FLVCR1-AS1 and FBXL19-AS1: Two Putative lncRNA Candidates in Multiple Human Cancers

Potential role of lncRNA LOXL1-AS1 in human cancer development: a narrative review

Background and Objective

Long non-coding RNAs (lncRNAs) are a group of non-coding RNAs consisting of more than 200 nucleotides that are widely involved in various physiological and pathobiological processes in the body. LncRNA plays a crucial role in tumorigenesis and development with its unique functions, such as playing a role in a variety of biological processes of malignant tumors as a cancer-promoting factor or a cancer-suppressor factor. Lysyl oxidase-like protein 1-antisense RNA1 (LOXL1-AS1) is a novel functional lncRNA recently reported. This article reviews the current findings on the role of LOXL1-AS1 in cancer, and discusses the potential clinical significance and application prospects, in order to provide a theoretical basis and reference for the clinical diagnosis, treatment and screening of prognostic markers for malignant tumors.

Methods

The PubMed and Embase databases were searched using the keywords "cancer" or "tumor" or "neoplasm" and "LOXL1-AS1" for publications from 2018 to the present. The English literature was searched, with a focus on relevant articles. These articles validated the role and mechanism of LOXL1-AS1 in different cancers.

Key Content and Findings

LOXL1-AS1 is a recently reported novel lncRNA, which is abnormally expressed and upregulated in more than ten cancers, and is positively correlated with adverse clinical features and poor prognosis in cancer patients. LOXL1-AS1 competently binds to a variety of microRNAs to regulate the expression of downstream target genes and regulate related signaling pathways, including proliferation, migration, invasion and inhibition of malignant biological behaviors such as apoptosis.

Conclusions

LOXL1-AS1 is expected to become a novel biomarker for cancer diagnosis and treatment, with great potential as an independent prognostic indicator.

Prediction of immune infiltration and prognosis for patients with cholangiocarcinoma based on a cuproptosis-related lncRNA signature

Objective

Cholangiocarcinoma (CHOL) is a malignant disease that affects the digestive tract, and it is characterized by a poor prognosis. This research sought to explore the involvement of cuproptosis-related lncRNAs (CRLs) in the prognostic prediction and immune infiltration of cholangiocarcinoma.

Methods

The expression profiles and clinical data of CHOL patients were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and CRLs were defined via co-expression analysis. Two molecular clusters distinguished by cuproptosis-related genes (CRGs) were produced. Then a risk signature consisted by four CRLs was formed, and all samples were separated into low- and high-risk groups using a risk score. Kaplan-Meier survival analysis, principal component analysis, differentially expressed analysis, immune cell infiltration analysis, and sensitivities analysis of chemotherapy drugs were conducted between the two groups. Simultaneously, the expression values of four lncRNAs confirmed by real-time PCR in our own 20 CHOL samples were brought into the risk model.

Results

The CHOL samples could be differentiated into two molecular clusters, which displayed contrasting survival times. Additionally, patients with higher risk scores had significantly worse prognosis compared to those in the low-risk group. Furthermore, both immune infiltration and enrichment analysis revealed significant discrepancies in the tumor immune microenvironment (TIME) between different risk groups. Moreover, the predictive power and the correlation with CA19-9 and CEA of risk signature were validated in our own samples.

Conclusion

We developed a risk signature which could serve as an independent prognostic factor and offer a promising prediction for not only prognosis but also TIME in CHOL patients.

Identification of necroptosis-related lncRNAs for prognosis prediction and screening of potential drugs in patients with colorectal cancer

BACKGROUND

Tumor recurrence and metastasis lead to a poor prognosis in colorectal cancer (CRC). Necroptosis is closely related to the tumor microenvironment (TME) and affects tumor recurrence and metastasis. We aimed to stratify CRC patients according to necroptosis-related long noncoding RNAs (lncRNAs), which can be used to not only evaluate prognosis and improve precision medicine in clinical practice but also screen potential immunotherapy drugs.

AIM

To stratify CRC patients according to necroptosis-related lncRNAs (NRLs), which can be used to not only evaluate prognosis and improve precision medicine in clinical practice but also screen potential immunotherapy drugs.

METHODS

LncRNA expression profiles were collected from The Cancer Genome Atlas. NRLs were identified by coexpression analysis. Cox regression analysis identified a NRL signature. Then, the value of this signature was comprehensively and multidimensionally evaluated, and its reliability for CRC prognosis prediction was assessed with clinical CRC data and compared with that of six other lncRNA signatures. Gene set enrichment analysis, TME analysis and half-maximal inhibitory concentration (IC₅₀) prediction were also performed according to the risk score (RS) of the signature.

