Multiple myeloma (MM) is a common type of blood cancer affecting plasma cells originating from the lymphoid B-cell lineage. It accounts for about 10% of all hematological malignancies and can cause significant end-organ damage. The emergence of genomic technologies such as next-generation sequencing and gene expression analysis has opened new possibilities for early detection of multiple myeloma and identification of personalized treatment options. However, there remain significant challenges to overcome in MM research, including integrating multi-omics data, achieving a comprehensive understanding of the disease, and developing targeted therapies and biomarkers. The extensive data generated by these technologies presents another challenge for data analysis and interpretation. To bridge this gap, we have developed a multi-omics open-access database called MyeloDB. It includes gene expression profiling, high-throughput CRISPR-Cas9 screens, drug sensitivity resources profile, and biomarkers. MyeloDB contains 47 expression profiles, 3 methylation profiles comprising a total of 5630 patient samples and 25 biomarkers which were reported in previous studies. In addition to this, MyeloDB can provide significant insight of gene mutations in MM on drug sensitivity. Furthermore, users can download the datasets and conduct their own analyses. Utilizing this database, we have identified five novel genes, i.e., CBFB, MANF, MBNL1, SEPHS2, and UFM1 as potential drug targets for MM. We hope MyeloDB will serve as a comprehensive platform for researchers and foster novel discoveries in MM. MyeloDB Database URL: https://project.iith.ac.in/cgntlab/myelodb/.

多发性骨髓瘤 (MM) 是一种常见的血癌类型，影响源自淋巴 B 细胞谱系的浆细胞。它约占所有血液系统恶性肿瘤的 10%，可导致严重的终末器官损伤。下一代测序和基因表达分析等基因组技术的出现为多发性骨髓瘤的早期检测和个性化治疗方案的确定开辟了新的可能性。然而，多发性骨髓瘤研究仍然存在重大挑战需要克服，包括整合多组学数据、全面了解该疾病以及开发靶向疗法和生物标志物。这些技术生成的大量数据给数​​据分析和解释带来了另一个挑战。为了弥补这一差距，我们开发了一个名为 MyeloDB 的多组学开放访问数据库。它包括基因表达谱、高通量 CRISPR-Cas9 筛选、药物敏感性资源谱和生物标志物。MyeloDB 包含 47 个表达谱、3 个甲基化谱（包括总共 5630 个患者样本）和 25 个生物标志物，这些都在之前的研究中报告过。除此之外，MyeloDB 还可以提供 MM 基因突变对药物敏感性的重要见解。此外，用户可以下载数据集并进行自己的分析。利用该数据库，我们确定了CBFB、MANF、MBNL1、SEPHS2和UFM1五个新基因作为 MM 的潜在药物靶点。我们希望 MyeloDB 能够成为研究人员的综合平台，并促进 MM 领域的新发现。MyeloDB 数据库 URL：https://project.iith.ac.in/cgntlab/myelodb/。