Classifying gastric cancer using FLORA reveals clinically relevant molecular subtypes and highlights LINC01614 as a biomarker for patient prognosis

Current development of molecular classifications of gastric cancer based on omics (Review)

Gastric cancer (GC) is a complex and heterogeneous disease with significant phenotypic and genetic variation. Traditional classification systems rely mainly on the evaluation of clinical pathological features and conventional biomarkers and might not capture the diverse clinical processes of individual GCs. The latest discoveries in omics technologies such as next‑generation sequencing, proteomics and metabolomics have provided crucial insights into potential genetic alterations and biological events in GC. Clustering strategies for identifying subtypes of GC might offer new tools for improving GC treatment and clinical trial outcomes by enabling the development of therapies tailored to specific subtypes. However, the feasibility and therapeutic significance of implementing molecular classifications of GC in clinical practice need to addressed. The present review examines the current molecular classifications, delineates the prevailing landscape of clinically relevant molecular features, analyzes their correlations with traditional GC classifications, and discusses potential clinical applications.

Transcriptomic subtyping of gastrointestinal malignancies

Gastrointestinal (GI) cancers are highly heterogeneous at multiple levels. Tumor heterogeneity can be captured by molecular profiling, such as genetic, epigenetic, proteomic, and transcriptomic classification. Transcriptomic subtyping has the advantage of combining genetic and epigenetic information, cancer cell-intrinsic properties, and the tumor microenvironment (TME). Unsupervised transcriptomic subtyping systems of different GI malignancies have gained interest because they reveal shared biological features across cancers and bear prognostic and predictive value. Importantly, transcriptomic subtypes accurately reflect complex phenotypic states varying not only per tumor region, but also throughout disease progression, with consequences for clinical management. Here, we discuss methodologies of transcriptomic subtyping, proposed taxonomies for GI malignancies, and the challenges posed to clinical implementation, highlighting opportunities for future transcriptomic profiling efforts to optimize clinical impact.

LINC01614 is a promising diagnostic and prognostic marker in HNSC linked to the tumor microenvironment and oncogenic function

Background

Tumor initiation and metastasis influence tumor immune exclusion and immunosuppression. Long non-coding RNA (lncRNA) LINC01614 is associated with the prognosis and metastasis of several cancers. However, the relationship between LINC01614 and cancer immune infiltration and the biofunction of LINC01614 in head and neck squamous cell carcinoma (HNSC) remain unclear.

Methods

The Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) datasets were used to analyze the expression difference and diagnostic value of LINC01614 in normal and tumor tissues. The correlation of pan-cancer prognosis and tumor stage of LINC01614 was analyzed based on the TCGA database. The pan-cancer association of LINC01614 expression with the tumor microenvironment (TME) including immune infiltration, expression of immune-related genes, and genomic instability parameters, was analyzed using the Spearman correlation method. The correlation between LINC01614 and tumor stemness evaluation indicators, RNA methylation-related genes, and drug resistance was also analyzed. The functional analysis of LINC01614 was performed using the clusterProfiler R package. The protein-protein interaction (PPI) network and ceRNA network of LINC01614 co-expressed genes and miRNA were constructed and visualized by STRING and Cytoscape, respectively. Finally, the cell location and influence of LINC01614 on cell proliferation and metastasis of HNSC cell lines were evaluated using FISH, CCK-8, wound-healing assay, and transwell assay.

Results

LINC01614 was found to be overexpressed in 23 cancers and showed a highly sensitive prediction value in nine cancers (AUC >0.85). LINC01614 dysregulation was associated with tumor stage in 12 cancers and significantly influenced the survival outcomes of 26 cancer types, with only Lymphoid Neoplasm Diffuse Large B-cell Lymphoma (DLBC), uterine corpus endometrial carcinoma (UCEC), and bladder urothelial carcinoma (BLCA) showing a benign influence. LINC01614 was also associated with immune cell infiltration, tumor heterogeneity, cancer stemness, RNA methylation modification, and drug resistance. The potential biological function of LINC01614 was verified in HNSC, and it was found to play important roles in proliferation, immune infiltration, immunotherapy response, and metastasis of HNSC.

Conclusion

LINC01614 may serve as a cancer diagnosis and prognosis biomarker and an immunotherapy target for specific cancers.

The landscape of lncRNAs in gastric cancer: from molecular mechanisms to potential clinical applications

Gastric cancer (GC) is a highly prevalent and deadly malignant neoplasm worldwide. Currently, long non-coding RNAs (lncRNAs) have recently been identified as crucial regulators implicated in GC development and progression. Dysregulated expression of lncRNAs is commonly associated with enhanced tumor migration, invasiveness, and therapy resistance, highlighting their potential as promising targets for clinical applications. This review offers a comprehensive historical overview of lncRNAs in GC, describes the molecular mechanisms, and discusses the prospects and challenges of establishing lncRNAs as precision biomarkers.

