Prognostic Implications of the Complement Protein C1Q and Its Correlation with Immune Infiltrates in Osteosarcoma

Advances in prognostic models for osteosarcoma risk

The risk prognosis model is a statistical model that uses a set of features to predict whether an individual will develop a specific disease or clinical outcome. It can be used in clinical practice to stratify disease severity and assess risk or prognosis. With the advancement of large-scale second-generation sequencing technology, along Prognosis models for osteosarcoma are increasingly being developed as large-scale second-generation sequencing technology advances and clinical and biological data becomes more abundant. This expansion greatly increases the number of prognostic models and candidate genes suitable for clinical use. This article will present the predictive effects and reliability of various prognosis models, serving as a reference for their evaluation and application.

Identification of TREM2-positive tumor-associated macrophages in esophageal squamous cell carcinoma: implication for poor prognosis and immunotherapy modulation

Background

It is now understood that the effectiveness of checkpoint immunotherapy can be impaired by immunosuppressive tumor-associated macrophages (TAMs). Nonetheless, the impact of different TAM subpopulations on the antitumor immune response remains unclear, mainly due to their heterogeneity. Herein, we identified a novel TAM subpopulation in esophageal squamous cell carcinoma (ESCC) that might contribute to poor clinical outcomes and immunotherapy modulation.

Methods and results

We analyzed two single-cell RNA sequencing (scRNA-seq) datasets (GSE145370 and GSE160269) of esophageal squamous cell carcinoma to identify a novel TREM2-positive TAM subpopulation characterized by upregulation of TREM2, C1QC, C1QB, C1QA, SPP1, and APOE. Quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) demonstrated that these genes were significantly overexpressed in ESCC. Multiplex immunofluorescence validated the infiltration of TREM2⁺ TAMs in ESCC tissues, which correlated with poorer overall survival (OS). The scRNA-seq analysis in dataset GSE120575 indicated significant enrichment of TREM2⁺ TAMs in melanoma patients (n=48) with poor immunotherapy response, which had an identical gene signature with TREM2⁺ TAMs from ESCC. Analysis of 29 bulk-RNA melanoma samples from dataset GSE78220 revealed that a gene signature of 40 genes associated with TREM2⁺ TAMs was upregulated in the transcriptome of melanomas that did not respond to anti-PD1 therapy. Validation in the TCGA ESCC cohort (n=80) showed that a high enrichment score of the TREM2⁺ TAM was associated with poor prognosis. In addition, 10 ESCC patients treated with anti-PD1 therapy suggested that patients who are not sensitive to immunotherapy have higher density of TREM2+TAMs infiltration.

Conclusion

Overall, TREM2⁺ TAM infiltration in ESCC is associated with poor prognosis and may serve as a biomarker for predicting outcomes and immunotherapy modulation in this patient population. modulation; single-cell RNA sequencing.

Detection of Complement C1q B Chain Overexpression and Its Latent Molecular Mechanisms in Cervical Cancer Tissues Using Multiple Methods

Aim

The aim of this study is to demonstrate the expression and clinicopathological significance of complement C1q B chain (C1QB) in cervical cancer.

Methods

In total, 120 cervical cancer tissues, as well as 20 samples each of high-grade squamous intraepithelial lesions (HSILs), low-grade squamous intraepithelial lesions (LSILs), and benign cervical tissue, were collected to evaluate the expression of C1QB protein via immunohistochemical staining. We conducted an integrated analysis of C1QB mRNA expression in cervical cancer using public microarrays and RNA-seq data sets by calculating standard mean differences (SMDs). Simultaneously, we explored the relations of C1QB with clinicopathological parameters and the expression of P16, Ki-67, and P53.

Results

The expression of C1QB protein was higher in cervical cancer samples than that in benign cervical tissue, LSIL, and HSIL samples (p < 0.05). A combined SMD of 0.65 (95% CI: [0.52, 0.79], p < 0.001) revealed upregulation of C1QB mRNA in cervical cancer. C1QB expression may also be related to the depth of infiltration, lymphovascular invasion, and perineural invasion in cervical cancer (p < 0.05). We also found that C1QB protein expression was positively correlated with P16 and Ki-67 expression in cervical cancer (p < 0.05). The gene set enrichment analysis showed that C1QB may participate in apoptosis and autophagy. A relationship was predicted between C1QB expression and drug sensitivity to cisplatin, paclitaxel, and docetaxel.

