Construction of prognostic microRNA signature for human invasive breast cancer by integrated analysis

miR-484 as an "OncomiR" in Breast Cancer Promotes Tumorigenesis by Suppressing Apoptosis Genes

PURPOSE

Breast cancer (BC) is one of the most common causes of death among females. Cancer cells escape from apoptosis, causing the cells to proliferate uncontrollably. MicroRNAs (miRNAs) are known to regulate apoptosis in cancer cells.

OBJECTIVE

This study aimed to determine the change in miR-484 in different BC cells and its relationship with the apoptosis pathway.

METHODS

In the study, tumor and healthy tissue samples adjacent to the tumor were collected from 42 patients (6 benign, 36 malignant). Tissue samples were classified according to tumor type, tumor histological grade, proliferation index, and molecular subtypes. Gene expression levels were determined by quantitative real-time polymerase chain reaction (qRT-PCR), and protein levels were determined using the Western Blot method. The results were analyzed using the delta-delta Ct method.

RESULTS

Findings showed that miR-484 expression levels were higher in malignant tumors than in benign tumors, and higher in tumor tissues than healthy tissues. Additionally, it was determined that as Ki-67 levels and histological grade and aggressiveness increased, miR-484 expression levels also increased. In tumor tissue compared with healthy adjacent tissue, there was an increase in BCL2 expression and a decrease in Casp3 and Casp9 expression. Therefore, a positive correlation was found between miR-484 expression and BCL2, and a negative correlation was found between CASP3 and CASP9 expression.

CONCLUSION

Our results show that miR-484 may play a roll as an onco-miR in BC. Increased miR-484 and BCL2, and decreased Casp3, in breast tumor tissues suggest that Casp9 expression may increase uncontrolled cell proliferation by suppressing apoptosis in BC cells and may contribute to tumor progression.

Value of miR-31 and miR-150-3p as diagnostic and prognostic biomarkers for breast cancer

BACKGROUND

The most prevalent malignancy among women is breast cancer (BC). MicroRNAs (miRNAs) play a role in the initiation and progression of BC by influencing breast cancer stem cells (BCSCs) but the diagnostic and prognostic roles of those miRNAs on BC patients are still unknown. It was aimed to investigate expression profiles, diagnostic and prognostic potentials of BCSC-related miRNAs in different subtypes (Luminal A and B, HER2 + and TNBC) of BC patients.

METHODS AND RESULTS

Expression analysis of 15 BCSC-related miRNAs was performed in 50 breast tumor tissues and 20 adjacent non-tumor tissues obtained from BC patients using the qRT-PCR method. The expression levels of miR-31 and miR-150-3p were significantly upregulated in the tumor tissues compared to the adjacent non-tumor tissues (p < 0.05). miR-31 expression upregulated in the Luminal A and Luminal B group compared to non-tumor tissue (p < 0.05). miR-31 expression was determined to be significantly higher in the Luminal group (Luminal A and B) compared to the aggressive group (HER2 + and TNBC) (p < 0.05). According to the ROC analysis, the area under the curve (AUC) of miR-31 and miR-150-3p were 0.66 with a sensitivity of 68% and a specificity of 70%. A significant inverse correlation was observed between miR-31 expression with metastatic carcinoma status, in situ component, and Ki67 value in tumors, and high miR-150-3p expression was correlated with p63 expression (p < 0.05).

CONCLUSION

miR-31 and miR-150-3p have the potential to serve as biomarkers for guiding diagnosis, evaluating prognosis, and metastatic process in patients with BC.

Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection

BACKGROUND

Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors.

METHODS

We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers.

RESULTS

We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations in TP53, PLXNB3, Zinc finger genes, and fewer mutations in SDC2, CDH1, PIK3CA, SVIL, and PTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA-protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, including KIAA1522, DCK, FOXO3, MYO9B, ARID1A, EPRS, ZC3HAV1, and RBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors.

CONCLUSIONS

This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.

