Recombinant Human Coiled-coil domain-containing protein 107 (CCDC107)

What is CCDC107 and what cellular functions does it perform?

CCDC107 (Coiled-coil domain-containing protein 107) is a protein involved in cellular processes related to membrane trafficking and ion channel regulation. It contains coiled-coil domains, which are structural motifs commonly involved in protein-protein interactions. Though relatively underexplored, CCDC107 plays roles in calcium signaling, vesicular transport, and membrane stabilization . Current research suggests it maintains cellular homeostasis through these mechanisms, though the complete characterization of its function remains ongoing.

To study CCDC107 function, researchers typically employ knockdown or knockout approaches followed by phenotypic analysis focusing on membrane dynamics, calcium flux measurements, and vesicular transport assays. Immunofluorescence and co-immunoprecipitation techniques are valuable for determining subcellular localization and identifying interaction partners.

How is CCDC107 gene expression regulated?

The regulation of CCDC107 expression involves complex mechanisms that remain partially characterized. Evidence indicates tissue-specific expression patterns with notable dysregulation in disease states, particularly in colorectal cancer where it shows significant downregulation compared to normal tissues . RT-qPCR analysis of 72 colorectal cancer cases demonstrated that CCDC107 downregulation correlates with poor disease-free survival, fraction genome alteration, and surgical margin status .

For researchers investigating CCDC107 regulation, recommended approaches include:

• Promoter analysis using luciferase reporter assays

• Chromatin immunoprecipitation to identify transcription factor binding

• DNA methylation profiling to assess epigenetic regulation

• Analysis of miRNA targeting using 3'UTR reporter constructs

• Evaluation of enhancer elements through chromosome conformation capture techniques

What is the relationship between CCDC107 and the RMRP lncRNA?

Despite their genomic proximity, CCDC107 and RMRP lncRNA display distinct expression patterns in disease contexts. In colorectal cancer studies, CCDC107 shows significant downregulation (p < 0.05), while RMRP expression remains relatively unchanged between cancerous and normal tissues . This differential expression pattern suggests independent regulatory mechanisms despite potential shared genomic regulatory elements.

ROC curve analysis reveals striking differences in their diagnostic potential for colorectal cancer:

These findings indicate CCDC107 has substantial potential as a diagnostic biomarker, while RMRP does not demonstrate similar utility in this context . Researchers investigating this relationship should employ RNA-seq analysis of both coding and non-coding transcripts, followed by functional studies to determine potential regulatory interactions.

What are the optimal approaches for CCDC107 gene knockout studies?

For effective CCDC107 knockout studies, CRISPR-Cas9 gene editing represents the gold standard approach. Specific gRNA sequences designed by Feng Zhang's laboratory at the Broad Institute have been validated for targeting the CCDC107 gene with minimal off-target effects . When designing knockout experiments, researchers should consider using at least two different gRNA constructs to increase success rates and confirm phenotypic findings .

A comprehensive experimental protocol should include:

• Sequence verification of the target region in your specific cell line

• Transfection optimization with both Cas9 and the validated gRNA constructs

• Implementation of appropriate selection markers for edited cell isolation

• Verification of knockout efficiency at both genomic (sequencing) and protein levels

• Thorough phenotypic characterization compared to wildtype controls

• Rescue experiments to confirm specificity of observed phenotypes

For physiologically relevant results, consider using cell types that naturally express CCDC107 at detectable levels, particularly those involved in membrane trafficking processes.

How can CCDC107 expression be accurately quantified in clinical samples?

Precise quantification of CCDC107 expression in clinical samples requires rigorous methodology to ensure reproducible results. Based on successful approaches in colorectal cancer research , implement the following protocol:

• RNA extraction from fresh-frozen or FFPE tissues using specialized kits that preserve RNA integrity

• DNase treatment to eliminate genomic DNA contamination

• Quality control assessment of RNA (RIN > 7 recommended for optimal results)

• cDNA synthesis using high-fidelity reverse transcriptase and consistent priming methods

• Quantitative PCR with validated CCDC107-specific primers and appropriate reference genes

• Data normalization using multiple housekeeping genes verified for stability in the specific tissue context

For comprehensive analysis, supplement qPCR data with protein-level assessment through Western blotting or immunohistochemistry. When designing clinical studies, include matched normal and diseased tissues from the same patients to control for individual variation and demographic factors.

What techniques are recommended for studying CCDC107 protein-protein interactions?

