ARHGEF10L Antibody

What is ARHGEF10L and what are its primary cellular functions?

ARHGEF10L (Rho guanine nucleotide exchange factor 10-like protein), also known as GrinchGEF, belongs to the RhoGEF subfamily of RhoGTPases. The protein contains a typical Dbl homology domain, a putative WD40-like domain, and two predicted transmembrane helices . It functions primarily as a guanine nucleotide exchange factor that activates Rho GTPases, particularly RhoA, playing a vital role in signal transduction pathways .

At the cellular level, ARHGEF10L regulates several critical processes:

• Cell proliferation and migration through RhoA activation

• Cytoskeletal reorganization via the RhoA-ROCK1-phospho-ERM signaling pathway

• Epithelial-to-mesenchymal transition (EMT) by regulating cadherin expression

• Cell apoptosis inhibition

The protein shows cytosolic distribution and multiple transcript variants exist due to alternative splicing .

How can researchers effectively detect endogenous versus overexpressed ARHGEF10L in cell systems?

When distinguishing between endogenous and overexpressed ARHGEF10L, researchers should implement the following methodological approaches:

For endogenous detection:

• Western blotting with validated antibodies at optimal dilutions (1:500-1:2000 is typically recommended)

• Expect a molecular weight of approximately 140 kDa for the native protein

• Use appropriate positive control tissues (rat lung samples have shown consistent expression)

• Blocking with 3% nonfat dry milk in TBST has demonstrated good results

For overexpressed systems:

• When using tagged constructs (RFP/Myc/His/Strep), the molecular weight will be higher than endogenous protein due to tag contribution

• qRT-PCR can verify increased mRNA expression using primers such as:

  • Forward: 5′AGTGCCAGGTGGTGTTCTTC3′

  • Reverse: 5′AAGAGGTCCCCGATCTTCTC3′

• Compare with appropriate mock-transfected controls rather than untransfected cells

• For immunofluorescence detection, higher concentrations of antibody may be necessary (≥10 μg/ml has been successful)

Note that recombinant ARHGEF10L with tags will show a distinct band shift compared to endogenous protein, which can serve as internal validation of expression system efficacy .

What experimental approaches are most effective for investigating ARHGEF10L's role in cancer progression?

Based on published research methodologies, a comprehensive investigation of ARHGEF10L in cancer progression should incorporate:

Gene expression manipulation:

• Overexpression systems using plasmids containing full-length ARHGEF10L with reporter tags (RFP has been successfully used)

• Knockdown approaches using siRNA (validated target sequence: 5′-CCGCGTGAAGGAGATCCTGCA-3′)

• Transfection protocols optimized for cancer cell lines (PolyJet™ DNA In Vitro Transfection Reagent for plasmids; HiPerFect for siRNA)

Functional assays:

• Cell proliferation: Cell counting kit-8 assays at 48-72h post-transfection

• Migration capacity: Wound-healing assays with standardized scratch protocols

• Apoptotic resistance: Flow cytometry-based apoptosis assays

• Angiogenic potential: Tube-like structure formation assays (particularly relevant for gastric cancer)

Molecular pathway analysis:

• RhoA activation: Rho pull-down assays to detect GTP-bound RhoA

• EMT assessment: Western blot analysis of E-cadherin (downregulation), N-cadherin and Slug (upregulation)

• Downstream effector activation: Monitor ROCK1 and phospho-ERM expression levels

Transcriptome profiling:

• RNA sequencing to identify associated pathways and gene expression changes

• KEGG and GO pathway analyses for systematic function prediction

• Validation of key targets (such as HSPA6) by qRT-PCR and Western blotting

These methodologies have been validated across multiple cancer types including cervical, liver, and gastric cancers, suggesting a conserved oncogenic mechanism .

How does ARHGEF10L signaling differ between various cancer types, and what are the implications for experimental design?

Research indicates both common mechanisms and cancer-specific aspects of ARHGEF10L signaling that should inform experimental design:

Common mechanisms across cancer types:

• ARHGEF10L consistently activates the RhoA-ROCK1-phospho-ERM axis in cervical, liver, and gastric cancers

• EMT induction occurs through similar cadherin switching patterns across tumor types

• HSPA6 upregulation appears to be a conserved downstream effect

Cancer-specific considerations:

• Cervical cancer: ARHGEF10L activates cyclin-dependent protein serine/threonine kinase activity, cell responses to vitamin A, and Toll-like receptor signaling pathways specifically in HeLa cells

• Gastric cancer: Shows pronounced effects on tube-like structure formation, suggesting angiogenesis regulation not prominently reported in other cancers

