Integrated Analysis of RNA Binding Protein-Related lncRNA Prognostic Signature for Breast Cancer Patients

Role of LncRNA MIR99AHG in breast cancer: Bioinformatic analysis and preliminary verification

Objective

This research was aimed to preliminarily explore the clinical roles and potential molecular mechanisms of MIR99AHG and its significant transcripts in breast cancer (BRCA).

Methods

Public databases were utilized to analyze the expression and prognostic roles of MIR99AHG and its transcripts. Relationships between MIR99AHG expression and immune cells infiltration were analyzed in Xiantao platform. In addition, co-expressed genes and interacting proteins of MIR99AHG were predicted. CancerSEA analyzed its relationship with functional states. Next, CNV status, DNA methylation, interacting transcription factors (TFs) and ceRNA network were analyzed to explore its possible mechanisms. Then, RNA ISH and FISH assays were used to detect its expression and location in BRCA tissues and cell lines, respectively. Finally, qRT-PCR was utilized to investigate MIR99AHG expression in cell lines.

Results

Compared with the corresponding normal tissues, MIR99AHG expression levels were lower in all BRCA subtypes, and luminal B's was the lowest one. And MIR99AHG expression was negatively related to the tumor stage. In addition, 4 transcripts (ENST00000619222.4, ENST00000418813.6, ENST00000602901.5 and ENST00000453910.5) of MIR99AHG showed significant differences in the expression. Databases also suggested that the high MIR99AHG expression levels indicated good prognosis, especially in patients without lymph node metastasis. Xiantao found that MIR99AHG was positively related to 17 immune cells and negatively linked with 2 immune cells. CancerSEA analysis showed no relationships between MIR99AHG and functional states. From GEPIA and BCIP databases, 19 co-expressed genes were highly related to these four significant transcripts of MIR99AHG. StarBase, RNAct and HDOCK showed that several tumor-associated proteins, including U2AF65, hnRNPC, AEBP2, CHIC1 and so on, might interact with MIR99AHG. Genetically, BRCA had a higher proportion of MIR99AHG CNV loss than CNV gain, and the high level of DNA methylation indicated a good prognosis. Furthermore, 19 TFs were predicted to combine with the promoter of MIR99AHG. Then, we screened out 10 miRNAs potentially interacting with the significant transcripts of MIR99AHG, and five were significantly increased in breast tumors compared to normal tissues, including miR-194-5p, miR-320 b and so on, which could combine 14 mRNAs. Through ISH and FISH assays, we verified that MIR99AHG was down-regulated in BRCA samples and cell lines in comparison to non-tumor tissues and mammary epithelial cell line (MCF10A), and MIR99AHG was located both in cytoplasm and nucleus. qRT-PCR assay also showed the lower expression of MIR99AHG in breast cancer cells than that in MCF10A.

Conclusion

These results indicate that MIR99AHG can be a favorable prognostic indicator for BRCA. ENST00000619222.4, ENST00000418813.6, ENST00000602901.5 and ENST00000453910.5 are significant transcripts and their down-regulation may play crucial roles in the progression of BRCA.

The Musashi RNA-binding proteins in female cancers: insights on molecular mechanisms and therapeutic relevance

RNA-binding proteins have increasingly been identified as important regulators of gene expression given their ability to bind distinct RNA sequences and regulate their fate. Mounting evidence suggests that RNA-binding proteins are involved in the onset and progression of multiple malignancies, prompting increasing interest in their potential for therapeutic intervention.The Musashi RNA binding proteins Musashi-1 and Musashi-2 were initially identified as developmental factors of the nervous system but have more recently been found to be ubiquitously expressed in physiological tissues and may be involved in pathological cell behavior. Both proteins are increasingly investigated in cancers given dysregulation in multiple tumor entities, including in female malignancies. Recent data suggest that the Musashi proteins serve as cancer stem cell markers as they contribute to cancer cell proliferation and therapy resistance, prompting efforts to identify mechanisms to target them. However, as the picture remains incomplete, continuous efforts to elucidate their role in different signaling pathways remain ongoing.In this review, we focus on the roles of Musashi proteins in tumors of the female - breast, endometrial, ovarian and cervical cancer - as we aim to summarize current knowledge and discuss future perspectives.

The current advances of lncRNAs in breast cancer immunobiology research

Breast cancer is the most frequently diagnosed malignancy and the leading cause of cancer-related death in women worldwide. Breast cancer development and progression are mainly associated with tumor-intrinsic alterations in diverse genes and signaling pathways and with tumor-extrinsic dysregulations linked to the tumor immune microenvironment. Significantly, abnormal expression of lncRNAs affects the tumor immune microenvironment characteristics and modulates the behavior of different cancer types, including breast cancer. In this review, we provide the current advances about the role of lncRNAs as tumor-intrinsic and tumor-extrinsic modulators of the antitumoral immune response and the immune microenvironment in breast cancer, as well as lncRNAs which are potential biomarkers of tumor immune microenvironment and clinicopathological characteristics in patients, suggesting that lncRNAs are potential targets for immunotherapy in breast cancer.

