CCL8 as a promising prognostic factor in diffuse large B-cell lymphoma via M2 macrophage interactions: A bioinformatic analysis of the tumor microenvironment

Angiogenesis-related gene signature for prognostic prediction and immune microenvironment characterization in diffuse large B-cell lymphoma

Diseases often result from multiple factors, and angiogenesis-related genes (ARGs) have been demonstrated to be associated with cancer. However, their role in diffuse large B-cell lymphoma (DLBCL) has not been fully elucidated. ARGs associated with DLBCL prognosis were identified utilizing Cox regression and LASSO analyses. A prognostic model was constructed based on 7 ARGs, and its biological function was analyzed. Differences in the tumor immune microenvironment based on the prognostic signature were evaluated. Finally, DLBCL cell experiments confirmed the differential expression of genes in DLBCL. The prognostic value of ARGs in DLBCL patients was comprehensively analyzed for the first time, identifying 7 ARGs with prognostic significance. A prognostic risk model was constructed based on these 7 ARGs and validated on an independent external DLBCL dataset. In DLBCL patients, this prognostic feature was an independent risk factor and significantly correlated with clinical characteristics. This feature was also associated with the immune microenvironment of DLBCL. DLBCL cell experiments confirmed significant expression of the 7 ARGs in DLBCL cells. This research provides a fundamental theoretical basis for improving the diagnosis and treatment of DLBCL in clinical practice.

Plasma Cytokine and Chemokine Profiles Predict Efficacy and Toxicity of Anti-CD19 CAR-T Cell Therapy in Large B-Cell Lymphoma

BACKGROUND

Anti-CD19 chimeric antigen receptor T-cell (CAR-T) therapy has emerged as a promising treatment for large B-cell lymphoma (LBCL); however, durable complete responses are achieved in only 30% to 40% of patients. Additionally, CAR-T therapy is frequently associated with significant toxicities, including cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS).

PATIENTS AND METHODS

We explored the translational potential of cytokines and chemokines as predictive biomarkers for CAR-T outcomes by analyzing 47 plasma cytokines/chemokines in serial blood samples from 24 LBCL patients undergoing CAR-T therapy. Blood samples were collected at multiple times: prelymphodepletion, day of CAR-T infusion (Day 0), and post-infusion. We investigated the association between cytokine levels and key clinical outcomes using machine learning models, including treatment response at 3 months, CRS, and ICANS.

RESULTS

Higher day 0 IL-7, day 7 IL-21, and day 0 CCL8 levels correlated with improved remission rates. Conversely, elevated CRS risk was linked to higher day 0 CCL17 and day 3 CCL13, IL-6, and IFN-γ levels. ICANS development was associated with increased day 0 TGF-β1, and day 3 IL-5 and IL-7 levels, while lower day 0 CCL19 and day 3 VIP levels were inversely related to ICANS risk. Additionally, patients who received higher-intensity lymphodepletion had elevated day 0 CCL2 and IL-15 levels.

CONCLUSION

These findings highlight the role of plasma cytokines and chemokines as biomarkers for predicting both the therapeutic efficacy and toxicity of CART, with the potential to guide more personalized, safer, and effective immunotherapies for B cell lymphoma.

Construction of regulatory T cells specific genes predictive models of prostate cancer patients based on machine learning: a computational analysis and in vitro experiments

BACKGROUND

Diseases are often caused by multiple factors, regulatory T cells specific genes (RTSGs) have been shown to be associated with cancer, however, their role in prostate cancer (PRAD) has not been fully explored.

METHODS

RTSGs associated with PRAD prognosis were identified using Cox regression analysis and LASSO analysis. Furthermore, a prognostic model was constructed in PRAD based on the 4 RTSGs, and its biological function were analyzed. We evaluated the differences in tumor immune microenvironment based on prognostic signature. Finally, cell experiments confirmed the function of synaptonemal complex protein-2 (SYCP2) in PRAD cells.

RESULTS

The prognostic value of RTSGs in PRAD patients has been comprehensively analyzed for the first time and identified four RTSGs with prognostic values. A prognosis risk model was constructed based on four RTSGs and its prognostic value was validated on an independent external PRAD dataset. In PRAD patients, this prognostic feature is an independent risk factor and was significantly correlated with clinical feature information of PRAD patients. This feature is also related to the immune microenvironment of PRAD. Cell experiments have confirmed that SYCP2 regulates the apoptosis and cycle progression of PRAD cells significantly. Therefore, SYCP2 may become an important regulatory factor in the progression of PRAD by participating in intracellular functional regulation.

