The tumor suppressor MIR139 is silenced by POLR2M to promote AML oncogenesis

NNBGWO-BRCA marker: Neural Network and binary grey wolf optimization based Breast cancer biomarker discovery framework using multi-omics dataset

BACKGROUND AND OBJECTIVE

Breast cancer is a multifaceted condition characterized by diverse features and a substantial mortality rate, underscoring the imperative for timely detection and intervention. The utilization of multi-omics data has gained significant traction in recent years to identify biomarkers and classify subtypes in breast cancer. This kind of research idea from part to whole will also be an inevitable trend in future life science research. Deep learning can integrate and analyze multi-omics data to predict cancer subtypes, which can further drive targeted therapies. However, there are few articles leveraging the nature of deep learning for feature selection. Therefore, this paper proposes a Neural Network and Binary grey Wolf Optimization based BReast CAncer bioMarker (NNBGWO-BRCAMarker) discovery framework using multi-omics data to obtain a series of biomarkers for precise classification of breast cancer subtypes.

METHODS

NNBGWO-BRCAMarker consists of two phases: in the first phase, relevant genes are selected using the weights obtained from a trained feedforward neural network; in the second phase, the binary grey wolf optimization algorithm is leveraged to further screen the selected genes, resulting in a set of potential breast cancer biomarkers.

RESULTS

The SVM classifier with RBF kernel achieved a classification accuracy of 0.9242 ± 0.03 when trained using the 80 biomarkers identified by NNBGWO-BRCAMarker, as evidenced by the experimental results. We conducted a comprehensive gene set analysis, prognostic analysis, and druggability analysis, unveiling 25 druggable genes, 16 enriched pathways strongly linked to specific subtypes of breast cancer, and 8 genes linked to prognostic outcomes.

CONCLUSIONS

The proposed framework successfully identified 80 biomarkers from the multi-omics data, enabling accurate classification of breast cancer subtypes. This discovery may offer novel insights for clinicians to pursue in further studies.

Crosstalk between Noncoding RNAs and the Epigenetics Machinery in Pediatric Tumors and Their Microenvironment

According to the World Health Organization, every year, an estimated 400,000+ new cancer cases affect children under the age of 20 worldwide. Unlike adult cancers, pediatric cancers develop very early in life due to alterations in signaling pathways that regulate embryonic development, and environmental factors do not contribute much to cancer development. The highly organized complex microenvironment controlled by synchronized gene expression patterns plays an essential role in the embryonic stages of development. Dysregulated development can lead to tumor initiation and growth. The low mutational burden in pediatric tumors suggests the predominant role of epigenetic changes in driving the cancer phenotype. However, one more upstream layer of regulation driven by ncRNAs regulates gene expression and signaling pathways involved in the development. Deregulation of ncRNAs can alter the epigenetic machinery of a cell, affecting the transcription and translation profiles of gene regulatory networks required for cellular proliferation and differentiation during embryonic development. Therefore, it is essential to understand the role of ncRNAs in pediatric tumor development to accelerate translational research to discover new treatments for childhood cancers. This review focuses on the role of ncRNA in regulating the epigenetics of pediatric tumors and their tumor microenvironment, the impact of their deregulation on driving pediatric tumor progress, and their potential as effective therapeutic targets.

Human circulating small non-coding RNA signature as a non-invasive biomarker in clinical diagnosis of acute myeloid leukaemia

