The Role of Long Non-coding RNAs in Immunotherapy Resistance

Radiotherapy-immunity lncRNA model predicts lung adenocarcinoma prognosis and treatment outcome and distinguishes between hot and cold tumors

BACKGROUND

There are many prognostic markers for lung adenocarcinoma (LUAD). However, studies on the prognosis of LUAD by radiotherapy immune-related long noncoding RNAs (lncRNAs) are extremely rare.

METHODS

We have compiled 1121 radiotherapy susceptibility differential genes and 6195 immune-related genes. After that, we screened radiotherapy-immunity lncRNAs associated with proliferation by co-expression, univariate, least absolute shrinkage selection operator regression (LASSO), and multivariate analysis of variance. Finally, we constructed a prognostic model based on 6 lncRNAs, and verified the accuracy of the predictive model by ROC and C index. In addition, we used the constructed scoring model to analyze the model's association with the characteristics of immune cell infiltration, immune checkpoint and drug sensitivity. Finally, the whole sample was divided into 2 clusters to further distinguish hot and cold tumors.

RESULTS

We constructed a risk score model built on 6 prognostically relevant lncRNAs. Patients were categorized into high-risk and low-risk patients based on median scores in the Train group. We found that people in the high-risk group had a lower survival rate than those in the low-risk group. However, those in the high-risk group were more sensitive to chemotherapy, targeted drugs and also more sensitive to immunotherapy drugs. Based on the line graphs of T, N, Age, Stage and Risk, the corresponding scores can be summed up to visualize the survival rate of patients at 1, 3 and 5 years. Gene set enrichment analysis (GSEA) suggested that radiotherapy-immunity-related lncRNA might be related to pathways such as cell cycle, T cell receptor signaling pathway. It is noteworthy that in our study, cluster 1 was considered to be a hot tumor more sensitive to immunotherapy.

CONCLUSION

In summary, we constructed a risk score model built on six radiosensitivity and immune-related lncRNAs, which is expected to be a potential predictive biomarker for radiosensitivity and LUAD prognosis.

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

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

High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC)

BACKGROUND

Despite the impressive outcomes with immune checkpoint inhibitor (ICI) in non-small cell lung cancer (NSCLC), only a minority of the patients show long-term benefits from ICI. In this study, we used retrospective cohorts of ICI treated patients with NSCLC to discover and validate spatially resolved protein markers associated with resistance to programmed cell death protein-1 (PD-1) axis inhibition.

METHODS

Pretreatment samples from 56 patients with NSCLC treated with ICI were collected and analyzed in a tissue microarray (TMA) format in including four different tumor regions per patient using the GeoMx platform for spatially informed transcriptomics. 34 patients had assessable tissue with tumor compartment in all 4 TMA spots, 22 with leukocyte compartment and 12 with CD68 compartment. The patients' tissue that was not assessable in fourfold redundancy in each compartment was designated as the validation cohort; cytokeratin (CK) (N=22), leukocytes CD45 (N=31), macrophages, CD68 (N=43). The human whole transcriptome, represented by~18,000 individual genes assessed by oligonucleotide-tagged in situ hybridization, was sequenced on the NovaSeq platform to quantify the RNAs present in each region of interest.

RESULTS

54,000 gene variables were generated per case, from them 25,740 were analyzed after removing targets with expression lower than a prespecified frequency. Cox proportional-hazards model analysis was performed for overall and progression-free survival (OS, PFS, respectively). After identifying genes significantly associated with limited survival benefit (HR>1)/progression per spot per patient, we used the intersection of them across the four TMA spots per patient. This resulted in a list of 12 genes in the tumor-cell compartment (RPL13A, GNL3, FAM83A, CYBA, ACSL4, SLC25A6, EPAS1, RPL5, APOL1, HSPD1, RPS4Y1, ADI1). RPL13A, GNL3 in tumor-cell compartment were also significantly associated with OS and PFS, respectively, in the validation cohort (CK: HR, 2.48; p=0.02 and HR, 5.33; p=0.04). In CD45 compartment, secreted frizzled-related protein 2, was associated with OS in the discovery cohort but not in the validation cohort. Similarly, in the CD68 compartment ARHGAP and PNN interacting serine and arginine rich protein were significantly associated with PFS and OS, respectively, in the majority but not all four spots per patient.

CONCLUSION

This work highlights RPL13A and GNL3 as potential indicative biomarkers of resistance to PD-1 axis blockade that might help to improve precision immunotherapy strategies for lung cancer.

Identification and evaluation of a six-lncRNA prognostic signature for multiple myeloma

PURPOSE

Multiple myeloma (MM) is the second most common hematologic malignancy, and there is no cure for this disease. This study aimed to explore the prognostic value of long noncoding RNAs (lncRNAs) in MM and to reveal related immune and chemotherapy resistance mechanisms.

METHODS

In this study, lncRNA profiles from the Multiple Myeloma Research Foundation (MMRF) and Gene Expression Omnibus (GEO) databases were analyzed to identify lncRNAs linked to MM patient survival. A risk assessment model stratified patients into high- and low-risk groups, and survival was evaluated. Additionally, a triple-ceRNA (lncRNA-miRNA-mRNA) network was constructed, and functional analysis was performed. The research also involved immune function analysis and chemotherapy drug sensitivity assessment using oncoPredict and the GDSC dataset.

RESULTS

We identified 422 lncRNAs significantly associated with overall survival in MM patients and ultimately focused on the 6 with the highest prognostic value. These lncRNAs were used to develop a risk score formula that stratified patients into high- and low-risk groups. Kaplan-Meier analysis revealed shorter survival in high-risk patients. We integrated this lncRNA signature with clinical parameters to construct a nomogram for predicting MM prognosis. Additionally, a triple-ceRNA network was constructed to reveal potential miRNA targets, coding genes related to these lncRNAs and significantly enriched pathways. Immune checkpoint gene expression and immune cell composition were also analyzed in relation to the lncRNA risk score. Finally, using the oncoPredict tool, we observed that high-risk patients exhibited decreased sensitivity to key MM chemotherapeutics, suggesting that lncRNA profiles are linked to chemotherapy resistance.

Systematic analysis reveals a pan-cancer SNHG family signature predicting prognosis and immunotherapy response

Small nucleolar RNA host genes (SNHGs) are a special family of long non-coding RNAs (lncRNAs), which not only function in a way similar to other lncRNAs but also influence the intracellular level of small nucleolar RNAs to modulate cancers. However, the features of SNHGs and their role in the prognosis and immunotherapeutic response of human cancer have not been explored. We found that SNHGs were commonly deregulated and correlated with patient survival in various cancers. The critical role of DNA methylation and somatic alterations on deregulation was also identified. SNHG family score was significantly associated with survival, multiple tumor characteristics, and tumor microenvironment. SNHG-related risk score could serve as a prognostic and immunotherapeutic response biomarker based on multiple databases. This study emphasizes the potential of SNHGs as biomarkers for prognosis and immunotherapeutic response, enabling further research into the immune regulatory mechanism and therapeutic potentials of SNHGs in cancer.