Given CCDC107's coiled-coil domains and likely participation in multiprotein complexes , a multi-technique approach is essential for comprehensive interaction studies:

• Affinity purification coupled with mass spectrometry (AP-MS)

  • Express tagged CCDC107 at near-physiological levels

  • Use crosslinking to capture transient interactions

  • Include appropriate controls (BioGRID database recommendations)

  • Validate hits with reciprocal pulldowns

• Proximity labeling techniques

  • BioID or TurboID fusion with CCDC107

  • APEX2 proximity labeling in relevant cellular compartments

  • Analyze labeled proteins by mass spectrometry

  • Compare results across multiple cell types

• Biophysical interaction validation

  • Surface plasmon resonance (SPR) for kinetic measurements

  • Isothermal titration calorimetry (ITC) for thermodynamic parameters

  • Microscale thermophoresis for interactions in complex solutions

• Live-cell interaction visualization

  • Förster resonance energy transfer (FRET)

  • Bimolecular fluorescence complementation (BiFC)

  • Fluorescence lifetime imaging microscopy (FLIM)

Integration of multiple approaches provides the most reliable characterization of CCDC107's interactome and helps distinguish direct from indirect interactions.

What is the diagnostic potential of CCDC107 in cancer research?

CCDC107 demonstrates significant promise as a diagnostic biomarker, particularly in colorectal cancer where its expression is markedly downregulated in tumor tissues . ROC curve analysis has established an area under the curve (AUC) of 0.871 for CCDC107, indicating excellent discrimination between cancerous and normal tissues . This high diagnostic accuracy, coupled with the association between CCDC107 downregulation and poor disease-free survival, positions it as a valuable biomarker candidate.

For researchers investigating CCDC107 as a cancer biomarker, implement the following comprehensive approach:

• Multi-cohort validation across diverse patient populations

• Correlation with established clinical parameters and molecular subtypes

• Multivariate analysis to determine independent prognostic value

• Longitudinal studies to assess expression changes during disease progression

• Integration with existing biomarker panels to evaluate additive diagnostic value

While CCDC107 expression does not appear to significantly vary between different cancer stages, its consistent downregulation across stages suggests utility throughout the disease course . This pattern makes it particularly valuable for early detection applications.

How can inhibitors of CCDC107 be designed and validated for research purposes?

Development of selective CCDC107 inhibitors requires a structured approach targeting the protein's functional domains :

• Structure-based design process:

  • Computational modeling of CCDC107's coiled-coil domains

  • Identification of potential binding pockets and interaction surfaces

  • Virtual screening of compound libraries

  • Molecular dynamics simulations to assess binding stability

• Inhibitor types and development strategies:

  • Small molecules targeting critical protein interfaces

  • Peptide-based inhibitors mimicking natural binding partners

  • Allosteric modulators affecting protein conformation

  • Proteolysis-targeting chimeras (PROTACs) for targeted degradation

• Comprehensive validation pipeline:

  • Binding affinity assessment (SPR, ITC)

  • Selectivity profiling against related coiled-coil proteins

  • Cellular target engagement verification

  • Functional assays measuring membrane trafficking and ion regulation

• Controls for inhibitor studies:

  • Inactive analogs as negative controls

  • Comparison with genetic knockdown effects

  • Dose-response relationships to establish specificity

  • Verification in multiple cell types

When designing inhibitors, researchers should prioritize compounds that offer selective modulation of CCDC107 with minimal off-target effects to facilitate precise investigation of its cellular functions .

How does CCDC107 contribute to membrane trafficking and ion channel regulation?

CCDC107's role in membrane trafficking and ion channel regulation can be investigated through multiple complementary approaches:

• Membrane trafficking assessment:

  • Fluorescent cargo tracking in live cells

  • Vesicle budding and fusion assays

  • Golgi fragmentation and reassembly kinetics

  • Endocytic and exocytic rate measurements

• Ion channel regulation analysis:

  • Patch-clamp electrophysiology

  • Ion-selective microelectrode recordings

  • Fluorescent ion indicators for real-time monitoring

  • Surface biotinylation to quantify channel expression

• Structure-function relationship studies:

  • Domain deletion/mutation analysis

  • Chimeric protein construction

  • Force spectroscopy for mechanical properties

  • Super-resolution imaging of molecular organization

The experimental approach should include both gain- and loss-of-function studies, with particular attention to calcium signaling pathways given CCDC107's potential involvement in calcium homeostasis . Time-resolved experiments are essential to distinguish direct from indirect effects on these complex cellular processes.

What are the challenges in producing recombinant CCDC107 for structural studies?

Production of recombinant CCDC107 for structural studies presents several technical challenges requiring systematic optimization:

• Expression system selection challenges:

  • Bacterial systems may not provide appropriate post-translational modifications

  • Mammalian systems offer authentic modifications but lower yields

  • Insect cells provide a balance but require specialized equipment

• Protein solubility and stability issues:

  • Coiled-coil domains may require specific buffer conditions

  • Hydrophobic regions can promote aggregation

  • Protease sensitivity may reduce yield

• Purification strategy optimization:

  • Multi-step chromatography typically required

  • Tag selection impacts folding and function

  • Removal of contaminating nucleic acids

• Structural technique selection considerations:

  • X-ray crystallography requires stable crystals

  • NMR suitable for smaller domains only

  • Cryo-EM may require larger complexes for alignment

For researchers approaching this challenge, a recommended workflow includes:

• Bioinformatic analysis to identify stable domains and disorder regions

• Small-scale expression trials with various constructs and conditions

• Solubility enhancement through fusion partners (MBP, SUMO, etc.)

