model. Transcriptome profile, patient prognosis, correlation between the risk score and clinicopathological features, immune cell infiltration characteristics, immunotherapy sensitivity and chemotherapy sensitivity differed between low- and high-risk groups after grouping according to median risk score. The reliability and applicability of the signature were further validated in the GSE31210, GSE50081 and GSE68465 cohort. CMap predicted 62 small molecule drugs on the base of the prognostic MAGs. Targeted drug staurosporine had hydrogen bonding with Gln-172 of SLC2A1, which is one of MAGs. Staurosporine could inhibit cell migration in A549 and H1299. We further verified mRNA and protein expression of 6 MAGs in A549 and H1299. The signature can serve as a promising prognostic tool and may provide a novel personalized therapeutic strategy for LUAD patients.

Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures

Increasing evidence has implicated the modification of 7-methylguanosine (m7G), a type of RNA modification, in tumor progression. However, no comprehensive analysis to date has summarized the predicted role of m7G-related gene signatures in lung adenocarcinoma (LUAD). Herein, we aimed to develop a novel prognostic model in LUAD based on m7G-related gene signatures. The LUAD transcriptome profiling data and corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus datasets. After screening, we first obtained 29 m7G-related genes, most of which were upregulated in tumor tissues and negatively associated with overall survival (OS). According to the expression similarity of m7G-related genes, the combined samples from the TCGA-LUAD and GSE68465 datasets were further classified as two clusters that exhibit distinct OS rates and genetic heterogeneity. Then, we constructed a novel prognostic model involving four genes by using 130 differentially expressed genes among the two clusters. The combined samples were randomly divided into a training cohort and an internal validation cohort in a 1:1 ratio, and the GSE72094 dataset was used as an external validation cohort. The samples were divided into high- and low-risk groups. We demonstrated that a higher risk score was an independent negative prognostic factor and predicted poor OS. A nomogram was further constructed to better predict the survival of LUAD patients. Functional enrichment analyses indicated that cell cycle and DNA replication-related biological processes and pathways were enriched in the high-risk group. More importantly, the low-risk group had greater infiltration and enrichment of most immune cells, as well as higher ESTIMATE, immune, and stromal scores. In addition, the high-risk group had a lower TIDE score and higher expressions of most immune checkpoint-related genes. We finally noticed that patients in the high-risk group were more sensitive to chemotherapeutic agents commonly used in LUAD. In conclusion, we herein summarized for the first time the alterations and prognostic role of m7G-related genes in LUAD and then constructed a prognostic model based on m7G-related gene signatures that could accurately and stably predict survival and guide individualized treatment decision-making in LUAD patients.

Predicting Differences in Treatment Response and Survival Time of Lung Adenocarcinoma Patients Based on a Prognostic Risk Model of Glycolysis-Related Genes

Background: Multiple factors influence the survival of patients with lung adenocarcinoma (LUAD). Specifically, the therapeutic outcomes of treatments and the probability of recurrence of the disease differ among patients with the same stage of LUAD. Therefore, effective prognostic predictors need to be identified.

Methods: Based on the tumor mutation burden (TMB) data obtained from The Cancer Genome Atlas (TCGA) database, LUAD patients were divided into high and low TMB groups, and differentially expressed glycolysis-related genes between the two groups were screened. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to obtain a prognostic model. A receiver operating characteristic (ROC) curve and a calibration curve were generated to evaluate the nomogram that was constructed based on clinicopathological characteristics and the risk score. Two data sets (GSE68465 and GSE11969) from the Gene Expression Omnibus (GEO) were used to verify the prognostic performance of the gene. Furthermore, differences in immune cell distribution, immune-related molecules, and drug susceptibility were assessed for their relationship with the risk score.

Results: We constructed a 5-gene signature (FKBP4, HMMR, B4GALT1, SLC2A1, STC1) capable of dividing patients into two risk groups. There was a significant difference in overall survival (OS) times between the high-risk group and the low-risk group (p < 0.001), with the low-risk group having a better survival outcome. Through multivariate Cox analysis, the risk score was confirmed to be an independent prognostic factor (HR = 2.709, 95% CI = 1.981–3.705, p < 0.001), and the ROC curve and nomogram exhibited accurate prediction performance. Validation of the data obtained in the GEO database yielded similar results. Furthermore, there were significant differences in sensitivity to immunotherapy, cisplatin, paclitaxel, gemcitabine, docetaxel, gefitinib, and erlotinib between the low-risk and high-risk groups.

Conclusion: Our results reveal that glycolysis-related genes are feasible predictors of survival and the treatment response of patients with LUAD.

NcRNA-Mediated High Expression of HMMR as a Prognostic Biomarker Correlated With Cell Proliferation and Cell Migration in Lung Adenocarcinoma

Background

Hyaluronan-mediated motility receptor (HMMR) plays a pivotal role in cell proliferation in various cancers, including lung cancer. However, its function and biological mechanism in lung adenocarcinoma (LUAD) remain unclear.

