Mechanism of CD79A and CD79B Support for IgM+ B Cell Fitness through B Cell Receptor Surface Expression

Evaluation of the Immune Response within the Tumor Microenvironment in African American and Non-Hispanic White Patients with Non-Small Cell Lung Cancer

BACKGROUND

African Americans have higher incidence and mortality from lung cancer than non-Hispanic Whites, but investigations into differences in immune response have been minimal. Therefore, we compared components of the tumor microenvironment among African Americans and non-Hispanic Whites diagnosed with non-small cell lung cancer based on PDL1 or tertiary lymphoid structure (TLS) status to identify differences of translational relevance.

METHODS

Using a cohort of 280 patients with non-small cell lung cancer from the Inflammation, Health, Ancestry, and Lung Epidemiology study (non-Hispanic White: n = 155; African American: n = 125), we evaluated PDL1 tumor proportion score (<1% vs. ≥1%) and TLS status (presence/absence), comparing differences within the tumor microenvironment based on immune cell distribution and differential expression of genes.

RESULTS

Tumors from African Americans had a higher proportion of plasma cell signatures within the tumor microenvironment than non-Hispanic Whites. In addition, gene expression patterns in African American PDL1-positive samples suggest that these tumors contained greater numbers of γδ T cells and resting dendritic cells, along with fewer CD8+ T cells after adjusting for age, sex, pack-years, stage, and histology. Investigation of differential expression of B cell/plasma cell-related genes between the two patient populations revealed that two immunoglobulin genes (IGKV2-29 and IGLL5) were associated with decreased mortality risk in African Americans.

CONCLUSIONS

In the first known race-stratified analysis of tumor microenvironment components in lung cancer based on PDL1 expression or TLS status, differences within the immune cell composition and transcriptomic signature were identified that may have therapeutic implications.

IMPACT

Future investigation of racial variation within the tumor microenvironment may help direct the use of immunotherapy.

Disruption of KLHL6 Fuels Oncogenic Antigen Receptor Signaling in B-Cell Lymphoma

Pathomechanisms that activate oncogenic B-cell receptor (BCR) signaling in diffuse large B-cell lymphoma (DLBCL) are largely unknown. Kelch-like family member 6 (KLHL6) encoding a substrate-adapter for Cullin-3-RING E3 ubiquitin ligase with poorly established targets is recurrently mutated in DLBCL. By applying high-throughput protein interactome screens and functional characterization, we discovered that KLHL6 regulates BCR by targeting its signaling subunits CD79A and CD79B. Loss of physiologic KLHL6 expression pattern was frequent among the MCD/C5-like activated B-cell DLBCLs and was associated with higher CD79B levels and dismal outcome. Mutations in the bric-a-brac tramtrack broad domain of KLHL6 disrupted its localization and heterodimerization and increased surface BCR levels and signaling, whereas Kelch domain mutants had the opposite effect. Malfunctions of KLHL6 mutants extended beyond proximal BCR signaling with distinct phenotypes from KLHL6 silencing. Collectively, our findings uncover how recurrent mutations in KLHL6 alter BCR signaling and induce actionable phenotypic characteristics in DLBCL. Significance: Oncogenic BCR signaling sustains DLBCL cells. We discovered that Cullin-3-RING E3 ubiquitin ligase substrate-adapter KLHL6 targets BCR heterodimer (CD79A/CD79B) for ubiquitin-mediated degradation. Recurrent somatic mutations in the KLHL6 gene cause corrupt BCR signaling by disrupting surface BCR homeostasis. Loss of KLHL6 expression and mutant-induced phenotypes associate with targetable disease characteristics in B-cell lymphoma. See related commentary by Leveille et al. See related commentary by Corcoran et al.