Epigenetically regulated gene expression profiles decipher four molecular subtypes with prognostic and therapeutic implications in gastric cancer

BACKGROUND

Gastric cancer (GC) is one of the most common malignant tumors of the digestive tract which seriously endangers the health of human beings worldwide. Transcriptomic deregulation by epigenetic mechanisms plays a crucial role in the heterogeneous progression of GC. This study aimed to investigate the impact of epigenetically regulated genes on the prognosis, immune microenvironment, and potential treatment of GC.

RESULTS

Under the premise of verifying significant co-regulation of the aberrant frequencies of microRNA (miRNA) correlated (MIRcor) genes and DNA methylation-correlated (METcor) genes. Four GC molecular subtypes were identified and validated by comprehensive clustering of MIRcor and METcor GEPs in 1521 samples from five independent multicenter GC cohorts: cluster 1 was characterized by up-regulated cell proliferation and transformation pathways, with good prognosis outcomes, driven by mutations, and was sensitive to 5-fluorouracil and paclitaxel; cluster 2 performed moderate prognosis and benefited more from apatinib and cisplatin; cluster 3 was featured by an up-regulated ligand-receptor formation-related pathways, poor prognosis, an immunosuppression phenotype with low tumor purity, resistant to chemotherapy (e.g., 5-fluorouracil, paclitaxel, and cisplatin), and targeted therapy drug (apatinib) and sensitive to dasatinib; cluster 4 was characterized as an immune-activating phenotype, with advanced tumor stages, benefit more from immunotherapy and displayed worst prognosis.

CONCLUSIONS

According to the epigenetically regulated GEPs, we developed four robust GC molecular subtypes, which facilitated the understanding of the epigenetic mechanisms underlying GC heterogeneity, offering an optimized decision-making and surveillance platform for GC patients.

Integrative network analysis reveals subtype-specific long non-coding RNA regulatory mechanisms in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSC) is one of most common malignancies with high mortality worldwide. Importantly, the molecular heterogeneity of HNSC complicates the clinical diagnosis and treatment, leading to poor overall survival outcomes. To dissect the complex heterogeneity, recent studies have reported multiple molecular subtyping systems. For instance, HNSC can be subdivided to four distinct molecular subtypes: atypical, basal, classical, and mesenchymal, of which the mesenchymal subtype is characterized by upregulated epithelial-mesenchymal transition (EMT) and associated with poorer survival outcomes. Despite a wealth of studies into the complex molecular heterogeneity, the regulatory mechanism specific to this aggressive subtype remain largely unclear. Herein, we developed a network-based bioinformatics framework that integrates lncRNA and mRNA expression profiles to elucidate the subtype-specific regulatory mechanisms. Applying the framework to HNSC, we identified a clinically relevant lncRNA LNCOG as a key master regulator mediating EMT underlying the mesenchymal subtype. Five genes with strong prognostic values, namely ANXA5, ITGA5, CCBE1, P4HA2, and EPHX3, were predicted to be the putative targets of LNCOG and subsequently validated in other independent datasets. By integrative analysis of the miRNA expression profiles, we found that LNCOG may act as a ceRNA to sponge miR-148a-3p thereby upregulating ITGA5 to promote HNSC progression. Furthermore, our drug sensitivity analysis demonstrated that the five putative targets of LNCOG were also predictive of the sensitivities of multiple FDA-approved drugs. In summary, our bioinformatics framework facilitates the dissection of cancer subtype-specific lncRNA regulatory mechanisms, providing potential novel biomarkers for more optimized treatment of HNSC.

Low expression of lncRNA APTR promotes gastric cancer progression

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APTR is actively expressed in gastric cancer cells.

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Low expression of APTR is associated with poor clinical characteristics in patients with gastric cancer.

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Silencing APTR promotes gastric cancer proliferation and invasiveness.

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APTR expression is negatively associated with inflammatory signaling in the gastric tumor microenvironment.

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LncRNA APRT is a potential biomarker for gastric cancer patients' diagnosis and prognosis, and could be a potential therapeutic target.

Background

Gastric cancer (GC) is one of the most common cancers worldwide and the majority of GC patients are diagnosed at advanced stages due to the lack of early detection biomarkers. LncRNAs have been shown to play important roles in various diseases and could be predictive biomarkers and therapeutic targets. Our study demonstrated that low expression of lncRNA APTR could promote gastric cancer progression.

Methods

Differentiated expressed lncRNAs were identified through analyzing TCGA paired GC RNA sequencing data. LncRNA APTR's clinical relevance was analyzed using the TCGA dataset and GEO datasets. APTR expression in patient samples was detected through qPCR. The proliferation, colony formation, and migration of GC cells were tested. Bioinformatic analyses were performed to explore APTR-affected signaling pathways in GC.

