Recombinant Human Uncharacterized protein C11orf92 (C11orf92)

What is the genomic location and basic structure of C11orf92/COLCA1?

C11orf92/COLCA1 is located on chromosome 11q23.1 (specifically at position 111,293,389-111,305,048 on the complement strand according to NC_000011.10) . The gene structure includes multiple alternative 5' non-coding exons and one constant exon that codes for a 124-amino acid protein . It is a primate-specific gene without homology to other proteins in public databases .

Protein structure analysis predicts:

• A signal peptide

• A transmembrane domain

• O-linked glycosylation sites

The revised gene model shows at least 6 exons, with varying transcripts depending on alternative splicing patterns .

How was C11orf92/COLCA1 initially identified and characterized?

C11orf92 was identified through high-resolution mapping studies of the 11q23 colorectal cancer (CRC) locus. Researchers used microarray-based target selection coupled to next-generation sequencing to interrogate 103,418 bp of DNA at this locus . The region was initially highlighted because the SNP rs3802842 in this region was associated with CRC in a genome-wide association study (GWAS) .

Further characterization involved:

• RNA expression analyses in normal and tumor tissues

• Luciferase reporter assays to assess regulatory potential

• Protein expression studies

• Histochemical examinations

This multi-modal approach revealed that C11orf92, subsequently renamed COLCA1, is heavily glycosylated – a feature common to other granule-associated proteins .

What is known about the expression pattern of C11orf92/COLCA1 in normal and cancer tissues?

COLCA1 exhibits a tissue-specific expression pattern that varies considerably across normal tissues and cancer cell lines:

Normal tissue expression:

• Expressed throughout the gastrointestinal tract (from esophagus to rectum)

• Present in multiple immune organs

• Detected in prostate, testis, and ovary

Cancer cell line expression:

• Almost undetectable in commonly used CRC cell lines like HCT116, RKO, and SW48

• Expressed in only 3 out of 60 cell lines in the NCI-60 panel

• Primarily expressed in well-differentiated CRC cell lines (~4400 fold higher) compared to poorly differentiated lines

This differential expression pattern suggests potential relevance to CRC differentiation status and may explain why some studies have overlooked this gene in CRC research using standard cell lines.

How is C11orf92/COLCA1 transcriptionally regulated?

The transcriptional regulation of COLCA1 involves several key mechanisms:

• FOXA1-mediated regulation: FOXA1 has been identified as a critical transcription factor that enhances COLCA1 transcription in well-differentiated CRC cells. FOXA1 is significantly more abundant (~16 fold, p<0.0001) in well-differentiated lines compared to poorly differentiated ones .

• Genetic variants in the regulatory region: The region contains several SNPs in high linkage disequilibrium with rs3802842, which appear to modulate expression. Notably:

  • rs10891246 (r² = 0.99 with rs3802842) coincides with a splice site resulting in alternative versions of exon 1

  • The higher risk haplotype shows reduced expression levels of COLCA1 in both benign adjacent colonic tissues and tumors

• Shared regulatory elements: COLCA1 and COLCA2 (C11orf93) are arranged on opposite strands and share a regulatory region , creating potential for coordinated expression.

Luciferase reporter assays showed that fragments harboring the lower risk haplotype exhibit higher activity compared to those with the higher risk haplotype, providing experimental evidence for the functional impact of these variants .

What are the recommended protocols for expressing recombinant C11orf92/COLCA1 protein?

Based on successful expression models described in the literature, researchers should consider the following approaches for recombinant COLCA1 expression:

Cell-based expression systems:

• CD34+ hematopoietic progenitor cells: Can be differentiated into CD45+CD34-CD117+CD11c-CD11b- mast cells or CD11b+CD11c+ dendritic cells that express COLCA1

• LAD2 mast cells: Successful expression achieved using GFP-fused COLCA1 cDNA transfection

• TLS-ERG transduced CD34+ TEX cells: Can be stimulated to differentiate into eosinophil-like cells using IL3, IL5, and GM-CSF, resulting in COLCA1 expression

Critical factors for successful expression:

• Post-translational modifications: Given the heavy glycosylation of COLCA1, mammalian expression systems are likely preferred over bacterial systems

• Signal peptide considerations: When designing constructs, researchers should account for the presence of the signal peptide to ensure proper cellular localization

• Fusion tags: GFP fusion has been successfully demonstrated and can assist with tracking protein localization

What methods are most effective for detecting C11orf92/COLCA1 at the RNA and protein levels?

