Recombinant Human Uncharacterized protein C5orf46 (C5orf46)

What is the C5orf46 gene and what does it encode?

C5orf46 is a protein-coding gene located in the open reading frame of chromosome 5. It encodes a small amphipathic secreted peptide known as antimicrobial peptide with 64 amino acid residues (AP-64). This peptide functions as an antimicrobial protein with direct antibacterial effects, particularly against gram-negative bacteria. Current research indicates that C5orf46 plays roles in both immune response and cancer biology, with significant implications for each field .

What are the basic structural characteristics of the C5orf46-encoded protein?

AP-64, the protein encoded by C5orf46, is an anionic amphiphilic peptide that notably lacks cysteine residues. It has a molecular weight of 7.2 kDa and an isoelectric point (pI) of 4.54, indicating its acidic nature. Compared to other human antimicrobial peptides, AP-64 possesses distinct characteristics including a longer sequence length, absence of cysteine residues, a highly anionic character, and demonstrated cell toxicity. These structural features contribute to its ability to interact with bacterial membranes and exert antimicrobial effects against various Gram-negative bacteria .

What is the cellular localization of the C5orf46 protein?

Nucleoplasmic isolation experiments have demonstrated that the C5orf46 protein is predominantly located in the cytoplasm of cells. This cytoplasmic localization is consistent with its role as a secreted peptide that can be released from cells to perform antimicrobial functions in the extracellular environment . Understanding this localization is important for researchers investigating the protein's function and potential interactions with other cellular components.

What are the primary biological functions of C5orf46?

C5orf46 demonstrates multiple biological functions:

• Antimicrobial activity: AP-64 exhibits significant antibacterial activity against Gram-negative bacteria, including Escherichia coli DH5α, Escherichia coli O157:H7, Vibrio cholerae, and Pseudomonas aeruginosa .

• Infection control: Studies have shown AP-64 to be efficient in combating Escherichia coli O157:H7 infections in mouse models .

• Cytotoxic effects: AP-64 exhibits cytotoxic effects against human T-cell lymphoma Jurkat and B-cell lymphoma Raji cells .

• Cancer promotion: In renal cancer, high expression of C5orf46 is associated with increased cell proliferation, enhanced migration, and reduced apoptosis .

• Immune regulation: C5orf46 expression correlates with immune cell infiltration in tumor microenvironments and may modulate anti-tumor immunity .

How is C5orf46 expression regulated in normal versus diseased tissues?

Research reveals significant differences in C5orf46 expression between normal and diseased tissues:

• Expression patterns: C5orf46 is significantly upregulated in renal cancer compared to normal kidney tissues. Analysis of TCGA data from 539 kidney renal clear cell carcinoma (KIRC) tissues and 72 paired normal tissues confirmed this overexpression at both the mRNA and protein levels .

• Epigenetic regulation: DNA methylation plays a key role in C5orf46 expression. Studies have found that promoter methylation of C5orf46 is lower in renal cancer than in normal tissue, with more significant hypomethylation observed in higher stages and grades of cancer .

• Mutational status: Analysis from the COSMIC database shows that C5orf46 can undergo various mutations, with missense substitution and synonymous substitution being the most common types .

What experimental approaches are most effective for studying C5orf46 expression in cancer tissues?

For comprehensive analysis of C5orf46 expression in cancer tissues, researchers should consider this multi-modal approach:

• Transcriptional analysis: Quantitative PCR (qPCR) has been successfully used to measure C5orf46 mRNA expression in both tissue samples and cell lines. Public database mining (TCGA, GEO) provides additional transcriptomic data across multiple cancer types .

• Protein detection: Immunohistochemical staining using validated antibodies (such as Atlas antibody HPA079692) can effectively visualize C5orf46 protein expression in tissue sections .

• Clinical correlation: Expression data should be integrated with patient clinical information for survival analysis using Kaplan-Meier curves and Cox regression models. The R packages ggplot, pROC, survminer, and rms have proven useful for these analyses .

• Database utilization: Multiple databases including TIMER 2.0, TCGA, GEO, and Human Protein Atlas provide valuable data on C5orf46 expression across different cancer types .

How can researchers effectively knock down C5orf46 in cellular models?

