CD27 antigen negative expression indicates poor prognosis in newly diagnosed multiple myeloma

Predicting biomarkers in laryngeal squamous cell carcinoma based on the cytokine-cytokine receptor interaction pathway

Objective

To analyze and validate differential genes in the cytokine-cytokine receptor interaction CCRI pathway in laryngeal squamous cell carcinoma (LSCC) using bioinformatics and Mendelian randomization (MR) to find potential biomarkers for LSCC.

Methods

Five sets of LSCC-related gene chips were downloaded from the GEO database, and four sets of combined datasets were randomly selected as the test set and one set as the validation set to screen for differential genes in the CCRI pathway; two-way Mendelian randomization was performed to analyze the causal relationship between cytokine receptor as the exposure factor and LSCC as the outcome variable; and the causal relationship was analyzed by DGIdb, Miranda, miRDB, miRWalk, TargetScan, spongeScan, and TISIDB databases to analyze the relationship between differential genes and drugs, immune cell infiltration, and mRNA-miNA-lncRNA interactions.

Results

A total of 7 differentially expressed genes CD27, CXCL2, CXCL9, INHBA, IL6, CXCL11, and TNFRSF17 were screened for enrichment in the CCRI signaling pathway; MR analysis showed that the CCRI receptor was a risk factor for LSCC (IVW: OR = 1.629, 95 % CI:1.060-2.504, P = 0.026); Seven differential genes were correlated with drugs, immune cells and mRNA-miNA-lncRNA, respectively; the CCRI differential gene expression analysis in the validation set was consistent with the test set results.

Conclusion

This study provided CCRI differential gene expression by bioinformatics, and MR analysis demonstrated that cytokine receptors are risk factors for LSCC, providing new ideas for the pathogenesis and therapeutic targets of LSCC.

Integrative single-cell chromatin and transcriptome analysis of human plasma cell differentiation

ABSTRACT

Plasma cells (PCs) are highly specialized cells representing the end stage of B-cell differentiation. We have shown that PC differentiation can be reproduced in vitro using elaborate culture systems. The molecular changes occurring during PC differentiation are recapitulated in this in vitro differentiation model. However, a major challenge exists to decipher the spatiotemporal epigenetic and transcriptional programs that drive the early stages of PC differentiation. We combined single cell (sc) RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin with high throughput sequencing (scATAC-seq) to decipher the trajectories involved in PC differentiation. ScRNA-seq experiments revealed a strong heterogeneity of the preplasmablastic and plasmablastic stages. Among genes that were commonly identified using scATAC-seq and scRNA-seq, we identified several transcription factors with significant stage specific potential importance in PC differentiation. Interestingly, differentially accessible peaks characterizing the preplasmablastic stage were enriched in motifs of BATF3, FOS and BATF, belonging to activating protein 1 (AP-1) transcription factor family that may represent key transcriptional nodes involved in PC differentiation. Integration of transcriptomic and epigenetic data at the single cell level revealed that a population of preplasmablasts had already undergone epigenetic remodeling related to PC profile together with unfolded protein response activation and are committed to differentiate in PC. These results and the supporting data generated with our in vitro PC differentiation model provide a unique resource for the identification of molecular circuits that are crucial for early and mature PC maturation and biological functions. These data thus provide critical insights into epigenetic- and transcription-mediated reprogramming events that sustain PC differentiation.

Immunophenotypic profile defines cytogenetic stability and unveils distinct prognoses in patients with newly-diagnosed multiple myeloma (NDMM)

