Recombinant Pongo abelii Integral membrane protein 2C (ITM2C)

Basic Research Questions

• What is Recombinant Pongo abelii Integral Membrane Protein 2C (ITM2C)?

  Recombinant Pongo abelii Integral Membrane Protein 2C (ITM2C) is a full-length protein (267 amino acids) derived from the Sumatran orangutan (Pongo abelii) with UniProt ID Q5NVC3. It belongs to the integral membrane protein family and is typically expressed with tags (such as His-tag) to facilitate purification and detection in experimental settings. The protein is also known by the synonyms "Integral membrane protein 2C" and can be cleaved into CT-BRI3. ITM2C has been implicated in various biological processes, particularly in relation to immune responses and cancer biology .

• How is Recombinant Pongo abelii ITM2C typically produced for research applications?

  Recombinant Pongo abelii ITM2C is typically produced using bacterial expression systems, most commonly E. coli. The full-length protein (amino acids 1-267) is expressed with an N-terminal His-tag to facilitate purification through affinity chromatography. The expression construct contains the complete coding sequence, and after induction and expression, the protein is purified to ≥90% purity as determined by SDS-PAGE. The purified protein is then lyophilized for stability and long-term storage. Researchers should verify protein quality through SDS-PAGE analysis before experimental use .

• What are the optimal storage conditions for maintaining the stability of Recombinant Pongo abelii ITM2C?

  For optimal stability, Recombinant Pongo abelii ITM2C should be stored as follows:

  Storage Parameter	Recommendation
  Long-term storage	-20°C to -80°C
  Working aliquots	4°C for up to one week
  Storage buffer	Tris/PBS-based buffer, pH 8.0, with 6% Trehalose or Tris-based buffer with 50% glycerol
  Important precautions	Avoid repeated freeze-thaw cycles

  Upon receipt, it is recommended to briefly centrifuge the vial before opening to bring contents to the bottom. For extended storage periods, aliquoting is necessary to minimize freeze-thaw cycles that can degrade the protein .

• What is the recommended reconstitution protocol for Recombinant Pongo abelii ITM2C?

  The recommended reconstitution protocol for lyophilized Recombinant Pongo abelii ITM2C is:

  1. Briefly centrifuge the vial prior to opening to collect the powder at the bottom

  2. Reconstitute in deionized sterile water to a concentration of 0.1-1.0 mg/mL

  3. Add glycerol to a final concentration of 5-50% (the standard recommendation is 50%)

  4. Prepare working aliquots for long-term storage at -20°C/-80°C

  This protocol maintains protein stability while preventing aggregation and denaturation. The addition of glycerol helps prevent freeze damage during storage .

Advanced Research Questions

• How does ITM2C function as a tumor suppressor gene and what signaling pathways does it influence?

  ITM2C has been identified as a potential tumor suppressor, particularly in breast cancer. Research has demonstrated that high expression of ITM2A (a related family member) reduces the aggressiveness of breast cancer cells and correlates with favorable patient outcomes. RNA-sequencing of breast cancer cells overexpressing ITM2A revealed that it is associated with immunity responses, suggesting similar functions may exist for ITM2C. The protein appears to modulate multiple cellular pathways:

  1. Upregulation of immune checkpoint molecules (PD-L1, PD-L2, and B7-H3)

  2. Correlation with tumor-infiltrating lymphocytes (TILs)

  3. Potential involvement in mTOR activity and glycolytic metabolism

  These functions collectively suggest that ITM2C plays a role in tumor immune microenvironment regulation, which may explain its tumor suppressive properties in certain contexts .

• What is the relationship between ITM2C expression and tumor immunology markers?

  ITM2C expression shows significant correlations with several important immunological markers in cancer:

  Immune Marker	Correlation with ITM2C	Cancer Types
  PD-L1	Positive correlation	Luminal and basal breast cancer subtypes
  PD-L2	Upregulated upon ITM2C overexpression	Breast cancer cell lines
  B7-H3	Upregulated upon ITM2C overexpression	Breast cancer cell lines
  CD8+ T cells	Positive correlation (intermediate to high)	All breast cancer subtypes

  The positive correlation between ITM2C and CD8+ T cells has also been observed in multiple other cancer types, including lung adenocarcinoma, lung squamous cell carcinoma, colon adenocarcinoma, head and neck cancer, and prostate adenocarcinoma. This suggests a conserved role for ITM2C in regulating tumor immune responses across various cancer types .

• What experimental approaches are recommended for studying ITM2C function in cancer cells?