Results

LncRNA APTR is lower expressed in gastric tumor samples and low expression of APTR predicts a poor diagnosis and outcome in GC patients. Silencing APTR promotes gastric cancer proliferation and invasiveness. APTR expression is negatively correlated with inflammatory signaling in the gastric tumor microenvironment.

Conclusion

Our study showed that low expression of lncRNA APTR in gastric cancer is correlated with tumorigenesis and poor diagnosis and prognosis, which is a potential biomarker for gastric cancer patients' diagnosis and treatment.

Cancer-associated fibroblast-specific lncRNA LINC01614 enhances glutamine uptake in lung adenocarcinoma

Background

Besides featured glucose consumption, recent studies reveal that cancer cells might prefer “addicting” specific energy substrates from the tumor microenvironment (TME); however, the underlying mechanisms remain unclear.

Methods

Fibroblast-specific long noncoding RNAs were screened using RNA-seq data of our NJLCC cohort, TCGA, and CCLE datasets. The expression and package of LINC01614 into exosomes were identified using flow cytometric sorting, fluorescence in situ hybridization (FISH), and quantitative reverse transcription polymerase chain reaction (RT-PCR). The transfer and functional role of LINC01614 in lung adenocarcinoma (LUAD) and CAFs were investigated using 4-thiouracil-labeled RNA transfer and gain- and loss-of-function approaches. RNA pull-down, RNA immunoprecipitation, dual-luciferase assay, gene expression microarray, and bioinformatics analysis were performed to investigate the underlying mechanisms involved.

Results

We demonstrate that cancer-associated fibroblasts (CAFs) in LUAD primarily enhance the glutamine metabolism of cancer cells. A CAF-specific long noncoding RNA, LINC01614, packaged by CAF-derived exosomes, mediates the enhancement of glutamine uptake in LUAD cells. Mechanistically, LINC01614 directly interacts with ANXA2 and p65 to facilitate the activation of NF-κB, which leads to the upregulation of the glutamine transporters SLC38A2 and SLC7A5 and eventually enhances the glutamine influx of cancer cells. Reciprocally, tumor-derived proinflammatory cytokines upregulate LINC01614 in CAFs, constituting a feedforward loop between CAFs and cancer cells. Blocking exosome-transmitted LINC01614 inhibits glutamine addiction and LUAD growth in vivo. Clinically, LINC01614 expression in CAFs is associated with the glutamine influx and poor prognosis of patients with LUAD.

Conclusion

Our study highlights the therapeutic potential of targeting a CAF-specific lncRNA to inhibit glutamine utilization and cancer progression in LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13045-022-01359-4.

Long non‑coding RNA 01614 hyperactivates WNT/β‑catenin signaling to promote pancreatic cancer progression by suppressing GSK‑3β

Pancreatic cancer (PC) is a lethal type of cancer for which effective therapies are limited. Long non-coding RNAs (lncRNAs) represent a critical type of regulator category, mediating the tumorigenesis and development of various tumor types, including PC. However, the expression patterns and functions of numerous lncRNAs in PC remain poorly understood. In the present study, linc01614 was identified as a PC-related lncRNA. linc01614 was notably upregulated in PC tissues and cell lines and was associated with the poor disease-free survival of patients with PC according to the analysis of The Cancer Genome Atlas-derived datasets. Functionally, linc01614 knockdown suppressed PC cell proliferation, migration and invasion in vitro, and inhibited tumor proliferation in vitro and in vivo. Mechanistically, linc01614 overexpression stabilized the level of β-catenin protein to hyperactivate the WNT/β-catenin signaling pathway in PC cells. Further analyses revealed that linc01614 bound to GSK-3β and perturbed the interaction between GSK-3β and AXIN1, thereby preventing the formation of the β-catenin degradation complex and reducing the degradation of β-catenin. In summary, the present findings reveal that linc01614 may function as an oncogene and promote the progression of PC and may thus be considered as a potential therapeutic target in the future.

Risk SNP-mediated LINC01614 upregulation drives head and neck squamous cell carcinoma progression via PI3K/AKT signaling pathway