Integrated analysis of inflammatory mRNAs, miRNAs, and lncRNAs elucidates the molecular interactome behind bovine mastitis

Mastitis is known as intramammary inflammation, which has a multifactorial complex phenotype. However, the underlying molecular pathogenesis of mastitis remains poorly understood. In this study, we utilized a combination of RNA-seq and miRNA-seq techniques, along with computational systems biology approaches, to gain a deeper understanding of the molecular interactome involved in mastitis. We retrieved and processed one hundred transcriptomic libraries, consisting of 50 RNA-seq and 50 matched miRNA-seq data, obtained from milk-isolated monocytes of Holstein-Friesian cows, both infected with Streptococcus uberis and non-infected controls. Using the weighted gene co-expression network analysis (WGCNA) approach, we constructed co-expressed RNA-seq-based and miRNA-seq-based modules separately. Module-trait relationship analysis was then performed on the RNA-seq-based modules to identify highly-correlated modules associated with clinical traits of mastitis. Functional enrichment analysis was conducted to understand the functional behavior of these modules. Additionally, we assigned the RNA-seq-based modules to the miRNA-seq-based modules and constructed an integrated regulatory network based on the modules of interest. To enhance the reliability of our findings, we conducted further analyses, including hub RNA detection, protein-protein interaction (PPI) network construction, screening of hub-hub RNAs, and target prediction analysis on the detected modules. We identified a total of 17 RNA-seq-based modules and 3 miRNA-seq-based modules. Among the significant highly-correlated RNA-seq-based modules, six modules showed strong associations with clinical characteristics of mastitis. Functional enrichment analysis revealed that the turquoise module was directly related to inflammation persistence and mastitis development. Furthermore, module assignment analysis demonstrated that the blue miRNA-seq-based module post-transcriptionally regulates the turquoise RNA-seq-based module. We also identified a set of different RNAs, including hub-hub genes, hub-hub TFs (transcription factors), hub-hub lncRNAs (long non-coding RNAs), and hub miRNAs within the modules of interest, indicating their central role in the molecular interactome underlying the pathogenic mechanisms of S. uberis infection. This study provides a comprehensive insight into the molecular crosstalk between immunoregulatory mRNAs, miRNAs, and lncRNAs during S. uberis infection. These findings offer valuable directions for the development of molecular diagnosis and biological therapies for mastitis.

Histone acetylation-related IncRNA: Potential biomarkers for predicting prognosis and immune response in lung adenocarcinoma, and distinguishing hot and cold tumours

Background

Histone acetylation-related lncRNAs (HARlncRNAs) play significant roles in various cancers, but their impact on lung adenocarcinoma (LUAD) remains unclear. This study aimed to develop a new HARlncRNA-based prognostic model for LUAD and to explore its potential biological mechanisms.

Methods

We identified 77 histone acetylation genes based on previous studies. HARlncRNAs related to prognosis were screened by co-expression, univariate and multivariate analyses, and least absolute shrinkage selection operator regression (LASSO). Afterward, a prognostic model was established based on the screened HARlncRNAs. We analysed the relationship between the model and immune cell infiltration characteristics, immune checkpoint molecule expression, drug sensitivity, and tumour mutational burden (TMB). Finally, the entire sample was divided into three clusters to further distinguish between hot and cold tumours.

Results

A seven-HARlncRNA-based prognostic model was established for LUAD. The area under the curve (AUC) of the risk score was the highest among all the analysed prognostic factors, indicating the accuracy and robustness of the model. The patients in the high-risk group were predicted to be more sensitive to chemotherapeutic, targeted, and immunotherapeutic drugs. It was worth noting that clusters could effectively identify hot and cold tumours. In our study, clusters 1 and 3 were considered hot tumours that were more sensitive to immunotherapy drugs.

Conclusion

We developed a risk-scoring model based on seven prognostic HARlncRNAs that promises to be a new tool for evaluating the prognosis and efficacy of immunotherapy in patients with LUAD.

Comprehensive landscape and future perspectives of long noncoding RNAs (lncRNAs) in colorectal cancer (CRC): Based on a bibliometric analysis

This review aimed to use bibliometric analysis to sort out, analyze and summarize the knowledge foundation and hot topics in the field of long noncoding RNAs (lncRNAs) in colorectal cancer (CRC), and point out future trends to inspire related research and innovation. We used CiteSpace to analyze publication outputs, countries, institutions, authors, journals, references, and keywords. Knowledge foundations, hotspots, and future trends were then depicted. The overall research showed the trend of biomedical-oriented multidisciplinary. Much evidence indicates that lncRNA plays the role of oncogene or tumor suppressor in the occurrence and development of CRC. Besides, many lncRNAs have multiple mechanisms. lncRNAs and metastasis of CRC, lncRNAs and drug resistance of CRC, and the clinical application of lncRNAs in CRC are current research hotspots. Through insight into the development trend of lncRNAs in CRC, this study will help researchers extract hidden valuable information for further research.

Identification of m6A-related lncRNAs for thyroid cancer recurrence

Background

Although the prognosis of thyroid cancer (THCA) is generally good, many patients have a high risk of recurrence after treatment. N6-methyladenosine (m6A)-related long noncoding RNAs (lncRNAs) have been extensively studied in recent years. However, the potential of m6A-related lncRNAs to predict recurrence in THCA is unknown.

Methods

RNA sequencing (RNA-seq) data and clinical information for THCA were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs (DELs) were identified using the R package DESeq2. A coexpression network based on m6A-related genes and lncRNAs was constructed. The CIBERSORT algorithm and gene set enrichment analysis (GSEA) were used for immune-infiltrating cell estimation and clustering functional enrichment analysis, respectively. A Kaplan-Meier plot was used for prognostic analysis based on m6A-associated lncRNA risk patterns. The expression of lncRNAs in recurrent and nonrecurrent THCA tissues was analyzed by real-time quantitative polymerase chain reaction (RT-qPCR).

Results

A network of m6A-related lncRNAs containing 8 lncRNAs was constructed with good predictive power for recurrence in THCA. A total of 3 clusters were obtained, and cluster 1 was most associated with THCA recurrence. We found significantly lower levels of CD8 T cells and follicular helper T cells, and significantly higher levels of dendritic cells (DCs), M2 macrophages, resting DCs, regulatory T cells, and mast cells in cluster 1 patients. Pathway analysis revealed significant enrichment in natural killer cell-mediated cytotoxicity, butyrate metabolism, and cell adhesion molecules in cluster 1. The m6A-related lncRNA risk model was effective in predicting progression-free survival (PFS) in patients with THCA recurrence. RT-qPCR analysis based on 40 THCA clinical samples from our center found the risk model to be a good predictor of recurrence in THCA patients.

Conclusions

In summary, m6A-related lncRNAs may provide a novel predictive method for prognostic relapse in THCA patients.

Long Non-Coding RNAs as Epigenetic Regulators of Immune Checkpoints in Cancer Immunity

In recent years, cancer treatment has undergone significant changes, predominantly in the shift towards immunotherapeutic strategies using immune checkpoint inhibitors. Despite the clinical efficacy of many of these inhibitors, the overall response rate remains modest, and immunotherapies for many cancers have proved ineffective, highlighting the importance of knowing the tumor microenvironment and heterogeneity of each malignancy in patients. Long non-coding RNAs (lncRNAs) have attracted increasing attention for their ability to control various biological processes by targeting different molecular pathways. Some lncRNAs have a regulatory role in immune checkpoints, suggesting they might be utilized as a target for immune checkpoint treatment. The focus of this review is to describe relevant lncRNAs and their targets and functions to understand key regulatory mechanisms that may contribute in regulating immune checkpoints. We also provide the state of the art on super-enhancers lncRNAs (selncRNAs) and circular RNAs (circRNAs), which have recently been reported as modulators of immune checkpoint molecules within the framework of human cancer. Other feasible mechanisms of interaction between lncRNAs and immune checkpoints are also reported, along with the use of miRNAs and circRNAs, in generating new tumor immune microenvironments, which can further help avoid tumor evasion.