Prognostic significance of multiple immune antigens in multiple myeloma has been well established. However, a level of uncertainty remains regarding the intrinsic relationship between immunophenotypes and cytogenetic stability and precise risk stratification. To address these unresolved issues, we conducted a study involving 1389 patients enrolled in the National Longitudinal Cohort of Hematological Diseases in China (NCT04645199). Our results revealed that the correlation between antigen expression and cytogenetics is more prominent than cytopenia or organ dysfunction. Most immune antigens, apart from CD38, CD138, and CD81, exhibit significant associations with the incidence of at least one cytogenetic abnormality. In turn, we identified CD138-low/CD27-neg as specific adverse immunophenotypic profile, which remaining independent impact on progression-free survival (HR, 1.49; P = 0.007) and overall survival (HR, 1.77; P < 0.001) even in the context of cytogenetics. Importantly, CD138-low/CD27-neg profile was also associated with inferior survival after first relapse (P < 0.001). Moreover, the antigen expression profiles were not strictly similar when comparing diagnosis and relapse; in particular, the CD138-low/CD27-neg pattern was notably increased after disease progression (19.1 to 29.1%; P = 0.005). Overall, our study demonstrates that diverse immune profiles are strongly associated with cytogenetic stability, and a specific immunophenotype (CD138-low/CD27-neg) could effectively predict prognoses across different disease stages.

Prognostic marker CD27 and its micro-environmental in multiple myeloma

BACKGROUND

The Cluster of Differentiation 27 (CD27) is aberrantly expressed in multiple myeloma (MM) -derived. This expression facilitates the interaction between tumor and immune cells within TME via the CD27-CD70 pathway, resulting in immune evasion and subsequent tumor progression. The objective of this study is to investigate the correlation between CD27 expression and the prognosis of MM, and to elucidate its potential relationship with the immune microenvironment.

METHODS

In this research, CD27 expression in T cells within the 82 newly diagnosed MM microenvironment was assessed via flow cytometry. We then examined the association between CD27 expression levels and patient survival. Subsequent a series of bioinformatics and in vitro experiments were conducted to reveal the role of CD27 in MM.

RESULTS

Clinical evidence suggests that elevated CD27 expression in T cells within the bone marrow serves as a negative prognostic marker for MM survival. Data analysis from the GEO database has demonstrated a strong association between MM-derived CD27 and the immune response, as well as the hematopoietic system. Importantly, patients with elevated levels of CD27 expression were also found to have an increased presence of MDSCs and macrophages in the bone marrow microenvironment. Furthermore, the PERK-ATF4 signaling pathway has been implicated in mediating the effects of CD27 in MM.

CONCLUSIONS

We revealed that CD27 expression levels serve as an indicative marker for the prognosis of MM patients. The CD27- PERK-ATF4 is a promising target for the treatment of MM.

Multiparametric Flow Cytometry in the Evaluation of Plasma Cell Proliferative Disorders: Current Paradigms for Clinical Practice

Diagnosis of plasma cell proliferative disorders (PCPDs) is primarily based on the demonstration of monoclonal protein (M-Protein) in blood and/ or urine which often precedes clinical manifestations of the disease. The basic pathophysiology behind the M-protein presence is the proliferation of clonal plasma cells (PCs) in bone marrow or extramedullary sites and is assessed using cytomorphology and immunophenotyping. The role of multiparametric flow cytometry (MFC) for PC identification is technically the most valuable tool in this context as it characterizes as well as quantifies the clonal PCs based on differential expression of various immunophenotypic (IPT) markers. From a diagnostic perspective, MFC is critical in the definite identification of the clonal PCs and delineates benign and borderline entities at one end of the spectrum (MGUS, SMM) with lower clonal PC% and, malignant diseases at the other end (MM and PCL) with higher clonal PC fraction. The role of MFC in assessment of measurable residual disease (MRD) and monitoring of progression in MM and various PCPDs has been validated in multiple clinical studies and is probably one of the most promising tools for predicting treatment outcomes. Furthermore, MFC also plays a crucial role in disease prognostication based on specific IPT profiles. An additional role of MFC in the current clinical scenario is the evaluation of tumor microenvironment based on immune cell repertoire, which is reflecting encouraging results across. Thus, in the current review we concisely describe the role of MFC as a reliable and essential modality in PCPDs, from diagnosis to prediction of treatment outcome and disease monitoring.

