Determining the role of LSD1 in multiple myeloma through a multi-omics approach at single cell resolution

通过单细胞分辨率的多组学方法确定 LSD1 在多发性骨髓瘤中的作用

• 批准号: 10547824
• 负责人: Michael Edward Vinyard
• 金额: $ 4.25万
• 依托单位: HARVARD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-04 至 2026-01-03
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10547824
• 关键词: Acute Myelocytic Leukemia; Address; Architecture; Automobile Driving; Blood; Blood Cells; Bone Marrow; Cell Differentiation process; Cells; Cellular biology; Chromatin; Clinical Trials; Clonal Expansion; Collaborations; Computing Methodologies; DNA; Data; Development; Diagnosis; Differential Equation; Dimensions; Disease; Disease Progression; Doctor of Philosophy; Drug Design; Drug Targeting; Drug resistance; Epigenetic Process; Equation; Event; Gene Expression; Gene Expression Profiling; Gene Expression Regulation; Genes; Genetic; Genetic Heterogeneity; Genomics; Growth; Hematologic Neoplasms; Hematopoietic Neoplasms; Heritability; Histones; Investigation; KDM1A gene; Learning; Life; Link; Lysine; Machine Learning; Malignant - descriptor; Malignant Neoplasms; Mathematics; Mediating; Methods; Modeling; Multiple Myeloma; Mutation; Neoplasms; Oncogenes; Oncogenic; Patients; Persons; Pharmaceutical Preparations; Plasma Cells; Plasma Enhancement; Play; Precancerous Conditions; Process; Proliferating; Proteins; Publishing; Regulation; Regulatory Element; Repression; Research; Resolution; Role; Sampling; Shapes; Susceptibility Gene; System; Techniques; Testing; Therapeutic Intervention; Tissues; Tumor Suppressor Proteins; United States; Visualization; Work; acute myeloid leukemia cell; autosome; bone cell; cell growth; cohort; comparative; computer framework; computerized tools; disorder prevention; epigenome; epigenomics; experimental study; gene regulatory network; high dimensionality; improved; insight; machine learning method; multiple omics; neural; novel; patient subsets; prevent; rate of change; reconstruction; single-cell RNA sequencing; transcription factor; transcriptomics

PROJECT SUMMARY / ABSTRACT Multiple myeloma (MM) kills nearly 13,000 people annually in the United States1. MM is preceded by a less life- threating blood condition, which is similar to MM, yet non-lethal and asymptomatic2. in fact, most people don’t even know they have it. An outstanding question in MM research is why some patients diagnosed with the precursor condition go on to develop the full disease and why others do not. This question has been approached from a genetics standpoint, however there is no clear genetic link defining who goes on to develop MM from a precursor condition and who does not. Bone marrow creates a microenvironment to support developing blood cells. Multiple myeloma hijacks the bone marrow microenvironment (BMM) to favor its own growth3. Without a genetic driver of cancer development, I hypothesize that the BMM is modified epigenetically to facilitate the selective growth of MM. Epigenetics encompasses that which influences the expression of genes without altering the genes themselves. Chromatin regulators (CRs) are proteins that mediate epigenetic changes through altering the ability of a cell to express a given gene. CRs carry out this process through modifying the histone proteins around which genes are wrapped (histones and DNA taken together comprise chromatin, hence: chromatin regulators). In addition to these very specific functions, CRs can also mediate interactions with transcription factors (TFs), the proteins that turn the expression levels of genes up or down. A specific CR LSD1, which is known to repress or turn off genes, has been the target of other blood cancer diseases and drugs designed to block LSD1 activity are quite effective in models of acute myeloid leukemia (AML)45. These drugs work by disrupting an interaction between LSD1 and another protein. When that interaction is disrupted, a master TF is able to turn on genes that cause AML cells to die5. Despite some similarities between AML and MM, treatment with LSD1-targeting drugs actually enhances the growth of MM6. Interestingly, a small subset of patients have been found to be predisposed to MM development through a heritable set of mutations in LSD1 – these mutations mimic mutations that confer drug resistance in AML5,6. While these mutations only make up a small fraction of MM cases, it points to LSD1 as a key component in the development of MM7. I thereby hypothesize that LSD1 plays a role in the progression of MM; this role is potentially specific to the BMM. The specific aims of this project can be summarized as follows: 1. Develop a computational tool using novel techniques from machine learning and mathematics to learn about factors that drive the BMM to contribute to the progression of MM. 2. Collect BMM samples from patients across a spectrum of MM development to analyze single cell gene expression and chromatin accessibility data to learn the ways in which the epigenome is altered as MM progresses in the BMM.

项目摘要/摘要