Are Long Noncoding RNAs New Potential Biomarkers in Gastrointestinal Stromal Tumors (GISTs)? The Role of H19 and MALAT1

Establishing biomarkers for soft tissue sarcomas

INTRODUCTION

Soft tissue sarcomas (STS) are a rare and diverse group of tumors. Curative options are limited to localized disease, with surgery being the mainstay. Advanced stages are associated with a poor prognosis. Currently, the prognosis of the patient is based on histological classification and clinical characteristics, with only a few biomarkers having entered clinical practice.

AREAS COVERED

This article covers extensive recent research that has established novel potential biomarkers based on genomics, proteomics, and clinical characteristics. Validating and incorporating these biomarkers into clinical practice can improve prognosis, prediction of recurrence, and treatment response. Relevant literature was collected from PubMed, Scopus, and clinicaltrials.gov databases (November 2023).

EXPERT OPINION

Currently, defining prognostic markers in soft tissue sarcomas remains challenging. More studies are required, especially to personalize treatment through advanced genetic profiling and analysis using individual tumor and patient characteristics.

Harnessing the supremacy of MEG3 LncRNA to defeat gastrointestinal malignancies

Evidence suggests that long non-coding RNAs (lncRNAs) play a pivotal role in the carcinogenesis and progression of various human malignancies including gastrointestinal malignancies. This comprehensive review reports the functions and mechanisms of the lncRNA maternally expressed gene 3 (MEG3) involved in gastrointestinal malignancies. It summarizes its roles in mediating the regulation of cellular proliferation, apoptosis, migration, invasiveness, epithelial-to-mesenchymal transition, and drug resistance in several gastrointestinal cancers such as colorectal cancer, gall bladder cancer, pancreatic cancer, gastric cancer, esophageal cancer, cholangiocarcinoma, gastrointestinal stromal tumors and most importantly, hepatocellular carcinoma. In addition, the authors briefly highlight its implicated mechanistic role and interactions with different non-coding RNAs and oncogenic signaling cascades. This review presents the rationale for developing non coding RNA-based anticancer therapy via harnessing the power of MEG3 in gastrointestinal malignancies.

Integrated Analysis Identifies Novel Fusion Transcripts in Laterally Spreading Tumors Suggestive of Distinct Etiology Than Colorectal Cancers

BACKGROUND

Laterally spreading tumors (LSTs) of the colon and rectum are a class of abnormality which spreads laterally and appears ulcerated. They are a subclass of colorectal cancer (CRCs) with higher invasive potential than CRCs. Moreover, the etiology of LST still remains obscure.

METHODS

This study aimed to identify unique fusion transcript(s) in LSTs and evaluate their role in LST development and progression. RNA-Seq data for LST samples from the EMBL-EBI database were used to identify fusion transcripts. An integrated approach using Gene Ontology, pathway analysis, hub gene, and co-expression network analysis functionally characterized fusion transcripts to shed light upon the etiology of LSTs.

RESULT

We identified 48 unique fusion genes in LSTs. GO terms were enriched in mRNA metabolic (p ≤ 2.06E-06), mRNA stabilization (p ≤ 1.60E-05), in cytosol (1.20E-05), RBP (p ≤ 2.30E-04), and RNA binding activity (p ≤ 3.51E-08) processes. Pathway analysis revealed an inflammatory phenotype of LSTs suggesting a distinct etiology than CRCs as pathways were enriched in salmonella infection (p ≤ 4.41 e-03), proteoglycans in cancer (p ≤ 1.18 e-02), and insulin signaling (p ≤ 2.13 e-02). Our exclusion and inclusion criteria and hub gene analysis finally identified 9 hub genes. Co-expression analysis of hub genes identified the most significant transcription factors (NELFE, MYC, TAF1, MAX) and kinases (MAPK14, CSNK2A1, CDK1, MAPK1) which were implicated in various cancer pathways. Furthermore, an overall survival analysis of hub genes was performed. Our predefined criterion resulted in the enrichment of NPM1-PTMA (NPM1: p ≤ 0.005) and HIST1H2BO-YBX1 (YBX1: p ≤ 0.02) fusion transcripts, significantly associated with the patient's overall survival.

