CD56dim Natural Killer Cells Research Articles

Integrative Bioinformatics Analysis Unravel the Association between Intracerebral Hemorrhage and Cellular Apoptosis through Immune Infiltration

Background. Intracerebral hemorrhage (ICH, IH) is a stroke syndrome characterized by high mortality and disability rates. However, the apoptotic mechanisms underlying ICH remain incompletely understood. We employed bioinformatics methods to identify key apoptotic genes associated with ICH, thereby offering potential therapeutic targets and contributing to a deeper understanding of the pathogenic mechanisms of apoptosis in ICH. Materials and Methods. We retrieved microarray data of ICH patients from the Gene Expression Omnibus database and intersected it with apoptotic genes, filtering out apoptosis‐related differentially expressed genes (ARDEGs). Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted, and a logic regression‐based diagnostic model for ICH was constructed. Key genes were identified through least absolute shrinkage and selection operator regression after model validation. Subsequently, mRNA‐transcription factor (mRNA‐TF), mRNA–microRNA (mRNA–miRNA), mRNA‐RNA‐binding protein (mRNA‐RBP), and mRNA‐drug regulatory networks were established, followed by immune infiltration analysis. Results. We identified 29 ARDEGs related to ICH, primarily participating in biological processes such as the extrinsic apoptotic signaling pathway and neuroinflammatory response. The ICH model confirmed PPP1R15A, IL1R1, and TYROBP as key genes with diagnostic and therapeutic value. Thirteen immune cell types showed a correlation with ICH; notably, activated dendritic cells and CD56dim natural killer cells exhibited significant correlations, and key genes were positively correlated with all 13 immune cell types. The regulatory networks (mRNA‐TF, mRNA–miRNA, mRNA‐RBP, and mRNA‐drug) provided insights into the apoptotic gene regulation mechanisms and potential drugs in ICH. Conclusion. Through bioinformatics analysis, we identified PPP1R15A, IL1R1, and TYROBP as crucial genes in the occurrence and progression of ICH, with the potential involvement of Activated dendritic cells and CD56dim natural killer cells in these processes.

Effect of intensive training on immune system cells in elite female weightlifters.

This study aimed to investigate the effects of intense weightlifting training on lymphocyte and natural killer cell subgroups, which are the major cells of the immune system, in elite female weightlifters. A total of 20 elite female weightlifters were evaluated using flow cytometry before training (pre-T), immediately after training (post-T), and after a 120-min rest period (rest-T). Post-T and rest-T showed significant decreases in helper T (Th) and cytotoxic T compared with pre-T (p=0.045, p<0.001 and p=0.05, p<0.001, respectively). B and natural killer cells were higher in post-T and rest-T than in pre-T. The increase in B cells was significant in pre-T/rest-T (p<0.001) but not in pre-T/post-T (p=0.122). Intense training significantly increased natural killer cells in both post-T and rest-T (p<0.001). CD56bright and CD56dim natural killer cell subgroups were significantly lower in post-T and rest-T than in pre-T (p=0.005, p=0.006 and p<0.001, p=0.004, respectively). This study shows that intense weightlifting alters peripheral lymphocyte and natural killer subgroup ratios, being the first investigation in this field.

Comprehensive Analysis of N6-Methyladenosine RNA Methylation Regulators in the Diagnosis and Subtype Classification of Rheumatoid Arthritis.

m6A modification is the most abundant mRNA modifications and plays an integral role in various biological processes in eukaryotes. However, the role of m6A regulators in rheumatoid arthritis remains unknown. To determine the expression of m6A RNA methylation regulators in rheumatoid arthritis and their possible functional and prognostic value. In this study, we performed differential analysis in the comprehensive gene expression database GSE93272 dataset between non-rheumatoid arthritis patients and rheumatoid arthritis patients to obtain 15 important m6A regulators. A random forest model and lasso regression were used to screen the five most important m6A regulators to predict the risk of developing rheumatoid arthritis. After further validation using in vitro qPCR experiments, a nomogram model was developed based on the four most important m6A regulators (ELAVL1, WTAP, YTHDF1, and ALKBH5). Immuno-infiltration analysis and consensus clustering analysis were then performed. An analysis of the decision curve showed that the nomogram model could be beneficial to patients. According to selected important m6A regulators, patients with rheumatoid arthritis were classified into two m6A models (ClusterA and ClusterB) via consensus approach. Activated B cells, CD56dim natural killer cells, immature B cells, monocytes, natural killer T cells, and T lymphocytes were associated with ClusterA in immune infiltration analysis. Importantly, immune infiltration in patients with high ELAVL1 expression was strikingly similar to ClusterA. m6A regulators play a non-negligible role in the development of rheumatoid arthritis. A study of m6A patterns may provide future therapeutic options for rheumatoid arthritis.

