ITGA3 Antibody

What is ITGA3 and why is it significant in cancer research?

ITGA3 (Integrin subunit alpha 3) is a protein that interacts with a beta 1 subunit to form a heterodimeric integral membrane protein that serves as a cell surface adhesion molecule . As a member of the integrin family, ITGA3 plays crucial roles in cell-matrix interactions, signal transduction, and cellular migration processes. ITGA3 has gained significant attention in cancer research due to its consistent overexpression across multiple cancer types, including cervical cancer, pancreatic cancer, ovarian cancer, and intrahepatic cholangiocarcinoma . Recent studies have demonstrated that elevated ITGA3 expression correlates with poor prognosis, aggressive tumor characteristics, and reduced survival rates in several cancers. For instance, in cervical cancer, ITGA3 promotes tumor progression by regulating the PI3K/AKT pathway, while in intrahepatic cholangiocarcinoma, it significantly influences cell proliferation and cell cycle progression . The dual role of ITGA3 as both a prognostic biomarker and a potential therapeutic target makes it particularly valuable for translational cancer research.

What types of ITGA3 antibodies are commonly used in research protocols?

Researchers typically employ several types of ITGA3 antibodies depending on their experimental objectives. Polyclonal antibodies against ITGA3, such as the rabbit polyclonal antibody (ab131055; Abcam), are frequently used for immunohistochemistry applications, offering broad epitope recognition . For more specific applications requiring higher specificity, monoclonal antibodies like OV-Ab 30-7 have been developed and used in therapeutic research contexts, particularly in ovarian cancer studies . Commercial ITGA3 antibodies are available in various formats including unconjugated forms for Western blotting and immunohistochemistry, as well as fluorophore-conjugated versions for flow cytometry and immunofluorescence microscopy. When selecting an appropriate ITGA3 antibody, researchers should consider the specific application, host species compatibility, clonality requirements, and the particular domain of ITGA3 they wish to target. For optimal reproducibility in research, validation of antibody specificity using positive and negative controls, including ITGA3 knockdown cell lines, is essential before proceeding with experimental work.

How should researchers validate ITGA3 antibody specificity?

Validating ITGA3 antibody specificity is critical to ensure experimental reproducibility and reliable data interpretation. A multi-step validation approach is recommended. First, researchers should perform Western blotting using cell lines known to express ITGA3 at different levels to confirm that the antibody detects a protein of the expected molecular weight (~120-130 kDa). The specificity can be further confirmed using ITGA3 knockdown models, as demonstrated in studies with ICC cell lines HuccT-1 and Hccc-9810 . In these studies, researchers constructed three different short interfering RNAs targeting different truncations of ITGA3 (Si-1, Si-2, and Si-3) and found Si-3 to be the most efficient for knockdown validation . Immunoprecipitation assays using recombinant ITGA3 (#TP320975, OriGene) provide another validation method, as shown in ovarian cancer research where researchers coupled OV-Ab 30-7 or normal mouse IgG to Protein G Sepharose for specific binding analysis . For immunohistochemical applications, researchers should include appropriate positive control tissues (such as cancer tissues known to overexpress ITGA3) and negative controls (antibody diluent only), alongside comparison with established ITGA3 expression patterns from resources like the Human Protein Atlas .

What clinicopathological features are associated with high ITGA3 expression?