Focus on PD-1/PD-L1 as a Therapeutic Target in Ovarian Cancer

Ovarian cancer is considered one of the most aggressive and deadliest gynecological malignancies worldwide. Unfortunately, the therapeutic methods that are considered the gold standard at this moment are associated with frequent recurrences. Survival in ovarian cancer is associated with the presence of a high number of intra tumor infiltrating lymphocytes (TILs). Therefore, immunomodulation is considered to have an important role in cancer treatment, and immune checkpoint inhibitors may be useful for restoring T cell-mediated antitumor immunity. However, the data presented in the literature until now are not sufficient to allow for the identification and selection of patients who really respond to immunotherapy among those with ovarian cancer. Although there are some studies with favorable results, more prospective trials are needed in this sense. This review focuses on the current and future perspectives of PD-1/L1 blockade in ovarian cancer and analyzes the most important immune checkpoint inhibitors used, with the aim of achieving optimal clinical outcomes. Future studies and trials are needed to maximize the efficacy of immune checkpoint blockade therapy in ovarian cancer, as well as in all cancers, in general.

Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Background

Advances in our understanding of the tumor microenvironment have radically changed the cancer field, highlighting the emerging need for biomarkers of an active, favorable tumor immune phenotype to aid treatment stratification and clinical prognostication. Numerous immune-related gene signatures have been defined; however, their prognostic value is often limited to one or few cancer types. Moreover, the area of non-coding RNA as biomarkers remains largely unexplored although their number and biological roles are rapidly expanding.

Methods

We developed a multi-step process to identify immune-related long non-coding RNA signatures with prognostic connotation in multiple TCGA solid cancer datasets.

Results

Using the breast cancer dataset as a discovery cohort we found 2988 differentially expressed lncRNAs between immune favorable and unfavorable tumors, as defined by the immunologic constant of rejection (ICR) gene signature. Mapping of the lncRNAs to a coding-non-coding network identified 127 proxy protein-coding genes that are enriched in immune-related diseases and functions. Next, we defined two distinct 20-lncRNA prognostic signatures that show a stronger effect on overall survival than the ICR signature in multiple solid cancers. Furthermore, we found a 3 lncRNA signature that demonstrated prognostic significance across 5 solid cancer types with a stronger association with clinical outcome than ICR. Moreover, this 3 lncRNA signature showed additional prognostic significance in uterine corpus endometrial carcinoma and cervical squamous cell carcinoma and endocervical adenocarcinoma as compared to ICR.

Conclusion

We identified an immune-related 3-lncRNA signature with prognostic connotation in multiple solid cancer types which performed equally well and in some cases better than the 20-gene ICR signature, indicating that it could be used as a minimal informative signature for clinical implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03654-7.

Predicting prognosis and immunotherapy response among colorectal cancer patients based on a tumor immune microenvironment-related lncRNA signature

Long non-coding RNAs (lncRNAs) remodel the tumor immune microenvironment (TIME) by regulating the functions of tumor-infiltrating immune cells. It remains uncertain the way that TIME-related lncRNAs (TRLs) influence the prognosis and immunotherapy response of colorectal cancer (CRC). Aiming at providing survival and immunotherapy response predictions, a CRC TIME-related lncRNA signature (TRLs signature) was developed and the related potential regulatory mechanisms were explored with a comprehensive analysis on gene expression profiles from 97 immune cell lines, 61 CRC cell lines and 1807 CRC patients. Stratifying CRC patients with the TRLs signature, prolonged survival was observed in the low-risk group, while the patients in the high-risk group had significantly higher pro-tumor immune cells infiltration and higher immunotherapy response rate. Through the complex TRLs-mRNA regulation network, immunoregulation pathways and immunotherapy response pathways were found to be differently activated between the groups. In conclusion, the CRC TRLs signature is capable of making prognosis and immunotherapy response predictions, which may find application in stratifying patients for immunotherapy in the bedside.

Comprehensive Analysis of the Correlation Between Pyroptosis-Related LncRNAs and Tumor Microenvironment, Prognosis, and Immune Infiltration in Hepatocellular Carcinoma

Background: Accumulating evidence shows that pyroptosis plays a crucial role in hepatocellular carcinoma (HCC). However, the relationship between pyroptosis-related long non-coding RNAs (lncRNAs) and HCC tumor characteristics remains enigmatic. We aimed to explore the predictive effect of pyroptosis-related lncRNAs (PRLs) in the prognosis of HCC.

Methods: We comprehensively analyzed the role of the PRLs in the tumor microenvironment and HCC prognosis by integrating genomic data from patients of HCC. Consensus clustering analysis of PRLs was applied to identify HCC subtypes. A prognostic model was then established with a training cohort from The Cancer Genome Atlas (TCGA) using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Further, we evaluated the accuracy of this predictive model using a validation set. We predicted IC50s of commonly used chemotherapeutic and targeted drugs through the R package pRRophetic.

Results: Based on pyroptosis-related lncRNAs, a prognostic risk signature composed of seven PRLs (MKLN1AS, AL031985.3, SNHG4, GHRLOS, AC005479.2, AC099850.4, and AC026412.3) was established. For long-term prognosis of HCC patients, our model shows excellent accuracy to forecast overall survival of HCC individuals both in training set and testing set. We found a significant correlation between clinical features and the risk score. Patients in the high-risk group had tumor characteristics associated with progression such as aggressive pathological grade and stage. Besides that, gene set enrichment analysis (GSEA) showed that cell cycle and focal adhesion were significantly enriched in the high-risk group.

Conclusion: The association of the risk model constituted by these seven pyroptosis-related lncRNAs with clinical prognosis, tumor microenvironment, chemotherapy and small molecule drugs was evaluated. Our study provides strong evidence for individualized prediction of prognosis, shedding light on immunotherapy in HCC patients.

Establishment of a Cell Necroptosis Index to Predict Prognosis and Drug Sensitivity for Patients With Triple-Negative Breast Cancer

Background: Necroptosis has been an alternatively identified mechanism of programmed cancer cell death, which plays a significant role in cancer. However, research about necroptosis-related long noncoding RNAs (lncRNAs) in cancer are still few. Moreover, the potentially prognostic value of necroptosis-related lncRNAs and their correlation with the immune microenvironment remains unclear. The present study aimed to explore the potential prognostic value of necroptosis-related lncRNAs and their relationship to immune microenvironment in triple-negative breast cancer (TNBC).

Methods: The RNA expression matrix of patients with TNBC was obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Finally, 107 patients of GSE58812, 159 patients of TCGA, and 143 patients of GSE96058 were included. Necroptosis-related lncRNAs were screened by Cox regression and Pearson correlation analysis with necroptosis-related genes. By LASSO regression analysis, nine necroptosis-related lncRNAs were employed, and a cell necroptosis index (CNI) was established; then, we evaluated its prognostic value, clinical significance, pathways, immune infiltration, and chemotherapeutics efficacy.

Results: Based on the CNI value, the TNBC patients were divided into high- and low-CNI groups, and the patients with high CNI had worse prognosis, more lymph node metastasis, and larger tumor (p < 0.05). The receiver operating characteristic (ROC) analysis showed that the signature performed well. The result of the infiltration proportion of different immune cell infiltration further explained that TNBC patients with high CNI had low immunogenicity, leading to poor therapeutic outcomes. Moreover, we found significant differences of the IC50 values of various chemotherapeutic drugs in the two CNI groups, which might provide a reference to make a personalized chemotherapy for them.

Conclusion: The novel prognostic marker CNI could not only precisely predict the survival probability of patients with TNBC but also demonstrate a potential role in antitumor immunity and drug sensitivity.

Comprehensive analysis of ZFPM2-AS1 prognostic value, immune microenvironment, drug sensitivity, and co-expression network: from gastric adenocarcinoma to pan-cancers

BACKGROUND

ZFPM2-AS1, as an oncogenic lncRNA, plays an essential role in the progression of several tumors. However, the prognostic significance, biological function, and molecular mechanism of ZFPM2-AS1 in most tumors have not been fully elucidated.

