A pan-cancer atlas of cancer hallmark-associated candidate driver lncRNAs

Identification of a cancer driver gene-associated lncRNA signature for prognostic prediction and immune response evaluation in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) predominates among kidney cancer cases and is influenced by mutations in cancer driver genes (CDGs). However, significant obstacles persist in the early diagnosis and treatment of ccRCC. While various genetic models offer new hopes for improving ccRCC management, the relationship between CDG-related long non-coding RNAs (CDG-RlncRNAs) and ccRCC remains poorly understood. Therefore, this study aims to construct prognostic molecular features based on CDG-RlncRNAs to predict the prognosis of ccRCC patients, and aims to provide a new strategy to enhance clinical management of ccRCC patients.

Methods

This study employed Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses to comprehensively investigate the association between lncRNAs and CDGs in ccRCC. Leveraging The Cancer Genome Atlas (TCGA) dataset, we identified 97 prognostically significant CDG-RlncRNAs and developed a robust prognostic model based on these CDG-RlncRNAs. The performance of the model was rigorously validated using the TCGA dataset for training and the International Cancer Genome Consortium (ICGC) dataset for validation. Functional enrichment analysis elucidated the biological relevance of CDG-RlncRNA features in the model, particularly in tumor immunity. Experimental validation further confirmed the functional role of representative CDG-RlncRNA SNHG3 in ccRCC progression.

Results

Our analysis revealed that 97 CDG-RlncRNAs are significantly associated with ccRCC prognosis, enabling patient stratification into different risk groups. Development of a prognostic model incorporating key lncRNAs such as HOXA11-AS, AP002807.1, APCDD1L-DT, AC124067.2, and SNHG3 demonstrated robust predictive accuracy in both training and validation datasets. Importantly, risk stratification based on the model revealed distinct immune-related gene expression patterns. Notably, SNHG3 emerged as a key regulator of the ccRCC cell cycle, highlighting its potential as a therapeutic target.

Conclusions

Our study established a concise CDG-RlncRNA signature and underscored the pivotal role of SNHG3 in ccRCC progression. It emphasizes the clinical relevance of CDG-RlncRNAs in prognostic prediction and targeted therapy, offering potential avenues for personalized intervention in ccRCC.

Long Non-Coding RNAs as "MYC Facilitators"

In this article, we discuss a class of MYC-interacting lncRNAs (long non-coding RNAs) that share the following criteria: They are direct transcriptional targets of MYC. Their expression is coordinated with the expression of MYC. They are required for sustained MYC-driven cell proliferation, and they are not essential for cell survival. We refer to these lncRNAs as "MYC facilitators" and discuss two representative members of this class of lncRNAs, SNHG17 (small nuclear RNA host gene) and LNROP (long non-coding regulator of POU2F2). We also present a general hypothesis on the role of lncRNAs in MYC-mediated transcriptional regulation.

Decoding the associations between cell functional states in head and neck cancer based on single-cell transcriptome

OBJECTIVES

Systematically identifying cancer cell functional states, especially their associations, is key to understanding the pathogenesis of cancers.

MATERIALS AND METHODS

Here, we systematically identified six cancer-related states, including epithelial-mesenchymal transition (EMT), immune response, epithelial differentiation, stress, G1/S and G2/M phases, in head and neck squamous cell carcinoma (HNSCC) based on single-cell RNA-sequencing (scRNA-seq).

RESULTS AND CONCLUSION

We defined the association patterns between these functional states and found the patterns were correlated with the state activity. Particularly, immune response and EMT were negatively, positively, or non-significantly correlated in samples with the highest immune response activity, the lowest activity of the two states, or with the highest EMT activity, respectively. Combining scRNA-seq data of immune cells and four independent HNSCC cohorts, we found the negative relationship between EMT and immune response was correlated with an activated immune microenvironment and a longer survival, while the non-significant relationship was correlated with an immunosuppressed microenvironment and a poor prognosis. Collectively, our results provide insight into the association patterns between functional states in HNSCC, and may facilitate the elucidation of the interactions between cancer cells and immune system during cancer progression.