Conclusion

We confirmed the overexpression of C1QB in cervical cancer at both mRNA and protein levels for the first time. C1QB may serve as an oncogene in the tumorigenesis of cervical cancer, but this possibility requires further study.

m6A-Related lncRNAs Predict Overall Survival of Patients and Regulate the Tumor Immune Microenvironment in Osteosarcoma

Background

m6A-related lncRNAs have demonstrated great potential tumor diagnostic and therapeutic targets. The goal of this work was to find m6A-regulated lncRNAs in osteosarcoma patients.

Method

The Cancer Genome Atlas (TCGA) database was used to retrieve RNA sequencing and medical information from osteosarcoma sufferers. The Pearson's correlation test was used to identify the m6A-related lncRNAs. A risk model was built using univariate and multivariable Cox regression analysis. Kaplan–Meier survival analysis and receiver functional requirements were used to assess the risk model's performance (ROC). By using the CIBERSORT method, the associations between the relative risks and different immune cell infiltration were investigated. Lastly, the bioactivities of high-risk and low-risk subgroups were investigated using Gene Set Enrichment Analysis (GSEA).

Result

A total of 531 m6A-related lncRNAs were obtained from TCGA. Seven lncRNAs have demonstrated prognostic values. A total of 88 OS patients were separated into cluster 1, cluster 2, and cluster 3. The overall survival rate of OS patients in cluster 3 was more favorable than that of those in cluster 1 and cluster 2. The average Stromal score was much higher in cluster 1 than in cluster 2 and cluster 3 (P < 0.05). The expression levels of lncRNAs used in the construction of the risk prediction model in the high-risk group were generally lower than those in the low-risk group. Analysis of patient survival indicated that the survival of the low-risk group was higher than that of the high-risk group (P < 0.0001) and the area under the curve (AUC) of the ROC curve was 0.719. Using the CIBERSORT algorithm, the results revealed that Macrophages M0, Macrophages M2, and T cells CD4 memory resting accounted for a large proportion of immune cell infiltration. By GSEA analysis, our results implied that the high-risk group was mainly involved in unfolded protein response, DNA repair signaling, and epithelial-mesenchymal transition signaling pathway and glycolysis pathway; meanwhile, the low-risk group was mainly involved in estrogen response early and KRAS signaling pathway.

Conclusion

Our investigation showed that m6A-related lncRNAs remained tightly connected to the immunological microenvironment of osteosarcoma tumors, potentially influencing carcinogenesis and development. The immune microenvironment and immune-related biochemical pathways can be changed by regulating the transcription of M6A modulators or lncRNAs. In addition, we looked for risk-related signaling of m6A-related lncRNAs in osteosarcomas and built and validated the risk prediction system. The findings of our current analysis will facilitate the assessment of outcomes and the development of immunotherapies for sufferers of osteosarcomas.

Immune Microenvironment in Osteosarcoma: Components, Therapeutic Strategies and Clinical Applications

Osteosarcoma is a primary malignant tumor that tends to threaten children and adolescents, and the 5-year event-free survival rate has not improved significantly in the past three decades, bringing grief and economic burden to patients and society. To date, the genetic background and oncogenesis mechanisms of osteosarcoma remain unclear, impeding further research. The tumor immune microenvironment has become a recent research hot spot, providing novel but valuable insight into tumor heterogeneity and multifaceted mechanisms of tumor progression and metastasis. However, the immune microenvironment in osteosarcoma has been vigorously discussed, and the landscape of immune and non-immune component infiltration has been intensively investigated. Here, we summarize the current knowledge of the classification, features, and functions of the main infiltrating cells, complement system, and exosomes in the osteosarcoma immune microenvironment. In each section, we also highlight the complex crosstalk network among them and the corresponding potential therapeutic strategies and clinical applications to deepen our understanding of osteosarcoma and provide a reference for imminent effective therapies with reduced adverse effects.

