Prognostic Implications of the Complement Protein C1q in Gliomas

Identification of crucial genes through WGCNA in the progression of gastric cancer

Background: To explore the hub gene closely related to the progression of gastric cancer (GC), so as to provide a theoretical basis for revealing the therapeutic mechanism of GC. Methods: The gene expression profile and clinical data of GSE15459 in Gene Expression Omnibus (GEO) database were downloaded. The weighted gene co-expression network analysis (WGCNA) was used to screen the key modules related to GC progression. Survival analysis was used to assess the influence of hub genes on patients' outcomes. CIBERSORT analysis was used to predict the tissue infiltrating immune cells in patients. Immunohistochemical staining was conducted to further verify the expression of hub genes. Results: Through WGCNA, a total of 26 co-expression modules were constructed, in which salmon module and royalblue module had strong correlation with GC progression. The results of enrichment analysis showed that genes in the two modules were mainly involved in toll-like receptor signaling pathway, cholesterol metabolism and neuroactive ligand-receptor interaction. Six hub genes (C1QA, C1QB, C1QC, FCER1G, FPR3 and TYROBP) related to GC progression were screened. Survival analysis showed overall survival in the high expression group was significantly lower than that in the low expression group. CIBERSORT analysis revealed that immune characteristics difference between patients in early stage and advanced stage. Immunohistochemical results confirmed that C1QB, FCER1G, FPR3 and TYROBP were significantly associated with disease progression in GC. Conclusion: Our study identified that C1QB, FCER1G, FPR3 and TYROBP played important roles in the progression of GC, and their specific mechanisms are worth further study.

Macrophage diversity in human cancers: New insight provided by single-cell resolution and spatial context

M1/M2 paradigm of macrophage plasticity has existed for decades. Now it becomes clear that this dichotomy doesn't adequately reflect the diversity of macrophage phenotypes in tumor microenvironment (TME). Tumor-associated macrophages (TAMs) are a major population of innate immune cells in the TME that promotes tumor cell proliferation, angiogenesis and lymphangiogenesis, invasion and metastatic niche formation, as well as response to anti-tumor therapy. However, the fundamental restriction in therapeutic TAM targeting is the limited knowledge about the specific TAM states in distinct human cancer types. Here we summarized the results of the most recent studies that use advanced technologies (e.g. single-cell RNA sequencing and spatial transcriptomics) allowing to decipher novel functional subsets of TAMs in numerous human cancers. The transcriptomic profiles of these TAM subsets and their clinical significance were described. We emphasized the characteristics of specific TAM subpopulations - TREM2+, SPP1+, MARCO+, FOLR2+, SIGLEC1+, APOC1+, C1QC+, and others, which have been most extensively characterized in several cancers, and are associated with cancer prognosis. Spatial transcriptomics technologies defined specific spatial interactions between TAMs and other cell types, especially fibroblasts, in tumors. Spatial transcriptomics methods were also applied to identify markers of immunotherapy response, which are expressed by macrophages or in the macrophage-abundant regions. We highlighted the perspectives for novel techniques that utilize spatial and single cell resolution in investigating new ligand-receptor interactions for effective immunotherapy based on TAM-targeting.

Complement and coagulation cascades are associated with prognosis and the immune microenvironment of lower-grade glioma

Background

Abnormal coagulation is a common feature of glioma. There is a strong correlation between coagulation and the complement system, named complement and coagulation cascades (CCC). However, the role of CCC genes in lower-grade glioma (LGG) remains unclear. This study aimed to investigate the role of CCC genes in LGG.

Methods

In total, 5,628 differential expressed genes were identified between 498 LGG tissues from The Cancer Genome Atlas (TCGA) and 207 normal brain tissues from Genotype-Tissue Expression Project (GTEx). Among them, 20 overlapped CCC genes were identified as differentially expressed CCC genes. Then, comprehensive bioinformatics analysis was used to investigate the role of CCC genes in LGG; 271 LGG tissues from the Chinese Glioma Genome Atlas (CGGA) were used as the validation dataset. Cell Counting Kit-8 (CCK8) proliferation assay, colony formation assay, and wound healing assay were conducted to explore the anti-glioma effect of the sensitive drugs we predicted.

Results

We constructed a risk signature consisting of six CCC genes, including F2R, SERPINA1, TFPI, C1QC, C2, and C3AR1. The CCC gene-based risk signature could accurately predict the prognosis of patients with LGG. In addition, we found that the JAK-STAT, NOD-like receptor, Notch, PI3K-Akt, and Rap1 signaling pathways might be activated and had crosstalk with CCC in the high-risk group. Our findings analyses demonstrated that samples in high- and low-risk groups had different immune landscapes. Moreover, patients in the high-risk group might have greater resistance to immunotherapy. We validated the accuracy of the risk signature in predicting immunotherapy response in two public immunotherapy cohorts, GSE135222 and GSE78220. By means of oncoPredict, MG-132, BMS-536924, PLX-4720, and AZD6482 were identified as potential sensitive drugs for high-risk patients, of which MG-132 was particularly recommended for high-risk patients. We performed in vitro experiments to explore the anti-glioma effect of MG-132, and the results demonstrated MG-132 could inhibit the proliferation and migration of glioma cells.

Conclusions

Our findings show that CCC genes are associated with the prognosis and immune infiltration of LGG and provide possible immunotherapeutic and novel chemotherapeutic strategies for patients with LGG based on the risk signature.

Single-Cell Transcriptome Reveals Cell Type-Specific Molecular Pathology in a 2VO Cerebral Ischemic Mouse Model

Post-ischemia memory impairment is a major sequela in cerebral ischemia patients. However, cell type-specific molecular pathology in the hippocampus after ischemia is poorly understood. In this study, we adopted a mouse two-vessel occlusion ischemia model (2VO model) to mimic cerebral ischemia-induced memory impairment and investigated the single-cell transcriptome in the hippocampi in 2VO mice. A total of 27,069 cells were corresponding 14 cell types with neuronal, glial, and vascular lineages. We next analyzed cell-specific gene alterations in 2VO mice and the function of these cell-specific genes. Differential expression analysis identified cell type-specific genes with altered expression in neurons, astrocytes, microglia, and oligodendrocytes in 2VO mice. Notably, four subtypes of oligodendrocyte precursor cells with distinct differentiation pathways were suggested. Taken together, this is the first single-cell transcriptome analysis of gene expression in a 2VO model. Furthermore, we suggested new types of oligodendrocyte precursor cells with angiogenesis and neuroprotective potential, which might offer opportunities to identify new avenues of research and novel targets for ischemia treatment.

