Systematic identification of lincRNA-based prognostic biomarkers by integrating lincRNA expression and copy number variation in lung adenocarcinoma

Linc00941 fuels ribogenesis and protein synthesis by supporting robust cMYC translation in malignant pleural mesothelioma

Malignant pleural mesothelioma is a rare and lethal cancer caused by exposure to asbestos. The highly inflammatory environment caused by fibers accumulation forces cells to undergo profound adaptation to gain survival advantages. Prioritizing the synthesis of essential transcripts is an efficient mechanism coordinated by multiple molecules, including long non-coding RNAs. Enhancing the knowledge about these mechanisms is an essential weapon in combating mesothelioma. Linc00941 correlates to bad prognosis in various cancers, but it is reported to partake in distinct and apparently irreconcilable processes. In this work, we report that linc00941 supports the survival and aggressiveness of mesothelioma cells by influencing protein synthesis and ribosome biogenesis. Linc00941 binds to the translation initiation factor eIF4G, promoting the selective protein synthesis of cMYC, which, in turn, enhances the expression of key genes involved in translation. We analyzed a retrospective cohort of 97 mesothelioma patients' samples from our institution, revealing that linc00941 expression strongly correlates with reduced survival probability. This discovery clarifies linc00941's role in mesothelioma and proposes a unified mechanism of action for this lncRNA involving the selective translation of essential oncogenes, reconciling the discrepancies about its function.

LncRNA TDRKH-AS1 promotes breast cancer progression via the miR-134-5p/CREB1 axis

BACKGROUND

Breast cancer (BC) is a prevalent malignancy with complex etiology and varied clinical behavior. Long non-coding RNAs (lncRNAs) have emerged as key regulators in cancer progression, including BC. Among these, lncRNA TDRKH-AS1 has been implicated in several cancers, but its role in BC remains unclear.

METHODS

We conducted a comprehensive investigation to elucidate the role of TDRKH-AS1 in BC. Clinical samples were collected from BC patients, and BC cell lines were cultured. Bioinformatics analysis using the starBase database was carried out to assess TDRKH-AS1 expression levels in BC tissue samples. Functional experiments, including knockdown, colony formation, CCK-8, Transwell, and wound-healing assays, were conducted to determine the role of TDRKH-AS1 in BC cell proliferation and invasion. Luciferase reporter and RIP assays were used to examine the interactions between TDRKH-AS1 and miR-134-5p. In addition, the downstream target gene of miR-134-5p, cAMP response element-binding protein 1 (CREB1), was identified and studied using various methods, including RT-qPCR, immunoprecipitation, and rescue experiments. In vivo experiments using mouse tumor xenograft models were conducted to examine the role of TDRKH-AS1 in BC tumorigenesis.

RESULTS

TDRKH-AS1 was found to be significantly upregulated in BC tissues and cell lines. High TDRKH-AS1 expression correlated with advanced BC stages and worse patient outcomes. Knockdown of TDRKH-AS1 led to decreased BC cell proliferation and invasion. Mechanistically, TDRKH-AS1 acted as a sponge for miR-134-5p, thereby reducing the inhibitory effects of miR-134-5p on CREB1 expression. Overexpression of CREB1 partially rescued the effects of TDRKH-AS1 knockdown in BC cells. In vivo studies further confirmed the tumor-promoting role of TDRKH-AS1 in BC.

CONCLUSIONS

Our study unveiled a novel regulatory axis involving TDRKH-AS1, miR-134-5p, and CREB1 in BC progression. TDRKH-AS1 functioned as an oncogenic lncRNA by promoting BC cell proliferation and invasion through modulation of the miR-134-5p/CREB1 axis. These findings highlighted TDRKH-AS1 as a potential diagnostic biomarker and therapeutic target for BC treatment.

The human long non-coding RNA LINC00941 and its modes of action in health and disease

Long non-coding RNAs have gained attention in recent years as they were shown to play crucial roles in the regulation of cellular processes, but the understanding of the exact mechanisms is still incomplete in most cases. This is also true for long non-coding RNA LINC00941, which was recently found to be highly upregulated in various types of cancer influencing cell proliferation and metastasis. Initial studies could not elucidate the mode of action to understand the role and real impact of LINC00941 in tissue homeostasis and cancer development. However, recent analyses have demonstrated multiple potential modes of action of LINC00941 influencing the functionality of various cancer cell types. Correspondingly, LINC00941 was proposed to be involved in regulation of mRNA transcription and modulation of protein stability, respectively. In addition, several experimental approaches suggest a function of LINC00941 as competitive endogenous RNA, thus acting in a post-transcriptional regulatory fashion. This review summarizes our recent knowledge about the mechanisms of action of LINC00941 elucidated so far and discusses its putative role in miRNA sequestering processes. In addition, the functional role of LINC00941 in regulating human keratinocytes is discussed to also highlight its role in normal tissue homeostasis tissue aside from its involvement in cancer.

Machine learning-based immune prognostic model and ceRNA network construction for lung adenocarcinoma

PURPOSE

Lung adenocarcinoma (LUAD) is a malignant tumor with a high lethality rate. Immunotherapy has become a breakthrough in cancer treatment and improves patient survival and prognosis. Therefore, it is necessary to find new immune-related markers. However, the current research on immune-related markers in LUAD is not sufficient. Therefore, there is a need to find new immune-related biomarkers to help treat LUAD patients.

METHODS

In this study, a bioinformatics approach combined with a machine learning approach screened reliable immune-related markers to construct a prognostic model to predict the overall survival (OS) of LUAD patients, thus promoting the clinical application of immunotherapy in LUAD. The experimental data were obtained from The Cancer Genome Atlas (TCGA) database, including 535 LUAD and 59 healthy control samples. Firstly, the Hub gene was screened using a bioinformatics approach combined with the Support Vector Machine Recursive Feature Elimination algorithm; then, a multifactorial Cox regression analysis by constructing an immune prognostic model for LUAD and a nomogram to predict the OS rate of LUAD patients. Finally, the regulatory mechanism of Hub genes in LUAD was analyzed by ceRNA.

RESULTS

Five genes, ADM2, CDH17, DKK1, PTX3, and AC145343.1, were screened as potential immune-related genes in LUAD. Among them, ADM2 and AC145343.1 had a good prognosis in LUAD patients (HR < 1) and were novel markers. The remaining three genes screened were associated with poor prognosis in LUAD patients (HR > 1). In addition, the experimental results showed that patients in the low-risk group had better OS rates than those in the high-risk group (P < 0.001).

CONCLUSION

In this paper, we propose an immune prognostic model to predict OS rate in LUAD patients and show the correlation between five immune genes and the level of immune-related cell infiltration. It provides new markers and additional ideas for immunotherapy in patients with LUAD.

Overexpressed RBPMS-AS1 increased cell radiosensitivity by sponging miR-19a-3p in lung cancer cell lines (A549 and SK-MES-1) via regulating PTEN/AKT axis

PURPOSE

This paper intended to study RBPMS-AS1 in lung cancer (LC) radiosensitivity.

MATERIALS AND METHODS

LC cells were transfected with RBPMS-AS1 overexpression plasmid and miR-19a-3p mimic and treated with radiation. PTEN, AKT, p-AKT, RBPMS-AS1, and miR-19a-3p expressions were detected via Western blot and qRT-PCR. The localization of RBPMS-AS1 in cells was determined through fluorescence in situ hybridization assay. The targeting relationships of RBPMS-AS1 and miR-19a-3p/miR-19a-3p and PTEN were determined through RIP and dual luciferase reporter analysis. Cell survival, viability, and apoptosis were assessed through colony formation, CCK-8, and flow-cytometry assays.

RESULTS

RBPMS-AS1 was downregulated in LC and mainly distributed in cytoplasm. RBPMS-AS1 targeted miR-19a-3p in LC cells. Radiation suppressed LC cell survival, viability, and induced apoptosis, as overexpressed RBPMS-AS1 performed the similar effects and enhanced those effects induced by radiation. MiR-19a-3p mimic reversed the effect of overexpressed RBPMS-AS1 on enhancing radiation-induced LC cell apoptosis. MiR-19a-3p targeted PTEN and miR-19a-3p mimic reversed the effect of overexpressed RBPMS-AS1 on PTEN and phosphorylation of AKT in LC cells.

CONCLUSION

Overexpressed RBPMS-AS1 sponged miR-19a-3p to increase cell radiosensitivity in LC via regulating PTEN/AKT axis.

Construction and validation of an angiogenesis-related lncRNA prognostic model in lung adenocarcinoma

Background: There is increasing evidence that long non-coding RNAs (lncRNAs) can be used as potential prognostic factors for cancer. This study aimed to develop a prognostic model for lung adenocarcinoma (LUAD) using angiogenesis-related long non-coding RNAs (lncRNAs) as potential prognostic factors.

Methods: Transcriptome data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to identify aberrantly expressed angiogenesis-related lncRNAs in LUAD. A prognostic signature was constructed using differential expression analysis, overlap analysis, Pearson correlation analysis, and Cox regression analysis. The model’s validity was assessed using K-M and ROC curves, and independent external validation was performed in the GSE30219 dataset. Prognostic lncRNA-microRNA (miRNA)-messenger RNA (mRNA) competing endogenous RNA (ceRNA) networks were identified. Immune cell infiltration and mutational characteristics were also analyzed. The expression of four human angiogenesis-associated lncRNAs was quantified using quantitative real-time PCR (qRT-PCR) gene arrays.

Results: A total of 26 aberrantly expressed angiogenesis-related lncRNAs in LUAD were identified, and a Cox risk model based on LINC00857, RBPMS-AS1, SYNPR-AS1, and LINC00460 was constructed, which may be an independent prognostic predictor for LUAD. The low-risk group had a significant better prognosis and was associated with a higher abundance of resting immune cells and a lower expression of immune checkpoint molecules. Moreover, 105 ceRNA mechanisms were predicted based on the four prognostic lncRNAs. qRT-PCR results showed that LINC00857, SYNPR-AS1, and LINC00460 were significantly highly expressed in tumor tissues, while RBPMS-AS1 was highly expressed in paracancerous tissues.

Conclusion: The four angiogenesis-related lncRNAs identified in this study could serve as a promising prognostic biomarker for LUAD patients.

Expression analysis of novel long non-coding RNAs for invasive ductal and invasive lobular breast carcinoma cases

AIM

Long non-coding RNAs (LncRNAs) serve as important regulatory molecules of gene expression and protein functionality at multiple biological levels, and their deregulation plays a key role in tumorigenesis including in breast cancer metastasis. Therefore, in this study, we aim to compare the expression of novel lncRNAs in the landscape of invasive ductal carcinoma (IDC) and invasive lobular (ILC) carcinoma of breast.