CONCLUSION

Our systematic analysis resulted in novel fusion genes in LSTs suggesting a different etiology than CRCs. Fusion transcripts were observed more frequently in non-granular LSTs suggestive of genetically more unstable than granular LST. We hypothesize that NPM1-PTMA and HIST1H2BO-YBX1 could be implicated in LST development and progression and may also serve as a prognostic or diagnostic biomarker in future for better management of LSTs.

Prognostic value of long non-coding RNA MALAT1 in hepatocellular carcinoma: A study based on multi-omics analysis and RT-PCR validation

Background: This study aimed to explore the relationship between MALAT1 and the prognosis of patients with hepatocellular carcinoma (HCC). Methods: We constructed a MALAT1 protein-protein interaction network using the STRING database and a network of competing endogenous RNAs (ceRNAs) using the StarBase database. Using data from the GEPIA2 database, we studied the association between genes in these networks and survival of patients with HCC. The potential mechanisms underlying the relationship between MALAT1 and HCC prognosis were studied using combined data from RNA sequencing, DNA methylation, and somatic mutation data from The Cancer Genome Atlas (TCGA) liver cancer cohort. Tumor tissues and 19 paired adjacent non-tumor tissues (PANTs) from HCC patients who underwent radical resection were analyzed for MALAT1 mRNA levels using real-time PCR, and associations of MALAT1 expression with clinicopathological features or prognosis of patients were analyzed using log-rank test and Gehan-Breslow-Wilcoxon test. Results: Five interacting proteins and five target genes of MALAT1 in the ceRNA network significantly correlated with poor survival of patients with HCC (p < 0.05). High MALAT1 expression was associated with mutations in two genes leading to poor prognosis and may upregulate some prognostic risk genes through methylation. MALAT1 was significantly co-expressed with various signatures of genes involved in HCC progression, including the cell cycle, DNA damage repair, mismatch repair, homologous recombination, molecular cancer m6A, exosome, ferroptosis, infiltration of lymphocyte (p < 0.05). The expression of MALAT1 was markedly upregulated in HCC tissues compared with PANTs. In Kaplan-Meier analysis, patients with high MALAT1 expression had significantly shorter progression-free survival (PFS) (p = 0.033) and overall survival (OS) (p = 0.023) than those with low MALAT1 expression. Median PFS was 19.2 months for patients with high MALAT1 expression and 52.8 months for patients with low expression, while the corresponding median OS was 40.5 and 78.3 months. In subgroup analysis of patients with vascular invasion, cirrhosis, and HBsAg positive or AFP positive, MALAT1 overexpression was significantly associated with shorter PFS and OS. Models for predicting PFS and OS constructed based on MALAT1 expression and clinicopathological features had moderate predictive power, with areas under the receiver operating characteristic curves of 0.661-0.731. Additionally, MALAT1 expression level was significantly associated with liver cirrhosis, vascular invasion, and tumor capsular infiltration (p < 0.05 for all). Conclusion: MALAT1 is overexpressed in HCC, and higher expression is associated with worse prognosis. MALAT1 mRNA level may serve as a prognostic marker for patients with HCC after hepatectomy.

Exploring the Dynamic Crosstalk between the Immune System and Genetics in Gastrointestinal Stromal Tumors

Gastrointestinal Stromal Tumors (GISTs) represent a paradigmatic model of oncogene addiction. Despite the well-known impact of the mutational status on clinical outcomes, we need to expand our knowledge to other factors that influence behavior heterogeneity in GIST patients. A growing body of studies has revealed that the tumor microenvironment (TME), mostly populated by tumor-associated macrophages (TAMs) and lymphocytes (TILs), and stromal differentiation (SD) have a significant impact on prognosis and response to treatment. Interestingly, even though the current knowledge of the role of immune response in this setting is still limited, recent pre-clinical and clinical data have highlighted the relevance of the TME in GISTs, with possible implications for clinical practice in the near future. Moreover, the expression of immune checkpoints, such as PD-L1, PD-1, and CTLA-4, and their relationship to the clinical phenotype in GIST are emerging as potential prognostic biomarkers. Looking forward, these variables related to the underlying tumoral microenvironment in GIST, though limited to still-ongoing trials, might lead to the potential use of immunotherapy, alone or in combination with targeted therapy, in advanced TKI-refractory GISTs. This review aims to deepen understanding of the potential link between mutational status and the immune microenvironment in GIST.