Comprehensive Analysis Reveals Prognostic and Therapeutic Immunity-Related Biomarkers for Pediatric Metastatic Osteosarcoma

Background and Objectives: Osteosarcoma, the most prevalent malignant bone tumor in children and adolescents, presents a complex pathogenesis characterized by various genetic and epigenetic alterations. This study aims to identify key differentially expressed genes (DEGs) in pediatric osteosarcoma, with a focus on those influencing metastasis and patient survival. Materials and Methods: We utilized the GSE33382 dataset from the GEO database for a comprehensive bioinformatic analysis. This included a protein-protein interaction (PPI) network analysis, Cox regression, and Kaplan-Meier survival analysis to identify central DEGs associated with osteosarcoma metastasis and patient survival. Results: Our analysis identified 88 DEGs related to osteosarcoma metastasis. Among them, three survival-related central DEGs-C1QA, CD74, and HLA-DMA-were significantly linked to patient outcomes. Further correlation analysis established a strong relationship between these genes, tumor mutation burden (TMB), immune checkpoint gene expression, and overall survival. Notably, C1QA and CD74 exhibited higher expression in non-metastatic osteosarcoma cases, suggesting a potential role in disease progression. Conclusions: The identified DEGs, particularly C1QA, CD74, and HLA-DMA, may serve as critical biomarkers for pediatric osteosarcoma prognosis and potential targets for immunotherapy. These findings provide a deeper understanding of the molecular landscape of osteosarcoma and open new avenues for therapeutic intervention.

Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods

Gliomas are primary malignant brain tumors with poor survival and high resistance to available treatments. Improving the molecular understanding of glioma and disclosing novel biomarkers of tumor development and progression could help to find novel targeted therapies for this type of cancer. Public databases such as The Cancer Genome Atlas (TCGA) provide an invaluable source of molecular information on cancer tissues. Machine learning tools show promise in dealing with the high dimension of omics data and extracting relevant information from it. In this work, network inference and clustering methods, namely Joint Graphical lasso and Robust Sparse K-means Clustering, were applied to RNA-sequencing data from TCGA glioma patients to identify shared and distinct gene networks among different types of glioma (glioblastoma, astrocytoma, and oligodendroglioma) and disclose new patient groups and the relevant genes behind groups' separation. The results obtained suggest that astrocytoma and oligodendroglioma have more similarities compared with glioblastoma, highlighting the molecular differences between glioblastoma and the others glioma subtypes. After a comprehensive literature search on the relevant genes pointed our from our analysis, we identified potential candidates for biomarkers of glioma. Further molecular validation of these genes is encouraged to understand their potential role in diagnosis and in the design of novel therapies.

Complement protein C1q stimulates hyaluronic acid degradation via gC1qR/HABP1/p32 in malignant pleural mesothelioma

Complement component C1q can act as a pro-tumorigenic factor in the tumor microenvironment (TME). The TME in malignant pleural mesothelioma (MPM) is rich in C1q and hyaluronic acid (HA), whose interaction enhances adhesion, migration and proliferation of malignant cells. HA-bound C1q is also capable of modulating HA synthesis. Thus, we investigated whether HA-C1q interaction would affect HA degradation, analyzing the main degradation enzymes, hyaluronidase (HYAL)1 and HYAL2, and a C1q receptor candidate. We first proceeded with the characterization of HYALs in MPM cells, especially HYAL2, since bioinformatics survival analysis revealed that higher HYAL2 mRNA levels have an unfavorable prognostic index in MPM patients. Interestingly, Real-Time quantitative PCR, flow cytometry and Western blot highlighted an upregulation of HYAL2 after seeding of primary MPM cells onto HA-bound C1q. In an attempt to unveil the receptors potentially involved in HA-C1q signaling, a striking co-localization between HYAL2 and globular C1q receptor/HABP1/p32 (gC1qR) was found by immunofluorescence, surface biotinylation and proximity ligation assays. RNA interference experiments revealed a potentially regulatory function exerted by gC1qR on HYAL2 expression, since C1QBP (gene for gC1qR) silencing unexpectedly caused HYAL2 downregulation. In addition, the functional blockage of gC1qR by a specific antibody hindered HA-C1q signaling and prevented HYAL2 upregulation. Thus, C1q-HA interplay is responsible for enhanced HYAL2 expression, suggesting an increased rate of HA catabolism and the release of pro-inflammatory and pro-tumorigenic HA fragments in the MPM TME. Our data support the notion of an overall tumor-promoting property of C1q. Moreover, the overlapping localization and physical interaction between HYAL2 and gC1qR suggests a potential regulatory effect of gC1qR within a putative HA-C1q macromolecular complex.

Complement Activation and Up-Regulated Expression of Anaphylatoxin C3a/C3aR in Glioblastoma: Deciphering the Links with TGF-β and VEGF

The complement (C) innate immune system has been shown to be activated in the tumor microenvironment of various cancers. The C may support tumor growth by modulating the immune response and promoting angiogenesis through the actions of C anaphylatoxins (e.g., C5a, C3a). The C has important double-edged sword functions in the brain, but little is known about its role in brain tumors. Hence, we analyzed the distribution and the regulated expression of C3a and its receptor C3aR in various primary and secondary brain tumors. We found that C3aR was dramatically upregulated in Grade 4 diffuse gliomas, i.e., glioblastoma multiforme, IDH-wildtype (GBM) and astrocytoma, IDH-mutant, Grade 4, and was much less expressed in other brain tumors. C3aR was observed in tumor-associated macrophages (TAM) expressing CD68, CD18, CD163, and the proangiogenic VEGF. Robust levels of C3a were detected in the parenchyma of GBM as a possible result of Bb-dependent C activation of the alternative C pathway. Interestingly, in vitro models identified TGF-β1 as one of the most potent growth factors that upregulate VEGF, C3, and C3aR in TAM (PMA-differentiated THP1) cell lines. Further studies should help to delineate the functions of C3a/C3aR on TAMs that promote chemotaxis/angiogenesis in gliomas and to explore the therapeutic applications of C3aR antagonists for brain tumors.

Single-Cell Transcriptomics Reveals Evidence of Endothelial Dysfunction in the Brains of COVID-19 Patients with Implications for Glioblastoma Progression

BACKGROUND

Endothelial dysfunction is implicated in various inflammatory diseases such as ischemic stroke, heart attack, organ failure, and COVID-19. Recent studies have shown that endothelial dysfunction in the brain is attributed to excessive inflammatory responses caused by the SARS-CoV-2 infection, leading to increased permeability of the blood-brain barrier and consequently neurological damage. Here, we aim to examine the single-cell transcriptomic landscape of endothelial dysfunction in COVID-19 and its implications for glioblastoma (GBM) progression.