• Liver cancer: Strong genetic association with specific SNPs (rs2244444 and rs12732894) suggests potential genotype-dependent effects

Experimental design implications:

• Control selection: When comparing across cancer types, include both normal tissue controls and other cancer types to distinguish cancer-specific from general oncogenic mechanisms

• Pathway inhibitor studies: Include RhoA/ROCK inhibitors alongside ARHGEF10L manipulation to confirm pathway dependence across cancer types

• Genetic background: For cervical cancer specifically, consider SNP analysis (particularly rs12067869) due to its reported association

• Endpoint selection: Choose functional assays most relevant to the cancer type (e.g., angiogenesis assays for gastric cancer; proliferation and migration for cervical cancer)

• Timeline considerations: Allow sufficient time (72h minimum) for epithelial-to-mesenchymal transition effects to manifest

This comparative approach can help distinguish universal oncogenic mechanisms from tissue-specific effects, potentially revealing more targeted therapeutic approaches .

What are the critical factors for selecting an appropriate ARHGEF10L antibody for specific experimental applications?

When selecting an ARHGEF10L antibody, researchers should consider the following technical factors:

Application compatibility:

• Western blotting: Most commercial antibodies are validated for WB with recommended dilutions ranging from 1:500-1:2000

• Immunofluorescence/ICC: Select antibodies specifically validated for cellular localization studies; not all WB-validated antibodies perform well in IF applications

• ELISA: Several antibodies are validated for both WB and ELISA applications

Epitope considerations:

• Target domain specificity: Some antibodies target the N-terminal region while others target C-terminal domains (aa 1120-1230)

• For studying specific isoforms, select antibodies raised against unique regions not shared among transcript variants

• When studying domain-specific functions, choose antibodies that don't interfere with functional domains

Host species compatibility:

• For co-localization studies with other antibodies, select from different host species (rabbit and mouse options are available)

• Consider secondary antibody compatibility within your experimental system

Cross-reactivity profile:

• Human reactivity is consistently available across commercial options

• Rat cross-reactivity has been confirmed for some antibodies

• Mouse reactivity is more variable and requires validation

Detection system compatibility:

• For chemiluminescent detection, HRP-conjugated secondary antibodies with ECL systems have shown good results

• For fluorescence-based applications, confirm absence of spectral overlap with other fluorophores

Technical validation data:

• Review provided validation data for expected band size (~140 kDa)

• Check for demonstration of specificity (e.g., knockdown controls)

• Assess background levels in provided images

This systematic approach to antibody selection helps ensure experimental success and reliable data interpretation in ARHGEF10L research applications .

What are the most effective validation strategies to confirm ARHGEF10L antibody specificity in experimental systems?

A comprehensive validation approach for ARHGEF10L antibodies should include:

Genetic manipulation controls:

• Overexpression validation: Compare signal between ARHGEF10L-transfected cells and mock-transfected controls, expecting significantly increased signal intensity at the correct molecular weight

• Knockdown validation: Confirm reduced signal intensity following siRNA-mediated ARHGEF10L knockdown using validated sequences (e.g., 5′-CCGCGTGAAGGAGATCCTGCA-3′)

• Knockout controls: When available, CRISPR/Cas9-mediated knockout cells provide the most stringent validation

Multiple detection methods:

• Correlate protein detection (Western blot) with mRNA levels (qRT-PCR using validated primers)

• Compare results using antibodies targeting different epitopes of ARHGEF10L

• For tagged constructs, compare detection with tag-specific antibodies versus ARHGEF10L-specific antibodies

Technical validations:

• Peptide competition assay: Pre-incubation with immunizing peptide should abolish specific signal

• Dilution series: Signal should decrease proportionally with antibody dilution

• Multiple batches: Test consistency across antibody lots when available

Immunoprecipitation validation:

• IP-MS verification: Immunoprecipitate ARHGEF10L and confirm identity by mass spectrometry

• Co-IP of known interaction partners (e.g., RhoA) to confirm functional relevance

Species-specific considerations:

• For antibodies claiming multi-species reactivity, validate separately in each species

• Use appropriate positive control tissues (e.g., rat lung has shown consistent expression)

Application-specific validations:

• For ICC/IF: Include parallel staining with another validated ARHGEF10L antibody or tag antibody in overexpression systems

• For proximity ligation assays: Include reverse antibody combinations and appropriate negative controls

Implementing these rigorous validation strategies ensures reliable detection of ARHGEF10L and prevents misinterpretation of experimental results due to non-specific antibody binding .

How can researchers effectively study ARHGEF10L-mediated RhoA activation and subsequent signaling cascades?

