HTATIP2 Antibody

What is HTATIP2 and what is its biological significance?

HTATIP2, also known as TIP30 or CC3, is a tumor-suppressor gene initially identified in 1997 through differential display analysis of mRNA from metastatic versus less metastatic small-cell lung carcinoma cell lines . HTATIP2 functions as a critical regulator in multiple cellular processes including apoptosis, cell proliferation, and metastasis. Research indicates that HTATIP2 is frequently downregulated in various cancer types, including melanoma, breast cancer, neuroblastoma, glioblastoma, and colon cancer . Recent evidence also implicates HTATIP2 as a regulator of T cell function with potential roles in autoimmune conditions such as type 1 diabetes .

How are polyclonal HTATIP2 antibodies typically produced and validated?

Polyclonal HTATIP2 antibodies, such as the Rabbit Polyclonal Anti-HTATIP2 Antibody, are typically produced by immunizing animals (usually rabbits) with specific HTATIP2 antigens . The production process involves rigorous standardization to ensure consistent quality. For validation, these antibodies undergo multiple techniques including immunohistochemistry (IHC), immunocytochemistry/immunofluorescence (ICC-IF), and Western blotting (WB) . High-quality manufacturers employ enhanced validation protocols to verify specificity, sensitivity, and reproducibility across different experimental conditions and sample types.

Which experimental applications are HTATIP2 antibodies most commonly used for?

HTATIP2 antibodies are validated and optimized for several key experimental applications:

What are the optimal conditions for HTATIP2 immunohistochemical staining?

For optimal immunohistochemical staining with HTATIP2 antibodies, researchers should follow this validated protocol: Fix specimens with 4% paraformaldehyde, embed in paraffin, and section to 5μm thickness. Incubate sections with polyclonal anti-rabbit antibody against HTATIP2 at an appropriate dilution (typically 1:100 to 1:500 depending on the antibody concentration), followed by incubation with a secondary antibody (such as Dako Real Envision/HRP, K5007) for 15 minutes at room temperature . The intensity of immunochemical staining can be categorized into weak, moderate, and strong staining patterns. For studies involving HTATIP2 expression analysis, samples can be classified into overexpression (OE) or underexpression (UE) groups based on criteria such as a sum of strong and moderate staining of 50% or more, or a strong staining rate of 25% or more .

How can researchers quantify HTATIP2 expression levels in experimental samples?

Researchers can employ multiple quantitative approaches to assess HTATIP2 expression:

• mRNA quantification: RT-qPCR using validated primers targeting HTATIP2 transcripts, with normalization to housekeeping genes.

• Protein quantification by immunoblotting: Western blot analysis with appropriate loading controls followed by densitometric analysis.

• Immunohistochemical scoring: Semi-quantitative scoring systems based on:

  • Staining intensity (weak, moderate, strong)

  • Percentage of positive cells (0-100%)

  • Combined scores using algorithms such as H-score or Allred score

• Transcriptome analysis: RNA-sequencing followed by differential expression analysis using software such as edgeR, as demonstrated in T cell studies .

What controls should be included when using HTATIP2 antibodies in experimental protocols?

When utilizing HTATIP2 antibodies in research protocols, the following controls are essential:

How does HTATIP2 expression correlate with gastric cancer prognosis and staging?

HTATIP2 expression demonstrates significant correlations with gastric cancer prognosis and clinical parameters. In comparative studies of poorly cohesive carcinoma (PCC) and well-differentiated tubular adenocarcinoma (WD), HTATIP2 was identified among genes with significantly reduced expression in PCC versus WD tumors . Immunohistochemical analyses revealed that patients in the HTATIP2 overexpression (OE) group had:

• Significantly higher incidence of early gastric cancer (EGC) (T1 stage) (P = 0.024)

• Reduced lymph node metastasis (P = 0.008)

• Lower TNM staging (P = 0.017)

Survival analyses using both Kaplan-Meier plots and the PrognoScan database confirmed better survival rates in patients with HTATIP2 overexpression . These findings establish HTATIP2 as a potential prognostic biomarker in gastric cancer, with higher expression correlating with more favorable outcomes.

What molecular mechanisms underlie HTATIP2's tumor suppressor function?

HTATIP2 exerts its tumor suppressor functions through multiple cellular mechanisms:

• Inhibition of cell migration and invasion: In vitro studies with HTATIP2-overexpressing KATO III gastric cancer cells demonstrated significant decreases in cancer cell migration and invasion capabilities .

• Regulation of epithelial-mesenchymal transition (EMT): HTATIP2 overexpression leads to decreased expression of EMT-associated transcription factors including Snail and Slug, suggesting that HTATIP2 maintains epithelial phenotype and suppresses mesenchymal transition .

• Cell proliferation regulation: HTATIP2 knockdown enhances cell proliferation, while HTATIP2 knockout mice are prone to spontaneous hepatocellular carcinoma and other tumors . This indicates HTATIP2's role in controlling cellular proliferation.

• Apoptosis modulation: HTATIP2 has been implicated in apoptotic pathways, potentially explaining why reduced expression may lead to cancer cell survival advantage .