MAIN METHODS

We have designed an in-silico approach to find the lncRNAs that regulate the breast cancer. Then, we used the clinical samples to carry out the verification of our in silico finding. In the present study, the tissues of breast cancer were deparaffinized. RNA was extracted by the TRIzole method. After synthesizing cDNA from the extracted RNA, expression levels of lncRNAs were analyzed by qPCR using primers specifically designed and validated for the targeted lncRNAs. In this study, breast biopsy materials from 41 female patients with IDC and 10 female patients with ILC were examined histopathological and expression changes of candidate lncRNAs were investigated in line with the findings. The results were analyzed using IBM SPSS Statistics 25 version.

RESULTS

The mean age of the cases was 53.78 ± 14.96. The minimum age was 29, while the maximum age was 87. While 27 of the cases were pre-menopausal, 24 cases were post-menopausal. The number of hormone receptor-positive cases was found to be 40, 35, and 27 for ER, PR, and cerb2/neu, respectively. While the expressions of LINC00501, LINC00578, LINC01209, LINC02015, LINC02584, ABCC5-AS1, PEX5L-AS2, SHANK2-AS3 and SOX2-OT showed significant differences (p < 0.05), the expressions of LINC01206, LINC01994, SHANK2-AS1, and TPRG1-AS2 showed no significant differences (p > 0.05). In addition, it was determined that the regulation of all lncRNAs could be able to involve in the development of cancer such as the NOTCH1, NFKB, and estrogen receptor signalings.

CONCLUSION

As a result, it was thought that the discovery of novel lncRNAs might be an important player in the diagnosis, prognosis and therapeutic development of breast cancer.

Long Noncoding RNA LINC00578 Inhibits Ferroptosis in Pancreatic Cancer via Regulating SLC7A11 Ubiquitination

Background

Pancreatic cancer is a highly aggressive malignancy worldwide with rapid development and an exceedingly poor prognosis. lncRNAs play crucial roles in regulating the biological behaviors of tumor cells. In this study, we discovered that LINC00578 acted as a regulator of ferroptosis in pancreatic cancer.

Methods

A series of loss- and gain-of-function experiments in vitro and in vivo were performed to explore the oncogenic role of LINC00578 in pancreatic cancer development and progression. Label-free proteomic analysis was performed to select LINC00578-related differentially expressed proteins. Pull-down and RNA immunoprecipitation assays were carried out to determine and validate the binding protein of LINC00578. Coimmunoprecipitation assays were used to investigate the association of LINC00578 with SLC7A11 in ubiquitination and to confirm the interaction between ubiquitin-conjugating enzyme E2 K (UBE2K) and SLC7A11. An immunohistochemical assay was used to confirm the correlation between LINC00578 and SLC7A11 in the clinic.

Results

LINC00578 positively regulated cell proliferation and invasion in vitro and tumorigenesis in vivo in pancreatic cancer. LINC00578 can obviously inhibit ferroptosis events, including cell proliferation, reactive oxygen species (ROS) generation, and mitochondrial membrane potential (MMP) depolarization. In addition, the LINC00578-induced inhibitory effect on ferroptosis events was rescued by SLC7A11 knockdown. Mechanistically, LINC00578 directly binds UBE2K to decrease the ubiquitination of SLC7A11, thus accelerating SLC7A11 expression. In the clinic, LINC00578 is closely associated with clinicopathologic factors and poor prognosis and correlated with SLC7A11 expression in pancreatic cancer.

Conclusions

This study elucidated that LINC00578 acts as an oncogene to promote pancreatic cancer cell progression and suppress ferroptosis by directly combining with UBE2K to inhibit the ubiquitination of SLC7A11, which provides a promising option for the diagnosis and treatment of pancreatic cancer.

Reciprocal regulation of LINC00941 and SOX2 promotes progression of esophageal squamous cell carcinoma

LINC00941 is a novel long noncoding RNA (lncRNA) and emerging as an important factor in cancer development. However, the exact function and relative regulatory mechanism of LINC00941 in carcinogenesis of esophageal squamous cell carcinoma (ESCC) remain to be further clarified. The present study was to investigate the expression level, functions, and mechanisms of LINC00941 in ESCC tumorigenesis. LINC00941 was significantly upregulated in ESCC, and upregulated LINC00941 was correlated with dismal patient outcomes. LINC00941 functioned as an oncogene by promoting cells proliferation, stemness, migration, and invasion in ESCC. In terms of mechanisms, SOX2 could bind directly to the promoter region of LINC00941 and activate its transcription. In turn, LINC00941 upregulated SOX2 through interacting with interleukin enhancer binding factor 2 (ILF2) and Y-box binding protein 1 (YBX1) at the transcriptional and post-transcriptional levels. LINC00941 recruited ILF2 and YBX1 to the promoter region of SOX2, leading to upregulation of the transcription of SOX2. Moreover, LINC00941 could promote the binding ability of ILF2 and YBX1 on mRNA of SOX2 and further stabilize SOX2 mRNA. Therefore, LINC00941 contributed to the malignant behaviors of ESCC cells via the unrestricted increase in SOX2 expression. In conclusion, our data indicate that LINC00941 exacerbates ESCC progression through forming a LINC00941-ILF2/YBX1-SOX2 positive feedback loop, and LINC00941 may be a promising prognostic and therapeutic target for ESCC.

Analysis of eEF1A2 gene expression and copy number in cervical carcinoma

OBJECTIVE

To explore and analyze the expression of eukaryotic translation elongation factor 1 alpha 2 (eEF1A2) gene in cervical cancer tissues, its relationship with patient survival, gene mutations, and changes in copy number in cervical cancer and chronic cervicitis tissues.

METHODS

The expression of the eEF1A2 gene in cervical cancer and its relationship with patient survival were analyzed using gene expression profile interactive analysis. Changes in eEF1A2 expression in cervical cancer tissues were analyzed using cBioPortal, a portal for cancer genomics analysis. The eEF1A2 copy number in cervical cancer tissues and chronic cervicitis tissues was determined by real-time fluorescence quantitative polymerase chain reaction. The relationship between the expression of eEF1A2 protein and the clinical stage, pathological grade, and patient survival of cervical cancer was analyzed by the database: The Human Protein Atlas, an integrated repository portal for tumor-immune system interactions.

RESULTS

Gene expression profile interactive analysis database analysis showed no significant differences in the expression of eEF1A2 between cervical cancer and normal cervical tissues (P > .05). The eEF1A2 gene expression level was not correlated with the survival of cervical cancer patients (P > .05). Analysis of the cBioPortal database showed that 18 of 297 cervical cancer patients had eEF1A2 gene changes, including missense mutation, splice mutation, amplification, and messenger RNA increase. There was no significant difference in eEF1A2 gene copy number between cervical cancer and chronic cervicitis (P > .05). The Human Protein Atlas and an integrated repository portal for tumor-immune system interactions database analysis of immunohistochemical data showed that eEF1A2 protein expression was no significant difference in clinical stage, pathological grade and patient survival of cervical cancer (P > .05).

CONCLUSION

The eEF1A2 gene was mutated in cervical cancer tissues. The eEF1A2 gene copy number was not associated with changes in the expression of the eEF1A2 gene in cervical cancer tissues.

Long Non-Coding RNAs Associated with Mitogen-Activated Protein Kinase in Human Pancreatic Cancer

Long non-coding RNAs (lncRNAs) have emerged as a significant player in various cancers, including pancreatic cancer. However, how lncRNAs are aberrantly expressed in cancers is largely unknown. We hypothesized that lncRNAs would be regulated by signaling pathways and contribute to malignant phenotypes of cancer. In this study, to understand the significance of mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK), which is a major aberrant signaling pathway in pancreatic cancer, for the expression of lncRNAs, we performed comparative transcriptome analyses between pancreatic cancer cell lines with or without activation of MAPK. We identified 45 lncRNAs presumably associated with MAPK in pancreatic cancer cells; among these, LINC00941 was consistently upregulated by MAPK. The immediate genomic upstream region flanking LINC00941 was identified as a promoter region, the activity of which was found to be preferentially associated with MAPK activity via ETS-1 binding site. LINC00941 promoted cell proliferation in vitro. Moreover, TCGA data analysis indicated that high expression of LINC00941 was associated with poor prognosis of patients with pancreatic cancer. Transcriptomes comparing transcriptions between cells with and without LINC00941 knockdown revealed 3229 differentially expressed genes involved in 44 biological processes, including the glycoprotein biosynthetic process, beta-catenin-TCF complex assembly, and histone modification. These results indicate that MAPK mediates the aberrant expression of lncRNAs. LINC00941 is the lncRNA by MAPK most consistently promoted, and is implicated in the dismal prognosis of pancreatic cancer. MAPK-associated lncRNAs may play pivotal roles in malignant phenotypes of pancreatic cancer, and as such might represent both potentially valid therapeutic targets and diagnostic biomarkers.

An autophagy-associated lncRNAs model for predicting the survival in non-small cell lung cancer patients

Long non-coding RNAs (lncRNAs) can influence the proliferation, autophagy, and apoptosis of non-small cell lung cancer (NSCLC). LncRNAs also emerge as valuable prognostic factors for NSCLC patients. Consequently, we set out to discover more autophagy-associated lncRNAs. We acquired autophagy-associated genes and information on lncRNAs from The Cancer Genome Atlas database (TCGA), and the Human Autophagy Database (HADb). Then, the prognostic prediction signature was constructed through using co-expression and Cox regression analysis. The signature was constructed including 7 autophagy-associated lncRNAs (ABALON, NKILA, LINC00941, AL161431.1, AL691432.2, AC020765.2, MMP2-AS1). After that, we used univariate and multivariate Cox regression analysis to calculate the risk score. The survival analysis and ROC curve analysis confirmed good performances of the signature. GSEA indicated that the high-risk group was principally enriched in the adherens junction pathway. In addition, biological experiments showed that ABALON promoted the proliferation, metastasis and autophagy levels of NSCLC cells. These findings demonstrate that the risk signature consisting of 7 autophagy-associated lncRNAs accurately predicts the prognosis of NSCLC patients and should be investigated for potential therapeutic targets in clinic.

c-Myc-Regulated lncRNA-IGFBP4 Suppresses Autophagy in Cervical Cancer-Originated HeLa Cells

LncRNAs are known to regulate a plethora of key events of cellular processes; however, little is known about the function of lncRNAs in autophagy. Here in the current study, we report lncRNA-IGFBP4 which has previously been known to regulate the proliferation and reprogramming of cancer cells, but its role in autophagy is not yet known. We found that serum starvation provokes autophagy-induced downregulation of lncRNA-IGFBP4 levels. Next, we determined that c-Myc can negatively regulate lncRNA-IGFBP4 in HeLa cells. Phenotypically, we found that upon depletion of lncRNA-IGFBP4, the HeLa cells undergo autophagy through ULK1/Beclin1 signaling. Furthermore, through TCGA data analysis, we found lncRNA-IGFB4 overexpressed in most cancers including cervical cancer. Based on these findings, we conclude that c-Myc maintains cellular homeostasis through negatively regulating lncRNA-IGFBP4 in cervical cancer cells.