The role of SPI1-TYROBP-FCER1G network in oncogenesis and prognosis of osteosarcoma, and its association with immune infiltration

Osteosarcoma is an aggressive malignant bone sarcoma worldwide. A causal gene network with specific functions underlying both the development and progression of OS was still unclear. Here we firstly identified the differentially expressed genes (DEGs) between control and OS samples, and then defined the hub genes and top clusters in the protein–protein interaction (PPI) network of these DEGs. By focusing on the hub gene TYROBP in the top 1 cluster, a conserved TYROBP co-expression network was identified. Then the effect of the network on OS overall survival was analyzed. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and Gene Set Enrichment Analysis (GSEA) were used to explore the functions of the network. XCell platform and ssGSEA algorithm were conducted to estimate the status of immune infiltration. ChEA3 platform, GSEA enrichment analysis, and Drug Pair Seeker (DPS) were used to predict the key transcription factor and its upstream signal. We identified the downregulated SPI1-TYROBP-FCER1G network in OS, which were significantly enriched in immune-related functions. We also defined a two-gene signature (SPI1/FCER1G) that can predict poorer OS overall survival and the attenuated immune infiltration when downregulated. The SPI1-TYROBP-FCER1G network were potentially initiated by transcription factor SPI1 and would lead to the upregulated CD86, MHC-II, CCL4/CXCL10/CX3CL1 and hence increased immune infiltrations. With this study, we could better explore the mechanism of OS oncogenesis and metastasis for developing new therapies.

Comprehensive analysis of Transcription Factors identified novel prognostic biomarker in human bladder cancer

Background: Transcriptional factors (TFs) are responsible for regulating the transcription of pro-oncogenes and tumor suppressor genes in the process of tumor development. However, the role of these transcription factors in Bladder cancer (BCa) remains unclear. And the main purpose of this research is to explore the possibility of these TFs serving as biomarkers for BCa.

Methods: We analyzed the differential expression of TFs in BCa from The Cancer Genome Atlas (TCGA) online database, identified 408 up-regulated TFs and 751down-regulated TFs. We obtained some hub genes via WGCNA model and detected the RNAs level in BCa cells and tissues. Then, the relationship between the expression and clinicopathological parameters was further investigated. Kaplan-Meier curves and the log-rank test were carried out to analyze the relationship between NFATC1, AKNA and five-TFs combination and overall survival (OS). And RT-PCR assay was conducted to further consolidate and verify these results.

Results: There were significant differences in the expression of five TFs (CBX7, AKNA, HDAC4, EBF2 and NFATC1) between bladder cancer and normal bladder tissue. In BCa tissue and cell lines, the five TFs were frequently down-regulated, and closely related to poor prognosis. Moreover, the RT-PCR results of five TFs in bladder cancer and normal bladder tissue were consistent with the database results, and reduced TFs could significantly induce or restrain the transcription of many critical factors. The expression level of AKNA and NFATC1 could serve as independent biomarker to predict the overall survival (P<0.05). And the above five TFs combined detection of bladder cancer has higher sensitivity and specificity. Furthermore, differential neutrophils expression between high-risk and low-risk were found, which consolidated the role and function of the five TFs combination model in the progression of BCa.

Conclusions: Our analysis effectively provides a newly TFs-associated prognostic model for bladder cancer. The combination of five identified-TFs is an independent prognostic biomarker, which could serve as a more effective therapeutic target for BCa patients.

Pan-Cancer Analysis of Immune Complement Signature C3/C5/C3AR1/C5AR1 in Association with Tumor Immune Evasion and Therapy Resistance

Despite the advances in our understanding of the genetic and immunological basis of cancer, cancer remains a major public health burden with an ever-increasing incidence rate globally. Nevertheless, increasing evidence suggests that the components of the complement system could regulate the tumor microenvironment (TME) to promote cancer progression, recurrence, and metastasis. In the present study, we used an integrative multi-omics analysis of clinical data to explore the relationships between the expression levels of and genetic and epigenetic alterations in C3, C5, C3AR1, and C5AR1 and tumor immune evasion, therapy response, and patient prognosis in various cancer types. We found that the complements C3, C5, C3AR1, and C5AR1 have deregulated expression in human malignancies and are associated with activation of immune-related oncogenic processes and poor prognosis of cancer patients. Furthermore, we found that the increased expression levels of C3, C5, C3AR1, and C5AR1 were primarily predicted by copy number variation and gene methylation and were associated with dysfunctional T-cell phenotypes. Single nucleotide variation in the gene signature co-occurred with multiple oncogenic mutations and is associated with the progression of onco-immune-related diseases. Further correlation analysis revealed that C3, C5, C3AR1, and C5AR1 were associated with tumor immune evasion via dysfunctional T-cell phenotypes with a lesser contribution of T-cell exclusion. Lastly, we also demonstrated that the expression levels of C3, C5, C3AR1, and C5AR1 were associated with context-dependent chemotherapy, lymphocyte-mediated tumor killing, and immunotherapy outcomes in different cancer types. In conclusion, the complement components C3, C5, C3AR1, and C5AR1 serve as attractive targets for strategizing cancer immunotherapy and response follow-up.

