Phospho-STMN1 (S62) Antibody

What is STMN1 and its phosphorylated form at Serine 62?

STMN1 (Stathmin 1) is a 17kDa cytoplasmic phosphoprotein that regulates microtubule dynamics through two primary mechanisms: promoting microtubule catastrophe and sequestering free tubulin heterodimers . The protein contains multiple phosphorylation sites, including Serine 62 (Ser62), which significantly affects its function. Phosphorylation at Ser62 is one of several post-translational modifications that regulate STMN1's interaction with microtubules and its subsequent biological activities . This specific phosphorylation contributes to cell cycle regulation, cell migration, and other cellular processes critical to both normal function and disease states.

What are the standard applications for Phospho-STMN1 (S62) antibodies in research?

Phospho-STMN1 (S62) antibodies are versatile tools employed across multiple experimental techniques including:

When designing experiments, researchers should validate the antibody specificity by confirming it detects STMN1 only when phosphorylated at Ser62 and not in its unphosphorylated state or when phosphorylated at other sites (Ser16, Ser25, Ser38, or Ser63) . The antibody's capacity to detect endogenous levels of phosphorylated protein makes it particularly valuable for studying physiological conditions without requiring overexpression systems.

How should Phospho-STMN1 (S62) antibodies be stored and handled to maintain optimal activity?

For maximum antibody performance and longevity, follow these evidence-based handling protocols:

• Initial receipt: Antibodies are typically shipped at 4°C in stabilizing buffer containing phosphate-buffered saline (PBS without Mg²⁺ and Ca²⁺, pH 7.4), with 150mM NaCl, 0.02% sodium azide, and 50% glycerol .

• Long-term storage: Upon delivery, aliquot the antibody solution into smaller volumes to minimize freeze-thaw cycles. Store aliquots at -20°C .

• Working practices:

  • Limit freeze-thaw cycles to fewer than 5

  • Thaw aliquots on ice

  • Keep the antibody at 4°C during experimental procedures

  • Return to -20°C promptly after use

Research has demonstrated that repeated freeze-thaw cycles significantly reduce antibody binding capacity, with each cycle potentially decreasing activity by 5-10%. Creating multiple small aliquots immediately upon receipt represents best practice for preserving antibody function over extended periods.

What optimization strategies are recommended for Western blotting with Phospho-STMN1 (S62) antibodies?

Optimizing Western blotting protocols for phospho-specific antibodies requires special attention to several parameters:

• Sample preparation:

  • Include phosphatase inhibitors (e.g., sodium orthovanadate, sodium fluoride) in lysis buffers

  • Process samples quickly and maintain at 4°C to prevent dephosphorylation

  • Consider using membrane crosslinking with 0.25% glutaraldehyde for 10 minutes at room temperature in TTBS to preserve phospho-epitopes

• Blocking conditions:

  • Use 5% non-fat dry milk in TTBS for general blocking

  • For enhanced specificity, consider 3-5% BSA in TTBS as alternative blocking agent

• Antibody incubation:

  • Start with 1:500 dilution and adjust based on signal intensity

  • Incubate overnight at 4°C for optimal sensitivity

  • Use gentle rocking to ensure even antibody distribution

• Detection optimization:

  • For low abundance phosphorylated proteins, employ enhanced chemiluminescence (ECL) substrates with extended sensitivity

  • Consider using secondary antibodies conjugated to HRP for standard detection methods

When troubleshooting, evaluate both positive controls (e.g., cell lysates with known STMN1 phosphorylation at Ser62) and negative controls (e.g., samples treated with phosphatase or from cells with STMN1 knockout).

How does Ser62 phosphorylation of STMN1 compare functionally to phosphorylation at other serine residues?

STMN1 contains four phosphorylatable serine residues (Ser16, Ser25, Ser38, and Ser62), each with distinct functional impacts:

Research has shown that phosphorylation at Ser62 interacts with other phosphorylation events, particularly at Ser16, creating complex regulatory patterns . In breast cancer studies, patients with specific phosphorylation signatures showed differential responses to paclitaxel-based chemotherapy, with high-risk patients receiving only 28% of the benefit compared to low-risk patients .

Functionally, Ser62 phosphorylation appears to modulate STMN1's interaction with tubulin in ways distinct from other phosphorylation sites, potentially affecting its role in cell division and migration. Unlike phosphorylation at Ser16 and Ser63, which are generally associated with better clinical outcomes, the impact of Ser62 phosphorylation appears more context-dependent .

What experimental approaches are effective for studying STMN1 phosphorylation dynamics in live cells?

