Search

Simple Summary: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related morbidity and mortality. In the last decade, a breakthrough in the treatment landscape of HCC has been experienced. The unprecedented number of therapeutic options for advanced stages has made the selection of sequence strategies more complex and the need for biomarkers of treatment response or tumor escape more urgent. The understanding of molecular events leading to drug resistance has identified noncoding RNAs as promising therapeutic targets. Preclinical studies testing the combined efficacy of noncoding RNAs and clinically available drugs represent a crucial step to prevent/limit the onset of drug resistance in advanced cases. The incidence of hepatocellular carcinoma (HCC) is increasing, and 40% of patients are diagnosed at advanced stages. Over the past 5 years, the number of clinically available treatments has dramatically increased for HCC, making patient management particularly complex. Immune checkpoint inhibitors (ICIs) have improved the overall survival of patients, showing a durable treatment benefit over time and a different response pattern with respect to tyrosine kinase inhibitors (TKIs). Although there is improved survival in responder cases, a sizeable group of patients are primary progressors or are ineligible for immunotherapy. Indeed, patients with nonviral etiologies, such as nonalcoholic steatohepatitis (NASH), and alterations in specific driver genes might be less responsive to immunotherapy. Therefore, improving the comprehension of mechanisms of drug resistance and identifying biomarkers that are informative of the best treatment approach are required actions to improve patient survival. Abundant evidence indicates that noncoding RNAs (ncRNAs) are pivotal players in cancer. Molecular mechanisms through which ncRNAs exert their effects in cancer progression and drug resistance have been widely investigated. Nevertheless, there are no studies summarizing the synergistic effect between ncRNA-based strategies and TKIs or ICIs in the preclinical setting. This review aims to provide up-to-date information regarding the possible use of ncRNAs as therapeutic targets in association with molecular-targeted agents and immunotherapies and as predictive tools for the selection of optimized treatment options in advanced HCCs. [ABSTRACT FROM AUTHOR]

Simple Summary: Glioblastoma is a grade IV glioma of heterogeneous nature, which complicates disease pathophysiology and biomarker research. The aim of this meta-analysis was to identify long non-coding RNAs (lncRNAs) and protein-coding genes (PCGs) that are differentially expressed in glioblastoma. Additionally, small RNA-seq of glioblastoma tissues was performed to identify differentially expressed microRNAs (miRNAs) compared to normal tissue controls. The meta-analysis identified 98 and 360 differentially expressed lncRNAs (DElncRNAs) and PCGs (DEPCGs), respectively, in addition to five differentially expressed miRNAs (DEmiRNAs) identified by small RNA-seq. Co-expression correlation network clustering of DElncRNAs/DEPCGs identified a functionally relevant sub-cluster containing DANCR and SNHG6, with DElncRNAs overlapping with TCGA-GBM output. Analysis of the pathways associated with these DElncRNAs and DEPCGs revealed an association with a novel cell death pathway, ferroptosis. Thus, our results confirm the involvement of ferroptosis in glioblastoma pathophysiology and present several candidates for further research Glioblastoma is a devastating grade IV glioma with poor prognosis. Identification of predictive molecular biomarkers of disease progression would substantially contribute to better disease management. In the current study, we performed a meta-analysis of different RNA-seq datasets to identify differentially expressed protein-coding genes (PCGs) and long non-coding RNAs (lncRNAs). This meta-analysis aimed to improve power and reproducibility of the individual studies while identifying overlapping disease-relevant pathways. We supplemented the meta-analysis with small RNA-seq on glioblastoma tissue samples to provide an overall transcriptomic view of glioblastoma. Co-expression correlation of filtered differentially expressed PCGs and lncRNAs identified a functionally relevant sub-cluster containing DANCR and SNHG6, with two novel lncRNAs and two novel PCGs. Small RNA-seq of glioblastoma tissues identified five differentially expressed microRNAs of which three interacted with the functionally relevant sub-cluster. Pathway analysis of this sub-cluster identified several glioblastoma-linked pathways, which were also previously associated with the novel cell death pathway, ferroptosis. In conclusion, the current meta-analysis strengthens evidence of an overarching involvement of ferroptosis in glioblastoma pathogenesis and also suggests some candidates for further analyses. [ABSTRACT FROM AUTHOR]