The complex roles of efferocytosis in cancer development, metastasis, and treatment

When tumor cells are killed by targeted therapy, radiotherapy, or chemotherapy, they trigger their primary tumor by releasing pro-inflammatory cytokines. Microenvironmental interactions can also promote tumor heterogeneity and development. In this line, several immune cells within the tumor microenvironment, including macrophages, dendritic cells, regulatory T-cells, and CD8⁺ and CD4⁺ T cells, are involved in the clearance of apoptotic tumor cells through a process called efferocytosis. Although the efficiency of apoptotic tumor cell efferocytosis is positive under physiological conditions, there are controversies regarding its usefulness in treatment-induced apoptotic tumor cells (ATCs). Efferocytosis can show the limitation of cytotoxic treatments, such as chemotherapy and radiotherapy. Since cytotoxic treatments lead to extensive cell mortality, efferocytosis, and macrophage polarization toward an M2 phenotype, the immune response may get involved in tumor recurrence and metastasis. Tumor cells can use the anti-inflammatory effect of apoptotic tumor cell efferocytosis to induce an immunosuppressive condition that is tumor-tolerant. Since M2 polarization and efferocytosis are tumor-promoting processes, the receptors on macrophages act as potential targets for cancer therapy. Moreover, researchers have shown that efferocytosis-related molecules/pathways are potential targets for cancer therapy. These include phosphatidylserine and calreticulin, Tyro3, Axl, and Mer tyrosine kinase (MerTK), receptors of tyrosine kinase, indoleamine-2,3-dioxygenase 1, annexin V, CD47, TGF-β, IL-10, and macrophage phenotype switch are combined with conventional therapy, which can be more effective in cancer treatment. Thus, we set out to investigate the advantages and disadvantages of efferocytosis in treatment-induced apoptotic tumor cells.

Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer

Introduction

Breast cancer is the main reason for cancer-related deaths in women and the most common malignant cancer among women. In recent years, immunosuppressive factors have become a new type of treatment for cancer. However, there are no effective biomarkers for breast cancer immunotherapy. Therefore, exploring immune-related biomarkers is presently an important topic in breast cancer.

Methods

Gene expression profile data of breast cancer from The Cancer Genome Atlas (TCGA) was downloaded. Scale-free gene co-expression networks were built with weighted gene co-expression network analysis. The correlation of genes was performed with Pearson’s correlation values. The potential associations between clinical features and gene sets were studied, and the hub genes were screened out. Gene Ontology and gene set enrichment analysis were used to reveal the function of hub gene in breast cancer. The gene expression profiles of GSE15852, downloaded from the Gene Expression Omnibus database, were used for hub gene verification. In addition, candidate biomarkers expression in breast cancer was studied. Survival analysis was performed using Log rank test and Kaplan–Meier. Immunohistochemistry was used to analyze the expression of CCNA2.

Results

A total of 6 modules related to immune cell infiltration were identified via the average linkage hierarchical clustering. According to the threshold criteria (module membership >0.9 and gene significance >0.35), a significant module consisting of 13 genes associated with immune cells infiltration were identified as candidate hub genes after performed with the human protein interaction network. And 3 genes with high correlation to clinical traits were identified as hub genes, which were negatively associated with the overall survival. Among them, the expression of CCNA2 was increased in metastatic breast cancer compare with non-metastatic breast cancer, who underwent immunotherapy. Immunohistochemistry results showed that CCNA2 expression in carcinoma tissues was elevated compared with normal control.

Discussion

CCNA2 identified as a potential immune therapy marker in breast cancer, which were first reported here and deserved further research.