High ITGA3 expression has been consistently associated with several adverse clinicopathological features across multiple cancer types. In intrahepatic cholangiocarcinoma, ITGA3 overexpression significantly correlates with increased gross tumor size, presence of lymph node metastasis, and advanced TNM stage . Similarly, in pancreatic adenocarcinoma (PAAD), tumors with advanced grades (3/4) demonstrate significantly higher ITGA3 levels compared to early-grade tumors (1/2, p < 0.05) . Interestingly, ITGA3 expression does not appear to show gender-specific differences in pancreatic cancer patients, suggesting its prognostic value applies across patient demographics . In cervical cancer, elevated ITGA3 expression is associated with immunosuppressed tumor microenvironments, which may impact therapeutic responsiveness . Patients with high ITGA3 expression may not benefit from immunotherapy but might show increased sensitivity to certain chemotherapeutic agents . The association of ITGA3 with epithelial-mesenchymal transition pathways and angiogenesis in cervical cancer further explains its correlation with aggressive tumor behavior and metastatic potential . Collectively, these findings suggest that ITGA3 expression assessment could serve as a valuable addition to conventional clinicopathological evaluation, potentially improving risk stratification and personalized treatment approaches in multiple cancer types.

What molecular mechanisms underlie ITGA3's role in cancer progression?

ITGA3 contributes to cancer progression through multiple molecular mechanisms that collectively promote tumor cell survival, proliferation, and invasiveness. In cervical cancer, ITGA3 activates the PI3K/AKT signaling pathway, a critical regulator of cell growth, survival, and metabolism . This activation leads to increased angiogenesis and epithelial-mesenchymal transition (EMT), two processes essential for tumor growth and metastatic spread . In intrahepatic cholangiocarcinoma, ITGA3 significantly influences cell cycle progression, as demonstrated by experiments where ITGA3 knockdown arrested cells in G1 phase and reduced entry into S phase . At the molecular level, ITGA3 silencing downregulates several cell cycle regulators, including cyclin-dependent kinases (CDK2, CDK4, and CDK6) and cyclins D1 and E1 in ICC cell lines . In ovarian cancer, integrin α3 interacts with laminin in the extracellular matrix, triggering focal adhesion kinase (FAK) signaling pathways that promote cell survival and proliferation . Antibody-mediated blockade of ITGA3 induces cancer cell apoptosis by disrupting these integrin-laminin interactions . Across multiple cancer types, ITGA3 expression is also associated with immunosuppressive tumor microenvironments and may influence sensitivity to both immunotherapy and chemotherapy . The involvement of ITGA3 in these diverse signaling networks underscores its potential as a therapeutic target in cancer, particularly through approaches that disrupt its interaction with binding partners or downstream effectors.

What are the optimal protocols for using ITGA3 antibodies in immunohistochemistry?

For optimal immunohistochemistry (IHC) using ITGA3 antibodies, researchers should follow a carefully optimized protocol. Based on published research, 3-μm thick tissue sections are recommended for ITGA3 immunostaining . When using rabbit polyclonal antibodies against human ITGA3 (such as ab131055; Abcam), proper antigen retrieval is essential for exposing epitopes that may be masked during fixation . For paraffin-embedded sections, heat-induced epitope retrieval in citrate buffer (pH 6.0) for 20 minutes is typically effective. Blocking should be performed with 1-5% bovine serum albumin (BSA) to minimize non-specific binding . The primary ITGA3 antibody concentration requires optimization, though many studies use a 1:100 to 1:200 dilution with overnight incubation at 4°C . After primary antibody incubation, sections should be thoroughly washed and incubated with an appropriate HRP-conjugated secondary antibody, followed by chromogenic detection. For quantification of ITGA3 expression, a scoring system based on the percentage of positively stained cells is commonly employed, with scores ranging from 0 to 3 (0: 0% positive cells; 1: <5%; 2: 5-50%; and 3: >50% immunoreactive cells) . Scores of 0 or 1 are typically classified as "low" expression, while scores of 2 or 3 indicate "high" expression . Including both positive controls (tissues known to express ITGA3) and negative controls (antibody diluent only) in each IHC run is essential for validating staining specificity and ensuring result reliability.

How can researchers effectively use ITGA3 antibodies in Western blotting applications?