As potential biomarkers and therapeutic targets, long noncoding RNAs (lncRNAs) are involved in the tumorigenesis of various tumors. Genetic variation in long noncoding regions can lead to lncRNA dysfunction and even cancer. Nevertheless, studies on the association between lncRNA-associated single-nucleotide polymorphisms (SNPs) and the risk of head and neck squamous cell carcinoma (HNSCC) remain inadequate. Here, we aimed to explore the association between SNPs in LINC01614 and HNSCC risk, and the potential role of LINC01614 in tumorigenesis. In this study, we found that rs16854802 A > G (odds ratio [OR] = 1.42, 95% confidence interval [CI]: 1.22-1.77, p < 0.001) and rs3113503 G > C (OR = 1.38, 95% CI: 1.15-1.64, p < 0.001) in LINC01614 increased the risk of HNSCC in the Chinese population. Functional bioinformatic analysis and luciferase reporter assay revealed that rs3113503 G > C variant disrupted the binding of miRNA-616-3p to LINC01614, which resulted in the increased expression of LINC01614. Further analysis of the TCGA database demonstrated that the upregulated LINC01614 in HNSCC cancer tissues was associated with poor prognostic in HNSCC patients. In vitro experiments showed that knockdown of LINC01614 inhibited the proliferation, invasion, and migration ability of HNSCC cells. Mechanistically, allele C of rs3113503 in LINC01614 was more effective than allele G in activating the PI3K/AKT signaling pathway. Moreover, the reduced expression of LINC01614 also inhibited the activation of the PI3K/AKT signaling pathway. In summary, our findings revealed that the risk SNP rs3113503 G > C in LINC01614 altered the binding to miR-616-3p, which led to increased LINC01614 expression and promoted HNSCC progression by activating the PI3K/AKT signaling pathway.

LncRNA TNFRSF10A-AS1 promotes gastric cancer by directly binding to oncogenic MPZL1 and is associated with patient outcome

Background: LncRNA is closely associated with the progression of human tumors. The role of lncRNA TNFRSF10A-AS1 (T-AS1) in gastric cancer (GC) is still unclear. We aim to investigate the functional significance and the underlying mechanisms of T-AS1 in the pathogenesis and progression of GC. Experimental Design: The clinical impact of T-AS1 was assessed in 103 patients with GC. The biological function of T-AS1 was studied in vitro and in vivo. T-AS1 downstream effector were identified by RNA sequencing and RNA pulldown assay. Results: T-AS1 was upregulated in GC cell lines and GC tissues as compared to adjacent non-cancer tissues (n = 47, P < 0.001). Multivariate analysis showed that GC patients with T-AS1 high expression had a significantly shortened survival (n=103, P < 0.05). T-AS1 significantly promoted GC cell proliferation, cell-cycle progression, and cell migration/invasion abilities, but suppressed cell apoptosis. Silencing of T-AS1 in GC cells exerted opposite effects in vitro. Knockout of T-AS1 significantly inhibited xenograft tumor growth in nude mice. Mechanistically, T-AS1 directly bound to Myelin Protein Zero Like 1 (MPZL1). MPZL1 showed an oncogenic function in GC by promoting cell proliferation, migration and invasion but inhibiting cell apoptosis. High expression of MPZL1 was associated with poor survivor of GC patients. Knockdown of MPZL1 could abrogate the effect of T-AS1 in the tumor-promoting function. Conclusions: T-AS1 plays a pivotal oncogenic role in GC and is an independent prognostic factor for GC patients. The oncogenic function of T-AS1 is dependent on its direct downstream effector MPZL1.

Potential Key Markers for Predicting the Prognosis of Gastric Adenocarcinoma Based on the Expression of Ferroptosis-Related lncRNA

Background. Gastric cancer is one of the most common malignant tumors, and it ranks third in global cancer-related mortality. This research was aimed at identifying new targeted treatments for gastric adenocarcinoma by constructing a ferroptosis-related lncRNA prognostic feature model. Methods. The gene expression profile and clinical data of gastric adenocarcinoma patients were downloaded from TCGA database. FerrDb database was used to determine the expression of iron death-related genes. We used R software to clean the TCAG gastric adenocarcinoma gene expression cohort and screen iron death-related differential genes and lncRNAs. The potential prognostic markers and immune infiltration characteristics were determined by constructing prognostic model and multivariate validation of lncRNA related to ferroptosis prognosis. Finally, the characteristics of immune infiltration were determined by immune correlation analysis. Results. We identified 26 ferroptosis-related lncRNAs with independent prognostic value. The Kaplan-Meier analysis identified high-risk lncRNAs associated with poor prognosis of STAD. The risk scoring model constructed by AC115619.1, AC005165.1, LINC01614, and AC002451.1 was better than traditional clinicopathological features. The 1-, 3-, and 5-year survival rates of STAD patients were predicted by the nomogram. GSEA reveals the oxidative respiration and tumor-related pathways in different risk groups. Immune analysis found significant differences in the expression of immune checkpoint-related genes TNFSF9, TNFSF4, and PDCD1LG2 between the two groups of patients. Meanwhile, there were significant differences in APC co stimulation, CCR, and checkpoint between the two groups. Conclusion. Based on the prognostic characteristics of ferroptosis-related lncRNAs, we identified the potential ferroptosis-related lncRNAs and immune infiltration characteristics in gastric adenocarcinoma, which will help provide new targeted treatments for gastric adenocarcinoma.

