Identification of targets of miRNA-221 and miRNA-222 in fulvestrant-resistant breast cancer

Unraveling the MicroRNA tapestry: exploring the molecular dynamics of locoregional recurrent rectal cancer

Introduction

Colorectal cancer (CRC) ranks as the third most prevalent malignancy globally, with a concerning rise in incidence among young adults. Despite progress in understanding genetic predispositions and lifestyle risk factors, the intricate molecular mechanisms of CRC demand exploration. MicroRNAs (miRNAs) emerge as key regulators of gene expression and their deregulation in tumor cells play pivotal roles in cancer progression.

Methods

NanoString's nCounter technology was utilized to measure the expression of 827 cancer-related miRNAs in tumor tissue and adjacent non-involved normal colon tissue from five patients with locoregional CRC progression. These expression profiles were then compared to those from the primary colon adenocarcinoma (COAD) cohort in The Cancer Genome Atlas (TCGA).

Results and discussion

Intriguingly, 156 miRNAs showed a contrasting dysregulation pattern in reccurent tumor compared to their expression in the TCGA COAD cohort. This observation implies dynamic alterations in miRNA expression patterns throughout disease progression. Our exploratory study contributes to understanding the regulatory landscape of recurrent CRC, emphasizing the role of miRNAs in disease relapse. Notable findings include the prominence of let-7 miRNA family, dysregulation of key target genes, and dynamic changes in miRNA expression patterns during progression. Univariate Cox proportional hazard models highlighted miRNAs associated with adverse outcomes and potential protective factors. The study underscores the need for more extensive investigations into miRNA dynamics during tumor progression and the value of stage specific biomarkers for prognosis.

Identification of an interactome network between lncRNAs and miRNAs in thyroid cancer reveals SPTY2D1-AS1 as a new tumor suppressor

Thyroid cancer is the most common primary endocrine malignancy in adults and its incidence is rapidly increasing. Long non-coding RNAs (lncRNAs), generally defined as RNA molecules longer than 200 nucleotides with no protein-encoding capacity, are highly tissue-specific molecules that serve important roles in gene regulation through a variety of different mechanisms, including acting as competing endogenous RNAs (ceRNAs) that ‘sponge’ microRNAs (miRNAs). In the present study, using an integrated approach through RNA-sequencing of paired thyroid tumor and non-tumor samples, we have identified an interactome network between lncRNAs and miRNAs and examined the functional consequences in vitro and in vivo of one of such interactions. We have identified a likely operative post-transcriptional regulatory network in which the downregulated lncRNA, SPTY2D1-AS1, is predicted to target the most abundant and upregulated miRNAs in thyroid cancer, particularly miR-221, a well-known oncomiRNA in cancer. Indeed, SPTY2D1-AS1 functions as a potent tumor suppressor in vitro and in vivo, it is downregulated in the most advanced stages of human thyroid cancer, and it seems to block the processing of the primary form of miR-221. Overall, our results link SPTY2D1-AS1 to thyroid cancer progression and highlight the potential use of this lncRNA as a therapeutic target of thyroid cancer.

Identification of epigenetic regulators in the estrogen signaling pathway via siRNA screening

Breast cancer is the most prevalent malignant disease among women across the globe. Notably, estrogen signaling plays a vital role in the progression of estrogen receptor-positive breast cancer. Therefore, targeting epigenetic regulators is a promising therapy for cancer. To identify epigenetic regulators, we conducted a siRNA screening targeting 140 epigenetic genes by which 32 positive and 15 negative regulators of estrogen signaling were obtained. The protein-protein interaction network of the candidate genes was constructed and the topological parameters of the network were calculated. As a result, the top 10 genes with higher MCC (Maximal Clique Centrality) scores were considered as hub genes. Notably, the hub genes all belong to polycomb group genes. The transcription levels of the above genes were compared between breast cancer and normal tissues using the UALCAN database. Then, the survival analysis of the hub genes was conducted using the Kaplan-Meier Plotter online database. Lastly, the effect of hub genes on MCF-7 cell proliferation and ER target gene expression were investigated. These results indicate that PcG genes regulate estrogen signaling and breast cancer development.

Prognosis of clear cell renal cell carcinoma (ccRCC) based on a six-lncRNA-based risk score: an investigation based on RNA-sequencing data

Background

The scientific understanding of long non-coding RNAs (lncRNAs) has improved in recent decades. Nevertheless, there has been little research into the role that lncRNAs play in clear cell renal cell carcinoma (ccRCC). More lncRNAs are assumed to influence the progression of ccRCC via their own molecular mechanisms.

Methods

This study investigated the prognostic significance of differentially expressed lncRNAs by mining high-throughput lncRNA-sequencing data from The Cancer Genome Atlas (TCGA) containing 13,198 lncRNAs from 539 patients. Differentially expressed lncRNAs were assessed using the R packages edgeR and DESeq. The prognostic significance of lncRNAs was measured using univariate Cox proportional hazards regression. ccRCC patients were then categorized into high- and low-score cohorts based on the cumulative distribution curve inflection point the of risk score, which was generated by the multivariate Cox regression model. Samples from the TCGA dataset were divided into training and validation subsets to verify the prognostic risk model. Bioinformatics methods, gene set enrichment analysis, and protein–protein interaction networks, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses were subsequently used.