Investigating phosphorylation dynamics requires specialized techniques beyond static antibody-based detection. Recommended approaches include:

• CRISPR/Cas9-mediated phospho-mutant generation:

  • Create serine-to-alanine (S→A) mutations to prevent phosphorylation

  • Create serine-to-aspartate (S→D) mutations to mimic constitutive phosphorylation

  • Compare phenotypic outcomes between wild-type, S→A, and S→D mutants

• Phosphorylation-specific biosensors:

  • Develop FRET-based sensors incorporating STMN1 domains

  • Monitor real-time phosphorylation changes in response to stimuli

  • Correlate phosphorylation status with cellular behaviors (migration, division)

• Photoactivatable phosphatase inhibitors:

  • Apply targeted control of phosphorylation state in specific cellular regions

  • Analyze spatial and temporal dynamics of STMN1 function

• Kinase/phosphatase manipulation:

  • Identify and modulate activity of kinases targeting Ser62

  • Use specific inhibitors to isolate phosphorylation events at individual sites

  • Apply p38MAPK activators/inhibitors to study feedback mechanisms, as p38MAPK activation has been shown to affect STMN1 phosphorylation states

These approaches allow researchers to move beyond correlation to establish causative relationships between STMN1 phosphorylation status and cellular functions. For example, in prostate cancer cell lines, manipulating STMN1 phosphorylation through CRISPR/Cas9 revealed distinct effects on metastatic potential, providing mechanistic insights beyond what static antibody detection could reveal .

How can researchers distinguish between cause and effect when studying STMN1 phosphorylation in cancer progression?

Establishing causal relationships requires sophisticated experimental designs:

• Temporal analysis frameworks:

  • Employ inducible expression systems to control timing of phospho-mutant expression

  • Monitor cellular changes at defined intervals following expression

  • Correlate phosphorylation kinetics with phenotypic progression

• Rescue experiments:

  • Deplete endogenous STMN1 using siRNA/shRNA targeting untranslated regions

  • Re-express phospho-site mutants resistant to silencing

  • Determine which phosphorylation sites are necessary and sufficient for specific phenotypes

• Pathway dissection:

  • Implement systems biology approaches including phosphoproteomics

  • Map signaling networks upstream and downstream of STMN1

  • Use inhibitor panels to distinguish primary from secondary effects

• In vivo validation strategies:

  • Develop xenograft models with phospho-mutant STMN1 variants

  • Track tumor growth, invasion, and metastasis parameters

  • Correlate with clinical samples using tissue microarrays and phospho-specific antibodies

Research using these methods has revealed that STMN1 phosphorylation status influences cancer progression through multiple mechanisms. For example, studies in non-small cell lung cancer showed that STMN1 promotes metastasis through both microtubule-dependent and non-microtubule-dependent mechanisms, with phosphorylation at Ser16 playing a critical role in this process .

What are the methodological considerations for analyzing STMN1 phosphorylation in primary tissue samples?

Working with primary tissues presents unique challenges that require specialized protocols:

• Specimen preservation:

  • Process samples immediately after collection to prevent phosphoprotein degradation

  • Use phosphatase inhibitors in all buffers

  • Consider heat stabilization or snap-freezing to preserve phosphorylation state

• Extraction optimization:

  • Compare different tissue homogenization methods (mechanical, enzymatic, ultrasonic)

  • Optimize buffer composition for phosphoprotein recovery

  • Fractionate cellular components to enrich for cytoskeletal/cytoplasmic fractions

• Multiplexed detection strategies:

  • Employ multi-color immunofluorescence to simultaneously detect multiple phosphorylation sites

  • Use spectral unmixing to distinguish between closely related epitopes

  • Implement tissue microarray technology for high-throughput analysis

• Validation approaches:

  • Confirm antibody specificity using phosphatase treatment controls

  • Include isotype controls to assess non-specific binding

  • Compare results across multiple detection platforms (IHC, WB, MS)

Studies using these approaches revealed significant differences in phosphorylation patterns between tumor and non-tumor tissues. For example, analysis of lung adenocarcinoma samples showed that while total STMN1 protein was higher in tumors, phosphorylation at Ser16 and Ser25 was actually higher in non-tumor tissues, highlighting the complexity of STMN1 regulation in cancer .

How can Phospho-STMN1 (S62) status be integrated into predictive models for cancer treatment response?

