ska3 Antibody

What is SKA3 and what role does it play in cellular processes?

SKA3 (also known as C13orf3 or RAMA1) is a 412 amino acid protein that functions as a critical component of the SKA1 complex, a microtubule-binding subcomplex of the outer kinetochore essential for proper chromosome segregation during cell division . This complex localizes to the outer kinetochore and spindle microtubules, where SKA3 mediates microtubule-stimulated oligomerization, facilitating chromosome movement along microtubules . In the SKA1 complex, SKA3 ensures accurate chromosome alignment and segregation, vital processes for maintaining genomic stability . The affinity of this complex for microtubules is synergistically enhanced in the presence of the ndc-80 complex, potentially allowing it to track depolymerizing microtubules .

What types of SKA3 antibodies are available for research applications?

Multiple types of SKA3 antibodies are available for research, including:

• Mouse monoclonal antibodies (e.g., H-9) with IgG2b kappa light chain isotype, suitable for detecting SKA3 in mouse, rat, and human samples

• Rabbit polyclonal antibodies targeting the C-terminal region (aa 350 to C-terminus) of human SKA3

• Goat polyclonal antibodies raised against synthetic peptides corresponding to internal regions of human SKA3 (sequence C-PLSKTNSSSNDLE)

These antibodies are available in various formats including non-conjugated forms and conjugated versions with agarose, horseradish peroxidase (HRP), phycoerythrin (PE), fluorescein isothiocyanate (FITC), and multiple Alexa Fluor® conjugates .

What are the validated applications for SKA3 antibodies in experimental protocols?

SKA3 antibodies have been validated for multiple experimental techniques:

Each application requires specific optimization based on sample type and experimental conditions.

How should researchers approach optimization of immunohistochemistry protocols using SKA3 antibodies?

For effective IHC with SKA3 antibodies, researchers should follow these methodological guidelines:

• Tissue preparation: Use paraffin-embedded sections with appropriate antigen retrieval methods. For SKA3, steam-based antigen retrieval has been validated for certain antibodies .

• Antibody selection: Choose antibodies validated specifically for IHC applications. Goat polyclonal antibodies at 3.75 μg/ml concentration have shown good results .

• Staining evaluation: Implement standardized scoring systems such as the modified immunoreactive score (IRS):

  • Score staining intensity: 0 (negative/weak), 1 (moderate), 2 (strong)

  • Score percentage of positive expression: 1 (<25%), 2 (25-50%), 3 (50-75%), 4 (75-100%)

  • Calculate IRS by multiplying intensity and percentage scores

• Controls: Include appropriate negative controls (normal tissue) and positive controls (tissues known to express SKA3, such as placenta) .

• Results interpretation: SKA3 typically shows cytoplasmic staining in positive samples. In bladder cancer studies, for example, increased cytoplasmic SKA3 staining was observed in 21 of 25 cases, while normal urothelial tissues showed negative staining .

How does SKA3 contribute to cancer progression mechanisms?

SKA3 has emerged as a significant factor in cancer progression through multiple mechanisms:

• Promotion of stem cell-like properties: In hepatocellular carcinoma (HCC), SKA3 enhances stemness properties through activation of the Notch signaling pathway. This is evidenced by positive correlations between SKA3 expression and stemness markers like CD44 and Oct4 .

• Enhanced cell proliferation and migration: Knockdown studies demonstrate that suppressing SKA3 decreases cell viability, proliferation, migration, and invasion capabilities in liver cancer cells, while upregulation produces opposite effects .

• Resistance to therapeutic agents: Cells overexpressing SKA3 show increased resistance to Sorafenib, suggesting a role in therapeutic resistance mechanisms .

• Cell cycle regulation: SKA3 knockdown induces G1/S phase arrest, inhibiting proliferation of liver cancer cells .

• Immune microenvironment modulation: SKA3 expression positively correlates with infiltration of specific immune cells, including M2 macrophages in bladder cancer, potentially contributing to an immunosuppressive tumor microenvironment .