Simple Summary: Thyroid tumors represent the most common neoplastic pathology of the endocrine system. Mutations occurring in oncogenes and tumor suppressor genes are responsible for thyroid carcinogenesis; however, the complete mutational landscape characterizing these neoplasias has not been completely unveiled. It has been established that only the 2% of the human genome codes for proteins, suggesting that the vast majority of the genome has regulatory capabilities, which, if altered, could account for the onset of cancer. Hence, many scientific efforts are currently focused on the characterization of the heterogeneous class of noncoding RNAs, which represent an abundant part of the transcribed noncoding genome. In this review, we mainly focus on the involvement of microRNAs, long noncoding RNAs, and pseudogenes in thyroid cancer. The determination of the diagnosis, prognosis, and treatment of thyroid cancers based on the evaluation of the noncoding RNA network could allow the implementation of a more personalized approach to fighting these pathologies. Among the thyroid neoplasias originating from follicular cells, we can include well-differentiated carcinomas, papillary (PTC) and follicular (FTC) thyroid carcinomas, and the undifferentiated anaplastic (ATC) carcinomas. Several mutations in oncogenes and tumor suppressor genes have already been observed in these malignancies; however, we are still far from the comprehension of their full regulation-altered landscape. Even if only 2% of the human genome has the ability to code for proteins, most of the noncoding genome is transcribed, constituting the heterogeneous class of noncoding RNAs (ncRNAs), whose alterations are associated with the development of several human diseases, including cancer. Hence, many scientific efforts are currently focused on the elucidation of their biological role. In this review, we analyze the scientific literature regarding the involvement of microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and pseudogenes in FTC, PTC, and ATC. Recent findings emphasized the role of lncRNAs in all steps of cancer progression. In particular, lncRNAs may control progression steps by regulating the expression of genes and miRNAs involved in cell proliferation, apoptosis, epithelial–mesenchymal transition, and metastatization. In conclusion, the determination of the diagnosis, prognosis, and treatment of cancer based on the evaluation of the ncRNA network could allow the implementation of a more personalized approach to fighting thyroid tumors. [ABSTRACT FROM AUTHOR]

Simple Summary: Ewing sarcoma is a pediatric tumor characterized by chromosomal translocations, giving rise to the oncogene EWS-FLI1, which triggers the transcription of genes involved in neoplastic transformation including CCND1. In this work, we found that exposure to etoposide, a topoisomerase II inhibitor usually administered in combination with other drugs in the standard regimen for Ewing sarcoma treatment, induced cell death and reduced CCND1 levels. Etoposide acts, at least in part, by enhancing the expression of the pncCCND1_B, a promoter-associated noncoding RNA transcribed from the promoter region of the CCND1 gene. PncCCND1_B regulates in cisCCND1 expression by forming a molecular complex with the RNA binding protein Sam68 and the DNA/RNA helicase DHX9. Upon exposure to etoposide, the increase in pncCCND1_B coupled with the decrease in DHX9 expression promote epigenetic changes and formation of DNA:RNA hybrids at the promoter region of CCND1 gene, which downregulate its expression. Promoter-associated noncoding RNAs (pancRNAs) represent a class of noncoding transcripts driven from the promoter region of protein-coding or non-coding genes that operate as cis-acting elements to regulate the expression of the host gene. PancRNAs act by altering the chromatin structure and recruiting transcription regulators. PncCCND1_B is driven by the promoter region of CCND1 and regulates CCND1 expression in Ewing sarcoma through recruitment of a multi-molecular complex composed of the RNA binding protein Sam68 and the DNA/RNA helicase DHX9. In this study, we investigated the regulation of CCND1 expression in Ewing sarcoma cells upon exposure to chemotherapeutic drugs. Pan-inhibitor screening indicated that etoposide, a drug used for Ewing sarcoma treatment, promotes transcription of pncCCND1_B and repression of CCND1 expression. RNA immunoprecipitation experiments showed increased binding of Sam68 to the pncCCND1_B after treatment, despite the significant reduction in DHX9 protein. This effect was associated with the formation of DNA:RNA duplexes at the CCND1 promoter. Furthermore, Sam68 interacted with HDAC1 in etoposide treated cells, thus contributing to chromatin remodeling and epigenetic changes. Interestingly, inhibition of the ATM signaling pathway by KU 55,933 treatment was sufficient to inhibit etoposide-induced Sam68-HDAC1 interaction without rescuing DHX9 expression. In these conditions, the DNA:RNA hybrids persist, thus contributing to the local chromatin inactivation at the CCND1 promoter region. Altogether, our results show an active role of Sam68 in DNA damage signaling and chromatin remodeling on the CCND1 gene by fine-tuning transitions of epigenetic complexes on the CCND1 promoter. [ABSTRACT FROM AUTHOR]