Efficacy and safety of pegylated interferon alpha-2b for patients with myeloproliferative neoplasm

Objective: To evaluate the efficacy and safety of pegylated interferon alpha-2b (PEG-IFN-α2b) in the treatment of myeloproliferative neoplasm (MPN). Methods: Thirty-four MPN patients receiving PEG-IFN-α2b treatment in the Second Hospital of Tianjin Medical University from August 2019 to October 2022 were prospectively included. Among the patients, 9 were male and 25 were female, and the median age [M (Q1, Q3)] was 57 (19, 78) years. Patients' clinical characteristics were collected and the follow-up was performed. As of January 30, 2023, the follow-up period [M(Q1, Q3)] was 24 (16, 33) months. The efficacy, safety and changes in immune cell and cytokine levels after 12 and 24 months of treatment were analyzed. Results: During the follow-up period, 4 patients dropped out, and the efficacy was evaluable in 30 patients. Following 12 and 24 months of treatment, the complete hematologic response (CHR) rates were 57.1% (16/28) and 75.0% (18/24), respectively. The complete molecular response (CMR)+partial molecular response (PMR) rates were 27.3% (6/22) and 55.0% (11/20), respectively. The bone marrow histopathological overall response rates (ORR) were 34.6% (9/26) and 47.6% (10/21), respectively. At 12 and 24 months of treatment, the proportions of CD8+HLA-DR+T cells, effector T cell subpopulations, CD56bright natural killer (NK) cells, and plasmacytoid dendritic cells (pDC) were higher than the pre-treatment levels, while the proportion of CD56dim NK cells was lower than the pre-treatment level (all P<0.05). The levels of motif chemokine ligand 10 (CXCL10), tumor necrosis factor (TNF)-α and TNF-β in bone marrow all increased from those prior to treatment, while the levels of vascular endothelial growth factor (VEGF) and interleukin (IL-4) decreased from those prior to treatment (all P<0.05). Among hematological adverse reactions, white blood cells decrease [47% (16/34)] was observed with high incidence. Among non-hematological adverse reactions, asthenia [44.1% (15/34)] and transaminases increase [32.3% (11/34)] were observed with high incidences. Conclusions: PEG-IFN-α2b has high hematologic, molecular, and bone marrow histopathological response rates in the treatment of MPN. It can reduce malignant clone loads and regulate the immune microenvironment and is safe and well tolerated overall.

PRDM1 Promotes Primary Human Circulating CD56 dim NK-Cell Differentiation

Background: Natural killer (NK) cells are innate lymphocytes that mount immune responses against viral infection and malignant cells. Circulating NK-cells can be generally divided into two groups, CD56 bright and CD56 dim, with the latter constituting ~90% of NK-cells in peripheral blood. While CD56 bright NK-cells are considered less mature and capable of producing more cytokines, CD56 dim population represents more differentiated cells with greater cytotoxicity. Transcription factor (TF) regulatory circuits were proposed for CD56 bright and CD56 dim NK-cells, indicating that TCF1/LEF1 and BACH2 are important in the former population and that Blimp1 and MAF are master TFs in the latter group. Blimp1 (encoded by PRDM1) has been previously found to regulate terminal differentiation of B-cells and CD8 + T-cells. In NK-cells, deletion of PRDM1 has been shown to promote cell growth and survival in vitro, and its loss of function was commonly detected in NK-cell lymphomas. Here, we employed a multi-omics approach to investigate the role of PRDM1 in the differentiation of human primary NK-cells. Methods: We used CRISPR-Cas9 system to knock out PRDM1 in primary human NK-cells isolated from PBMCs of healthy donors and performed whole transcriptome sequencing. ChIP-seq was employed to investigate the global binding spectrum of PRDM1 in primary human NK-cells cultured with K562-mbIL21-Cl9 feeder cells or with IL-2 alone. We also performed integrative genomics analyses to examine the transcriptomic regulation of NK-cell differentiation by PRDM1. Results: Gene set enrichment analyses (GSEA) demonstrated that PRDM1 KO resulted in enrichment of genes highly expressed in CD56 bright cells and depletion of genes upregulated in CD56 dim NK-cells. Specifically, we found that PRDM1 deficient NK-cells expressed CD56 bright NK-cell master TFs at higher levels, such as TCF7, RUNX2, and MYC. In contrast, TFs that play an important role in more differentiated CD56 dim NK cells were downregulated in PRDM1-KO cells, including IKZF3, MAF, and TBX21. Notably, BCL11B, a TF that has been reported to promote canonical and adaptive NK-cell differentiation, was significantly downregulated along with its target gene ZBTB16 when PRDM1 was deleted. Moreover, genes encoding cytotoxic molecules such as PRF1 and GZMB were also repressed in PRDM1-KO NK-cells. Together, these results indicate that PRDM1-KO NK-cells closely resembled the less mature CD56 bright NK-cells than the CD56 dim terminally differentiated counterpart. ChIP-seq analysis of PRDM1 revealed that many of the differentially expressed genes (DEGs) between PRDM1 KO and WT cells were directly bound by PRDM1. When integrated with publicly available ATAC-seq datasets, we found that some of these PRDM1 bound sites showed differential chromatin accessibility between CD56 bright and CD56 dim NK-cells. To explore the transcriptional program regulated by PRDM1, we utilized a regulated system to re-express PRDM1 in KHYG1, an NK-cell lymphoma cell line that is sensitive to PRDM1 overexpression. RNA-seq analysis showed that the DEGs between KHYG1 with short-term re-expression of PRDM1 and control cells overlapped with DEGs between PRDM1 KO vs WT NK-cells. These genes included BCL11B, MAF, PRF1, and GZMB. Therefore, PRDM1 directly regulates genes that are crucial in NK-cell differentiation. Furthermore, we detected upregulation of memory T-cell or progenitor exhausted T-cell signature genes in PRDM1 KO NK-cells compared with WT, including TCF7, SELL, CCR7, and IL7R. Consistent with this, GSEA analysis demonstrated enrichment of TCF1 + progenitor exhausted T cell or memory T cell upregulated genes in PRDM1 deleted NK-cells, suggesting that PRDM1 KO NK-cells may share some features with memory T-cells or progenitor exhausted T cells. Importantly, MYB, which was found to be essential in progenitor exhausted T cells, was also a direct target of PRDM1 and was upregulated in PRDM1 KO NK-cells. GSEA also showed that PRDM1 depletion in NK-cells led to upregulation of genes highly expressed in mast cell, Th1 cell, B cell, or CD8 + T cell compared to NK cells, which may indicate a role of PRDM1 in maintaining lineage commitment. Conclusions: Our findings collectively show that PRDM1 may be a master TF that regulates human NK-cell differentiation and functions through direct transcriptional regulation of key target genes.