Establishment of novel cell lines that maintain the features of B cells derived from patients with neuromyelitis optica spectrum disorder

B cells that produce anti-aquaporin-4 (AQP4) antibodies play a crucial role in neuromyelitis optica spectrum disorder (NMOSD) pathogenesis. We previously reported that naïve B (NB) cells from patients with NMOSD, unlike those from healthy controls, exhibit transcriptional changes suggesting the adoption of an antibody-secreting cell (ASCs) phenotype. CD25+ NB cells, whose numbers are increased in NMOSD patients, have a greater capacity to differentiate into ASCs than do CD25- NB cells. Here, we attempted to establish novel B cell subset cell lines from patients with NMOSD to enable molecular analysis of their abnormalities. We generated Epstein-Barr virus-immortalized lymphoblastoid cell lines (LCLs) from CD25+ NB, CD25- NB, and switched memory B (SMB) cells. All LCLs largely maintained the features of the original cell type in terms of cell surface marker expression and could differentiate into ASCs. Notably, CD25+ NB-LCLs derived from patients with NMOSD exhibited a greater capacity to differentiate into SMB-LCLs than did CD25- NB-LCLs derived from patients with NMOSD, suggesting that the established LCLs maintained the characteristics of cells isolated from patients. The LCLs established in this study are likely to be useful for elucidating the mechanism by which cells that produce anti-AQP4 antibodies develop in NMOSD.

Novel insights: crosstalk with non-puerperal mastitis and immunity

The two primary types of non-puerperal mastitis (NPM) are granulomatous lobular mastitis (GLM) and plasma cell mastitis (PCM). Existing research indicates that immune inflammatory response is considered to be the core of the pathogenesis of GLM and PCM, and both innate and adaptive immune responses play an important role in the pathophysiology of PCM and GLM. However, the regulatory balance between various immune cells in these diseases is still unclear. Consequently, we present a comprehensive summary of the immune-related variables and recent advances in GLM and PCM.

Dynamics and Activation of Membrane-Bound B Cell Receptor Assembly

B-cell receptor complexes (BCR) are expressed on the surface of a B-cell and are the critical regulators of adaptive immune response. Even though the relevance of antibodies has been known for almost a hundred years, the antigen-dependent activation of antibody-producing B-cells has remained elusive. Several models have been proposed for BCR activation, including cross-linking, conformation-induced oligomerization, and dissociation activation models. Recently, the first cryo-EM structure of the human B-cell antigen receptor of the IgM isotype was published. Given the new asymmetric BCR complex, we have carried out extensive molecular dynamics simulations to probe the conformational changes upon antigen binding and the influence of the membrane. We identified two critical dynamical events that could be associated with antigen-dependent activation of BCR. First, antigen binding caused increased flexibility in regions distal to the antigen binding site. Second, this increased flexibility led to the rearrangement of helices in transmembrane helices, including the relative interaction of Igα/Igβ, which has been responsible for intracellular signaling. Further, these transmembrane rearrangements led to changes in localized lipid composition. Even though the simulations considered only a single BCR complex, our work indirectly supports the dissociation activation model.

Genes involved in the cholecystokinin receptor signaling map were differentially expressed in the jejunum of steers with variation in residual feed intake

The jejunum is a critical site for nutrient digestion and absorption, and variation in its ability to take up nutrients within the jejunum is likely to affect feed efficiency. The purpose of this study was to determine differences in gene expression in the jejunum of beef steers divergent for residual feed intake (RFI) in one cohort of steers (Year 1), and to validate those genes in animals from a second study (Year 2). Steers from Year 1 (n = 16) were selected for high and low RFI. Jejunum mucosal tissue was obtained for RNA-seq. Thirty-two genes were differentially expressed (PFDR≤0.15), and five were over-represented in pathways including inflammatory mediator, cholecystokinin receptor (CCKR) signaling, and p38 MAPK pathways. Several differentially expressed genes (ALOX12, ALPI, FABP6, FABP7, FLT1, GSTA2, MEF2B, PDK4, SPP1, and TTF2) have been previously associated with RFI in other studies. Real-time qPCR was used to validate nine differentially expressed genes in the Year 1 steers used for RNA-seq, and in the Year 2 validation cohort. Six genes were validated as differentially expressed (P < 0.1) using RT-qPCR in the Year 1 population. In the Year 2 population, five genes displayed the same direction of expression as the Year 1 population and 3 were differentially expressed (P < 0.1). The CCKR pathway is involved in digestion, appetite control, and regulation of body weight making it a compelling candidate for feed efficiency in cattle, and the validation of these genes in a second population of cattle is suggestive of a role in feed efficiency.