A lactate-related LncRNA model for predicting prognosis, immune landscape and therapeutic response in breast cancer

Breast cancer (BC) has the highest incidence rate of all cancers globally, with high heterogeneity. Increasing evidence shows that lactate and long non-coding RNA (lncRNA) play a critical role in tumor occurrence, maintenance, therapeutic response, and immune microenvironment. We aimed to construct a lactate-related lncRNAs prognostic signature (LRLPS) for BC patients to predict prognosis, tumor microenvironment, and treatment responses. The BC data download from the Cancer Genome Atlas (TCGA) database was the entire cohort, and it was randomly assigned to the training and test cohorts at a 1:1 ratio. Difference analysis and Pearson correlation analysis identified 196 differentially expressed lactate-related lncRNAs (LRLs). The univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were used to construct the LRLPS, which consisted of 7 LRLs. Patients could be assigned into high-risk and low-risk groups based on the medium-risk sore in the training cohort. Then, we performed the Kaplan–Meier survival analysis, time-dependent receiver operating characteristic (ROC) curves, and univariate and multivariate analyses. The results indicated that the prognosis prediction ability of the LRLPS was excellent, robust, and independent. Furthermore, a nomogram was constructed based on the LRLPS risk score and clinical factors to predict the 3-, 5-, and 10-year survival probability. The GO/KEGG and GSEA indicated that immune-related pathways differed between the two-risk group. CIBERSORT, ESTIMATE, Tumor Immune Dysfunction and Exclusion (TIDE), and Immunophenoscore (IPS) showed that low-risk patients had higher levels of immune infiltration and better immunotherapeutic response. The pRRophetic and CellMiner databases indicated that many common chemotherapeutic drugs were more effective for low-risk patients. In conclusion, we developed a novel LRLPS for BC that could predict the prognosis, immune landscape, and treatment response.

Oncogenic roles of LINC01234 in various forms of human cancer

Abnormal expression of long non-coding RNAs (lncRNAs) plays an essential role in various malignant neoplasia. As a newly identified lncRNA, LINC01234 is abnormally expressed in several types of cancers and promotes the development of cancers. Accumulating evidence indicates that overexpression of LINC01234 is associated with poor clinical outcomes. Moreover, LINC01234 modulates many cellular events as a putative proto-oncogene, including proliferation, migration, invasion, apoptosis, cell cycle progression, and EMT. In terms of molecular mechanism, LINC01234 regulates gene expression by acting as ceRNA, participating in signaling pathways, interacting with proteins and other molecules, and encoding polypeptide. It reveals that LINC01234 may serve as a potential biomarker for cancer diagnosis, treatment, and prognosis. This review summarizes the expression pattern, biological function, and molecular mechanism of LINC01234 in human cancer and discusses its potential clinical utility.

Integrated Analysis of a Ferroptosis-Related LncRNA Signature for Evaluating the Prognosis of Patients with Colorectal Cancer

LncRNAs have been well known for their multiple functions in the tumorigenesis, development, and relapse of colorectal cancer (CRC). Accumulating studies demonstrated that the expression of lncRNAs can be regulated by ferroptosis, a biological process that has been revealed to suppress CRC progression. However, the functions and clinical implications of ferroptosis-associated lncRNAs in CRC remain largely unknown. We, herein, aim to construct a prognostic signature with ferroptosis-related lncRNAs for the prognostic estimation of CRC patients. Firstly, we identified the lncRNAs related to ferroptosis based on the RNA-Seq data of CRC from the TCGA database. The univariate and multivariate Cox analyses were then performed to establish a prognostic signature composed of eight ferroptosis-related lncRNAs (AL161729.4, AC010973.2, CCDC144NL-AS1, AC009549.1, LINC01857, AP003555.1, AC099850.3, and AC008494.3). Furthermore, we divided the CRC patients into high- and low-risk groups based on the signature and found the overall survival (OS) of patients in the high-risk group was significantly shorter than that in the low-risk group (p = 3.31 × 10-11). Moreover, the patients in the high-risk groups had shorter recurrence-free survival (RFS) (p = 6.5 × 10-3) and disease-free survival (DFS) (p = 4.27 × 10-4), as well as higher tumor recurrence rate. Additionally, we found that the oncogenic pathways were enriched in the high-risk group, whereas the ferroptosis pathway that probably repressed CRC development was enriched in the low-risk group. In summary, our signature may provide a theoretical foundation for not only accurate judgment for prognosis but also evaluation for recurrence and metastasis in CRC patients.

Necroptosis-Related LncRNAs Signature and Subtypes for Predicting Prognosis and Revealing the Immune Microenvironment in Breast Cancer

Purpose

Necroptosis is a mode of programmed cell death that overcomes apoptotic resistance. We aimed to construct a steady necroptosis-related signature and identify subtypes for prognostic and immunotherapy sensitivity prediction.

Methods

Necroptosis-related prognostic lncRNAs were selected by co-expression analysis, and were used to construct a linear stepwise regression model via univariate and multivariate Cox regression, along with least absolute shrinkage and selection operator (LASSO). Quantitative reverse transcription polymerase chain reaction (RT-PCR) was used to measure the gene expression levels of lncRNAs included in the model. Based on the riskScore calculated, we separated patients into high- and low-risk groups. Afterwards, we performed CIBERSORT and the single-sample gene set enrichment analysis (ssGSEA) method to explore immune infiltration status. Furthermore, we investigated the relationships between the signature and immune landscape, genomic integrity, clinical characteristics, drug sensitivity, and immunotherapy efficacy.

Results

We constructed a robust necroptosis-related 22-lncRNA model, serving as an independent prognostic factor for breast cancer (BRCA). The low-risk group seemed to be the immune-activated type. Meanwhile, it showed that the higher the tumor mutation burden (TMB), the higher the riskScore. PD-L1-CTLA4 combined immunotherapy seemed to be a promising treatment strategy. Lastly, patients were assigned to 4 clusters to better discern the heterogeneity among patients.

Conclusions

The necroptosis-related lncRNA signature and molecular clusters indicated superior predictive performance in prognosis and the immune microenvironment, which may also provide guidance to drug regimens for immunotherapy and provide novel insights into precision medicine.