Methods

Data on HMMR expression from several public databases were extensively analyzed, including the prognosis of HMMR in the Gene Expression Profiling Interactive Analysis (GEPIA) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed using DAVID and gene set enrichment analysis (GSEA) software. The correlation between HMMR expression and immune cell infiltration was analyzed in the Tumor Immune Estimation Resource (TIMER) database, and the gene and protein networks were examined using the GeneMANIA and STRING databases. Experimentally, the expression of HMMR in LUAD and lung cancer cell lines was determined using immunohistochemistry and quantitative RT-PCR assays. Besides, the function of HMMR on cancer cell proliferation and migration was examined using cell growth curve and colony formation, Transwell, and wound healing assays.

Results

In this study, we found that HMMR was elevated in LUAD and that its high expression was associated with poor clinicopathological features and adverse outcomes in LUAD patients. Furthermore, our results demonstrated that the expression of HMMR was positively correlated with immune cell infiltration and immune modulation. Interestingly, diverse immune cell infiltration affects the prognosis of LUAD. In the functional assay, depletion of HMMR significantly repressed the cancer cell growth and migration of LUAD. Mechanically, we found that that the DNA methylation/TMPO-AS1/let-7b-5p axis mediated the high expression of HMMR in LUAD. Depletion of TMPO-AS1 and overexpression of let-7b-5p could result in the decreased expression of HMMR in LUAD cells. Furthermore, we found that TMPO-AS1 was positively correlated with HMMR, yet negatively correlated with let-7b-5p expression in LUAD.

Conclusions

Our findings elucidated that the DNA methylation/TMPO-AS1/let-7b-5p axis mediated the high expression of HMMR, which may be considered as a biomarker to predict prognosis in LUAD.

LncRNA HCG18 promotes osteosarcoma growth by enhanced aerobic glycolysis via the miR-365a-3p/PGK1 axis

Background

Osteosarcoma (OS) is a common primary bone malignancy. Long noncoding RNA HCG18 is known to play an important role in a variety of cancers. However, its role in OS and relevant molecular mechanisms are unclear.

Methods

Real-time quantitative PCR was performed to determine the expression of target genes. Function experiments showed the effects of HCG18 and miR-365a-3p on OS cell growth.

Results

HCG18 expression was increased in OS cell lines. Moreover, in vitro and in vivo experiments demonstrated that HCG18 knockdown inhibited OS cell proliferation. Mechanistically, HCG18 was defined as a competing endogenous RNA by sponging miR-365a-3p, thus elevating phosphoglycerate kinase 1 (PGK1) expression by directly targeting its 3ʹUTR to increase aerobic glycolysis.

Conclusion

HCG18 promoted OS cell proliferation via enhancing aerobic glycolysis by regulating the miR-365a-3p/PGK1 axis. Therefore, HCG18 may be a potential target for OS treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11658-021-00304-6.

Long Noncoding RNA HCG18 Promotes Malignant Phenotypes of Breast Cancer Cells via the HCG18/miR-103a-3p/UBE2O/mTORC1/HIF-1α-Positive Feedback Loop

In recent years, an increasing number of studies have reported that long noncoding RNAs (lncRNAs) play crucial roles in breast cancer (BC) progression and metastasis. Another study group of our research center reported that lncRNA HCG18 was one of the 30 upregulated lncRNAs in BC tissues compared with normal tissues in The Cancer Genome Atlas database. However, the exact biological roles of HCG18 in BC remain unclear. In this study, we demonstrated that HCG18 is significantly upregulated in BC tissues and cells and that BC patients with high HCG18 expression tend to have poor prognosis. In vitro assays indicated that HCG18 promotes BC cell proliferation and invasion and endows BC cells with cancer stemness properties. In vivo assays revealed that reducing HCG18 expression in the BC cell line MDA-MB-231 markedly decreased tumor growth and lung metastasis in xenograft mouse models. In terms of mechanism, we found that HCG18 positively regulated the expression of BC-related ubiquitin-conjugating enzyme E2O (UBE2O) by sponging miR-103a-3p, and our previous research verified that UBE2O could promote the malignant phenotypes of BC cells through the UBE2O/AMPKα2/mTORC1 axis. Furthermore, as a downstream target of the HCG18/miR-103a-3p/UBE2O/mTORC1 axis, hypoxia-inducible factor 1α transcriptionally promoted HCG18 expression and then formed a positive feedback loop in BC. Taken together, these results confirm that HCG18 plays an oncogenic role in BC and might serve as a prognostic biomarker and a potential therapeutic target for BC treatment.