For successful knockdown of C5orf46 in cellular models:

• siRNA transfection: Small interfering RNA has been effectively used to silence C5orf46 expression in renal cancer cell lines (A498 and OSRC-2). Multiple siRNA sequences targeting different regions of the C5orf46 mRNA should be tested to identify the most effective construct .

• Knockdown verification: qPCR should be performed 24-48 hours post-transfection to confirm reduction in C5orf46 mRNA levels, as demonstrated in previous studies .

• Functional validation: Following knockdown, researchers should validate functional consequences through appropriate assays including:

  • Transwell migration assays to assess cell motility

  • Colony formation assays to evaluate proliferative capacity

  • CCK-8 assays to measure cell growth

  • Flow cytometry for cell cycle analysis and apoptosis detection using Annexin V-PI costaining

What are the key signaling pathways affected by C5orf46 in cancer progression?

Transcriptomic sequencing after C5orf46 knockdown in renal cancer cells has revealed several affected pathways:

• Cell cycle regulation: Silencing C5orf46 arrests renal cancer cells in the G0/G1 phase, suggesting involvement in cell cycle progression pathways .

• Apoptotic pathways: Knockdown of C5orf46 increases apoptosis in cancer cells, indicating it may normally suppress pro-apoptotic signaling .

• Cell adhesion and migration: Pathway analysis shows that C5orf46 influences cellular adhesion, which directly impacts the migratory capabilities of cancer cells .

• Immune response pathways: C5orf46 modulates multiple immune-related signaling cascades, affecting immune cell recruitment and function in the tumor microenvironment .

Gene set enrichment analysis (GSEA) has revealed that genes in cells with normal C5orf46 expression are enriched in tumor pathways, immune infiltration, and cell adhesion-related signaling pathways .

How does C5orf46 influence the tumor immune microenvironment?

C5orf46 demonstrates significant associations with the tumor immune microenvironment:

• Immune cell infiltration: Analysis using the R package GSVA shows that C5orf46 expression positively correlates with infiltration of regulatory T cells (Tregs), B cells, natural killer (NK) cells, and macrophages, while negatively correlating with Th17 cell infiltration in renal cancer .

• Immune modulators: TISIDB database analysis reveals positive associations between C5orf46 expression and key immune factors including:

  • CXCR4 (C-X-C Motif Chemokine Receptor 4)

  • TMEM173 (Stimulator Of Interferon Response CGAMP Interactor 1)

  • TGFB1 (Transforming Growth Factor Beta 1)

• Immune subtypes: C5orf46 expression varies across immune subtypes, being highest in IFN-gamma dominant and inflammatory subtypes and lowest in immunologically quiet subtypes .

• Survival impact: High C5orf46 expression combined with abundant immune cell infiltration correlates with shorter survival times in kidney renal papillary cell carcinoma (KIRP) patients .

What is the relationship between C5orf46 expression and patient prognosis in renal cancer?

C5orf46 expression has demonstrated significant prognostic value in renal cancer:

• Independent prognostic factor: Univariate and multivariate analyses identify C5orf46 as an independent prognostic factor and risk factor for renal cancer, similar to tumor (T), node (N), metastasis (M) stage, histologic grade, and pathologic stage .

• Nomogram models: Incorporating C5orf46 expression with histologic grade and primary therapy outcome demonstrates good performance in predicting patient survival at 1, 3, and 5 years (C-index of 0.817) .

• Diagnostic capability: ROC curve analysis shows that C5orf46 has excellent diagnostic performance in distinguishing renal cancer from normal tissue (area under the ROC curve >0.94) .

How can C5orf46 be targeted for potential therapeutic development?

Several approaches can be considered for targeting C5orf46 therapeutically:

• RNA interference: siRNA or antisense oligonucleotides targeting C5orf46 mRNA could be developed, as experimental knockdown has shown promising anti-cancer effects in vitro including reduced proliferation, inhibited migration, and increased apoptosis in renal cancer cell lines .

• Immune modulation: Since C5orf46 affects immune cell infiltration and function, combining C5orf46 inhibition with immune checkpoint inhibitors might enhance therapeutic efficacy by reprogramming the tumor microenvironment .

