Proteogenomic characterization of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

Identification and Verification of Ubiquitin D as a Gene Associated with Hepatitis C Virus-Induced Hepatocellular Carcinoma.

INTRODUCTION: Accumulated studies have suggested that hepatitis C virus (HCV) infection is one of the leading causes for hepatocellular carcinoma (HCC). However, the mechanisms underlying the effect of HCV on the occurrence of HCC are still poorly understood. METHODS: HCV infection datasets (GSE82177 and GSE17856) and HCC datasets (The Cancer Genome Atlas Liver Hepatocellular Carcinoma and GSE89377) were downloaded from Gene Expression Omnibus or TCGA for analysis. The common differentially expressed genes in the above four datasets were identified by R software. The expression of ubiquitin D (UBD) in HCV-infected HepG2 cells was detected by RT-qPCR and Western blot, respectively. The interaction between NS3 and p53 was detected by co-immunoprecipitation. The influence of UBD on the proliferation and migration ability of HepG2 cells was evaluated by CCK-8 and wound healing assay, respectively. RESULTS: UBD was upregulated in both HCV-infected samples and HCC samples. HCV NS3 interacted with p53 and inhibited its expression. HCV NS3-induced UBD promoted the proliferation and migration of HepG2 cells. CONCLUSION: Our results suggest that HCV NS3-induced UBD is positively correlated with the development of HCV-related HCC during HCV infection. Targeting UBD could be a potential strategy for preventing and treating HCV-induced HCC.

[Statins enhance anti-tumor effect of suberoylanilide hydroxamic acid on human non-small cell lung carcinoma cells].

OBJECTIVE: To evaluate the anti-tumor effect of the combination of suberoylanilide hydroxamic acid(SAHA) with statins(lovastatin or simvastatin) on non-small cell lung carcinoma(NSCLC) cells. METHODS: Human NSCLC A549 cells were treated with SAHA in combination of lovastatin or simvastatin. The cell growth was analyzed by SRB method, and the apoptosis of A549 cells was assessed by flow cytometer. The expression of cleaved poly-ADP-ribose polymerase(cleaved-PARP) and p21 protein was analyzed by Western-blotting when A549 cells were challenged with 2.5µmol/L SAHA and 5µmol/L lovastatin. RESULTS: Lovastatin and simvastatin synergized SAHA in the inhibition of A549 cells. SAHA induced apoptosis was also enhanced by lovastatin. Treatment with 2.5µmol/L SAHA significantly up-regulated the expression of p21 protein in 48 h, while the protein expression was reduced in combined treatment with 5µmol/L lovastatin. CONCLUSION: Statins can synergize the anti-tumor effect of SAHA in human NSCLC cells through a p21-dependent way.

ATP6V1D drives hepatocellular carcinoma stemness and progression via both lysosome acidification-dependent and -independent mechanisms.

Metabolic reprogramming is pivotal in cancer stem cell (CSC) self-renewal. However, the intricate regulatory mechanisms governing the crosstalk between metabolic reprogramming and liver CSCs remain elusive. Here, using a metabolic CRISPR-Cas9 knockout screen, we identify ATP6V1D, a subunit of the vacuolar-type H+-translocating ATPase (V-ATPase), as a key metabolic regulator of hepatocellular carcinoma (HCC) stemness. Elevated ATP6V1D expression correlates with poor clinical outcomes in HCC patients. ATP6V1D knockdown inhibits HCC stemness and malignant progression both in vitro and in vivo. Mechanistically, ATP6V1D enhances HCC stemness and progression by maintaining macroautophagic/autophagic flux. Specifically, ATP6V1D not only promotes lysosomal acidification, but also enhances the interaction between CHMP4B and IST1 to foster ESCRT-III complex assembly, thereby facilitating autophagosome-lysosome fusion to maintain autophagic flux. Moreover, silencing CHMP4B or IST1 attenuates HCC stemness and progression. Notably, low-dose bafilomycin A1 targeting the V-ATPase complex shows promise as a potential therapeutic strategy for HCC. In conclusion, our study highlights the critical role of ATP6V1D in driving HCC stemness and progression via the autophagy-lysosomal pathway, providing novel therapeutic targets and approaches for HCC treatment.Abbreviations: 3-MA: 3-methyladenine; ANT: adjacent normal liver tissues; ATP6V1D: ATPase H+ transporting V1 subunit D; BafA1: bafilomycin A1; CHMP: charged multivesicular body protein; co-IP: co-immunoprecipitation; CSC: cancer stem cell; ESCRT: endosomal sorting complex required for transport; HCC: hepatocellular carcinoma; IF: immunofluorescence; IHC: immunohistochemical; LCSCs: liver cancer stem cells; qRT-PCR: quantitative real time PCR; V-ATPase: vacuolar-type H+- translocating ATPase; WB: western blot.

