C9orf16 Antibody

What is C9orf16 and what is its biological significance?

C9orf16 (Chromosome 9 open reading frame 16) is a protein-encoding gene whose functions were largely unknown until recently. Research has now established its crucial role in cancer development and progression, particularly in pancreatic ductal adenocarcinoma (PDAC) . The protein is rarely detectable in normal epithelial cells but shows significant upregulation in primary PDAC cancer cells and is further elevated in metastatic PDAC cancer cells . This expression pattern makes it a promising biomarker for early detection and potentially a therapeutic target.

How does C9orf16 interact with major cancer pathways?

C9orf16 has been identified as a critical component in the MYC signaling pathway, which is one of the most activated pathways in PDAC development and progression. Pathway analysis and functional studies have revealed that MYC signaling pathways are heavily involved in regulating C9orf16 expression . This constitutes a crucial gene regulation system, termed MYC-C9orf16, which actively participates in PDAC pathogenesis. The interaction suggests that targeting this pathway could offer novel therapeutic approaches for PDAC treatment.

How reliable are current methods for detecting C9orf16 expression?

Detection methods for C9orf16 have been validated through multiple approaches. Immunohistochemical staining using specific antibodies such as the Sigma-Aldrich HPA020725 (1:500 dilution) has been successfully employed to compare C9orf16 expression between tumor and benign tissues from PDAC patients . Additionally, C9orf16 expression has been analyzed through RNA-sequencing data, particularly in comparative studies between tumor tissues and normal/healthy tissues in colorectal cancer research . These methods provide reliable detection when appropriate antibody validation procedures are followed.

What approaches should researchers use to validate C9orf16 antibodies?

Researchers should implement a comprehensive validation strategy that includes:

• Gene knockout (KO) controls - Use CRISPR/Cas9 to generate C9orf16 KO cell lines as negative controls

• Expression analysis - Identify high-expressing cell lines through proteomics databases like PaxDB

• Multiple application testing - Validate antibodies through immunoblot, immunoprecipitation, and immunofluorescence

• Cross-validation - Compare results from multiple antibodies against the same target

What controls are essential when using C9orf16 antibodies?

These controls are critical for ensuring that research findings are reliable and reproducible. The comparison between parental cell lines and knockout models is particularly important for confirming antibody specificity .

How can CRISPR/Cas9 be effectively used to validate C9orf16 antibodies?

CRISPR/Cas9 technology provides a powerful approach for antibody validation. Researchers should:

• Identify a cell line with relatively high C9orf16 expression using proteomics databases

• Design sgRNAs targeting early exons of C9orf16

• Transfect cells with a plasmid expressing both Cas9 and the sgRNA

• Select transfected cells and isolate clones

• Verify knockouts through genomic DNA sequencing

• Test antibodies by comparing immunoblot signals between parental and knockout lines

This methodology allows for definitive validation of antibody specificity and provides essential negative controls for subsequent experiments . For C9orf16, this approach would follow similar protocols to those used for validating other proteins like C9ORF72, where knockout cell lines revealed which commercial antibodies were truly specific .

What are the optimal conditions for C9orf16 immunohistochemistry?

Based on published research protocols for C9orf16 detection in PDAC tissue samples, the following conditions are recommended:

• Sample preparation: Deparaffinize slides and perform antigen retrieval by heating in citrate buffer (pH 6.0)

• Peroxidase blocking: Treat with 3% hydrogen peroxide

• Primary antibody: Use C9orf16 antibody (Sigma-Aldrich, HPA020725) at 1:500 dilution

• Secondary antibody: Apply goat anti-rabbit IgG H&L (HRP) (e.g., Abcam ab6721) at 1:1000 dilution

• Visualization: Use DAB substrate kit according to manufacturer's instructions

• Evaluation: Count stained cells in at least 500 tumor cells across five different fields

These conditions have been empirically determined in PDAC research and should be optimized for specific experimental contexts.

How should C9orf16 knockdown/overexpression experiments be designed?

For functional studies of C9orf16, researchers can use lentiviral approaches:

• For knockdown: Use C9orf16 shRNA lentiviral particles (similar to Santa Cruz sc-92859-V mentioned for other procedures)

• For overexpression: Use C9orf16 lentiviral activation particles (similar to Santa Cruz sc-413133-LAC used in related studies)

• Infection protocol: Infect target cells with lentivirus for 48 hours

• Selection: Treat with puromycin to select successfully modified cells

• Validation: Confirm knockdown or activation efficiency via real-time PCR or western blotting

• Functional analysis: Assess effects on cell proliferation (MTT assay), invasion, or chemotherapy resistance

This approach allows for direct assessment of C9orf16's functional role in cancer cell biology.

