Identification of Therapy-Induced Clonal Evolution and Resistance Pathways in Minimal Residual Clones in Multiple Myeloma through Single-Cell Sequencing

Author:

Cui Jian12ORCID,Li Xiaoyun12ORCID,Deng Shuhui123ORCID,Du Chenxing12ORCID,Fan Huishou4ORCID,Yan Wenqiang12ORCID,Xu Jingyu12ORCID,Li Xiaoqing5ORCID,Yu Tengteng12ORCID,Zhang Shuaishuai12ORCID,Lv Rui12ORCID,Sui Weiwei12ORCID,Hao Mu12ORCID,Du Xin5ORCID,Xu Yan12ORCID,Yi Shuhua12ORCID,Zou Dehui12ORCID,Cheng Tao12ORCID,Qiu Lugui126ORCID,Gao Xin12ORCID,An Gang126ORCID

Affiliation:

1. State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Tianjin, China. 1

2. Tianjin Institutes of Health Science, Tianjin, China. 2

3. LeBow Institute for Myeloma Therapeutics and Jerome Lipper Center for Multiple Myeloma Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts. 3

4. Department of Hematology, Affiliated Hospital of Qingdao University, Qingdao, China. 4

5. Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, China. 5

6. Institute of Multiple Myeloma, Beijing GoBroad Boren Hospital, Beijing, China. 6

Abstract

Abstract Purpose: In multiple myeloma (MM), therapy-induced clonal evolution is associated with treatment resistance and is one of the most important hindrances toward a cure for MM. To further understand the molecular mechanisms controlling the clonal evolution of MM, we applied single-cell RNA sequencing (scRNA-seq) to paired diagnostic and posttreatment bone marrow (BM) samples. Experimental Design: scRNA-seq was performed on 38 BM samples from patients with monoclonal gammopathy of undetermined significance (n = 1), MM patients at diagnosis (n = 19), MM posttreatment (n = 17), and one healthy donor (HD). The single-cell transcriptome data of malignant plasma cells (PC) and the surrounding immune microenvironment were analyzed. Results: Profiling by scRNA-seq data revealed three primary trajectories of transcriptional evolution after treatment: clonal elimination in patients with undetectable minimal residual disease (MRD−) and clonal stabilization and clonal selection in detectable MRD (MRD+) patients. We noted a metabolic shift toward fatty acid oxidation in cycling-resistant PCs, whereas selective PCs favored the NF-κB pathway. Intriguingly, when comparing the genetic and transcriptional dynamics, we found a significant correlation between genetic and nongenetic factors in driving the clonal evolution. Furthermore, we identified variations in cellular interactions between malignant PCs and the tumor microenvironment. Selective PCs showed the most robust cellular interactions with the tumor microenvironment. Conclusions: These data suggest that MM cells could rapidly adapt to induction treatment through transcriptional adaptation, metabolic adaptation, and specialized immune evasion. Targeting therapy-induced resistance mechanisms may help to avert refractory disease in MM.

Funder

National Natural Science Foundation of China

Chinese Academy of Medical Sciences Initiative for Innovative Medicine

International Cooperation and Exchange Programme

International Myeloma Society

National Youth Foundation of China

Publisher

American Association for Cancer Research (AACR)

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