Erratum to 'B4GALNT1 promotes hepatocellular carcinoma stemness and progression via integrin α2ß1-mediated FAK and AKT activation' (JHEP Reports 5 [2023] 100903).

[This corrects the article DOI: 10.1016/j.jhepr.2023.100903.].

TMX2 potentiates cell viability of hepatocellular carcinoma by promoting autophagy and mitophagy.

The dysregulation of membrane protein expression has been implicated in tumorigenesis and progression, including hepatocellular carcinoma (HCC). In this study, we aimed to identify membrane proteins that modulate HCC viability. To achieve this, we performed a CRISPR activation screen targeting human genes encoding membrane-associated proteins, revealing TMX2 as a potential driver of HCC cell viability. Gain- and loss-of-function experiments demonstrated that TMX2 promoted growth and tumorigenesis of HCC. Clinically, TMX2 was an independent prognostic factor for HCC patients. It was significantly upregulated in HCC tissues and associated with poor prognosis of HCC patients. Mechanistically, TMX2 was demonstrated to promote macroautophagy/autophagy by facilitating KPNB1 nuclear export and TFEB nuclear import. In addition, TMX2 interacted with VDAC2 and VADC3, assisting in the recruitment of PRKN to defective mitochondria to promote cytoprotective mitophagy during oxidative stress. Most interestingly, HCC cells responded to oxidative stress by upregulating TMX2 expression and cell autophagy. Knockdown of TMX2 enhanced the anti-tumor effect of lenvatinib. In conclusion, our findings emphasize the pivotal role of TMX2 in driving the HCC cell viability by promoting both autophagy and mitophagy. These results suggest that TMX2 May serve as a prognostic marker and promising therapeutic target for HCC treatment.Abbreviation: CCCP: Carbonyl cyanide 3-chlorophenylhydrazone; Co-IP: co-immunoprecipitation; CRISPR: clustered regularly interspaced short palindromic repeat; ER: endoplasmic reticulum; HCC: hepatocellular carcinoma; KPNB1: karyopherin subunit beta 1; PRKN: parkin RBR E3 ubiquitin protein ligase; ROS: reactive oxygen species; TFEB: transcription factor EB; TMX2: thioredoxin related transmembrane protein 2; VDAC2: voltage dependent anion channel 2; VDAC3: voltage dependent anion channel 3; WB: western blot.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages.

Breast cancer (BC) is defined by distinct molecular subtypes with different cells of origin. The transcriptional networks that characterize the subtype-specific tumor-normal lineages are not established. In this work, we applied bulk, single-cell and single-nucleus multi-omic techniques as well as spatial transcriptomics and multiplex imaging on 61 samples from 37 patients with BC to show characteristic links in gene expression and chromatin accessibility between BC subtypes and their putative cells of origin. Regulatory network analysis of transcription factors underscored the importance of BHLHE40 in luminal BC and luminal mature cells and KLF5 in basal-like tumors and luminal progenitor cells. Furthermore, we identify key genes defining the basal-like (SOX6 and KCNQ3) and luminal A/B (FAM155A and LRP1B) lineages. Exhausted CTLA4-expressing CD8+ T cells were enriched in basal-like BC, suggesting an altered means of immune dysfunction. These findings demonstrate analysis of paired transcription and chromatin accessibility at the single-cell level is a powerful tool for investigating cancer lineage and highlight transcriptional networks that define basal and luminal BC lineages.