For effective Western blotting with ITGA3 antibodies, careful optimization of each step is crucial. Cell lysate preparation should include appropriate protease inhibitors to prevent ITGA3 degradation, and protein extraction should be performed using lysis buffers containing 1% NP-40 or Triton X-100, which effectively solubilize membrane proteins like ITGA3. Protein samples (20-40 μg) should be separated on 8-10% SDS-PAGE gels, as ITGA3 has a molecular weight of approximately 120-130 kDa. For optimal transfer of high molecular weight proteins like ITGA3, a wet transfer system with 10-20% methanol in the transfer buffer is recommended. When blocking membranes, 1% bovine serum albumin (BSA) in TBS-T is effective in reducing background while preserving specific antibody binding . For primary antibody incubation, a 1:1000 dilution of anti-ITGA3 antibody with overnight incubation at 4°C has been successfully used in multiple studies . Following incubation with HRP-conjugated secondary antibodies (typically at 1:5000-1:10000 dilution for 1 hour at room temperature), signals should be detected using an ECL kit . For validation and comparative analysis, researchers commonly use β-actin or GAPDH as loading controls. When investigating ITGA3 knockdown effects, comparison between control siRNA and ITGA3-specific siRNA samples provides robust validation of antibody specificity, as demonstrated in studies with ICC cell lines where three different siRNAs targeting ITGA3 were evaluated for knockdown efficiency .

What approaches are effective for studying ITGA3 in immunoprecipitation experiments?

Effective immunoprecipitation (IP) of ITGA3 requires careful consideration of experimental conditions to preserve protein interactions while minimizing non-specific binding. For successful ITGA3 immunoprecipitation, cell lysates should be prepared using non-denaturing lysis buffers containing mild detergents such as 1% NP-40 or 0.5% Triton X-100, which solubilize membrane proteins while preserving protein-protein interactions. When coupling ITGA3 antibodies to solid supports, Protein G Sepharose has been demonstrated as an effective matrix . In published protocols, researchers have applied cell lysates and recombinant integrin α3 (#TP320975, OriGene) to antibody-coupled Protein G Sepharose for 1 hour, followed by thorough washing (typically 4 times) with PBS containing 1% Tween-20 to remove non-specifically bound proteins . Elution is commonly performed using 2-mercaptoethanol-containing buffer, followed by SDS-PAGE separation and Western blotting for detection . To control for non-specific binding, normal mouse IgG (NM IgG)-coupled Protein G Sepharose should be included as a negative control in parallel experiments . For studying ITGA3 interaction partners, co-immunoprecipitation followed by mass spectrometry has proven valuable. When investigating specific interactions, such as those between ITGA3 and integrin β1, researchers have successfully used recombinant integrin β1 (#H00003688-P01, Abnova) in pull-down assays . These approaches enable detailed analysis of ITGA3's binding partners and their potential roles in cancer-related signaling pathways.

How are ITGA3 antibodies being developed for therapeutic applications?

The development of therapeutic ITGA3 antibodies represents an emerging frontier in targeted cancer therapy. The most promising example in the literature is OV-Ab 30-7, a novel monoclonal antibody against integrin α3 that has shown therapeutic potential in ovarian cancer . This antibody was developed through a systematic approach beginning with hybridoma technology using BALB/cJ mice immunized with human ovarian cancer cells (SKOV-3) . The hybridomas were selectively screened for recognition of cancer cells (SKOV-3) but not normal human cells (foreskin fibroblast CCD-1112Sk), followed by clonal selection through limiting dilution . Antibody production was scaled up in pristane-primed BALB/cJ mice, with subsequent purification using Protein G Sepharose . Mechanistically, OV-Ab 30-7 induces ovarian cancer cell apoptosis by blocking integrin-laminin signaling pathways . Flow cytometry analysis revealed that treatment with this antibody increases active caspase-3, 8, and 9 levels, confirming its pro-apoptotic mechanism . The therapeutic efficacy of OV-Ab 30-7 correlates with ITGA3 expression levels, as demonstrated by comparing its effects in wild-type versus ITGA3-knockdown cells . These findings suggest that patient selection based on ITGA3 expression might be crucial for maximizing therapeutic responses in future clinical applications. As research progresses, next-generation ITGA3-targeted therapeutics may include antibody-drug conjugates, bispecific antibodies, and chimeric antigen receptor (CAR) T-cell approaches, expanding the potential applications of ITGA3 antibodies beyond current horizons.