Simple Summary: Imprecision and biases inherited in current cancer detection innovations hamper their applications at population level. Here, we employ deep learning neural networks and noncoding RNA biomarkers to develop an accurate cancer detection system to detect multiple cancer types. Our system binarily classifies 26 common cancers vs. normal with >96% AUC, and it can become a practical cancer screening system at population level. Detecting cancers at early stages can dramatically reduce mortality rates. Therefore, practical cancer screening at the population level is needed. To develop a comprehensive detection system to classify multiple cancer types, we integrated an artificial intelligence deep learning neural network and noncoding RNA biomarkers selected from massive data. Our system can accurately detect cancer vs. healthy objects with 96.3% of AUC of ROC (Area Under Curve of a Receiver Operating Characteristic curve), and it surprisingly reaches 78.77% of AUC when validated by real-world raw data from a completely independent data set. Even validating with raw exosome data from blood, our system can reach 72% of AUC. Moreover, our system significantly outperforms conventional machine learning models, such as random forest. Intriguingly, with no more than six biomarkers, our approach can easily discriminate any individual cancer type vs. normal with 99% to 100% AUC. Furthermore, a comprehensive marker panel can simultaneously multi-classify common cancers with a stable 82.15% accuracy rate for heterogeneous cancerous tissues and conditions. This detection system provides a promising practical framework for automatic cancer screening at population level. Key points: (1) We developed a practical cancer screening system, which is simple, accurate, affordable, and easy to operate. (2) Our system binarily classify cancers vs. normal with >96% AUC. (3) In total, 26 individual cancer types can be easily detected by our system with 99 to 100% AUC. (4) The system can detect multiple cancer types simultaneously with >82% accuracy. [ABSTRACT FROM AUTHOR]

Simple Summary: Uveal melanoma is a rare cancer with a bad prognosis that needs new therapeutic and diagnostic approaches. In this regard, long non-coding RNAs (lncRNAs) play a pivotal role in cancer, among other diseases, and could be used as therapeutic targets of diagnostic markers. In this review, lncRNAs related to uveal melanoma are revealed to better understand their mechanism of action, and inspire the development of novel treatment and diagnostic approaches. In addition, the interaction of lncRNA with other non-coding RNAs (ncRNAs) is also discussed since it might be one of the most relevant mechanisms of action. The compiled information is helpful not only for uveal melanoma experts, but also for ncRNA cancer researchers. Uveal melanoma (UM) is an intraocular cancer tumor with high metastatic risk. It is considered a rare disease, but 90% of affected patients die within 15 years. Non-coding elements (ncRNAs) such as long non-coding RNAs (lncRNAs) have a crucial role in cellular homeostasis maintenance, taking part in many critical cellular pathways. Their deregulation, therefore, contributes to the induction of cancer and neurodegenerative and metabolic diseases. In cancer, lncRNAs are implicated in apoptosis evasion, proliferation, invasion, drug resistance, and other roles because they affect tumor suppressor genes and oncogenes. For these reasons, lncRNAs are promising targets in personalized medicine and can be used as biomarkers for diseases including UM. [ABSTRACT FROM AUTHOR]

Simple Summary: Neurofibromatosis type 1 (NF1) is a common cancer predisposition genetic disease that is associated with significant morbidity and mortality. In this literature review, we discuss the major pathways in the nervous system that are affected by NF1, tumors that are associated with NF1, drugs that target these pathways, and genetic models of NF1. We also summarize the latest updates from clinical trials that are evaluating pharmacological agents to treat these tumors and discuss the efforts that are being made to cure the disease in the future Neurofibromatosis type 1 is an autosomal dominant genetic disease and a common tumor predisposition syndrome that affects 1 in 3000 to 4000 patients in the USA. Although studies have been conducted to better understand and manage this disease, the underlying pathogenesis of neurofibromatosis type 1 has not been completely elucidated, and this disease is still associated with significant morbidity and mortality. Treatment options are limited to surgery with chemotherapy for tumors in cases of malignant transformation. In this review, we summarize the advances in the development of targeted pharmacological interventions for neurofibromatosis type 1 and related conditions. [ABSTRACT FROM AUTHOR]