Multi-omics integration method based on attention deep learning network for biomedical data classification

BACKGROUND AND OBJECTIVE

Integrating multi-omics data for the comprehensive analysis of the biological processes in human diseases has become one of the most challenging tasks of bioinformatics. Deep learning (DL) algorithms have recently become one of the most promising multi-omics data integration analysis methods. However, existing DL-based studies almost integrate the multi-omics data by concatenation in the input data space or the learned feature space, ignoring the correlations between patients and omics.

METHODS

We propose a novel multi-omics integration method, called Multi-omics Attention Deep Learning Network (MOADLN), which is used for biomedical data classification. Firstly, for each type of omics data, we use three fully-connected layers and the self-attention mechanism to reduce dimensionality, and construct the correlations between patients, respectively. Then, we apply the feature vector learned from self-attention to generate the initial category labels. Secondly, for the initial label predicted of each omics data, we use an effective Multi-Omics Correlation Discovery Network (MOCDN) to learn the cross-omic correlations in the label space. Finally, we use the softmax classifier for label prediction.

RESULTS

We demonstrate that our method outperforms several state-of-the-art methods on two datasets with mRNA expression data, DNA methylation data, and miRNA expression data. In addition, we identified essential biomarkers of relevant diseases by MOADLN, and the generality of MOADLN is also demonstrated in the KIRP and KIRC datasets.

CONCLUSIONS

MOADLN jointly explores correlations between patients in intra-omics and correlations of cross-omics in label space, which is an effective DL-based classification of biomedical data.

miR-31-5p as a Potential Circulating Biomarker and Tracer of Clinical Improvement for Chronic Inflammatory Demyelinating Polyneuropathy

Background

MicroRNAs are endogenous, small noncoding RNA molecules that play a pivotal role in the regulation of gene expression. MicroRNAs are involved in many biological processes such as proliferation, cell differentiation, neovascularization, and apoptosis. Studies on microRNA expression may contribute to a better understanding of the pathomechanism of chronic inflammatory demyelinating polyneuropathy (CIDP) and consequently enable the development of new therapeutic measures using antisense miRNAs (antagomirs). In this study, we evaluated the level of miR-31-5p in the serum of patients with CIDP and its correlation with the miR-31-5p level and clinical presentation and electrophysiological and biochemical parameters.

Methods

The study group consisted of 48 patients, mean age 61.60 ± 11.76, who fulfilled the diagnostic criteria of a typical variant of CIDP. The expression of miR-31-5p in patient serum probes was investigated by droplet digital PCR. The results were correlated with neurophysiological findings and the patient's clinical and biochemical parameters.

Results

The mean copy number of miRNA-31 in 100 μl serum was 1288.64 ± 2001.02 in the CIDP group of patients, while in the control group, it was 3743.09 ± 4026.90. There was a significant positive correlation (0.426) between IgIV treatment duration and miR-31-5p expression. Patients without IgIV treatment showed significantly lower levels of miR-31 compared to the treated group (259.44 ± 304.02 vs. 1559.48 ± 2168.45; p = 0.002). The group of patients with body weight > 80 kg showed statistically significantly lower levels of miRNA-31-5p than the patients with lower body weight (934.37 ± 1739.66 vs. 1784.62 ± 2271.62, respectively; p = 0.014). Similarly, the patients with elevated cerebrospinal fluid (CSF) protein levels had significantly higher miRNA-31-5p expression than those with normal protein levels (1393.93 ± 1932.27 vs. 987.38 ± 2364.10, respectively; p = 0.044).

Conclusion

The results may support the hypothesis that miR-31-5p is strongly involved in the autoimmune process in CIDP. The positive correlation between higher miR-31-5p levels and duration of IVIg treatment may be an additional factor explaining the efficacy of prolonged IVIg therapy in CIDP.

