A MIR17HG-derived long noncoding RNA provides an essential chromatin scaffold for protein interaction and myeloma growth

Identification of lipid metabolism-related gene signature in the bone marrow microenvironment of multiple myelomas through deep analysis of transcriptomic data

Dysregulated lipid metabolism in the bone marrow microenvironment (BMM) plays a vital role in multiple myeloma (MM) development, progression, and drug resistance. However, the exact mechanism by which lipid metabolism impacts the BMM, promotes tumorigenesis, and triggers drug resistance remains to be fully elucidated.By analyzing the bulk sequencing and single-cell sequencing data of MM patients, we identified lipid metabolism-related genes differential expression significantly associated with MM prognosis, referred to as LMRPgenes. Using a cohort of ten machine learning algorithms and 117 combinations, LMRPgenes predictive models were constructed. Further exploration of the effects of the model risk score (RS) on the survival status, immune status of patients with BMM, and response to immunotherapy was conducted. The study also facilitated the identification of personalized therapeutic strategies targeting specified risk categories within patient cohorts.Analysis of the scRNA-seq data revealed increased lipid metabolism-related gene enrichment scores (LMESs) in erythroblasts and progenitor, malignant, and Tprolif cells but decreased LMESs in lymphocytes. LMESs were also strongly correlated with most of the 50 hallmark pathways within these cell populations. An elevated malignant cell ratio and reduced lymphocytes were observed in the high LMES group. Moreover, the LMRPgenes predictive model, consisting of 14 genes, showed great predictive power. The risk score emerged as an independent indicator of poor outcomes. Inverse relationships between the RS and immune status were noted, and a high RS was associated with impaired immunotherapy responses. Drug sensitivity assays indicated the effectiveness of bortezomib, buparlisib, dinaciclib, staurosporine, rapamycin, and MST-312 in the high-RS group, suggesting their potential for treating patients with high-RS values and poor response to immunotherapy. Ultimately, upon verification via qRT-PCR, we observed a significant upregulation of ACBD6 in NDMM group compared to the control group.Our research enhances the knowledge base regarding the association between lipid metabolism-related genes (LMRGs) and the BMM in MM patients, offering substantive insights into the mechanistic effects of the BMM mediated by LMRGs.

Loss of GABARAP mediates resistance to immunogenic chemotherapy in multiple myeloma

ABSTRACT

Immunogenic cell death (ICD) is a form of cell death by which cancer treatments can induce a clinically relevant antitumor immune response in a broad range of cancers. In multiple myeloma (MM), the proteasome inhibitor bortezomib is an ICD inducer and creates durable therapeutic responses in patients. However, eventual relapse and resistance to bortezomib appear inevitable. Here, by integrating patient transcriptomic data with an analysis of calreticulin (CRT) protein interactors, we found that GABA type A receptor-associated protein (GABARAP) is a key player whose loss prevented tumor cell death from being perceived as immunogenic after bortezomib treatment. GABARAP is located on chromosome 17p, which is commonly deleted in patients with high risk MM. GABARAP deletion impaired the exposure of the eat-me signal CRT on the surface of dying MM cells in vitro and in vivo, thus reducing tumor cell phagocytosis by dendritic cells and the subsequent antitumor T-cell response. Low GABARAP was independently associated with shorter survival in patients with MM and reduced tumor immune infiltration. Mechanistically, we found that GABARAP deletion blocked ICD signaling by decreasing autophagy and altering Golgi apparatus morphology, with consequent defects in the downstream vesicular transport of CRT. Conversely, upregulating autophagy using rapamycin restored Golgi morphology, CRT exposure, and ICD signaling in GABARAPKO cells undergoing bortezomib treatment. Therefore, coupling an ICD inducer, such as bortezomib, with an autophagy inducer, such as rapamycin, may improve patient outcomes in MM, in which low GABARAP in the form of del(17p) is common and leads to worse outcomes.