Integration of single-cell sequencing and bulk RNA-seq to identify and develop a prognostic signature related to colorectal cancer stem cells

The prognosis for patients with colorectal cancer (CRC) remains worse than expected due to metastasis, recurrence, and resistance to chemotherapy. Colorectal cancer stem cells (CRCSCs) play a vital role in tumor metastasis, recurrence, and chemotherapy resistance. However, there are currently no prognostic markers based on CRCSCs-related genes available for clinical use. In this study, single-cell transcriptome sequencing was employed to distinguish cancer stem cells (CSCs) in the CRC microenvironment and analyze their properties at the single-cell level. Subsequently, data from TCGA and GEO databases were utilized to develop a prognostic risk model for CRCSCs-related genes and validate its diagnostic performance. Additionally, functional enrichment, immune response, and chemotherapeutic drug sensitivity of the relevant genes in the risk model were investigated. Lastly, the key gene RPS17 in the risk model was identified as a potential prognostic marker and therapeutic target for further comprehensive studies. Our findings provide new insights into the prognostic treatment of CRC and offer novel perspectives for a systematic and comprehensive understanding of CRC development.

Decoding host-microbiome interactions through co-expression network analysis within the non-human primate intestine

The gut microbiome affects the health status of the host through complex interactions with the host's intestinal wall. These host-microbiome interactions may spatially vary along the physical and chemical environment of the intestine, but these changes remain unknown. This study investigated these intricate relationships through a gene co-expression network analysis based on dual transcriptome profiling of different intestinal sites-cecum, transverse colon, and rectum-of the primate common marmoset. We proposed a gene module extraction algorithm based on the graph theory to find tightly interacting gene modules of the host and the microbiome from a vast co-expression network. The 27 gene modules identified by this method, which include both host and microbiome genes, not only produced results consistent with previous studies regarding the host-microbiome relationships, but also provided new insights into microbiome genes acting as potential mediators in host-microbiome interplays. Specifically, we discovered associations between the host gene FBP1, a cancer marker, and polysaccharide degradation-related genes (pfkA and fucI) coded by Bacteroides vulgatus, as well as relationships between host B cell-specific genes (CD19, CD22, CD79B, and PTPN6) and a tryptophan synthesis gene (trpB) coded by Parabacteroides distasonis. Furthermore, our proposed module extraction algorithm surpassed existing approaches by successfully defining more functionally related gene modules, providing insights for understanding the complex relationship between the host and the microbiome.IMPORTANCEWe unveiled the intricate dynamics of the host-microbiome interactions along the colon by identifying closely interacting gene modules from a vast gene co-expression network, constructed based on simultaneous profiling of both host and microbiome transcriptomes. Our proposed gene module extraction algorithm, designed to interpret inter-species interactions, enabled the identification of functionally related gene modules encompassing both host and microbiome genes, which was challenging with conventional modularity maximization algorithms. Through these identified gene modules, we discerned previously unrecognized bacterial genes that potentially mediate in known relationships between host genes and specific bacterial species. Our findings underscore the spatial variations in host-microbiome interactions along the colon, rather than displaying a uniform pattern throughout the colon.