RNA detection methods:

• RT-qPCR: Effective for quantifying expression levels, particularly important given the variable expression across tissues and cell lines

• Northern blotting: Successfully used to confirm the ~1.5kb transcript size in positive cell lines (SW1222 and LS180)

• RNA-seq: Provides comprehensive transcriptome data and has been vital in identifying differential expression patterns

Protein detection methods:

• Western blotting: Useful for detecting the protein and its post-translational modifications

• Subcellular fractionation: COLCA1 is absent in cytosol, nucleus, and cytoskeleton fractions but enriched in membrane protein fractions, suggesting isolation protocols should focus on membrane extracts

• Immunohistochemistry: Can be used to detect protein expression in tissue samples

Recommended controls:

• For well-differentiated CRC studies: SW1222 and LS180 (positive controls)

• For poorly differentiated CRC studies: HCT116, RKO, and SW48 (negative controls)

What is the evidence linking C11orf92/COLCA1 to colorectal cancer risk?

Multiple lines of evidence connect C11orf92/COLCA1 to colorectal cancer risk:

Genetic association studies:

• GWAS findings: The rs3802842 SNP at 11q23 was initially identified in a genome-wide association study and subsequently replicated in case-control studies worldwide

• Meta-analysis results: A meta-analysis of the rs3802842 variant in Chinese populations found:

  • Significant association with CRC risk in allelic model (C vs. A): P=3.00E-04, OR=1.21, 95% CI [1.09, 1.35]

  • Stronger association in recessive model (CC vs. CA+AA): P=2.22E-07, OR=1.39, 95% CI [1.23, 1.57]

  • Significant association in dominant model (CC+CA vs. AA): P=9.00E-03, OR=1.37, 95% CI [1.08, 1.74]

• Expression correlation: Lower risk alleles correlate with increased expression of COLCA1 in both benign adjacent colonic tissues and tumors , suggesting a protective effect of COLCA1 expression

• Functional evidence: Knockdown of COLCA1 in SW1222 cells resulted in increased proliferation, enhanced clonogenic potential, increased colony formation on soft agar, and enhanced tumor growth in mouse xenografts , supporting a tumor suppressor role

These findings collectively suggest that COLCA1 may function as a tumor suppressor, with the higher risk haplotype associated with reduced expression levels.

How do chromatin interactions at the C11orf92/COLCA1 locus contribute to colorectal cancer biology?

Chromatin interaction studies have revealed complex regulatory networks involving the C11orf92/COLCA1 locus:

• Long-range interactions: Capture Hi-C (cHi-C) experiments identified significant interactions between the 11q23 locus and other genomic regions

• Consistent interactions: At 11q23, interactions with a region encoding the uncharacterized protein AB231705 were consistently observed at both 3kb and 9kb resolution

• Validation methods: These interactions were validated using orthogonal approaches:

  • 4C-seq confirmed close-cis interactions

  • Fluorescence in situ hybridization (FISH) verified far-cis (>5 Mb) and trans-interactions

• Functional significance: These chromatin interactions may explain how genetic variants at the 11q23 locus can influence genes beyond the immediate region, potentially affecting multiple pathways relevant to colorectal cancer development

The complex interaction network suggests bi-directional regulation and long-range interactions that could impact the expression of multiple genes involved in CRC pathogenesis, extending our understanding beyond simple single-gene effects.

How can CRISPR/Cas9 be optimized for studying C11orf92/COLCA1 function?

When designing CRISPR/Cas9 experiments to study COLCA1 function, researchers should consider these specialized approaches:

• Knockout strategies:

  • Design guide RNAs targeting the constant coding exon rather than variable non-coding exons

  • Consider the primate-specific nature of the gene when selecting appropriate model systems

  • Validate knockouts at both genomic DNA and protein levels due to potential alternative splicing

• Enhancer deletion:

  • Target the shared regulatory region between COLCA1 and COLCA2

  • Previous studies have successfully deleted risk-associated enhancers to identify genes showing altered expression

  • Consider the potential impact on both genes due to their shared regulatory elements

• Base editing approaches:

  • Design experiments to introduce or correct specific risk-associated SNPs (e.g., rs3802842, rs10891246)

  • Use paired control edits in neutral regions to control for off-target effects

• Model systems:

  • Preferentially use well-differentiated CRC lines that express COLCA1 (SW1222, LS180) rather than common CRC lines that lack expression

  • Consider parallel editing in normal colonic organoids to compare effects in normal versus cancer contexts

What are the challenges in analyzing C11orf92/COLCA1 expression data from patient samples?