METHODS

Single-cell transcriptome data GSE131928 and GSE159812 were obtained from the gene expression omnibus (GEO) to analyze the expression profiles of key players in innate immunity and inflammation between brain endothelial dysfunction caused by COVID-19 and GBM progression.

RESULTS

Single-cell transcriptomic analysis of the brain of COVID-19 patients revealed that endothelial cells had undergone significant transcriptomic changes, with several genes involved in immune responses and inflammation upregulated. Moreover, transcription factors were observed to modulate this inflammation, including interferon-regulated genes.

CONCLUSIONS

The results indicate a significant overlap between COVID-19 and GBM in the context of endothelial dysfunction, suggesting that there may be an endothelial dysfunction link connecting severe SARS-CoV-2 infection in the brain to GBM progression.

The Role of Cellular Immunity and Adaptive Immunity in Pathophysiology of Brain and Spinal Cord Tumors

Major advances have been made in our understanding of CNS tumors, especially glioma, however, the survival of patients with malignant glioma remains poor. While radiation and chemotherapy have increased overall survival, glioblastoma multiforme (GBM) still has one of the worst 5-year survival rates of all human cancers. Here, in this chapter, the authors review the abrogation of the immune system in the tumor setting, revealing many plausible targets for therapy and the current immunotherapy treatment strategies employed. Notably, glioma has also been characterized as a subset of primary spinal cord tumor and current treatment recommendations are outlined here.

C1q and central nervous system disorders

C1q is a crucial component of the complement system, which is activated through the classical pathway to perform non-specific immune functions, serving as the first line of defense against pathogens. C1q can also bind to specific receptors to carry out immune and other functions, playing a vital role in maintaining immune homeostasis and normal physiological functions. In the developing central nervous system (CNS), C1q functions in synapse formation and pruning, serving as a key player in the development and homeostasis of neuronal networks in the CNS. C1q has a close relationship with microglia and astrocytes, and under their influence, C1q may contribute to the development of CNS disorders. Furthermore, C1q can also have independent effects on neurological disorders, producing either beneficial or detrimental outcomes. Most of the evidence for these functions comes from animal models, with some also from human specimen studies. C1q is now emerging as a promising target for the treatment of a variety of diseases, and clinical trials are already underway for CNS disorders. This article highlights the role of C1q in CNS diseases, offering new directions for the diagnosis and treatment of these conditions.

Machine learning and bioinformatics-based insights into the potential targets of saponins in Paris polyphylla smith against non-small cell lung cancer

Background: Lung cancer has the highest mortality rate among cancers worldwide, and non-small cell lung cancer (NSCLC) is the major lethal factor. Saponins in Paris polyphylla smith exhibit antitumor activity against non-small cell lung cancer, but their targets are not fully understood.

Methods: In this study, we used differential gene analysis, lasso regression analysis and support vector machine recursive feature elimination (SVM-RFE) to screen potential key genes for NSCLC by using relevant datasets from the GEO database. The accuracy of the signature genes was verified by using ROC curves and gene expression values. Screening of potential active ingredients for the treatment of NSCLC by molecular docking of the reported active ingredients of saponins in Paris polyphylla Smith with the screened signature genes. The activity of the screened components and their effects on key genes expression were further validated by CCK-8, flow cytometry (apoptosis and cycling) and qPCR.

Results: 204 differential genes and two key genes (RHEBL1, RNPC3) stood out in the bioinformatics analysis. Overall survival (OS), First-progression survival (FP) and post-progression survival (PPS) analysis revealed that low expression of RHEBL1 and high expression of RNPC3 indicated good prognosis. In addition, Polyphyllin VI(PPVI) and Protodioscin (Prot) effectively inhibited the proliferation of non-small cell lung cancer cell line with IC50 of 4.46 μM ± 0.69 μM and 8.09 μM ± 0.67μM, respectively. The number of apoptotic cells increased significantly with increasing concentrations of PPVI and Prot. Prot induces G1/G0 phase cell cycle arrest and PPVI induces G2/M phase cell cycle arrest. After PPVI and Prot acted on this cell line for 48 h, the expression of RHEBL1 and RNPC3 was found to be consistent with the results of bioinformatics analysis.

Conclusion: This study identified two potential key genes (RHEBL1 and RNPC3) in NSCLC. Additionally, PPVI and Prot may act on RHEBL1 and RNPC3 to affect NSCLC. Our findings provide a reference for clinical treatment of NSCLC.

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.

Prognostic and immune-related value of complement C1Q (C1QA, C1QB, and C1QC) in skin cutaneous melanoma

Background: Skin cutaneous melanoma (SKCM) is a common malignancy that is associated with increased morbidity and mortality. Complement C1Q is composed of C1QA, C1QB, and C1QC and is involved in the occurrence and development of many malignant tumours. However, the effect of C1QA, C1QB, and C1QC expression on tumour immunity and prognosis of cutaneous melanoma remains unclear.

Methods: First, we analysed C1QA, C1QB, and C1QC expression levels and prognostic values using Gene Expression Profiling Interactive Analysis (GEPIA) and Tumour Immune Estimation Resource (TIMER) analysis, and further validation was performed using RT-qPCR, The Human Protein Atlas, The Cancer Genome Atlas (TCGA) dataset, and Gene Expression Omnibus dataset. We then performed univariate/multivariate Cox proportional hazard model, clinicopathological correlation, and receiver operating characteristic curve analysis using TCGA dataset and established a nomogram model. Differentially expressed genes associated with C1QA, C1QB, and C1QC in SKCM were identified and analysed using LinkedOmics, TIMER, the Search Tool for the Retrieval of Interacting Genes database, and Metascape and Cytoscape software platforms. We used TIMER, GEPIA, and single-sample gene set enrichment analysis (ssGSEA) to analyse the relationship between the three genes and the level of immune cell infiltration, biomarkers, and checkpoint expression in SKCM. Finally, GSEA was utilized to study the functional pathways of C1QA, C1QB, and C1QC enrichment in SKCM.

Results: The overexpression of C1QA, C1QB, and C1QC provided significant value in the diagnosis of SKCM and has been associated with better overall survival (OS). Multivariate Cox regression analysis indicated that C1QA, C1QB, and C1QC are independent prognostic biomarkers for patients with SKCM. Immune cell infiltration, biomarkers, and checkpoints were positively correlated with the expression of C1QA, C1QB, and C1QC. Furthermore, the results of functional and pathway enrichment analysis showed that immune-related and apoptotic pathways were significantly enriched in the high-expression group of C1QA, C1QB, and C1QC.