Simple Summary: Most glioblastoma patients succumb to the disease within 12 to 18 months, and only 9% are alive 2 years after diagnosis. Even with extensive research, the life expectancy of glioblastoma patients has not changed in decades. We aimed to identify differences in the transcriptomic profiles of glioblastoma patients with long and short survival. With large-scale transcriptomic analysis, we examined information from publicly available datasets (TCGA and CGGA) in combination with FFPE patient tissue samples. We identified one gene, the long noncoding RNA CRNDE, whose overexpression is directly correlated with poor patient survival. Therefore, we suggest its further confirmation as a negative prognostic glioblastoma biomarker. Glioblastoma management still lacks suitable diagnostic, predictive, and prognostic biomarkers for early disease diagnosis, and treatment follow-up. We believe our findings can serve as the basis for identification of new and potential suitable disease biomarkers by looking beyond the classical molecules (DNA, RNA, and proteins) into the noncoding genome. Glioblastoma is the most common and malignant brain malignancy worldwide, with a 10-year survival of only 0.7%. Aggressive multimodal treatment is not enough to increase life expectancy and provide good quality of life for glioblastoma patients. In addition, despite decades of research, there are no established biomarkers for early disease diagnosis and monitoring of patient response to treatment. High throughput sequencing technologies allow for the identification of unique molecules from large clinically annotated datasets. Thus, the aim of our study was to identify significant molecular changes between short- and long-term glioblastoma survivors by transcriptome RNA sequencing profiling, followed by differential pathway-activation-level analysis. We used data from the publicly available repositories The Cancer Genome Atlas (TCGA; number of annotated cases = 135) and Chinese Glioma Genome Atlas (CGGA; number of annotated cases = 218), and experimental clinically annotated glioblastoma tissue samples from the Institute of Pathology, Faculty of Medicine in Ljubljana corresponding to 2–58 months overall survival (n = 16). We found one differential gene for long noncoding RNA CRNDE whose overexpression showed correlation to poor patient OS. Moreover, we identified overlapping sets of congruently regulated differential genes involved in cell growth, division, and migration, structure and dynamics of extracellular matrix, DNA methylation, and regulation through noncoding RNAs. Gene ontology analysis can provide additional information about the function of protein- and nonprotein-coding genes of interest and the processes in which they are involved. In the future, this can shape the design of more targeted therapeutic approaches. [ABSTRACT FROM AUTHOR]

