• rac1 GTP-Binding Protein/metabolism
• rac1 GTP-Binding Protein/chemistry
• Molecular Dynamics Simulation
• Humans
• Alternative Splicing
• Guanine Nucleotide Exchange Factors/metabolism
• Guanine Nucleotide Exchange Factors/chemistry
• Adaptor Proteins, Signal Transducing/metabolism
• Adaptor Proteins, Signal Transducing/chemistry
• Guanosine Diphosphate/metabolism
• Protein Binding
• Guanosine Triphosphate/metabolism
• Protein Conformation

Cancer has become the most life-threatening disease in the world. Mutations in and aberrant expression of genes encoding proteins and mutations in noncoding RNAs, especially long noncoding RNAs (lncRNAs), have significant effects in human cancers. LncRNAs have no protein-coding ability but function extensively in numerous physiological and pathological processes. Small nucleolar RNA host gene 3 (SNHG3) is a novel lncRNA and has been reported to be differentially expressed in various tumors, such as liver cancer, gastric cancer, and glioma. However, the interaction mechanisms for the regulation between SNHG3 and tumor progression are poorly understood. In this review, we summarize the results of SNHG3 studies in humans, animal models, and cells to underline the expression and role of SNHG3 in cancer. SNHG3 expression is upregulated in most tumors and is detrimental to patient prognosis. SNHG3 expression in lung adenocarcinoma remains controversial. Concurrently, SNHG3 affects oncogenes and tumor suppressor genes through various mechanisms, including competing endogenous RNA effects. A deeper understanding of the contribution of SNHG3 in clinical applications and tumor development may provide a new target for cancer diagnosis and treatment.

• Small nucleolar RNA host gene 3
• Long noncoding RNAs, Biomarker
• Clinical characters
• Molecular mechanism
• Competing endogenous RNA
• Liver cancer

• Animals
• Biomarkers
• Cell Proliferation/genetics
• Gene Expression Regulation, Neoplastic
• Humans
• Liver Neoplasms/genetics
• RNA, Long Noncoding/genetics
• RNA, Small Nucleolar/genetics

This study assessed the effects of Epstein-Barr virus (EBV) and one form of virally encoded BART long noncoding RNAs (lncRNAs) on cellular expression in epithelial cells grown in vitro and as tumors in vivo determined by high-throughput RNA sequencing of mRNA and small RNAs. Hierarchical clustering based on gene expression distinguished the cell lines from the tumors and distinguished the EBV-positive tumors and the BART tumors from the EBV-negative tumors. EBV and BART expression also induced specific expression changes in cellular microRNAs (miRs) and lncRNAs. Multiple known and predicted targets of the viral miRs, the induced cellular miRs, and lncRNAs were identified in the altered gene set. The changes in expression in vivo indicated that the suppression of growth pathways in vivo reflects increased expression of cellular miRs in all tumors. In the EBV and BART tumors, many of the targets of the induced miRs were not changed and the seed sequences of the nonfunctional miRs were found to have homologous regions within the BART lncRNA. The inhibition of these miR effects on known targets suggests that these induced miRs have reduced function due to sponging by the BART lncRNA. This composite analysis identified the effects of EBV on cellular miRs and lncRNAs with a functional readout through identification of the simultaneous effects on gene expression. Major shifts in gene expression in vivo are likely mediated by effects on cellular noncoding RNAs. Additionally, a predicted property of the BART lncRNA is to functionally inhibit the induced cellular miRs.

• Non-coding RNA
• Quadruple negative breast cancer (QNBC)
• Triple negative breast cancer (TNBC)
• circRNA
• lncRNA
• miRNA

The long non-coding RNA (lncRNA) SNHG3 has been shown to play oncogenic roles in several cancer types, but the mechanisms underlying its activity are poorly understood. In this study, we aimed to explore the clinical relevance and mechanistic role of SNHG3 in gastric cancer (GC). We found that SNHG3 expression in GC cell lines and tissues was significantly increased, and the upregulation of this lncRNA was correlated with tumor clinical stage and decreased patient survival. Knocking down SNHG3 in GC cells impaired the proliferative, migratory, and invasive activity in vitro and constrained in vivo GC xenograft tumor growth. Mechanistically, SNHG3 was found to bind and sequester miR-139-5p, thereby indirectly promoting the upregulation of the miR-139-5p target gene MYB. These data demonstrated that SNHG3 functions in an oncogenic manner to drive GC proliferation, migration, and invasion by regulating the miR-139-5p/MYB axis.