CONCLUSIONS

This research provides a fundamental theoretical basis for improving the diagnosis and treatment of PRAD in clinical practice.

The cross-talk between B cells and macrophages

B cells and macrophages are significant immune cells that maintain the immune balance of the body. B cells are involved in humoral immunity, producing immune effects mainly by secreting antibodies. Macrophages participate in non-specific and specific immune responses. To gain a further understanding of macrophages and B cells, researchers have not only paid attention to the unidirectional influence between B cells and macrophages, but also have focused on the cross-talk between them, and the effect of this cross talk on diseases. Therefore, this review summarizes the influence of macrophages on B cells, the ways and mechanisms by which B cells affect macrophages, and their cross-talk, leading to a more comprehensive understanding of the mechanism of the interaction between macrophages and B cells.

Single-cell analysis identifies distinct macrophage phenotypes associated with prodisease and proresolving functions in the endometriotic niche

Endometriosis negatively impacts the health-related quality of life of 190 million women worldwide. Novel advances in nonhormonal treatments for this debilitating condition are desperately needed. Macrophages play a vital role in the pathophysiology of endometriosis and represent a promising therapeutic target. In the current study, we revealed the full transcriptomic complexity of endometriosis-associated macrophage subpopulations using single-cell analyses in a preclinical mouse model of experimental endometriosis. We have identified two key lesion-resident populations that resemble i) tumor-associated macrophages (characterized by expression of Folr2, Mrc1, Gas6, and Ccl8+) that promoted expression of Col1a1 and Tgfb1 in human endometrial stromal cells and increased angiogenic meshes in human umbilical vein endothelial cells, and ii) scar-associated macrophages (Mmp12, Cd9, Spp1, Trem2+) that exhibited a phenotype associated with fibrosis and matrix remodeling. We also described a population of proresolving large peritoneal macrophages that align with a lipid-associated macrophage phenotype (Apoe, Saa3, Pid1) concomitant with altered lipid metabolism and cholesterol efflux. Gain of function experiments using an Apoe mimetic resulted in decreased lesion size and fibrosis, and modification of peritoneal macrophage populations in the preclinical model. Using cross-species analysis of mouse and human single-cell datasets, we determined the concordance of peritoneal and lesion-resident macrophage subpopulations, identifying key similarities and differences in transcriptomic phenotypes. Ultimately, we envisage that these findings will inform the design and use of specific macrophage-targeted therapies and open broad avenues for the treatment of endometriosis.

Tumor purity-related genes for predicting the prognosis and drug sensitivity of DLBCL patients

Background

Diffuse large B-cell lymphoma (DLBCL) is the predominant type of malignant B-cell lymphoma. Although various treatments have been developed, the limited efficacy calls for more and further exploration of its characteristics.

Methods

Datasets from the Gene Expression Omnibus (GEO) database were used for identifying the tumor purity of DLBCL. Survival analysis was employed for analyzing the prognosis of DLBCL patients. Immunohistochemistry was conducted to detect the important factors that influenced the prognosis. Drug-sensitive prediction was performed to evaluate the value of the model.

Results

VCAN, CD3G, and C1QB were identified as three key genes that impacted the outcome of DLBCL patients both in GEO datasets and samples from our center. Among them, VCAN and CD3G+ T cells were correlated with favorable prognosis, and C1QB was correlated with worse prognosis. The ratio of CD68 + macrophages and CD8 + T cells was associated with better prognosis. In addition, CD3G+T cells ratio was significantly correlated with CD68 + macrophages, CD4 + T cells, and CD8 +T cells ratio, indicating it could play an important role in the anti-tumor immunity in DLBCL. The riskScore model constructed based on the RNASeq data of VCAN, C1QB, and CD3G work well in predicting the prognosis and drug sensitivity.

Conclusions

VCAN, CD3G, and C1QB were three key genes that influenced the tumor purity of DLBCL, and could also exert certain impact on drug sensitivity and prognosis of DLBCL patients.

Funding

This work is supported by the Shenzhen High-level Hospital Construction Fund and CAMS Innovation Fund for Medical Sciences (CIFMS) (2022-I2M-C&T-B-062).

