BCAP31 Antibody Pair

Basic Research Questions

• What is BCAP31 and why is it significant in cancer research?

  BCAP31 (B-cell receptor-associated protein 31, also known as BAP31) is a 28 kDa polytopic integral protein primarily located in the endoplasmic reticulum (ER) and ER-mitochondria associated membranes . It plays crucial roles in multiple cellular processes including:

  • Anterograde transport of membrane proteins from the endoplasmic reticulum to the Golgi apparatus

  • Regulation of caspase 8-mediated apoptosis

  • T-cell activation through TCR signal pathways

  • Cancer cell migration, invasion, and proliferation mechanisms

  Recent pan-cancer analysis has identified BCAP31 as significantly overexpressed in several prevalent malignancies, with high expression associated with poor prognosis, making it a valuable biomarker for cancer progression and immunotherapy response .

• How do BCAP31 antibody pairs function in research applications?

  BCAP31 antibody pairs consist of complementary antibodies designed for specific and sensitive detection of BCAP31 protein:

  • Capture antibody: Typically a mouse monoclonal anti-BCAP31 (100 μg) that binds to BCAP31 with high specificity

  • Detection antibody: Often a rabbit purified polyclonal anti-BCAP31 (50 μg) that recognizes a different epitope

  In sandwich ELISA applications, the capture antibody immobilizes BCAP31 protein from samples, while the detection antibody enables visualization and quantification. This paired system allows detection sensitivity ranging from approximately 729× to 3× dilution of BCAP31 293T overexpression lysates (non-denatured) , providing researchers with reliable tools for analyzing BCAP31 expression levels across experimental conditions.

• What are recommended protocols for BCAP31 antibody pair storage and handling?

  For optimal performance and longevity of BCAP31 antibody pairs:

  • Store reagents at -20°C or lower (some recombinant formats may require -80°C storage)

  • Aliquot antibodies to avoid repeated freeze-thaw cycles which can degrade antibody quality

  • Return reagents to recommended storage temperature immediately after use

  • For conjugation-ready formats, maintain in PBS-only buffer without BSA or sodium azide until conjugation

  Commercial antibody pairs typically contain sufficient reagents for 3-5 × 96-well plates using recommended protocols , making them cost-effective for multiple experimental runs.

Advanced Research Questions

• How can BCAP31 antibody pairs be optimized for studying cancer progression and metastasis?

  When investigating BCAP31's role in cancer progression:

  Methodological approach:

  • Pair BCAP31 detection with markers of epithelial-mesenchymal transition (EMT) to assess correlation with metastatic potential

  • Combine with fluorescent visualization of cytoskeletal proteins like F-actin, as BCAP31 may influence their distribution rather than expression levels

  • Implement multiplex assays to simultaneously detect BCAP31 and cell migration/invasion-related proteins

  • Correlate BCAP31 expression with patient survival data using Cox regression analysis across multiple cancer types

  Technical considerations:

  • Validate antibody specificity in tissue microarrays containing both tumor and adjacent normal tissues from multiple cancer types

  • When analyzing metastasis, compare BCAP31 expression between primary tumors and metastatic lesions

  • Consider that BCAP31 has demonstrated significant associations with DNA replication, mismatch repair, and DNA damage response pathways in some cancer types

• What strategies should be employed when using BCAP31 antibody pairs to investigate immune modulation in cancer?

  BCAP31 plays significant roles in immune cell function and tumor microenvironment modulation:

  Experimental design recommendations:

  • Analyze correlations between BCAP31 expression and specific immune cell infiltrates, especially:

    • Positive correlations: Neutrophils, DCs, Tem, macrophages, monocytes, nTreg, Th17, and NKT cells

    • Negative correlations: Tgd, Tc, Tr1, CD8 T, NK, iTreg, Tcm, B cells, Tfh, and CD4 T cells

  • Implement dual or triple staining protocols to visualize BCAP31 alongside immune cell markers in tissue sections

  • Consider BCAP31's established role in:

    • Facilitating transportation of MHC molecules from the ER

    • Contributing to maturation and activation of T-cell antigen receptors

    • Regulating helper T-cell activation through effects on macrophage polarization

  Analytical considerations:

  • Use computational methods like ESTIMATE to assess the proportion of immune cells infiltrating tumors in relation to BCAP31 expression

  • Analyze stromal and immune components separately, as BCAP31 may affect them differently based on cancer type

  • Consider integrating BCAP31 expression analysis with immunotherapy response data to identify predictive biomarker potential

• How should researchers validate BCAP31 knockdown experiments for functional studies?