GATA2-TAL1 Axis Is Essential for Human NK Cell Development and Function

Introduction: Natural killer (NK) cells, as the major subset of innate lymphocytes, produce proinflammatory cytokines and mediate anti-tumor cytotoxicity (1-3). Since NK cells are not limited by clonotypic receptors, they can be utilized in cell therapies against a broad spectrum of malignancies. Irrespective of the clinical potentials, the transcriptional regulation of the development and functions of human NK cells is far from fully understood. A dysregulated NK cell development is a hallmark of GATA2 haploinsufficiency (4)(eg. GATA2 T354M mutation). The specific loss of the CD56 bright NK cell population is a significant striking feature in GATA2-deficient patients (4), with or without reduced total CD56 dim NK cells (4, 12, 13). Consequently, the effector functions of these NK cells are significantly reduced, including inflammatory cytokine production and anti-tumor cytotoxicity (4, 12). However, a mechanistic understanding of GATA2 functions is lacking. In humans, GATA2 forms a core heptad complex with six other transcription factors (TF), including TAL1, regulating more than 1000 target genes. However, the unique functions of the GATA2-TAL1 axis in immature and mature NK cell has not been established. Based on these, we hypothesize that GATA2-dependent and independent functions of TAL1 play an essential role in the development and functions of human NK cells. Results: To explore the mechanism of co-transcriptional regulation of GATA2 and TAL1, we transduced NK-92 cells with lentiviral vectors containing GATA2 WT or GATA2 T354M plasmid and quantified TAL1 mRNA levels by qPCR and protein levels by WB. TAL1 is upregulated in GATA2 T354M-expressing NK-92 cells both at mRNA ( Fig. 1A) and protein levels ( Fig. 1B). TAL1 is a TF activating GTPase of immunity-associated protein (GIMAP) family super-enhancer regions in HSC and T cells (11). As TAL1 target genes, we further quantify GIMAP mRNA levels by qPCR. The result indicates that genes from the GIMAP family were notably upregulated in GATA2 T354M-expressing NK-92 cells ( Fig. 1C). Knocking down TAL1 results in the significant downregulation of TAL1 and GIMAPs in GATA2 T354M-expressingcells ( Fig. 1D). To further validate the GATA2-TAL1 axis, sorted NK cells from PBMCs of three GATA2 T354M patients and five age-matched healthy controls (HC) were analyzed with single-cell RNA-seq. We identified the genes from GIMAP family were significantly upregulated in all three GATA2 T354M patients. The representative data from one patient is shown in Fig. 1E. To explore how GATA2 and TAL1 mediate transcriptional regulation, we performed GATA2 CUT&amp;Tag experiments with human NK cells, in which TAL1 motif was predominately enriched in 63.2% of GATA2 targets among NK cells through HOMER motif enrichment analyses ( Fig. 1F). On the other hand, the TAL1 ChIP-seq data from the K562 cells (download from ENCFF101DBG) reveals that the GATA2 motif is enriched in approximately 44% of TAL1 targets ( Fig. 1G). Moreover, both GATA2 and TAL1 expression in NK cells are modified by H3K27Me3 instead of H3K4Me3, suggesting a repressive methylenation signature in their expression ( Fig. 1H). Conclusion: Based on this study, we uncover a novel role for the GATA2-TAL1 axis in human NK cells. we define the transcriptional regulation role of GATA2 and TAL1 complex and provide direct evidence for the mechanism of NK cell deficiency among GATA2 T354M patients. Importantly, through our current study, we will determine the unique role of TAL1 in NK development and function and its transcriptional network.

Dynamic evaluation of blood immune cells predictive of response to immune checkpoint inhibitors in NSCLC by multicolor spectrum flow cytometry.