What are the most effective methods for ITGA3 knockdown experimental design?

Designing effective ITGA3 knockdown experiments requires careful consideration of targeting strategies, validation methods, and functional assays. RNA interference (RNAi) using short hairpin RNAs (shRNAs) has proven highly effective for stable ITGA3 knockdown. In published studies, researchers have successfully generated stable ITGA3-knockdown cell lines using lentiviruses carrying shRNAs cloned into the pLKO.1 vector, with clone TRCN0000057714 demonstrating particularly good knockdown efficiency . For control conditions, luciferase-knockdown (clone TRCN0000231719) provides an appropriate comparison . Stable cell selection is typically achieved using puromycin treatment for approximately one week . For transient knockdown approaches, short interfering RNAs (siRNAs) targeting different regions of ITGA3 have been evaluated, with varying efficiencies reported . In studies with ICC cell lines, three different siRNAs (Si-1, Si-2, and Si-3) were compared, with Si-3 demonstrating the highest knockdown efficiency . Validation of ITGA3 knockdown should be performed at both protein levels (Western blotting) and functional levels. Functional assays to assess the phenotypic consequences of ITGA3 knockdown include proliferation assays (EdU incorporation), colony formation assays, cell cycle analysis (flow cytometry), and apoptosis assays (using markers such as annexin-V and active caspase staining) . For comprehensive mechanistic insights, combining ITGA3 knockdown with pathway analysis through Western blotting for downstream effectors (such as FAK phosphorylation, cyclin-dependent kinases, and cyclins) provides valuable information about the molecular consequences of ITGA3 depletion .

How does ITGA3 interact with the tumor microenvironment and immune infiltration?

ITGA3 plays significant roles in modulating the tumor microenvironment (TME) and influencing immune cell infiltration patterns. In cervical cancer, bioinformatic analyses have revealed that patients with high ITGA3 expression exhibit distinct immune profiles characterized by immunosuppressive features . The tumor microenvironment of these high-risk patients demonstrates reduced immune cell activation and increased immunosuppressive mechanisms . This immunosuppressive phenotype may explain why patients with high ITGA3 expression potentially derive less benefit from immunotherapy approaches compared to those with lower expression . Interestingly, while high ITGA3 expression may predict poor responses to immunotherapy, these patients may demonstrate increased sensitivity to specific chemotherapeutic agents, suggesting potential for personalized treatment selection based on ITGA3 status . Beyond immune cell interactions, ITGA3 significantly influences angiogenesis within the tumor microenvironment, as evidenced by pathway enrichment analyses showing upregulation of angiogenesis-related processes in ITGA3-high tumors . The epithelial-mesenchymal transition (EMT) process, critical for cancer cell invasion and metastasis, is also enhanced in tumors with high ITGA3 expression . These findings suggest that ITGA3 functions as a multifaceted regulator of the TME, influencing not only cancer cell behavior but also stromal and immune components. Future research targeting ITGA3 should consider these broader effects on the tumor ecosystem, potentially combining ITGA3-directed therapies with immunomodulatory approaches to overcome the immunosuppressive features associated with high ITGA3 expression.

What are common challenges when using ITGA3 antibodies in various applications?