METHODS

We analyzed differentially expressed immune-related lncRNAs (IRlncRNAs) and clustered gastric adenocarcinoma (GAC) samples based on these lncRNAs expression. Then, WGCNA and survival analysis were performed to determine key IRlncRNA (ZFPM2-AS1) in GAC. The comprehensive analysis was performed to evaluate the association between ZFPM2-AS1 expression and survival, tumor microenvironment (TME), immune-related factors, and related signal pathways in pan-cancers. Furthermore, we constructed a co-expression network of ZFPM2-AS1, and NUP107 and C8orf76 were identified as target mRNAs. We further evaluated the role of NUP107 and C8orf76 in the GAC microenvironment. More importantly, real-time polymerase chain reaction (qRT-PCR) was employed to validate ZFPM2-AS1, NUP107 and C8orf76 expression.

RESULTS

ZFPM2-AS1 was remarkably overexpressed and correlated with poor overall survival in most tumors. Further analysis showed that ZFPM2-AS1 was related to various immune cells infiltrated in the microenvironment of most tumors. GSEA revealed that ZFPM2-AS1 in GAC was primarily involved in immune-related pathways. Furthermore, NUP107 and C8orf76 were identified as potential target mRNAs of ZFPM2-AS1, which was related to infiltrating immune cells in the GAC microenvironment. qRT-PCR verified that ZFPM2-AS, NUP107 and C8orf76 were highly expressed in gastric cancer cells.

CONCLUSION

ZFPM2-AS1 could be a potential biomarker for cancer prognosis, and a promising immune target for cancer therapy. Furthermore, ZFPM2-AS1 might play an immunosuppressive role in the GAC microenvironment.

Immune-related lincRNA pairs predict prognosis and therapeutic response in hepatocellular carcinoma

Growing evidence has demonstrated the functional relevance of long intergenic noncoding RNAs (lincRNAs) to tumorigenesis and immune response. However, immune-related lincRNAs and their value in predicting the clinical outcomes of patients with liver cancer remain largely unexplored. Herein, we utilized the strategy of iterative gene pairing to construct a tumor-specific immune-related lincRNA pairs signature (IRLPS), which did not require specific expression levels, as an indicator of patient outcomes. The 18-IRLPS we developed was associated with overall survival, tumor progression, and recurrence in liver cancer patients. Multivariate analysis revealed that the risk model was an independent predictive factor. A high IRLPS risk was correlated suppressive immune microenvironment, and IRLPS-high patients might benefit more from CD276 blockade or TMIGD2 agonist. Patients in the high-risk group were associated with elevated tumor mutation, increased sensitivity to dopamine receptor antagonists, cisplatin, doxorubicin, and mitomycin but more resistance to vinblastine. Mechanistically, IRLPS high scores might lead to poor prognosis by promoting cell proliferation and metabolic reprogramming. The prognostic significance of the 18-IRLPS was confirmed in independent cancer datasets. These findings highlighted the robust predictive performances of the 18-IRLPS for prognosis and personalized treatment.

Functions of non-coding RNAs in regulating cancer drug targets

With the development of precision medicine, the efficiency of tumor treatment has been significantly improved. More attention has been paid to targeted therapy and immunotherapy as the key to precision treatment of cancer. Targeting epidermal growth factor receptor (EGFR) has become one of the most important targeted treatments for various cancers. Comparing with traditional chemotherapy drugs, targeting EGFR is highly selective in killing tumor cells with better safety, tolerability and less side effect. In addition, tumor immunotherapy has become the fourth largest tumor therapy after surgery, radiotherapy and chemotherapy, especially immune checkpoint inhibitors. However, these treatments still produce a certain degree of drug resistance. Non-coding RNAs (ncRNAs) were found to play a key role in carcinogenesis, treatment and regulation of the efficacy of anticancer drugs in the past few years. Therefore, in this review, we aim to summarize the targeted treatment of cancers and the functions of ncRNAs in cancer treatment.

RNA-mediated immunotherapy regulating tumor immune microenvironment: next wave of cancer therapeutics

Accumulating research suggests that the tumor immune microenvironment (TIME) plays an essential role in regulation of tumor growth and metastasis. The cellular and molecular nature of the TIME influences cancer progression and metastasis by altering the ratio of immune- suppressive versus cytotoxic responses in the vicinity of the tumor. Targeting or activating the TIME components show a promising therapeutic avenue to combat cancer. The success of immunotherapy is both astounding and unsatisfactory in the clinic. Advancements in RNA-based technology have improved understanding of the complexity and diversity of the TIME and its effects on therapy. TIME-related RNA or RNA regulators could be promising targets for anticancer immunotherapy. In this review, we discuss the available RNA-based cancer immunotherapies targeting the TIME. More importantly, we summarize the potential of various RNA-based therapeutics clinically available for cancer treatment. RNA-dependent targeting of the TIME, as monotherapy or combined with other evolving therapeutics, might be beneficial for cancer patients’ treatment in the near future.

The regulatory role of long non- coding RNAs as a novel controller of immune response against cancer cells

Immunotherapy has been established as a promising therapy for different cancer types. However, many patients experience primary or secondary resistance to treatment. Immune cells and anti-inflammatory factors are regulated by long noncoding RNAs (lncRNAs). In addition, lncRNAs have a role in immune resistance through antigen presentation loss or attenuation, PD-L1 upregulation, loss of T-cell activities, and activation of G-MDSCs and Tregs in the tumor environment. LncRNAs can also influence the interaction between cancer stem cells and immune cells in the tumor microenvironment, potentially resulting in cancer stem cell resistance to immunotherapy. Immunological-related lncRNAs can influence immune responses either directly by affecting neighboring protein-coding genes or indirectly by sponging miRNAs through various mechanisms. We have emphasized the role and levels of expression of lncRNAs that have been linked to immune cell formation, differentiation, and activation, which may have an influence on immunotherapy efficacy.

An immune-related lncRNA signature predicts prognosis and adjuvant chemotherapeutic response in patients with small-cell lung cancer

Background

Patients with small-cell lung cancer (SCLC) are burdened by limited treatment options and the disease’s dismal prognosis. Long non-coding RNAs (lncRNAs) are essential regulators of genetic alteration and are actively involved in tumor immunity. However, few studies have examined interactions between immune genes and lncRNAs in SCLC.

Methods

Immune-related lncRNA (irlncRNA) expression profiles and their clinical significance were explored. We enrolled 227 patients with SCLC, including 79 cases from GSE65002 and 148 cases from a validation cohort with corresponding qPCR data. The least absolute shrinkage and selection operator (LASSO) model was applied to identify prognostic irlncRNAs for an irlncRNA-based SCLC signature. We additionally investigated the potential mechanisms and immune landscape of the signature using bioinformatics methods.

Results

An irlncRNA signature including 8 irlncRNAs (ENOX1-AS1, AC005162, LINC00092, RPL34-AS1, AC104135, AC015971, AC126544, AP001189) was established for patients with SCLC in the training cohort. Low-risk patients were more likely to benefit from chemotherapy and achieve a favorable prognosis. The signature was also well-validated in the validation cohort and various clinical subgroups. Compared to other clinical parameters, the irlncRNA signature exhibited superior predictive performance for chemotherapy response and prognosis. The signature was as an independent prognostic factor in the training and validation cohorts. Interestingly, low-risk patients showed an activated immune phenotype.

Conclusion

We constructed the first irlncRNA-based signature for chemotherapy efficacy and outcome prediction. The irlncRNA signature is a reliable and robust prognostic classifier that could be useful for clinical management and determination of potential chemotherapy benefit for patients with SCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02357-1.