• MYB
• SNHG3
• gastric cancer
• miR-139-5p

In this work, an algorithm named mRBioM was developed for the identification of potential mRNA biomarkers (PmBs) from complete transcriptomic RNA profiles of gastric adenocarcinoma (GA).

mRBioM initially extracts differentially expressed (DE) RNAs (mRNAs, miRNAs, and lncRNAs). Next, mRBioM calculates the total information amount of each DE mRNA based on the coexpression network, including three types of RNAs and the protein-protein interaction network encoded by DE mRNAs. Finally, PmBs were identified according to the variation trend of total information amount of all DE mRNAs. Four PmB-based classifiers without learning and with learning were designed to discriminate the sample types to confirm the reliability of PmBs identified by mRBioM. PmB-based survival analysis was performed. Finally, three other cancer datasets were used to confirm the generalization ability of mRBioM.

mRBioM identified 55 PmBs (41 upregulated and 14 downregulated) related to GA. The list included thirteen PmBs that have been verified as biomarkers or potential therapeutic targets of gastric cancer, and some PmBs were newly identified. Most PmBs were primarily enriched in the pathways closely related to the occurrence and development of gastric cancer. Cancer-related factors without learning achieved sensitivity, specificity, and accuracy of 0.90, 1, and 0.90, respectively, in the classification of the GA and control samples. Average accuracy, sensitivity, and specificity of the three classifiers with machine learning ranged within 0.94–0.98, 0.94–0.97, and 0.97–1, respectively. The prognostic risk score model constructed by 4 PmBs was able to correctly and significantly (^∗∗∗p < 0.001) classify 269 GA patients into the high-risk (n = 134) and low-risk (n = 135) groups. GA equivalent classification performance was achieved using the complete transcriptomic RNA profiles of colon adenocarcinoma, lung adenocarcinoma, and hepatocellular carcinoma using PmBs identified by mRBioM.

GA-related PmBs have high specificity and sensitivity and strong prognostic risk prediction. MRBioM has also good generalization. These PmBs may have good application prospects for early diagnosis of GA and may help to elucidate the mechanism governing the occurrence and development of GA. Additionally, mRBioM is expected to be applied for the identification of other cancer-related biomarkers.

• biomarkers
• complete transcriptomic profiles
• generalization ability
• prognosis
• sample classification

RAS-related C3 botulinum toxin substrate 1 (Rac.1) is one of the important members of Rho GTPases. It is well known that Rac1 is a cytoskeleton regulation protein that regulates cell adhesion, morphology, and movement. Rac1 is highly expressed in different types of tumors, which is related to poor prognosis. Studies have shown that Rac1 not only participates in the tumor cell cycle, apoptosis, proliferation, invasion, migration and angiogenesis, but also participates in the regulation of tumor stem cell, thus promoting the occurrence of tumors. Rac1 also plays a key role in anti-tumor therapy and participates in immune escape mediated by the tumor microenvironment. In addition, the good prospects of Rac1 inhibitors in cancer prevention and treatment are exciting. Therefore, Rac1 is considered as a potential target for the prevention and treatment of cancer. The necessity and importance of Rac1 are obvious, but it still needs further study.

• Rac1
• cancer stemness
• metastasis
• therapy resistance
• tumorigenesis

Long noncoding RNAs (lncRNAs) are composed of > 200 nucleotides; they lack the ability to encode proteins but play important roles in a variety of human tumors. A large number of studies have shown that dysregulated expression of lncRNAs is related to tumor oncogenesis and progression. Emerging evidence shows that SNHG3 is a novel oncogenic lncRNA that is abnormally expressed in various tumors, including osteosarcoma, liver cancer, lung cancer, etc. SNHG3 primarily competes as a competitive endogenous RNA (ceRNA) that targets tumor suppressor microRNAs (miRNAs) and ceRNA mechanisms that regulate biological processes of tumors. In addition, abnormal expression of SNHG3 is significantly correlated with patient clinical features. Upregulation of SNHG3 contributes to biological functions, including tumor cell proliferation, migration, invasion and EMT. Therefore, SNHG3 may represent a potential diagnostic and prognostic biomarker, as well as a novel therapeutic target.

• Biomarker
• Cancer
• LncRNA
• SNHG3