Ferroptosis‑related long non‑coding RNAs and the roles of LASTR in stomach adenocarcinoma

Ferroptosis is a form of programmed cell death that participates in diverse physiological processes. Increasing evidence suggests that long noncoding RNAs (lncRNAs) regulate ferroptosis in tumors, including stomach adenocarcinoma (STAD). In the present study, RNA-sequencing data from The Cancer Genome Atlas database and ferroptosis-related markers from the FerrDb data resource were analyzed to select differentially expressed lncRNAs. Univariate and multivariate Cox regression analyses were performed on these differentially expressed lncRNAs to screen 12 lncRNAs linked with overall survival (OS) and 13 associated with progression-free survival (PFS). Subsequently, two signatures for predicting OS and PFS were established based on these lncRNAs. Kaplan-Meier analyses indicated that the high-risk group of patients with STAD had relatively poor prognosis. The areas under the receiver operating characteristic curves of the two signatures indicated their excellent efficacy in predicting STAD prognosis. In addition, the effect of the lncRNA LASTR on proliferation and migration in gastric cancer was confirmed and the relationship between LASTR and ferroptosis was initially explored through experiments. These results provide potential novel targets for tumor treatment and promote personalized medicine.

Prognostic Ferroptosis-Related lncRNA Signatures Associated With Immunotherapy and Chemotherapy Responses in Patients With Stomach Cancer

Ferroptosis is associated with the prognosis and therapeutic responses of patients with various cancers. LncRNAs are reported to exhibit antitumor or oncogenic functions. Currently, few studies have assessed the combined effects of ferroptosis and lncRNAs on the prognosis and therapy of stomach cancer. In this study, transcriptomic and clinical data were downloaded from TCGA database, and ferroptosis-related genes were obtained from the FerrDb database. Through correlation analysis, Cox analysis, and the Lasso algorithm, 10 prognostic ferroptosis-related lncRNAs (AC009299.2, AC012020.1, AC092723.2, AC093642.1, AC243829.4, AL121748.1, FLNB-AS1, LINC01614, LINC02485, LINC02728) were screened to construct a prognostic model, which was verified in two test cohorts. Risk scores for patients with stomach cancer were calculated, and patients were divided into two risk groups. The low-risk group, based on the median value, had a longer overall survival time in the KM curve, and a lower proportion of dead patients in the survival distribution curve. Potential mechanisms and possible functions were revealed using GSEA and the ceRNA network. By integrating clinical information, the association between lncRNAs and clinical features was analyzed and several features affecting prognosis were identified. Then, a nomogram was developed to predict survival rates, and its good predictive performance was indicated by a relatively high C-index (0.67118161) and a good match in calibration curves. Next, the association between these lncRNAs and therapy was explored. Patients in the low-risk group had an immune-activating environment, higher immune scores, higher TMB, lower TIDE scores, and higher expression of immune checkpoints, suggesting they might receive a greater benefit from immune checkpoint inhibitor therapy. In addition, a significant difference in the sensitivity to mitomycin. C, cisplatin, and docetaxel, but not etoposide and paclitaxel, was observed. In summary, this model had guiding significance for prognosis and personalized therapy. It helped screen patients with stomach cancer who might benefit from immunotherapy and guided the selection of personalized chemotherapeutic drugs.

Construction and Comprehensive Prognostic Analysis of a Novel Immune-Related lncRNA Signature and Immune Landscape in Gastric Cancer

Gastric cancer (GC) is a malignant tumor with high mortality and poor prognosis. Immunotherapies, especially immune checkpoint inhibitors (ICI), are widely used in various tumors, but patients with GC do not benefit much from immunotherapies. Therefore, effective predictive biomarkers are urgently needed for GC patients to realize the benefits of immunotherapy. Recent studies have indicated that long noncoding RNAs (lncRNAs) could be used as biomarkers in the immune landscape of multiple tumors. In this study, we constructed a novel immune-related lncRNA (irlncRNA) risk model to predict the survival and immune landscape of GC patients. First, we identified differentially expressed irlncRNAs (DEirlncRNAs) from RNA-Seq data of The Cancer Genome Atlas (TCGA). By using various algorithms, we constructed a risk model with 11 DEirlncRNA pairs. We then tested the accuracy of the risk model, demonstrating that the risk model has good efficiency in predicting the prognosis of GC patients. Inner validation sets were further used to confirm the effectiveness of the risk model. In addition, our risk model has a preferable performance in predicting the immune infiltration status of tumors, immune checkpoint status of the patients, and immunotherapy score. In conclusion, our risk model may provide insights into the prognosis of and immunotherapy strategy for GC.