IRF4 Knockdown Inhibits the Chronic Rhinosinusitis Without Nasal Polyps Development by Regulating NLRP3/Caspase-1/GSDMD-Mediated Pyroptosis

Chronic rhinosinusitis without nasal polyps (CRSsNP) is a CRS phenotype. However, the mechanisms of CRSsNP remains unclear. Differentially expressed genes (DEGs) were obtained from the GSE36830 and GSE198950 datasets through the GEO2R tool. The six hub genes were screened by the protein-protein interaction (PPI) network analysis and Cytoscape software. Then we constructed the mouse models of CRS and verified the expression levels of hub genes by reverse transcription quantitative PCR (RT-qPCR). Hematoxylin-eosin (HE) staining was employed to observe pathological alterations in mouse tissues. Casepase-3 expression was detected by immunohistochemistry (IHC). The levels of TNF-α, IL-12, IL-6, IL-1β, LDH, and IL-18 were evaluated using enzyme-linked immunosorbent assay (ELISA). Pyroptosis-related protein expressions were measured by western blotting. Cell counting kit-8 (CCK-8) and flow cytometry were performed to assess the proliferation and apoptosis of lipopolysaccharide (LPS)-induced NP69 cells. Six hub DEGs were identified. The expression levels of IRF4, IKZF1, and CD79A were obviously increased in CRSsNP, while those of ADH6, ADH1A, and LDHC were significantly decreased. IRF4 knockdown attenuated the pathologic features of CRSsNP. IRF4 knockdown reduced levels of the TNF-α, IL-12, IL-6 IL-1β, LDH, and IL-18 as well as the proteins expression of Casepase-1, GSDMD, and NLRP3 both in vivo and in vitro, implying that inflammation and pyroptosis were inhibited. IRF4 knockdown hinders the development of CRSsNP by inhibiting the inflammatory response and NLRP3/Caspase-1/GSDMD-mediated pyroptosis, which offers novel promising treatment strategies for clinical intervention.

Analysis of the effect of CCR7 on the microenvironment of mouse oral squamous cell carcinoma by single-cell RNA sequencing technology

BACKGROUND

Studies have shown that CCR7, an important inflammatory factor, can promote the proliferation and metastasis of oral squamous cell carcinoma (OSCC), but its role in the tumor microenvironment (TME) remains unclear. This paper explores the role of CCR7 in the TME of OSCC.

METHODS

In this work, we constructed CCR7 gene knockout mice and OSCC mouse models. Single-cell RNA sequencing (scRNA-seq) and bioinformatics were used to analyze the differences in the OSCC microenvironment between three CCR7 gene knockout mice (KO) and three wild-type mice (WT). Immunohistochemistry, immunofluorescence staining, and flow cytometry were used to analyze the expression of key genes in significantly different cell types between the KO and WT groups. An in vitro experiment was used to verify the effect of CCR7 on M2 macrophage polarization.

RESULTS

In the mouse OSCC models, the tumor growth rate in the KO group was significantly lower than that in the WT group. Eight main cell types (including tumor cells, fibroblasts, macrophages, granulocytes, T cells, endothelial cells, monocytes, and B cells) were identified by Seurat analysis. The scRNA-seq results showed that the proportion of tumor cells was lower, but the proportion of inflammatory cells was significantly higher in the KO group than in the WT group. CellPhoneDB analysis results indicated a strong interaction relationship between tumor cells and macrophages, T cells, fibroblasts, and endothelial cells. Functional enrichment results indicated that the expression level of the Dusp1 gene in the KO group was generally higher than that in the WT group in various cell types. Macrophage subclustering results indicated that the proportion of M2 macrophages in the KO group was lower than that in the WT group. In vitro experimental results showed that CCR7 can promote M2 macrophage polarization, thus promoting the proliferation, invasion and migration of OSCC cells.

CONCLUSIONS

CCR7 gene knockout can significantly inhibit the growth of mouse oral squamous cell carcinoma by promoting the polarization of M2 macrophages.