Researchers face several methodological challenges when analyzing COLCA1 expression in patient samples:

• Expression heterogeneity:

  • COLCA1 expression varies dramatically between well-differentiated and poorly-differentiated CRC samples

  • Expression correlates with differentiation markers (CEACAM5, CDX1, CDX2, KRT20, VIL1)

  • Analysis requires stratification by tumor differentiation status to avoid misleading results

• Genetic variation impact:

  • Different risk haplotypes significantly affect expression levels

  • Analysis should account for patient genotypes at key SNPs (rs3802842, rs10891246)

  • Careful interpretation is needed when comparing expression across populations with different allele frequencies

• Technical considerations:

  • Alternative splicing produces multiple transcript variants

  • Primer/probe design must account for splice variants

  • Post-translational modifications (heavy glycosylation) can affect protein detection

• Reference selection issues:

  • Many commonly used CRC cell lines (HCT116, RKO, SW48) lack COLCA1 expression

  • Studies using these lines as references may misinterpret patient data

  • Suggested controls: SW1222 and LS180 as positive references; HCT116 as negative

• RNA integrity:

  • Expression analysis in surgical specimens requires rigorous RNA quality control

  • Normalization to housekeeping genes stable in CRC tissue is essential

What is the potential translational significance of C11orf92/COLCA1 research?

The translational potential of COLCA1 research extends to several clinical applications:

• Risk stratification:

  • Genotyping the rs3802842 locus could identify individuals at increased CRC risk

  • Meta-analysis shows significant associations with ORs ranging from 1.21-1.39 depending on genetic model

  • Could be incorporated into polygenic risk scores for improved screening recommendations

• Biomarker development:

  • COLCA1 expression levels correlate inversely with tumor progression

  • Potential utility as a prognostic marker for well-differentiated vs. poorly-differentiated tumors

  • Expression analysis in non-invasive samples (liquid biopsies) could be explored

• Therapeutic implications:

  • COLCA1's apparent tumor suppressor function suggests potential therapeutic avenues

  • Knockdown experiments demonstrate increased proliferation and tumorigenicity

  • Strategies to upregulate or restore COLCA1 function might inhibit tumor growth

• Mechanistic insights:

  • COLCA1 protein localizes to membrane fractions associated with granules and secretory vesicles

  • Co-sediments with proteins associated with eosinophilic granules and secretory vesicles (LAMP2, CD63/LAMP3, VAMP2, VAMP7)

  • Understanding these pathways could reveal novel therapeutic targets beyond COLCA1 itself

• Colorectal cancer subtyping:

  • Expression patterns could contribute to molecular classification systems for CRC

  • May help identify subgroups more likely to respond to specific therapeutic approaches

How should researchers design experiments to investigate C11orf92/COLCA1's role in cellular processes?

When investigating COLCA1's role in cellular processes, consider these methodological recommendations:

• Knockdown and overexpression approaches:

  • Use siRNA knockdown in well-differentiated CRC lines (SW1222, LS180) that express COLCA1

  • Establish stable overexpression systems in poorly-differentiated lines (HCT116, RKO) that lack endogenous expression

  • Compare phenotypic effects between knockdown and overexpression models

• Phenotypic assays:

  • Proliferation assays: Previous research showed increased proliferation upon COLCA1 knockdown

  • Clonogenic assays: Assess colony formation on plastic and in soft agar

  • Migration and invasion assays: Evaluate potential impact on metastatic capabilities

  • Xenograft models: Assess tumorigenicity in vivo as previously demonstrated

• Subcellular localization studies:

  • Fluorescence microscopy with GFP-tagged COLCA1

  • Co-localization studies with markers of:

    • Endoplasmic reticulum

    • Secretory vesicles

    • Eosinophilic granules (LAMP2, CD63/LAMP3, VAMP2, VAMP7)

• Interaction studies:

  • Immunoprecipitation followed by mass spectrometry to identify binding partners

  • Yeast two-hybrid screening to detect protein-protein interactions

  • Proximity labeling approaches (BioID, APEX) to identify proteins in the same subcellular compartment

• Stress response experiments:

  • Given its ER localization, investigate COLCA1's role under ER stress conditions

  • Test response to agents causing ER dysfunction and unfolded protein accumulation

  • Examine relationship to unfolded protein response pathways

What bioinformatics approaches are most informative for analyzing C11orf92/COLCA1 in multi-omics datasets?