Significantly, high SKA3 expression correlates with poor prognosis in multiple cancer types, including liver and bladder cancers, making it a potential prognostic biomarker .

What experimental approaches are effective for investigating SKA3's role in mitotic processes?

For researching SKA3's function in mitosis, several validated experimental approaches can be employed:

• RNA interference techniques:

  These approaches have demonstrated high efficiency in reducing SKA3 expression .

• Live cell imaging: Time-lapse microscopy with GFP-histone H2B-expressing cells enables visualization of mitotic defects following SKA3 depletion. This approach has revealed that SKA3 reduction leads to transient metaphase arrest, chromosome scattering, and prolonged mitotic arrest .

• Overexpression studies: Using pGV plasmids containing the full-length SKA3 gene to investigate gain-of-function effects. Transfection efficiency should be validated by qRT-PCR and Western blot .

• Functional assays:

  • Colony formation assays to assess proliferative capacity

  • Transwell migration and invasion assays to evaluate motility

  • Apoptosis assays using annexin V and propidium iodide staining

• In vivo models: Subcutaneous xenograft models in BALB/c nude mice with SKA3-manipulated cell lines have successfully demonstrated the role of SKA3 in tumor growth .

What methodologies are recommended for studying SKA3 in relation to cancer stemness?

To investigate SKA3's role in cancer stemness, researchers should consider these methodological approaches:

• Sphere formation assays: This technique evaluates self-renewal capacity of cancer stem cells. SKA3-overexpressing cells form more and larger spheres, while SKA3-suppressed cells form fewer and smaller spheres .

• Expression analysis of stemness markers:

  • Western blot for protein expression of stemness markers (Oct4, CD44)

• Drug resistance assays: Testing resistance to chemotherapeutic agents (e.g., Sorafenib) at various concentrations in SKA3-manipulated cells .

• Signaling pathway investigation: Western blot analysis of key signaling pathway components (Notch, Hedgehog, Wnt) to identify mechanisms of SKA3-mediated stemness. For Notch pathway specifically, evaluate NICD expression levels .

How can researchers analyze the relationship between SKA3 expression and immune infiltration?

For investigating associations between SKA3 and immune infiltration, researchers should implement these methodological approaches:

• Computational analysis using immune deconvolution algorithms:

  • Utilize established databases like TIMER to analyze correlations between SKA3 expression and immune cell infiltration

  • Apply multiple algorithms (EPIC, TIMER, XCELL, MCPCOUNTER) to ensure robust findings

• Correlation analysis with immune cell markers:

  • Examine relationships between SKA3 expression and established markers for specific immune cell populations (e.g., M2 macrophages: MRC1, CD163)

  • Implement statistical approaches such as Pearson's correlation analysis with appropriate significance thresholds (P < 0.05)

• Gene Ontology and pathway analysis:

  • Conduct GO enrichment analysis to identify biological processes associated with SKA3

  • Perform KEGG pathway analysis to identify signaling pathways (e.g., cytokine-cytokine receptor interaction, chemokine signaling pathway)

• Tissue validation:

  • Compare SKA3 expression between tumor and non-tumor tissues using immunohistochemistry

  • Analyze immune cell infiltration patterns in relation to SKA3 expression levels

This multifaceted approach has revealed that SKA3 expression positively correlates with infiltration of CD8+ T cells, macrophages, neutrophils, and dendritic cells in bladder cancer, while showing negative correlation with CD4+ T cell infiltration .

What technical considerations are important when validating SKA3 antibody specificity?