Pathologic features of brain hemorrhage after radiation treatment: case series with somatic mutation analysis

BACKGROUND

Radiation treatment for diseases of the brain can result in hemorrhagic adverse radiation effects. The underlying pathologic substrate of brain bleeding after irradiation has not been elucidated, nor potential associations with induced somatic mutations.

METHODS

We retrospectively reviewed our department's pathology database over 5 years and identified 5 biopsy specimens (4 patients) for hemorrhagic lesions after brain irradiation. Tissues with active malignancy were excluded. Samples were characterized using H&E, Perl's Prussian Blue, and Masson's Trichrome; immunostaining for B-cells (anti-CD20), T-cells (anti-CD3), endothelium (anti-CD31), macrophages (anti-CD163), α-smooth muscle actin, and TUNEL. DNA analysis was done by two panels of next-generation sequencing for somatic mutations associated with known cerebrovascular anomalies.

RESULTS

One lesion involved hemorrhagic expansion among multifocal microbleeds that had developed after craniospinal irradiation for distant medulloblastoma treatment. Three bleeds arose in the bed of focally irradiated arteriovenous malformations (AVM) after confirmed obliteration. A fifth specimen involved the radiation field distinct from an irradiated AVM bed. From these, 2 patterns of hemorrhagic vascular pathology were identified: encapsulated hematomas and cavernous-like malformations. All lesions included telangiectasias with dysmorphic endothelium, consistent with primordial cavernous malformations with an associated inflammatory response. DNA analysis demonstrated genetic variants in PIK3CA and/or PTEN genes but excluded mutations in CCM genes.

CONCLUSIONS

Despite pathologic heterogeneity, brain bleeding after irradiation is uniformly associated with primordial cavernous-like telangiectasias and disruption of genes implicated in dysangiogenesis but not genes implicated as causative of cerebral cavernous malformations. This may implicate a novel signaling axis as an area for future study.

Dissecting causal links between gut microbiota, inflammatory cytokines, and DLBCL: a Mendelian randomization study

ABSTRACT

Causal relationships between gut microbiota, inflammatory cytokines, and diffuse large B-cell lymphoma (DLBCL) remain elusive. In addressing this gap, our Mendelian randomization (MR) study used data from the MiBioGen consortium encompassing 211 microbiota taxa (n = 18 340), genome-wide association study meta-analyses of 47 inflammatory cytokines, and DLBCL cases and controls from the FinnGen consortium (cases, n = 1010; controls, n = 287 137). Through bidirectional MR analyses, we examined the causal links between gut microbiota and DLBCL and used mediation analyses, including 2-step MR and multivariable MR (MVMR), to identify potential mediating inflammatory cytokines. Our findings revealed that 4 microbiota taxa were causally associated with DLBCL, and conversely, DLBCL influenced the abundance of 20 taxa. Specifically, in the 2-step MR analysis, both the genus Ruminococcaceae UCG-002 (odds ratio [OR], 1.427; 95% confidence interval [CI], 1.011-2.015; P = .043) and the inflammatory cytokine monokine induced by gamma (MIG) (OR, 1.244; 95% CI, 1.034-1.487; P = .020) were found to be causally associated with an increased risk of DLBCL. Additionally, a positive association was observed between genus Ruminococcaceae UCG-002 and MIG (OR, 1.275; 95% CI, 1.069-1.520; P = .007). Furthermore, MVMR analysis indicated that the association between genus Ruminococcaceae UCG-002 and DLBCL was mediated by MIG, contributing to 14.9% of the effect (P = .005). In conclusion, our MR study provides evidence that supports the causal relationship between genus Ruminococcaceae UCG-002 and DLBCL, with a potential mediating role played by the inflammatory cytokine MIG.

A two-sample Mendelian randomization analysis: causal association between chemokines and pan-carcinoma