Tumor immune microenvironment lncRNAs

Long non-coding ribonucleic acids (RNAs) (lncRNAs) are key players in tumorigenesis and immune responses. The nature of their cell type-specific gene expression and other functional evidence support the idea that lncRNAs have distinct cellular functions in the tumor immune microenvironment (TIME). To date, the majority of lncRNA studies have heavily relied on bulk RNA-sequencing data in which various cell types contribute to an averaged signal, limiting the discovery of cell type-specific lncRNA functions. Single-cell RNA-sequencing (scRNA-seq) is a potential solution for tackling this limitation despite the lack of annotations for low abundance yet cell type-specific lncRNAs. Hence, updated annotations and further understanding of the cellular expression of lncRNAs will be necessary for characterizing cell type-specific functions of lncRNA genes in the TIME. In this review, we discuss lncRNAs that are specifically expressed in tumor and immune cells, summarize the regulatory functions of the lncRNAs at the cell type level and highlight how a scRNA-seq approach can help to study the cell type-specific functions of TIME lncRNAs.

Current State and Progress of Research on the Role of lncRNA in HBV-Related Liver Cancer

Hepatocellular carcinoma (HCC) is a malignant tumor with the highest mortality rate in the world, and hepatitis B virus (HBV) plays an important role in its development. Long noncoding RNA (lncRNA) is highly related to the inactivation of tumor suppressor genes and the activation of oncogenes in HCC. Researchers have used high-throughput sequencing technology to identify many noncoding transcripts related to the development of HCC and have studied the interaction between these transcripts and DNA, RNA, or protein to determine the relevant mechanism in the development of HCC. In general, the research on lncRNA represents a new field of cancer research, and the imbalance in lncRNA plays an pivotal role in the occurrence of liver cancer. In this review, we summarize some of the dysfunctional lncRNAs in human HCC associated with HBV infection. Their regulatory pathways, functions, and potential molecular mechanisms in the occurrence and development of HCC are discussed.

Comprehensive analysis of immune related lncRNAs in the tumor microenvironment of stage II-III colorectal cancer

Background

Long non-coding RNAs (lncRNAs) associated with immunological function have increasingly been found to act as effective prognostic biomarkers of the overall survival (OS) of colorectal cancer (CRC) patients. We sought to identify a signature of immune-related lncRNAs that offered value as a tool for the prospective prognostic evaluation of patients with stage II-III CRC.

Methods

The clinical and gene expression data of CRC patients in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases was obtained and separated into a training cohort composed of 202 samples, a test cohort of 124 samples from the GSE72970 dataset, and a validation cohort of 91 samples from the GSE143985 dataset.

Results

We firstly evaluated intratumoral immune cell infiltration by conducting a Single-sample gene set enrichment analyses (ssGSEA) analysis to separate patient tumors into those with low immune cell infiltration and those with high immune cell infiltration. We then compared lncRNA and mRNA expression profiles between these two tumor types, leading us to focus on eight lncRNAs identified within the resultant mRNA-lncRNA co-expression network. Multivariate Cox regression models were then utilized to detect an immune-associated lncRNA signature that offered value for prognostic model construction. Functional analyses revealed this lncRNA signature to be associated with key immunological pathways including the JAK-STAT signaling, T cell receptor signaling, and Rap1 signaling pathways.

Conclusions

Together, our results suggest that our immune-related 4 lncRNA signature can reliably predict stage II-III CRC patient prognosis, thereby guiding efforts to better understand this disease and to effectively treat it.

m6A methyltransferase METTL3-mediated lncRNA FOXD2-AS1 promotes the tumorigenesis of cervical cancer

Recent studies have indicated that long noncoding RNA (lncRNA) and N⁶-methyladenosine (m⁶A) methylation modification play critical roles in human cancers; however, their regulation on cervical cancer is largely unclear. Here, our study tries to investigate the underlying mechanisms by which lncRNA FOXD2 adjacent opposite strand RNA 1 (FOXD2-AS1) modulates cervical cancer tumorigenesis. Results illuminated that FOXD2-AS1 expression was significantly upregulated in cervical cancer cells and tissue, which was closely correlated to the unfavorable prognosis. Functionally, gain and loss-of-function assays showed that FOXD2-AS1 promoted the migration and proliferation of cervical cancer cells. Besides, FOXD2-AS1 silencing repressed the tumor growth in vivo. Mechanistically, m⁶A methyltransferase methyltransferase-like 3 (METTL3) enhanced the stability of FOXD2-AS1 and maintained its expression. Moreover, FOXD2-AS1 recruited lysine-specific demethylase 1 (LSD1) to the promoter region of p21 to silence its transcription abundance. In conclusion, these findings support that METTL3/FOXD2-AS1 accelerates cervical cancer progression via a m⁶A-dependent modality, which may serve as a potential therapeutic target for cervical cancer.

Signal transducer and activator of transcription 3 signaling in tumor immune evasion

The underlying mechanism of tumor immune evasion is a highly concerning subject for researchers. Increasing evidences reveal that the over-activated signal transducer and activator of transcription 3 (STAT3) is a crucial molecular hub in malignant tumors. STAT3 controls autophagy molecules that impair CTL-mediated tumor cell lysis, inhibiting natural killer cells and inducing apoptosis in T lymphocytes to create an immunosuppressive environment. STAT3 signaling regulates the expression of immune factors and recruits immunosuppressive cells to establish a tolerant tumor microenvironment (TME). STAT3 signaling regulates the expression of immune factors and recruits immunosuppressive cells to create an immunosuppressive environment. All this aid tumor cells in escaping from immune surveillance. In this review, we outlined the STAT3-mediated mechanisms involved in tumor immune evasion and their potential regulatory functions in the TME. We discussed the impact of STAT3 signaling on PD-L1, HIF-1α, exosome, lncRNA, and autophagy in the promotion of tumor immune evasion and highlighted the recent research on STAT3 signaling and tumor immune evasion that may assist in developing effective STAT3-targeted drugs for advancing immunotherapy.

The lncRNAs in HBV-Related HCCs: Targeting Chromatin Dynamics and Beyond

Hepatocellular carcinoma (HCC) represents the fourth leading and fastest rising cause of cancer death (841,000 new cases and 782,000 deaths annually), and hepatitis B (HBV), with 250 million people chronically infected at risk of developing HCC, accounts for >50% of the cases worldwide. Long non-coding RNAs (lncRNAs), untranslated transcripts longer than 200 nucleotides, are implicated in gene regulation at the transcriptional and post-transcriptional levels, exerting their activities both in the nuclear and cytoplasmic compartments. Thanks to high-throughput sequencing techniques, several lncRNAs have been shown to favor the establishment of chronic HBV infection, to change the host transcriptome to establish a pro-carcinogenic environment, and to directly participate in HCC development and progression. In this review, we summarize current knowledge on the role of lncRNAs in HBV infection and HBV-related liver carcinogenesis and discuss the potential of lncRNAs as predictive or diagnostic biomarkers.

Potential impact and mechanism of Long Non-coding RNAs on cancer and associated T cells

The discovery of many aberrant expressions of long non-coding RNAs (lncRNAs) in various cancers has focused attention on the effects of lncRNA on cancer cells themselves, including cell proliferation, growth inhibition, cell migration, cell immortality, vascular regeneration and cell viability. But with the increasing role of immunotherapy in cancer therapy, a large number of studies have revealed that the regulatory role of lncRNAs in immunity such as differentiation of immune cells can also influence the development and progression of cancer. In particular, recent publications have suggested that lncRNAs play critical roles in T-lymphocyte activation, proliferation, differentiation, function, apoptosis and metabolism. To elucidate the actual functions of lncRNAs at the molecular level of cancer pathogenesis, we summarize some of the current lncRNA regulatory mechanisms associated with T cell to discuss their effects in cancer in the hope of providing potential cancer therapeutic targets or cancer biomarkers. However, we all know that the differentiation and function of T cells is an extremely complex process that involves the expression and regulation of multiple lncRNAs. As a result, more regulatory mechanisms of lncRNAs need to be further studied.