How does HTATIP2 expression vary across different cancer types?

HTATIP2 expression patterns vary considerably across cancer types, with important implications for disease progression and patient outcomes:

What role does HTATIP2 play in T cell regulation and function?

HTATIP2 has emerged as an important regulator of T cell function with significant implications for immunological research. Experimental evidence from knockdown and overexpression studies has revealed:

• T cell receptor (TCR) signaling modulation: siRNA-mediated HTATIP2 knockdown in CD4+ T cells altered their response to TCR stimulation, as measured by CD69 expression following anti-CD3/CD28 antibody activation .

• Proliferation and viability effects:

  • HTATIP2 knockdown enhanced T cell proliferation approximately 1.5-fold at 72 hours compared to control cells without further stimulation (P < 0.01)

  • HTATIP2 overexpression by mRNA transfection showed enhanced proliferation (50% greater abundance) when cells were cultured in conditioned media from activated T cells

• Gene network alterations: Transcriptome analysis of HTATIP2 knockdown in CD4+ T cells revealed effects on:

  • MAP kinase signaling network, including p38 and JNK pathways

  • Antiviral interferon signaling (downregulation of OAS family genes, RSAD2, and EIF2AK2)

  • Cell adhesion molecules (upregulation of α-integrin paralogs ITGAM and ITGAX)

How is HTATIP2 implicated in type 1 diabetes pathogenesis?

Genome-wide association studies have implicated HTATIP2 as a type 1 diabetes susceptibility gene acting through T cell regulation mechanisms . Experimental evidence suggests several mechanisms by which HTATIP2 may influence type 1 diabetes development:

• Modulation of T cell infiltration: HTATIP2 expression appears to affect genes involved in cell motility, adhesion, and chemotaxis through a network centered on phosphoinositide-3-kinase and AKT signaling . When HTATIP2 is knocked down:

  • Matrix adhesion-related α-integrin genes (ITGA4, ITGA2) are upregulated

  • Leukocyte adhesion mediator L-selectin (SELL) is highly upregulated

  • Cytoskeletal regulators show altered expression (upregulation of paxillin and vinculin, downregulation of plectin)

• Interferon signaling and antiviral responses: HTATIP2 expression promotes antiviral interferon signaling, which is relevant as viral infection and immune responses to viruses are thought to be triggers of β cell autoimmunity in type 1 diabetes .

• Enhanced T cell activation and proliferation: The experimental data showing that HTATIP2 overexpression enhances cytokine-mediated signaling and proliferation suggests it could potentially contribute to heightened autoimmune responses against pancreatic β cells .

How can researchers manipulate HTATIP2 expression in primary immune cells for functional studies?

Researchers can effectively modulate HTATIP2 expression in primary immune cells using the following validated methodologies:

• siRNA-mediated knockdown:

  • Electroporation of primary CD4+ T cells with siRNA pools targeting HTATIP2

  • Validation of knockdown efficiency by RT-qPCR or western blot

  • Assessment of knockdown effects using functional assays (proliferation, activation markers, transcriptome analysis)

• mRNA-mediated overexpression:

  • Amplification of HTATIP2 gene from cDNA clones (e.g., Mammalian Gene Collection cDNA clone 3455757)

  • Ligation to expression vectors containing T7 RNA polymerase promoter for in vitro transcription

  • Synthesis of capped-and-tailed mRNA in vitro using appropriate kits (e.g., HiScribe T7 ARCA mRNA Kit)

  • Transfection of primary immune cells with the synthesized mRNA via electroporation

• Functional analysis approaches:

  • Cell viability/proliferation assays (e.g., CellTiter-Glo for ATP measurement)

  • Flow cytometry for activation markers (e.g., CD69)

  • RNA-seq for transcriptome-wide effects

  • Pathway analysis (e.g., Ingenuity Pathways Analysis) for identifying affected gene networks

How do different fixation methods affect HTATIP2 antibody staining patterns in tissues?

The choice of fixation method can significantly impact HTATIP2 antibody staining patterns and results interpretation. While 4% paraformaldehyde fixation is documented in published protocols , researchers should consider several factors when optimizing fixation for HTATIP2 immunodetection:

• Fixation duration: Over-fixation may mask epitopes through excessive protein cross-linking, while under-fixation can lead to poor tissue morphology and antigen loss. Optimization of fixation time (typically 12-24 hours for standard tissues) is recommended.

• Epitope retrieval methods: When using formalin-fixed paraffin-embedded (FFPE) tissues, heat-induced epitope retrieval (HIER) methods using citrate buffer (pH 6.0) or EDTA buffer (pH 9.0) should be systematically compared to determine optimal conditions for HTATIP2 detection.

• Alternative fixatives: For certain applications, alternative fixatives such as Bouin's solution, zinc-based fixatives, or alcohol-based fixatives may provide superior antigen preservation and should be experimentally compared.

• Fresh versus frozen sections: For certain sensitive epitopes, freezing tissue and performing staining on cryosections may provide superior results compared to fixed tissues, particularly for quantitative studies or when examining subcellular localization.

What strategies can address inconsistent HTATIP2 antibody performance across different experimental replicates?