Multiomics Analysis of Neuroblastoma Cells Reveals a Diversity of Malignant Transformations

Neuroblastoma (NB) is a pediatric cancer of the developing sympathetic nervous system that exhibits significant variation in the stage of differentiation and cell composition of tumors. Global loss of DNA methylation and genomic 5-hydroxymethylcytosine (5hmC) is a hallmark of human cancers. Here, we used our recently developed single-base resolution approaches, hmTOP-seq and uTOP-seq, for construction of 5hmC maps and identification of large partially methylated domains (PMDs) in different NB cell subpopulations. The 5hmC profiles revealed distinct signatures characteristic to different cell lineages and stages of malignant transformation of NB cells in a conventional and oxygen-depleted environment, which often occurs in tumors. The analysis of the cell-type-specific PMD distribution highlighted differences in global genome organization among NB cells that were ascribed to the same lineage identity by transcriptomic networks. Collectively, we demonstrated a high informativeness of the integrative epigenomic and transcriptomic research and large-scale genome structure in investigating the mechanisms that regulate cell identities and developmental stages of NB cells. Such multiomics analysis, as compared with mutational studies, open new ways for identification of novel disease-associated features which bring prognostic and therapeutic value in treating this aggressive pediatric disease.

Identification and Roles of miR-29b-1-3p and miR29a-3p-Regulated and Non-Regulated lncRNAs in Endocrine-Sensitive and Resistant Breast Cancer Cells

Despite improvements in the treatment of endocrine-resistant metastatic disease using combination therapies in patients with estrogen receptor α (ERα) primary tumors, the mechanisms underlying endocrine resistance remain to be elucidated. Non-coding RNAs (ncRNAs), including microRNAs (miRNA) and long non-coding RNAs (lncRNA), are targets and regulators of cell signaling pathways and their exosomal transport may contribute to metastasis. Previous studies have shown that a low expression of miR-29a-3p and miR-29b-3p is associated with lower overall breast cancer survival before 150 mos. Transient, modest overexpression of miR-29b1-3p or miR-29a-3p inhibited MCF-7 tamoxifen-sensitive and LCC9 tamoxifen-resistant cell proliferation. Here, we identify miR-29b-1/a-regulated and non-regulated differentially expressed lncRNAs in MCF-7 and LCC9 cells using next-generation RNA seq. More lncRNAs were miR-29b-1/a-regulated in LCC9 cells than in MCF-7 cells, including DANCR, GAS5, DSCAM-AS1, SNHG5, and CRND. We examined the roles of miR-29-regulated and differentially expressed lncRNAs in endocrine-resistant breast cancer, including putative and proven targets and expression patterns in survival analysis using the KM Plotter and TCGA databases. This study provides new insights into lncRNAs in endocrine-resistant breast cancer.

lincRNA-RP11400K9.4 Regulates Cell Survival and Migration of Breast Cancer Cells

BACKGROUND/AIM

Several works in the past decades pointed out the key role of long intergenic non-coding RNA (lincRNA) in breast cancer development. Here in we report for first time the importance of deregulation of lincRNA RP11-400K9.4 in breast cancer cells which played a role in cell survival and migration.

MATERIALS AND METHODS

After RP11-400K9.4 silencing by short hairpin RNAs or overexpression by GeneBlocks, real-time quantitative polymerase chain reaction (RT-PCR), microarray, migration, proliferation and viability assay were performed.

RESULTS

RP11-400K9.4 expression was mainly in the cytoplasmic fraction in 2D culture. Overexpression of RP11-400K9.4 led to a reduction of migration by MCF-7 and MDA-MB-368 cells and an increase in cellular survival after UV-C radiation. Bioinformatic analyses highlighted irradiation-induced DNA damage, DNA repair and cell-cycle pathways as the mainly affected by RP11-400K9.4. Furthermore RT-PCR assay demonstrated the overexpression of baculoviral IAP repeat containing 3 (BIRC3) a known oncogene that promotes radiotherapy resistance through the nuclear factor kappa B (NFĸB) pathway.

CONCLUSION

RP11-400K9.4 participates in the modulation of migration and survival processes probably via the BIRC3/NFĸB pathway.