LncRNA HCG18 upregulates TRAF4/TRAF5 to facilitate proliferation, migration and EMT of epithelial ovarian cancer by targeting miR-29a/b

Background

Although long noncoding RNA HLA complex group 18 (lncRNA HCG18) has been suggested to regulate cell growth in several tumours, the function of HCG18 in epithelial ovarian cancer (EOC) and its mechanism are still unclear.

Methods

shRNAs were applied to reduce HCG18 and related genes. For overexpression of miRNA, a miRNA mimic was transfected into cells. Quantitative real-time PCR (qRT–PCR) was used to detect levels of HCG18, miR-29a/b, and mRNAs. MTT, colony formation, wound healing and Transwell assays were used to evaluate cell proliferation, migration and invasion, respectively. A luciferase reporter assay was utilized to evaluate NF-κB activity and the binding of miRNAs with HCG18 or TRAF4/5. BALB nude mice injected with cells stably expressing shHCG18 or shNC were used for in vivo modelling. Subcutaneous tumour growth was monitored in nude mice, and immunohistochemistry (IHC) was used to determine expression of the proliferation marker Ki67.

Results

Abnormal expression of HCG18 and miR-29a/b was observed in EOC tissues. Knockdown of HCG18 using shRNA inhibited proliferation, migration, EMT and the proinflammatory pathway in EOC cells. miR-29a/b mimics and TRAF4/5 knockdown exhibited effects similar to HCG18 knockdown. Further experiments suggested that HCG18 directly targets miR-29a/b and upregulates TRAF4/5 expression, which are inhibited by targeting miR-29a/b. Moreover, overexpression of TRAF4/5 antagonized the inhibitory effect of HCG18 knockdown, suggesting that they are involved in HCG18-mediated oncogenic effects. Silencing HCG18 reduced tumour size and levels of Ki67 and TRAF4/5 while increasing miR-29a/b levels in vivo.

Conclusions

Taken together, our data revealed an oncogenic signalling pathway mediated by HCG18 in ovarian cell lines, which functions as a ceRNA of miR-29a/b and thus derepresses expression levels of TRAF4/5, facilitating NF-κB pathway-mediated promotion of EOC cell proliferation and migration.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-021-00415-y.

Genomics and Prognosis Analysis of N6-Methyladenosine Regulators in Lung Adenocarcinoma

Objective: N⁶-methyladenosine (m⁶A) modification is involved in modulating various biological processes in human cancers. But the implication of m⁶A modification in lung adenocarcinoma (LUAD) is still unclear. Hence, this study conducted a comprehensive analysis of the expression and clinical implication of m⁶A regulators in LUAD.

Methods: Consensus clustering analysis of 502 LUAD samples in the TCGA dataset was presented based on the expression profiles of 20 m⁶A regulators using ConsensusClusterPlus package. Overall survival (OS), activation of signaling pathways and tumor immunity (immune/stromal score, tumor purity, expression of HLA and immune checkpoints, and immune cell infiltration) were compared between m⁶A modification patterns. The m⁶A-related genes between patterns were identified and prognostic m⁶A-related genes were imported into LASSO-cox regression analysis. The m⁶A risk score was developed and its prognostic implication was evaluated and externally verified in the GSE30219 and GSE72094 dataset. Furthermore, a nomogram that contained independent prognostic indicators was established, followed by external verification.

Results: Two m⁶A modification patterns were clustered across LUAD based on the expression similarity of the m⁶A regulators via consensus clustering analysis, with distinct OS, activation of signaling pathways and tumor immunity. Totally, 213 m⁶A-related genes that were identified by comparing two patterns were significantly related to LUAD prognosis. By LASSO method, we constructed the m⁶A risk score that was a reliable and independent prognostic factor for LUAD. Patients with low m⁶A risk score displayed a prominent survival advantage. After incorporating independent clinical features, we developed the prognostic nomogram that exhibited high predictive accuracy and the best clinical net benefit for OS.

Conclusion: Collectively, our study may provide a clinically useful tool for precise prognostic management and optimization of immunotherapeutic strategies for LUAD patients.

Identification and Validation of a Novel Six-Gene Expression Signature for Predicting Hepatocellular Carcinoma Prognosis

Background

Hepatocellular carcinoma (HCC) is a highly lethal disease. Effective prognostic tools to guide clinical decision-making for HCC patients are lacking.

Objective

We aimed to establish a robust prognostic model based on differentially expressed genes (DEGs) in HCC.

Methods

Using datasets from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the International Genome Consortium (ICGC), DEGs between HCC tissues and adjacent normal tissues were identified. Using TCGA dataset as the training cohort, we applied the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analyses to identify a multi-gene expression signature. Proportional hazard assumptions and multicollinearity among covariates were evaluated while building the model. The ICGC cohort was used for validation. The Pearson test was used to evaluate the correlation between tumor mutational burden and risk score. Through single-sample gene set enrichment analysis, we investigated the role of signature genes in the HCC microenvironment.