Conclusion: We found that C1QA, C1QB, and C1QC can be used as biomarkers for the diagnosis and prognosis of SKCM patients. The upregulated expression levels of these three complement components benefit patients from OS and may increase the effect of immunotherapy. This result may be due to the dual effects of anti-tumour immunity and apoptosis.

Identification of plasma proteins associated with oesophageal cancer chemotherapeutic treatment outcomes using SWATH-MS

Oesophageal adenocarcinoma (OAC) is an aggressive cancer with a five-year survival of <15%. Current chemotherapeutic strategies only benefit a minority (20-30%) of patients and there are no methods available to differentiate between responders and non-responders. We performed quantitative proteomics using Sequential Window Acquisition of all THeoretical fragment-ion spectra-Mass Spectrometry (SWATH-MS) on albumin/IgG-depleted and non-depleted plasma samples from 23 patients with locally advanced OAC prior to treatment. Individuals were grouped based on tumour regression (TRG) score (TRG1/2/3 vs TRG4/5) after chemotherapy, and differentially abundant proteins were compared. Protein depletion of highly abundant proteins led to the identification of around twice as many proteins. SWATH-MS revealed significant quantitative differences in the abundance of several proteins between the two groups. These included complement c1q subunit proteins, C1QA, C1QB and C1QC, which were of higher abundance in the low TRG group. Of those that were found to be of higher abundance in the high TRG group, glutathione S-transferase pi (GSTP1) exhibited the lowest p-value and highest classification accuracy and Cohen's kappa value. Concentrations of these proteins were further examined using ELISA-based assays. This study provides quantitative information relating to differences in the plasma proteome that underpin response to chemotherapeutic treatment in oesophageal cancers. SIGNIFICANCE: Oesophageal cancers, including oesophageal adenocarcinoma (OAC) and oesophageal gastric junction cancer (OGJ), are one of the leading causes of cancer mortality worldwide. Curative therapy consists of surgery, either alone or in combination with adjuvant or neoadjuvant chemotherapy or radiation, or combination chemoradiotherapy regimens. There are currently no clinico-pathological means of predicting which patients will benefit from chemotherapeutic treatments. There is therefore an urgent need to improve oesophageal cancer disease management and treatment strategies. This work compared proteomic differences in OAC patients who responded well to chemotherapy as compared to those who did not, using quantitative proteomics prior to treatment commencement. SWATH-MS analysis of plasma (with and without albumin/IgG-depletion) from OAC patients prior to chemotherapy was performed. This approach was adopted to determine whether depletion offered a significant improvement in peptide coverage. Resultant datasets demonstrated that depletion increased peptide coverage significantly. Additionally, there was good quantitative agreement between commonly observed peptides. Data analysis was performed by adopting both univariate as well as multivariate analysis strategies. Differentially abundant proteins were identified between treatment response groups based on tumour regression grade. Such proteins included complement C1q sub-components and GSTP1. This study provides a platform for further work, utilising larger sample sets across different treatment regimens for oesophageal cancer, that will aid the development of 'treatment response prediction assays' for stratification of OAC patients prior to chemotherapy.

The Potential Role of Exosomal Proteins in Prostate Cancer

Prostate cancer is the most prevalent malignant tumor in men across developed countries. Traditional diagnostic and therapeutic methods for this tumor have become increasingly difficult to adapt to today’s medical philosophy, thus compromising early detection, diagnosis, and treatment. Prospecting for new diagnostic markers and therapeutic targets has become a hot topic in today’s research. Notably, exosomes, small vesicles characterized by a phospholipid bilayer structure released by cells that is capable of delivering different types of cargo that target specific cells to regulate biological properties, have been extensively studied. Exosomes composition, coupled with their interactions with cells make them multifaceted regulators in cancer development. Numerous studies have described the role of prostate cancer-derived exosomal proteins in diagnosis and treatment of prostate cancer. However, so far, there is no relevant literature to systematically summarize its role in tumors, which brings obstacles to the later research of related proteins. In this review, we summarize exosomal proteins derived from prostate cancer from different sources and summarize their roles in tumor development and drug resistance.

Aberrant Expression of Mitochondrial SAM Transporter SLC25A26 Impairs Oocyte Maturation and Early Development in Mice

The immature germinal vesicle (GV) oocytes proceed through metaphase I (MI) division, extrude the first polar body, and become mature metaphase II (MII) oocytes for fertilization which is followed by preimplantation and postimplantation development until birth. Slc25a26 is the gene encoding S-adenosylmethionine carrier (SAMC), a member of the mitochondrial carrier family. Its major function is to catalyze the uptake of S-adenosylmethionine (SAM) from cytosol into mitochondria, which is the only known mitochondrial SAM transporter. In the present study, we demonstrated that excessive SLC25A26 accumulation in mouse oocytes mimicked naturally aged oocytes and resulted in lower oocyte quality with decreased maturation rate and increased reactive oxygen species (ROS) by impairing mitochondrial function. Increased level of Slc25a26 gene impacted gene expression in mouse oocytes such as mt-Cytb which regulates mitochondrial respiratory chain. Furthermore, increased level of Slc25a26 gene in fertilized oocytes slightly compromised blastocyst formation, and Slc25a26 knockout mice displayed embryonic lethality around 10.5 dpc. Taken together, our results showed that Slc25a26 gene plays a critical role in oocyte maturation and early mouse development.

The role of complement in the tumor microenvironment

Tumorigenesis has long been linked to the evasion of the immune system and the uncontrolled proliferation of transformed cells. The complement system, a major arm of innate immunity, is a key factor in the progression of cancer because many of its components have critical regulatory roles in the tumor microenvironment. For example, complement anaphylatoxins directly and indirectly inhibit antitumor T-cell responses in primary and metastatic sites, enhance proliferation of tumor cells, and promote metastasis and tumor angiogenesis. Many recent studies have provided evidence that cancer is able to hijack the immunoregulatory components of the complement system which fundamentally are tasked with protecting the body against abnormal cells and pathogens. Indeed, recent evidence shows that many types of cancer use C1q receptors (C1qRs) to promote tumor growth and progression. More importantly, most cancer cells express both C1q and its major receptors (gC1qR and cC1qR) on their surface which are essential for cell proliferation and survival. In this review, we discuss the ability of cancer to control and manipulate the complement system in the tumor microenvironment and identify possible therapeutic targets, including C1q and gC1qR.

Combined Identification of Novel Markers for Diagnosis and Prognostic of Classic Hodgkin Lymphoma

Background

An effective diagnostic and prognostic marker based on the gene expression profile of classic Hodgkin lymphoma (cHL) has not yet been developed. The aim of the present study was to investigate potential markers for the diagnosis and prediction of cHL prognosis.