Identifying Key Somatic Copy Number Alterations Driving Dysregulation of Cancer Hallmarks in Lower-Grade Glioma

Somatic copy-number alterations (SCNAs) are major contributors to cancer development that are pervasive and highly heterogeneous in human cancers. However, the driver roles of SCNAs in cancer are insufficiently characterized. We combined network propagation and linear regression models to design an integrative strategy to identify driver SCNAs and dissect the functional roles of SCNAs by integrating profiles of copy number and gene expression in lower-grade glioma (LGG). We applied our strategy to 511 LGG patients and identified 98 driver genes that dysregulated 29 cancer hallmark signatures, forming 143 active gene-hallmark pairs. We found that these active gene-hallmark pairs could stratify LGG patients into four subtypes with significantly different survival times. The two new subtypes with similar poorest prognoses were driven by two different gene sets (one including EGFR, CDKN2A, CDKN2B, INFA8, and INFA5, and the other including CDK4, AVIL, and DTX3), respectively. The SCNAs of the two gene sets could disorder the same cancer hallmark signature in a mutually exclusive manner (including E2F_TARGETS and G2M_CHECKPOINT). Compared with previous methods, our strategy could not only capture the known cancer genes and directly dissect the functional roles of their SCNAs in LGG, but also discover the functions of new driver genes in LGG, such as IFNA5, IFNA8, and DTX3. Additionally, our method can be applied to a variety of cancer types to explore the pathogenesis of driver SCNAs and improve the treatment and diagnosis of cancer.

Identification of lncRNA Signature Associated With Pan-Cancer Prognosis

Long noncoding RNAs (lncRNAs) have emerged as potential prognostic markers in various human cancers as they participate in many malignant behaviors. However, the value of lncRNAs as prognostic markers among diverse human cancers is still under investigation, and a systematic signature based on these transcripts that related to pan-cancer prognosis has yet to be reported. In this study, we proposed a framework to incorporate statistical power, biological rationale, and machine learning models for pan-cancer prognosis analysis. The framework identified a 5-lncRNA signature (ENSG00000206567, PCAT29, ENSG00000257989, LOC388282, and LINC00339) from TCGA training studies (n = 1,878). The identified lncRNAs are significantly associated (all P ≤ 1.48E-11) with overall survival (OS) of the TCGA cohort (n = 4,231). The signature stratified the cohort into low- and high-risk groups with significantly distinct survival outcomes (median OS of 9.84 years versus 4.37 years, log-rank P = 1.48E-38) and achieved a time-dependent ROC/AUC of 0.66 at 5 years. After routine clinical factors involved, the signature demonstrated better performance for long-term prognostic estimation (AUC of 0.72). Moreover, the signature was further evaluated on two independent external cohorts (TARGET, n = 1,122; CPTAC, n = 391; National Cancer Institute) which yielded similar prognostic values (AUC of 0.60 and 0.75; log-rank P = 8.6E-09 and P = 2.7E-06). An indexing system was developed to map the 5-lncRNA signature to prognoses of pan-cancer patients. In silico functional analysis indicated that the lncRNAs are associated with common biological processes driving human cancers. The five lncRNAs, especially ENSG00000206567, ENSG00000257989 and LOC388282 that never reported before, may serve as viable molecular targets common among diverse cancers.

Establishing a consensus for the hallmarks of cancer based on gene ontology and pathway annotations

BACKGROUND

The hallmarks of cancer provide a highly cited and well-used conceptual framework for describing the processes involved in cancer cell development and tumourigenesis. However, methods for translating these high-level concepts into data-level associations between hallmarks and genes (for high throughput analysis), vary widely between studies. The examination of different strategies to associate and map cancer hallmarks reveals significant differences, but also consensus.

RESULTS

Here we present the results of a comparative analysis of cancer hallmark mapping strategies, based on Gene Ontology and biological pathway annotation, from different studies. By analysing the semantic similarity between annotations, and the resulting gene set overlap, we identify emerging consensus knowledge. In addition, we analyse the differences between hallmark and gene set associations using Weighted Gene Co-expression Network Analysis and enrichment analysis.