Developing clinically relevant predictive models requires a multifaceted approach:

• Multiparameter scoring systems:

  • Integrate STMN1 expression with phosphorylation status at multiple sites

  • Develop weighted algorithms based on prognostic significance

  • Create risk stratification models that include clinicopathological characteristics

• Machine learning integration:

  • Train algorithms using phosphorylation data from patient cohorts

  • Identify patterns not evident through conventional statistics

  • Validate models through independent patient cohorts

• Treatment response correlation:

  • Track phosphorylation changes before and during treatment

  • Correlate dynamic changes with clinical outcomes

  • Identify phosphorylation signatures predictive of response to specific therapies

Research has demonstrated the potential of this approach through the development of a "STMN1 expression signature and phosphorylation profile plus clinicopathological characteristics" (STMN1-E/P/C) model in breast cancer . This model was able to predict response to paclitaxel-based chemotherapy, with high-risk patients receiving only 28% of the benefit compared to low-risk patients. The HR of interaction between the risk score and paclitaxel-based chemotherapy was 3.532, indicating a strong predictive value .

What methodological approaches can determine if STMN1 phosphorylation is a viable therapeutic target?

Evaluating STMN1 phosphorylation as a therapeutic target requires systematic validation:

• Target validation hierarchy:

  • Genetic manipulation (CRISPR/Cas9, siRNA) to establish necessity

  • Phospho-mimetic mutations to establish sufficiency

  • Small molecule modulation to establish druggability

  • In vivo models to establish physiological relevance

• Rational drug design approaches:

  • Structure-based design targeting phosphorylation sites

  • Development of conformation-specific inhibitors

  • Allosteric modulators affecting kinase accessibility

• Combination therapy rationales:

  • Identify synergistic interactions with established therapies

  • Test sequencing strategies (e.g., sensitization before cytotoxics)

  • Develop biomarker-guided combination approaches

• Resistance mechanism prediction:

  • Map compensatory phosphorylation events

  • Identify alternative pathways activated upon STMN1 inhibition

  • Develop strategies to prevent or overcome resistance

Ongoing research has shown promising results in targeting STMN1 phosphorylation to inhibit cancer metastasis. For example, studies in prostate cancer have used CRISPR/Cas9 to generate Stmn1 phospho-mutant cell lines to evaluate the impact on metastatic potential . Similarly, work in non-small cell lung cancer has demonstrated that STMN1 promotes metastasis through both microtubule-dependent and independent mechanisms, suggesting multiple intervention points .

How does STMN1 phosphorylation at Ser62 influence cellular functions beyond microtubule dynamics?

Recent research has uncovered non-canonical roles of phosphorylated STMN1:

• Signaling pathway integration:

  • STMN1 activates the p38MAPK/STAT1 signaling pathway independent of microtubule stability

  • A positive feedback loop exists between STMN1 and p38MAPK, which synergistically promotes cell migration

  • Phosphorylation status affects STMN1's ability to interact with signaling components

• Mitochondrial function regulation:

  • Loss of Stathmin 1 is associated with defective mitochondrial structure and function

  • STMN1 has been identified as a novel regulator of mitophagy and mitochondrial health

  • The phosphorylation state may determine STMN1's impact on mitochondrial dynamics

• Stem cell maintenance mechanisms:

  • STMN1 is highly expressed in hematopoietic stem cells (HSCs)

  • Its loss is associated with altered microtubule architecture and impaired HSC function

  • Phosphorylation at different sites may differentially affect stem cell properties

These findings suggest that targeting STMN1 phosphorylation could have broader implications beyond affecting microtubule dynamics, potentially impacting multiple cellular processes simultaneously. For example, research in hematopoietic stem cells revealed that Stathmin 1 deficiency led to impaired mitophagy, with stimulation of autophagy improving the colony-forming ability of Stmn1-/- hematopoietic stem and progenitor cells .

What are the latest technological advances for studying site-specific phosphorylation dynamics in vivo?

Cutting-edge technologies are transforming phosphorylation research:

• Advanced imaging technologies:

  • Super-resolution microscopy to visualize phosphorylation events at nanoscale resolution

  • Intravital microscopy for real-time phosphorylation dynamics in living organisms

  • Correlative light and electron microscopy to connect phosphorylation with ultrastructural changes

• Mass spectrometry innovations:

  • Targeted parallel reaction monitoring for absolute quantification of phosphopeptides

  • Cross-linking mass spectrometry to capture phosphorylation-dependent interactions

  • Top-down proteomics to analyze intact phosphoproteins with multiple modifications

• Genetically encoded biosensors:

  • Development of site-specific phosphorylation sensors with improved signal-to-noise ratios

  • Multiplexed sensors for simultaneous monitoring of multiple phosphorylation sites

  • Integration with optogenetic tools for spatiotemporal control of phosphorylation

• Single-cell phosphoproteomics:

  • Methods to analyze phosphorylation states in individual cells

  • Integration with transcriptomics for multi-omics analysis

  • Spatial phosphoproteomics to map phosphorylation events within tissue architecture