Clinicopathological value of long non-coding RNA profiles in gastrointestinal stromal tumor

Background

Long non-coding RNAs (lncRNAs) have been implicated in diagnosis and prognosis in various cancers. However, few lncRNA signatures have been established for prediction of gastrointestinal stromal tumors (GIST). We aimed to explore a lncRNA signature profile that associated with clinical relevance by mining data from Gene Expression Ominus (GEO) and Surveillance, Epidemiology, and End Results (SEER) Program.

Methods

Using a lncRNA-mining approach, we performed non-negative matrix factorization (NMF) consensus algorithm in Gastrointestinal stromal tumors (GISTs) cohorts (61 patients from GSE8167 and GSE17743) to cluster LncRNA expression profiles. Comparative markers selection, and Gene Set Enrichment Analysis (GSEA) algorithm were performed between distinct molecular subtypes of GIST. The survival rate of GIST patients from SEER stratified by gender were compared by Kaplan-Meier method and log-rank analysis. lncRNA-mRNA co-expression analysis was performed by Pearson correlation coefficients (PCC) using R package LINC. Somatic copy number alterations of GIST patients (GSE40966) were analyzed via web server GenePattern GISTIC2 algorithm.

Results

A total of four lncRNA molecular subtypes of GIST were identified with distinct biological pathways and clinical characteristics. LncRNA expression profiles well clustered the GIST samples into small size (<5 mm) and large size tumors (>5 mm), which is a fundamental index for GIST malignancy diagnosis. Several lncRNAs with abundant expression (LRRC75A-AS1, HYMAI, NEAT1, XIST and FTX) were closely associated with tumor size, which may suggest to be biomarkers for the GIST malignancy. Particularly, LRRC75A-AS1 was positively associated with tumor diameters and suggested an oncogene in GIST. Co-expression analysis suggested that chromosome region 17p11.2-p12 may contribute to the oncogenic process in malignant GIST. Interestingly, the gender had a strong influence on clustering by lncRNA expression profile. Data from the Surveillance, Epidemiology, and End Results (SEER) Program were further explored and 7983 patients who were diagnosed with GISTs from 1973 to 2014 were enrolled for analysis. The results also showed the favorable prognosis for female patients. The survival rate between male and female with GIST was statistically significant (P < 0.0001). Gene set enrichment analysis (GSEA) indicated distinct pathways between female and male, and malignant GIST was associated with several cancer metabolism and cell cycle associated pathways.

Conclusions

This lncRNAs-based classification for GISTs may provide a molecular classification applicable to individual GIST that has implications to influence lncRNA markers selection and prediction of tumor progression.

The Role of lncRNAs in Rare Tumors with a Focus on HOX Transcript Antisense RNA (HOTAIR)

Rare cancers are identified as those with an annual incidence of fewer than 6 per 100,000 persons and includes both epithelial and stromal tumors from different anatomical areas. The advancement of analytical methods has produced an accurate molecular characterization of most human cancers, suggesting a “molecular classification” that has allowed the establishment of increasingly personalized therapeutic strategies. However, the limited availability of rare cancer samples has resulted in very few therapeutic options for these tumors, often leading to poor prognosis. Long non coding RNAs (lncRNAs) are a class of non-coding RNAs mostly involved in tumor progression and drug response. In particular, the lncRNA HOX transcript antisense RNA (HOTAIR) represents an emergent diagnostic, prognostic and predictive biomarker in many human cancers. The aim of this review is to highlight the role of HOTAIR in rare cancers, proposing it as a new biomarker usable in the management of these tumors.