Machine learning reveals diverse cell death patterns in lung adenocarcinoma prognosis and therapy

Cancer cell growth, metastasis, and drug resistance pose significant challenges in the management of lung adenocarcinoma (LUAD). However, there is a deficiency in optimal predictive models capable of accurately forecasting patient prognoses and guiding the selection of targeted treatments. Programmed cell death (PCD) pathways play a pivotal role in the development and progression of various cancers, offering potential as prognostic indicators and drug sensitivity markers for LUAD patients. The development and validation of predictive models were conducted by integrating 13 PCD patterns with comprehensive analysis of bulk RNA, single-cell RNA transcriptomics, and pertinent clinicopathological details derived from TCGA-LUAD and six GEO datasets. Utilizing the machine learning algorithms, we identified ten critical differentially expressed genes associated with PCD in LUAD, namely CHEK2, KRT18, RRM2, GAPDH, MMP1, CHRNA5, TMPRSS4, ITGB4, CD79A, and CTLA4. Subsequently, we conducted a programmed cell death index (PCDI) based on these genes across the aforementioned cohorts and integrated this index with relevant clinical features to develop several prognostic nomograms. Furthermore, we observed a significant correlation between the PCDI and immune features in LUAD, including immune cell infiltration and the expression of immune checkpoint molecules. Additionally, we found that patients with a high PCDI score may exhibit resistance to immunotherapy and standard adjuvant chemotherapy regimens; however, they may benefit from other FDA-supported drugs such as docetaxel and dasatinib. In conclusion, the PCDI holds potential as a prognostic signature and can facilitate personalized treatment for LUAD patients.

B cell receptor signaling and associated pathways in the pathogenesis of chronic lymphocytic leukemia

B cell antigen receptor (BCR) signaling is a key driver of growth and survival in both normal and malignant B cells. Several lines of evidence support an important pathogenic role of the BCR in chronic lymphocytic leukemia (CLL). The significant improvement of CLL patients' survival with the use of various BCR pathway targeting inhibitors, supports a crucial involvement of BCR signaling in the pathogenesis of CLL. Although the treatment landscape of CLL has significantly evolved in recent years, no agent has clearly demonstrated efficacy in patients with treatment-refractory CLL in the long run. To identify new drug targets and mechanisms of drug action in neoplastic B cells, a detailed understanding of the molecular mechanisms of leukemic transformation as well as CLL cell survival is required. In the last decades, studies of genetically modified CLL mouse models in line with CLL patient studies provided a variety of exciting data about BCR and BCR-associated kinases in their role in CLL pathogenesis as well as disease progression. BCR surface expression was identified as a particularly important factor regulating CLL cell survival. Also, BCR-associated kinases were shown to provide a crosstalk of the CLL cells with their tumor microenvironment, which highlights the significance of the cells' milieu in the assessment of disease progression and treatment. In this review, we summarize the major findings of recent CLL mouse as well as patient studies in regard to the BCR signalosome and discuss its relevance in the clinics.

B-Cell Receptor Signaling and Beyond: The Role of Igα (CD79a)/Igβ (CD79b) in Normal and Malignant B Cells

B-cell receptor (BCR) is a B cell hallmark surface complex regulating multiple cellular processes in normal as well as malignant B cells. Igα (CD79a)/Igβ (CD79b) are essential components of BCR that are indispensable for its functionality, signal initiation, and signal transduction. CD79a/CD79b-mediated BCR signaling is required for the survival of normal as well as malignant B cells via a wide signaling network. Recent studies identified the great complexity of this signaling network and revealed the emerging role of CD79a/CD79b in signal integration. In this review, we have focused on functional features of CD79a/CD79b, summarized signaling consequences of CD79a/CD79b post-translational modifications, and highlighted specifics of CD79a/CD79b interactions within BCR and related signaling cascades. We have reviewed the complex role of CD79a/CD79b in multiple aspects of normal B cell biology and how is the normal BCR signaling affected by lymphoid neoplasms associated CD79A/CD79B mutations. We have also summarized important unresolved questions and highlighted issues that remain to be explored for better understanding of CD79a/CD79b-mediated signal transduction and the eventual identification of additional therapeutically targetable BCR signaling vulnerabilities.

Identification of cuproptosis and immune-related gene prognostic signature in lung adenocarcinoma

Background

Cuproptosis is a novel form of programmed cell death that differs from other types such as pyroptosis, ferroptosis, and autophagy. It is a promising new target for cancer therapy. Additionally, immune-related genes play a crucial role in cancer progression and patient prognosis. Therefore, our study aimed to create a survival prediction model for lung adenocarcinoma patients based on cuproptosis and immune-related genes. This model can be utilized to enhance personalized treatment for patients.