Methods

The gene expression profiles with all available clinical features were downloaded from the Gene Expression Omnibus (GEO) database. Then, multiple machine learning algorithms were applied to develop and validate a diagnostic signature by comparing cHL with normal control. In addition, we identified prognostic genes and built a prognostic model with them to predict the prognosis for 130 patients with cHL which were treated with first-line treatment (ABVD chemotherapy or an ABVD-like regimen).

Results

A diagnostic prediction signature was constructed and showed high specificity and sensitivity (training cohort: AUC=0.981,95% CI 0.933–0.998, P<0.001, validation cohort: AUC=0.955,95% CI 0.895–0.986, P<0.001). Additionally, nine prognostic genes (LAMP1, STAT1, MMP9, C1QB, ICAM1, CD274, CCL19, HCK and LILRB2) were screened and a prognostic prediction model was constructed with them, which had been confirmed effectively predicting prognosis (P<0.001). Furthermore, the results of the immune infiltration assessment indicated that the high scale of the fraction of CD8 + T cells, M1 macrophages, resting mast cells associated with an adverse outcome in cHL, and naive B cells related to prolonged survival. In addition, a nomogram that combined the prognostic prediction model and clinical characteristics is also suggested to have a good predictive value for the prognosis of patients.

Conclusion

The new markers found in this study may be helpful for the diagnosis and prediction of the prognosis of cHL.

Development and Validation of a Prognostic Gene Signature Correlated With M2 Macrophage Infiltration in Esophageal Squamous Cell Carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is the most common type of esophageal cancer and the seventh most prevalent cause of cancer-related death worldwide. Tumor microenvironment (TME) has been confirmed to play an crucial role in ESCC progression, prognosis, and the response to immunotherapy. There is a need for predictive biomarkers of TME-related processes to better prognosticate ESCC outcomes.

Aim

To identify a novel gene signature linked with the TME to predict the prognosis of ESCC.

Methods

We calculated the immune/stromal scores of 95 ESCC samples from The Cancer Genome Atlas (TCGA) using the ESTIMATE algorithm, and identified differentially expressed genes (DEGs) between high and low immune/stromal score patients. The key prognostic genes were further analyzed by the intersection of protein–protein interaction (PPI) networks and univariate Cox regression analysis. Finally, a risk score model was constructed using multivariate Cox regression analysis. We evaluated the associations between the risk score model and immune infiltration via the CIBERSORT algorithm. Moreover, we validated the signature using the Gene Expression Omnibus (GEO) database. Within the ten gene signature, five rarely reported genes were further validated with quantitative real time polymerase chain reaction (qRT-PCR) using an ESCC tissue cDNA microarray.

Results

A total of 133 up-regulated genes were identified as DEGs. Ten prognostic genes were selected based on intersection analysis of univariate COX regression analysis and PPI, and consisted of C1QA, C1QB, C1QC, CD86, C3AR1, CSF1R, ITGB2, LCP2, SPI1, and TYROBP (HR>1, p<0.05). The expression of 9 of these genes in the tumor samples were significantly higher compared to matched adjacent normal tissue based on the GEO database (p<0.05). Next, we assessed the ability of the ten-gene signature to predict the overall survival of ESCC patients, and found that the high-risk group had significantly poorer outcomes compared to the low-risk group using univariate and multivariate analyses in the TCGA and GEO cohorts (HR=2.104, 95% confidence interval:1.343-3.295, p=0.001; HR=1.6915, 95% confidence interval:1.053-2.717, p=0.0297). Additionally, receiver operating characteristic (ROC) curve analysis demonstrated a relatively sensitive and specific profile for the signature (1-, 2-, 3-year AUC=0.672, 0.854, 0.81). To identify the basis for these differences in the TME, we performed correlation analyses and found a significant positive correlation with M1 and M2 macrophages and CD8+ T cells, as well as a strong correlation to M2 macrophage surface markers. A nomogram based on the risk score and select clinicopathologic characteristics was constructed to predict overall survival of ESCC patients. For validation, qRT-PCR of an ESCC patient cDNA microarray was performed, and demonstrated that C1QA, C3AR1, LCP2, SPI1, and TYROBP were up-regulated in tumor samples and predict poor prognosis.

Conclusion

This study established and validated a novel 10-gene signature linked with M2 macrophages and poor prognosis in ESCC patients. Importantly, we identified C1QA, C3AR1, LCP2, SPI1, and TYROBP as novel M2 macrophage-correlated survival biomarkers. These findings may identify potential targets for therapy in ESCC patients.

Integrative analysis of DNA methylation and gene expression profiles to identify biomarkers of glioblastoma

Glioblastoma multiforme (GBM) is the most common, most invasive, and malignant type of primary brain tumor with poor prognosis and poor survival rate. Using GSE22891 the expression and methylation status of same GBM patients was evaluated to identify key epigenetic genes in GBM. Using |log2FC| > 1 and FDR 〈 0.05 as the threshold, DEGs including 4910 downregulated and 2478 upregulated were screened and by |log2FC| 〉 0.2 and p-value < 0.05, 3223 DMCs were detected. By merging the results of DEGs and DMCs, 643 genes were selected for network analysis by WGCNA, and based on expression values three modules and by methylation values, one module was selected. Using STRING and Cytoscape databases, PPI network of genes of all modules were constructed separately. According to the PPI network, core genes were picked out. The expression status of core genes was evaluated using GSE77043, GSE42656, GSE30563, GSE22891, GSE15824, and GSE122498, and 50 genes were validated. The methylation status of 50 genes was explored using GSE50923, GSE22891, and GSE36245, and finally, 12 hub genes including ARHGEF7, RAB11FIP4, PPP1R16B, OLFM1, CLDN10, BCAT1, C1QB, C1QC, IFI16, NUP37, PARP9, and PCLAF were selected. Using GEPIA database, the expression and by cBioportal the survival plot and also scatterplot of methylation versus expression of 12 hub genes were extracted based on TCGA. To determine the diagnostic values of the hub genes, the receiver operating characteristic (ROC) curve and the area under the curve (AUC) were extracted based on GSE22891 and GSE122498. Finally, we evaluated the expression level of the genes in tissue of 83 GBM patients and also non-tumoral adjacent (as control) tissues.

The Novel Tumor Microenvironment-Related Prognostic Gene AIF1 May Influence Immune Infiltrates and is Correlated with TIGIT in Esophageal Cancer

BACKGROUND

Esophageal carcinoma (EC) is the sixth most common cause of cancer-related mortality worldwide. Studying the associations of the tumor microenvironment (TME) with pathology and prognosis would illustrate the underlying mechanism of prognostic prediction and provide novel targets for immunotherapy in the treatment of EC.