For rigorous validation of SKA3 antibody specificity, researchers should incorporate these technical considerations:

• Positive and negative controls:

  • Positive controls: Tissues or cell lines with confirmed SKA3 expression (e.g., placenta for IHC)

  • Negative controls: SKA3 knockdown samples using validated siRNA sequences

  • Isotype controls: Use appropriate isotype control antibodies (e.g., Goat IgG for goat polyclonal antibodies)

• Molecular weight verification:

  • Canonical SKA3 protein appears at approximately 46 kDa

  • Verify detection of additional reported bands at 35 kDa and 150 kDa that may represent alternative isoforms or post-translational modifications

• Cross-reactivity assessment:

  • Evaluate antibody performance across species (human, mouse, rat) when cross-reactivity is claimed

  • Test in multiple cell lines to confirm consistent detection patterns

• Method-specific validations:

  • For IHC: Test multiple antigen retrieval methods and titrate antibody concentrations

  • For WB: Test under reducing and non-reducing conditions

  • For IF: Verify co-localization with known kinetochore markers

• Reproducibility testing:

  • Compare results across different lot numbers of the same antibody

  • Validate findings using alternative antibodies targeting different epitopes of SKA3

Implementing these rigorous validation steps ensures reliable and reproducible results in SKA3 research applications.

What are common challenges in SKA3 detection and recommended solutions?

Researchers may encounter several challenges when working with SKA3 antibodies. The following table outlines common issues and their methodological solutions:

How can researchers optimize protocols for studying SKA3 in different cancer models?

For optimizing SKA3 investigation across cancer models, researchers should implement these methodological adaptations:

• Cancer-specific cell line selection:

  • For liver cancer: MHCC-97h and SNU-398 cell lines have been validated for SKA3 studies

  • For bladder cancer: Consider established bladder cancer cell lines with variable SKA3 expression

  • Include non-cancerous control cell lines from the same tissue origin

• Expression verification:

  • Confirm protein expression with Western blot using antibody dilutions of approximately 1:1000

• Model-specific scoring systems:

  • For tissue analysis in liver cancer: Use staining index (SI) calculation with optimal cut-off value (SI ≥6 indicating high expression)

  • For bladder cancer: Apply modified immunoreactive score (IRS) methodology

• Statistical analysis adaptation:

  • Use chi-square tests and Fisher's exact tests to assess associations between SKA3 expression and clinicopathological factors

  • Apply Pearson's correlation analysis to evaluate relationships between SKA3 and clinical pathologic factors

  • Construct survival curves via Kaplan-Meier method and compare with log-rank test

  • Perform univariate and multivariate Cox regression analysis to evaluate prognostic significance

• In vivo model considerations:

  • For subcutaneous xenograft models: Use 10^6 cells per injection site in BALB/c nude mice

  • Validate tumor growth alterations through both volume measurements and Ki67 staining

These optimizations have enabled successful investigation of SKA3's role in multiple cancer models, revealing its function as a potential oncogene and prognostic biomarker.

What emerging research areas involving SKA3 warrant further investigation?

Based on current findings, several promising research directions for SKA3 investigation include:

• Therapeutic targeting potential: Development and evaluation of small molecule inhibitors or antibody-drug conjugates targeting SKA3, given its upregulation in multiple cancers and association with poor prognosis .

• Predictive biomarker development: Investigation of SKA3 as a predictive biomarker for treatment response, particularly for therapies targeting mitotic processes or the Notch signaling pathway .

• Combinatorial targeting approaches: Exploration of synergistic effects when targeting SKA3 alongside other components of the mitotic machinery or cancer stemness pathways .

• Immune modulation mechanisms: Further characterization of how SKA3 influences the tumor immune microenvironment, particularly its effects on M2 macrophage and Th2 cell infiltration, which could provide insights for immunotherapy approaches .

• Post-translational regulation: Investigation of how phosphorylation or other post-translational modifications affect SKA3 function, potentially explaining the multiple molecular weight bands observed in Western blot analyses .

• Structural biology studies: Determination of SKA3's three-dimensional structure and its interaction interfaces with other components of the kinetochore complex, which could inform structure-based drug design .

• Cancer-specific isoform analysis: Characterization of the expression patterns and functional differences of the three reported SKA3 isoforms across different cancer types .