Inconsistent antibody performance can undermine experimental reproducibility. Researchers encountering variability in HTATIP2 antibody results should consider:

• Antibody qualification and validation:

  • Verify antibody lot-to-lot consistency by testing new lots against previous ones

  • Confirm antibody specificity using positive and negative controls, including HTATIP2 knockdown and overexpression samples

  • Consider parallel testing of multiple HTATIP2 antibodies targeting different epitopes

• Protocol standardization:

  • Develop and strictly adhere to standardized protocols with precise timing, temperature, and reagent concentrations

  • Prepare and aliquot stock solutions to minimize freeze-thaw cycles

  • Maintain consistent incubation times and temperatures across experiments

• Sample handling optimization:

  • Standardize tissue processing procedures, including time from collection to fixation

  • Implement consistent antigen retrieval methods

  • Use automated staining platforms when available to reduce operator variability

• Positive and negative controls:

  • Include consistent positive and negative controls in each experimental run

  • Consider using tissue microarrays containing standardized control samples

How can researchers integrate HTATIP2 expression data with other molecular profiling approaches for comprehensive disease understanding?

Modern research increasingly requires integration of multiple molecular datasets. For comprehensive understanding of HTATIP2's role in disease pathology, researchers should consider:

• Multi-omics integration approaches:

  • Correlate HTATIP2 protein expression (immunohistochemistry) with mRNA expression (RNA-seq or qPCR)

  • Integrate with DNA methylation analysis of the HTATIP2 promoter region to understand epigenetic regulation

  • Perform chromatin immunoprecipitation (ChIP) studies to identify transcription factors regulating HTATIP2

• Pathway and network analysis:

  • Utilize tools like Ingenuity Pathway Analysis to identify gene networks affected by HTATIP2 modulation

  • Perform Gene Set Enrichment Analysis (GSEA) to identify biological processes associated with HTATIP2 expression levels

  • Integrate protein-protein interaction data to map HTATIP2's interactome

• Clinical data integration:

  • Correlate HTATIP2 expression patterns with clinical outcomes and patient characteristics

  • Perform survival analyses stratified by HTATIP2 expression levels, as demonstrated in gastric cancer studies

  • Develop multivariate models incorporating HTATIP2 expression with other molecular markers and clinical variables

• Single-cell approaches:

  • Apply single-cell RNA-seq to characterize cell type-specific HTATIP2 expression patterns

  • Combine with spatial transcriptomics to understand HTATIP2 expression in tissue microenvironments

  • Implement high-dimensional cytometry (mass cytometry or spectral flow cytometry) to correlate HTATIP2 expression with multiple cellular markers

How might HTATIP2 function as a biomarker in personalized medicine approaches?

HTATIP2 shows significant potential as a biomarker in personalized medicine strategies based on current research findings:

• Prognostic stratification: In gastric cancer, HTATIP2 overexpression correlates with better prognosis, less lymph node metastasis, and earlier disease stage . This suggests HTATIP2 expression could be incorporated into risk stratification algorithms to identify patients requiring more aggressive follow-up or treatment.

• Treatment response prediction: Although not directly studied yet, the involvement of HTATIP2 in cellular pathways affected by cancer therapeutics suggests potential utility in predicting treatment responses. Prospective studies correlating HTATIP2 expression with responses to standard therapies could establish its predictive value.

• Immunotherapy biomarker potential: Given HTATIP2's role in T cell regulation , expression levels might correlate with response to immunotherapies. Particularly in cancers where immune checkpoint inhibitors are employed, HTATIP2 expression in tumor or infiltrating immune cells could potentially predict immunotherapy efficacy.

• Autoimmune disease risk assessment: The identification of HTATIP2 as a type 1 diabetes gene suggests utility in autoimmune disease risk stratification . Genetic variants affecting HTATIP2 expression or function could be incorporated into polygenic risk scores for type 1 diabetes susceptibility.

What is the current understanding of how post-translational modifications affect HTATIP2 function?

The role of post-translational modifications (PTMs) in regulating HTATIP2 function represents an understudied area with significant research potential:

• Phosphorylation: HTATIP2's involvement in MAPK and PI3K/AKT signaling pathways suggests it may be regulated by phosphorylation. Researchers should investigate potential phosphorylation sites and their functional consequences using phospho-specific antibodies, mass spectrometry, and site-directed mutagenesis.

• Ubiquitination and protein stability: As a tumor suppressor frequently downregulated in cancers , HTATIP2 protein stability may be regulated through the ubiquitin-proteasome system. Studies examining HTATIP2 protein half-life, ubiquitination patterns, and interactions with E3 ligases could provide insights into post-transcriptional regulation mechanisms.

• Other potential modifications: Additional PTMs including SUMOylation, acetylation, or methylation might influence HTATIP2 localization, protein-protein interactions, or function. Comprehensive proteomic approaches could identify novel modifications and their regulatory significance.

• PTM crosstalk: The interplay between different types of HTATIP2 modifications could create a complex regulatory code affecting its function in different cellular contexts. Investigating how multiple PTMs cooperate or antagonize each other would provide deeper mechanistic understanding.