Long non-coding RNA BZRAP1-AS1 functions in malignancy and prognosis for non-small-cell lung cancer

Purpose

The function of BZRAP1-AS1 is unknown in lung cancer. We evaluated the clinicopathologic significance of BZRAP1-AS1, and its role in non-small-cell lung cancer (NSCLC) progression.

Patient and methods

Sixty-three NSCLC patients from Beijing Chest Hospital were included. The expression of BZRAP1-AS1 was detected by real-time quantitative polymerase chain reaction (RT-qPCR) in tumor tissues and adjacent normal tissues. Then, the clinicopathological significance and prognostic value of BZRAP1-AS1 were analyzed by using our cohort and TCGA cohort. Finally, the effect of BZRAP1-AS1 on proliferation and motility of NSCLC cell lines were evaluated by cell growth assay, colony formation assay, xenograft tumorigenesis experiment in nude mice and transwell assays respectively.

Results

Compared with adjacent normal tissues, BZRAP1-AS1 showed lower expression in NSCLC tumor tissues. As for the relationship between BZRAP1-AS1 and clinical characteristics, our results were consistent with those of TCGA data. BZRAP1-AS1 was lower in T1 than T2-T4 patients, N1-N3 than N0 patients. Low level BZRAP1-AS1 was related to shorter overall survival time (OS) in lung adenocarcinoma (LUAD), and poor first progression time (FP) in LUAD and lung squamous cell carcinoma (LUSC) patients. BZRAP1-AS1 was significantly associated with the prognosis of NSCLC patients. Overexpression of BZRAP1-AS1 inhibited proliferation and migration of H1299 and HCC827 cells.

Conclusion

BZRAP1-AS1 expression decreases in tumor tissues with the increase of malignancy grades in NSCLC. BZRAP1-AS1 plays an anticancer role by inhibiting cell proliferation, invasion, and metastasis, and has a potential prognostic value in NSCLC. BZRAP1-AS1 may serve as a diagnostic marker and therapeutic target for NSCLC.

Comprehensive characterization of clonality of driver genes revealing their clinical relevance in colorectal cancer

Background

Genomic studies of colorectal cancer have revealed the complex genomic heterogeneity of the tumor. The acquisition and selection of genomic alterations may be critical to understanding the initiation and progression of this disease.

Methods

In this study, we have systematically characterized the clonal architecture of 97 driver genes in 536 colorectal cancer patients from TCGA.

Results

A high proportion of clonal mutations in 93 driver genes were observed. 40 genes showed significant associations between their clonality and multiple clinicopathologic factors. Kaplan–Meier analysis suggested that the mutation clonality of ANK1, CASP8, SMAD2, and ARID1A had a significant impact on the CRC patients' outcomes. Multivariable analysis revealed that subclonal ANK1 mutations, clonal CASP8 mutations, and clonal SMAD2 mutations independently predicted for shorter overall survival after adjusting for clinicopathological factors. The poor outcome of the subclonal ANK1 mutation may be caused by upregulation of IL4I1, IDO1, IFNG and MAPK12 which showed potential roles in tumor immune evasion through accumulation of immunosuppressive cells such as regulatory T cells and myeloid derived suppressor cells.

Conclusion

These results suggested that the clonality of driver genes could act as prognostic markers and potential therapeutic targets in human colorectal cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03529-x.

Construction of a Novel Prognostic Signature in Lung Adenocarcinoma Based on Necroptosis-Related lncRNAs

Background: Long non-coding RNAs (lncRNAs) are drawing increasing attention as promising predictors of prognosis for lung adenocarcinoma (LUAD) patients. Necroptosis, a novel regulated mechanism of necrotic cell death, plays an important role in the biological process of cancer. The aim of this study was to identify the necroptosis-related lncRNAs (NRLRs) in a LUAD cohort and establish a necroptosis-related lncRNA signature (NRLSig) to stratify LUAD patients.

Methods: NRLRs were identified in LUAD patients from The Cancer Genome Atlas (TCGA) database using Pearson correlation analysis between necroptosis-related genes and lncRNAs. Then the NRLSig was identified using univariate Cox regression analysis and LASSO regression analysis. Assessments of the signature were performed based on survival analysis, receiver operating characteristic (ROC) curve analysis and clustering analysis. Next, a nomogram containing the NRLSig and clinical information was developed through univariate and multivariate Cox regression analysis. Further, functional enrichment analysis of the selected lncRNAs in NRLSig and the association between NRLSig and the immune infiltration were also evaluated.

Results: A 4-lncRNA signature, incorporating LINC00941, AP001453.2, AC026368.1, and AC236972.3, was identified to predict overall survival (OS) and stratify LUAD patients into different groups. Survival analysis, ROC curve analysis and clustering analysis showed good performance in the prognostic prediction of the lncRNA signature. Then, a nomogram containing the NRLSig was developed and showed satisfactory predictive accuracy, calibration and clinical usefulness. The co-expressed genes of selected NRLRs were enriched in several biological functions and signaling pathways. Finally, differences in the abundance of immune cells were investigated among the high-risk group and low-risk group divided by the NRLSig.

Conclusion: The proposed NRLSig may provide promising therapeutic targets or prognostic predictors for LUAD patients.

A novel cuproptosis-related prognostic lncRNA signature and lncRNA MIR31HG/miR-193a-3p/TNFRSF21 regulatory axis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) remains the most common subtype of lung malignancy. Cuproptosis is a newly identified cell death which could regulate tumor cell proliferation and progression. Long non-coding RNAs (lncRNAs) are key molecules and potential biomarkers for diagnosing and treating various diseases. However, the effects of cuproptosis-related lncRNAs on LUAD are still unclear. In our study, 7 cuproptosis-related lncRNAs were selected to establish a prognostic model using univariate Cox regression analysis, LASSO algorithm, and multivariate analysis. Furthermore, we evaluated AC008764.2, AL022323.1, ELN-AS1, and LINC00578, which were identified as protective lncRNAs, while AL031667.3, AL606489.1, and MIR31HG were identified as risk lncRNAs. The risk score calculated by the prognostic model proved to be an effective independent factor compared with other clinical features by Cox regression analyses [univariate analysis: hazard ratio (HR) = 1.065, 95% confidence interval (CI) = 1.043–1.087, P < 0.001; multivariate analysis: HR = 1.067, 95% CI = 1.044–1.091, P < 0.001]. In addition, both analyses (ROC and nomogram) were used to corroborate the accuracy and reliability of this signature. The correlation between cuproptosis-related lncRNAs and immune microenvironment was elucidated, where 7 immune cells and 8 immune-correlated pathways were found to be differentially expressed between two risk groups. Furthermore, our results also identified and verified the ceRNA of cuproptosis-related lncRNA MIR31HG/miR-193a-3p/TNFRSF21 regulatory axis using bioinformatics tools. MIR31HG was highly expressed in LUAD specimens and some LUAD cell lines. Inhibition of MIR31HG clearly reduced the proliferation, migration, and invasion of the LUAD cells. MIR31HG showed oncogenic features via sponging miR-193a-3p and tended to positively regulate TNFRSF21 expression. In a word, lncRNA MIR31HG acts as an oncogene in LUAD by targeting miR-193a-3p to modulate TNFRSF21, which may be beneficial to the gene therapy of LUAD.

Identification of metastasis-related long non-coding RNAs in lung cancer through a novel tumor mesenchymal score

Long non-coding RNAs (lncRNAs) have been proven to play critical roles in epithelial-mesenchymal transition (EMT) and metastasis of lung cancer. However, the biological functions and related mechanisms of lncRNAs are unclear. In addition, the EMT-based prognosis prediction in lung cancer still lacks investigation. Here, we established the methodology of identifying critical metastasis-related lncRNAs using comprehensive datasets of cancer transcriptome, genome and epigenome, and also provided tools for prognosis prediction in lung cancer. Initially, important mesenchymal marker genes were identified to compose the tumor mesenchymal score, which predicted patient prognosis in lung cancer, especially lung adenocarcinoma (LUAD). The score was also correlated with several crucial biological and physiological processes, such as tumor immune and hypoxia. Based on the score, lung cancer patients was classified into epithelial and mesenchymal subtypes, and lncRNAs which exhibited expressional dysregulation, promotor methylation alteration and copy number variation between the two subtypes in LUAD were identified and underwent further prognostic analyses. Finally, we identified 14 lncRNAs as EMT-related and significant biomarkers in prognosis prediction of LUAD. As validation, lncRNA RBPMS-AS1 was proven to be co-expressed with epithelial biomarkers, suppressive for A549 cell migration, invasion and EMT, and also significantly associated with better outcomes of LUAD patients, suggesting the potential of RBPMS-AS1 to serve as a lncRNA epithelial biomarker in metastasis of LUAD. Based on the identified lncRNAs, an EMT-linked lncRNA prognostic signature was further established. Taken together, our study provides robust predictive tools, potential lncRNA targets and feasible screening strategies for future study of lung cancer metastasis.

Functional regulations between genetic alteration-driven genes and drug target genes acting as prognostic biomarkers in breast cancer

Differences in genetic molecular features including mutation, copy number alterations and DNA methylation, can explain interindividual variability in response to anti-cancer drugs in cancer patients. However, identifying genetic alteration-driven genes and characterizing their functional mechanisms in different cancer types are still major challenges for cancer studies. Here, we systematically identified functional regulations between genetic alteration-driven genes and drug target genes and their potential prognostic roles in breast cancer. We identified two mutation and copy number-driven gene pairs (PARP1-ACSL1 and PARP1-SRD5A3), three DNA methylation-driven gene pairs (PRLR-CDKN1C, PRLR-PODXL2 and PRLR-SRD5A3), six gene pairs between mutation-driven genes and drug target genes (SLC19A1-SLC47A2, SLC19A1-SRD5A3, AKR1C3-SLC19A1, ABCB1-SRD5A3, NR3C2-SRD5A3 and AKR1C3-SRD5A3), and four copy number-driven gene pairs (ADIPOR2-SRD5A3, CASP12-SRD5A3, SLC39A11-SRD5A3 and GALNT2-SRD5A3) that all served as prognostic biomarkers of breast cancer. In particular, RARP1 was found to be upregulated by simultaneous copy number amplification and gene mutation. Copy number deletion and downregulated expression of ACSL1 and upregulation of SRD5A3 both were observed in breast cancers. Moreover, copy number deletion of ACSL1 was associated with increased resistance to PARP inhibitors. PARP1-ACSL1 pair significantly correlated with poor overall survival in breast cancer owing to the suppression of the MAPK, mTOR and NF-kB signaling pathways, which induces apoptosis, autophagy and prevents inflammatory processes. Loss of SRD5A3 expression was also associated with increased sensitivity to PARP inhibitors. The PARP1-SRD5A3 pair significantly correlated with poor overall survival in breast cancer through regulating androgen receptors to induce cell proliferation. These results demonstrate that genetic alteration-driven gene pairs might serve as potential biomarkers for the prognosis of breast cancer and facilitate the identification of combination therapeutic targets for breast cancers.

