The complement system as a regulator of tumor-promoting activities mediated by myeloid-derived suppressor cells

Identification of Hub Genes in Liver Hepatocellular Carcinoma Based on Weighted Gene Co-expression Network Analysis

Liver hepatocellular carcinoma (LIHC) is a malignant cancer with high incidence and poor prognosis. To investigate the correlation between hub genes and progression of LIHC and to provided potential prognostic markers and therapy targets for LIHC. Our study mainly used The Cancer Genome Atlas (TCGA) LIHC database and the gene expression profiles of GSE54236 from the Gene Expression Omnibus (GEO) to explore the differential co-expression genes between LIHC and normal tissues. The differential co-expression genes were extracted by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. The Genetic Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were carried out to annotate the function of differential genes. Then the hub genes were validated using protein-protein interaction (PPI) network. And the expression level and prognostic analysis were performed. The probable associations between the expression of hub genes and both tumor purity and infiltration of immune cells were explored by TIMER. A total of 68 differential co-expression genes were extracted. These genes were mainly enriched in complement activation (biological process), collagen trimer (cellular component), carbohydrate binding and receptor ligand activity (molecular function) and cytokine - cytokine receptor interaction. Then we demonstrated that the 10 hub genes (CFP, CLEC1B, CLEC4G, CLEC4M, FCN2, FCN3, PAMR1 and TIMD4) were weakly expressed in LIHC tissues, the qRT-PCR results of clinical samples showed that six genes were significantly downregulated in LIHC patients compared with adjacent tissues. Worse overall survival (OS) and disease-free survival (DFS) in LIHC patients were associated with the lower expression of CFP, CLEC1B, FCN3 and TIMD4. Ten hub genes had positive association with tumor purity. CFP, CLEC1B, FCN3 and TIMD4 could serve as novel potential molecular targets for prognosis prediction in LIHC.

Complement factor H: a novel innate immune checkpoint in cancer immunotherapy

The elimination of cancer cells critically depends on the immune system. However, cancers have evolved a variety of defense mechanisms to evade immune monitoring, leading to tumor progression. Complement factor H (CFH), predominately known for its function in inhibiting the alternative pathway of the complement system, has recently been identified as an important innate immunological checkpoint in cancer. CFH-mediated immunosuppression enhances tumor cells' ability to avoid immune recognition and produce an immunosuppressive tumor microenvironment. This review explores the molecular underpinnings, interactions with immune cells, clinical consequences, and therapeutic possibilities of CFH as an innate immune checkpoint in cancer control. The difficulties and opportunities of using CFH as a target in cancer immunotherapy are also explored.

gC1qR: A New Target for Cancer Immunotherapy

Although breakthroughs in cancer treatment have been achieved, immunotherapy yields only modest benefits in most patients. There is still a gap in clarifying the immune evasiveness and immune-resistance mechanisms. Identifying other candidate targets for cancer immunotherapy is therefore a clear unmet clinical need. The complement system, a pillar of innate immunity, has recently entered the limelight due to its immunoregulatory functions in the tumor microenvironment (TME). In particular, gC1qR, a receptor for globular heads of C1q, serves as a promising new target and has attracted more attention. gC1qR, also named P32/C1qBP/HABP1, is a multifunctional protein that is overexpressed in various cancers and holds prognostic value. It regulates the tumorigenic, progression and metastatic properties of tumor cells through several downstream signaling pathways, including the Wnt/β-catenin, PKC-NF-κB and Akt/PKB pathways. A few preclinical experiments conducted through gC1qR interventions, such as monoclonal antibody, chimeric antigen receptor T-cell (CAR-T) therapy, and tumor vaccination, have shown encouraging results in anticancer activity. The efficacy may rely on the regulatory role on the TME, induction of tumor cells apoptosis and antiangiogenic activity. Nevertheless, the current understanding of the relationship between cancer immunotherapy and gC1qR remains elusive and often contradictory, posing both opportunities and challenges for therapeutic translation in the clinic. In this review, we focus on the current understanding of gC1qR function in cancer immunology and highlight the vital roles in regulating the TME. We also examines the rationale behind targeting gC1qR and discusses the potential for translating into clinical practice.