Researchers working with ITGA3 antibodies frequently encounter several technical challenges that can impact experimental outcomes. One significant challenge is specificity validation, particularly in tissues or cell lines with variable ITGA3 expression levels. Cross-reactivity with other integrin alpha subunits (especially ITGA6, which shares structural similarities with ITGA3) can confound results if antibodies are not thoroughly validated . For immunohistochemistry applications, variable ITGA3 protein expression across different pancreatic cancer tumor samples has been observed, ranging from high to completely negative staining . This heterogeneity necessitates careful optimization of staining protocols and scoring systems. In Western blotting, ITGA3's high molecular weight (~120-130 kDa) can present transfer efficiency challenges, often requiring extended transfer times or specialized protocols for large proteins. Additionally, as a membrane protein, ITGA3 can form aggregates during sample preparation, resulting in multiple bands or smears on Western blots. For immunoprecipitation experiments, preserving ITGA3's native conformation and interaction partners requires gentle lysis conditions that may not completely solubilize the protein, affecting yield and reproducibility . Flow cytometry applications face challenges with detecting membrane-bound ITGA3 due to potentially low surface expression or epitope masking. To overcome these challenges, researchers should implement rigorous validation steps using positive and negative controls, including ITGA3 knockdown systems as demonstrated in multiple studies . Additionally, comparing results across multiple ITGA3 antibodies targeting different epitopes can help confirm the specificity and reliability of experimental findings.

What quality control measures ensure reliable results with ITGA3 antibodies?

Implementing rigorous quality control measures is essential for generating reliable and reproducible results with ITGA3 antibodies. First, researchers should verify antibody specificity through multiple approaches, including Western blotting against recombinant ITGA3 protein (such as #TP320975, OriGene) and lysates from cells with confirmed ITGA3 expression levels . Comparing signals between wild-type and ITGA3 knockdown cells provides definitive validation of antibody specificity, as demonstrated in studies with ICC and ovarian cancer cell lines . For immunohistochemistry applications, researchers should include both positive controls (tissues known to express ITGA3) and negative controls (antibody diluent only or isotype-matched non-specific antibodies) . The inclusion of an antibody titration series in each experiment helps identify optimal working concentrations and ensures consistent staining intensity across different experimental batches. Batch-to-batch antibody variation can significantly impact results, necessitating validation of each new antibody lot against previously validated samples. For quantitative applications, researchers should establish standardized scoring methods with clear criteria, such as the 0-3 scale based on percentage of positively stained cells used in ICC studies . Inter-observer validation with multiple trained scorers enhances the reliability of IHC interpretation. For therapeutic applications, functional validation through assays measuring expected biological effects (such as apoptosis induction by OV-Ab 30-7 in ovarian cancer cells) provides critical quality control beyond simple binding assessment . Finally, researchers should maintain detailed records of antibody sources, catalog numbers, lot numbers, and experimental conditions to facilitate reproducibility both within and between laboratories, addressing the broader replication challenges in antibody-based research.

How might ITGA3 antibodies contribute to personalized cancer medicine?

ITGA3 antibodies hold significant promise for advancing personalized cancer medicine through both diagnostic and therapeutic applications. As diagnostic tools, ITGA3 antibodies can help stratify patients based on ITGA3 expression levels, which have been consistently associated with prognosis across multiple cancer types . This stratification capability could inform treatment decisions, as patients with high ITGA3 expression may require more aggressive therapeutic approaches given their generally poorer outcomes. In cervical cancer, for example, patients with high ITGA3 expression demonstrate immunosuppressed tumor microenvironments and may not benefit from immunotherapy but might show increased sensitivity to specific chemotherapeutic agents . This suggests potential for ITGA3-based companion diagnostics to guide therapy selection. Therapeutically, monoclonal antibodies targeting ITGA3, such as OV-Ab 30-7, have demonstrated promising results in preclinical ovarian cancer models by inducing cancer cell apoptosis through blockade of integrin-laminin signaling . Future development of humanized anti-ITGA3 antibodies could translate these findings toward clinical applications. Additionally, the emergence of antibody-drug conjugates (ADCs) presents opportunities to deliver cytotoxic payloads specifically to ITGA3-expressing cancer cells, potentially increasing therapeutic efficacy while minimizing systemic toxicity. As research advances, integration of ITGA3 expression data with other molecular markers could generate comprehensive predictive signatures for patient stratification. Multi-parametric imaging approaches combining ITGA3 antibodies with other cancer biomarkers might further enhance diagnostic precision. The continued development of these applications positions ITGA3 antibodies as valuable tools in the evolving landscape of personalized cancer medicine, potentially improving patient outcomes through more precise diagnosis and targeted therapeutic interventions.