Immunoprognostic model of lung adenocarcinoma and screening of sensitive drugs

Screening of mRNAs and lncRNAs associated with prognosis and immunity of lung adenocarcinoma (LUAD) and used to construct a prognostic risk scoring model (PRS-model) for LUAD. To analyze the differences in tumor immune microenvironment between distinct risk groups of LUAD based on the model classification. The CMap database was also used to screen potential therapeutic compounds for LUAD based on the differential genes between distinct risk groups. he data from the Cancer Genome Atlas (TCGA) database. We divided the transcriptome data into a mRNA subset and a lncRNA subset, and use multiple methods to extract mRNAs and lncRNAs associated with immunity and prognosis. We further integrated the mRNA and lncRNA subsets and the corresponding clinical information, randomly divided them into training and test set according to the ratio of 5:5. Then, we performed the Cox risk proportional analysis and cross-validation on the training set to construct a LUAD risk scoring model. Based on the risk scoring model, patients were divided into distinct risk group. Moreover, we evaluate the prognostic performance of the model from the aspects of Area Under Curve (AUC) analysis, survival difference analysis, and independent prognostic analysis. We analyzed the differences in the expression of immune cells between the distinct risk groups, and also discuss the connection between immune cells and patient survival. Finally, we screened the potential therapeutic compounds of LUAD in the Connectivity Map (CMap) database based on differential gene expression profiles, and verified the compound activity by cytostatic assays. We extracted 26 mRNAs and 74 lncRNAs related to prognosis and immunity by using different screening methods. Two mRNAs (i.e., KLRC3 and RAET1E) and two lncRNAs (i.e., AL590226.1 and LINC00941) and their risk coefficients were finally used to construct the PRS-model. The risk score positions of the training and test set were 1.01056590 and 1.00925190, respectively. The expression of mRNAs involved in model construction differed significantly between the distinct risk population. The one-year ROC areas on the training and test sets were 0.735 and 0.681. There was a significant difference in the survival rate of the two groups of patients. The PRS-model had independent predictive capabilities in both training and test sets. Among them, in the group with low expression of M1 macrophages and resting NK cells, LUAD patients survived longer. In contrast, the monocyte expression up-regulated group survived longer. In the CMap drug screening, three LUAD therapeutic compounds, such as resveratrol, methotrexate, and phenoxybenzamine, scored the highest. In addition, these compounds had significant inhibitory effects on the LUAD A549 cell lines. The LUAD risk score model constructed using the expression of KLRC3, RAET1E, AL590226.1, LINC00941 and their risk coefficients had a good independent prognostic power. The optimal LUAD therapeutic compounds screened in the CMap database: resveratrol, methotrexate and phenoxybenzamine, all showed significant inhibitory effects on LUAD A549 cell lines.

Identification of Fatty Acid Metabolism-Related lncRNAs as Biomarkers for Clinical Prognosis and Immunotherapy Response in Patients With Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most common malignant tumors with poor prognosis. Fatty acid metabolism is associated with cancer progression and a poor prognosis. We searched for long noncoding RNAs (lncRNAs) associated with fatty acid metabolism to predict the overall survival (OS) of patients with LUAD. We obtained lncRNA expression profiles and clinical follow-up data related to fatty acid metabolism in patients with LUAD from The Cancer Genome Atlas and Molecular Signatures database. Patients were randomly divided into training, experimental, and combination groups. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression models were used to construct fatty acid metabolism-related prognostic markers, Kaplan-Meier analysis was used to compare the prognosis of each group, and receiver operating characteristic (ROC) analysis was used to evaluate the accuracy of the prognostic model. We used the pRRophetic algorithm to assess the treatment response based on the half-maximal inhibitory concentration (IC50) of each sample in the Genomics of Cancer Drug Sensitivity (GDSC) database. A fatty acid metabolism-related prognostic marker containing seven lncRNAs was constructed to predict OS in LUAD. In the training, test and combination groups, the patients were divided into high- and low-risk groups according to a formula. K–M analysis showed that patients in the high-risk group had poorer prognosis, with significant differences in the subgroup analysis. ROC analysis showed that the predictive ability of the model was more accurate. A clinical prediction nomogram combining lncRNA and clinical features was constructed to accurately predict OS and had high clinical application value. Therapeutics were screened based on the IC50 values of each sample in the GDSC database. We found that A.443654, AUY922, AZ628, A.770041, AZD.0530, AMG.706, and AG.014699 were more effective in high-risk patients. We constructed a 7-lncRNA prognostic model to predict the OS of patients with LUAD. In addition, the predictive nomogram model based on our established seven fatty acid metabolism-related lncRNA signatures provides better clinical value than that of the traditional TNM staging system in predicting the prognosis of patients with LUAD and presents new insights for personalized treatment.

Testing lncRNAs signature as clinical stage–related prognostic markers in gastric cancer progression using TCGA database

LncRNA expression can be conducive to gastric cancer (GC) prognosis. The objective of this study is to ascertain five specific lncRNAs involved in tumor progression of GC and their role as prognostic markers to diagnose clinical stage-wise GC. High-throughput RNA sequencing data were obtained from The Cancer Genome Atlas (TCGA) database and performed genome-wide lncRNA expression analysis using edgeR package, Bioconductor.org , and R-statistical computing to analyze differentially expressed lncRNA analysis. Cutoff parameters were FDR < 0.05 and |Log2FC| > 2. Total 351 tumor samples with differentially expressed lncRNAs were divided into group-1 lncRNAs such as AC019117.2 and LINC00941, and group-2 lncRNAs such as LINC02410, AC012317.2, and AC141273.1 by 2:1. The Spearman correlation coefficients ( p < 0.05) and correlation test function (cor.test ()) were performed for lncRNAs as per clinical stage. Cytoscape software was used to construct lncRNA–mRNA interaction networks. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway ( p < 0.05) analysis were conducted using the clusterProfiler package. Kaplan–Meier survival analysis was performed to determine the overall survival of patients based on the expression of five lncRNAs in different clinical stages of GC. AC019117.2 and LINC00941 of group 1 inferred a positive correlation with clinical stages of stage I to stage IV, and their expressions were higher in tumor tissues than normal tissues. On the contrary, LINC02410, AC012317.2, and AC141273.1 of group 2 exhibited a negative correlation with clinical stage, and they exhibited more expression in normal tissues compared to tumor tissues. GO and KEGG pathway analysis reported that AC019117.2 may interact with LINC00941 via ITGA3 and trophoblast glycoprotein (TPBG) to foster tumor progression. Tumor-specific group-1 lncRNAs were conducive to the poor overall survival and exhibited a positive correlation with the clinical stages of stage I to stage IV in GC as per the lncRNA–mRNA networking analysis. These five lncRNAs could be considered as clinically useful lncRNA-based prognostic markers to predict clinical stage-wise GC progression.

Identification of a 7-miRNA signature for predicting the prognosis of patients with lung adenocarcinoma

The role of microRNAs (miRNAs) in tumor diagnosis and patients’ prognosis has recently gained extensive research attention. This study was designed to analyze miRNA in lung adenocarcinoma (LUAD) using bioinformatics analysis and to identify novel biomarkers to predict overall survival (OS) for LUAD patients. Differential miRNA expression analysis was performed on LUAD, and normal tissues were extracted from The Cancer Genome Atlas (TCGA). Univariate Cox risk regression and least absolute shrinkage and selection operator (LASSO) Cox analysis were used to screen prognostic miRNAs and develop a risk score model. The prognostic performance of the system was examined utilizing the Kaplan–Meier and receiver operating characteristic (ROC) curves. Independent prognostic factors of LUAD were determined by multivariate Cox regression analysis. Nomogram was constructed according to the independent prognostic factors to evaluate the patients’ one-, three- and five-year OS. A 7-miRNA signature based on miR-584-5p, miR-31-3p, miR-490-3, miR-4661-5p, miR-30e-5p, miR-582-5p, and miR-148a-3p was established. To categorize patients into high- and low-risk groups, the risk score was computed. The OS of the low-risk group was significantly longer than the high-risk group, and the signature showed high sensitivity and specificity in anticipating the one-, three- and five-year OS. The system was an independent factor in predicting the OS of LUAD patients and performed better when combined with the N stage in nomogram. A 7-miRNA signature developed in this study could accurately predict LUAD survival.

Long Noncoding RNA LINC00941 Promotes Cell Proliferation and Invasion by Interacting with hnRNPK in Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) is a prevalent carcinoma of the head, neck and mouth. Recently studies involving the role of long noncoding RNAs (lncRNAs) that play key regulatory roles in altering gene expression has been reported in the context of promoting tumorigenesis. However, the functions of lncRNAs in the context of oral squamous cell carcinoma have not been extensively described. In this study, we report a never identified before lncRNA, LINC00941, which was highly expressed in OSCC tissues and cells. Expression of LINC00941 promoted cell proliferation, migration, invasion, and metastasis of OSCC cells In Vitro by inducing epithelial-mesenchymal transition (EMT) and activating the Wnt/β-catenin signaling cascade. In silico analyses revealed heterogeneous nuclear ribonucleoprotein K (hnRNPK) to be a strong positive regulator of LINC00941 activity. Experimental verification of this association revealed a direct interaction of LINC00941 and hnRNPK to induce cell growth and invasion by activating EMT in OSCC cells. Therefore, our study reports that LINC00941 promotes progression of OSCC by its interaction with hnRNPK, and it may present a promising strategy for diagnosis and treatment of OSCC.

Immune-Related lncRNA Pairs as Prognostic Signature and Immune-Landscape Predictor in Lung Adenocarcinoma

BACKGROUND

Suppressive tumor microenvironment is closely related to the progression and poor prognosis of lung adenocarcinoma (LUAD). Novel individual and universal immune-related biomarkers to predict the prognosis and immune landscape of LUAD patients are urgently needed. Two-gene pairing patterns could integrate and utilize various gene expression data.

METHODS

The RNA-seq and relevant clinicopathological data of the LUAD project from the TCGA and well-known immune-related genes list from the ImmPort database were obtained. Co-expression analysis followed by an analysis of variance was performed to identify differentially expressed immune-related lncRNA (irlncRNA) (DEirlncRNA) between tumor and normal tissues. Two arbitrary DEirlncRNAs (DEirlncRNAs pair) in a tumor sample underwent pairwise comparison to generate a score (0 or 1). Next, Univariate analysis, Lasso regression and Multivariate analysis were used to screen survival-related DEirlncRNAs pairs and construct a prognostic model. The Acak information standard (AIC) values of the receiver operating characteristic (ROC) curve for 3 years are calculated to determine the cut-off point for high- or low-risk score. Finally, we evaluated the relationship between the risk score and overall survival, clinicopathological features, immune landscape, and chemotherapy efficacy.