B4GALNT1 promotes hepatocellular carcinoma stemness and progression via integrin α2ß1-mediated FAK and AKT activation.

Background & Aims: ß-1,4-N-Acetyl-galactosaminyltransferase 1 (B4GALNT1) has been reported to contribute to the development of human malignancies. However, its role in hepatocellular carcinoma (HCC) remains uncharacterised. In this study, we aimed to elucidate the role of B4GALNT1 in HCC stemness and progression. Methods: Immunohistochemical staining was used to evaluate B4GALNT1 expression in HCC tissues and adjacent normal liver tissues. Flow cytometry analysis and sphere formation analysis were performed to investigate the role of B4GALNT1 in HCC stemness. Colony formation, Incucyte, wound-healing, Transwell migration, and invasion assays, and an animal model were used to study the role of B4GALNT1 in HCC progression. RNA-sequencing and co-immunoprecipitation were used to investigate the downstream targets of B4GALNT1. Results: B4GALNT1 was upregulated in HCC and associated with poor clinical outcome of patients with the disease. Moreover, B4GALNT1 promoted HCC stemness, migration, invasion, and growth. Mechanistically, B4GALNT1 not only promoted the expression of the integrin α2ß1 ligand THBS4, but also directly interacted with the ß subunit of integrin α2ß1 ITGB1 to inhibit its ubiquitin-independent proteasomal degradation, resulting in activation of FAK and AKT. Ophiopogonin D inhibited HCC stemness and progression by reducing ITGB1 and THBS4 expression and inhibiting FAK and AKT activation. Conclusions: Our study suggests the B4GALNT1/integrin α2ß1/FAK/PI3K/AKT axis as a therapeutic target for the inhibition of HCC stemness and tumour progression. Impact and implications: The role and regulatory mechanism of B4GALNT1 in HCC have not been studied previously. Here, we reveal that B4GALNT1 has a crucial role in HCC stemness and progression by activating the integrin α2ß1/FAK/PI3K/AKT axis, providing a potential target for HCC therapy. In addition, we find Ophiopogonin D as a potential therapeutic drug for patients with HCC.

Single-Cell Discovery and Multiomic Characterization of Therapeutic Targets in Multiple Myeloma.

Multiple myeloma (MM) is a highly refractory hematologic cancer. Targeted immunotherapy has shown promise in MM but remains hindered by the challenge of identifying specific yet broadly representative tumor markers. We analyzed 53 bone marrow (BM) aspirates from 41 MM patients using an unbiased, high-throughput pipeline for therapeutic target discovery via single-cell transcriptomic profiling, yielding 38 MM marker genes encoding cell-surface proteins and 15 encoding intracellular proteins. Of these, 20 candidate genes were highlighted that are not yet under clinical study, 11 of which were previously uncharacterized as therapeutic targets. The findings were cross-validated using bulk RNA sequencing, flow cytometry, and proteomic mass spectrometry of MM cell lines and patient BM, demonstrating high overall concordance across data types. Independent discovery using bulk RNA sequencing reiterated top candidates, further affirming the ability of single-cell transcriptomics to accurately capture marker expression despite limitations in sample size or sequencing depth. Target dynamics and heterogeneity were further examined using both transcriptomic and immuno-imaging methods. In summary, this study presents a robust and broadly applicable strategy for identifying tumor markers to better inform the development of targeted cancer therapy. SIGNIFICANCE: Single-cell transcriptomic profiling and multiomic cross-validation to uncover therapeutic targets identifies 38 myeloma marker genes, including 11 transcribing surface proteins with previously uncharacterized potential for targeted antitumor therapy.

Epigenetic and transcriptomic characterization reveals progression markers and essential pathways in clear cell renal cell carcinoma.