Immune checkpoint inhibitors (ICIs) only benefit a subset of cancer patients, underlining the need for predictive biomarkers for patient selection. Given the limitations of tumor tissue availability, flow cytometry of peripheral blood mononuclear cells (PBMCs) is considered a noninvasive method for immune monitoring. This study explores the use of spectrum flow cytometry, which allows a more comprehensive analysis of a greater number of markers using fewer immune cells, to identify potential blood immune biomarkers and monitor ICI treatment in non-small-cell lung cancer (NSCLC) patients. PBMCs were collected from 14 non-small-cell lung cancer (NSCLC) patients before and after ICI treatment and 4 healthy human donors. Using spectrum flow cytometry, 24 immune cell markers were simultaneously monitored using only 1 million PBMCs. The results were also compared with those from clinical flow cytometry and bulk RNA sequencing analysis. Our findings showed that the measurement of CD4+ and CD8+ T cells by spectrum flow cytometry matched well with those by clinical flow cytometry (Pearson R ranging from 0.75 to 0.95) and bulk RNA sequencing analysis (R=0.80, P=1.3 x 10-4). A lower frequency of CD4+ central memory cells before treatment was associated with a longer median progression-free survival (PFS) [Not reached (NR) vs. 5 months; hazard ratio (HR)=8.1, 95% confidence interval (CI) 1.5-42, P=0.01]. A higher frequency of CD4-CD8- double-negative (DN) T cells was associated with a longer PFS (NR vs. 4.45 months; HR=11.1, 95% CI 2.2-55.0, P=0.003). ICIs significantly changed the frequency of cytotoxic CD8+PD1+ T cells, DN T cells, CD16+CD56dim and CD16+CD56- natural killer (NK) cells, and CD14+HLDRhigh and CD11c+HLADR + monocytes. Of these immune cell subtypes, an increase in the frequency of CD16+CD56dim NK cells and CD14+HLADRhigh monocytes after treatment compared to before treatment were associated with a longer PFS (NR vs. 5 months, HR=5.4, 95% CI 1.1-25.7, P=0.03; 7.8 vs. 3.8 months, HR=5.7, 95% CI 169 1.0-31.7, P=0.04), respectively. Our preliminary findings suggest that the use of multicolor spectrum flow cytometry helps identify potential blood immune biomarkers for ICI treatment, which warrants further validation.

Development and validation of biomarkers related to PANoptosis in osteoarthritis.

Osteoarthritis (OA) is a high-incidence disease of the orthopedic system. However, studies on the molecular mechanisms of OA and pyroptosis, apoptosis, and necroptosis (PANoptosis) at the transcriptome level remain scarce. Therefore, this study purposed to detect biomarkers in OA and explore their relationship to the immune microenvironment. OA-related expression data was sourced from the Gene Expression Omnibus (GEO) database. Subsequently, differentially expressed analysis and a Venn diagram were performed to obtain differentially expressed PANoptosis-related genes (DEPGs). Furthermore, the least absolute shrinkage and selection operator (LASSO), Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and random forest (RF) were implemented to screen diagnostic genes. Receiver operating characteristic (ROC) curves were performed to verify the diagnostic ability of the diagnostic genes. Next, immune infiltration analysis was performed to find the relationships between differential immune cells (OA vs. normal) and diagnostic genes. Finally, drug prediction analysis was also carried out, and the expression of diagnostic genes was verified in external datasets. A total of 62 DEPGs were identified, which were enriched for regulating apoptotic signaling pathways, tumor necrosis factor (TNF) signaling pathways, and other related pathways. Three feature genes, nuclear factor-kappa-B inhibitor-alpha (NFKBIA), RING finger protein 34 (RNF34), and serine incorporator 3 (SERINC3) were obtained by intersecting genes obtained by the LASSO regression algorithm, SVM algorithm, and RF algorithm and showed excellent diagnostic efficacy with the Area under the curve (AUC) values of individual genes were all greater than 0.7, indicating that the model was more effective. Immuno-infiltration analysis showed that RNF34 was positively correlated with CD56dim natural killer cells, type 17 helper T cells, and NFKBIA was positively correlated with plasmacytoid dendritic cells. Additionally, 12 drugs were predicted by NFKBIA, such as gambogic acid and dioscin. In addition, NFKBIA and SERINC3 were significantly downregulated, and RNF34 was upregulated in OA samples. Three genes (NFKBIA, RNF34, and SERINC3) related to PANoptosis, were obtained by bioinformatics analysis, which would provide a new direction for the diagnosis and treatment of OA.

Impact of interval progression before autologous stem cell transplant in patients with multiple myeloma.

In transplant-eligible patients who undergo upfront autologous stem cell transplant (ASCT) for multiple myeloma (MM), standard practice is to treat with six to eight cycles of induction therapy followed by high-dose chemotherapy with ASCT. A gap between the end of induction and the day of ASCT exists to allow stem cell mobilization and collection. Despite attempts to limit the length of this interval, we noticed that some patients experience interval progression (IP) of disease between the end of induction therapy and the day of ASCT. We analyzed 408 MM patients who underwent ASCT between 2011 and 2016. The median length of the interval between end of induction and ASCT was 38 days. We observed that 26% of patients in the entire cohort and 23.6% of patients who received induction with bortezomib-lenalidomide-dexamethasone (VRD) experienced IP. These patients deepened their responses with ASCT, independently of induction regimen. In the entire cohort, IP was significantly associated with shorter PFS in the univariable analysis (Hazard Ratio, HR = 1.37, P = 0.022) but not in the multivariable analysis (HR = 1.14, P = 0.44). However, analyzing only patients who received VRD as induction, progression-free survival (PFS) remained inferior in both the univariable (HR = 2.02; P = 0.002) and the multivariable analyses (HR = 1.96; P = 0.01). T cells and natural killer (NK) cells are increasingly studied targets of immunomodulatory therapy, as immune dysfunction is known to occur in patients with MM. Peripheral blood from 35 MM patients were analyzed. At time of ASCT, patients with IP had significantly increased percentages of CD3+CD8+CD57+ CD28- (P = 0.05) and CD3+CD4+LAG3+ (P = 0.0022) T-cells, as well as less CD56bright and CD56dim NK cells bearing activated markers such as CD69, NKG2D, and CD226. These data suggest that IP can impact the length of response to ASCT; therefore, further studies on the management of these patients are needed.