RESULTS

Data of 54 normal and 497 tumor samples of LUAD were enrolled. After a strict screening process, 15 survival-independent-related DEirlncRNA pairs were integrated to construct a prognostic model. The AUC value of the 3-year ROC curve was 0.828. Kaplan-Meier analysis showed that patients with low risk lived longer than patients with high risk (p <0.001). Univariate and Multivariate Cox analysis suggested that the risk score was an independent factor of survival. The risk score was negatively associated with most tumor-infiltrating immune cells, immune score, and microenvironment scores. The low-risk group was correlated with increased expression of ICOS. The high-risk group had a connection with lower half inhibitory centration (IC50) of most chemotherapy drugs (e.g., etoposide, paclitaxel, vinorelbine, gemcitabine, and docetaxel) and targeted medicine-erlotinib, but with higher IC50 of methotrexate.

CONCLUSION

The established irlncRNA pairs-based model is a promising prognostic signature for LUAD patients. Furthermore, the prognostic signature has great potential in the evaluation of tumor immune landscape and guiding individualized treatment regimens.

Development and Validation of a Novel Hypoxia-Related Long Noncoding RNA Model With Regard to Prognosis and Immune Features in Breast Cancer

Background: Female breast cancer is currently the most frequently diagnosed cancer in the world. This study aimed to develop and validate a novel hypoxia-related long noncoding RNA (HRL) prognostic model for predicting the overall survival (OS) of patients with breast cancer. Methods: The gene expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. A total of 200 hypoxia-related mRNAs were obtained from the Molecular Signatures Database. The co-expression analysis between differentially expressed hypoxia-related mRNAs and lncRNAs based on Spearman's rank correlation was performed to screen out 166 HRLs. Based on univariate Cox regression and least absolute shrinkage and selection operator Cox regression analysis in the training set, we filtered out 12 optimal prognostic hypoxia-related lncRNAs (PHRLs) to develop a prognostic model. Kaplan-Meier survival analysis, receiver operating characteristic curves, area under the curve, and univariate and multivariate Cox regression analyses were used to test the predictive ability of the risk model in the training, testing, and total sets. Results: A 12-HRL prognostic model was developed to predict the survival outcome of patients with breast cancer. Patients in the high-risk group had significantly shorter median OS, DFS (disease-free survival), and predicted lower chemosensitivity (paclitaxel, docetaxel) compared with those in the low-risk group. Also, the risk score based on the expression of the 12 HRLs acted as an independent prognostic factor. The immune cell infiltration analysis revealed that the immune scores of patients in the high-risk group were lower than those of the patients in the low-risk group. RT-qPCR assays were conducted to verify the expression of the 12 PHRLs in breast cancer tissues and cell lines. Conclusion: Our study uncovered dozens of potential prognostic biomarkers and therapeutic targets related to the hypoxia signaling pathway in breast cancer.

Development and Validation of Lactate Metabolism-Related lncRNA Signature as a Prognostic Model for Lung Adenocarcinoma

BACKGROUND

Lung cancer has been a prominent research focus in recent years due to its role in cancer-related fatalities globally, with lung adenocarcinoma (LUAD) being the most prevalent histological form. Nonetheless, no signature of lactate metabolism-related long non-coding RNAs (LMR-lncRNAs) has been developed for patients with LUAD. Accordingly, we aimed to develop a unique LMR-lncRNA signature to determine the prognosis of patients with LUAD.

METHOD

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to derive the lncRNA expression patterns. Identification of LMR-lncRNAs was accomplished by analyzing the co-expression patterns between lncRNAs and LMR genes. Subsequently, the association between lncRNA levels and survival outcomes was determined to develop an effective signature. In the TCGA cohort, Cox regression was enlisted to build an innovative signature consisting of three LMR-lncRNAs, which was validated in the GEO validation cohort. GSEA and immune infiltration analysis were conducted to investigate the functional annotation of the signature and the function of each type of immune cell.

RESULTS

Fourteen differentially expressed LMR-lncRNAs were strongly correlated with the prognosis of patients with LUAD and collectively formed a new LMR-lncRNA signature. The patients could be categorized into two cohorts based on their LMR-lncRNA signatures: a low-risk and high-risk group. The overall survival of patients with LUAD in the high-risk group was considerably lower than those in the low-risk group. Using Cox regression, this signature was shown to have substantial potential as an independent prognostic factor, which was further confirmed in the GEO cohort. Moreover, the signature could anticipate survival across different groups based on stage, age, and gender, among other variables. This signature also correlated with immune cell infiltration (including B cells, neutrophils, CD4⁺ T cells, CD8⁺ T cells, etc.) as well as the immune checkpoint blockade target CTLA-4.

CONCLUSION

We developed and verified a new LMR-lncRNA signature useful for anticipating the survival of patients with LUAD. This signature could give potentially critical insight for immunotherapy interventions in patients with LUAD.

LINC00941 promotes glycolysis in pancreatic cancer by modulating the Hippo pathway

Pancreatic ductal adenocarcinoma (PDAC) is one of most lethal cancers and is projected to be the second leading cause of cancer deaths in the United States by 2030. The lack of effective treatment and increased incidence in PDAC encourage a deeper knowledge of PDAC progression. By analyzing a long noncoding RNA (lncRNA) dataset, we found that increased LINC00941 expression led to poor outcomes in PDAC patients. Furthermore, in vitro and in vivo experiments revealed that LINC00941 promoted PDAC cancer cell growth by enhancing aerobic glycolysis. Mechanistically, LINC00941 was found to interact with mammalian STE20-like protein kinase 1 (MST1), which facilitated the protein phosphatase 2A (PP2A)-mediated dephosphorylation of MST1, resulting in Hippo pathway activation and consequently, enhanced glycolysis in PDAC. These results suggest that LINC00941 plays a key role in regulating PDAC tumorigenesis, potentially highlighting novel avenues for PDAC therapy.

LncRNA RBPMS-AS1 promotes NRGN transcription to enhance the radiosensitivity of glioblastoma through the microRNA-301a-3p/CAMTA1 axis

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RBPMS-AS1 and CAMTA1 are lowly expressed in GBM patients.

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RBPMS-AS1 and CAMTA1 enhance the radiosensitivity of GBM.

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miR-301a-3p diminishes the radiosensitivity of GBM.

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RBPMS-AS1 enhances CAMTA1 expression in GBM cells through sponging miR-301a-3p.

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CAMTA1 promotes NRGN transcription.

Objective

Glioblastoma (GBM) is the most frequent brain malignancy with high incidence, and long noncoding RNAs (lncRNAs) exerts functions in GBM. In this research, we focused on the capabilities of lncRNA RBPMS-AS1 in radiosensitivity of GBM.

Methods

RBPMS-AS1 and CAMTA1 expression levels were determined in GBM tissues and cells. StarBase v3.0 database was searched for predicting miRNAs that simultaneously bound to RBPMS-AS1 and CAMTA1. pcDNA3.1-RBPMS-AS1, pcDNA3.1-CAMTA1, miR-301a-3p mimic, or pcDNA3.1-RBPMS-AS1/pcDNA3.1-CAMTA1 and miR-301a-3p mimic were transfected into GBM cells to test radiosensitivity, cell proliferation and apoptosis. The interactions of miR-301a-3p with RBPMS-AS1 and CAMTA1, as well as CAMTA1 and NRGN, were confirmed. In vivo imaging technology was utilized to detect tumor growth in orthotopic xenograft tumors, and Ki67 expression was tested in intracranial tumors.

Results

RBPMS-AS1 and CAMTA1 levels were reduced in GBM tissues and cells. miR-301a-3p had a binding site with both RBPMS-AS1 and CAMTA1 and it was the most significantly-upregulated one. Upregulation of RBPMS-AS1 or CAMTA1 enhanced the radiosensitivity and cell apoptosis while suppressing proliferation of GBM cells. Conversely, miR-301a-3p overexpression diminished the radiosensitivity and cell apoptosis while inducing proliferation of GBM cells. Overexpression of RBPMS-AS1 or CAMTA1 reversed the effects of overexpressed miR-301a-3p in GBM cells. Mechanistically, RBPMS-AS1 enhanced CAMTA1 expression in GBM cells through sponging miR-301a-3p, and CAMTA1 promoted NRGN expression. In animal experiments, overexpressed RBPMS-AS1 inhibited tumor growth and the positive expression of Ki67 both before and after radiation therapy.

Conclusion

RBPMS-AS1 promotes NRGN transcription through the miR-301a-3p/CAMTA1 axis and enhances the radiosensitivity of GBM.

Cell-free DNA 5-hydroxymethylcytosine profiles of long non-coding RNA genes enable early detection and progression monitoring of human cancers

BACKGROUND

5-Hydroxymethylcytosine (5hmC) is a significant DNA epigenetic modification. However, the 5hmC modification alterations in genomic regions encoding long non-coding RNA (lncRNA) and their clinical significance remain poorly characterized.

RESULTS

A three-phase discovery-modeling-validation study was conducted to explore the potential of the plasma-derived 5hmC modification level in genomic regions encoding lncRNAs as a superior alternative biomarker for cancer diagnosis and surveillance. Genome-wide 5hmC profiles in the plasma circulating cell-free DNA of 1632 cancer and 1379 non-cancerous control samples from different cancer types and multiple centers were repurposed and characterized. A large number of altered 5hmC modifications were distributed at genomic regions encoding lncRNAs in cancerous compared with healthy subjects. Furthermore, most 5hmC-modified lncRNA genes were cancer-specific, with only a relatively small number of 5hmC-modified lncRNA genes shared by various cancer types. A 5hmC-LncRNA diagnostic score (5hLD-score) comprising 39 tissue-shared 5hmC-modified lncRNA gene markers was developed using elastic net regularization. The 5hLD-score was able to accurately distinguish tumors from healthy controls with an area under the curve (AUC) of 0.963 [95% confidence interval (CI) 0.940-0.985] and 0.912 (95% CI 0.837-0.987) in the training and internal validation cohorts, respectively. Results from three independent validations confirmed the robustness and stability of the 5hLD-score with an AUC of 0.851 (95% CI 0.786-0.916) in Zhang's non-small cell lung cancer cohort, AUC of 0.887 (95% CI 0.852-0.922) in Tian's esophageal cancer cohort, and AUC of 0.768 (95% CI 0.746-0.790) in Cai's hepatocellular carcinoma cohort. In addition, a significant association was identified between the 5hLD-score and the progression from hepatitis to liver cancer. Finally, lncRNA genes modified by tissue-specific 5hmC alteration were again found to be capable of identifying the origin and location of tumors.

CONCLUSION

The present study will contribute to the ongoing effort to understand the transcriptional programs of lncRNA genes, as well as facilitate the development of novel invasive genomic tools for early cancer detection and surveillance.

Screening of Significant Biomarkers Related to Prognosis of Cervical Cancer and Functional Study Based on lncRNA-associated ceRNA Regulatory Network

BACKGROUND

Cervical cancer (CESC), which threatens the health of women, has a very high recurrence rate.

PURPOSES

This study aimed to identify the signature long non-coding RNAs (lncRNAs) associated with the prognosis of CESC and predict the prognostic survival rate with the clinical risk factors.