METHODS

Transcriptomic profiles of 159 EC patients were obtained from The Cancer Genome Atlas (TCGA) database. Stromal and immune scores were calculated using the ESTIMATE algorithm. Differentially expressed genes (DEGs) were identified by the optimal score cutoff. Functional enrichments were analyzed by DAVID, while prognostic genes were explored using the Kaplan-Meier method. Validation analysis was performed using immunohistochemistry in tissue microarrays containing samples from 145 EC patients. Multiplex immunofluorescence staining was performed to detect a panel of 6 immune markers, including T-cell immunoreceptor with Ig and ITIM domains (TIGIT), in 90 EC patients.

RESULTS

Immune scores significantly increased with increasing age, while stromal scores were dramatically elevated with increasing tumor stage. Fifteen TME-related DEGs including allograft inflammatory factor 1 (AIF1) were identified as prognostic factors of EC. Furthermore, the validation cohort indicated that AIF1 was negatively associated with the prognosis of esophageal squamous cell carcinoma patients. Subsequent analyses suggested that AIF1 may affect immune infiltrates, including T cells and natural-killer cells. Moreover, a correlation between AIF1 and TIGIT was identified.

CONCLUSIONS

These results indicate that the TME-related gene AIF1 is a promising predictor of prognosis and is related to immune infiltrates and TIGIT expression in EC. However, further mechanistic studies are needed.

Circulating C1q levels in health and disease, more than just a biomarker

C1q is the recognition molecule of the classical pathway of the complement system. By binding to its targets, such as antigen-bound immunoglobulins or C-reactive protein, C1q contributes to the innate defense against infections. However, C1q also plays several other roles beyond its traditional role in complement activation. Circulating levels of C1q are determined in routine diagnostics as biomarker in several diseases. Decreased C1q levels are present in several autoimmune conditions. The decreased levels reflect the consumption of C1q by complement activation and serves as a biomarker for disease activity. In contrast, increased C1q levels are present in infectious and inflammatory diseases and may serve as a diagnostic biomarker. The increased levels of C1q are still incompletely understood but are suggested to modulate the adaptive immune response as C1q is known to impact on the maturation status of antigen-presenting cells and C1q impacts directly on T cells leading to decreased T-cell activity in high C1q conditions. In this review, we provide a comprehensive overview of the current literature on circulating levels of C1q in health and disease, and discuss how C1q can both protect against infections as well as maintain tolerance by regulating adaptive immunity.

Modulation of the Complement System by Neoplastic Disease of the Central Nervous System

The complement system is a highly conserved component of innate immunity that is involved in recognizing and responding to pathogens. The system serves as a bridge between innate and adaptive immunity, and modulation of the complement system can affect the entire host immune response to a foreign insult. Neoplastic diseases have been shown to engage the complement system in order to evade the immune system, gain a selective growth advantage, and co-opt the surrounding environment for tumor proliferation. Historically, the central nervous system has been considered to be an immune-privileged environment, but it is now clear that there are active roles for both innate and adaptive immunity within the central nervous system. Much of the research on the role of immunological modulation of neoplastic disease within the central nervous system has focused on adaptive immunity, even though innate immunity still plays a critical role in the natural history of central nervous system neoplasms. Here, we review the modulation of the complement system by a variety of neoplastic diseases of the central nervous system. We also discuss gaps in the current body of knowledge and comment on future directions for investigation.

The Role of Complement in Synaptic Pruning and Neurodegeneration

The complement system, an essential part of the innate immune system, is composed of a group of secreted and membrane proteins that collectively participate in maintaining the function of the healthy and diseased brain. However, an inappropriate activation of the complement system has been related to an inflammatory response in multiple diseases, such as stroke, traumatic brain injury, multiple sclerosis, and Alzheimer's disease, as well as Zika infection and radiotherapy. In addition, C1q and C3 (initial activation components of the complement cascade) have been shown to play a key beneficial role in the refinement of synaptic circuits during developmental stages and adult plasticity. Nevertheless, excessive synaptic pruning in the adult brain can be detrimental and has been associated with synaptic loss in several pathological conditions. In this brief review, we will discuss the role of the complement system in synaptic pruning as well as its contribution to neurodegeneration and cognitive deficits. We also mention potential therapeutic approaches to target the complement system to treat several neuroinflammatory diseases and unintended consequences of radiotherapy.

The Complement System in Ovarian Cancer: An Underexplored Old Path

Ovarian cancer is one of the most lethal gynecological cancers. Current therapeutic strategies allow temporary control of the disease, but most patients develop resistance to treatment. Moreover, although successful in a range of solid tumors, immunotherapy has yielded only modest results in ovarian cancer. Emerging evidence underscores the relevance of the components of innate and adaptive immunity in ovarian cancer progression and response to treatment. Particularly, over the last decade, the complement system, a pillar of innate immunity, has emerged as a major regulator of the tumor microenvironment in cancer immunity. Tumor-associated complement activation may support chronic inflammation, promote an immunosuppressive microenvironment, induce angiogenesis, and activate cancer-related signaling pathways. Recent insights suggest an important role of complement effectors, such as C1q or anaphylatoxins C3a and C5a, and their receptors C3aR and C5aR1 in ovarian cancer progression. Nevertheless, the implication of these factors in different clinical contexts is still poorly understood. Detailed knowledge of the interplay between ovarian cancer cells and complement is required to develop new immunotherapy combinations and biomarkers. In this context, we discuss the possibility of targeting complement to overcome some of the hurdles encountered in the treatment of ovarian cancer.

Complement C1q (C1qA, C1qB, and C1qC) May Be a Potential Prognostic Factor and an Index of Tumor Microenvironment Remodeling in Osteosarcoma

The tumor microenvironment (TME) has important effects on the tumorigenesis and development of osteosarcoma (OS). However, the dynamic mechanism regulating TME immune and matrix components remains unclear. In this study, we collected quantitative data on the gene expression of 88 OS samples from The Cancer Genome Atlas (TCGA) database and downloaded relevant clinical cases of OS from the TARGET database. The proportions of tumor-infiltrating immune cells (TICs) and the numbers of immune and matrix components were determined by CIBERSORT and ESTIMATE calculation methods. Protein-protein interaction (PPI) network construction and Cox regression analysis were conducted to analyze differentially expressed genes (DEGs). The complement components C1qA, C1qB and C1qC were then determined to be predictive factors through univariate Cox analysis and PPI cross analysis. Further analysis found that the levels of C1qA, C1qB and C1qC expression were positively linked to OS patient survival time and negatively correlated with the clinicopathological feature percent necrosis at definitive surgery. The results of gene set enrichment analysis (GSEA) demonstrated that genes related to immune functions were significantly enriched in the high C1qA, C1qB and C1qC expression groups. Proportion analysis of TICs by CIBERSORT showed that the levels of C1qA, C1qB and C1qC expression were positively related to M1 and M2 macrophages and CD8+ cells and negatively correlated with M0 macrophages. These results further support the influence of the levels of C1qA, C1qB and C1qC expression on the immune activity of the TME. Therefore, C1qA, C1qB and C1qC may be potential indicators of remodeling in the OS TME, which is helpful to predict the prognosis of patients with OS and provide new ideas for immunotherapy for OS.