Results

It was found that the risk score based on 6 novel lncRNAs (CTA-384D8.35, CTD-2263F21.1, LINC01510, RP11-352G9.1, RP11-395B7.2, RP11-426C22.4) exhibited superior prognostic value for ccRCC. Moreover, we categorized the cases into two groups (high-risk and low-risk), and also examined related pathways and genetic differences between them. Kaplan–Meier curves indicated that the median survival time of patients in the high-risk group was 73.5 months, much shorter than that of the low-risk group (112.6 months; P < 0.05). Furthermore, the risk score predicted the 5-year survival of all 539 ccRCC patients (AUC at 5 years, 0.683; concordance index [C-index], 0.853; 95% CI 0.817–0.889). The training set and validation set also showed similar performance (AUC at 5 years, 0.649 and 0.681, respectively; C-index, 0.822 and 0.891; 95% CI 0.774–0.870 and 0.844–0.938).

Conclusions

The results of this study can be applied to analyzing various prognostic factors, leading to new possibilities for clinical diagnosis and prognosis of ccRCC.

Dysregulation of DNA methylation patterns may identify patients with breast cancer resistant to endocrine therapy: A predictive classifier based on differentially methylated regions

Endocrine therapy (ET) is one of a number of targeted therapies for estrogen receptor-positive breast cancer (BRCA); however, resistance to ET has become the primary issue affecting treatment outcome. In the present study, a predictive classifier was created using a DNA methylation dataset to identify patients susceptible to endocrine resistance. DNA methylation and RNA sequencing data, and the clinicopathological features of BRCA, were obtained from The Cancer Genome Atlas. Stringent criteria were set to select and classify patients into two groups, namely those resistant to ET (n=11) and sensitive to ET (n=21) groups. Bump hunting analysis revealed that 502 out of 135,418 genomic regions were differentially methylated between these two groups; these regions were differentially methylated regions (DMRs). The majority of the CpG sites contained in the DMRs mapped to the promoter region. Functional enrichment analyses indicated that a total of 562 specific genes encompassing these DMRs were primarily associated with 'biological progress of organ morphogenesis and development' and 'cell-cell adhesion' gene ontologies. Logistic regression and Pearson's correlation analysis were conducted to construct a predictive classifier for distinguishing patients resistant or sensitive to ET. The highest areas under the curve and relatively low Akaike information criterion values were associated with a total of 60 DMRs; a risk score retained from this classifier was revealed to be an unfavorable predictor of survival in two additional independent datasets. Furthermore, the majority of genes (55/63) exhibited a statistically significant association between DNA methylation and mRNA expression (P<0.05). The association between the mRNA expression of a number of genes (namely calcium release activated channel regulator 2A, Schlafen family member 12, chromosome 3 open reading frame 18, zinc finger protein 880, dual oxidase 1, major histocompatibility complex, class II, DP β1, C-terminal binding protein 1, ALG13 UDP-N-acetylglucosaminyltransferase subunit and RAS protein activator like 2) and the prognosis of patients with estrogen receptor-positive BRCA and ET resistance was determined using Kaplan-Meier Plotter. In summary, the predictive classifier proposed in the present study may aid the identification of patients sensitive or resistant to ET, and numerous genes maybe potential therapeutic targets to delay the development of resistance to ET.

Emergence of MicroRNAs as Key Players in Cancer Cell Metabolism

BACKGROUND

Metabolic reprogramming is a hallmark of cancer. MicroRNAs (miRNAs) have been found to regulate cancer metabolism by regulating genes involved in metabolic pathways. Understanding this layer of complexity could lead to the development of novel therapeutic approaches.

CONTENT

miRNAs are noncoding RNAs that have been implicated as master regulators of gene expression. Studies have revealed the role of miRNAs in the metabolic reprogramming of tumor cells, with several miRNAs both positively and negatively regulating multiple metabolic genes. The tricarboxylic acid (TCA) cycle, aerobic glycolysis, de novo fatty acid synthesis, and altered autophagy allow tumor cells to survive under adverse conditions. In addition, major signaling molecules, hypoxia-inducible factor, phosphatidylinositol-3 kinase/protein kinase B/mammalian target of rapamycin/phosphatase and tensin homolog, and insulin signaling pathways facilitate metabolic adaptation in tumor cells and are all regulated by miRNAs. Accumulating evidence suggests that miRNA mimics or inhibitors could be used to modulate the activity of miRNAs that drive tumor progression via altering their metabolism. Currently, several clinical trials investigating the role of miRNA-based therapy for cancer have been launched that may lead to novel therapeutic interventions in the future.