METHODS

The CESC gene expression profiling data were downloaded from TCGA database and NCBI Gene Expression Omnibus. Afterwards, the differentially expressed RNAs (DERs) were screened using limma package of R software. R package "survival" was then used to screen the signature lncRNAs associated with independently recurrence prognosis, and a nomogram recurrence rate model based on these signature lncRNAs was constructed to predict the 3-year and 5-year survival probability of CESC. Finally, a competing endogenous RNAs (ceRNA) regulatory network was proposed to study the functions of these genes.

RESULTS

We obtained 305 DERs significantly associated with prognosis. Afterwards, a risk score (RS) prediction model was established using the screened 5 signature lncRNAs associated with independently recurrence prognosis (DLEU1, LINC01119, RBPMS-AS1, RAD21-AS1 and LINC00323). Subsequently, a nomogram recurrence rate model, proposed with Pathologic N and RS model status, was found to have a good prediction ability for CESC. In ceRNA regulatory network, LINC00323 and DLEU1 were hub nodes which targeted more miRNAs and mRNAs. After that, 15 GO terms and 3 KEGG pathways were associated with recurrence prognosis and showed that the targeted genes PTK2, NRP1, PRKAA1 and HMGCS1 might influence the prognosis of CESC.

CONCLUSION

The signature lncRNAs can help improve our understanding of the development and recurrence of CESC and the nomogram recurrence rate model can be applied to predict the survival rate of CESC patients in clinical practice.

Upregulation of Linc00284 Promotes Lung Cancer Progression by Regulating the miR-205-3p/c-Met Axis

Lung cancer (LC) is a malignant tumor with the highest incidence and mortality rates worldwide. Linc00284, a long non-coding RNA, is a newly discovered regulator of LC. This study aimed to explore the role of Linc00284 in LC progression. Gene expression levels were detected by RT-qPCR and/or western blot analysis. Cell migratory and invasive capabilities were measured by wound healing and transwell assays. Subcutaneous xenograft models were constructed to examine tumor growth of LC cells. Data showed that Linc00284 was significantly upregulated in LC tissues compared to adjacent normal lung tissues and predicted poor prognosis in patients with LC. In vitro, Linc00284 was highly expressed in LC cells and was mainly localized in the cytoplasm. Mechanistically, Linc00284 directly bound to miR-205-3p, leading to the upregulation of c-Met expression. A significant negative correlation was observed between Linc00284 and miR-205-3p expression levels, and the Linc00284 level was positively correlated with the c-Met expression. Linc00284/miR-205-3p/c-Met regulatory axis promotes LC cell proliferation, migration, and invasion. Furthermore, the in vivo results indicated that Linc00284 knockdown markedly suppressed tumor growth. Taken together, these data suggest that Linc00284 facilitates LC progression by targeting the miR-205-3p/c-Met axis, which may be a potential target for LC treatment.

Construction of an immune-related lncRNA signature as a novel prognosis biomarker for LUAD

The tumor immune microenvironment of lung cancer is associated with prognosis and immunotherapy efficacy. Long noncoding RNAs are identified as prognostic biomarkers associated with immune functions. We constructed a signature comprising differentially expressed immune-related lncRNAs to predict the prognosis of patients with lung adenocarcinoma. We established the immune-related lncRNA signature by pairing immune-related lncRNAs regardless of expression level and lung adenocarcinoma patients were divided into high- and low-risk groups. The prognosis of patients in the two groups was significantly different; The immune-related lncRNA signature could serve as an independent lung adenocarcinoma prognostic indicator. The signature correlated negatively with B cell, CD4+ T cell, M2 macrophage, neutrophil, and monocyte immune infiltration. Patients with low risk scores had a higher abundance of immune cells and stromal cells around the tumor. Gene set enrichment analysis showed that samples from low-risk group were more active in the IgA production in intestinal immune network and the T and B cell receptor signaling pathway. High-risk groups had significant involvement of the cell cycle, DNA replication, adherens junction, actin cytoskeleton regulation, pathways in cancer, and TGF-β signaling pathways. High risk scores correlated significantly negatively with high CTLA-4 and HAVCR2 expression and higher median inhibitory concentration of common anti-tumor chemotherapeutics (e.g., cisplatin, paclitaxel, gemcitabine) and targeted therapy (e.g., erlotinib and gefitinib). We identified a reliable immune-related lncRNA lung adenocarcinoma prognosis model, and the immune-related lncRNA signature showed promising clinical prediction value.

A novel prognostic signature of immune-related lncRNA pairs in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, but the prognosis of LUAD patients remains unsatisfactory. Here, we retrieved the RNA-seq data of LUAD cohort from The Cancer Genome Atlas (TCGA) database and then identified differentially expressed immune-related lncRNAs (DEirlncRNAs) between LUAD and normal controls. Based on a new method of cyclically single pairing along with a 0-or-1 matrix, we constructed a novel prognostic signature of 8 DEirlncRNA pairs in LUAD with no dependence upon specific expression levels of lncRNAs. This prognostic model exhibited significant power in distinguishing good or poor prognosis of LUAD patients and the values of the area under the curve (AUC) were all over 0.70 in 1, 3, 5 years receiver operating characteristic (ROC) curves. Moreover, the risk score of the model could serve as an independent prognostic factor for patients with LUAD. In addition, the risk model was significantly associated with clinicopathological characteristics, tumor-infiltrating immune cells, immune-related molecules and sensitivity of anti-tumor drugs. This novel signature of DEirlncRNA pairs in LUAD, which did not require specific expression levels of lncRNAs, might be used to guide the administration of patients with LUAD in clinical practice.

Linc00941 regulates esophageal squamous cell carcinoma via functioning as a competing endogenous RNA for miR-877-3p to modulate PMEPA1 expression

Esophageal squamous cell carcinoma (ESCC) represents one of the most common malignancies and is the fifth leading cause of cancer-related deaths. Long intergenic non-coding RNAs (lincRNAs) have been suggested to be dysregulated in various types of cancers, and a growing number of lincRNAs have been implicated to be functional in the ESCC progression. In this study, we examined the role of linc00941 in the ESCC progression and explored the underlying molecular mechanisms. The bioinformatics analysis identified the up-regulation of linc00941 in the ESCC tissues. Further in vitro studies showed that linc00941 was up-regulated in ESCC cell lines. The loss-of-function studies demonstrated that linc00941 knockdown suppressed ESCC cell proliferation, invasion and migration, and also suppressed the in vivo tumor growth. Furthermore, bioinformatics prediction along with luciferase reporter assay and RNA immunoprecipitation assay implied that linc00941 acted as a competing endogenous RNA for miR-877-3p, and linc00941 regulated ESCC cell progression via at least targeting miR-877-3p. Subsequently, miR-877-3p targeted prostate transmembrane protein, androgen induced 1 (PMEPA1) 3' untranslated region and repressed PMEPA1 expression in ESCC cells; overexpression of PMEPA1 attenuated the inhibitory effects of linc00941 knockdown on the ESCC cell progression. Linc00941 knockdown suppressed epithelial-mesenchymal transition (EMT) via targeting miR-877-3p/PMEPA1 axis in ESCC cells. In conclusion, our results indicated the oncogenic role of linc00941 in ESCC, and knockdown of linc00941 suppressed ESCC cell proliferation, invasion, migration and EMT via interacting with miR-877-3p/PMEPA1 axis.

MIR99AHG is a noncoding tumor suppressor gene in lung adenocarcinoma

Little is known about noncoding tumor suppressor genes. An effective way to identify these genes is by analyzing somatic copy number variation (CNV)-related noncoding genes. By integrated bioinformatics analyses of differentially expressed long noncoding RNAs (lncRNAs) and arm-level CNVs in lung adenocarcinoma (LUAD), we identified a potential antitumor gene, MIR99AHG, encoding lncRNA MIR99AHG as well as a miR-99a/let-7c/miR-125b2 cluster on chromosome 21q. All four of these transcripts were downregulated in LUAD tissues partly due to the copy number deletion of the MIR99AHG gene. Both MIR99AHG and miR-99a expression was positively correlated with the survival of LUAD patients. MIR99AHG suppressed proliferation and metastasis and promoted autophagy both in vitro and in vivo. Mechanistically, the interaction between MIR99AHG and ANXA2 could accelerate the ANXA2-induced ATG16L+ vesicle biogenesis, thus promoting phagophore assembly. Additionally, miR-99a targeted a well-known autophagy suppressor, mammalian target of rapamycin (mTOR), thereby synergistically promoting autophagy and postponing LUAD progression with MIR99AHG. In summary, MIR99AHG emerges as a noncoding tumor suppressor gene in LUAD, providing a new strategy for antitumor therapy.

Identification of prognostic marker genes in head and neck squamous cell carcinoma: A study based on The Cancer Genome Atlas database and experimental validation

BACKGROUND

Early detection and prognostic prediction are crucial in improving the survival of patients with head and neck squamous cell carcinoma (HNSCC). Therefore, we provided potential molecular markers in this study for early diagnosis and prognosis of this cancer based on The Cancer Genome Atlas (TCGA) database analysis and experimental validations.

METHODS

Differentially expressed genes (DEGs) between HNSCC tumor and normal samples were identified by TCGA database-based analyses. Univariate and multivariate Cox regression analyses were applied, respectively, to identify survival-related DEGs and independent prognostic factors in HNSCC. Further, RT-qPCR was employed to verify expression of DEGs in cancer and adjacent tissues from HNSCC patients recruited in our hospital, in which we also clarified the correlation between candidate genes and clinicopathological characteristics and prognosis of HNSCC patients.

RESULTS

TCGA data analyses yielded 59 DEGs. Cox analyses identified 13 candidate genes closely related to prognosis of HNSCC patients and established a five-gene signature comprising AC103702.2, LINC00941, RPL29, FOXL2, and CCL11. This five-gene signature could classify patients into high- and low-risk groups. The survival rate of the high-risk group was significantly lower than that of the low-risk group. Clinical tissue experiments further confirmed that AC103702.2, LINC00941, CCL11, and RPL29P19 genes were inversely associated with the prognosis of HNSCC patients, while CCL11 gene was positively associated. We also found that high-risk HNSCC patients presented a higher incidence of lymph node metastasis.

CONCLUSION

Five prognostic marker genes (AC103702.2, LINC00941, CCL11, RPL29P19, and FOXL2) as a gene cluster may serve as prognostic marker genes in HNSCC.