Understanding the Bioactivity and Prognostic Implication of Commonly Used Surface Antigens in Multiple Myeloma

Multiple myeloma (MM) progression is dependent on its interaction with the bone marrow microenvironment and the immune system and is mediated by key surface antigens. Some antigens promote adhesion to the bone marrow matrix and stromal cells, while others are involved in intercellular interactions that result in differentiation of B-cells to plasma cells (PC). These interactions are also involved in malignant transformation of the normal PC to MM PC as well as disease progression. Here, we review selected surface antigens that are commonly used in the flow cytometry analysis of MM for identification of plasma cells (PC) and the discrimination between normal and malignant PC as well as prognostication. These include the markers: CD38, CD138, CD45, CD19, CD117, CD56, CD81, CD27, and CD28. Furthermore, we will discuss the novel marker CD24 and its involvement in MM. The bioactivity of each antigen is reviewed, as well as its expression on normal vs. malignant PC, prognostic implications, and therapeutic utility. Understanding the role of these specific surface antigens, as well as complex co-expressions of combinations of antigens, may allow for a more personalized prognostic monitoring and treatment of MM patients.

Accurate classification of plasma cell dyscrasias is achieved by combining artificial intelligence and flow cytometry

Monoclonal gammopathy of unknown significance (MGUS), smouldering multiple myeloma (SMM), and multiple myeloma (MM) are very common neoplasms. However, it is often difficult to distinguish between these entities. In the present study, we aimed to classify the most powerful markers that could improve diagnosis by multiparametric flow cytometry (MFC). The present study included 348 patients based on two independent cohorts. We first assessed how representative the data were in the discovery cohort (123 MM, 97 MGUS) and then analysed their respective plasma cell (PC) phenotype in order to obtain a set of correlations with a hypersphere visualisation. Cluster of differentiation (CD)27 and CD38 were differentially expressed in MGUS and MM (P < 0·001). We found by a gradient boosting machine method that the percentage of abnormal PCs and the ratio PC/CD117 positive precursors were the most influential parameters at diagnosis to distinguish MGUS and MM. Finally, we designed a decisional algorithm allowing a predictive classification ≥95% when PC dyscrasias were suspected, without any misclassification between MGUS and SMM. We validated this algorithm in an independent cohort of PC dyscrasias (n = 87 MM, n = 41 MGUS). This artificial intelligence model is freely available online as a diagnostic tool application website for all MFC centers worldwide (https://aihematology.shinyapps.io/PCdyscrasiasToolDg/).

Diagnostic and Predictive Value of Immune-Related Genes in Crohn's Disease

Abnormal immune cell infiltration is associated with the pathogenesis of Crohn’s disease (CD). This study aimed to determine the diagnostic and predictive value of immune-related genes in CD. Seven Gene Expression Omnibus datasets that analyzed the gene expression in CD tissues were downloaded. Single-sample gene set enrichment analysis (ssGSEA) was used to estimate the infiltration of the immune cells in CD tissues. Immune-related genes were screened by overlapping the immune-related genes with differentially expressed genes (DEGs). The protein-protein interaction (PPI) network was used to identify key immune-related DEGs. Diagnostic value of CD and predictive value of anti-TNFα therapy were analyzed. Immunohistochemical (IHC) assay was used to verify gene expression in CD tissues. There were significant differences among CD tissues, paired CD tissues, and normal intestinal tissues regarding the infiltration of immune cells. AQP9, CD27, and HVCN1 were identified as the key genes of the three sub-clusters in the PPI network. AQP9, CD27, and HVCN1 had mild to moderate diagnostic value in CD, and the diagnostic value of AQP9 was better than that of CD27 and HVCN1. AQP9 expression was decreased in CD after patients underwent anti-TNFα therapy, but no obvious changes were observed in non-responders. AQP9 had a moderate predictive value in patients who had undergone treatment. IHC assay confirmed that the expression of AQP9, CD27, and HVCN1 in CD tissues was higher than that in normal intestinal tissues, and AQP9, CD27 was correlated with the activity of CD. Immune-related genes, AQP9, CD27, and HVCN1 may act as auxiliary diagnostic indicators for CD, and AQP9 could serve as a promising predictive indicator in patients who underwent anti-TNF therapy.