Data mining of immune-related prognostic genes in metastatic melanoma microenvironment

Skin cutaneous melanoma (SKCM) is one of the most deadly malignancies. Although immunotherapies showed the potential to improve the prognosis for metastatic melanoma patients, only a small group of patients can benefit from it. Therefore, it is urgent to investigate the tumor microenvironment in melanoma as well as to identify efficient biomarkers in the diagnosis and treatments of SKCM patients. A comprehensive analysis was performed based on metastatic melanoma samples from the Cancer Genome Atlas (TCGA) database and ESTIMATE algorithm, including gene expression, immune and stromal scores, prognostic immune‐related genes, infiltrating immune cells analysis and immune subtype identification. Then, the differentially expressed genes (DEGs) were obtained based on the immune and stromal scores, and a list of prognostic immune‐related genes was identified. Functional analysis and the protein–protein interaction network revealed that these genes enriched in multiple immune-related biological processes. Furthermore, prognostic genes were verified in the Gene Expression Omnibus (GEO) databases and used to predict immune infiltrating cells component. Our study revealed seven immune subtypes with different risk values and identified T cells as the most abundant cells in the immune microenvironment and closely associated with prognostic outcomes. In conclusion, the present study thoroughly analyzed the tumor microenvironment and identified prognostic immune‐related biomarkers for metastatic melanoma.

Targeting the Complement Pathway in Malignant Glioma Microenvironments

Malignant glioma is a highly fatal type of brain tumor, and its reoccurrence is largely due to the ordered interactions among the components present in the complex microenvironment. Besides its role in immune surveillance and clearance under physiological conditions, the complement system is expressed in a variety of tumor types and mediates the interactions within the tumor microenvironments. Recent studies have uncovered the broad expression spectrum of complement signaling molecules in the tumor microenvironment and various tumor cells, in particular, malignant glioma cells. Involvement of the complement system in tumor growth, immunosuppression and phenotype transition have also been elucidated. In this review, we enumerate the expression and function of complement molecules in multiple tumor types reported. Moreover, we elaborate the complement pathways in glioma cells and various components of malignant glioma microenvironments. Finally, we summarize the possibility of the complement molecules as prognostic factors and therapeutic targets in the treatment of malignant glioma. Specific targeting of the complement system maybe of great significance and value in the future treatment of multi-type tumors including malignant glioma.

Hepcidin Upregulation in Lung Cancer: A Potential Therapeutic Target Associated With Immune Infiltration

Lung cancer has the highest death rate among cancers globally. Hepcidin is a fascinating regulator of iron metabolism; however, the prognostic value of hepcidin and its correlation with immune cell infiltration in lung cancer remain unclear. Here, we comprehensively clarified the prognostic value and potential function of hepcidin in lung cancer. Hepcidin expression was significantly increased in lung cancer. High hepcidin expression was associated with sex, age, metastasis, and pathological stage and significantly predicted an unfavorable prognosis in lung cancer patients. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) results suggested that hepcidin is involved in the immune response. Furthermore, hepcidin expression was positively correlated with the infiltration levels of immune cells and the expression of diverse immune cell marker sets. Importantly, hepcidin may affect prognosis partially by regulating immune infiltration in lung cancer patients. Hepcidin may serve as a candidate prognostic biomarker for determining prognosis associated with immune infiltration in lung cancer.

Brain Mapping-Aided SupraTotal Resection (SpTR) of Brain Tumors: The Role of Brain Connectivity

Brain gliomas require a deep knowledge of their effects on brain connectivity. Understanding the complex relationship between tumor and functional brain is the preliminary and fundamental step for the subsequent surgery. The extent of resection (EOR) is an independent variable of surgical effectiveness and it correlates with the overall survival. Until now, great efforts have been made to achieve gross total resection (GTR) as the standard of care of brain tumor patients. However, high and low-grade gliomas have an infiltrative behavior and peritumoral white matter is often infiltrated by tumoral cells. According to these evidences, many efforts have been made to push the boundary of the resection beyond the contrast-enhanced lesion core on T1w MRI, in the so called supratotal resection (SpTR). SpTR is aimed to maximize the extent of resection and thus the overall survival. SpTR of primary brain tumors is a feasible technique and its safety is improved by intraoperative neuromonitoring and advanced neuroimaging. Only transient cognitive impairments have been reported in SpTR patients compared to GTR patients. Moreover, SpTR is related to a longer overall and progression-free survival along with preserving neuro-cognitive functions and quality of life.

Identification of a Prognostic Signature Model with Tumor Microenvironment for predicting Disease-free Survival after Radical Prostatectomy

Background: The tumor microenvironment (TME) and immune checkpoint inhibitors have been shown to promote active immune responses through different mechanisms. We attempted to identify the important prognostic genes and prognostic characteristics related to TME in prostate cancer (PCa).

Methods: The gene transcriptome profiles and clinical information of PCa patients were obtained from The Cancer Genome Atlas (TCGA) database, and the immune and stromal scores were calculated by the ESTIMATE algorithm. We evaluated the prognostic value of the risk score (RS) model based on univariate Cox analysis and least absolute shrinkage and selection operation (LASSO) Cox regression analysis and established a nomogram to predict disease-free survival (DFS) in PCa patients. The GSE70768 dataset was utilized for external validation. Twenty-two subsets of tumor-infiltrating immune cells were analyzed using the CIBERSORT algorithm.

Results: In this study, the patients with higher immune/stromal scores were associated with a worse DFS, higher Gleason score, and higher pathological T stage. Based on the immune and stromal scores, 515 differentially expressed genes (DEGs) were identified. The univariate Cox and LASSO Cox regression models were employed to select 18 DEGs from 515 DEGs and construct an RS model. The DFS of the high-RS group was significantly lower than that of the low-RS group (P<0.001). The AUCs for the 1-year, 3-year and 5-year DFS rates in the RS model were 0.890, 0.877 and 0.841, respectively. A nomogram of DFS was established based on the RS and Gleason score, and the AUCs for the 1-year, 3-year and 5-year DFS rates in the nomogram were 0.907, 0.893, and 0.872, respectively. These results were further validated in the GSE70768 dataset. In addition, the proportion of Tregs was determined to be higher in high-RS patients (P<0.05), and the expression levels of five immune checkpoints (CTLA-4, PD-1, LAG-3, TIM-3 and TIGIT) were observed to be higher in high-RS patients (P<0.05).