MicroRNA-484 / Akt axis in the regulation of breast cancer cells sensitivity to antitumor drugs

The development of acquired resistance of malignant tumors to specific drugs, such as target and hormonal drugs, is usually associated with a rearrangement of the intracellular signaling network and activation of unblocked growth pathways. Epigenetic regulators, in particular, non-coding miRNAs that control the level of expression of specific signaling proteins, are directly involved in the development and maintenance of such changes. We have previously shown that the development of resistance of breast cancer cells to mTOR (mammalian target of rapamycin) inhibitors and hormonal drugs is accompanied by constitutive activation of protein kinase Akt, the key anti-apoptotic protein.Aim. To study the role of microRNAs in the regulation of Akt expression and the formation of a resistant phenotype of breast cancer cells.We have shown that Akt activation in the tamoxifen- or rapamycin-resistant MCF-7 sublines is associated with a decrease in the level of miRNA-484, one of the Akt suppressors. Transfection of microRNA-484 into MCF-7 cells does not affect the activity of estrogen signaling, but leads to a marked decrease in Akt expression and is accompanied by an increase in cell sensitivity to tamoxifen and rapamycin. The obtained data demonstrate the involvement of the miRNA-484 / Akt axis in the breast cancer cells’ sensitization to target and hormonal drugs, which allows us to consider miRNA-484 as a potential candidate for drug development to cure resistant cancers.

Inhibitory role of microRNA-484 in kidney stone formation by repressing calcium oxalate crystallization via a VDR/FoxO1 regulator axis

Kidney stones are regarded as common malignant diseases in the developed world. As a result, significant research examining their formation is ongoing, with microRNAs (miRs) recently being linked with kidney stone formation. Here, we aim to define the potential role of miR-484 in regulating renal tubular epithelial cell (RTEC) viability and the attachment of calcium oxalate (CaOx) crystals to RTECs via vitamin D receptor (VDR)/forkhead box protein O1 (FoxO1) axis. The pathological condition of CaOx crystallization was induced and examined in Sprague-Dawley rats, while RTECs were isolated and cultured in vitro. Loss- and gain-function assays were performed to study the effects that miR-484, VDR, and FoxO1 on RTEC functions and CaOx crystallization in vitro and on kidney stone formation in vivo. The interaction between miR-484 and VDR was confirmed by dual-luciferase reporter gene assays. Downregulation of miR-484 and FoxO1 as well as overexpression of VDR were identified in kidney stone modelled rats. VDR was confirmed as a target gene of miR-484, while knockdown of VDR upregulated the FoxO1 expression. miR-484 overexpression or VDR suppression reduced RTEC cytotoxicity and crystal attachment to RTECs in vitro and reduced the CaOx crystallization in vivo. Taken together, these findings suggest that miR-484 overexpression may be a potential inhibitor of RTEC proliferation and CaOx crystallization through a VDR/FoxO1 regulatory axis, providing a novel therapeutic target for the treatment of kidney stone.

Application of Proteogenomics to Urine Analysis towards the Identification of Novel Biomarkers of Prostate Cancer: An Exploratory Study

Simple Summary

Prostate cancer (PCa) is one of the most common cancers. Due to the limited and invasive approaches for PCa diagnosis, it is crucial to identify more accurate and non-invasive biomarkers for its detection. The aim of our study was to non-invasively uncover new protein targets for detecting PCa using a proteomics and proteogenomics approach. This work identified several dysregulated mutant protein isoforms in urine from PCa patients, some of them predicted to have a protective or an adverse role in these patients. These results are promising given urine’s non-invasive nature and offers an auspicious opportunity for research and development of PCa biomarkers.

Abstract

To identify new protein targets for PCa detection, first, a shotgun discovery experiment was performed to characterize the urinary proteome of PCa patients. This revealed 18 differentially abundant urinary proteins in PCa patients. Second, selected targets were clinically tested by immunoblot, and the soluble E-cadherin fragment was detected for the first time in the urine of PCa patients. Third, the proteogenome landscape of these PCa patients was characterized, revealing 1665 mutant protein isoforms. Statistical analysis revealed 6 differentially abundant mutant protein isoforms in PCa patients. Analysis of the likely effects of mutations on protein function and PPIs involving the dysregulated mutant protein isoforms suggests a protective role of mutations HSPG2*Q1062H and VASN*R161Q and an adverse role of AMBP*A286G and CD55*S162L in PCa patients. This work originally characterized the urinary proteome, focusing on the proteogenome profile of PCa patients, which is usually overlooked in the analysis of PCa and body fluids. Combined analysis of mass spectrometry data using two different software packages was performed for the first time in the context of PCa, which increased the robustness of the data analysis. The application of proteogenomics to urine proteomic analysis can be very enriching in mutation-related diseases such as cancer.