CONCLUSIONS

Reaching a community-wide consensus on how to identify cancer hallmark activity from research data would enable more systematic data integration and comparison between studies. These results highlight the current state of the consensus and offer a starting point for further convergence. In addition, we show how a lack of consensus can lead to large differences in the biological interpretation of downstream analyses and discuss the challenges of annotating changing and accumulating biological data, using intermediate knowledge resources that are also changing over time.

Long non-coding RNAs regulate the hallmarks of cancer in HPV-induced malignancies

High-risk human papillomavirus (HPV) is the most frequent sexually transmitted agent worldwide and is responsible for approximately 5% of human cancers. Identifying novel biomarkers and therapeutic targets for these malignancies requires a deeper understanding of the mechanisms involved in the progression of HPV-induced cancers. Long non-coding RNAs (lncRNAs) are crucial in the regulation of biological processes. Importantly, these molecules are key players in the progression of multiple malignancies and are able to regulate the development of the different hallmarks of cancer. This review highlights the action of lncRNAs in the regulation of cellular processes leading to the typical hallmarks of cancer. The regulation of lncRNAs by HPV oncogenes, their targets and also their mechanisms of action are also discussed, in the context of HPV-induced malignancies. Overall, accumulating data indicates that lncRNAs may have a significant potential to become useful tools for clinical practice as disease biomarkers or therapy targets.

LINC00885 a Novel Oncogenic Long Non-Coding RNA Associated with Early Stage Breast Cancer Progression

Long intergenic non-protein coding RNA 885 (LINC00885) was identified as significantly upregulated in breast ductal carcinoma in situ (DCIS). The aim of this study was to characterize the phenotypic effects and signaling pathways modulated by LINC00885 in non-invasive and invasive breast cancer models. We determined that LINC00885 induces premalignant phenotypic changes by increasing cell proliferation, motility, migration and altering 3D growth in normal and DCIS breast cell lines. Transcriptomic studies (RNA-seq) identified the main signaling pathways modulated by LINC00885, which include bioprocesses related to TP53 signaling pathway and proliferative signatures such as activation of EREG, EGFR and FOXM1 pathways. LINC00885 silencing in breast cancer lines overexpressing this lncRNA leads to downregulation of proliferation related transcripts such as EREG, CMYC, CCND1 and to significant decrease in cell migration and motility. TCGA-BRCA data analyses show an association between high LINC00885 expression and worse overall survival in patients with primary invasive breast carcinomas (p = 0.024), suggesting that the pro-tumorigenic effects of LINC00885 overexpression persist post-invasion. We conclude that LINC00885 behaves as a positive regulator of cell growth both in normal and DCIS breast cells possibly operating as a ceRNA and representing a novel oncogenic lncRNA associated with early stage breast cancer progression.

Integrated Dissection of lncRNA-Perturbated Triplets Reveals Novel Prognostic Signatures Across Cancer Types

Long noncoding RNA (lncRNA)/microRNA(miRNA)/mRNA triplets contribute to cancer biology. However, identifying significative triplets remains a major challenge for cancer research. The dynamic changes among factors of the triplets have been less understood. Here, by integrating target information and expression datasets, we proposed a novel computational framework to identify the triplets termed as “lncRNA-perturbated triplets”. We applied the framework to five cancer datasets in The Cancer Genome Atlas (TCGA) project and identified 109 triplets. We showed that the paired miRNAs and mRNAs were widely perturbated by lncRNAs in different cancer types. LncRNA perturbators and lncRNA-perturbated mRNAs showed significantly higher evolutionary conservation than other lncRNAs and mRNAs. Importantly, the lncRNA-perturbated triplets exhibited high cancer specificity. The pan-cancer perturbator OIP5-AS1 had higher expression level than that of the cancer-specific perturbators. These lncRNA perturbators were significantly enriched in known cancer-related pathways. Furthermore, among the 25 lncRNA in the 109 triplets, lncRNA SNHG7 was identified as a stable potential biomarker in lung adenocarcinoma (LUAD) by combining the TCGA dataset and two independent GEO datasets. Results from cell transfection also indicated that overexpression of lncRNA SNHG7 and TUG1 enhanced the expression of the corresponding mRNA PNMA2 and CDC7 in LUAD. Our study provides a systematic dissection of lncRNA-perturbated triplets and facilitates our understanding of the molecular roles of lncRNAs in cancers.