Conclusions: Our study established and validated an 18-gene prognostic signature model associated with TME, which might serve as a prognosis stratification tool to predict DFS in PCa patients after radical prostatectomy.

Immunological and clinicopathological characteristics of C1RL in 2120 glioma patients

BACKGROUND

Glioma is a deadly and immunosuppressive brain tumour. Complement C1r subcomponent like (C1RL), a prognostic biomarker in several kinds of tumours, has attracted increasing attention from oncologists. However, the role of C1RL in glioma remains unclear.

METHODS

Through analysis of 2120 glioma patients from 5 public datasets, the relationships between C1RL expression and clinicopathological characteristics were evaluated. Furthermore, the C1RL-associated genes were screened, and Gene Ontology (GO) analysis was conducted to investigate biological process enrichment. In addition, tumour purity, leukocyte infiltration and overall survival were evaluated based on C1RL expression.

RESULTS

We found that C1RL expression was upregulated in glioblastoma (GBM), especially mesenchymal GBM and primary GBM. Increased C1RL expression accompanied the IDH1-wt phenotype in both lower grade glioma (LGG) and GBM. C1RL- associated genes were mainly enriched in biological processes related to the immune response. C1RL expression was also correlated with reduced tumour purity and increased M2 macrophage infiltration. Higher C1RL expression predicted unfavourable survival in patients with glioma and therapeutic resistance in GBM.

CONCLUSIONS

Our results imply that C1RL is involved in immunological activities and is an independent unfavourable prognostic biomarker in patients with glioma. C1RL is a potential clinical immunotherapeutic target for glioma treatment in the future.

Multiple paragangliomas: a case report

Background

Carotid and vagal paragangliomas (CPGLs and VPGLs) are rare neoplasms that arise from the paraganglia located at the bifurcation of carotid arteries and vagal trunk, respectively. Both tumors can occur jointly as multiple paragangliomas accounting for approximately 10 to 20% of all head and neck paragangliomas. However, molecular and genetic mechanisms underlying the pathogenesis of multiple paragangliomas remain elusive.

Case presentation

We report a case of multiple paragangliomas in a patient, manifesting as bilateral CPGL and unilateral VPGL. Tumors were revealed via computed tomography and ultrasound study and were resected in two subsequent surgeries. Both CPGLs and VPGL were subjected to immunostaining for succinate dehydrogenase (SDH) subunits and exome analysis. A likely pathogenic germline variant in the SDHD gene was indicated, while likely pathogenic somatic variants differed among the tumors.

Conclusions

The identified germline variant in the SDHD gene seems to be a driver in the development of multiple paragangliomas. However, different spectra of somatic variants identified in each tumor indicate individual molecular mechanisms underlying their pathogenesis.

Identification of TYROBP and C1QB as Two Novel Key Genes With Prognostic Value in Gastric Cancer by Network Analysis

Background: Gastric cancer (GC) is the fifth most frequently diagnosed malignancy, and the third leading cause of tumor-related mortalities worldwide. Due to a high heterogeneity in GC, its treatment and prognosis are challenging, necessitating urgent identification of novel prognostic predictors for GC patients. Methods: We downloaded RNA sequence data, from the Cancer Genome Atlas and microarray data from Gene Expression Omnibus database, then identified common differentially-expressed genes (DEGs) between GC and normal gastric tissues across four datasets. We then used a combination of protein-protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA) to identify key genes with prognostic value in GC. Thereafter, we used quantitative real time polymerase chain reaction (qRT-PCR) to validate expression of the identified key genes in the Zhejiang University (ZJU) cohort. Finally, we evaluated the relationships between gene expression and immune factors, including immune cells and biomarkers of immunotherapy. Results: Among 426 common DEGs screened, 333 and 93 were upregulated and downregulated, respectively. PPI network and WGCNA successfully identified the top 30 hub genes, among which PTPRC, TYROBP, CCR1, CYBB, LCP2, and C1QB were common. Furthermore, TYROBP and C1QB were negatively associated with prognosis of GC patients, implying that they were key GC predictors. Interestingly, TYROBP and C1QB were positively correlated with predictive biomarkers for GC immunotherapy, including PD-L1 expression, CD8⁺ T cells infiltration, and EBV status. Conclusions: TYROBP and C1QB were identified as two novel key genes with prognostic value in GC by network analysis.

Prognostic Value of Complement Properdin in Cancer

The complement system is readily triggered by the presence of damage-associated molecular patterns on the surface of tumor cells. The complement alternative pathway provides rapid amplification of the molecular stress signal, leading to complement cascade activation to deal with pathogens or malignant cells. Properdin is the only known positive regulator of the alternative pathway. In addition, properdin promotes the phagocytic uptake of apoptotic T cells by macrophages and dendritic cells without activating the complement system, thus, establishing its ability to recognize "altered-self". Dysregulation of properdin has been implicated in substantial tissue damage in the host, and in some cases, chronic unresolved inflammation. A corollary of this may be the development of cancer. Hence, to establish a correlation between properdin presence/levels in normal and cancer tissues, we performed bioinformatics analysis, using Oncomine and UALCAN. Survival analyses were performed using UALCAN and PROGgeneV2 to assess if properdin can serve as a potential prognostic marker for human lung adenocarcinoma (LUAD), liver hepatocellular carcinoma (LIHC), cervical squamous cell carcinoma (CESC), and pancreatic adenocarcinoma (PAAD). We also analyzed levels of tumor-infiltrating immune cells using TIMER, a tool for characterizing immune cell composition in cancers. We found that in LUAD and LIHC, there was a lower expression of properdin in the tumors compared to normal tissues, while no significant difference was observed in CESC and PAAD. Survival analysis demonstrated a positive association between properdin mRNA expression and overall survival in all 4 types of cancers. TIMER analysis revealed that properdin expression correlated negatively with tumor purity and positively with levels of infiltrating B cells, cytotoxic CD8⁺ T cells, CD4⁺ helper T cells, macrophages, neutrophils and dendritic cells in LUAD, CESC and PAAD, and with levels of B cells, CD8⁺ T cells and dendritic cells in LIHC. Immunohistochemical analysis revealed that infiltrating immune cells were the most likely source of properdin in the tumor microenvironment. Thus, complement protein properdin shows promise as a prognostic marker in cancer and warrants further study.