Recombinant Human Coiled-coil domain-containing protein 109B (CCDC109B)

What is the basic structure and function of CCDC109B?

CCDC109B is an evolutionarily conserved protein that possesses two coiled-coil domains and two transmembrane domains . Functionally, it acts as a negative subunit of the mitochondrial calcium uniporter (MCU) channel, regulating the efficiency of mitochondrial calcium (Ca²⁺) intake. The MCU/MCUb ratio varies in different tissues, providing a molecular mechanism to mediate calcium homeostasis . CCDC109B's role in calcium regulation impacts multiple cellular signaling cascades that control cell growth and invasion processes .

Experimentally, researchers can visualize CCDC109B's subcellular localization using immunofluorescence techniques with anti-CCDC109B antibodies (1:100 dilution), followed by secondary antibody staining with Alexa Fluor 594 goat anti-rabbit IgG (1:800 dilution) . This reveals a predominantly cytoplasmic localization pattern consistent with its mitochondrial function.

How does CCDC109B expression differ between normal and cancerous tissues?

CCDC109B shows differential expression between normal tissue and cancer samples. In glioma studies, immunofluorescence staining revealed increased expression of CCDC109B protein in glioma cell lines (U87MG, U251, and T98) compared to normal human astrocytes (NHA) . This observation was confirmed by western blot analysis showing elevated CCDC109B protein levels in glioma cell lines relative to NHA .

Analysis of multiple databases (Rembrandt, TCGA, and Chinese Glioma Genome Atlas) demonstrated significantly higher mRNA levels of CCDC109B in high-grade gliomas (HGG; WHO III-IV) compared to low-grade gliomas (LGG; WHO I-II) and normal brain tissues (p < 0.001) . Protein expression analysis through immunohistochemistry confirmed these findings, with high CCDC109B expression (scores ≥3) in 59.2% of HGG (29/49) compared to only 10.5% of LGG (2/19) and virtually no expression in normal brain tissue samples .

What molecular methods are used to detect and quantify CCDC109B expression?

Multiple complementary techniques can be employed to measure CCDC109B expression:

• Western Blot Analysis: Proteins are extracted using RIPA buffer containing protease inhibitors, separated by 10% polyacrylamide gel electrophoresis, and transferred to PVDF membranes. Anti-CCDC109B antibody (1:500 dilution) is used for detection, followed by HRP-conjugated secondary antibody (1:5000) .

• Immunohistochemistry (IHC): Tissue samples are processed and stained with anti-CCDC109B antibodies to visualize protein expression in different tissue types and to perform semi-quantitative analysis .

• Immunofluorescence: Cells are fixed with 4% paraformaldehyde, permeabilized with 0.5% Triton X-100, and stained with anti-CCDC109B antibody (1:100) and fluorescent secondary antibodies to visualize subcellular localization .

• qRT-PCR: RNA extraction followed by reverse transcription and real-time PCR can be used to quantify mRNA levels of CCDC109B .

• Database Mining: Analysis of public databases like TCGA, Rembrandt, and CGGA provides large-scale mRNA expression data across different tumor grades and molecular subtypes .

How does CCDC109B affect cancer cell proliferation and what methods can measure this impact?

CCDC109B significantly influences cancer cell proliferation, as demonstrated in glioma models. Knockdown studies have shown that reducing CCDC109B expression inhibits cancer cell growth.

Methodological approach:

• EdU Incorporation Assay: Following CCDC109B knockdown in U87MG and U251 glioma cell lines, EdU assays revealed significant decreases in the percentage of EdU-positive cells (p < 0.05), indicating reduced cell proliferation .

• Colony Formation Assay: CCDC109B knockdown significantly reduced colony-forming ability in both U87MG and U251 cells (p < 0.05) .

• In vivo tumor growth: Orthotopic xenograft models using U87MG cells with stable CCDC109B knockdown showed decreased tumor volume compared to control tumors .

• Proliferation marker analysis: IHC staining for Ki-67 in tumor xenografts revealed lower expression levels in CCDC109B-knockdown tumors compared to controls (p < 0.01) .

These complementary approaches provide strong evidence that CCDC109B positively regulates cancer cell proliferation, making it a potential therapeutic target.

What is the relationship between CCDC109B expression and patient prognosis?

CCDC109B expression has significant prognostic value in glioma patients. Analysis of multiple databases revealed:

Researchers can leverage this prognostic information by including CCDC109B expression analysis in their patient stratification approaches for clinical studies.

How does CCDC109B influence cancer cell migration and invasion?

CCDC109B plays a critical role in regulating cancer cell migration and invasion capabilities. Experimental evidence includes:

• Transwell migration and invasion assays: Knockdown of CCDC109B significantly reduced the number of U87MG and U251 cells that migrated or invaded through the membrane after 24 hours of incubation (p < 0.05) .