LINC00941 Promotes Progression of Non-Small Cell Lung Cancer by Sponging miR-877-3p to Regulate VEGFA Expression

Long noncoding RNAs (lncRNAs) play critical roles in carcinoma occurrence and metastasis. LINC00941 has been found to mediate the development of gastric cancer, and LINC00941 was negatively associated with the longer overall survival of lung adenocarcinoma patients. Herein, our aim was to investigate the effects and mechanisms of LINC00941 in NSCLC progression. Microarray was used to identify the change lncRNAs in NSCLC, LINC00941 was found to increase in tumor tissues and patients' plasma. Knockdown of LINC00941 didn't modulate the proliferation of NSCLC cells, but inhibition of LINC00941 in NSCLC cells suppressed the angiogenesis ability of human umbilical vein endothelial cells (HUVECs). Moreover, LINC00941 promoted tumorigenesis in vivo, while si-LINC00941 inhibited tumor development of NSCLC. VEGFA was should to be significantly modulated by LINC00941 in NSCLC cells, then luciferase assay proved that LINC00941 regulated VEGFA expression via interacting with miR-877-3p. Followed functional experiments indicated that overexpression of LINC00941 accelerated angiogenesis and NSCLC tumor progression via miR-877-3p/VEGFA axis both in vitro and in vivo. In conclusion, our results clarified the LINC00941 function for the first time, and LINC00941 promoted the progression of NSCLC, which was mediated by miR-877-3p/VEGFA axis. This study might provide new understanding and targets for NSCLC diagnosis and treatment.

Comprehensive Profiling of Genomic and Transcriptomic Differences between Risk Groups of Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

Lung cancer is the second most frequently diagnosed cancer type and responsible for the highest number of cancer deaths worldwide. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are subtypes of non-small-cell lung cancer which has the highest frequency of lung cancer cases. We aimed to analyze genomic and transcriptomic variations including simple nucleotide variations (SNVs), copy number variations (CNVs) and differential expressed genes (DEGs) in order to find key genes and pathways for diagnostic and prognostic prediction for lung adenocarcinoma and lung squamous cell carcinoma. We performed a univariate Cox model and then lasso-regularized Cox model with leave-one-out cross-validation using The Cancer Genome Atlas (TCGA) gene expression data in tumor samples. We generated 35- and 33-gene signatures for prognostic risk prediction based on the overall survival time of the patients with LUAD and LUSC, respectively. When we clustered patients into high- and low-risk groups, the survival analysis showed highly significant results with high prediction power for both training and test datasets. Then, we characterized the differences including significant SNVs, CNVs, DEGs, active subnetworks, and the pathways. We described the results for the risk groups and cancer subtypes separately to identify specific genomic alterations between both high-risk groups and cancer subtypes. Both LUAD and LUSC high-risk groups have more downregulated immune pathways and upregulated metabolic pathways. On the other hand, low-risk groups have both up- and downregulated genes on cancer-related pathways. Both LUAD and LUSC have important gene alterations such as CDKN2A and CDKN2B deletions with different frequencies. SOX2 amplification occurs in LUSC and PSMD4 amplification in LUAD. EGFR and KRAS mutations are mutually exclusive in LUAD samples. EGFR, MGA, SMARCA4, ATM, RBM10, and KDM5C genes are mutated only in LUAD but not in LUSC. CDKN2A, PTEN, and HRAS genes are mutated only in LUSC samples. The low-risk groups of both LUAD and LUSC tend to have a higher number of SNVs, CNVs, and DEGs. The signature genes and altered genes have the potential to be used as diagnostic and prognostic biomarkers for personalized oncology.

Novel lncRNA LINC00941 Promotes Proliferation and Invasion of Colon Cancer Through Activation of MYC

Purpose

We conducted the study to elucidate how LncRNA LINC00941 affects colon cancer progression and its possible regulatory mechanism.

Methods

The expression level of LINC00941 in colon cancer tissues and cells was detected by qRT-PCR. The function of LINC00941 on colon cancer cell proliferation, migration, and invasion was detected by CCK-8 and Transwell assay respectively. The target interactions among LINC00941, miR-205-5p, and MYC were further confirmed by dual-luciferase reporter gene assays and RNA pull-down experiments. Meanwhile, in vivo experiments were carried out to study the role of LINC00941 in the xenotransplantation model.

Results

LINC00941 expression level was elevated in colon cancer tissues and cells. LINC00941 overexpression accelerated proliferation, migration, and invasion of colon cancer cells, while the LINC00941 knockdown showed the opposite results. In addition, LINC00941 regulated the expression of MYC by sponging miR-205-5p as a competitive endogenous RNA, and miR-205-5p knockdown reversed the tumor inhibition of LINC00941 knockdown on colon cancer cells. Xenograft model assay confirmed that LINC00941 silencing could inhibit colon cancer cell growth and metastasis.

Conclusion

LINC00941 may markedly promote colon cancer progression by acting on the miR-205-5p/MYC axis as a ceRNA, which offers novel clues for lncRNA to guide the treatment and prognosis of colon cancer.

FAM83H-AS1 is a noncoding oncogenic driver and therapeutic target of lung adenocarcinoma

BACKGROUND

Little is known about noncoding oncogenes of lung adenocarcinoma (LUAD), and these potential drivers might provide novel therapeutic targets.

METHODS

Since abnormally overexpression of oncogenic drivers is induced by genomic variation, we here utilized genomic, transcriptomic, and clinical prognosis data of The Cancer Genome Atlas (TCGA) LUAD datasets to discover novel drivers from long noncoding RNAs. We further used zebrafish models to validate the biological function of candidates in vivo. The full length of FAM83H-AS1 was obtained by rapid amplification of the cDNA ends assay. RNA pull-down, RNA immunoprecipitation, quantitative mass spectrometry, and RNA sequencing assays were conducted to explore the potential mechanisms. Additionally, we used CRISPR interference (CRISPRi) method and patient-derived tumor xenograft (PDTX) model to evaluate the therapeutic potential of targeting FAM83H-AS1.

RESULTS

The results suggest that FAM83H-AS1 is a potential oncogenic driver due to chromosome 8q24 amplification. Upregulation of FAM83H-AS1 results in poor prognosis of LUAD patients in both Jiangsu Cancer Hospital (JSCH) and TCGA cohorts. Functional assays revealed that FAM83H-AS1 promotes malignant progression and inhibits apoptosis. Mechanistically, FAM83H-AS1 binds HNRNPK to enhance the translation of antiapoptotic oncogenes RAB8B and RAB14. Experiments using CRISPRi-mediated xenografts and PDTX models indicated that targeting FAM83H-AS1 inhibited LUAD progression in vivo.

CONCLUSIONS

Our work demonstrates that FAM83H-AS1 is a noncoding oncogenic driver that inhibits LUAD apoptosis via the FAM83H-AS1-HNRNPK-RAB8B/RAB14 axis, which highlights the importance and potential roles that FAM83H-AS1 may serve as a novel therapeutic target for LUAD.

LINC00941 promotes CRC metastasis through preventing SMAD4 protein degradation and activating the TGF-β/SMAD2/3 signaling pathway

ABSTRICT

LINC00941 is a novel lncRNA that has been found to exhibit protumorigenic and prometastatic behaviors during tumorigenesis. However, its role in metastatic CRC remains unknown. We aimed to investigate the functions and mechanisms of LINC00941 in CRC metastasis. LINC00941 was shown to be upregulated in CRC, and upregulated LINC00941 was associated with poor prognosis. Functionally, LINC00941 promoted migratory and invasive capacities and accelerated lung metastasis in nude mice. Mechanistically, LINC00941 activated EMT in CRC cells, as indicated by the increased expression of key molecular markers of cell invasion and metastasis (Vimentin, Fibronectin, and Twist1) and simultaneous decreased expression of the main invasion suppressors E-cadherin and ZO-1. LINC00941 was found to activate EMT by directly binding the SMAD4 protein MH2 domain and competing with β-TrCP to prevent SMAD4 protein degradation, thus activating the TGF-β/SMAD2/3 signaling pathway. Our data reveal the essential role of LINC00941 in metastatic CRC via activation of the TGF-β/SMAD2/3 axis, which provides new insight into the mechanism of metastatic CRC and a novel potential therapeutic target for advanced CRC.

Comprehensive landscape of epigenetic-dysregulated lncRNAs reveals a profound role of enhancers in carcinogenesis in BC subtypes

Aberrant expression of long non-coding RNAs (lncRNA) is associated with altered DNA methylation and histone modifications during carcinogenesis. However, identifying epigenetically dysregulated lncRNAs and characterizing their functional mechanisms in different cancer subtypes are still major challenges for cancer studies. In this study, we systematically analyzed the epigenetic alterations of lncRNAs at important regulatory elements in three breast cancer subtypes. We identified 87, 691, and 1,197 epigenetically dysregulated lncRNAs in luminal, basal, and claudin-low subtypes of breast cancer, respectively. The landscape of epigenetically dysregulated lncRNAs at enhancer elements revealed that epigenetic changes of the majority of lncRNAs occurred in a subtype-specific manner and contributed to subtype-specific biological functions. We identified six acetylation of lysine 27 on histone H3 (H3K27ac)-dysregulated lncRNAs and three DNA methylation-dysregulated lncRNAs (CTC-303L1.2, RP11-738B7.1, and SLC26A4-AS1) as prognostic biomarkers of basal subtype. These lncRNAs were involved in immune response-related biological functions. Treatment of the basal breast cancer cell line MDA-MB-468 with CREBBP/EP300 bromodomain inhibitors downregulated H3K27 acetylation levels and caused a decrease in the expression of five H3K27ac-dysregulated lncRNAs (LINC00393, KB-1836B5.1, RP1-140K8.5, AC005162.1, and AC020916.2) and inhibition of the growth of breast cancer cells. One epigenetically dysregulated lncRNA (LINC01983) and four lncRNA regulators (UCA1, RP11-221J22.2, RP11-221J22.1, and RP1-212P9.3) were identified as prognostic biomarkers of the luminal molecular subtype of breast cancer by controlling the tumor necrosis factor (TNF) signaling pathway, T helper (Th)17 cell differentiation, and T cell migration. Finally, our results highlighted a profound role of enhancer-related H3K27ac-dysregulated lncRNAs, DNA methylation-dysregulated lncRNAs, and lncRNA regulators in breast cancer subtype carcinogenesis and their potential prognostic value.

Immune-related lncRNAs as predictors of survival in breast cancer: a prognostic signature

Background

Breast cancer is a highly heterogeneous disease, this poses challenges for classification and management. Long non-coding RNAs play acrucial role in the breast cancersdevelopment and progression, especially in tumor-related immune processes which have become the most rapidly investigated area. Therefore, we aimed at developing an immune-related lncRNA signature to improve the prognosis prediction of breast cancer.

Methods

We obtained breast cancer patient samples and corresponding clinical data from The Cancer Genome Atlas (TCGA) database. Immune-related lncRNAs were screened by co-expression analysis of immune-related genes which were downloaded from the Immunology Database and Analysis Portal (ImmPort). Clinical patient samples were randomly separated into training and testing sets. In the training set, univariate Cox regression analysis and LASSO regression were utilized to build a prognostic immune-related lncRNA signature. The signature was validated in the training set, testing set, and whole cohorts by the Kaplan–Meier log-rank test, time-dependent ROC curve analysis, principal component analysis, univariate andmultivariate Cox regression analyses.

