Fig. 5

Adverse pathological features of drug resistance recurrence in MM patients observed at the single-cell level. A Expression patterns of drug targets in malignant subclones and tumor microenvironment cells. Left: Bubble size represents the number of drugs with resistance in patients with RRMM. The connecting lines are colored according to the drug. Middle: Bubbles of different colors represent the tolerance of RRMM patients to different drugs, and the size represents the number of targets. Right: Expression of drug targets in malignant subclones and tumor microenvironment cells. B Single-cell contribution of DEGs in RRMM patients compared with NDMM patients. DEGs are expressed at the single-cell level (left), the average expression pattern at the cell cluster level (middle), and the differential expression (logFC) at the cell cluster level (right) in the malignant subclones and tumor microenvironment of NDMM and RRMM patients. C Biological signals related to drug resistance. These biological signals were significantly activated and inhibited in RRMM patients compared with NDMM patients in the six shared malignant subclones. Inhibitory signals included apoptosis, FoxO, and p53. The activated signals involved signals related to survival, proliferation, migration, and stem cell characteristics, such as calcium/Rap1/JAK-STAT/VEGF/mTOR signaling. Each edge represents a comparison of the NDMM and RRMM groups for any of the six shared malignant subclones with correlation signal scores in types I, II, III, VIII, IX, X, and XI. D Drug resistance-related genes significantly involved in signaling pathways. The DEGs of shared malignant subclones in RRMM patients compared with NDMM patients are identified as drug resistance-related genes. Top: DEGs and their significant signaling pathways. Middle: malignant driver of DEGs involving GRN, SNV, and CNV. Bottom: DEGs expression changes in six shared malignant subclones. E Clonal evolution mediates the signaling pathways significantly involved in drug resistance-related genes. Top: MM malignant clonal evolution mediates drug resistance-related genes and their biological signals. Middle: Malignant drivers of malignant clonal evolution of MM involving GRN, SNV, and CNV. Bottom: Drug resistance-related genes clustered into two gene expression modules during the evolution of MM malignant clones. F Comprehensive regulatory network of drug resistance in patients with RRMM. MM malignant subclones not only inhibit their own apoptosis-related signals and activate their own survival-promoting, proliferation, migration, and stem cell characteristics related signals but also reprogram microenvironment immune cells through intercellular communication, driving the latter to activate drug metabolism signals, thereby improving the drug microenvironment and survival probability. G Prognostic potential of drug resistance-related genes in a large-scale MM clinical patient training cohort. H Prognostic value of drug resistance-related genes in a large-scale MM clinical patient cohort based on the multivariate Cox model. I Time-independent ROC curves for evaluating the prediction performance of the prognostic model in MM patients’ OS and RFS. NDMM, newly diagnosed multiple myeloma; RRMM, refractory or recurrent multiple myeloma; GRN, gene regulation network; CNV, copy number variations; SNV, single nucleotide variation; DEG, differentially expressed gene; OS, overall survival; RFS, recurrence-free survival