Identifying tumor-cell-specific markers and elucidating their epigenetic regulation and spatial heterogeneity provides mechanistic insights into cancer etiology. Here, we perform snRNA-seq and snATAC-seq in 34 and 28 human clear cell renal cell carcinoma (ccRCC) specimens, respectively, with matched bulk proteogenomics data. By identifying 20 tumor-specific markers through a multi-omics tiered approach, we reveal an association between higher ceruloplasmin (CP) expression and reduced survival. CP knockdown, combined with spatial transcriptomics, suggests a role for CP in regulating hyalinized stroma and tumor-stroma interactions in ccRCC. Intratumoral heterogeneity analysis portrays tumor cell-intrinsic inflammation and epithelial-mesenchymal transition (EMT) as two distinguishing features of tumor subpopulations. Finally, BAP1 mutations are associated with widespread reduction of chromatin accessibility, while PBRM1 mutations generally increase accessibility, with the former affecting five times more accessible peaks than the latter. These integrated analyses reveal the cellular architecture of ccRCC, providing insights into key markers and pathways in ccRCC tumorigenesis.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages.

Breast cancer is a heterogeneous disease, and treatment is guided by biomarker profiles representing distinct molecular subtypes. Breast cancer arises from the breast ductal epithelium, and experimental data suggests breast cancer subtypes have different cells of origin within that lineage. The precise cells of origin for each subtype and the transcriptional networks that characterize these tumor-normal lineages are not established. In this work, we applied bulk, single-cell (sc), and single-nucleus (sn) multi-omic techniques as well as spatial transcriptomics and multiplex imaging on 61 samples from 37 breast cancer patients to show characteristic links in gene expression and chromatin accessibility between breast cancer subtypes and their putative cells of origin. We applied the PAM50 subtyping algorithm in tandem with bulk RNA-seq and snRNA-seq to reliably subtype even low-purity tumor samples and confirm promoter accessibility using snATAC. Trajectory analysis of chromatin accessibility and differentially accessible motifs clearly connected progenitor populations with breast cancer subtypes supporting the cell of origin for basal-like and luminal A and B tumors. Regulatory network analysis of transcription factors underscored the importance of BHLHE40 in luminal breast cancer and luminal mature cells, and KLF5 in basal-like tumors and luminal progenitor cells. Furthermore, we identify key genes defining the basal-like ( PRKCA , SOX6 , RGS6 , KCNQ3 ) and luminal A/B ( FAM155A , LRP1B ) lineages, with expression in both precursor and cancer cells and further upregulation in tumors. Exhausted CTLA4-expressing CD8+ T cells were enriched in basal-like breast cancer, suggesting altered means of immune dysfunction among breast cancer subtypes. We used spatial transcriptomics and multiplex imaging to provide spatial detail for key markers of benign and malignant cell types and immune cell colocation. These findings demonstrate analysis of paired transcription and chromatin accessibility at the single cell level is a powerful tool for investigating breast cancer lineage development and highlight transcriptional networks that define basal and luminal breast cancer lineages.

Combining the Tyrosine Kinase Inhibitor Cabozantinib and the mTORC1/2 Inhibitor Sapanisertib Blocks ERK Pathway Activity and Suppresses Tumor Growth in Renal Cell Carcinoma.

Current treatment approaches for renal cell carcinoma (RCC) face challenges in achieving durable tumor responses due to tumor heterogeneity and drug resistance. Combination therapies that leverage tumor molecular profiles could offer an avenue for enhancing treatment efficacy and addressing the limitations of current therapies. To identify effective strategies for treating RCC, we selected ten drugs guided by tumor biology to test in six RCC patient-derived xenograft (PDX) models. The multitargeted tyrosine kinase inhibitor (TKI) cabozantinib and mTORC1/2 inhibitor sapanisertib emerged as the most effective drugs, particularly when combined. The combination demonstrated favorable tolerability and inhibited tumor growth or induced tumor regression in all models, including two from patients who experienced treatment failure with FDA-approved TKI and immunotherapy combinations. In cabozantinib-treated samples, imaging analysis revealed a significant reduction in vascular density, and single-nucleus RNA sequencing (snRNA-seq) analysis indicated a decreased proportion of endothelial cells in the tumors. SnRNA-seq data further identified a tumor subpopulation enriched with cell-cycle activity that exhibited heightened sensitivity to the cabozantinib and sapanisertib combination. Conversely, activation of the epithelial-mesenchymal transition pathway, detected at the protein level, was associated with drug resistance in residual tumors following combination treatment. The combination effectively restrained ERK phosphorylation and reduced expression of ERK downstream transcription factors and their target genes implicated in cell-cycle control and apoptosis. This study highlights the potential of the cabozantinib plus sapanisertib combination as a promising treatment approach for patients with RCC, particularly those whose tumors progressed on immune checkpoint inhibitors and other TKIs. SIGNIFICANCE: The molecular-guided therapeutic strategy of combining cabozantinib and sapanisertib restrains ERK activity to effectively suppress growth of renal cell carcinomas, including those unresponsive to immune checkpoint inhibitors.