Interplay within tumor microenvironment orchestrates neoplastic RNA metabolism and transcriptome diversity

The heterogeneous population of cancer cells within a tumor mass interacts intricately with the multifaceted aspects of the surrounding microenvironment. The reciprocal crosstalk between cancer cells and the tumor microenvironment (TME) shapes the cancer pathophysiome in a way that renders it uniquely suited for immune tolerance, angiogenesis, metastasis, and therapy resistance. This dynamic interaction involves a dramatic reconstruction of the transcriptomic landscape of tumors by altering the synthesis, modifications, stability, and processing of gene readouts. In this review, we categorically evaluate the influence of TME components, encompassing a myriad of resident and infiltrating cells, signaling molecules, extracellular vesicles, extracellular matrix, and blood vessels, in orchestrating the cancer-specific metabolism and diversity of both mRNA and noncoding RNA, including micro RNA, long noncoding RNA, circular RNA among others. We also highlight the transcriptomic adaptations in response to the physicochemical idiosyncrasies of TME, which include tumor hypoxia, extracellular acidosis, and osmotic stress. Finally, we provide a nuanced analysis of existing and prospective therapeutics targeting TME to ameliorate cancer-associated RNA metabolism, consequently thwarting the cancer progression. This article is categorized under: RNA Processing > Splicing Regulation/Alternative Splicing RNA Turnover and Surveillance > Regulation of RNA Stability RNA in Disease and Development > RNA in Disease.

Immune Infiltrates of m6A RNA Methylation-Related lncRNAs and Identification of PD-L1 in Patients With Primary Head and Neck Squamous Cell Carcinoma

Background: The purpose of this study was to determine the association between m⁶A-modified lncRNAs, immune infiltration, and PD-L1 expression in patients with primary head and neck squamous cell carcinoma (HNSCC) and the prognostic value of m⁶A RNA methylation-related lncRNAs in HNSCC. Methods: We downloaded the RNA-seq transcriptome data and the clinical information for HNSCC from the TCGA databases and used consensus clustering analysis to divide the samples into two groups. To identify a risk signature, least absolute shrinkage and selection operator (LASSO) analyses were conducted. the association between m⁶A-modified lncRNAs, immune infiltration, and PD-L1 expression were detected by using the R packages. What is more, we used cBioPortal tools to identify genomic alterations and PD-L1 mutations and Gene set enrichment analysis (GSEA) was utilized to predict downstream access of two clusters. Results: Notably, lncRNAs play significant roles in tumorigenesis and development. In total, we identified two subtypes of HNSCC according to consensus clustering of the m⁶A RNA methylation-related lncRNAs, and the T, grade and age were proven to be related to the subtypes. The Cox regression and LASSO analyses identified a risk signature including GRHL3-AS1, AL121845.4, AC116914.2, AL513190.1. The prognostic value of the risk signature was then proven. The selected gene PD-L1 mutations and the immune infiltration in both groups were further explored. Conclusion: Collectively, our study elucidated the important role of m⁶A RNA methylation- related lncRNAs in tumor microenvironment of HNSCC. The proposed m⁶A RNA methylation- related lncRNAs might serve as crucial mediators of tumor microenvironment of HNSCC, representing promising therapeutic targets in improving immunotherapeutic efficacy.

Polyphenols Modulating Effects of PD-L1/PD-1 Checkpoint and EMT-Mediated PD-L1 Overexpression in Breast Cancer

Investigating dietary polyphenolic compounds as antitumor agents are rising due to the growing evidence of the close association between immunity and cancer. Cancer cells elude immune surveillance for enhancing their progression and metastasis utilizing various mechanisms. These mechanisms include the upregulation of programmed death-ligand 1 (PD-L1) expression and Epithelial-to-Mesenchymal Transition (EMT) cell phenotype activation. In addition to its role in stimulating normal embryonic development, EMT has been identified as a critical driver in various aspects of cancer pathology, including carcinogenesis, metastasis, and drug resistance. Furthermore, EMT conversion to another phenotype, Mesenchymal-to-Epithelial Transition (MET), is crucial in developing cancer metastasis. A central mechanism in the upregulation of PD-L1 expression in various cancer types is EMT signaling activation. In breast cancer (BC) cells, the upregulated level of PD-L1 has become a critical target in cancer therapy. Various signal transduction pathways are involved in EMT-mediated PD-L1 checkpoint overexpression. Three main groups are considered potential targets in EMT development; the effectors (E-cadherin and Vimentin), the regulators (Zeb, Twist, and Snail), and the inducers that include members of the transforming growth factor-beta (TGF-β). Meanwhile, the correlation between consuming flavonoid-rich food and the lower risk of cancers has been demonstrated. In BC, polyphenols were found to downregulate PD-L1 expression. This review highlights the effects of polyphenols on the EMT process by inhibiting mesenchymal proteins and upregulating the epithelial phenotype. This multifunctional mechanism could hold promises in the prevention and treating breast cancer.

Exploration of the Associations of lncRNA Expression Patterns with Tumor Mutation Burden and Prognosis in Colon Cancer

Background

Tumor mutation burden (TMB) is emerging as a new biomarker to monitor the response of cancer patients to immunotherapy. Long non-coding RNAs (lncRNAs) are critical in regulating gene expression and play a significant role in cancer-associated immune responses. However, the association between lncRNA expression patterns and TMB levels and survival outcomes remains unknown in colon cancer.

Methods

In colon cancer patients from The Cancer Genome Atlas Program (TCGA), a multi-lncRNAs based classifier for predicting TMB levels was established using the least absolute shrinkage and selection operator (LASSO) method. The association between classifier index and immune-related characteristics of patients was also investigated. Quantitative polymerase chain reaction (qPCR) was used to verify the expression levels of these lncRNAs in normal and CRC cell lines.

Results

The multi-lncRNAs based classifier had ability to predict TMB level of patients with accuracy (AUC= 0.70), and the general applicability of this classifier was proved in the validation set (AUC= 0.71) and the pooled set (AUC= 0.70). The classifier index was related to three immune checkpoints (PD1, PD-L1, and CTLA-4), the infiltration level of immune cells, and immune response-related score (IFN-γ score, gene expression profiles (GEP) score, cytolytic activity (CYT) score and MHC score). A nomogram, which integrates classifier and some common clinical information, was able to predict the overall survival of colon cancer patients accurately.

Conclusion

LncRNA expression patterns are associated with TMB, which may serve as a classifier to predict the TMB in colon cancer patients. The nomogram could potentially evaluate survival outcomes and provide a reference to better manage colon cancer patients.

Identification of immune-related lncRNA signature for predicting immune checkpoint blockade and prognosis in hepatocellular carcinoma

BACKGROUND

An increasing body of evidence has supported that long non-coding RNAs (lncRNAs) can play as essential roles of various physiological process and pathological diseases. We aimed to construct a robust immune-associated lncRNA signature associated with the prognosis for HCC survival prediction.

METHODS

7 immune-associated lncRNAs presenting significant correlation with survival were screened through stepwise univariate Cox regression and LASSO algorithm, and multivariate Cox regression. Kaplan-Meier analysis, proportional hazards model, and ROC analyses further conducted. Gene set enrichment analysis (GSEA) was applied for functional annotation. We conducted quantitative real-time polymerase chain reaction to determine NRAV expression and preliminarily explored the latent role of NRAV in prognosis of HCC patients.