• Molecular mechanism analysis: Western blot analysis revealed that CCDC109B knockdown reduced expression of MMP2 and MMP9, two key metalloproteinases involved in tumor invasion and migration .

• In vivo invasion assessment: IHC staining for invasion markers MMP2 and MMP9 in xenograft tissues showed lower expression in CCDC109B-knockdown tumors compared to controls (p < 0.01) .

• Molecular subtype correlation: Higher CCDC109B expression was significantly associated with the mesenchymal molecular subtype of glioma (p < 0.001), which is characteristically more invasive .

These findings suggest that targeting CCDC109B could potentially reduce tumor invasiveness, representing a promising therapeutic approach.

How is CCDC109B expression regulated under hypoxic conditions?

CCDC109B expression is significantly influenced by hypoxia, a common feature of the tumor microenvironment. Research has identified HIF1α as a key transcriptional regulator of CCDC109B:

• Spatial pattern observation: Immunohistochemistry staining of primary glioma samples revealed elevated CCDC109B expression specifically in necrotic areas, which are typically hypoxic .

• Hypoxia-induced expression: CCDC109B expression is drastically upregulated under hypoxic conditions in glioma cell models .

• HIF1α dependency: siRNA-mediated knockdown and specific inhibitors of HIF1α led to decreased expression of CCDC109B both in vitro and in vivo, establishing HIF1α as a potential transcriptional regulator .

• Functional relevance: Knockdown of CCDC109B inhibited hypoxia-induced migration and invasion of glioma cells, suggesting CCDC109B is a critical factor in mediating HIF1α-induced glioma cell migration and invasion .

This regulatory mechanism links CCDC109B to the hypoxic adaptation of cancer cells, providing insight into its role in tumor progression and potential therapeutic vulnerability.

What is the relationship between CCDC109B and treatment resistance in cancer?

Evidence suggests CCDC109B may play a role in treatment resistance, particularly in the context of glioma therapy:

• Temozolomide resistance: Gene profiling analysis has revealed increased CCDC109B as a potential factor contributing to or associated with temozolomide (TMZ) resistance in malignant gliomas .

• Molecular pathway involvement: As CCDC109B regulates mitochondrial calcium homeostasis, it may influence cellular stress responses and apoptotic pathways that are critical for drug sensitivity.

• Survival correlation: The association between high CCDC109B expression and poor patient survival may partially reflect its role in treatment resistance.

Researchers investigating drug resistance mechanisms should consider evaluating CCDC109B expression in their resistance models and potentially targeting this protein to overcome treatment resistance.

What experimental approaches can be used to study CCDC109B function in calcium regulation?

Given CCDC109B's role as a negative regulator of mitochondrial calcium uniporter (MCU), several specialized techniques can be employed to study its function:

• Mitochondrial calcium imaging: Using calcium-sensitive fluorescent dyes (e.g., Rhod-2 AM) or genetically encoded calcium indicators targeted to mitochondria to measure mitochondrial calcium levels in cells with varying CCDC109B expression.

• Patch-clamp electrophysiology: Direct measurement of mitochondrial calcium currents in mitoplasts (isolated mitochondrial inner membrane) to assess how CCDC109B alters MCU channel properties.

• Protein-protein interaction studies: Co-immunoprecipitation, proximity ligation assays, or FRET analysis to examine CCDC109B interaction with MCU and other calcium uniporter complex components.

• Reconstitution studies: Purified recombinant CCDC109B can be incorporated into liposomes or planar lipid bilayers to directly assess its impact on calcium transport.

• Mitochondrial function assays: Oxygen consumption rate (OCR) measurements to determine how CCDC109B-mediated changes in calcium homeostasis affect mitochondrial bioenergetics.

These approaches provide complementary insights into CCDC109B's functional role in calcium regulation and its downstream effects on cellular physiology.

What are the most effective methods for manipulating CCDC109B expression in research models?

Several approaches have proven effective for modulating CCDC109B expression in experimental settings:

• RNA interference (RNAi):

  • siRNA transfection: Transient knockdown using targeted siRNAs (demonstrated effectiveness in glioma cell lines)

  • shRNA lentiviral constructs: For stable long-term knockdown (e.g., sh-CCDC109B-1 achieved nearly complete protein knockdown in U87MG and U251 cells)

• CRISPR-Cas9 genome editing:

  • Complete gene knockout

  • Targeted mutation of specific domains to study structure-function relationships

• Overexpression systems:

  • Plasmid-based transient expression

  • Viral vector-mediated stable expression

  • Inducible expression systems for temporal control

• In vivo models:

  • Orthotopic xenograft models with CCDC109B-modified cells demonstrated significant effects on tumor growth and mouse survival (p < 0.05)

  • Genetically engineered mouse models for tissue-specific modulation

Each approach has specific advantages depending on the research question, with combinations often providing the most comprehensive insights.