Objective: According to the 2020 data from the World Health Organization (WHO), cancers stand as one of the foremost contributors to global mortality. Revealing novel cancer risk factors and protective factors is of paramount importance in the prevention of disease occurrence. Studies on the relationship between chemokines and cancer are ongoing; however, due to the coordination of multiple potential mechanisms, the specific causal association remains unclear. Methods: We performed a bidirectional Mendelian randomization analysis to explore the causal association between serum chemokines and pan-carcinoma. All data is from the GWAS catalog and IEU Open GWAS database. The inverse-variance weighted (IVW) method is primarily employed for assessing the statistical significance of the findings. In addition, the significance threshold after the multiple hypothesis test (Bonferroni) was 0.0013, and the evidence of a potential association was considered if the p-value < 0.05, but remained greater than Bonferroni's threshold. Results: The results indicate that CCL1 (odds ratio, OR = 1.18), CCL2 (OR = 1.04), CCL8 (OR = 1.36), CCL14 (Colorectal, OR = 1.08, Small intestine, OR = 0.77, Lung, OR = 1.11), CCL15 (OR = 0.85), CCL18 (Breast, OR = 0.95, Prostate, OR = 0.96), CCL19 (Lung, OR = 0.66, Prostate, OR = 0.92), CCL20 (Lung, OR = 0.53, Thyroid, OR = 0.76), CCL21 (OR = 0.62), CCL22 (OR = 2.05), CCL23 (OR = 1.31), CCL24 (OR = 1.06), CCL27 (OR = 1.49), CCL28 (OR = 0.74), CXCL5 (OR = 0.95), CXCL9 (OR = 3.60), CXCL12 (Breast, OR = 0.87, Small intestine, OR = 0.58), CXCL13 (Breast, OR = 0.93, Lung, OR = 1.29), CXCL14 (Colon, OR = 1.40) and CXCL17 (OR = 1.07) are potential risk factors for cancers. In addition, there was a reverse causal association between CCL1 (OR = 0.94) and CCL18 (OR = 0.94) and breast cancer. Sensitivity analysis results were similar. The results of the other four MR Methods were consistent with the main results, and the leave-one-out method showed that the results were not driven by a Single nucleotide polymorphism (SNP). Moreover, there was no heterogeneity and pleiotropy in our analysis. Conclusion: Based on the two-sample MR Analysis method, we found that chemokines might be upstream factors of cancer pathogenesis. These results might provide new insights into the future use of chemokines as potential targets for cancer prevention and treatment. Our results also provide important clues for tumor prevention, and changes of serum chemokine concentration may be recognized as one of the features of precancerous lesions in future clinical trials.

Unraveling the enigma of tumor-associated macrophages: challenges, innovations, and the path to therapeutic breakthroughs

Tumor-associated macrophages (TAMs) are integral to the tumor microenvironment (TME), influencing cancer progression significantly. Attracted by cancer cell signals, TAMs exhibit unparalleled adaptability, aligning with the dynamic tumor milieu. Their roles span from promoting tumor growth and angiogenesis to modulating metastasis. While substantial research has explored the fundamentals of TAMs, comprehending their adaptive behavior, and leveraging it for novel treatments remains challenging. This review delves into TAM polarization, metabolic shifts, and the complex orchestration of cytokines and chemokines determining their functions. We highlight the complexities of TAM-targeted research focusing on their adaptability and potential variability in therapeutic outcomes. Moreover, we discuss the synergy of integrating TAM-focused strategies with established cancer treatments, such as chemotherapy, and immunotherapy. Emphasis is laid on pioneering methods like TAM reprogramming for cancer immunotherapy and the adoption of single-cell technologies for precision intervention. This synthesis seeks to shed light on TAMs' multifaceted roles in cancer, pinpointing prospective pathways for transformative research and enhancing therapeutic modalities in oncology.

RAI2 acts as a tumor suppressor with functional significance in gastric cancer

Metastasis of gastric cancer (GC) is one of the major causes of death among GC patients. GC metastasis involves numerous biological processes, yet the specific molecular biological mechanisms have not been elucidated. Here, we report a novel tumor suppressor, retinoic acid-induced 2 (RAI2), which is located in the Xp22 region of the chromosome and plays a role in inhibiting GC growth and invasion. In this study, integrated analysis of The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) datasets and immunohistochemistry staining data suggested that RAI2 expression in GC samples was low. Moreover, the immune infiltration analysis indicated that low expression of RAI2 in GC was associated with a higher intensity of tumor-infiltrating lymphocytes (TILs) and an abundance of Programmed death ligand 1 (PD-L1) expression. Gene set enrichment analysis (GSEA) analysis further revealed that RAI2 regulated some pathways including the GAP junction, focal adhesion and ECM receptor interaction pathway, immune regulation, PI3K-Akt signaling, MAPK signaling, cell cycle, and DNA replication. Furthermore, the knockdown of RAI2 promoted GC cell proliferation, migration, and invasion in vitro. Taken together, these results suggest that the tumor suppressor RAI2 could be a potential target for the development of anti-cancer strategies in GC.

