Regulation of miR-126 and miR-122 Expression and Response of Imatinib Treatment on Its Expression in Chronic Myeloid Leukemia Patients

Empowering Graph Neural Networks with Block-Based Dual Adaptive Deep Adjustment for Drug Resistance-Related NcRNA Discovery

Drug resistance to chemotherapeutic agents remains a formidable challenge in cancer treatment, significantly impacting treatment efficacy. Extensive research has exposed the intimate involvement of noncoding RNAs (ncRNAs) in conferring resistance to cancer drugs. Understanding the intricate associations between ncRNAs and drug resistance is of pivotal importance in advancing clinical interventions and expediting drug development. However, traditional biological experimental methods are hampered by limitations, such as labor intensiveness, time consumption, and constraints in scalability. Addressing these challenges necessitates the development of efficient computational methods for the accurate prediction of potential ncRNA-drug resistance associations (NDRA). However, most existing predictive models primarily focus on known ncRNA-drug resistance associations, often neglecting the critical aspect of similarity information between ncRNAs and drug resistance. This oversight may hinder the accuracy of characterizing these associations. To overcome the limitations of existing computational models, we proposed B-NDRA, a computational framework designed for the discovery of drug resistance-related ncRNA. Initially, we constructed a heterogeneous graph that integrates ncRNA-drug resistance pairs, leveraging both known associations and similarity fusion information between ncRNAs and drug resistance. Subsequently, we employed an attention mechanism to aggregate local features of graph nodes following a dimensionality reduction of node features. Further, a graph neural network (GNN) facilitated the learning of global node embeddings. Notably, the integration of dual adaptive deep adjustment architectures, encompassing intrablock and interblock methodologies, enabled efficient extraction of global features while balancing local and global features. Finally, B-NDRA employed a multilayer perceptron to predict associations between ncRNAs and drug resistance. Through rigorous 5-fold cross-validation, B-NDRA achieved average AUC, AUPR, Accuracy, Precision, Recall, and F1-score values of 92.2%, 91.9%, 84.88%, 86.9%, 82.37%, and 84.44%, respectively. Furthermore, comparative evaluations were conducted on established models, namely, GAEMDA, GRPAMDA, and LRGCPND. The results, obtained through three distinct 5-fold cross-validation strategies, demonstrated a notable performance improvement across almost all metrics for our B-NDRA. Specific case studies targeting Doxorubicin and Imatinib further validated the practicality of our B-NDRA in discovering potential NDRA. These results confirm the potential of our B-NDRA as a valuable tool in advancing cancer research and therapeutic development. The source code and data set of B-NDRA can be found at https://github.com/XuanLi1145/B-NDRA.

Clinical Significance of microRNAs in Hematologic Malignancies and Hematopoietic Stem Cell Transplantation

Hematologic malignancies are a group of neoplastic conditions that can develop from any stage of the hematopoiesis cascade. Small non-coding microRNAs (miRNAs) play a crucial role in the post-transcriptional regulation of gene expression. Mounting evidence highlights the role of miRNAs in malignant hematopoiesis via the regulation of oncogenes and tumor suppressors involved in proliferation, differentiation, and cell death. In this review, we provide current knowledge about dysregulated miRNA expression in the pathogenesis of hematological malignancies. We summarize data about the clinical utility of aberrant miRNA expression profiles in hematologic cancer patients and their associations with diagnosis, prognosis, and the monitoring of treatment response. Moreover, we will discuss the emerging role of miRNAs in hematopoietic stem cell transplantation (HSCT), and severe post-HSCT complications, such as graft-versus-host disease (GvHD). The therapeutical potential of the miRNA-based approach in hemato-oncology will be outlined, including studies with specific antagomiRs, mimetics, and circular RNAs (circRNAs). Since hematologic malignancies represent a full spectrum of disorders with different treatment paradigms and prognoses, the potential use of miRNAs as novel diagnostic and prognostic biomarkers might lead to improvements, resulting in a more accurate diagnosis and better patient outcomes.

MicroRNA-122 in human cancers: from mechanistic to clinical perspectives

MicroRNAs (miRNAs) are endogenous short non-coding RNAs that can regulate the expression of target genes post-transcriptionally and interact with mRNA-coding genes. MiRNAs play vital roles in many biological functions, and abnormal miRNA expression has been linked to various illnesses, including cancer. Among the miRNAs, miR-122, miR-206, miR-21, miR-210, miR-223, and miR-424 have been extensively studied in various cancers. Although research in miRNAs has grown considerably over the last decade, much is yet to be discovered, especially regarding their role in cancer therapies. Several kinds of cancer have been linked to dysregulation and abnormal expression of miR-122, indicating that miR-122 may serve as a diagnostic and/or prognostic biomarker for human cancer. Consequently, in this review literature, miR-122 has been analyzed in numerous cancer types to sort out the function of cancer cells miR-122 and enhance patient response to standard therapy.

Implication of microRNAs in Carcinogenesis with Emphasis on Hematological Malignancies and Clinical Translation

MicroRNAs (miRNAs) are evolutionarily conserved small non-coding RNAs, that are involved in the multistep process of carcinogenesis, contributing to all established hallmarks of cancer. In this review, implications of miRNAs in hematological malignancies and their clinical utilization fields are discussed. As components of the complex regulatory network of gene expression, influenced by the tissue microenvironment and epigenetic modifiers, miRNAs are “micromanagers” of all physiological processes including the regulation of hematopoiesis and metabolic pathways. Dysregulated miRNA expression levels contribute to both the initiation and progression of acute leukemias, the metabolic reprogramming of malignantly transformed hematopoietic precursors, and to the development of chemoresistance. Since they are highly stable and can be easily quantified in body fluids and tissue specimens, miRNAs are promising biomarkers for the early detection of hematological malignancies. Besides novel opportunities for differential diagnosis, miRNAs can contribute to advanced chemoresistance prediction and prognostic stratification of acute leukemias. Synthetic oligonucleotides and delivery vehicles aim the therapeutic modulation of miRNA expression levels. However, major challenges such as efficient delivery to specific locations, differences of miRNA expression patterns between pediatric and adult hematological malignancies, and potential side effects of miRNA-based therapies should be considered.