• Peptide-based therapeutics: Given that C5orf46 encodes an antimicrobial peptide (AP-64), developing modified peptides that compete with or antagonize its cancer-promoting functions while preserving antimicrobial properties could represent a novel therapeutic strategy .

• Epigenetic modulation: Since C5orf46 expression appears to be regulated by promoter methylation, epigenetic drugs that modulate methylation patterns could potentially normalize its expression in cancer contexts .

What are the challenges in studying the dual role of C5orf46 in antimicrobial activity and cancer progression?

Investigating the seemingly contradictory roles of C5orf46 presents several methodological challenges:

• Functional dichotomy: C5orf46 encodes AP-64, which has direct antibacterial effects against Gram-negative bacteria, yet also appears to promote cancer progression. Researchers must design experiments that can evaluate both functions in appropriate models .

• Structural-functional relationships: Understanding which domains of the protein are responsible for antimicrobial versus pro-cancer effects requires detailed structure-function studies, potentially using truncated or mutated versions of the protein .

• Context-dependent effects: The protein may have different effects depending on cellular context, tissue type, and disease state. Comprehensive studies across multiple cell lines, primary cells, and tissue types are needed .

• Signaling complexity: The protein likely engages different signaling pathways in antimicrobial versus oncogenic contexts. Pathway analysis following manipulation of C5orf46 should be performed in both immune cells and cancer cells .

• Evolutionary considerations: Comparative studies with the mouse homolog Gm94 could provide insights into conserved versus divergent functions across species, potentially explaining the dual functionality .

How can researchers investigate the methylation status of the C5orf46 gene?

To investigate the methylation status of C5orf46:

• Platform selection: The UALCAN and UCSC Xena (Illumina human methylation 450) platforms have been successfully used to analyze C5orf46 methylation patterns across cancer stages, grades, and tissue types .

• Methylation analysis: Data indicates that promoter methylation of C5orf46 is lower in renal cancer than in normal tissue, with more significant hypomethylation observed in higher stages and grades of cancer .

• Correlation studies: Integrating methylation data with expression data can reveal the relationship between promoter methylation and C5orf46 expression levels. In renal cancer, lower methylation correlates with higher expression .

• Experimental approaches: Researchers can manipulate methylation using DNA methyltransferase inhibitors (like 5-azacytidine) to determine causality between methylation status and C5orf46 expression.

What are the appropriate animal models for studying C5orf46 function in vivo?

Several animal models can be considered for in vivo studies of C5orf46 function:

• Mouse models for cancer studies:

  • Orthotopic renal cancer models involving implantation of C5orf46-manipulated renal cancer cells

  • Genetically engineered mouse models with C5orf46 knockout or overexpression

  • Patient-derived xenograft models using human renal cancer tissue with known C5orf46 status

• Mouse models for antimicrobial function:

  • Bacterial infection models, as demonstrated in studies where AP-64 was efficient in combating E. coli O157:H7 infections in mice

  • Mouse C5orf46 homolog (Gm94) closely resembles AP-64 in antibacterial properties, making mouse models particularly relevant for translational studies

• Important considerations:

  • The immune status of the model is crucial given C5orf46's interactions with immune cells

  • Models must be appropriate for studying both the antimicrobial and oncogenic properties of C5orf46

How can researchers differentiate between the effects of C5orf46 mutation versus expression changes?

To distinguish between mutational and expression effects of C5orf46:

• Mutational analysis:

  • COSMIC database and cBioPortal can provide data on C5orf46 mutations in cancer, with missense substitution and synonymous substitution being the most common types

  • Significantly altered C5orf46 copy number occurs in approximately 9% of renal cancer patients

  • The predominant mutation types are G>A and C>T substitutions

• Expression analysis:

  • Quantitative PCR and immunohistochemistry can measure C5orf46 expression at mRNA and protein levels respectively

  • Controlled expression systems can be created using siRNA knockdown in cell models, as has been successfully demonstrated in A498 and OSRC-2 renal cancer cell lines

• Integrated approaches:

  • Correlate mutation status with expression levels in clinical samples

  • Compare phenotypic effects (proliferation, migration, immune interactions) between mutation and expression models