RESULTS

Finally, 7 immune-related lncRNA signature composed of AC007405.3, AC023157.3, NRAV, CASC19, MSC-AS1, GASAL1, and LINC00942 were validated. This lncRNAs signature can serve as an independent predictive biomolecular factor. This signature was further confirmed in the validation group and the entire cohort. We demonstrated that NRAV was significantly upregulated in HCC cell lines and it may serve as a key regulator in HCC. Our signature was associated to apoptosis and immunologic characteristics. This signature mediated immune cell infiltration (i.e., Dendritic, etc.,) and immune checkpoint blockade (ICB) immunotherapy-related molecules (i.e., CD274, etc.,).

CONCLUSION

This immune-related lncRNA signature possesses promising prognostic value in HCC and may have the potentiality to predict clinical outcome of ICB immunotherapy.

Identification of a Nine Immune-Related lncRNA Signature as a Novel Diagnostic Biomarker for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) ranks fifth among common cancers and is the second most common cause of cancer-related mortality worldwide. This study is aimed at identifying an immune-related long noncoding RNA (lncRNA) signature as a potential biomarker with prognostic value to improve early diagnosis and provide potential therapeutic targets for HCC patients. The subjects of this study were HCC samples with complete transcriptome data and clinical information downloaded from The Cancer Genome Atlas (TCGA) database. We then extracted the immune-related mRNA and lncRNA expression profiles. Based on the expression profiles of immune-related lncRNAs, we identified a nine-lncRNA signature that was related to the progression of HCC. The risk score was calculated based on the expression level of the nine lncRNAs of each sample, which divided patients into high-risk and low-risk groups. We found that the increased risk score was associated with a poor prognosis of HCC patients. To assess the accuracy of the survival model, we calculated a receiver operating characteristic (ROC) for validation. The curve showed that the area under the curve (AUC) for the risk score was 0.792. Besides, both principal component analysis (PCA) and gene set enrichment analysis (GSEA) were further used for functional annotation. We found that the distribution patterns were different between the low-risk and high-risk groups in PCA, and the underlying mechanism by which the nine lncRNAs promoted the progression of HCC involved an abnormal immune status. Finally, we analyzed the infiltration of twenty-nine kinds of immune cells and the activation of immune function in HCC using the ssGSEA algorithm. The results showed that aDCs, iDCs, macrophages, Tfh, Th1, Treg, and NK cells were correlated with the progress of HCC patients. And the immune functions including APC costimulation, CCR, check point, HLA, MHC class I, and Type II IFN responses were also significantly different between the high-risk and low-risk groups. In conclusion, our study identified a nine-lncRNA signature with potential prognostic value for patients with HCC, which could be used as a new biomarker for the diagnosis and immunotherapy of HCC.

The potential of long noncoding RNAs for precision medicine in human cancer

Precision medicine promises to better classify patients by individual clinical and biological biomarkers, which may provide an accurate assessment of disease risk, diagnosis, prognosis and treatment response. Cancer frequently displays substantial inter-tumor and intra-tumor heterogeneity and hence oncology is well suited for application of precision approaches. Recent studies have demonstrated that dysregulated lncRNAs play pivotal roles in tumor heterogeneity. In this review, attention is focused on the potential applications of lncRNAs as biomarker candidates for cancer risk evaluation, detection, surveillance and prognosis. LncRNAs are often stable in clinical samples and easily detected. The functional implications and therapeutic potential of targeting lncRNAs in human cancer are further discussed. Finally, existing deficiencies and future perspectives in translating fundamental lncRNA knowledge into clinical practice are highlighted.

Extracellular Vesicles Derived From Colorectal Cancer Affects CD8 T Cells: An Analysis Based on Body Mass Index

Colorectal cancer (CRC) is one of the most widely diagnosed cancers worldwide. It has been shown that the body-mass index (BMI) of the patients could influence the tumor microenvironment, treatment response, and overall survival rates. Nevertheless, the mechanism on how BMI affects the tumorigenesis process, particularly the tumor microenvironment is still elusive. Herein, we postulate that extracellular vesicles (EVs) from CRC patients and non-CRC volunteers with different BMI could affect immune cells differently, in CD8 T cells particularly. We isolated the EVs from the archived serum of CRC patients with high and low BMI, as well as healthy controls with similar BMI status. The EVs were further characterized via electron microscopy, western blot and dynamic light scattering. Then, functional analysis was performed on CD8 T cells including apoptosis, cell proliferation, gene expression profiling and cytokine release upon co-incubation with the different EVs. Our results suggest that CRC-derived EVs were able to regulate the CD8 T cells. In some assays, low BMI EVs were functionally different than high BMI EVs. This study highlights the possible difference in the regulatory mechanism of cancer patients-derived EVs, especially on CD8 T cells.

The Non-Coding Landscape of Cutaneous Malignant Melanoma: A Possible Route to Efficient Targeted Therapy

Considered to be highly lethal if not diagnosed in early stages, cutaneous malignant melanoma is among the most aggressive and treatment-resistant human cancers, and its incidence continues to rise, largely due to ultraviolet radiation exposure, which is the main carcinogenic factor. Over the years, researchers have started to unveil the molecular mechanisms by which malignant melanoma can be triggered and sustained, in order to establish specific, reliable biomarkers that could aid the prognosis and diagnosis of this fatal disease, and serve as targets for development of novel efficient therapies. The high mutational burden and heterogeneous nature of melanoma shifted the main focus from the genetic landscape to epigenetic and epitranscriptomic modifications, aiming at elucidating the role of non-coding RNA molecules in the fine tuning of melanoma progression. Here we review the contribution of microRNAs and lncRNAs to melanoma invasion, metastasis and acquired drug resistance, highlighting their potential for clinical applications as biomarkers and therapeutic targets.

LncRNAs as tumor cell intrinsic factors that affect cancer immunotherapy

Long noncoding RNAs (lncRNAs) have been found to associate with all major types of malignancies and play important roles in regulating several hallmarks of cancer by interacting with proteins, DNA, and RNA. The possible functions of lncRNAs and their roles in the regulation of tumour growth will be reported and discussed in the present review. In our recent report, based on genetic mice models and a series of systematic analyses, we suggested that lncRNAs also play critical roles in the regulation of antigen presentation in tumour cells and allow tumour cells to escape immune surveillance, which further broadens the scope of understanding lncRNA functions and how they relate to cancer immunotherapy resistance.

Immune checkpoints and their inhibitors: Reappraisal of a novel diagnostic and therapeutic dimension in the urologic malignancies

Advances in molecular immunology have unveiled some of the complexity of the mechanisms regulating cellular immune responses and led to the successful targeting of immune checkpoints in attempts to enhance antitumor T cell responses. Surgery, chemotherapy, and radiation therapy have been the mainstay of treatment in urologic malignancies. Immune checkpoint molecules such as cytotoxic T-lymphocyte associated protein-4, programmed cell death protein-1, and programmed death-ligand 1 have been shown to play central roles in evading cancer immunity. Thus these molecules have been targeted by inhibitors for the management of cancers forming the basis of immunotherapy. Immunotherapy is now among the first line therapeutic options for metastatic renal cell carcinomas. In advanced bladder cancer, immunotherapy is the standard of care in the second line and the first line for cisplatin ineligible patients. There continues to be ongoing research to identify the role if any of immunotherapy in testicular, prostatic, and penile cancers. The ideal biomarker for response to immunotherapy is still elusive. Although programmed death-ligand 1 immunohistochemical testing has been widely used across the globe as a biomarker for immunotherapy, companion diagnostic tests have inherent issues with testing and reporting and cannot have universal applicability. Additional biomarkers including, tumor mutational burden, deficient mismatch repair, high microsatellite instability, and immune gene expression profiling are being evaluated in various clinical trials. This review appraises the data of immunotherapy in the management of urologic malignancies.

lncRNA and Mechanisms of Drug Resistance in Cancers of the Genitourinary System

Available systemic treatment options for cancers of the genitourinary system have experienced great progress in the last decade. However, a large proportion of patients eventually develop resistance to treatment, resulting in disease progression and shorter overall survival. Biomarkers indicating the increasing resistance to cancer therapies are yet to enter clinical routine. Long non-coding RNAs (lncRNA) are non-protein coding RNA transcripts longer than 200 nucleotides that exert multiple types of regulatory functions of all known cellular processes. Increasing evidence supports the role of lncRNAs in cancer development and progression. Additionally, their involvement in the development of drug resistance across various cancer entities, including genitourinary malignancies, are starting to be discovered. Consequently, lncRNAs have been suggested as factors in novel therapeutic strategies to overcome drug resistance in cancer. In this review, the existing evidences on lncRNAs and their involvement in mechanisms of drug resistance in cancers of the genitourinary system, including renal cell carcinoma, bladder cancer, prostate cancer, and testicular cancer, will be highlighted and discussed to facilitate and encourage further research in this field. We summarize a significant number of lncRNAs with proposed pathways in drug resistance and available reported studies.