• Verification of folding status before structural analysis

• Consideration of co-expression with stabilizing binding partners

How can researchers address the limitations of computational methods for predicting CCDC107 variant pathogenicity?

The computational prediction of CCDC107 variant pathogenicity faces significant challenges, particularly for noncoding variants, as demonstrated by the underwhelming performance of existing prediction methods . To overcome these limitations:

• Combine multiple computational tools:

  • Use ensemble approaches rather than single predictors

  • Recognize that tools like CADD, DeepSEA, EIGEN, and GWAVA have limitations

  • Consider the specific assumptions underlying each tool

  • Be aware that AUC values can be misleading due to class imbalance

• Experimental validation framework:

  • Create isogenic cell lines with specific variants

  • Perform allele-specific expression analysis

  • Evaluate functional consequences through relevant assays

  • Use massively parallel reporter assays for regulatory variants

• Contextual analysis:

  • Consider variant location relative to known regulatory elements

  • Assess population frequencies across diverse backgrounds

  • Evaluate conservation patterns beyond simple alignment scores

  • Examine clustered variant distributions in regulatory regions

The limitations of computational prediction methods are particularly evident when analyzing variants within the same genomic region, with most tools showing poor discrimination between pathogenic and non-pathogenic variants in close proximity . This highlights the critical importance of experimental validation for CCDC107 variants, especially those in regulatory regions.

What experimental controls are essential for CCDC107 expression studies?

Robust experimental controls are crucial for reliable CCDC107 expression analysis, particularly given its potential as a biomarker :

• Reference gene selection controls:

  • Use multiple reference genes validated for your specific experimental context

  • Verify reference stability across all experimental conditions

  • Apply statistical algorithms to identify optimal normalizers

• Technical controls:

  • No-template controls to detect contamination

  • No-reverse transcriptase controls to assess genomic DNA presence

  • Positive controls with known CCDC107 expression levels

  • Inter-run calibrators for multi-batch experiments

• Biological controls:

  • Matched normal tissue from the same patients

  • Cell lines with verified CCDC107 expression profiles

  • Time-course controls for dynamic expression studies

  • Appropriate disease models reflecting clinical conditions

• Methodology validation:

  • Cross-platform verification (qPCR, digital PCR, RNA-seq)

  • Independent sample processing replicates

  • Blinded analysis where appropriate

  • Statistical power calculations to determine sample sizes

These comprehensive controls ensure that observed changes in CCDC107 expression represent true biological effects rather than technical artifacts, critical for its evaluation as a potential biomarker .

How might CCDC107 research contribute to precision medicine approaches in cancer?

The significant downregulation of CCDC107 in colorectal cancer and its association with poor disease-free survival suggest several promising research directions for precision medicine:

• Diagnostic biomarker development:

  • Integration of CCDC107 assessment into multi-biomarker panels

  • Development of liquid biopsy approaches for non-invasive detection

  • Creation of point-of-care diagnostic tools based on CCDC107 levels

  • Correlation with imaging biomarkers for comprehensive assessment

• Therapeutic targeting strategies:

  • Restoration of CCDC107 expression in deficient tumors

  • Modulation of CCDC107-dependent signaling pathways

  • Synthetic lethality approaches based on CCDC107 status

  • Development of selective inhibitors for mechanistic studies

• Patient stratification applications:

  • Identification of patient subgroups based on CCDC107 expression

  • Correlation with treatment response patterns

  • Integration with other molecular markers for refined classification

  • Longitudinal monitoring during treatment to predict recurrence

The consistently high diagnostic value of CCDC107 (AUC = 0.871) positions it as a strong candidate for clinical implementation, particularly if these findings can be validated across larger and more diverse patient cohorts.

What are promising approaches for deciphering the structure-function relationship of CCDC107?

Understanding the structure-function relationship of CCDC107 requires integrated approaches combining structural biology, functional genomics, and cellular physiology:

• Domain-specific functional characterization:

  • Systematic truncation and mutation analysis

  • Domain-swapping experiments with related proteins

  • Identification of critical residues for protein interactions

  • Correlation of structural features with cellular functions

• Advanced structural biology techniques:

  • Cryo-electron microscopy for full-length protein

  • X-ray crystallography for stable domains

  • Hydrogen-deuterium exchange mass spectrometry for dynamics

  • Integrative structural modeling combining multiple data sources

• In situ structural analysis:

  • Proximity labeling to map molecular neighborhoods

  • Cross-linking mass spectrometry for interaction interfaces

  • Super-resolution microscopy for native organization

  • Single-molecule tracking for dynamic behavior

• Computational approaches:

  • Molecular dynamics simulations of conformational changes

  • Protein-protein docking predictions

  • Co-evolution analysis for interaction surfaces

  • Machine learning integration of structural and functional data

These complementary approaches will provide insights into how CCDC107's coiled-coil domains mediate its roles in membrane trafficking and ion channel regulation , potentially revealing novel therapeutic targets and functional mechanisms.