Cytokine profiles in patients with newly diagnosed diffuse large B-cell lymphoma: IL-6 and IL-10 levels are associated with adverse clinical features and poor outcomes

BACKGROUND

The development of diffuse large B-cell lymphoma (DLBCL), a prevalent subgroup of non-Hodgkin lymphoma (NHL), potentially involves various cytokines. We aimed to determine the correlation between deregulated serum levels of cytokines and clinical features and investigate their impact on the prognosis of patients with DLBCL.

METHODS

We conducted a retrospective study of 77 patients with newly diagnosed DLBCL to explore the relationships between different cytokines, adverse clinical features, and poor outcomes. The Mann-Whitney U test was used to compare the cytokine profiles between patients with DLBCL and healthy controls. The Kaplan-Meier method was used to analyze the probability of survival, and the log-rank tests were used to evaluate the differences between survival curves. The Cox proportional hazards regression model was used to performed univariate and multivariate analyses to evaluate prognostic variables for survival analyze.

RESULTS

Serum levels of interleukin-2 (IL-2), tumor necrosis factor (TNF)-α, IL-6, IL-10, and IFN-γ were significantly elevated in patients with untreated DLBCL. Serum levels of IL-6 and IL-10 were significantly higher in patients with an International Prognostic Index (IPI) of 3-5, bone marrow involvement, serum levels of LDH ≥ 250 U/L, and β2-microglobulin (β2-MG) levels ≥ 2.3 mg/L. Patients with B symptoms only had higher serum IL-10 levels, whereas patients with a partial response or no response to treatment had significantly elevated serum levels of IL-6 as well as IL-10. Significant positive correlations were observed between the levels of IL-6 and IL-10 with those of β2-MG and LDH. Patients with levels of IL-6 ≥ 4.5 or IL-10 ≥ 5.0 pg/mL, as well as combined elevated IL-6 and IL-10 levels, exhibited shorter progression-free survival and overall survival. Additionally, univariate and multivariate analyses revealed that serum levels of IL-6 ≥ 4.5 pg/mL and IL-10 ≥ 5.0 pg/mL and IPI 3-5 were independent prognostic factors for relapse and survival in patients with DLBCL.

CONCLUSIONS

Pre-treatment serum IL-6 and IL-10 levels in patients with newly diagnosed DLBCL might be powerful markers for determining treatment response and predicting the prognosis of DLBCL.

Integrative bioinformatics approaches to establish potential prognostic immune-related genes signature and drugs in the non-small cell lung cancer microenvironment

Introduction: Research has revealed that the tumor microenvironment (TME) is associated with the progression of malignancy. The combination of meaningful prognostic biomarkers related to the TME is expected to be a reliable direction for improving the diagnosis and treatment of non-small cell lung cancer (NSCLC).

Method and Result: Therefore, to better understand the connection between the TME and survival outcomes of NSCLC, we used the “DESeq2” R package to mine the differentially expressed genes (DEGs) of two groups of NSCLC samples according to the optimal cutoff value of the immune score through the ESTIMATE algorithm. A total of 978 up-DEGs and 828 down-DEGs were eventually identified. A fifteen-gene prognostic signature was established via LASSO and Cox regression analysis and further divided the patients into two risk sets. The survival outcome of high-risk patients was significantly worse than that of low-risk patients in both the TCGA and two external validation sets (p-value &lt; 0.05). The gene signature showed high predictive accuracy in TCGA (1-year area under the time-dependent ROC curve (AUC) = 0.722, 2-year AUC = 0.708, 3-year AUC = 0.686). The nomogram comprised of the risk score and related clinicopathological information was constructed, and calibration plots and ROC curves were applied, KEGG and GSEA analyses showed that the epithelial-mesenchymal transition (EMT) pathway, E2F target pathway and immune-associated pathway were mainly involved in the high-risk group. Further somatic mutation and immune analyses were conducted to compare the differences between the two groups. Drug sensitivity provides a potential treatment basis for clinical treatment. Finally, EREG and ADH1C were selected as the key prognostic genes of the two overlapping results from PPI and multiple Cox analyses. They were verified by comparing the mRNA expression in cell lines and protein expression in the HPA database, and clinical validation further confirmed the effectiveness of key genes.

Conclusion: In conclusion, we obtained an immune-related fifteen-gene prognostic signature and potential mechanism and sensitive drugs underling the prognosis model, which may provide accurate prognosis prediction and available strategies for NSCLC.