The Landscape of lncRNAs in Multiple Myeloma: Implications in the "Hallmarks of Cancer", Clinical Perspectives and Therapeutic Opportunities

LINC01432 binds to CELF2 in newly diagnosed multiple myeloma promoting short progression-free survival to standard therapy

Multiple Myeloma (MM) is a highly prevalent and incurable form of cancer that arises from malignant plasma cells, with over 35,000 new cases diagnosed annually in the United States. While there are a growing number of approved therapies, MM remains incurable and nearly all patients will relapse and exhaust all available treatment options. Mechanisms for disease progression are unclear and in particular, little is known regarding the role of long non-coding RNAs (lncRNA) in mediating disease progression and response to treatment. In this study, we used transcriptome sequencing to compare newly diagnosed MM patients who had short progression-free survival (PFS) to standard first-line treatment (PFS < 24 months) to patients who had prolonged PFS (PFS > 24 months). We identified 157 differentially upregulated lncRNAs with short PFS and focused our efforts on characterizing the most upregulated lncRNA, LINC01432. We investigated LINC01432 overexpression and CRISPR/Cas9 knockdown in MM cell lines to show that LINC01432 overexpression significantly increases cell viability and reduces apoptosis, while knockdown significantly reduces viability and increases apoptosis, supporting the clinical relevance of this lncRNA. Next, we used individual-nucleotide resolution cross-linking immunoprecipitation with RT-qPCR to show that LINC01432 directly interacts with the RNA binding protein, CELF2. Lastly, we showed that LINC01432-targeted locked nucleic acid antisense oligonucleotides reduce viability and increases apoptosis. In summary, this fundamental study identified lncRNAs associated with short PFS to standard NDMM treatment and further characterized LINC01432, which inhibits apoptosis.

DeepIMAGER: Deeply Analyzing Gene Regulatory Networks from scRNA-seq Data

Understanding the dynamics of gene regulatory networks (GRNs) across diverse cell types poses a challenge yet holds immense value in unraveling the molecular mechanisms governing cellular processes. Current computational methods, which rely solely on expression changes from bulk RNA-seq and/or scRNA-seq data, often result in high rates of false positives and low precision. Here, we introduce an advanced computational tool, DeepIMAGER, for inferring cell-specific GRNs through deep learning and data integration. DeepIMAGER employs a supervised approach that transforms the co-expression patterns of gene pairs into image-like representations and leverages transcription factor (TF) binding information for model training. It is trained using comprehensive datasets that encompass scRNA-seq profiles and ChIP-seq data, capturing TF-gene pair information across various cell types. Comprehensive validations on six cell lines show DeepIMAGER exhibits superior performance in ten popular GRN inference tools and has remarkable robustness against dropout-zero events. DeepIMAGER was applied to scRNA-seq datasets of multiple myeloma (MM) and detected potential GRNs for TFs of RORC, MITF, and FOXD2 in MM dendritic cells. This technical innovation, combined with its capability to accurately decode GRNs from scRNA-seq, establishes DeepIMAGER as a valuable tool for unraveling complex regulatory networks in various cell types.

Identification and evaluation of a six-lncRNA prognostic signature for multiple myeloma

PURPOSE

Multiple myeloma (MM) is the second most common hematologic malignancy, and there is no cure for this disease. This study aimed to explore the prognostic value of long noncoding RNAs (lncRNAs) in MM and to reveal related immune and chemotherapy resistance mechanisms.

METHODS

In this study, lncRNA profiles from the Multiple Myeloma Research Foundation (MMRF) and Gene Expression Omnibus (GEO) databases were analyzed to identify lncRNAs linked to MM patient survival. A risk assessment model stratified patients into high- and low-risk groups, and survival was evaluated. Additionally, a triple-ceRNA (lncRNA-miRNA-mRNA) network was constructed, and functional analysis was performed. The research also involved immune function analysis and chemotherapy drug sensitivity assessment using oncoPredict and the GDSC dataset.

RESULTS

We identified 422 lncRNAs significantly associated with overall survival in MM patients and ultimately focused on the 6 with the highest prognostic value. These lncRNAs were used to develop a risk score formula that stratified patients into high- and low-risk groups. Kaplan-Meier analysis revealed shorter survival in high-risk patients. We integrated this lncRNA signature with clinical parameters to construct a nomogram for predicting MM prognosis. Additionally, a triple-ceRNA network was constructed to reveal potential miRNA targets, coding genes related to these lncRNAs and significantly enriched pathways. Immune checkpoint gene expression and immune cell composition were also analyzed in relation to the lncRNA risk score. Finally, using the oncoPredict tool, we observed that high-risk patients exhibited decreased sensitivity to key MM chemotherapeutics, suggesting that lncRNA profiles are linked to chemotherapy resistance.