  Based on established research methodologies, the following experimental approaches are recommended for studying ITM2C function in cancer:

  1. Gene Expression Manipulation:

     • Plasmid-based overexpression in cell lines (e.g., MCF-7 and MDA-MB-231)

     • siRNA or CRISPR-based knockdown/knockout strategies

  2. Functional Assays:

     • Proliferation assays to assess impact on cancer cell growth

     • Migration and invasion assays to evaluate effects on metastatic potential

     • Flow cytometry to measure expression of immune checkpoint molecules

  3. Molecular Analyses:

     • RNA-sequencing to identify differentially expressed genes

     • qRT-PCR for validation of expression changes

     • GO and KEGG pathway enrichment analyses

  4. Clinical Correlation Studies:

     • Analysis of patient samples using TIMER database

     • Examination of correlation with TILs and immune checkpoint molecules

     • Survival analysis to assess prognostic value

  These methodologies have been successfully employed to elucidate ITM2C function and can be adapted to specific research questions .

• How can ITM2C be incorporated into biomarker panels for colorectal cancer detection?

  ITM2C has been identified as a potential biomarker for colorectal cancer (CRC) when used in combination with other genes. Research has shown that a gene signature including CA2, CA7, and ITM2C demonstrates significant diagnostic and prognostic value in CRC:

  Gene	AUC Value	Function
  CA2	99.24%	Carbonic anhydrase
  CA7	100%	Carbonic anhydrase
  ITM2C	99.5%	Integral membrane protein

  Correlation analysis revealed strong positive correlations between these genes in CRC datasets:

  • CA7-CA2 correlation: 0.8

  • CA7-ITM2C correlation: 0.72-0.73

  • CA2-ITM2C correlation: 0.79-0.88

  This gene signature showed significant prognostic value with a logrank p-value of 0.044. For optimal implementation as a biomarker panel, researchers should employ machine learning-based classification models (particularly Random Forest) for validation across multiple datasets .

• What are the methodological challenges in studying ITM2C's immunomodulatory effects?

  Several methodological challenges must be addressed when investigating ITM2C's immunomodulatory effects:

  1. Correlation vs. Causation:

     • While correlations between ITM2C expression and immune markers have been established, the direct mechanisms remain unclear

     • Further research is needed to determine whether ITM2C directly regulates PD-L1 expression or if the correlation is secondary to other factors

  2. Database Limitations:

     • Correlations between ITM2C expression and TILs have been established based on single databases without extensive verification

     • Validation across multiple independent datasets is necessary

  3. Mechanistic Understanding:

     • The molecular mechanism by which ITM2C overexpression upregulates immune checkpoint molecules (PD-L1, PD-L2, B7-H3) remains to be elucidated

     • Pathway analysis and protein interaction studies are needed

  4. Clinical Translation:

     • Further research is required to determine the predictive value of ITM2C expression for response to immune checkpoint blockade therapies

     • Prospective clinical trials incorporating ITM2C assessment are needed

  Addressing these challenges requires integrated approaches combining in vitro functional studies, in vivo models, and extensive clinical sample analyses .

• How does ITM2C expression correlate with tumor-infiltrating lymphocytes across different cancer types?

  ITM2C expression shows consistent patterns of correlation with tumor-infiltrating lymphocytes (TILs) across multiple cancer types:

  Cancer Type	Correlation with CD8+ T cells	Other Notable Correlations
  Breast cancer (all subtypes)	Positive (intermediate to high)	Varies by immune cell type
  Breast cancer (basal)	Strong positive	Variable with other TILs
  Breast cancer (HER2+)	Positive	Variable with other TILs
  Breast cancer (luminal)	Positive	Variable with other TILs
  Lung adenocarcinoma	Positive	Variable by immune cell type
  Lung squamous cell carcinoma	Positive	Variable by immune cell type
  Colon adenocarcinoma	Positive	Variable by immune cell type
  Head and neck cancer	Positive	Variable by immune cell type
  Prostate adenocarcinoma	Positive	Variable by immune cell type

  The most consistent finding across cancer types is the positive correlation between ITM2C expression and CD8+ T cell infiltration. This suggests a conserved role for ITM2C in regulating cytotoxic T cell responses in the tumor microenvironment. The correlation patterns with other immune cell types (B cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells) vary by cancer type and subtype .

• What are the recommended protocols for analyzing ITM2C expression in tumor samples?

  For comprehensive analysis of ITM2C expression in tumor samples, the following protocols are recommended:

  1. RNA Expression Analysis:

     • qRT-PCR using validated primers specific to ITM2C

     • RNA-sequencing for genome-wide expression analysis

     • Normalization to established housekeeping genes

  2. Database Analysis:

     • TIMER database for correlations with TILs (http://cistrome.shinyapps.io/timer/)

     • TISIDB web portal for tumor-immune system interactions (http://cis.hku.hk/TISIDB/)

     • GEPIA server for survival analysis

     • GEO and TCGA databases for expression data across cancer types

  3. Protein Expression Analysis:

     • Immunohistochemistry on tumor tissue sections

     • Flow cytometry for cell line studies

     • Western blotting for quantitative protein analysis

  4. Correlation Analysis:

     • Multiple statistical methods to assess correlations with immune markers

     • Machine learning approaches (e.g., Random Forest) for diagnostic model development

     • ROC curve analysis to determine diagnostic efficiency

  These methodologies should be applied in an integrated manner for comprehensive characterization of ITM2C's role in cancer biology and immunology .