PD-1, CTLA4, PD-L1 and PD-L2 DNA methylation in papillary thyroid carcinoma

Aim: We investigated DNA methylation patterns of immune checkpoint genes PD-1, PD-L1, PD-L2, CTLA4 and an adjacent long noncoding RNA in papillary thyroid carcinoma (PTC). Materials & methods: DNA methylation and mRNA expression were examined in PTCs. DNA methylation was correlated with mRNA expression, BRAF and RAS mutational status, and immune cell infiltration. Results: Inverse correlations between DNA methylation and mRNA expression were observed. Immune checkpoint expression correlated positively, and DNA methylation negatively, with immune cell infiltration. Higher DNA methylation levels accompanied by lower immune checkpoint expression were observed in RAS-mutated tumors. Conclusion: We suggest epigenetic regulation of immune checkpoints in PTC. Methylation was associated with BRAF and RAS mutation status. DNA methylation might be a promising biomarker candidate in the context of immunotherapies in PTC.

Bioinformatics profiling integrating a four immune-related long non-coding RNAs signature as a prognostic model for papillary renal cell carcinoma

Background: Papillary renal cell carcinoma (pRCC) was the 2^nd most common subtype, accounting for approximately 15% incidence of renal cell carcinoma (RCC). Immune related long non-coding RNAs (IR-lncRs) plentiful in immune cells and immune microenvironment (IME) are potential in evaluating prognosis and assessing the effects of immunotherapy. A completed and meaningful IR-lncRs analysis based on abundant pRCC gene samples from The Cancer Genome Atlas (TCGA) will provide insight in this field.

Results: 17 IR-lncRs were selected by Pearson correlation analysis of immune score and the lncRNA expression level, and 5 sIRlncRs were significantly correlated with the OS of pRCC patients. 4 sIRlncRs (AP001267.3, AC026471.3, SNHG16 and ADAMTS9-AS1) with the most remarkable prognostic values were identified to establish the IRRS model and the OS of the low-risk group was longer than that in the high-risk group. The IRRS was certified as an independent prognosis factor and correlated with the OS. The high-risk group and low-risk group showed significantly different distributions and immune status through PCA and GSEA. In addition, we further found the expression levels of SNHG16 was remarkably enhanced in female patients with more advanced T-stages, but ADAMTS9-AS1 showed the opposite results.

Conclusion: The IRRS model based on the identified 4 sIRlncRs showed the significant values on forecasting prognoses of pRCC patients, with the longer OS in the low-risk group.

Methods: We integrated the expression profiles of LncRNA and overall survival (OS) in the 322 pRCC patients based on the TCGA dataset. The immune scores calculated on account of the expression level of immune-related genes were used to verify the most relevant IR-lncRs. Survival-related IR-lncRs (sIRlncRs) were estimated by COX regression analysis in pRCC patients. The high-risk group and low-risk group were identified by the median immune-related risk score (IRRS) model established by the screened sIRlncRs. Functional annotation was displayed by gene set enrichment analysis (GSEA) and principal component analysis (PCA), and the immune composition and purity of the tumor were evaluated through microenvironment cell count records. The expression levels of sIRlncRs of pRCC samples were verified by real-time quantitative PCR.

Long noncoding RNA loss in immune suppression in cancer

Long noncoding RNAs (lncRNAs) have multiple functions in the regulation of cellular homeostasis. In recent years, numerous studies have shown that tumor-associated lncRNAs play key roles in promoting and maintaining tumor initiation and progression by shaping the tumor microenvironment through changing tumor cell intrinsic properties. Here, we focus on the roles of lncRNAs in cancer immunology. In the first part, we provide an overview of the roles played by lncRNAs and their deregulation in cancer at the cancer cell- and tumor microenvironment-associated immune cell levels. We go on to describe preclinical strategies for targeting lncRNAs, particularly highlighting the effects on tumor microenvironments. We then discuss the possibility of combining lncRNA targeting and tumor immune checkpoint inhibitor antibodies to treat cancer.

Immune-related long noncoding RNA signature for predicting survival and immune checkpoint blockade in hepatocellular carcinoma

Long noncoding RNAs (lncRNAs) show multiple functions, including immune response. Recently, the immune-related lncRNAs have been reported in some cancers. We first investigated the immune-related lncRNA signature as a potential target in hepatocellular carcinoma (HCC) survival. The training set (n = 368) and the independent external validation cohort (n = 115) were used. Immune genes and lncRNAs coexpression were constructed to identify immune-related lncRNAs. Cox regression analyses were perfumed to establish the immune-related lncRNA signature. Regulatory roles of this signature on cancer pathways and the immunologic features were investigated. The correlation between immune checkpoint inhibitors and this signature was examined. In this study, the immune-related lncRNA signature was identified in HCC, which could stratify patients into high- and low-risk groups. This immune-related lncRNA signature was correlated with disease progression and worse survival and was an independent prognostic biomarker. Our immune-related lncRNA signature was still a powerful tool in predicting survival in each stratum of age, gender, and tumor stage. This signature mediated cell cycle, glycolysis, DNA repair, mammalian target of rapamycin signaling, and immunologic characteristics (i.e., natural killer cells vs. Th1 cells down, etc). This signature was associated with immune cell infiltration (i.e., macrophages M0, Tregs, CD4 memory T cells, and macrophages M1, etc.,) and immune checkpoint blockade (ICB) immunotherapy-related molecules (i.e., PD-L1, PD-L2, and IDO1). Our findings suggested that the immune-related lncRNA signature had an important value for survival prediction and may have the potential to measure the response to ICB immunotherapy. This signature may guide the selection of the immunotherapy for HCC.

Resistance to PD-L1/PD-1 Blockade Immunotherapy. A Tumor-Intrinsic or Tumor-Extrinsic Phenomenon?

Cancer immunotherapies targeting immune checkpoints such as programmed cell-death protein 1 (PD-1) and its ligand programmed cell-death 1 ligand 1 (PD-L1), are revolutionizing cancer treatment and transforming the practice of medical oncology. However, despite all the recent successes of this type of immunotherapies, most patients are still refractory and present either intrinsic resistance or acquired resistance. Either way, this is a major clinical problem and one of the most significant challenges in oncology. Therefore, the identification of biomarkers to predict clinical responses or for patient stratification by probability of response has become a clinical necessity. However, the mechanisms leading to PD-L1/PD-1 blockade resistance are still poorly understood. A deeper understanding of the basic mechanisms underlying resistance to cancer immunotherapies will provide insight for further development of novel strategies designed to overcome resistance and treatment failure. Here we discuss some of the major molecular mechanisms of resistance to PD-L1/PD-1 immune checkpoint blockade and argue whether tumor intrinsic or extrinsic factors constitute main determinants of response and resistance.