Results

A total of 274 DEGs were identified, and a six-DEG prognostic model was developed. Patients were stratified into low- or high-risk groups based on risk scoring by the model. Kaplan-Meier analysis revealed significant differences in overall survival and progression-free interval. Through univariate and multivariate Cox analyses, the model proved to be an independent prognostic factor compared to other clinic-pathological parameters. Time-dependent receiver operating characteristic curve analysis revealed satisfactory prediction of overall survival, but not progression-free interval. Functional enrichment analysis showed that cancer-related pathways were enriched, while immune infiltration analyses differed between the two risk groups. The risk score did not correlate with levels of PD-1, PD-L1, CTLA4, or tumor mutational burden.

Conclusions

We propose a six-gene expression signature that could help to determine HCC patient prognosis. These genes may serve as biomarkers in HCC and support personalized disease management.

Long non‑coding RNA HCG18 facilitates the progression of laryngeal and hypopharyngeal squamous cell carcinoma by upregulating FGFR1 via miR‑133b

It has been reported that long non-coding RNA HLA complex group 18 (HCG18) is involved in the progression of cancer, acting as an oncogenic gene. The aim of the present study was to investigate the mechanism underlying the action of HCG18 in laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC). The expression levels of HCG18, microRNA (miR)-133b and fibroblast growth factor receptor 1 (FGFR1) in LHSCC tissues and transfected LHSCC cells were evaluated by reverse transcription-quantitative PCR or immunohistochemistry. The viability, migration and invasion of transfected LHSCC cells were detected by Cell Counting Kit-8, wound healing and Transwell assays, respectively. The targeting relationships of HCG18, miR-133b and FGFR1 were predicted by bioinformatics analysis and confirmed using a dual-luciferase reporter assay. Moreover, the expression levels of FGFR1, phosphorylated (p)-PI3K, PI3K, p-AKT, AKT, p53, Bax and Bcl-2 in transfected LHSCC cells were measured by western blotting. It was found that the expression levels of HCG18 and FGFR1 were upregulated, but those of miR-133b were downregulated in LHSCC tissues. Short hairpin RNA (sh) HCG18 and miR-133b mimic inhibited LHSCC cell viability, while enhancing miR-133b expression. HCG18 could competitively bind with miR-133b. Moreover, the miR-133b inhibitor promoted cell viability, migration, invasion and the expression levels of Bcl-2, p-PI3K and p-AKT, but inhibited the expression levels of p53 and Bax, which were abrogated by shHCG18. miR-133b could competitively bind with FGFR1, and the miR-133b mimic decreased the expression level of FGFR1 in transfected LHSCC cells. shFGFR1 promoted the expression levels of p53 and Bax, while inhibiting viability, migration, invasion and Bcl-2, p-PI3K and p-AKT expression in LHSCC cells. In conclusion, the current results indicated that HCG18 facilitated the progression of LHSCC by upregulating FGFR1 via miR-133b. The present study evaluated the mechanism with regards to the action of HCG18 in LHSCC, and these experimental results may provide novel evidence for targeted therapy of LHSCC.

Comprehensive Analysis of Acetylation-Related lncRNAs and Identified AC099850.3 as Prognostic Biomarker in Non-Small Cell Lung Cancer

The present study aimed to analyze the effects of acetylation-related lncRNAs in non-small-cell lung cancer (NSCLC). A total of 399 differentially expressed lncRNAs (DElncRNAs) have been identified between 497 NSCLC tissues and 54 normal tissues in the TCGA database, and 105 of which were correlated with acetylation regulators. By using univariate cox regression analysis and combining it with clinical prognosis information, 12 prognostic-related lncRNAs were selected for the subsequent analysis. The NSCLC patients were divided into two subgroups (cluster 1 and cluster 2) by clustering software, and immunocyte infiltration analysis, microenvironmental analysis, and clinical relevance analysis were performed between the two subgroups. A risk model was also built to further assess the prognosis value of prognostic-related lncRNAs in NSCLC patients. We found that AC099850.3 was significantly higher in both cluster 1 and high-risk subgroups, which may serve as a potential biomarker for the prognosis of NSCLC patients. Then, based on ceRNA competition mechanisms, the pathway enrichment of 105 acetylation-related lncRNAs was conducted by GO and KEGG analyses. We found the acetylation-related lncRNAs were primarily enriched in MAPK and EGFR signaling pathways, which were closely associated with NSCLC development. Finally, we validated the expression levels of AC099850.3 in NSCLC tissues and adjacent non-cancerous tissues and confirmed that AC099850.3 was significantly highly expressed in NSCLC tissues and cells. These results may provide clues for our understanding of the role of acetylation-related lncRNAs and valuable information for future clinical diagnosis and prognosis in NSCLC patients.