Results

A total of 937 immune- related lncRNAs were identified, 15 candidate immune-related lncRNAs were significantly associated with overall survival (OS). Eight of these lncRNAs (OTUD6B-AS1, AL122010.1, AC136475.2, AL161646.1, AC245297.3, LINC00578, LINC01871, AP000442.2) were selected for establishment of the risk prediction model. The OS of patients in the low-risk group was higher than that of patients in the high-risk group (p = 1.215e − 06 in the training set; p = 0.0069 in the validation set; p = 1.233e − 07 in whole cohort). The time-dependent ROC curve analysis revealed that the AUCs for OS in the first, eighth, and tenth year were 0.812, 0.81, and 0.857, respectively, in the training set, 0.615, 0.68, 0.655 in the validation set, and 0.725, 0.742, 0.741 in the total cohort. Multivariate Cox regression analysis indicated the model was a reliable and independent indicator for the prognosis of breast cancer in the training set (HR = 1.432; 95% CI 1.204–1.702, p < 0.001), validation set (HR = 1.162; 95% CI 1.004–1.345, p = 0.044), and whole set (HR = 1.240; 95% CI 1.128–1.362, p < 0.001). GSEA analysis revealed a strong connection between the signature and immune-related biological processes and pathways.

Conclusions

We constructed and verified a robust signature of 8 immune-related lncRNAs for the prediction of breast cancer patient survival.

A novel autophagy-related lncRNA prognostic risk model for breast cancer

Long non-coding RNAs (lncRNAs) are well known as crucial regulators to breast cancer development and are implicated in controlling autophagy. LncRNAs are also emerging as valuable prognostic factors for breast cancer patients. It is critical to identify autophagy-related lncRNAs with prognostic value in breast cancer. In this study, we identified autophagy-related lncRNAs in breast cancer by constructing a co-expression network of autophagy-related mRNAs-lncRNAs from The Cancer Genome Atlas (TCGA). We evaluated the prognostic value of these autophagy-related lncRNAs by univariate and multivariate Cox proportional hazards analyses and eventually obtained a prognostic risk model consisting of 11 autophagy-related lncRNAs (U62317.4, LINC01016, LINC02166, C6orf99, LINC00992, BAIAP2-DT, AC245297.3, AC090912.1, Z68871.1, LINC00578 and LINC01871). The risk model was further validated as a novel independent prognostic factor for breast cancer patients based on the calculated risk score by Kaplan-Meier analysis, univariate and multivariate Cox regression analyses and time-dependent receiver operating characteristic (ROC) curve analysis. Moreover, based on the risk model, the low-risk and high-risk groups displayed different autophagy and oncogenic statues by principal component analysis (PCA) and Gene Set Enrichment Analysis (GSEA) functional annotation. Taken together, these findings suggested that the risk model of the 11 autophagy-related lncRNAs has significant prognostic value for breast cancer and might be autophagy-related therapeutic targets in clinical practice.

LINC00941 promotes oral squamous cell carcinoma progression via activating CAPRIN2 and canonical WNT/β-catenin signaling pathway

Dysregulation of long non-coding RNAs (lncRNAs) has been implicated in many cancer developments. Previous studies showed that lncRNA LINC00941 was aberrantly expressed in oral squamous cell carcinoma (OSCC). However, its role in OSCC development remains elusive. In this study, we demonstrated that in OSCC cells, EP300 activates LINC00941 transcription through up-regulating its promoter H3K27ac modification. Up-regulated LINC00941 in turn activates CAPRIN2 expression by looping to CAPRIN2 promoter. Functional assays suggest that both LINC00941 and CAPRIN2 play pivotal roles in promoting OSCC cell proliferation and colony formation. In vivo assay further confirmed the role of LINC00941 in promoting OSCC cell tumour formation. Lastly, we showed that the role of LINC00941 and CAPRIN2 in OSCC progression was mediated through activating the canonical WNT/β-catenin signaling pathway. Thus, LINC00941/CAPRIN2/ WNT/β-catenin signaling pathway provides new therapeutic targets for OSCC treatment.

Identification and validation of stemness-related lncRNA prognostic signature for breast cancer

BACKGROUND

Long noncoding RNAs (lncRNAs) are emerging as crucial contributors to the development of breast cancer and are involved in the stemness regulation of breast cancer stem cells (BCSCs). LncRNAs are closely associated with the prognosis of breast cancer patients. It is critical to identify BCSC-related lncRNAs with prognostic value in breast cancer.

METHODS

A co-expression network of BCSC-related mRNAs-lncRNAs from The Cancer Genome Atlas (TCGA) was constructed. Univariate and multivariate Cox proportional hazards analyses were used to identify a stemness risk model with prognostic value. Kaplan-Meier analysis, univariate and multivariate Cox regression analyses and receiver operating characteristic (ROC) curve analysis were performed to validate the risk model. Principal component analysis (PCA) and Gene Set Enrichment Analysis (GSEA) functional annotation were conducted to analyze the risk model.

RESULTS

In this study, BCSC-related lncRNAs in breast cancer were identified. We evaluated the prognostic value of these BCSC-related lncRNAs and eventually obtained a prognostic risk model consisting of 12 BCSC-related lncRNAs (Z68871.1, LINC00578, AC097639.1, AP003119.3, AP001207.3, LINC00668, AL122010.1, AC245297.3, LINC01871, AP000851.2, AC022509.2 and SEMA3B-AS1). The risk model was further verified as a novel independent prognostic factor for breast cancer patients based on the calculated risk score. Moreover, based on the risk model, the low- risk and high-risk groups displayed different stemness statuses.

CONCLUSIONS

These findings suggested that the 12 BCSC-related lncRNA signature might be a promising prognostic factor for breast cancer and can promote the management of BCSC-related therapy in clinical practice.

Screening key lncRNAs with diagnostic and prognostic value for head and neck squamous cell carcinoma based on machine learning and mRNA-lncRNA co-expression network analysis

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is the seventh most common type of cancer around the world. The aim of this study was to seek the long non-coding RNAs (lncRNAs) acting as diagnostic and prognostic biomarker of HNSCC.

METHODS

Base on TCGA dataset, the differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified between HNSCC and normal tissue. The machine learning and survival analysis were performed to estimate the potential diagnostic and prognostic value of lncRNAs for HNSCC. We also build the co-expression network and functional annotation. The expression of selected candidate mRNAs and lncRNAs were validated by Quantitative real time polymerase chain reaction (qRT-PCR).

RESULTS

A total of 3363 DEmRNAs (1822 down-regulated and 1541 up-regulated mRNAs) and 32 DElncRNAs (13 down-regulated and 19 up-regulated lncRNAs) between HNSCC and normal tissue were obtained. A total of 13 lncRNAs (IL12A.AS1, RP11.159F24.6, RP11.863P13.3, LINC00941, FOXCUT, RNF144A.AS1, RP11.218E20.3, HCG22, HAGLROS, LINC01615, RP11.351J23.1, AC024592.9 and MIR9.3HG) were defined as optimal diagnostic lncRNAs biomarkers for HNSCC. The area under curve (AUC) of the support vector machine (SVM) model, decision tree model and random forests model and were 0.983, 0.842 and 0.983, and the specificity and sensitivity of the three model were 95.5% and 96.2%, 77.3% and 97.6% and 93.2% and 97.8%, respectively. Among them, AC024592.9, LINC00941, LINC01615 and MIR9-3HG was not only an optimal diagnostic lncRNAs biomarkers, but also related to survival time. The focal adhesion, ECM-receptor interaction, pathways in cancer and cytokine-cytokine receptor interaction were four significantly enriched pathways in DEmRNAs co-expressed with the identified optimal diagnostic lncRNAs. But for most of the selected DEmRNAs and DElncRNAs, the expression was consistent with our integrated analysis results, including LINC00941, LINC01615, FOXCUT, TGA6 and MMP13.

CONCLUSION

AC024592.9, LINC00941, LINC01615 and MIR9-3HG was not only an optimal diagnostic lncRNAs biomarkers, but also were a prognostic lncRNAs biomarkers.

Characterization of gene expression profiles of esophageal cancer patients with different nonsynonymous tumor mutation burden

Background

Nonsynonymous tumor mutation burden (NSTMB) could affect the prognosis of esophageal cancer (EC) patients, but differentially expressed genes between EC patients with different NSTMB have not been explored. Our study aimed to compare differentially expressed genes between EC patients with different NSTMB (high vs. low).

Methods

RNA‐seq data for EC patients were downloaded from The Cancer Genome Atlas (TCGA). The edgeR package was used to identify differentially expressed genes between patients with different NSTMB. Cell type identification by estimating relative subsets of known RNA transcripts (CIBERSORT) software was employed to underscore immune cell differences between patients with different NSTMB.

Results

In total, we discovered 2215 differentially expressed genes between patients with different NSTMB, among which 842 genes were upregulated and 1373 downregulated in patients with high NSTMB. The differentially expressed genes were enriched in pathways such as heme binding and structural molecule activity. We built a logistic model that may be used to predict patients' NSTMB. We found that tumors with high NSTMB had a significantly higher percentage of resting natural killer (NK) cells than those with low NSTMB (P = 0.028). The percentages of regulatory T (Treg) and CD8⁺ T cells were also higher in those with high NSTMB, although it was not statistically significant (P = 0.064 for Treg cells and P = 0.12 for CD8⁺ T cells).

Conclusions

NSTMB may cause changes in gene expression and immune cell infiltration in EC patients, and affect the overall survival of EC patients.

Key points

Significant findings of the study

This study found differentially expressed genes and differences in infiltration of immune cells between esophageal cancer (EC) with different NSTMB.

What this study adds

This study highlights differences between EC patients with different NSTMB.

Genome-wide copy number variation analysis identified ANO1 as a novel oncogene and prognostic biomarker in esophageal squamous cell cancer

Copy number variations (CNVs) represent one of the most common genomic alterations. This study aimed to evaluate the roles of genes within highly aberrant genome regions in the prognosis of esophageal squamous cell cancer (ESCC). Exome sequencing data from 81 paired ESCC tissues were used to screen aberrant genomic regions. The associations between CNVs and gene expression were evaluated using gene expression data from the same individuals. Then, an RNA expression array profile from 119 ESCC samples was adopted for differential gene expression and prognostic analyses. Two independent ESCC cohorts with 315 subjects were further recruited to validate the prognostic value using immunohistochemistry tests. Finally, we explored the potential mechanism of our identified novel oncogene in ESCC. In total, 2003 genes with CNVs were observed, of which 76 genes showed recurrent CNVs in more than three samples. Among them, 32 genes were aberrantly expressed in ESCC tumor tissues and statistically correlated with CNVs. Strikingly, 4 (CTTN, SHANK2, INPPL1 and ANO1) of the 32 genes were significantly associated with the prognosis of ESCC patients. Patients with a positive expression of ANO1 had a poorer prognosis than ANO1 negative patients (overall survival rate: 42.91% versus 26.22% for ANO1-/+ samples, P < 0.001). Functionally, ANO1 promoted ESCC cell proliferation, migration and invasion by activating transforming growth factor-β pathway. Knockdown of ANO1 significantly inhibited tumor progression in vitro and in vivo. In conclusion, ANO1 is a novel oncogene in ESCC and may serve as a prognostic biomarker for ESCC.