NK cell phenotypic profile during active TB in people living with HIV-evolution during TB treatment and implications for bacterial clearance and disease severity

Natural killer (NK) cells, key effector cells of the innate immune system, play an important role in the clearance and control of Mycobacterium tuberculosis and HIV infections. Here, we utilized peripheral blood specimens from the Improving Retreatment Success CAPRISA 011 study to characterize NK cell phenotypes during active TB in individuals with or without HIV co-infection. We further assessed the effects of TB treatment on NK cell phenotype, and characterized the effects of NK cell phenotypes during active TB on mycobacterial clearance and TB disease severity measured by the presence of lung cavitation. TB/HIV co-infection led to the expansion of functionally impaired CD56neg NK cell subset. TB treatment completion resulted in restoration of total NK cells, NK cell subset redistribution and downregulation of several NK cell activating and inhibitory receptors. Higher percentage of peripheral CD56bright cells was associated with longer time to culture conversion, while higher expression of NKp46 on CD56dim NK cells was associated with lower odds of lung cavitation in the overall cohort and the TB/HIV co-infected participants. Together these results provide a detailed description of peripheral NK cells in TB and TB/HIV co-infection and yield insights into their role in TB disease pathology.

Circulating Natural Killer Cells as Prognostic Value for Non-Small-Cell Lung Cancer Patients Treated with Immune Checkpoint Inhibitors: Correlation with Sarcopenia.

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of tumors. Natural killer (NK) cells can play an important role in cancer immune surveillance. The aim of this prospective observational study was to analyze peripheral blood mononuclear cells (PBMCs) in patients with advanced non-small-cell lung cancer (NSCLC) receiving ICIs in order to identify predictive factors for better survival outcomes. Forty-seven stage IV NSCLC patients were enrolled. Patients underwent baseline (T0) and longitudinal (T1) evaluations after ICIs. Peripheral immune blood cell counts were analyzed using flow cytometry. Basal levels of CD3-CD56+ NK cells were higher in patients with controlled disease (DC) compared to progression disease (PD) patients (127 cells/µL vs. 27.8 cells/µL, p < 0.001). Lower NK cell values were independent prognostic factors for shorter overall survival (OS) (HR 0.992; 95% CI 0.987-0.997, p < 0.001) and progression-free survival (PFS) (HR 0.988; 95% CI 0.981-0.994, p < 0.001). During the longitudinal evaluation, CD3-CD56+ NK cells (138.1 cells/µL vs. 127 cells/µL, p = 0.025) and CD56bright NK cells (27.4 cells/µL vs. 18.1 cells/µL, p = 0.034) significantly increased in the DC group. Finally, lower values of CD3-CD56+ NK cells (28.3 cells/µL vs. 114.6 cells/µL, p = 0.004) and CD56dim NK cells (13.2 cells/µL vs. 89.4 cells/µL, p < 0.001) were found in sarcopenic patients compared to patients without sarcopenia. Peripheral NK cells could represent a non-invasive and useful tool to predict ICI therapy response in NSCLC patients, and the association of low NK cell levels with sarcopenia deserves even more attention in clinical evaluation.

A novel investigation into an E2F transcription factor-related prognostic model with seven signatures for colon cancer patients.

The pathogenesis of colon cancer, a common gastrointestinal tumour, involves complicated factors, especially a series of cell cycle-related genes. E2F transcription factors during the cell cycle play an essential role in the occurrence of colon cancer. It is meaningful to establish an efficient prognostic model of colon cancer targeting cellular E2F-associated genes. This has not been reported previously. The authors first aimed to explore the links of E2F genes with the clinical outcomes of colon cancer patients by integrating data from the TCGA-COAD (n=521), GSE17536 (n=177) and GSE39582 (n=585) cohorts. The Cox regression and Lasso modelling approach to identify a novel colon cancer prognostic model involving several hub genes (CDKN2A, GSPT1, PNN, POLD3, PPP1R8, PTTG1 and RFC1) were utilised. Moreover, an E2F-related nomogram that efficiently predicted the survival rates of colon cancer patients was created. Additionally, the authors first identified two E2F tumour clusters, which showed distinct prognostic features. Interestingly, the potential links of E2F-based classification and 'protein secretion' issues of multiorgans and tumour infiltration of 'T-cell regulatory (Tregs)' and 'CD56dim natural killer cell' were detected. The authors' findings are of potential clinical significance for the prognosis assessment and mechanistic exploration of colon cancer.

Immune Cell Infiltration Analysis Based on Bioinformatics Reveals Novel Biomarkers of Coronary Artery Disease.

Coronary artery disease (CAD) is a multifactorial immune disease, but research into the specific immune mechanism is still needed. The present study aimed to identify novel immune-related markers of CAD. Three CAD-related datasets (GSE12288, GSE98583, GSE113079) were downloaded from the Gene Expression Integrated Database. Gene ontology annotation, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis and weighted gene co-expression network analysis were performed on the common significantly differentially expressed genes (DEGs) of these three data sets, and the most relevant module genes for CAD obtained. The immune cell infiltration of module genes was evaluated with the CIBERSORT algorithm, and characteristic genes accompanied by their diagnostic effectiveness were screened by the machine-learning algorithm least absolute shrinkage and selection operator (LASSO) regression analysis. The expression levels of characteristic genes were evaluated in the peripheral blood mononuclear cells of CAD patients and healthy controls for verification. A total of 204 upregulated and 339 downregulated DEGs were identified, which were mainly enriched in the following pathways: "Apoptosis", "Th17 cell differentiation", "Th1 and Th2 cell differentiation", "Glycerolipid metabolism", and "Fat digestion and absorption". Five characteristic genes, LMAN1L, DOK4, CHFR, CEL and CCDC28A, were identified by LASSO analysis, and the results of the immune cell infiltration analysis indicated that the proportion of immune infiltrating cells (activated CD8 T cells and CD56 DIM natural killer cells) in the CAD group was lower than that in the control group. The expressions of CHFR, CEL and CCDC28A in the peripheral blood of the healthy controls and CAD patients were significantly different. We identified CHFR, CEL and CCDC28A as potential biomarkers related to immune infiltration in CAD based on public data sets and clinical samples. This finding will contribute to providing a potential target for early noninvasive diagnosis and immunotherapy of CAD.