miR-484: A Potential Biomarker in Health and Disease

Disorders of miR-484 expression are observed in cancer, different diseases or pathological states. There is accumulating evidence that miR-484 plays an essential role in the development as well as the regression of different diseases, and miR-484 has been reported as a key regulator of common cancer and non-cancer diseases. The miR-484 targets that have effects on inflammation, apoptosis and mitochondrial function include SMAD7, Fis1, YAP1 and BCL2L13. For cancer, identified targets include VEGFB, VEGFR2, MAP2, MMP14, HNF1A, TUSC5 and KLF12. The effects of miR-484 on these targets have been documented separately. Moreover, miR-484 is typically described as an oncosuppressor, but this claim is simplistic and one-sided. This review will combine relevant basic and clinical studies to find that miR-484 promotes tumorigenesis and metastasis in liver, prostate and lung tissues. It will provide a basis for the possible mechanisms of miR-484 in early tumor diagnosis, prognosis determination, disease assessment, and as a potential therapeutic target for tumors.

The Role of MicroRNA as Clinical Biomarkers for Breast Cancer Surgery and Treatment

Breast cancer is the most common cancer diagnosed in women. In recent times, survival outcomes have improved dramatically in accordance with our enhanced understanding of the molecular processes driving breast cancer proliferation and development. Refined surgical approaches, combined with novel and targeted treatment options, have aided the personalisation of breast cancer patient care. Despite this, some patients will unfortunately succumb to the disease. In recent times, translational research efforts have been focused on identifying novel biomarkers capable of informing patient outcome; microRNAs (miRNAs) are small non-coding molecules, which regulate gene expression at a post-transcriptional level. Aberrant miRNA expression profiles have been observed in cancer proliferation and development. The measurement and correlation of miRNA expression levels with oncological outcomes such as response to current conventional therapies, and disease recurrence are being investigated. Herein, we outline the clinical utility of miRNA expression profiles in informing breast cancer prognosis, predicting response to treatment strategies as well as their potential as therapeutic targets to enhance treatment modalities in the era of precision oncology.

Prediction of differentially expressed microRNAs in blood as potential biomarkers for Alzheimer's disease by meta-analysis and adaptive boosting ensemble learning

BACKGROUND

Blood circulating microRNAs that are specific for Alzheimer's disease (AD) can be identified from differentially expressed microRNAs (DEmiRNAs). However, non-reproducible and inconsistent reports of DEmiRNAs hinder biomarker development. The most reliable DEmiRNAs can be identified by meta-analysis. To enrich the pool of DEmiRNAs for potential AD biomarkers, we used a machine learning method called adaptive boosting for miRNA disease association (ABMDA) to identify eligible candidates that share similar characteristics with the DEmiRNAs identified from meta-analysis. This study aimed to identify blood circulating DEmiRNAs as potential AD biomarkers by augmenting meta-analysis with the ABMDA ensemble learning method.

METHODS

Studies on DEmiRNAs and their dysregulation states were corroborated with one another by meta-analysis based on a random-effects model. DEmiRNAs identified by meta-analysis were collected as positive examples of miRNA-AD pairs for ABMDA ensemble learning. ABMDA identified similar DEmiRNAs according to a set of predefined criteria. The biological significance of all resulting DEmiRNAs was determined by their target genes according to pathway enrichment analyses. The target genes common to both meta-analysis- and ABMDA-identified DEmiRNAs were collected to construct a network to investigate their biological functions.

RESULTS

A systematic database search found 7841 studies for an extensive meta-analysis, covering 54 independent comparisons of 47 differential miRNA expression studies, and identified 18 reliable DEmiRNAs. ABMDA ensemble learning was conducted based on the meta-analysis results and the Human MicroRNA Disease Database, which identified 10 additional AD-related DEmiRNAs. These 28 DEmiRNAs and their dysregulated pathways were related to neuroinflammation. The dysregulated pathway related to neuronal cell cycle re-entry (CCR) was the only statistically significant pathway of the ABMDA-identified DEmiRNAs. In the biological network constructed from 1865 common target genes of the identified DEmiRNAs, the multiple core ubiquitin-proteasome system, that is involved in neuroinflammation and CCR, was highly connected.