Identification of the mitophagy-related diagnostic biomarkers in hepatocellular carcinoma based on machine learning algorithm and construction of prognostic model

Background and aims

As a result of increasing numbers of studies most recently, mitophagy plays a vital function in the genesis of cancer. However, research on the predictive potential and clinical importance of mitophagy-related genes (MRGs) in hepatocellular carcinoma (HCC) is currently lacking. This study aimed to uncover and analyze the mitophagy-related diagnostic biomarkers in HCC using machine learning (ML), as well as to investigate its biological role, immune infiltration, and clinical significance.

Methods

In our research, by using Least absolute shrinkage and selection operator (LASSO) regression and support vector machine- (SVM-) recursive feature elimination (RFE) algorithm, six mitophagy genes (ATG12, CSNK2B, MTERF3, TOMM20, TOMM22, and TOMM40) were identified from twenty-nine mitophagy genes, next, the algorithm of non-negative matrix factorization (NMF) was used to separate the HCC patients into cluster A and B based on the six mitophagy genes. And there was evidence from multi-analysis that cluster A and B were associated with tumor immune microenvironment (TIME), clinicopathological features, and prognosis. After then, based on the DEGs (differentially expressed genes) between cluster A and cluster B, the prognostic model (riskScore) of mitophagy was constructed, including ten mitophagy-related genes (G6PD, KIF20A, SLC1A5, TPX2, ANXA10, TRNP1, ADH4, CYP2C9, CFHR3, and SPP1).

Results

This study uncovered and analyzed the mitophagy-related diagnostic biomarkers in HCC using machine learning (ML), as well as to investigate its biological role, immune infiltration, and clinical significance. Based on the mitophagy-related diagnostic biomarkers, we constructed a prognostic model(riskScore). Furthermore, we discovered that the riskScore was associated with somatic mutation, TIME, chemotherapy efficacy, TACE and immunotherapy effectiveness in HCC patients.

Conclusion

Mitophagy may play an important role in the development of HCC, and further research on this issue is necessary. Furthermore, the riskScore performed well as a standalone prognostic marker in terms of accuracy and stability. It can provide some guidance for the diagnosis and treatment of HCC patients.

Tumor-Microenvironment Characterization of the MB49 Non-Muscle-Invasive Bladder-Cancer Orthotopic Model towards New Therapeutic Strategies

Bacillus Calmette-Guérin (BCG) instillations for the treatment of non-muscle-invasive bladder cancer patients can result in significant side effects and treatment failure. Immune checkpoint blockade and/or decreasing tumor-infiltrating myeloid suppressor cells may be alternative or complementary treatments. Here, we have characterized immune cell infiltration and chemoattractant molecules in mouse orthotopic MB49 bladder tumors. Our data show a 100-fold increase in CD45⁺ immune cells from day 5 to day 9 tumors including T cells and mainly myeloid cells. Both monocytic myeloid-derived suppressor-cells (M-MDSC) and polymorphonuclear (PMN)-MDSC were strongly increased in day 9 tumors, with PMN-MDSC representing ca. 70% of the myeloid cells in day 12 tumors, while tumor associated macrophages (TAM) were only modestly increased. The kinetic of PD-L1 tumor expression correlated with published data from patients with PD-L1 expressing bladder tumors and with efficacy of anti-PD-1 treatment, further validating the orthotopic MB49 bladder-tumor model as suitable for designing novel therapeutic strategies. Comparison of chemoattractants expression during MB49 bladder tumors grow highlighted CCL8 and CCL12 (CCR2-ligands), CCL9 and CCL6 (CCR-1-ligands), CXCL2 and CXCL5 (CXCR2-ligands), CXCL12 (CXCR4-ligand) and antagonist of C5/C5a as potential targets to decrease myeloid suppressive cells. Data obtained with a single CCR2 inhibitor however showed that the complex chemokine crosstalk would require targeting multiple chemokines for anti-tumor efficacy.