Intensive cycles of neoadjuvant camrelizumab combined with chemotherapy in locally advanced esophageal squamous cell carcinoma: a single-arm, phase II trial

BackgroundTwo cycles of neoadjuvant PD-1 blockade plus chemotherapy induced favorable pathological response and tolerant toxicity in patients with locally advanced esophageal squamous cell carcinoma (ESCC). However, approximately 25% of patients relapsed within 1 year after surgery, indicating that a short course of treatment may not be sufficient. Therefore, exploring the effects of intensive treatment is needed for optimal clinical outcomes.MethodsLocally advanced ESCC patients were administered three cycles of camrelizumab plus nab-paclitaxel and capecitabine, followed by thoracoscopic esophagectomy. The primary endpoint was pathologic response. Secondary endpoints included safety, feasibility, radiologic response, survival outcomes, and immunologic/genomic correlates of efficacy.ResultsForty-seven patients were enrolled in the study. Forty-two patients received surgery, and R0 resection was achieved in all cases. The complete and major pathological response rates were 33.3% and 64.3%, respectively, and the objective response rate was 80.0%. Three cycles of treatment significantly improved T down-staging compared to two cycles (P = 0.03). The most common treatment-related adverse events were grades 1–2, and no surgical delay was reported. With a median follow-up of 24.3 months, the 1-year disease-free survival and overall survival rates were both 97.6%, and the 2-year disease-free survival and overall survival rates were 92.3% and 97.6%, respectively. Three patients experienced disease recurrence or metastasis ranging from 12.5 to 25.8 months after surgery, and one patient died 6 months after surgery due to cardiovascular disease. Neither programmed death-ligand 1 expression nor tumor mutational burden was associated with pathological response. An increased infiltration of CD56dim natural killer cells in the pretreatment tumor was correlated with better pathological response in the primary tumor.ConclusionsIt seems probable that intensive cycles of neoadjuvant camrelizumab plus nab-paclitaxel and capecitabine increased tumor regression and improved survival outcomes. Randomized controlled trials with larger sample sizes and longer follow-up periods are needed to validate these findings.Trial registration Chinese Clinical Trial Registry, ChiCTR2000029807, Registered February 14, 2020, https://www.chictr.org.cn/showproj.aspx?proj=49459.

Identification of AKI signatures and classification patterns in ccRCC based on machine learning.

Acute kidney injury can be mitigated if detected early. There are limited biomarkers for predicting acute kidney injury (AKI). In this study, we used public databases with machine learning algorithms to identify novel biomarkers to predict AKI. In addition, the interaction between AKI and clear cell renal cell carcinoma (ccRCC) remain elusive. Four public AKI datasets (GSE126805, GSE139061, GSE30718, and GSE90861) treated as discovery datasets and one (GSE43974) treated as a validation dataset were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between AKI and normal kidney tissues were identified using the R package limma. Four machine learning algorithms were used to identify the novel AKI biomarkers. The correlations between the seven biomarkers and immune cells or their components were calculated using the R package ggcor. Furthermore, two distinct ccRCC subtypes with different prognoses and immune characteristics were identified and verified using seven novel biomarkers. Seven robust AKI signatures were identified using the four machine learning methods. The immune infiltration analysis revealed that the numbers of activated CD4 T cells, CD56dim natural killer cells, eosinophils, mast cells, memory B cells, natural killer T cells, neutrophils, T follicular helper cells, and type 1 T helper cells were significantly higher in the AKI cluster. The nomogram for prediction of AKI risk demonstrated satisfactory discrimination with an Area Under the Curve (AUC) of 0.919 in the training set and 0.945 in the testing set. In addition, the calibration plot demonstrated few errors between the predicted and actual values. In a separate analysis, the immune components and cellular differences between the two ccRCC subtypes based on their AKI signatures were compared. Patients in the CS1 had better overall survival, progression-free survival, drug sensitivity, and survival probability. Our study identified seven distinct AKI-related biomarkers based on four machine learning methods and proposed a nomogram for stratified AKI risk prediction. We also confirmed that AKI signatures were valuable for predicting ccRCC prognosis. The current work not only sheds light on the early prediction of AKI, but also provides new insights into the correlation between AKI and ccRCC.