Exosomal lncRNA NEAT1 Inhibits NK-Cell Activity to Promote Multiple Myeloma Cell Immune Escape via an EZH2/PBX1 Axis

Exosomal long noncoding RNAs (lncRNA) derived from cancer cells are implicated in various processes, including cancer cell proliferation, metastasis, and immunomodulation. We investigated the role and underlying mechanism of exosome-transmitted lncRNA NEAT1 in the immune escape of multiple myeloma cells from natural killer (NK) cells. Multiple myeloma cells and samples from patients with multiple myeloma were obtained. The effects of multiple myeloma cell-derived exosomes (multiple myeloma exosomes) and exosomal NEAT1 on the functions of NK cells were evaluated using EdU staining, CCK-8, flow cytometry, and ELISA. Chromatin and RNA immunoprecipitation were performed to identify interactions between NEAT1, enhancer of Zeste Homolog 2 (EZH2), and pre-B-cell leukemia transcription factor 1 (PBX1). A xenograft tumor model was constructed to verify the effects of exosomal NEAT1 on tumor growth. qRT-PCR, Western blot analysis, and IHC were conducted to detect related genes. NEAT1 levels were upregulated in multiple myeloma tumor tissues, multiple myeloma cells, and multiple myeloma exosomes. Multiple myeloma exosomes suppressed cell proliferation, promoted apoptosis, reduced natural killer group 2, member D (NKG2D)-positive cells, and the production of TNFα) and interferon-gamma (IFN-γ) in NK cells, whereas NEAT1-silenced exosomes had little effect. NEAT1 silenced PBX1 by recruiting EZH2. PBX1 knockdown abrogated the effects of NEAT1-silenced exosomes on NK and multiple myeloma cells. NEAT1-silenced exosomes inhibited tumor growth in mice, decreased Ki67 and PD-L1, and increased NKG2D, TNFα, and IFNγ in tumor tissues. In summary, multiple myeloma cell-derived exosomal NEAT1 suppressed NK-cell activity by downregulating PBX1, promoting multiple myeloma cell immune escape. This study suggests a potential strategy for treating multiple myeloma.

IMPLICATIONS

This study reveals that exosomal NEAT1 regulates EZH2/PBX1 axis to inhibit NK-cell activity, thereby promoting multiple myeloma cell immune escape, which offers a novel therapeutic potential for multiple myeloma.

PVT1 interacts with polycomb repressive complex 2 to suppress genomic regions with pro-apoptotic and tumour suppressor functions in multiple myeloma

Multiple myeloma is a heterogeneous hematological disease that originates from the bone marrow and is characterized by the monoclonal expansion of malignant plasma cells. Despite novel therapies, multiple myeloma remains clinically challenging. A common feature among patients with poor prognosis is the increased activity of the epigenetic silencer EZH2, which is the catalytic subunit of the PRC2. Interestingly, the recruitment of PRC2 lacks sequence specificity and, to date, the molecular mechanisms that define which genomic locations are destined for PRC2-mediated silencing remain unknown. The presence of a long non-coding RNA (lncRNA)-binding pocket on EZH2 suggests that lncRNA could potentially mediate PRC2 recruitment to specific genomic regions. Here, we coupled RNA immunoprecipitation sequencing, RNA-sequencing and chromatin immunoprecipitation-sequencing analysis of human multiple myeloma primary cells and cell lines to identify potential lncRNA partners to EZH2. We found that the lncRNA plasmacytoma variant translocation 1 (PVT1) directly interacts with EZH2 and is overexpressed in patients with a poor prognosis. Moreover, genes predicted to be targets of PVT1 exhibited H3K27me3 enrichment and were associated with pro-apoptotic and tumor suppressor functions. In fact, PVT1 inhibition independently promotes the expression of the PRC2 target genes ZBTB7C, RNF144A and CCDC136. Altogether, our work suggests that PVT1 is an interacting partner in PRC2-mediated silencing of tumor suppressor and pro-apoptotic genes in multiple myeloma, making it a highly interesting potential therapeutic target.

Combination of multiple omics techniques for a personalized therapy or treatment selection

Despite targeted therapies and immunotherapies have revolutionized the treatment of cancer patients, only a limited number of patients have long-term responses. Moreover, due to differences within cancer patients in the tumor mutational burden, composition of the tumor microenvironment as well as of the peripheral immune system and microbiome, and in the development of immune escape mechanisms, there is no "one fit all" therapy. Thus, the treatment of patients must be personalized based on the specific molecular, immunologic and/or metabolic landscape of their tumor. In order to identify for each patient the best possible therapy, different approaches should be employed and combined. These include (i) the use of predictive biomarkers identified on large cohorts of patients with the same tumor type and (ii) the evaluation of the individual tumor with "omics"-based analyses as well as its ex vivo characterization for susceptibility to different therapies.