Integrated analysis of long non-coding RNAs and mRNAs associated with malignant transformation of gastrointestinal stromal tumors

Malignant transformation of gastrointestinal stromal tumors (GISTs) is correlated with poor prognosis; however, the underlying biological mechanism is not well understood. In the present study, low-risk (LR) GISTs, GISTs categorized as high-risk based on tumor size (HBS), and on mitotic rate (HBM) were collected for RNA sequencing. Candidate hub lncRNAs were selected by Oncomine analysis. Expression of a selected hub lncRNA, DNM3OS, and its correlation with patients’ prognosis were analyzed using FISH staining, followed with the determination of function and underlying mechanism. Our results revealed a series of key pathways and hub lncRNAs involved in the malignant transformation of GISTs. Oncomine analysis revealed a tight association between clinical signatures and DNM3OS and suggested that DNM3OS is a hub lncRNA that is involved in the Hippo signaling pathway. In addition, DNM3OS was upregulated in HBS, HBM, and HBS/M GIST and correlated with worse prognosis in patients with GISTs. In addition, DNM3OS promoted GIST cell proliferation and mitosis by regulating the expression of GLUT4 and CD36. Collectively, these results improve our understanding of the malignant transformation of GISTs and unveil a series of hub lncRNAs in GISTs.

LncRNAs in cancer: Regulatory and therapeutic implications

Long noncoding RNAs (lncRNAs) comprise a class of RNAs that do not code for proteins but are critical in regulating diverse cellular processes and maintaining cell function. In doing so, they have, in recent years, added a potentially new and significant layer of biological regulation. These are more than 200 nucleotides in length and are implicated in a range of diseases and therefore have emerged as potential tools for possible therapeutic intervention. For a disease as complex as cancer, emerging technologies suggest the presence of mutations on genomic loci that do not encode proteins, but give rise to lncRNAs. Aberrant signatures of lncRNAs are now a consistent feature of almost all types of cancers and their associated complications. Analysis and characterisation of functional pathways that lncRNAs are involved with suggest that lncRNAs interact with the chromatin, the protein or with the RNA to demonstrate their cellular effects to modulate proliferation, migration, differentiation, apoptosis and cell death. This review summarizes the current knowledge of lncRNAs, their implications in diverse types of cancer and their possible therapeutic utility.

Non-Coding RNAs, a Novel Paradigm for the Management of Gastrointestinal Stromal Tumors

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal malignancies found in the gastrointestinal tract. At a molecular level, most GISTs are characterized by gain-of-function mutations in V-Kit Hardy-Zuckerman 4 Feline Sarcoma Viral Oncogene Homolog (KIT) and Platelet Derived Growth Factor Receptor Alpha (PDGFRA), leading to constitutive activated signaling through these receptor tyrosine kinases, which drive GIST pathogenesis. In addition to surgery, treatment with the tyrosine kinase inhibitor imatinib forms the mainstay of GIST treatment, particularly in the advanced setting. Nevertheless, the majority of GISTs develop imatinib resistance. Biomarkers that indicate metastasis, drug resistance and disease progression early on could be of great clinical value. Likewise, novel treatment strategies that overcome resistance mechanisms are equally needed. Non-coding RNAs, particularly microRNAs, can be employed as diagnostic, prognostic or predictive biomarkers and have therapeutic potential. Here we review which non-coding RNAs are deregulated in GISTs, whether they can be linked to specific clinicopathological features and discuss how they can be used to improve the clinical management of GISTs.

Role of non-coding RNAs in pathogenesis of gastrointestinal stromal tumors

Gastrointestinal stromal tumors (GISTs) are considered the model solid malignancies of targeted therapy after the discovery of imatinib effectiveness against their tyrosine kinase inhibitors. Non-coding RNAs are molecules with no protein coding capacity that play crucial role to several biological steps of normal cell proliferation and differentiation. When the expression of these molecules found to be altered it seems that they affect the process of carcinogenesis in multiple ways, such as proliferation, apoptosis, differentiation, metastasis, and drug resistance. This review aims to provide an overview of the latest research papers and summarize the current evidence about the role of non-coding RNAs in pathogenesis of GISTs, including their potential clinical applications.