Methods

RNA sequencing (RNA-seq) data of lung adenocarcinoma (LUAD) patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The levels of immune cell infiltration in the GSE68465 cohort were determined using gene set variation analysis (GSVA), and immune-related genes (IRGs) were identified using weighted gene coexpression network analysis (WGCNA). Additionally, cuproptosis-related genes (CRGs) were identified using unsupervised clustering. Univariate COX regression analysis and least absolute shrinkage selection operator (LASSO) regression analysis were performed to develop a risk prognostic model for cuproptosis and immune-related genes (CIRGs), which was subsequently validated. Various algorithms were utilized to explore the relationship between risk scores and immune infiltration levels, and model genes were analyzed based on single-cell sequencing. Finally, the expression of signature genes was confirmed through quantitative real-time PCR (qRT-PCR), immunohistochemistry (IHC), and Western blotting (WB).

Results

We have identified 5 Oncogenic Driver Genes namely CD79B, PEBP1, PTK2B, STXBP1, and ZNF671, and developed proportional hazards regression models. The results of the study indicate significantly reduced survival rates in both the training and validation sets among the high-risk group. Additionally, the high-risk group displayed lower levels of immune cell infiltration and expression of immune checkpoint compared to the low-risk group.

Immunological modifications following chemotherapy are associated with delayed recurrence of ovarian cancer

Introduction

Ovarian cancer recurs in most High Grade Serous Ovarian Cancer (HGSOC) patients, including initial responders, after standard of care. To improve patient survival, we need to identify and understand the factors contributing to early or late recurrence and therapeutically target these mechanisms. We hypothesized that in HGSOC, the response to chemotherapy is associated with a specific gene expression signature determined by the tumor microenvironment. In this study, we sought to determine the differences in gene expression and the tumor immune microenvironment between patients who show early recurrence (within 6 months) compared to those who show late recurrence following chemotherapy.

Methods

Paired tumor samples were obtained before and after Carboplatin and Taxol chemotherapy from 24 patients with HGSOC. Bioinformatic transcriptomic analysis was performed on the tumor samples to determine the gene expression signature associated with differences in recurrence pattern. Gene Ontology and Pathway analysis was performed using AdvaitaBio's iPathwayGuide software. Tumor immune cell fractions were imputed using CIBERSORTx. Results were compared between late recurrence and early recurrence patients, and between paired pre-chemotherapy and post-chemotherapy samples.

Results

There was no statistically significant difference between early recurrence or late recurrence ovarian tumors pre-chemotherapy. However, chemotherapy induced significant immunological changes in tumors from late recurrence patients but had no impact on tumors from early recurrence patients. The key immunological change induced by chemotherapy in late recurrence patients was the reversal of pro-tumor immune signature.

Discussion

We report for the first time, the association between immunological modifications in response to chemotherapy and the time of recurrence. Our findings provide novel opportunities to ultimately improve ovarian cancer patient survival.

Single-cell transcriptome analysis reveals a cellular immune response in freshwater dark sleeper (Odontobutis potamophila) after infection with Aeromonas veronii

The bacterium Aeromonas veronii is a co-pathogenic species that can negatively impact the health of both humans and aquatic animals. In this study, we used single-cell transcriptome analysis (scRNA-seq) to investigate the effects of infection with A. veronii on head kidney cells and the regulation of gene expression in the dark sleeper (Odontobutis potamophila). scRNA-seq was used to assess the effects of infection with A. veronii in O. potamophila B cells, endothelial cells, macrophages, and granulocytes, and differential enrichment analysis of gene expression in B cells and granulocytes was performed. The analyses revealed a significant increase in neutrophils and decrease in eosinophils in granulocytes infected with A. veronii. Activation of neutrophils enhanced ribosome biogenesis by up-regulating the expression of RPS12 and RPL12 to fight against invading pathogens. Crucial pro-inflammatory mediators IL1B, IGHV1-4, and the major histocompatibility class II genes MHC2A and MHC2DAB, which are involved in virulence processes, were upregulated, suggesting that A. veronii activates an immune response that presents antigens and activates immunoglobulin receptors in B cells. These cellular immune responses triggered by infection with A. veronii enriched the available scRNA-seq data for teleosts, and these results are important for understanding the evolution of cellular immune defense and functional differentiation of head kidney cells.