RESULTS

An 8-lncRNA signature significantly associated with overall survival (OS) was constructed, and its reliability was validated with clinical CRC data. Most of the areas under the receiver operating characteristic curves (AUCs) values for 1-, 3- and 5-year OS for this signature were higher than those for the other six lncRNA signatures. OS, disease-specific survival and the progression-free interval were all significantly poorer in the high-risk group. The RS of the signature showed good concordance with the predicted prognosis, with AUCs for 1-, 3- and 5-year OS of 0.79, 0.81 and 0.77, respectively. Additionally, the calibration plots for this signature combined with clinical factors showed that this combination could effectively improve the ability to predict OS. The RS was correlated with tumor stage, lymph node metastasis and distant metastasis. Most of the enriched Kyoto Encyclopedia of Genes and Genomes and Gene Ontology terms were tumor metastasis-related pathways in the high-risk group; these patients showed greater infiltration of immunosuppressive cells, such as cancer-associated fibroblasts, hematopoietic stem cells and M2 macrophages, but less infiltration of infiltrating antitumor effector immune cells, such as cluster of differentiation 8⁺ T cells and regulatory T cells (Tregs). We explored additional potential immune checkpoint genes and potential immunotherapeutic and chemotherapeutic drugs with relatively low IC₅₀ values.

CONCLUSION

We identified an NRL signature with strong fidelity that could stably predict prognosis and might be an indicator of the TME of CRC. Furthermore, additional potential immunotherapeutic and chemotherapeutic drugs were explored.

Using machine learning approach for screening metastatic biomarkers in colorectal cancer and predictive modeling with experimental validation

Colorectal cancer (CRC) liver metastasis accounts for the majority of fatalities associated with CRC. Early detection of metastasis is crucial for improving patient outcomes but can be delayed due to a lack of symptoms. In this research, we aimed to investigate CRC metastasis-related biomarkers by employing a machine learning (ML) approach and experimental validation. The gene expression profile of CRC patients with liver metastasis was obtained using the GSE41568 dataset, and the differentially expressed genes between primary and metastatic samples were screened. Subsequently, we carried out feature selection to identify the most relevant DEGs using LASSO and Penalized-SVM methods. DEGs commonly selected by these methods were selected for further analysis. Finally, the experimental validation was done through qRT-PCR. 11 genes were commonly selected by LASSO and P-SVM algorithms, among which seven had prognostic value in colorectal cancer. It was found that the expression of the MMP3 gene decreases in stage IV of colorectal cancer compared to other stages (P value < 0.01). Also, the expression level of the WNT11 gene was observed to increase significantly in this stage (P value < 0.001). It was also found that the expression of WNT5a, TNFSF11, and MMP3 is significantly lower, and the expression level of WNT11 is significantly higher in liver metastasis samples compared to primary tumors. In summary, this study has identified a set of potential biomarkers for CRC metastasis using ML algorithms. The findings of this research may provide new insights into identifying biomarkers for CRC metastasis and may potentially lay the groundwork for innovative therapeutic strategies for treatment of this disease.

BBOX1-AS1: A novel oncogenic long non-coding RNA in human cancers

Long non-coding RNAs (lncRNAs) are transcripts that contain more than 200 nucleotides. Despite the fact that they cannot encode proteins, many studies have identified roles they play in human cancers through diverse mechanisms. BBOX1-AS1, an oncogenic lncRNA, has recently been demonstrated to participate in tumorigenesis and progression of numerous cancers. Experimental evidence has determined that it participates in diverse biological process, including cell proliferation, invasion, migration, and apoptosis. The dysregulation of BBOX1-AS1 exerts its oncogenicity by acting as a competitive endogenous RNA (ceRNA) or by directly impacting downstream molecules and signaling pathways. Here we summarize the current understanding of the biological functions and clinical significance of BBOX1-AS1 for human cancers.

Crosstalk between long non-coding RNAs and p53 signaling pathway in colorectal cancer: A review study

Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide and the third leading cause of cancer-related fatalities. Long non-coding RNAs (lncRNAs) are key regulators of diverse physiological processes and are dysregulated in a wide range of pathophysiological circumstances such as CRC. Studies revealed that aberrant expressions of lncRNAs clearly modulate the expression level of p53 gene in CRC, thereby transactivating multiple downstream pathways. P53 is regarded as a crucial tumor suppressor gene which promotes cell-cycle arrest, DNA repair, senescence or apoptosis in response to cellular stresses. P53 is also mutated in CRC as well as various types of human malignancies. Therefore, lncRNAs interact with the p53 signaling pathway in numerus ways and significantly influence CRC-related processes. The current findings in the investigation of the crosstalk between lncRNAs and the P53 pathway in controlling CRC carcinogenesis, tumor progression, and therapeutic resistance are summarized in the this review. A deeper knowledge of CRC carcinogenesis may also have implications in CRC prevention and treatment through more research.