Problems of China's Legal Supervision System on the Internet Medical Care Under the Background of 5G Medical Application.

With the advent of 5G network technology and the maturity of medical applications associated with 5G, the Internet medical service industry is gradually developing. Given the COVID-19 pandemic crisis occasionally happened in China, hospitals were taken up most of the medical resources, the Internet medical care is seen as the alternative way for patients to access medical care and treatment. With the aid of 5G, patients nowadays can seek remote medical care, diagnosis, and surgery. However, this is not without any problems. The current legal supervision system in the Internet medical service industry is still incomplete, and ought to be augmented. This essay serves to identify and evaluate the loopholes existing in the legal supervision system in the Internet medical service industry, in the hope to improve the current system and ensure the safety of patients who are seeking Internet medical services.

Are we ready for a new paradigm shift? A survey on visual deep MLP.

Recently, the proposed deep multilayer perceptron (MLP) models have stirred up a lot of interest in the vision community. Historically, the availability of larger datasets combined with increased computing capacity led to paradigm shifts. This review provides detailed discussions on whether MLPs can be a new paradigm for computer vision. We compare the intrinsic connections and differences between convolution, self-attention mechanism, and token-mixing MLP in detail. Advantages and limitations of token-mixing MLP are provided, followed by careful analysis of recent MLP-like variants, from module design to network architecture, and their applications. In the graphics processing unit era, the locally and globally weighted summations are the current mainstreams, represented by the convolution and self-attention mechanism, as well as MLPs. We suggest the further development of the paradigm to be considered alongside the next-generation computing devices.

Distinct Co-occurrence Relationships and Assembly Processes of Active Methane-Oxidizing Bacterial Communities Between Paddy and Natural Wetlands of Northeast China.

Studies of methane-oxidizing bacteria are updating our views of their composition and function in paddy and natural wetlands. However, few studies have characterized differences in the methane-oxidizing bacterial communities between paddy and natural wetlands. Here, we conducted a 13C stable isotope-probing experiment and high-throughput sequencing to determine the structure profiling, co-occurrence relationships, and assembly processes of methanotrophic communities in four wetlands of Northeast China. There was a clear difference in community structure between paddy and natural wetlands. LEfSe analyses revealed that Methylobacter, FWs, and Methylosinus were enriched in natural wetlands, while Methylosarcina were prevailing in paddy, all identified as indicative methanotrophs. We observed distinct co-occurrence relationships between paddy and natural wetlands: more robust and complex connections in natural wetlands than paddy wetlands. Furthermore, the relative importance of stochastic processes was greater than that of deterministic processes, as stochastic processes explained >50% of the variation in communities. These results demonstrated that the co-occurrence relationships and assembly processes of active methanotrophic communities in paddy and natural wetlands were distinct. Overall, the results of this study enhance our understanding of the communities of methane-oxidizing bacteria in paddy and natural wetlands of Northeast China.

Pollock: fishing for cell states.

Motivation: The use of single-cell methods is expanding at an ever-increasing rate. While there are established algorithms that address cell classification, they are limited in terms of cross platform compatibility, reliance on the availability of a reference dataset and classification interpretability. Here, we introduce Pollock, a suite of algorithms for cell type identification that is compatible with popular single-cell methods and analysis platforms, provides a set of pretrained human cancer reference models, and reports interpretability scores that identify the genes that drive cell type classifications. Results: Pollock performs comparably to existing classification methods, while offering easily deployable pretrained classification models across a wide variety of tissue and data types. Additionally, it demonstrates utility in immune pan-cancer analysis. Availability and implementation: Source code and documentation are available at https://github.com/ding-lab/pollock. Pretrained models and datasets are available for download at https://zenodo.org/record/5895221. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer.

Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor populations from normal and transitional cells, including acinar-to-ductal metaplasia and pancreatic intraepithelial neoplasia. Pathology-assisted deconvolution of spatial transcriptomic data identified tumor and transitional subpopulations with distinct histological features. We showed coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin in tumor cells. Chemo-resistant samples contain a threefold enrichment of inflammatory cancer-associated fibroblasts that upregulate metallothioneins. Our study reveals a deeper understanding of the intricate substructure of pancreatic ductal adenocarcinoma tumors that could help improve therapy for patients with this disease.

Corrosion behavior of HRB400 and HRB400M steel bars in concrete under DC interference.

The influence of direct current interference on the corrosion behavior of HRB400 and HRB400M steel bars in simulated concrete solution was studied using methods such as weight loss experiment, electrochemical experiment, surface technology and product analysis. The research results showed that with the increase of DC interference voltage, the corrosion rates of HRB400 and HRB400M steel bars would increase. The corrosion resistance of HRB400M steel bars was better than HRB400 steel bars under the experimental conditions. In addition, direct current interference could cause damage to the corrosion product layer on the surface of HRB400 steel bars and HRB400M steel bars. And the corrosion form and corrosion product types of HRB400 and HRB400M steel bars would be affected by direct current interference. The main corrosion products of HRB400 steel bars included γ-FeOOH and Fe2O3 when it was not interfered by DC. When DC interference was applied, the main corrosion products included Fe3O4 and Fe2O3. The corrosion products on the surface of HRB400M steel bars were mainly Fe3O4 and Fe2O3, and the types of products increased to form Cr2O3 and MnFe2O4.

Spatially interacting phosphorylation sites and mutations in cancer.

Advances in mass-spectrometry have generated increasingly large-scale proteomics datasets containing tens of thousands of phosphorylation sites (phosphosites) that require prioritization. We develop a bioinformatics tool called HotPho and systematically discover 3D co-clustering of phosphosites and cancer mutations on protein structures. HotPho identifies 474 such hybrid clusters containing 1255 co-clustering phosphosites, including RET p.S904/Y928, the conserved HRAS/KRAS p.Y96, and IDH1 p.Y139/IDH2 p.Y179 that are adjacent to recurrent mutations on protein structures not found by linear proximity approaches. Hybrid clusters, enriched in histone and kinase domains, frequently include expression-associated mutations experimentally shown as activating and conferring genetic dependency. Approximately 300 co-clustering phosphosites are verified in patient samples of 5 cancer types or previously implicated in cancer, including CTNNB1 p.S29/Y30, EGFR p.S720, MAPK1 p.S142, and PTPN12 p.S275. In summary, systematic 3D clustering analysis highlights nearly 3,000 likely functional mutations and over 1000 cancer phosphosites for downstream investigation and evaluation of potential clinical relevance.

Co-evolution of tumor and immune cells during progression of multiple myeloma.

Multiple myeloma (MM) is characterized by the uncontrolled proliferation of plasma cells. Despite recent treatment advances, it is still incurable as disease progression is not fully understood. To investigate MM and its immune environment, we apply single cell RNA and linked-read whole genome sequencing to profile 29 longitudinal samples at different disease stages from 14 patients. Here, we collect 17,267 plasma cells and 57,719 immune cells, discovering patient-specific plasma cell profiles and immune cell expression changes. Patients with the same genetic alterations tend to have both plasma cells and immune cells clustered together. By integrating bulk genomics and single cell mapping, we track plasma cell subpopulations across disease stages and find three patterns: stability (from precancer to diagnosis), and gain or loss (from diagnosis to relapse). In multiple patients, we detect "B cell-featured" plasma cell subpopulations that cluster closely with B cells, implicating their cell of origin. We validate AP-1 complex differential expression (JUN and FOS) in plasma cell subpopulations using CyTOF-based protein assays, and integrated analysis of single-cell RNA and CyTOF data reveals AP-1 downstream targets (IL6 and IL1B) potentially leading to inflammation regulation. Our work represents a longitudinal investigation for tumor and microenvironment during MM progression and paves the way for expanding treatment options.