Identifying Glycolysis-related LncRNAs for predicting prognosis in breast cancer patients

PURPOSE: Functions associated with glycolysis could serve as targets or biomarkers for therapy cancer. Our purpose was to establish a prognostic model that could evaluate the importance of Glycolysis-related lncRNAs in breast cancer. METHODS: Gene expressions were evaluated for breast cancer through The Cancer Genome Atlas (TCGA) database, and we calculated Pearson correlations to discover potential related lncRNAs. Differentially expressed genes were identified via criteria of FDR < 0.05 and |FC|> 2. Total samples were separated into training and validating sets randomly. Univariate Cox regression identified 14 prognostic lncRNAs in training set. A prognostic model was constructed to evaluate the accuracy in predicting prognosis. The univariate and multivariate Cox analysis were performed to verify whether lncRNA signature could be an independent prognostic factor The signature was validated in validating set. Immune infiltration levels were assessed. RESULTS: Eighty-nine differentially expressed lncRNAs were identified from 420 Glycolysis-related lncRNAs. 14 lncRNAs were correlated with prognosis in training set and were selected to establish the prognostic model. Low risk group had better prognosis in both training (p= 9.025 e -10) and validating (p= 4.272 e -3) sets. The univariate and multivariate Cox analysis revealed that risk score of glycolysis-related lncRNAs (P< 0.001) was an independent prognostic factor in both training and validating sets. The neutrophils (p= 4.214 e -13, r=-0.223), CD4+ T cells (p= 1.833 e -20, r=-0.283), CD8+ T cells (p= 7.641 e -12, r=-0.211), B cells (p= 2.502 e -10, r=-0.195) and dendritic cells (p= 5.14 e -18, r=-0.265) were negatively correlated with risk score of prognostic model. The Macrophage (p= 0.016, r= 0.0755) was positively correlated with the risk score. CONCLUSION: Our study indicated that glycolysis-related lncRNAs had a significant role to facilitate the individualized survival prediction in breast cancer patients, which would be a potential therapeutic target.

Identification of mRNA vaccines and conserved ferroptosis related immune landscape for individual precision treatment in bladder cancer

BACKGROUND

The aim of this study was to identify the ferroptosis induced tumor microenvironment (FeME) landscape in bladder cancer (BCa) for mRNA vaccine development and selecting suitable patients for precision treatment.

METHODS

Gene expression profiles and clinical information of 1216 BCa patients were extracted from TCGA-BLCA, three GEO databases and IMvigor210 cohort. We comprehensively established the FeME landscape of 1216 BCa samples based on 290 ferroptosis related genes (FRGs), and systematically correlated these regulation patterns with TME cell-infiltrating characteristics. Besides, we identified the patients' ferroptosis risk index (FRI) to predict the prognosis of BCa for precise treatment.

RESULTS

Six over-expressed and mutated tumor antigens associated with poor prognosis and infiltration of antigen presenting cells were identified in BCa. Furthermore, we demonstrated the evaluation of FeME within individual tumors could predict stages of tumor inflammation, subtypes, genetic variation, and patient prognosis. Then, 5-lncRNA signature was mined to produce the FRI. Low FRI was also linked to increased mutation load, better prognosis and enhanced response to anti-PD-L1 immunotherapy. Besides, an immunotherapy cohort confirmed patients with lower FRI demonstrated significant therapeutic advantages and clinical benefits.

CONCLUSIONS

TFRC, SCD, G6PD, FADS2, SQLE, and SLC3A2 are potent antigens for developing anti-BCa mRNA vaccine. Establishment of FRI will contribute to enhancing our cognition of TME infiltration characterization and guiding more effective immunotherapy strategies and selecting appropriate patients for tumor vaccine therapy.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s40537-022-00641-z.

Long Non-Coding RNA Neighbor of BRCA1 Gene 2: A Crucial Regulator in Cancer Biology

Long non-coding RNAs (lncRNAs) are involved in fundamental biochemical and cellular processes. The neighbor of BRCA1 gene 2 (NBR2) is a long intergenic non-coding RNA (lincRNA) whose gene locus is adjacent to the tumor suppressor gene breast cancer susceptibility gene 1 (BRCA1). In human cancers, NBR2 expression is dysregulated and correlates with clinical outcomes. Moreover, NBR2 is crucial for glucose metabolism and affects the proliferation, survival, metastasis, and therapeutic resistance in different types of cancer. Here, we review the precise molecular mechanisms underlying NBR2-induced changes in cancer. In addition, the potential application of NBR2 in the diagnosis and treatment of cancer is also discussed, as well as the challenges of exploiting NBR2 for cancer intervention.

Survival-Related lncRNA Landscape Analysis Identifies LINC01614 as an Oncogenic lncRNA in Gastric Cancer

Background: Long non-coding RNAs (lncRNAs) reportedly play important roles in biomarker and tumorigenesis of gastric cancer (GC). This study aimed to determine the potential application of prognostic lncRNA signature and identified the role of LINC01614 in carcinogenesis in GC.

Material and Methods: Data accessed from the Cancer Genome Atlas database was used to construct a lncRNA signature. Joint effect analysis of the signature and clinical parameters was performed to verify the clinical value of the signature. Co-expression analysis was conducted for prognostic lncRNAs and protein-coding genes. Moreover, the relative expression of LINC01614 was validated in GC tissues and cell lines. In vitro and in vivo experiments were conducted to analyze the biological functions of the newly identified gene in GC cells.