Transcriptome analysis reveals a reprogramming energy metabolism-related signature to improve prognosis in colon cancer

Although much progress has been made to improve treatment, colon cancer remains a leading cause of cancer death worldwide. Metabolic reprogramming is a significant ability of cancer cells to ensure the necessary energy supply in uncontrolled proliferation. Since reprogramming energy metabolism has emerged as a new hallmark of cancer cells, accumulating evidences have suggested that metabolism-related genes may serve as key regulators of tumorigenesis and potential biomarkers. In this study, we analyzed a set of reprogramming energy metabolism-related genes by transcriptome analysis in colon cancer and revealed a five-gene signature that could significantly predict the overall survival. The reprogramming energy metabolism-related signature could distinguish patients into high-risk and low-risk groups with significantly different survival times (P = 0.0011; HR = 1.92; 95% CI [1.29–2.87]). Its prognostic value was confirmed in another two independent colon cancer cohorts (P = 5.2e–04; HR = 2.09, 95%; CI [1.37–3.2] for GSE17538 and P = 3.8e−04; HR = 2.08, 95% CI [1.37–3.16] for GSE41258). By multivariable analysis, we found that the signature was independent of clinicopathological features. Its power in promoting risk stratification of the current clinical stage was then evaluated by stratified analysis. Moreover, the signature could improve the power of the TNM stage for the prediction of overall survival and could be used in patients who received adjuvant chemotherapy. Overall, our results demonstrated the important role of the reprogramming energy metabolism-related signature in promoting stratification of high-risk patients, which could be diagnostic of adjuvant therapy benefit.

Dissecting the Functional Mechanisms of Somatic Copy-Number Alterations Based on Dysregulated ceRNA Networks across Cancers

Somatic copy-number alterations (SCNAs) drive tumor growth and evolution. However, the functional roles of SCNAs across the genome are still poorly understood. We provide an integrative strategy to characterize the functional roles of driver SCNAs in cancers based on dysregulated competing endogenous RNA (ceRNA) networks. We identified 44 driver SCNAs in lower-grade glioma (LGG). The dysregulated patterns losing all correlation relationships dominated dysregulated ceRNA networks. Homozygous deletion of six genes in 9p21.3 characterized an LGG subtype with poor prognosis and contributed to the dysfunction of cancer-associated pathways in a complementary way. The pan-cancer analysis showed that different cancer types harbored different driver SCNAs through dysregulating the crosstalk with common ceRNAs. The same SCNAs destroyed their ceRNA networks through different miRNA-mediated ceRNA regulations in different cancers. Additionally, some SCNAs performed different functional mechanisms in different cancers, which added another layer of complexity to cancer heterogeneity. Compared with previous methods, our strategy could directly dissect functional roles of SCNAs from the view of ceRNA networks, which not only complemented the functions of protein-coding genes but also provided a new avenue to characterize the functions of noncoding RNAs. Also, our strategy could be applied to more types of cancers to identify pathogenic mechanism driven by the SCNAs.

Identification of cancer hallmark-associated gene and lncRNA cooperative regulation pairs and dictate lncRNA roles in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common malignant tumour in the oral and maxillofacial region. Numerous cancers share ten common traits ("hallmarks") that govern the transformation of normal cells into cancer cells. Long non-coding RNAs (lncRNAs) are important factors that contribute to tumorigenesis. However, very little is known about the cooperative relationships between lncRNAs and cancer hallmark-associated genes in OSCC. Through integrative analysis of cancer hallmarks, somatic mutations, copy number variants (CNVs) and expression, some OSCC-specific cancer hallmark-associated genes and lncRNAs are identified. A computational framework to identify gene and lncRNA cooperative regulation pairs (GLCRPs) associated with different cancer hallmarks is developed based on the co-expression and co-occurrence of mutations. The distinct and common features of ten cancer hallmarks based on GLCRPs are characterized in OSCC. Cancer hallmark insensitivity to antigrowth signals and self-sufficiency in growth signals are shared by most GLCRPs in OSCC. Some key GLCRPs participate in many cancer hallmarks in OSCC. Cancer hallmark-associated GLCRP networks have complex patterns and specific functions in OSCC. Specially, some key GLCRPs are associated with the prognosis of OSCC patients. In summary, we generate a comprehensive landscape of cancer hallmark-associated GLCRPs that can act as a starting point for future functional explorations, the identification of biomarkers and lncRNA-based targeted therapy in OSCC.