  For robust BCAP31 functional studies using knockdown approaches:

  Validation protocol:

  1. Select appropriate siRNA targeting BCAP31 (validated in previous studies)

  2. Confirm knockdown efficiency using Western blot analysis with specific anti-BCAP31 antibodies

  3. Establish stable cell lines with BCAP31 knockdown and appropriate controls

  4. Validate phenotypic effects through:

     • Transwell assays for migration and invasion capacity

     • Wound healing assays for cellular motility

     • Colony formation assays for growth potential

     • MTT assays for proliferation rate

  Important controls:

  • Include both negative control siRNA (si-NC) and wild-type cells

  • Test multiple cell lines to ensure reproducibility (e.g., KYSE-150 cells for ESCA studies)

  • Perform rescue experiments by re-expressing BCAP31 to confirm specificity of observed effects

  Expected outcomes:
  Based on published findings, BCAP31 knockdown has been shown to:

  • Inhibit cell proliferation (as measured by MTT assay)

  • Promote invasion and migration capacity

  • Enhance colony formation abilities

• How can BCAP31 antibody pairs be leveraged to investigate relationships between expression levels and drug sensitivity?

  To explore BCAP31 as a potential predictive biomarker for therapeutic response:

  Methodological approach:

  1. Establish baseline BCAP31 expression levels across cell lines or patient samples using validated antibody pairs in ELISA or Western blot

  2. Correlate BCAP31 expression with sensitivity to specific compounds:

     • Studies have identified positive correlations between BCAP31 expression and sensitivity to:

       • 5-Fluorouracil

       • ABT737 (Bcl-2 inhibitor)

       • Afuresertib (AKT inhibitor)

       • AGI-5198 (IDH1 inhibitor)

       • Alisertib (Aurora kinase inhibitor)

       • AGI-6780 (IDH2 inhibitor)

  3. Investigate mechanism of correlation through pathway analysis, considering BCAP31's roles in:

     • ER stress responses

     • Apoptosis regulation

     • Cell survival pathways

  Technical considerations:

  • Standardize BCAP31 quantification across samples using recombinant protein standards

  • Employ dose-response curves rather than single-dose experiments

  • Integrate findings with data on genetic alterations like copy number variations (CNVs), which have been associated with BCAP31 expression levels

• What are the technical challenges and solutions for using BCAP31 antibody pairs in multiplex protein detection systems?

  Common challenges:

  1. Cross-reactivity concerns:

     • BCAP31 shares sequence homology with related proteins

     • Solution: Use recombinant antibodies (e.g., 84584-1-PBS and 84584-2-PBS) validated for specificity in multiplex systems

  2. Buffer compatibility:

     • Different detection platforms require specific buffer conditions

     • Solution: Select conjugation-ready antibody formats (PBS-only without BSA/azide) that can be optimized for specific assay requirements

  3. Signal optimization:

     • BCAP31 expression varies greatly between tissue types

     • Solution: Validate detection limits using dilution series of positive controls (e.g., BCAP31 293T overexpression lysate)

  4. Standardization across experiments:

     • Solution: Implement recombinant BCAP31 protein standards and develop calibration curves specific to each multiplex platform

  Recommended approaches:

  • For cytometric bead arrays: Use validated matched pairs like MP01418-1 (84584-1-PBS capture and 84584-2-PBS detection)

  • For multiplex imaging: Select antibodies validated for immunofluorescence with minimal background in relevant tissue types

  • For simultaneous detection of multiple proteins: Verify epitope compatibility to prevent steric hindrance between antibodies

• How can researchers integrate BCAP31 expression data with tumor microenvironment analysis?

  BCAP31 expression correlates significantly with tumor microenvironment (TME) characteristics, providing opportunities for integrated analysis:

  Analytical framework:

  1. TME correlation analysis

     • Positive correlations observed in: OV, LGG, UVM, PAAD, GBM, COAD, KIRP, KICH, TGCT, UCEC, and PCPG

     • Negative correlations observed in: HNSC, BLCA, SARC, and SKCM

  2. Pathway integration

     • Connect BCAP31 expression with enrichment of key pathways:

       • DNA replication

       • Mismatch repair

       • DNA damage response

       • Base excision repair

       • Nucleotide excision repair

  3. Immune cell profiling methods

     • Use computational tools like TIMER2 and ImmuCellAI to assess immune cell infiltration in relation to BCAP31

     • Apply ESTIMATE computational method to calculate:

       • Immune cell infiltration proportions

       • Stromal and immune component ratios

  Research implications:

  • BCAP31's apparent immunosuppressive effect suggests potential as a target for immunomodulatory therapies

  • The strong correlation with specific immune cell subsets indicates BCAP31 may influence tumor immune evasion mechanisms

  • Integration of these datasets can help stratify patients for immunotherapy based on BCAP31 expression profiles