Studying ARHGEF10L-mediated RhoA activation requires a multi-faceted approach:

Direct measurement of RhoA activation:

• Rho pull-down assay: This gold-standard approach uses GST-Rhotekin-RBD fusion proteins to selectively capture GTP-bound (active) RhoA. Compare levels between ARHGEF10L-overexpressing cells and controls

• FRET-based biosensors: For live-cell imaging of RhoA activation kinetics in response to ARHGEF10L manipulation

• G-LISA assays: Provide quantitative measurement of active RhoA with higher sensitivity than traditional pull-down assays

Downstream signaling evaluation:

• ROCK1 activation: Monitor both total ROCK1 and phosphorylated ROCK1 levels by Western blot

• Phospho-ERM detection: Use phospho-specific antibodies against ezrin/radixin/moesin to assess cytoskeletal signaling activation

• Actin cytoskeleton visualization: Phalloidin staining to observe F-actin reorganization following ARHGEF10L manipulation

Pathway inhibitor studies:

• RhoA inhibition: Use C3 transferase to specifically inhibit RhoA and confirm its necessity in ARHGEF10L signaling

• ROCK inhibition: Apply Y-27632 to block ROCK activity and determine the dependence of ARHGEF10L-mediated effects on this downstream effector

• Rescue experiments: Attempt to rescue ARHGEF10L knockdown phenotypes with constitutively active RhoA constructs

Temporal dynamics:

• Establish time-course experiments to determine the sequence of activation events following ARHGEF10L overexpression

• Compare acute versus chronic activation patterns

Spatial regulation:

• Subcellular fractionation to determine compartment-specific activation of RhoA

• Co-localization studies of ARHGEF10L with RhoA and downstream effectors

Context-dependent activation:

• Examine RhoA activation under different conditions (serum starvation, growth factor stimulation, matrix rigidity changes)

• Compare RhoA activation in 2D versus 3D culture systems

This comprehensive approach allows for detailed characterization of how ARHGEF10L regulates RhoA signaling pathways in normal and cancer cell contexts .

What approaches can resolve contradictory data when studying ARHGEF10L function in different experimental systems?

When faced with contradictory results regarding ARHGEF10L function, researchers should implement a systematic troubleshooting approach:

Source of biological variation:

• Cell type-specific effects: ARHGEF10L functions differently across cell lines (HeLa versus SGC7901); always compare within the same cellular background

• Expression level differences: Quantify ARHGEF10L expression levels across systems, as dose-dependent effects may explain disparate results

• Genetic background variations: Check for polymorphisms in ARHGEF10L or pathway components (SNPs rs12067869, rs2244444, and rs12732894 have been linked to cancer risk)

Technical reconciliation approaches:

• Standardize detection methods: Use identical antibodies and detection protocols across experimental systems

• Validate knockdown/overexpression efficiency: Quantify the degree of manipulation achieved in each system

• Control for transfection effects: Include appropriate mock transfections and empty vector controls

Pathway component analysis:

• RhoA expression profiling: Measure baseline RhoA levels across systems, as ARHGEF10L effects may depend on RhoA abundance

• ROCK isoform expression: Determine whether ROCK1 versus ROCK2 predominates in each system

• Competing GEFs/GAPs: Profile other RhoGEFs and RhoGAPs that might counteract ARHGEF10L activity

Functional integration approaches:

• Multiplexed assays: Apply several functional readouts simultaneously (proliferation, migration, EMT markers) to build a comprehensive phenotypic profile

• Rescue experiments: Test whether contradictory phenotypes can be resolved by manipulating downstream components

• Pathway inhibitor dose-response: Generate dose-response curves for RhoA/ROCK inhibitors to determine sensitivity differences

Advanced reconciliation methods:

• Single-cell analyses: Determine whether population heterogeneity explains contradictory bulk results

• Temporal dynamics: Establish detailed time-course experiments, as contradictions may reflect different temporal stages of the same process

• Environmental factors: Systematically vary culture conditions (serum levels, cell density, matrix components) to identify context-dependent effects

Data integration strategy:

This systematic approach helps distinguish true biological variation from technical artifacts when investigating ARHGEF10L function across different experimental systems .

How can researchers effectively investigate ARHGEF10L's role in epithelial-to-mesenchymal transition (EMT) in cancer progression?