Anti-Angiogenic Activity of Drugs in Multiple Myeloma

Angiogenesis represents a pivotal hallmark of multiple myeloma (MM) that correlates to patients’ prognosis, overall survival, and drug resistance. Hence, several anti-angiogenic drugs that directly target angiogenic cytokines (i.e., monoclonal antibodies, recombinant molecules) or their cognate receptors (i.e., tyrosine kinase inhibitors) have been developed. Additionally, many standard antimyeloma drugs currently used in clinical practice (i.e., immunomodulatory drugs, bisphosphonates, proteasome inhibitors, alkylating agents, glucocorticoids) show anti-angiogenic effects further supporting the importance of inhibiting angiogenesis from potentiating the antimyeloma activity. Here, we review the most important anti-angiogenic therapies used for the management of MM patients with a particular focus on their pharmacological profile and on their anti-angiogenic effect in vitro and in vivo. Despite the promising perspective, the direct targeting of angiogenic cytokines/receptors did not show a great efficacy in MM patients, suggesting the need to a deeper knowledge of the BM angiogenic niche for the design of novel multi-targeting anti-angiogenic therapies.

Noncoding RNAs in the crosstalk between multiple myeloma cells and bone marrow microenvironment

Multiple myeloma (MM) is the second most common hematological malignancy; however, it remains incurable, and the underlying pathogenesis and mechanisms of drug resistance remain unclear. It is widely recognized that the bone marrow microenvironment plays a crucial role in regulating the immune response, inducing drug resistance, and promoting tumor proliferation and invasion in MM, and thus serves as a potential therapeutic target. Among the various signaling loops between myeloma cells and components of the microenvironment, noncoding RNAs are emerging as crucial regulators of intercellular communication within the microenvironment. Noncoding RNAs, such as microRNAs, long noncoding RNAs, circular RNAs, and PIWI-interacting RNAs, have been associated with numerous biological processes involved in myeloma cell growth, survival, migration, invasion, and drug resistance. This review summarizes recent advances in the regulatory mechanisms of noncoding RNAs involved in the interaction between the MM bone marrow microenvironment and discusses the therapeutic potential of noncoding RNAs in MM.

Expression levels of NONO, a nuclear protein primarily involved in paraspeckles function, are associated with several deregulated molecular pathways and poor clinical outcome in multiple myeloma

PURPOSE

The NONO protein belongs to the multifunctional family of proteins that can bind DNA, RNA and proteins. It is located in the nucleus of most mammalian cells and can affect almost every step of gene regulation. Dysregulation of NONO has been found in many types of cancer; however, data regarding its expression and relevance in Multiple Myeloma (MM) are virtually absent.

METHODS

We took advantage of a large cohort of MM patients enrolled in the Multiple Myeloma Research Foundation CoMMpass study to elucidate better the clinical and biological relevance of NONO expression in the context of the MM genomic landscape and transcriptome.

RESULTS

NONO is overexpressed in pathological samples compared to normal controls. In addition, higher NONO expression levels are significant independent prognostic markers of worse clinical outcome in MM. Our results indicate that NONO deregulation may play a pathogenetic role in MM by affecting cell cycle, DNA repair mechanisms, and influencing translation by regulating ribosome biogenesis and assembly. Furthermore, our data suggest NONO involvement in the metabolic reprogramming of glucose metabolism from respiration to aerobic glycolysis, a phenomenon known as the 'Warburg Effect' that supports rapid cancer cell growth, survival, and invasion.

CONCLUSION

These findings strongly support the need of future investigations for the understanding of the mechanisms of deregulation and the biological role and activity of NONO in MM.

Mechanisms of carcinogenic activity triggered by lysine-specific demethylase 1A

Epigenetics has emerged as a prime focus area in the field of cancer research. Lysine-specific demethylase 1A (LSD1), the first discovered histone demethylase, is mainly responsible for catalysing demethylation of histone 3 lysine 4 (H3K4) and H3K9 to activate or inhibit gene transcription. LSD1 is abnormally expressed in various cancers and participates in cancer proliferation, apoptosis, metastasis, invasion, drug resistance and other processes by interacting with regulatory factors. Therefore, it may serve as a potential therapeutic target for cancer. This review summarises the major oncogenic mechanisms mediated by LSD1 and provides a reference for developing novel and efficient anticancer strategies targeting LSD1.