SUMMARY

In this review, we summarize cancer-related metabolic pathways, including glycolysis, TCA cycle, pentose phosphate pathway, fatty acid metabolism, amino acid metabolism, and other metabolism-related oncogenic signaling pathways, and their regulation by miRNAs that are known to lead to tumorigenesis. Further, we discuss the current state of miRNA therapeutics in the clinic and their future potential.

Differential microRNA profiles between fulvestrant-resistant and tamoxifen-resistant human breast cancer cells

Increasing evidence has shown that the dysregulation of microRNAs (miRNAs) is associated with drug resistance. Fulvestrant and tamoxifen represent the major endocrine drugs for the treatment of breast cancer patients, and yet little is known about the biological mechanisms of acquiring resistance to fulvestrant and tamoxifen, let alone the differences between cell lines resistant to these two drugs. Exploration of the differential miRNA profiles between these two cell lines is a useful way to further clarify these resistance mechanisms. The fulvestrant-resistant cell line (MCF7-F) and the tamoxifen-resistant cell line (MCF7-T) were established from the drug-sensitive parental MCF7 cell line using a 21-day high-dose antiestrogen induction method. Differentially expressed miRNA profiles of MCF7-F and MCF7-T were detected using microarray; then, multiple bioinformatic analyses were carried out, including protein-protein interaction network, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes pathway analysis. Compared with the parental MCF7 cell line, more miRNAs were found to be participating in the process of acquiring fulvestrant resistance than tamoxifen resistance. miR-4532, miR-486-5p, miR-138, miR-1228, and miR-3178 could be new targets for combating both fulvestrant resistance and tamoxifen resistance. miR-3188, miR-21, miR-149, and others may be associated with fulvestrant resistance, whereas miR-342 and miR-1226 may be associated with tamoxifen resistance in breast cancer cells. We found differential miRNA profiles between fulvestrant-resistant and tamoxifen-resistant breast cancer cells, but the definite mechanism involved in gaining resistance still needs further study.

MicroRNA-221 promotes papillary thyroid carcinoma cell migration and invasion via targeting RECK and regulating epithelial-mesenchymal transition

Aim

The aim of this study was to detect the effects and potential mechanisms of microRNA-221 on a series of biological behaviors of papillary thyroid carcinoma (PTC) cells in vitro and in vivo.

Methods

First, we analyzed the relationship between the expression of miR-221 and several clinicopathological features of PTC patients and then detected the expression of the miR-221 in tumor tissues and cell lines. The effects of miR-221 on proliferation and invasion of PTC cells were verified by cell counting kit-8 (CCK-8) assay, wound healing assay and transwell assay. Western blot assay was applied to explore the correlation between miR-221 and RECK expression in PTC K1 cells. Finally, a xenograft model was established to further confirm the tumor-promoting effects of miR-221 in vivo.

Results

Our data indicated that miR-221 was relatively upregulated in metastatic PTC tissues. MiR-221 promoted the proliferation, migration and invasion activities of PTC K1 cells, following variations of epithelial-mesenchymal transition (EMT)-related protein expression. We identified RECK as a direct target of miR-221, revealed its expression to be inversely correlated with miR-221 in PTC samples and showed that its reintroduction reverses miR-221-induced PTC invasiveness. In addition, miR-221 was also verified to promote tumor growth and increase tumor volume and weight in vivo. Taken together, miR-221/RECK axis could be an effective way to regulate biological behaviors of PTC.

Conclusion

MiR-221 may be involved in PTC cell invasion and metastasis by targeting RECK, indicating that the miR-221/RECK pathway could be studied further as a potential new diagnostic or prognostic biomarker for PTC.

Correlation between miR-222 and uterine cancer and its prognostic value

Relationship between the expression of miR-222 and uterine cancer was investigated to explore its prognostic value. A total of 66 patients with uterine cancer diagnosed by pathological examination in Dongying People's Hospital were enrolled from March 2014 to October 2016. Uterine cancer and adjacent tissues were collected, and the expression of miR-222 in the tissues was detected by stem-loop RT-PCR. The relationship between miR-222 expression and various clinicopathological features of uterine cancer was analyzed. All the patients were followed up to record the survival conditions. The results revealed that stem-loop RT-PCR method could specifically amplify miR-222. The expression of miR-222 in uterine cancer tissues was significantly upregulated compared with that in adjacent tissues (p<0.05). The expression level of miR-222 was significantly increased with the increase of degree of tumor differentiation (p<0.05). The expression of miR-222 in uterine cancer tissue was not significantly correlated with patients age, tumor size, gross tumor type, pathological type and FIGO stage (p>0.05). There was a significant negative correlation between the expression of miR-222 and the survival of patients with uterine cancer. In conclusion, the expression of miR-222 in uterine cancer tissues was significantly upregulated in uterine cancer and negatively correlated with prognosis. miR-222 may play a pivotal role in the development and progression of uterine cancer. It is expected that miR-222 will be an indicator and target for the treatment and prognosis of uterine cancer.