Simple Summary: Developing effective therapies for glioblastoma (GBM), the most common primary brain cancer, remains challenging due to the heterogeneity within tumors and therapeutic resistance that drives recurrence. Noncoding RNAs are transcribed from a large proportion of the genome and remain largely unexplored in their contribution to the evolution of GBM tumors. Here, we will review the general mechanisms of long, noncoding RNAs and the current knowledge of how these impact heterogeneity and therapeutic resistance in GBM. A better understanding of the molecular drivers required for these aggressive tumors is necessary to improve the management and outcomes of this challenging disease. Transcription occurs across more than 70% of the human genome and more than half of currently annotated genes produce functional noncoding RNAs. Of these transcripts, the majority—long, noncoding RNAs (lncRNAs)—are greater than 200 nucleotides in length and are necessary for various roles in the cell. It is increasingly appreciated that these lncRNAs are relevant in both health and disease states, with the brain expressing the largest number of lncRNAs compared to other organs. Glioblastoma (GBM) is an aggressive, fatal brain tumor that demonstrates remarkable intratumoral heterogeneity, which has made the development of effective therapies challenging. The cooperation between genetic and epigenetic alterations drives rapid adaptation that allows therapeutic evasion and recurrence. Given the large repertoire of lncRNAs in normal brain tissue and the well-described roles of lncRNAs in molecular and cellular processes, these transcripts are important to consider in the context of GBM heterogeneity and treatment resistance. Herein, we review the general mechanisms and biological roles of lncRNAs, with a focus on GBM, as well as RNA-based therapeutics currently in development. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer onset and progression are promoted by high deregulation of the immune system. Recently, major advances in molecular and clinical cancer immunology have been achieved, offering new agents for the treatment of common tumors, often with astonishing benefits in terms of prolonged survival and even cure. Unfortunately, most tumors are still resistant to current immune therapy approaches, and basic knowledge of the resistance mechanisms is eagerly awaited. We focused our attention on noncoding RNAs, a class of RNA that regulates many biological processes by targeting selectively crucial molecular pathways and that, recently, had their role in cancer cell immune escape and modulation of the tumor microenvironment identified, suggesting their function as promising immunotherapeutic targets. In this scenario, we point out that noncoding RNAs are progressively emerging as immunoregulators, and we depict the current information on the complex network involving the immune system and noncoding RNAs and the promising therapeutic options under investigation. Novel opportunities are emerging from noncoding-RNAs for the treatment of immune-refractory tumors. Immunotherapy is presently one of the most promising areas of investigation and development for the treatment of cancer. While immune checkpoint-blocking monoclonal antibodies and chimeric antigen receptor (CAR) T-cell-based therapy have recently provided in some cases valuable therapeutic options, the goal of cure has not yet been achieved for most malignancies and more efforts are urgently needed. Noncoding RNAs (ncRNA), including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), regulate several biological processes via selective targeting of crucial molecular signaling pathways. Recently, the key roles of miRNA and lncRNAs as regulators of the immune-response in cancer have progressively emerged, since they may act (i) by shaping the intrinsic tumor cell and microenvironment (TME) properties; (ii) by regulating angiogenesis, immune-escape, epithelial-to-mesenchymal transition, invasion, and drug resistance; and (iii) by acting as potential biomarkers for prognostic assessment and prediction of response to immunotherapy. In this review, we provide an overview on the role of ncRNAs in modulating the immune response and the TME. We discuss the potential use of ncRNAs as potential biomarkers or as targets for development or clinical translation of new therapeutics. Finally, we discuss the potential combinatory approaches based on ncRNA targeting agents and tumor immune-checkpoint inhibitor antibodies or CAR-T for the experimental treatment of human cancer. [ABSTRACT FROM AUTHOR]

Head and neck squamous cell carcinoma (HNSCC) is one of the main neoformations of the head–neck region and is characterized by the presence of squamous carcinomatous cells of the multi-layered epithelium lining the oral cavity, larynx, and pharynx. The annual incidence of squamous cell carcinoma of the head and neck (HNSCC) comprises approximately 600,000 new cases globally. Currently, the 5-year survival from HNSCC is less than 50%. Surgical, radiotherapy, and chemotherapy treatments strongly compromise patient quality of life. MicroRNAs (miRNAs) are a family of small noncoding endogenous RNAs that function in regulating gene expression by regulating several biological processes, including carcinogenesis. The main upregulated microRNAs associated with oral carcinoma are miR-21, miR-455-5p, miR-155-5p, miR-372, miR-373, miR-29b, miR-1246, miR-196a, and miR-181, while the main downregulated miRNAs are miR-204, miR-101, miR-32, miR-20a, miR-16, miR-17, and miR-125b. miR-21 represents one of the first oncomirs studied. The present systematic review work was performed based on the preferred reporting items for systematic review and meta-analysis (PRISMA) protocol. A search was carried out in the PubMed and Scopus databases with the use of keywords. This search produced 628 records which, after the elimination of duplicates and the application of the inclusion and exclusion criteria, led to 7 included articles. The heterogeneity of the studies according to the odds ratio was high, with a Q value of 26.616 (p < 0.001), and the I2 was 77.457% for specificity. The heterogeneity was high, with a Q value of 25.243 (p < 0.001) and the I2 was 76.231% for sensitivity. The heterogeneity of data showed a Q value of 27.815 (p < 0.001) and the I2 was 78.429%. Therefore, the random-effects model was selected. The diagnostic odds ratio was 7.620 (95% CI 3.613–16.070). The results showed that the sensitivity was 0.771 (95% CI 0.680–0.842) (p < 0.001) while, for specificity, we found 0.663 (95% CI 0.538–0.770) (p < 0.001). The negative likelihood ratio (NLR) was 0.321 (95% CI 0.186–0.554), and the positive likelihood ratio (PLR) was 2.144 (95% CI 1.563–2.943). The summary ROC plot demonstrates that the diagnostic test presents good specificity and sensitivity, and the area under the curve (AUC), as calculated from the graph, was 0.79. [ABSTRACT FROM AUTHOR]