Results: A seven-lncRNA (LINC01614, LINC01537, LINC01210, OVAAL, LINC01446, CYMP-AS1, and SCAT8) signature was identified as a promising prognostic signature in GC. Results indicated that the seven-lncRNA was involved in tumorigenesis and progression pathways. LINC01614 expression was identified and found to be upregulated in GC tissues and cells. The study findings revealed that LINC01614 promoted cell proliferation, migration, invasion, and epithelial-mesenchymal transition. Knockdown of LINC01614 arrested cell cycle distribution at the G2/M phase. Further, LINC01614 also promoted tumor growth in vivo.

Conclusion: We developed an independent seven-lncRNA biomarker for prognostic prediction and identified LINC01614 as an oncogenic lncRNA in GC.

Cross-Talk of Focal Adhesion-Related Gene Defines Prognosis and the Immune Microenvironment in Gastric Cancer

Background: Focal adhesion, as the intermediary between tumor cells and extracellular matrix communication, plays a variety of roles in tumor invasion, migration, and drug resistance. However, the potential role of focal adhesion-related genes in the microenvironment, immune cell infiltration, and drug sensitivity of gastric cancer (GC) has not yet been revealed.

Methods: The genetic and transcriptional perspectives of focal adhesion-related genes were systematically analyzed. From a genetic perspective, the focal adhesion index (FAI) was constructed based on 18 prognosis-related focus adhesion-related genes to evaluate the immune microenvironment and drug sensitivity. Then three prognosis-related genes were used for consistent clustering to identify GC subtypes. Finally, use FLT1, EGF, COL5A2, and M2 macrophages to develop risk signatures, and establish a nomogram together with clinicopathological characteristics.

Results: Mutations in the focal adhesion-related gene affect the survival time and clinical characteristics of GC patients. FAI has been associated with a shorter survival time, immune signaling pathways, M2 macrophage infiltration, epithelial-mesenchymal transition (EMT) signaling, and diffuse type of GC. FAI recognizes ALK, cell cycle, and BMX signaling pathways inhibitors as sensitive agents for the treatment of GC. FLT1, EGF, and COL5A2 may distinguish GC subtypes. The established risk signature is of great significance to the prognostic evaluation of GC based on FLT1, EGF, and COL5A2 and M2 macrophage expression.

Conclusion: The focal adhesion-related gene is a potential biomarker for the evaluation of the immune microenvironment and prognosis. This work emphasizes the potential impact of the focal adhesion pathway in GC therapy and highlights its guiding role in prognostic evaluation.

Integrated Analysis of Stemness-Related LncRNAs Helps Predict the Immunotherapy Responsiveness of Gastric Cancer Patients

The immune microenvironment plays a critical role in tumor biology. As a critical feature of cancers, stemness is acknowledged as a contributor to the development of drug resistance in gastric cancers (GCs). Long non-coding RNAs (lncRNAs) have been revealed to participate in this process. In this study, we aimed to develop a stemness-related lncRNA signature (SRLncSig) with guiding significance for immunotherapy. Three cohorts (TCGA, Zhongshan, and IMvigor210) were enrolled for analysis. A list of stemness-related lncRNAs (SRlncRNAs) was collected by co-expression strategy under the threshold of coefficient value >0.35 and p-value < 0.05. Cox and Lasso regression analysis was further applied to find out the SRlncRNAs with prognosis-predictive value to establish the SRLncSig in the TCGA cohort. IPS and TIDE algorithms were further applied to predict the efficacy of SRLncSig in TCGA and Zhongshan cohorts. IMvigor210 was composed of patients with clinical outcomes of immunotherapy. The results indicated that SRLncSig not only was confirmed as an independent risk factor for GCs but also identified as a robust indicator for immunotherapy. The patient with a lower SRLncSig score was more likely to benefit from immunotherapy, and the results were highly consistent in three cohorts. In conclusion, our study not only could clarify the correlations between stemness and immunotherapy in GC patients but also provided a model to guide the applications of immunotherapy in clinical practice.

Stemness-related LncRNA pair signature for predicting therapy response in gastric cancer

Objective

As a critical feature of cancers, stemness is acknowledged as a contributor to the development of drug resistance in gastric cancer (GC). LncRNAs have been revealed to participate in this process. In this study, we tried to develop a stemness-related lncRNA pair signature as guidance for clinical decisions.

Methods

The analysis was initiated by collecting stemness-related lncRNAs in TCGA cohort. The differentially expressed stemness-related lncRNAs between normal and tumor tissues in GC patients from TCGA datasets were further collected to establish the signature based on Lasso and Cox regression analyses. The predictive efficacy of the signature for chemotherapy and immunotherapy was also tested. The practicality of this signature was also validated by Zhongshan cohort.