Adrenocortical tumors have a distinct, long, non-coding RNA expression profile and LINC00271 is downregulated in malignancy

BACKGROUND

Adrenocortical carcinoma is an aggressive malignancy with a low but variable overall survival rate. The role of in adrenocortical carcinoma is poorly understood. Thus, in this study we performed long noncoding RNA expression profiling in adrenocortical carcinomas, adrenocortical adenomas, and normal adrenal cortex.

METHODS

Long noncoding RNA expression profile using Human LncRNA/mRNA Expression Microarray V3.0 (Arraystar, Inc, Rockville, MD) was analyzed in samples from 11 adrenocortical adenomas, 9 adrenocortical carcinomas, and 5 normal adrenal cortex. Differentially expressed long noncoding RNAs were validated using TaqMan, real-time quantitative polymerase chain reaction with additional samples. The dataset from the adrenocortical carcinoma Cancer Genome Atlas Programproject was used to evaluate the prognostic utility of long noncoding RNAs.

RESULTS

Unsupervised hierarchical clustering showed distinct clustering of adrenocortical carcinoma samples compared with normal adrenal cortex and adrenocortical adenoma samples by long noncoding RNA expression profiles. A total of 874 long noncoding RNAs were differentially expressed between adrenocortical carcinoma and normal adrenal cortex. LINC00271 expression level was associated with prognosis, patients with low LINC00271 expression survived a shorter time than patients with high LINC00271 expression. Low LINC00271 expression was positively associated with WNT signaling, cell cycle, and chromosome segregation pathways.

CONCLUSION

Adrenocortical carcinoma has a distinct long noncoding RNA expression profile. LINC00271 is downregulated in adrenocortical carcinoma and appears to be involved in biologic pathways commonly dysregulated in adrenocortical carcinoma.

Non-Coding RNAs in Breast Cancer: Intracellular and Intercellular Communication

Non-coding RNAs (ncRNAs) are regulators of intracellular and intercellular signaling in breast cancer. ncRNAs modulate intracellular signaling to control diverse cellular processes, including levels and activity of estrogen receptor α (ERα), proliferation, invasion, migration, apoptosis, and stemness. In addition, ncRNAs can be packaged into exosomes to provide intercellular communication by the transmission of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) to cells locally or systemically. This review provides an overview of the biogenesis and roles of ncRNAs: small nucleolar RNA (snRNA), circular RNAs (circRNAs), PIWI-interacting RNAs (piRNAs), miRNAs, and lncRNAs in breast cancer. Since more is known about the miRNAs and lncRNAs that are expressed in breast tumors, their established targets as oncogenic drivers and tumor suppressors will be reviewed. The focus is on miRNAs and lncRNAs identified in breast tumors, since a number of ncRNAs identified in breast cancer cells are not dysregulated in breast tumors. The identity and putative function of selected lncRNAs increased: nuclear paraspeckle assembly transcript 1 (NEAT1), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), steroid receptor RNA activator 1 (SRA1), colon cancer associated transcript 2 (CCAT2), colorectal neoplasia differentially expressed (CRNDE), myocardial infarction associated transcript (MIAT), and long intergenic non-protein coding RNA, Regulator of Reprogramming (LINC-ROR); and decreased levels of maternally-expressed 3 (MEG3) in breast tumors have been observed as well. miRNAs and lncRNAs are considered targets of therapeutic intervention in breast cancer, but further work is needed to bring the promise of regulating their activities to clinical use.