Background: Acute myeloid leukaemia (AML) is the most common acute leukaemia in adults; AML is highly heterogeneous and involves abnormalities at multiple omics levels. Small non-coding RNAs (sncRNAs) present in body fluids are important regulatory molecules and considered promising non-invasive clinical diagnostic biomarkers for disease. However, the signature of sncRNA profile alteration in AML patient serum and bone marrow supernatant is still under exploration. Methods: We examined data for blood and bone marrow samples from 80 consecutive, newly-diagnosed patients with AML and 12 healthy controls for high throughput small RNA-sequencing. Differentially expressed sncRNAs were analysed to reveal distinct patterns between AML patients and controls. Machine learning methods were used to evaluate the efficiency of specific sncRNAs in discriminating individuals with AML from controls. The altered expression level of individual sncRNAs was evaluated by RT-PCR, Q-PCR, and northern blot. Correlation analysis was employed to assess sncRNA patterns between serum and bone marrow supernatant. Results: We identified over 20 types of sncRNA categories beyond miRNAs in both serum and bone marrow supernatant, with highly coordinated expression patterns between them. Non-classical sncRNAs, including rsRNA (62.86%), ysRNA (14.97%), and tsRNA (4.22%), dominated among serum sncRNAs and showed sensitive alteration patterns in AML patients. According to machine learning-based algorithms, the tsRNA-based signature robustly discriminated subjects with AML from controls and was more reliable than that comprising miRNAs. Our data also showed that serum tsRNAs to be closely associated with AML prognosis, suggesting the potential application of serum tsRNAs as biomarkers to assist in AML diagnosis. Conclusions: We comprehensively characterized the expression pattern of circulating sncRNAs in blood and bone marrow and their alteration signature between healthy controls and AML patients. This study enriches research of sncRNAs in the regulation of AML, and provides insights into the role of sncRNAs in AML.

Is the AURKB Gene Involved in Aml Cell Proliferation Since It is Targeted by miR-34a-5p and let-7b-5p?

ABSTRACT Objective: The production of normal blood cells in the bone marrow is interrupted in AML, which is characterized by the proliferation and accumulation of leukemic blasts. Therefore, patients experience anemia and thrombocytopenia. When gene expression of Aurora kinases, which is reported to be highly expressed in AML, decreases, it may be possible to alleviate the clinical findings in AML. In this study, it was aimed to examine the relationship of AURKB with important miRNAs that have the potential to regulate gene expression. Method: HL60 and NB4 cells were transfected with important tumor suppressor miRNAs miR-34a-5p and let-7b-5p mimics. Then, its effects on proliferation were examined with WST-8 technique and its effects on AURKB gene expression were examined with qRT-PCR. Results: It was determined that these miRNAs negatively regulated proliferation in both AML cell lines and downregulated the expression level of the Aurora kinase B (AURKB) gene in the miRNA transfected group compared to the control group. Conclusion: In conclusion, it was determined that miR-34a-5p and let-7b-5p could regulate AURKB expression in AML cells. Therefore, it was thought that these miRNAs may have an important potential as a therapeutic biomarker in preventing excessive cell division and poor prognosis in AML.

Comprehensive analysis of ID genes reveals the clinical and prognostic value of ID3 expression in acute myeloid leukemia using bioinformatics identification and experimental validation

BACKGROUND

Dysregulation of inhibitor of differentiation/DNA binding (ID) genes is linked to cancer growth, angiogenesis, invasiveness, metastasis and patient survival. Nevertheless, few investigations have systematically determined the expression and prognostic value of ID genes in acute myeloid leukemia (AML).

METHODS

The expression and clinical prognostic value of ID genes in AML were first identified by public databases and further validated by our research cohort.

RESULTS

Using public data, the expression of ID1/ID3 was markedly downregulated in AML, and the expression of ID2 was greatly upregulated in AML, whereas ID4 showed no significant difference. Among the ID genes, only ID3 expression may be the most valuable prognostic biomarker in both total AML and cytogenetically normal AML (CN-AML) and especially in CN-AML. Clinically, reduced ID3 expression was greatly associated with higher white blood cell counts, peripheral blood/bone marrow blasts, normal karyotypes and intermediate cytogenetic risk. In addition, low ID3 expression was markedly related to FLT3 and NPM1 mutations as well as wild-type TP53. Despite these associations, multivariate Cox regression analysis revealed that ID3 expression was an independent risk factor affecting overall survival (OS) and disease free survival (DFS) in CN-AML patients. Biologically, a total of 839 mRNAs/lncRNAs and 72 microRNAs were found to be associated with ID3 expression in AML. Importantly, the expression of ID3 with discriminative value in AML was further confirmed in our research cohort.

CONCLUSION

The bioinformatics analysis and experimental verification demonstrate that low ID3 expression independently affects OS and DFS in patients with CN-AML, which might be seen as a potential prognostic indicator in CN-AML.