Researchers should implement these specialized bioinformatics approaches when analyzing COLCA1 in multi-omics datasets:

• Integrative expression analysis:

  • Combine RNA-seq with proteomics data to account for post-transcriptional regulation

  • Use DESeq2 or edgeR for differential expression, with stratification by tumor differentiation status

  • Example from literature: Expression analyses from 5 different datasets identified 16 genes with differential expression in carcinoma compared to adenoma

• eQTL analysis:

  • Analyze how SNPs (particularly rs3802842 and rs10891246) affect COLCA1 expression

  • Use tools like Matrix eQTL or FastQTL

  • Implement colocalization analysis to determine if the same causal variant affects both gene expression and disease risk

• Chromatin interaction analysis:

  • Analyze Hi-C, Capture Hi-C, or 4C-seq data to identify regions interacting with the COLCA1 locus

  • Use visualization tools like WashU Epigenome Browser or Juicebox

  • Previous studies identified interactions with distant genomic regions that may contribute to gene regulation

• Pathway enrichment:

  • Use GSEA, ReactomeFIViz, or EnrichR to identify pathways affected by COLCA1

  • Consider custom gene sets based on COLCA1 co-expression patterns

  • Focus on ER stress, secretory pathways, and immune-related processes given COLCA1's localization

• Survival analysis:

  • Kaplan-Meier analysis stratified by COLCA1 expression levels

  • Cox proportional hazards models adjusting for clinical covariates

  • Implement competing risk analysis to distinguish effects on cancer-specific survival

• Single-cell analysis approaches:

  • Examine cell type-specific expression patterns in tumor microenvironment

  • Consider trajectory analysis to understand expression changes during differentiation

  • Use tools like Seurat, Scanpy or Monocle for comprehensive scRNA-seq analysis

How do researchers address contradictory findings about C11orf92/COLCA1's role in colorectal cancer?

Several contradictions and knowledge gaps exist in the current understanding of COLCA1's role in colorectal cancer:

• Expression level contradictions:

  • Some studies report decreased expression in tumors

  • Others find expression primarily in well-differentiated tumors but not in poorly-differentiated ones

  • Resolution approach: Stratify analyses by tumor differentiation status and genetic background (rs3802842 genotype)

• Functional role discrepancies:

  • Evidence suggests a tumor suppressor role (knockdown increases proliferation)

  • Yet risk variants that decrease expression are only moderately associated with CRC (ORs 1.2-1.4)

  • Methodological approach: Conduct parallel studies in multiple cell lines with different differentiation states

• Causality questions:

  • Unclear if altered COLCA1 expression is a cause or consequence of CRC development

  • Experimental strategy: Use inducible expression systems to assess temporal effects during tumor progression

• Mechanistic uncertainties:

  • Despite subcellular localization data, the biochemical function remains unknown

  • Research approach: Perform comprehensive protein domain analyses, structure prediction, and evolutionary studies to generate functional hypotheses

• Cell type specificity:

  • Expression in immune organs suggests potential roles beyond epithelial cells

  • Investigation strategy: Use single-cell RNA-seq to profile expression across cell types in the tumor microenvironment

When addressing these contradictions, researchers should:

• Clearly state methodological details (cell lines, antibodies, primers)

• Report genetic background (rs3802842 status) of experimental models

• Consider both cell-intrinsic and microenvironment effects

• Use multiple complementary approaches to validate findings

What are the current limitations and future research priorities for C11orf92/COLCA1 studies?

Key limitations and research priorities include:

• Structural characterization gaps:

  • No crystal structure or detailed protein domain analysis available

  • Priority: Structure determination through X-ray crystallography or cryo-EM

  • Challenge: Heavy glycosylation may complicate structural studies

• Functional mechanism uncertainty:

  • Biochemical function remains unknown despite localization data

  • Priority: Comprehensive protein-protein interaction studies and functional screens

  • Approach: BioID proximity labeling coupled with mass spectrometry

• Model system limitations:

  • Primate-specific gene limits use of common mouse models

  • Priority: Develop humanized mouse models or alternative systems (organoids)

  • Innovation needed: CRISPR knock-in of human COLCA1 into mouse models

• Therapeutic targeting challenges:

  • Unclear how to modulate COLCA1 function therapeutically

  • Priority: High-throughput screens for compounds that increase COLCA1 expression

  • Approach: Screen epigenetic modulators that might activate expression

• Population diversity gaps:

  • Most studies focused on European or East Asian populations

  • Priority: Multi-ethnic studies to assess risk variant frequencies and effects

  • Challenge: Assembling diverse patient cohorts with appropriate controls

• Clinical translation barriers:

  • Prognostic/predictive value not yet established

  • Priority: Retrospective and prospective studies correlating COLCA1 status with outcomes

  • Approach: Include COLCA1 assessment in existing clinical trial biospecimen analyses

The field would benefit from coordinated consortium efforts to address these priorities through standardized methodologies and open data sharing.