Adaptive and innate immune responses in multiple sclerosis with anti-CD20 therapy: Gene expression and protein profiles

Background

Anti-CD20 is a highly effective therapy for multiple sclerosis (MS), a disease with multiple abnormalities in function of B and T cells and innate immune cells. Anti-CD20 therapy depletes B cells, which alters antibody production and has diverse effects on B cell immunity. These changes potentially affect immunity beyond B cells in MS.

Objective

Determine if anti-CD20 therapy effects non-B cell, as well as B cell, gene expression, and serum protein levels.

Methods

Samples were collected from 10 healthy controls and from clinically stable relapsing-remitting MS - 10 untreated, 9 interferon-β-treated, and 15 ocrelizumab-treated patients were studied before, and 2  weeks and 6  months after, the first anti-CD20 infusion. Peripheral blood mononuclear cells (PBMC) were analyzed with sensitive, 135,000-transcript RNA expression microarrays, using stringent criteria. Gene expression was compared to 43 MS-relevant serum immune and neurotrophic proteins, using multiplex protein assays.

Results

Anti-CD20 therapy reduced expression of 413 total genes and 185 B-cell-regulated genes at 2  weeks vs. pre-therapy. Expression of 19 (15%) of these B cell genes returned toward baseline by 6  months, including genes for the B cell activation protein, CD79A, and for immunoglobulin A, D, and G heavy chains. Expression pathways for Th17 and CD4 regulatory T-cell (Treg) development, differentiation, and proliferation also quieted. In contrast, expression increased in Th1 and myeloid cell antiviral, pro-inflammatory, and toll-like receptor (TLR) gene pathways.

Conclusion

These findings have clinical implications. B cell gene expression diminishes 2  weeks after anti-CD20 antibody infusion, but begins to rebound by 6  months. This suggests that the optimum time for vaccination is soon before reinfusion of anti-CD20 therapy. In addition, at 6  months, there is enhanced Th1 cell gene expression and induction of innate immune response genes and TLR expression, which can enhance anti-viral and anti-tumor immunity. This may compensate for diminished B cell gene expression after therapy. These data suggest that anti-CD20 therapy has dynamic effect on B cells and causes a compensatory rise in Th1 and myeloid immunity.

Development and validation of an immune-related gene signature for prognosis in Lung adenocarcinoma

The most common type of lung cancer tissue is lung adenocarcinoma. The TCGA-LUAD cohort retrieved from the TCGA dataset was considered the internal training cohort, while GSE68465 and GSE13213 datasets from the GEO database were used as the external test cohort. The TCGA-LUAD cohort was classified into two immune subtypes using single-sample gene set enrichment analysis of the immune gene set and unsupervised clustering analysis. The ESTIMATE algorithm, the CIBERSORT algorithm, and HLA family expression levels again validated the reliability of this typing. We performed Venn analysis using immune-related genes from the immport dataset and differentially expressed genes from the subtypes to retrieve differentially expressed immune genes (DEIGs). In addition, DEIGs were used to construct a prognostic model with the least absolute shrinkage and selection operator regression analysis. A reliable risk model consisting of 11 DEIGs, including S100P, INHA, SEMA7A, INSL4, CD40LG, AGER, SERPIND1, CD1D, CX3CR1, SFTPD, and CD79A, was then built, and its reliability was further confirmed by ROC curve and calibration plot analysis. The high-risk score subgroup had a poor prognosis and a lower tumour immune dysfunction and exclusion score, indicating a greater likelihood of anti-PD-1/cytotoxic T lymphocyte antigen 4 benefit.