What emerging ITGA3 research areas show the most promise?

Several emerging research areas focusing on ITGA3 demonstrate substantial promise for advancing cancer biology understanding and therapeutic development. One particularly promising direction involves combining ITGA3-targeted therapies with immune checkpoint inhibitors to overcome the immunosuppressive tumor microenvironment associated with high ITGA3 expression . This approach could potentially convert "cold" tumors resistant to immunotherapy into more responsive "hot" tumors. Another emerging area focuses on deciphering the complex interplay between ITGA3 and cancer stem cell populations, as integrins often play crucial roles in maintaining stemness properties that contribute to therapeutic resistance and disease recurrence. The role of ITGA3 in epithelial-mesenchymal transition (EMT) and angiogenesis represents another promising research direction, particularly given the enrichment of these pathways in ITGA3-high tumors . Developing small molecule inhibitors targeting the ITGA3-mediated PI3K/AKT pathway activation could provide alternative therapeutic strategies beyond antibody-based approaches . The application of multi-omics approaches to understand how ITGA3 expression correlates with broader molecular profiles (including genomic alterations, transcriptomic signatures, and proteomic patterns) may reveal new insights into its regulatory mechanisms and functional significance across different cancer contexts. Additionally, investigating ITGA3's role in modulating response and resistance to standard therapies (including chemotherapy and radiation) could identify opportunities for combination approaches that enhance treatment efficacy. Finally, exploring ITGA3's potential as a target for chimeric antigen receptor (CAR) T-cell therapy represents an exciting frontier, potentially expanding the range of solid tumors amenable to cellular immunotherapy approaches. These diverse research directions collectively highlight ITGA3's multifaceted roles in cancer biology and its potential as a target for novel therapeutic strategies.

How do ITGA3 interactions with other integrins and binding partners affect experimental design?

ITGA3's interactions with other integrins and binding partners significantly influence experimental design considerations across various research applications. ITGA3 primarily forms heterodimers with integrin β1 (ITGB1), creating the α3β1 integrin complex that mediates interactions with extracellular matrix components, particularly laminins . This heterodimeric nature necessitates careful consideration in experimental design, as targeting ITGA3 alone may not fully disrupt all functional integrin complexes due to potential compensatory mechanisms involving other alpha subunits. When designing ITGA3 knockdown experiments, researchers should monitor potential compensatory upregulation of other integrin alpha subunits, particularly ITGA6, which can partially substitute for ITGA3 function in some contexts . For co-immunoprecipitation studies investigating ITGA3 interaction partners, non-denaturing conditions are essential to preserve native protein complexes. Published protocols have successfully used cell lysates and recombinant integrin α3 (#TP320975, OriGene) or integrin β1 (#H00003688-P01, Abnova) applied to antibody-coupled Protein G Sepharose for studying these interactions . Meta-analysis of pancreatic cancer datasets has revealed that high expression of ITGA3's key partners, including ITGB1, ITGB5, ITGB6, LAMA3, and CD9, is also associated with worse prognosis (with hazard ratios ranging from 1.6 to 2.3) . This suggests that comprehensive analysis of multiple integrin components may provide more robust prognostic information than ITGA3 alone. For therapeutic development, understanding these interaction networks is crucial, as effective targeting may require disruption of specific protein-protein interactions rather than simply reducing ITGA3 expression or activity. When designing functional assays, researchers should consider the tissue-specific extracellular matrix composition, as ITGA3's role may vary depending on the availability of specific binding partners in different tumor microenvironments .