Results

A 13-DEsrlncRNA pair-based signature was established. The cutoff point acquired by the AIC algorithm divided the TCGA cohort into high and low risk groups. We found that the low-risk group presented with better survival (Kaplan-Meier analysis, p < 0.001). Cox regression analyse was also conducted to confirm the signature as an independent risk factor for GC {p < 0.001, HR = 1.300, 95% CI (1.231–1.373)]}. As for the practicality of this signature, the IC50 of cytotoxic chemotherapeutics was significantly higher in the high-risk group. The low-risk group also presented with higher immunophenoscore (IPS) in both the “CTLA4+ PD1+” (Mann-Whitney U test, p = 0.019) and “CTLA4- PD1+” (Mann-Whitney U test, p = 0.013) groups, indicating higher sensitivity to immunotherapy. The efficacy of the signature was also validated by Zhongshan cohort.

Conclusions

This study could not only provide a stemness-related lncRNA signature for survival prediction in GC patients but also established a model with predictive potentials for GC patients’ sensitivity to chemotherapy and immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08798-1.

Keep your eyes peeled for long noncoding RNAs: Explaining their boundless role in cancer metastasis, drug resistance, and clinical application

Cancer metastasis and drug resistance are two major obstacles in the treatment of cancer and therefore, the leading cause of cancer-associated mortalities worldwide. Hence, an in-depth understanding of these processes and identification of the underlying key players could help design a better therapeutic regimen to treat cancer. Earlier thought to be merely transcriptional junk and having passive or secondary function, recent advances in the genomic research have unravelled that long noncoding RNAs (lncRNAs) play pivotal roles in diverse physiological as well as pathological processes including cancer metastasis and drug resistance. LncRNAs can regulate various steps of the complex metastatic cascade such as epithelial-mesenchymal transition (EMT), invasion, migration and metastatic colonization, and also affect the sensitivity of cancer cells to various chemotherapeutic drugs. A substantial body of literature for more than a decade of research evince that lncRNAs can regulate gene expression at different levels such as epigenetic, transcriptional, posttranscriptional, translational and posttranslational levels, depending on their subcellular localization and through their ability to interact with DNA, RNA and proteins. In this review, we mainly focus on how lncRNAs affect cancer metastasis by modulating expression of key metastasis-associated genes at various levels of gene regulation. We also discuss how lncRNAs confer cancer cells either sensitivity or resistance to various chemo-therapeutic drugs via different mechanisms. Finally, we highlight the immense potential of lncRNAs as prognostic and diagnostic biomarkers as well as therapeutic targets in cancer.

Long non‑coding RNA NEAT1 regulates glioma cell proliferation and apoptosis by competitively binding to microRNA‑324‑5p and upregulating KCTD20 expression

Previous studies have demonstrated that long non‑coding RNAs (lncRNAs) serve a key role in the development and progression of several types of cancer, including glioma. The lncRNA nuclear paraspeckle assembly transcript 1 (NEAT1) contributes to cancer growth through its effects on cell proliferation, migration, invasion and drug resistance. However, the exact regulatory mechanisms via which NEAT1 acts in glioma are unclear. In the present study, the expression levels and function of NEAT1 in glioma tissues and cell lines were examined in vitro and in vivo. By reverse transcription‑quantitative PCR and fluorescence in situ hybridization analysis, NEAT1 expression was upregulated in glioma tissues compared with in adjacent normal brain tissues, and elevated NEAT1 levels were associated with poor prognosis. Cell Counting Kit‑8, colony formation, ethynyldeoxyuridine, flow cytometry and western blotting assays were performed to detect the effects of NEAT1 on cell biological behavior. Knockdown of NEAT1 in glioma cell lines was associated with cell cycle arrest at the G₀/G₁ phase, decreased proliferation and elevated apoptosis in vitro, and resulted in reduced tumor growth and increased survival in a mouse xenograft model of glioma. Using bioinformatics analysis, RNA immunoprecipitation experiments and luciferase reporter assays, it was demonstrated that NEAT1 may competitively bind to microRNA (miR)‑324‑5p, thus blocking its interaction with target mRNAs. Potassium channel tetramerization protein domain containing 20 (KCTD20) was identified as a specific miR‑324‑5p target. Accordingly, the inhibition of NEAT1 resulted in the downregulation of KCTD20 through competitive binding with miR‑324‑5p, decreased cell proliferation and increased apoptosis. Concomitant NEAT1 knockdown and inhibition of miR‑324‑5p partially reversed the effects of NEAT1 knockdown on cell proliferation and apoptosis, and further regulated KCTD20 expression. Collectively, the present findings demonstrated that NEAT1 acted as a competing endogenous RNA for miR‑324‑5p, and identified the NEAT1/miR‑324‑5p/KCTD20 axis as a novel regulatory axis and a potential therapeutic target for human glioma.