Machine learning-based prediction of diagnostic markers for Graves’ orbitopathy

PurposeThe pathogenesis of Graves’ orbitopathy/thyroid-associated orbitopathy (TAO) is still unclear, and abnormal DNA methylation in TAO has been reported. Thus, selecting and exploring TAO biomarkers associated with DNA methylation may provide a reference for new therapeutic targets.MethodsThe TAO-associated expression data and methylation data were downloaded from The Gene Expression Omnibus database. Firstly, weighted gene co-expression network analysis was used to obtain the TAO-related genes, which were intersected with differentially methylated genes (DMGs), and differentially expressed genes between TAO samples and normal samples to obtain TAO-associated DMGs (TA-DMGs). Thereafter, the functions of the TA-DMGs were analyzed, and diagnostic markers were screened by least absolute shrinkage and selection operator (Lasso) regression analysis and support vector machine (SVM) analysis. The expression levels and diagnostic values of the diagnostic markers were also analyzed. Furthermore, single gene pathway enrichment analysis was performed for each diagnostic marker separately using gene set enrichment analysis (GSEA) software. Next, we also performed immune infiltration analysis for each sample in the GSE58331 dataset using the single-sample GSEA algorithm, and the correlation between diagnostic markers and differential immune cells was explored. Lastly, the expressions of diagnostic markers were explored by quantitative real-time polymerase chain reaction (qRT-PCR).ResultsA total of 125 TA-DMGs were obtained. The enrichment analysis results indicated that these TA-DMGs were mainly involved in immune-related pathways, such as Th1 and Th2 cell differentiation and the regulation of innate immune response. Moreover, two diagnostic markers, including S100A11 and NKD2, were obtained by Lasso regression analysis and SVM analysis. Single gene pathway enrichment analysis showed that S100A11 was involved in protein polyufmylation, pancreatic-mediated proteolysis, and NKD2 was involved in innate immune response in mucosa, Wnt signaling pathway, etc. Meanwhile, immune cell infiltration analysis screened 12 immune cells, including CD56 dim natural killer cells and Neutrophil cells that significantly differed between TAO and normal samples, with the strongest positive correlation between NKD2 and CD56 dim natural killer cells. Finally, the qRT-PCR illustrated the expressions of NKD2 and S100A11 between normal and TAO.ConclusionNKD2 and S100A11 were screened as biomarkers of TAO and might be regulated by DNA methylation in TAO, providing a new reference for the diagnosis and treatment of TAO patients.

Immunomodulatory role of vitamin D and selenium supplementation in newly diagnosed Graves' disease patients during methimazole treatment.

Methimazole (MMI) represents the conventional therapeutic agent for Graves' disease (GD) hyperthyroidism, but MMI efficacy is limited since it marginally affects the underlying autoimmune process. In a previous study, we randomly assigned 42 newly diagnosed GD patients with insufficient vitamin D (VitD) and selenium (Se) levels to treatment with MMI alone (standard) or combined with selenomethionine and cholecalciferol (intervention) and observed a prompter resolution of hyperthyroidism in the intervention group. In the present study, we aimed to explore changes in peripheral T regulatory (Treg) and circulating natural killer (NK) cell frequency, circulating NK cell subset distribution and function, during treatment. At baseline, circulating total CD3-CD56+NK cells and CD56bright NK cells were significantly higher in GD patients than in healthy controls (HC) (15.7 ± 9.6% vs 9.9 ± 5.6%, p=0.001; 12.2 ± 10.3% vs 7.3 ± 4.1%, p=0.02, respectively); no differences emerged in Treg cell frequency. Frequencies of total NK cells and CD56bright NK cells expressing the activation marker CD69 were significantly higher in GD patients than in HC, while total NK cells and CD56dim NK cells expressing CD161 (inhibitory receptor) were significantly lower. When co-cultured with the K562 target cell, NK cells from GD patients had a significantly lower degranulation ability compared to HC (p<0.001). Following 6 months of treatment, NK cells decreased in both the intervention and MMI-alone groups, but significantly more in the intervention group (total NK: -10.3%, CI 95% -15.8; -4.8% vs -3.6%, CI 95% -9; 1.8%, p=0.09 and CD56bright NK cells: -6.5%, CI 95% -10.1; -3 vs -0.9%, CI 95% -4.4; 2%, p=0.03). Compared to baseline, CD69+ NK cells significantly decreased, while degranulation ability slightly improved, although no differences emerged between the two treatment groups. Compared to baseline, Treg cell frequency increased exclusively in the intervention group (+1.1%, CI 95% 0.4; 1.7%). This pilot study suggested that VitD and Se supplementation, in GD patients receiving MMI treatment, modulates Treg and NK cell frequency, favoring a more pronounced reduction of NK cells and the increase of Treg cells, compared to MMI alone. Even if further studies are needed, it is possible to speculate that this immunomodulatory action might have facilitated the prompter and better control of hyperthyroidism in the supplemented group observed in the previous study.

Identification of epidermal growth factor receptor as an immune-related biomarker in epilepsy using multi-transcriptome data.