How can researchers integrate CCDC109B analysis into multiomics cancer studies?

CCDC109B can be effectively incorporated into comprehensive multiomics cancer research through several approaches:

• Transcriptomics integration:

  • RNA-seq analysis to correlate CCDC109B expression with global gene expression patterns

  • Analysis across molecular subtypes (e.g., CCDC109B shows highest expression in mesenchymal glioma subtype)

• Proteomics approaches:

  • Protein-protein interaction networks to identify CCDC109B binding partners

  • Phosphoproteomics to detect post-translational modifications affecting CCDC109B function

  • Proteome-wide changes following CCDC109B manipulation

• Metabolomics correlation:

  • Analysis of metabolic changes associated with CCDC109B-mediated calcium regulation

  • Integration with mitochondrial function data

• Clinical data integration:

  • Correlation with patient outcomes across different cancer types

  • Treatment response prediction models incorporating CCDC109B expression

  • Multi-variable analysis combining CCDC109B with other prognostic markers

• Single-cell analysis:

  • Examination of CCDC109B expression heterogeneity within tumors

  • Correlation with cell states and differentiation trajectories

This integrated approach allows researchers to position CCDC109B within broader molecular landscapes and signaling networks in cancer.

What are the challenges in developing therapeutic strategies targeting CCDC109B?

Developing therapeutic approaches targeting CCDC109B presents several specific challenges:

• Target specificity:

  • High homology with MCU may complicate selective targeting

  • Need for approaches that specifically modulate CCDC109B without affecting other calcium transport mechanisms

• Delivery challenges:

  • For brain tumors, blood-brain barrier penetration remains a significant obstacle

  • Need for targeted delivery systems for RNA-based therapeutics

• Functional redundancy:

  • Potential compensatory mechanisms in calcium regulation pathways

  • Requirement for combination approaches targeting multiple nodes

• Biomarker development:

  • Need for standardized assays to quantify CCDC109B expression for patient stratification

  • Identification of patient populations most likely to benefit from CCDC109B-targeted therapy

• Safety considerations:

  • Understanding the impact of CCDC109B inhibition on normal tissues

  • Calcium homeostasis disruption could have off-target effects in cardiac and neural tissues

Future research should address these challenges through development of highly specific inhibitors, advanced delivery technologies, and careful patient selection strategies based on comprehensive biomarker profiles.

What control experiments should be included when studying CCDC109B function?

Robust experimental design for CCDC109B research requires comprehensive controls:

• Expression manipulation controls:

  • Multiple shRNA/siRNA sequences targeting different regions of CCDC109B (as demonstrated with sh-CCDC109B-1, sh-CCDC109B-2, and sh-CCDC109B-3)

  • Non-targeting control sequences with similar chemical properties

  • Rescue experiments with shRNA-resistant CCDC109B constructs

• Cell model controls:

  • Multiple cell lines to ensure findings are not cell-type specific (e.g., U87MG and U251)

  • Comparison with normal cell counterparts (e.g., NHA for glioma studies)

  • Isogenic cell lines differing only in CCDC109B status

• Experimental validation controls:

  • Positive and negative controls for all assay systems

  • Time-course experiments to capture dynamic effects

  • Dose-response studies for pharmacological interventions

• In vivo controls:

  • Appropriate sham or vehicle-treated animals

  • Contralateral control injections in brain tumor models

  • Randomization and blinding procedures for animal studies

• Technical controls:

  • Multiple housekeeping genes/proteins for normalization

  • Antibody validation using knockout/knockdown samples

  • Inter-assay calibrators for longitudinal studies

These controls help distinguish specific CCDC109B effects from experimental artifacts and establish causality rather than mere correlation.

How can contradictory findings on CCDC109B function be reconciled?

Resolving contradictory findings in CCDC109B research requires systematic analysis:

• Context-dependent function analysis:

  • Tissue-specific effects (e.g., CCDC109B's prognostic value varies between databases for GBM)

  • Microenvironmental factors (e.g., hypoxia significantly alters CCDC109B function)

  • Baseline expression levels affecting outcomes of manipulation

• Methodological comparison:

  • Different knockdown/knockout approaches may have varying efficiencies

  • Transient vs. stable manipulation giving different adaptations

  • In vitro vs. in vivo models showing distinct phenomena

• Integrated analysis approaches:

  • Meta-analysis across multiple datasets

  • Subgroup analysis based on molecular features

  • Multivariable modeling to account for confounding factors

• Molecular mechanism delineation:

  • Detailed pathway analysis to identify context-specific interactors

  • Post-translational modification profiling

  • Subcellular localization studies in different conditions

• Replication studies:

  • Independent verification with standardized protocols

  • Cross-validation in different model systems

  • Collaborative research initiatives with shared resources

By systematically addressing these aspects, researchers can develop more nuanced models of CCDC109B function that accommodate seemingly contradictory observations.