To comprehensively investigate ARHGEF10L's role in EMT, researchers should implement a multi-dimensional approach:

Molecular marker assessment:

• Core EMT markers: Systematically quantify E-cadherin (decrease), N-cadherin (increase), and transcription factors including Slug following ARHGEF10L manipulation

• Extended EMT panel: Include vimentin, ZO-1, claudins, occludin, and matrix metalloproteinases for comprehensive EMT profiling

• Methodology combination: Integrate Western blotting, qRT-PCR, and immunofluorescence to assess both expression levels and subcellular localization

Functional EMT assays:

• Migration dynamics: Beyond simple wound healing assays, implement time-lapse microscopy to capture real-time migratory behavior changes

• Invasion assays: Use Matrigel-coated Transwell systems to assess 3D invasive capacity

• Cell morphology analysis: Quantify morphological transitions using automated image analysis

• Cell-cell adhesion: Measure cell-cell adhesion strength through dispase assays or atomic force microscopy

Mechanistic dissection:

• Pathway inhibition experiments: Systematically block RhoA (C3 transferase), ROCK (Y-27632), and other downstream components to establish dependency relationships

• Transcription factor ChIP assays: Determine whether ARHGEF10L affects direct binding of EMT-associated transcription factors to target promoters

• EMT transcription factor reporter assays: Use promoter-reporter constructs for key EMT regulators (Snail, Slug, ZEB1/2) to assess transcriptional activation

Contextual considerations:

• EMT plasticity: Investigate whether ARHGEF10L promotes partial versus complete EMT states

• Reversibility studies: Test whether ARHGEF10L knockdown can reverse established mesenchymal phenotypes

• Microenvironmental factors: Examine how matrix composition and stiffness modify ARHGEF10L-induced EMT

Translational approaches:

• Patient-derived models: Validate findings in primary cultures or patient-derived xenografts with varying ARHGEF10L expression levels

• Clinical correlation: Analyze ARHGEF10L expression in relation to EMT marker expression in patient samples

• Therapeutic targeting: Test whether inhibiting ARHGEF10L-RhoA-ROCK signaling can reverse EMT in established tumors

This comprehensive approach will provide mechanistic insights into how ARHGEF10L coordinates EMT programs across different cancer contexts and may reveal new intervention points for preventing metastatic progression .

What methodological approaches are most effective for analyzing the interplay between ARHGEF10L and heat shock proteins in cancer cell stress responses?

The emerging connection between ARHGEF10L and heat shock proteins (particularly HSPA6) requires sophisticated methodological approaches:

Expression correlation analysis:

• Co-expression profiling: Systematically quantify ARHGEF10L and HSPA6 expression across cell lines and patient samples using qRT-PCR and Western blotting

• Single-cell RNA-seq: Determine whether ARHGEF10L and HSPA6 are co-regulated at the single-cell level within heterogeneous populations

• Promoter analysis: Examine whether common transcription factors regulate both genes

Causal relationship determination:

• Sequential manipulation: Establish the temporal order by:

  • Testing whether ARHGEF10L overexpression induces HSPA6 (as observed in previous studies)

  • Determining whether HSPA6 knockdown affects ARHGEF10L expression

  • Creating rescue experiments with HSPA6 overexpression in ARHGEF10L-depleted cells

• Promoter reporter assays: Use HSPA6 promoter-luciferase constructs to test direct transcriptional activation by ARHGEF10L signaling

Stress response integration:

• Heat shock experiments: Compare cellular responses to heat shock between:

  • ARHGEF10L-overexpressing cells

  • ARHGEF10L-knockdown cells

  • Control cells

• Other stress inducers: Test responses to:

  • Proteotoxic stress (proteasome inhibitors)

  • Oxidative stress (H₂O₂, paraquat)

  • ER stress (tunicamycin, thapsigargin)

  • Hypoxia

Molecular mechanism exploration:

• Protein interaction studies: Investigate physical interactions between:

  • ARHGEF10L and heat shock proteins (co-IP, proximity ligation assay)

  • ARHGEF10L and heat shock transcription factors (HSF1)

• RhoA-dependency: Determine whether HSPA6 induction requires RhoA activation using dominant-negative RhoA or RhoA inhibitors

Functional consequence analysis:

• Chaperone activity: Measure protein aggregation and refolding efficiency in relation to ARHGEF10L/HSPA6 levels

• Apoptosis resistance: Quantify cell survival under stress conditions with varying ARHGEF10L/HSPA6 expression

• Therapeutic resistance: Test whether ARHGEF10L-mediated HSPA6 induction affects sensitivity to chemotherapeutics

Translational potential assessment:

• Combined targeting strategies: Test HSP inhibitors in combination with RhoA pathway inhibitors

• Biomarker potential: Evaluate whether ARHGEF10L/HSPA6 co-expression predicts therapeutic response

• Patient stratification: Analyze whether high ARHGEF10L/HSPA6 co-expression defines specific patient subgroups