What methods can be used to study C9orf16's role in chemotherapy resistance?

Researchers investigating C9orf16's role in chemotherapy resistance should consider these approaches:

• Generate stable C9orf16 knockdown and overexpression cell lines

• Treat cells with various chemotherapeutic agents at different concentrations

• Assess cell viability using MTT assays (as described in PDAC studies: plate 1.0 × 10^4 cells/well in 96-well plates with eight replicates per condition)

• Measure apoptosis markers through flow cytometry or western blotting

• Analyze drug efflux mechanisms to determine if C9orf16 affects drug transport

• Investigate downstream molecular pathways, particularly the MYC signaling pathway

These methods have been successfully employed in studying C9orf16's functions in PDAC and can be adapted for other cancer types.

How does C9orf16 expression profile differ between primary and metastatic PDAC?

Single-cell RNA sequencing analysis has revealed a distinct expression pattern for C9orf16 across PDAC progression:

• Normal epithelial cells: C9orf16 is rarely detectable

• Primary PDAC cells: Significant upregulation of C9orf16 expression

• Metastatic PDAC cells: Further elevated expression compared to primary tumors

This progressive increase in expression suggests that C9orf16 may be actively involved in metastatic processes. Researchers can use validated C9orf16 antibodies to further characterize this expression gradient through immunohistochemistry or immunofluorescence on patient-derived samples representing different disease stages.

What is C9orf16's prognostic value in colorectal cancer?

C9orf16 has demonstrated significant prognostic value in colorectal cancer:

This indicates C9orf16 antibodies may have potential application in risk stratification for colorectal cancer patients, extending their utility beyond PDAC research.

How can C9orf16 be integrated into multi-marker cancer detection panels?

Researchers developing multi-marker panels should consider:

• Combining C9orf16 with established biomarkers for the specific cancer type

• Using multiplexed immunofluorescence to simultaneously detect C9orf16 and other markers

• Developing sequential staining protocols if antibody species conflicts exist

• Validating the panel in tissue microarrays containing samples from multiple patients

• Employing machine learning algorithms to analyze complex expression patterns

Since C9orf16 shows specificity for tumor cells in both PDAC and colorectal cancer, it could enhance the sensitivity and specificity of diagnostic panels when combined with other markers .

What are common pitfalls when interpreting C9orf16 immunohistochemistry results?

Researchers should be aware of these potential challenges:

• Field effect masking: The molecular distinction between tumor-adjacent normal tissue and truly healthy tissue can mask important tumor-specific features

• Non-specific binding: Inadequately validated antibodies may recognize proteins other than C9orf16

• Heterogeneous expression: C9orf16 expression may vary across different regions of the same tumor

• Technical variability: Differences in tissue processing, antigen retrieval, and staining protocols can affect results

• Cut-off determination: Establishing meaningful thresholds for "high" versus "low" expression

To address these challenges, researchers should use properly validated antibodies, include appropriate controls, and compare results with truly healthy tissues rather than just tumor-adjacent samples.

How can transcriptomic data be integrated with antibody-based C9orf16 detection?

Integrating transcriptomic and protein-level data provides more robust findings:

• Compare RNA-seq expression data with immunohistochemistry results from the same samples

• Use scRNA-seq to identify cell populations with high C9orf16 expression for targeted antibody validation

• Employ immunofluorescence to confirm cellular localization of the protein predicted by transcriptomic analysis

• Validate transcriptome-derived hypotheses about C9orf16 function through antibody-based functional studies

• Consider field effect when interpreting results, as demonstrated in colorectal cancer studies

This integrated approach leverages the strengths of both methodologies while compensating for their respective limitations.

What emerging technologies might enhance C9orf16 antibody applications?

Researchers should consider incorporating these advanced approaches:

• Proximity ligation assays to study C9orf16 protein-protein interactions, particularly with MYC pathway components

• Mass spectrometry-based validation to complement antibody-based detection methods

• Live-cell imaging with fluorescently tagged antibody fragments to study dynamic C9orf16 behaviors

• Tissue clearing techniques combined with immunofluorescence for 3D visualization of C9orf16 distribution

• Antibody engineering to develop recombinant antibodies with enhanced specificity and reproducibility, following protocols similar to those used for other targets

These technologies could overcome current limitations and provide deeper insights into C9orf16 biology and pathological roles.