High-Throughput CRISPR Screening in Hematological Neoplasms

CRISPR is becoming an indispensable tool in biological research, revolutionizing diverse fields of medical research and biotechnology. In the last few years, several CRISPR-based genome-targeting tools have been translated for the study of hematological neoplasms. However, there is a lack of reviews focused on the wide uses of this technology in hematology. Therefore, in this review, we summarize the main CRISPR-based approaches of high throughput screenings applied to this field. Here we explain several libraries and algorithms for analysis of CRISPR screens used in hematology, accompanied by the most relevant databases. Moreover, we focus on (1) the identification of novel modulator genes of drug resistance and efficacy, which could anticipate relapses in patients and (2) new therapeutic targets and synthetic lethal interactions. We also discuss the approaches to uncover novel biomarkers of malignant transformations and immune evasion mechanisms. We explain the current literature in the most common lymphoid and myeloid neoplasms using this tool. Then, we conclude with future directions, highlighting the importance of further gene candidate validation and the integration and harmonization of the data from CRISPR screening approaches.

Potential of the miR-200 Family as a Target for Developing Anti-Cancer Therapeutics

MicroRNAs (miRNAs) are small non-coding RNAs (18–24 nucleotides) that play significant roles in cell proliferation, development, invasion, cancer development, cancer progression, and anti-cancer drug resistance. miRNAs target multiple genes and play diverse roles. miRNAs can bind to the 3′UTR of target genes and inhibit translation or promote the degradation of target genes. miR-200 family miRNAs mostly act as tumor suppressors and are commonly decreased in cancer. The miR-200 family has been reported as a valuable diagnostic and prognostic marker. This review discusses the clinical value of the miR-200 family, focusing on the role of the miR-200 family in the development of cancer and anti-cancer drug resistance. This review also provides an overview of the factors that regulate the expression of the miR-200 family, targets of miR-200 family miRNAs, and the mechanism of anti-cancer drug resistance regulated by the miR-200 family.

MicroRNA-139, an Emerging Gate-Keeper in Various Types of Cancer

Mounting data show that MIR139 is commonly silenced in solid cancer and hematological malignancies. MIR139 acts as a critical tumor suppressor by tuning the cellular response to different types of stress, including DNA damage, and by repressing oncogenic signaling pathways. Recently, novel insights into the mechanism of MIR139 silencing in tumor cells have been described. These include epigenetic silencing, inhibition of POL-II transcriptional activity on gene regulatory elements, enhanced expression of competing RNAs and post-transcriptional regulation by the microprocessor complex. Some of these MIR139-silencing mechanisms have been demonstrated in different types of cancer, suggesting that these are more general oncogenic events. Reactivation of MIR139 expression in tumor cells causes inhibition of tumor cell expansion and induction of cell death by the repression of oncogenic mRNA targets. In this review, we discuss the different aspects of MIR139 as a tumor suppressor gene and give an overview on different transcriptional mechanisms regulating MIR139 in oncogenic stress and across different types of cancer. The novel insights into the expression regulation and the tumor-suppressing activities of MIR139 may pave the way to new treatment options for cancer.

miR-139-3p/Kinesin family member 18B axis suppresses malignant progression of gastric cancer

miR-139-3p exerts tumor-suppressing functions in various cancers. We analyzed and identified that miR-139-3p expression was notably low in gastric cancer (GC) via edgeR differential analysis based on The Cancer Genome Atlas database and quantitative real-time polymerase chain reaction (qRT-PCR) assay. The binding relationship between Kinesin Family Member 18B (KIF18B) and miR-139-3p was predicted by bioinformatics databases, and verified through dual-luciferase assay. Western blot and qRT-PCR results also indicated that miR-139-3p restrained KIF18 expression at mRNA and protein levels. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, wound healing, transwell, flow cytometry assays were introduced to evaluate cell proliferation, migration, invasion, and cell cycle, respectively, where the results indicated that upregulating miR-139-3p inhibited proliferative, migratory, and invasive abilities of GC cells, while caused cell-cycle arrest. Moreover, the results of rescue experiments illustrated that miR-139-3p hampered the progression of GC cells by targeting and suppressing KIF18B. To sum up, we concluded that miR-139-3p suppressed GC progression by targeting KIF18B.