The complex nature of lncRNA-mediated chromatin dynamics in multiple myeloma

Extensive genome-wide sequencing efforts have unveiled the intricate regulatory potential of long non-protein coding RNAs (lncRNAs) within the domain of haematological malignancies. Notably, lncRNAs have been found to directly modulate chromatin architecture, thereby impacting gene expression and disease progression by interacting with DNA, RNA, and proteins in a tissue- or condition-specific manner. Furthermore, recent studies have highlighted the intricate epigenetic control of lncRNAs in cancer. Consequently, this provides a rationale to explore the possibility of therapeutically targeting lncRNAs themselves or the epigenetic mechanisms that govern their activity. Within the scope of this review, we will assess the current state of knowledge regarding the epigenetic regulation of lncRNAs and how, in turn, lncRNAs contribute to chromatin remodelling in the context of multiple myeloma.

p53-regulated lncRNAs in cancers: from proliferation and metastasis to therapy

Long non-coding RNAs (lncRNAs) have been identified as master gene regulators through various mechanisms such as transcription, translation, protein modification and RNA-protein complexes. LncRNA dysregulation is frequently associated with a variety of biological functions and human diseases including cancer. The p53 network is a key tumor-suppressive mechanism that transcriptionally activates target genes to suppress cellular proliferation in human malignancies. Recent research indicates that lncRNAs play an important role in the p53 signaling pathway. In this review, we summarize the current knowledge of lncRNAs in p53-relevant functions and provide an overview of how these altered lncRNAs contribute to tumor initiation and progression. We also discuss the association between lncRNA and up- or downstream genes of p53. These findings imply that lncRNAs can help identify cellular vulnerabilities that may prove to be promising potential biomarkers and therapeutic targets for cancer treatment.

Lipid metabolic vulnerabilities of multiple myeloma

Multiple myeloma (MM) is the second most common hematological malignancy worldwide, characterized by abnormal proliferation of malignant plasma cells within a tumor-permissive bone marrow microenvironment. Metabolic dysfunctions are emerging as key determinants in the pathobiology of MM. In this review, we highlight the metabolic features of MM, showing how alterations in various lipid pathways, mainly involving fatty acids, cholesterol and sphingolipids, affect the growth, survival and drug responsiveness of MM cells, as well as their cross-talk with other cellular components of the tumor microenvironment. These findings will provide a new path to understanding the mechanisms underlying how lipid vulnerabilities may arise and affect the phenotype of malignant plasma cells, highlighting novel druggable pathways with a significant impact on the management of MM.

Pharmacogenomics: Driving Personalized Medicine

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, and metagenomics). This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. Food and Drug Administration approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multicomponent biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues, providing insights into the current status and future direction of health care. SIGNIFICANCE STATEMENT: Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.

The Expression of Serum lncRNA MIR17HG in Patients with Multiple Myeloma and Its Clinical Significance

Objective. Multiple myeloma (MM) represents a malignant tumor with abnormal proliferation of plasma cells. The current study sought to investigate the changes in serum lncRNA MIR17HG (long noncoding RNA miR-17-92a-1 cluster host gene) levels in MM patients and its values in assessing the accuracy of MM diagnosis and predicting diagnosis. Methods. First, 108MM patients and 85 healthy controls were enrolled as the study subjects. The serum levels of MIR17HG in all subjects were determined by RT-qPCR. MM patients were clinically staged according to the Durie-Salmon (DS) and international staging system (ISS), and the levels of serum MIR17HG were compared among patients at different stages. The correlation of serum MIR17H level with serum creatinine (Scr), lactate dehydrogenase (LDH), and albumin (ALB) was analyzed using the Pearson method. The accuracy of the serum MIR17HG level in identifying MM was evaluated using receiver operating characteristic curves. The progression-free survival (PFS) and overall survival (OS) curves of MM patients were plotted using the Kaplan–Meier method. Results. Serum MIR17HG levels were up-regulated in MM patients and elevated with the development of DS and ISS stages. The serum MIR17HG was positively correlated with Scr and LDH and negatively correlated with ALB in MM patients. Serum MIR17HG level >1.485 could evaluate the accuracy of identifying MM. The PFS and OS were significantly shortened in MM patients with elevated MIR17HG levels. Conclusion. Our findings collectively indicate that the serum MIR17HG can aid the evaluation of accurate MM identification, and a high serum MIR17HG level can predict poor prognosis of patients with MM.