Epilepsy is a chronic disease that is characterized by transient brain dysfunction caused by an abrupt abnormal neuronal discharge. Recent studies have indicated that the pathways related to inflammation and innate immunity play significant roles in the pathogenesis of epilepsy, suggesting an interrelationship between immunity and inflammatory processes and epilepsy. However, the immune-related mechanisms are still not precisely understood; therefore, this study aimed to explore the immune-related mechanisms in epilepsy disorders, highlight the role of immune cells at the molecular level in epilepsy, and provide therapeutic targets for patients with epilepsy. Brain tissue samples from healthy and epileptic individuals were collected for transcriptome sequencing to identify differentially expressed genes (DEGs) and differentially expressed (DE)-long coding RNAs (lncRNAs). Based on interactions from the miRcode, starBase2.0, miRDB, miRTarBase, TargetScan, and ENCORI databases, a lncRNA-associated competitive endogenous RNA (ceRNA) network was created. Gene ontology and the Kyoto encyclopedia of genes analyses established that the genes in the ceRNA network were mainly enriched in immune-related pathways. Immune cell infiltration, screening, and protein-protein interaction analyses of the immune-related ceRNAs, and correlation analysis between immune-related core messenger RNA (mRNA) and immune cells were also performed. Nine hub genes (EGFR, GRB2, KRAS, FOS, ESR1, MAPK1, MAPK14, MAPK8, and PPARG) were obtained. Also, 38 lncRNAs, one miRNA (hsa-miR-27a-3p), and one mRNA (EGFR) comprised the final core ceRNA network. Mast cells, plasmacytoid dendritic cells, and immature dendritic cells all showed positive correlations with EGFR, while Cluster of differentiation 56 dim natural killer cells (CD56dim natural killer cells) showed negative correlations. Finally, we employed an epilepsy mouse model to validate EGFR, which is consistent with disease progression. In conclusion, the pathophysiology of epilepsy was correlated with EGFR. Thus, EGFR could be a novel biomarker of juvenile focal epilepsies, and our findings provide promising therapeutic targets for epilepsy.

Exploring the Potential Molecular Mechanism of Sijunzi Decoction in the Treatment of Non-Segmental Vitiligo Based on Network Pharmacology and Molecular Docking.

Non-segmental vitiligo is a common decolorized skin disease. The purpose of this study was to reveal the active components of Sijunzi decoction (SJZD) and the target genes for the treatment of non-segmental vitiligo. Based on TCMSP and GEO databases, effective components and targets of SJZD in the treatment of non-segmental vitiligo were revealed by network pharmacology. GO and KEGG were used to analyze the biological functions of SJZD targets. The Cytoscape-cytoHubba plugin was used to identify hub target genes. SsGSEA method was used to analyze the infiltration level of immune cells in non-segmental vitiligo. Molecular docking was performed to predict the interaction between active compounds and hub target genes. Finally, real-time PCR detection was also performed. It was found that 104 active compounds may be effective ingredients in the treatment of non-segmental vitiligo. These 104 compounds acted on 42 differentially expressed target genes. KEGG analysis showed that target genes were significantly enriched in immune-related pathways such as MAPK and TNF signaling pathways. A total of 6 hub target genes (AKT1, CASP3, PPARG, SIRT1, TNF and TP53) were identified using the Cytoscape-cytoHubba plugin. Molecular docking showed that active compounds quercetin, kaempferol, formononetin and naringenin had good binding to hub target genes. We also found that Type 2 T helper cells, CD56bright natural killer cell and CD56dim natural killer cell infiltration levels were abnormal in non-segmental vitiligo and correlated with AKT1. The results of this study indicate that quercetin, kaempferol, formononetin and naringenin in SJZD may play an important role in the treatment of non-segmental vitiligo by acting on AKT1, CASP3, PPARG, SIRT1, TNF and TP53 to regulate immune cell infiltration and multiple signaling pathways.

Cellular Immune Profiling of Lung and Blood Compartments in Patients with SARS-CoV-2 Infection.

SARS-CoV-2 related immunopathology may be the driving cause underlying severe COVID-19. Through an immunophenotyping analysis on paired bronchoalveolar lavage fluid (BALF) and blood samples collected from mechanically ventilated patients with COVID-19-associated Acute Respiratory Distress Syndrome (CARDS), this study aimed to evaluate the cellular immune responses in survivors and non-survivors of COVID-19. A total of 36 paired clinical samples of bronchoalveolar lavage fluid (BALF) mononuclear cells (BALF-MC) and peripheral blood mononuclear cells (PBMC) were collected from 18 SARS-CoV-2-infected subjects admitted to the intensive care unit (ICU) of the Policlinico Umberto I, Sapienza University Hospital in Rome (Italy) for severe interstitial pneumonia. The frequencies of monocytes (total, classical, intermediate and non-classical) and Natural Killer (NK) cell subsets (total, CD56bright and CD56dim), as well as CD4+ and CD8+ T cell subsets [naïve, central memory (TCM) and effector memory (TEM)], and those expressing CD38 and/or HLADR were evaluated by multiparametric flow cytometry. Survivors with CARDS exhibited higher frequencies of classical monocytes in blood compared to non-survivors (p < 0.05), while no differences in the frequencies of the other monocytes, NK cell and T cell subsets were recorded between these two groups of patients (p > 0.05). The only exception was for peripheral naïve CD4+ T cells levels that were reduced in non-survivors (p = 0.04). An increase in the levels of CD56bright (p = 0.012) and a decrease in CD56dim (p = 0.002) NK cell frequencies was also observed in BALF-MC samples compared to PBMC in deceased COVID-19 patients. Total CD4+ and CD8+ T cell levels in the lung compartment were lower compared to blood (p = 0.002 and p < 0.01, respectively) among non-survivors. Moreover, CD38 and HLA-DR were differentially expressed by CD4+ and CD8+ T cell subsets in BALF-MC and in PBMC among SARS-CoV-2-infected patients who died from COVID-19 (p < 0.05). These results show that the immune cellular profile in blood and pulmonary compartments was similar in survivors and non-survivors of COVID-19. T lymphocyte levels were reduced, but resulted highly immune-activated in the lung compartment of patients who faced a fatal outcome.