CONCLUSION

This study identified 28 DEmiRNAs as potential AD biomarkers in blood, by meta-analysis and ABMDA ensemble learning in tandem. The DEmiRNAs identified by meta-analysis and ABMDA were significantly related to neuroinflammation, and the ABMDA-identified DEmiRNAs were related to neuronal CCR.

Discovery of potential serum and urine-based microRNA as minimally-invasive biomarkers for breast and gynecological cancer

BACKGROUND

Deregulated microRNAs (miRNAs) in breast and gynecological cancer might contribute to improve early detection of female malignancies.

OBJECTIVE

Specification of miRNA types in serum and urine as minimally-invasive biomarkers for breast (BC), endometrial (EC) and ovarian cancer (OC).

METHODS

In a discovery phase, serum and urine samples from 17 BC, five EC and five OC patients vs. ten healthy controls (CTRL) were analyzed with Agilent human miRNA microarray chip. Selected miRNA types were further investigated by RT-qPCR in serum (31 BC, 13 EC, 15 OC patients, 32 CTRL) and urine (25 BC, 10 EC, 10 OC patients, 30 CTRL) applying two-sample t-tests.

RESULTS

Several miRNA biomarker candidates exhibited diagnostic features due to distinctive expression levels (serum: 26; urine: 22). Among these, miR-518b, -4719 and -6757-3p were found specifically deregulated in BC serum. Four, non-entity-specific, novel biomarker candidates with unknown functional roles were identified in urine (miR-3973; -4426; -5089-5p and -6841). RT-qPCR identified miR-484/-23a (all p⩽ 0.001) in serum as potential diagnostic markers for EC and OC while miR-23a may also serve as an endogenous control in BC diagnosis.

CONCLUSIONS

Promising miRNAs as liquid biopsy-based tools in the detection of BC, EC and OC qualified for external validation in larger cohorts.

Identifying prognostic biomarkers in endometrial carcinoma based on ceRNA network

PURPOSE

Endometrial carcinoma (EC), a common gynecological malignancy with high incidence, affects the mental and physical health of women. Mounting evidence shows that long noncoding RNAs (lncRNAs), messenger RNAs (mRNAs), and microRNAs (miRNAs) have instrumental roles in various biological processes associated with the pathogenesis of EC. In this research, we intend to further study the mechanism of EC and the potential predictive markers of EC.

METHODS

First, we obtained original data of EC RNA transcripts from The Cancer Genome Atlas database and performed differential analysis. Subsequently, according to the miRcode online software, relationship pairs of lncRNA-miRNA were constructed, and miRNA-mRNA pairs were established based on miRDB, TargetScan, and miRTarBase. Then, we constructed the competing endogenous RNA (ceRNA) network based on lncRNA-miRNA and miRNA-mRNA pairs. To further explain the function of the ceRNA network and explore the potential prognostic markers, functional enrichment analysis, and survival analysis were carried out.

RESULTS

The research showed that there were 744 differential expression lncRNAs (DElncRNAs), 164 differential expression miRNAs (DEmiRNAs), and 2447 differential expression mRNAs (DEmRNAs) between EC tissues and normal tissues. Subsequently, we built 103 DEmiRNA-DEmRNA interaction pairs and 369 DElncRNA-DEmiRNA pairs. Then, we established the ceRNA network of EC, including 62 DElncRNAs, 26 DEmiRNAs, and 70 DEmRNAs. Moreover, 10 of 62 lncRNAs, 19 of 70 mRNAs, and 4 of 26 miRNAs that closely related to the survival of EC with P < .05 were obtained. Notably, based on this network, it was found that LINC00261-hsa-mir-31 pair and LINC00261-hsa-mir-211 target pairs could be used as the potential prognostic markers of EC.

CONCLUSION

This research recommended an available basis for the molecular mechanism of EC and prognosis prediction, which could help guide the subsequent treatments and predict the prognosis for patients with EC.