SSR2 Human

What is SSR2 and what is its genomic location in humans?

SSR2 (signal sequence receptor subunit 2) is a 22-kD glycoprotein that functions as a component of the signal sequence receptor (SSR) complex in the endoplasmic reticulum (ER) membrane. The SSR complex consists of multiple subunits, with SSR2 serving as the beta subunit (also known as TRAPB or TRAP-BETA) . The human SSR2 gene is located on chromosome 1q22 and consists of 6 exons spanning approximately 11,903 base pairs (156009048..156020951 on the complementary strand) . SSR2 is one of four subunits (SSR1-4) that comprise the complete SSR protein complex, with each playing distinct roles in protein processing .

What is the normal physiological function of SSR2 in human cells?

SSR2 functions primarily as part of the protein translocation machinery in the endoplasmic reticulum. The SSR complex is a glycosylated ER membrane receptor associated with protein translocation across the ER membrane . Specifically, SSR2 works in conjunction with other SSR subunits (particularly SSR1, a 34-kD glycoprotein) to facilitate the movement of nascent polypeptides into or across the ER membrane during protein synthesis . This process is crucial for the proper folding and processing of secretory and membrane proteins. Additionally, SSR2 has been reported to be involved in the unfolded protein response (UPR) on the endoplasmic reticulum, participating in cellular responses to ER stress . Its role in protein translocation makes it an essential component for maintaining cellular proteostasis under both normal and stress conditions.

How is SSR2 expression regulated in normal tissues versus cancer tissues?

The regulation of SSR2 appears to involve the Unfolded Protein Response (UPR) pathway, particularly through X-Box Binding Protein 1s (XBP1s) . Under ER stress conditions, which are common in rapidly proliferating cancer cells, XBP1s is activated and acts as a transcriptional regulator of SSR2 . This creates an "ER stress-UPR-Transcription Factor XBP1s-SSR2 response axis" that drives SSR2 overexpression in cancer cells . Additionally, SSR2 upregulation has been observed upon development of therapy resistance to BRAF inhibitors in melanoma, suggesting that treatment-induced stress can further enhance SSR2 expression .

What evidence links SSR2 overexpression to hepatocellular carcinoma progression?

Multiple lines of evidence establish SSR2 as a significant factor in hepatocellular carcinoma (HCC) progression:

Expression analysis: Both public databases and independently collected patient samples have confirmed SSR2 overexpression in HCC tissues. Immunohistochemistry studies showed elevated SSR2 protein levels in tumor tissues compared to adjacent normal tissues . Quantitative PCR analysis of patient samples further confirmed increased SSR2 mRNA expression in HCC tumors .

Clinical correlations: SSR2 expression levels strongly associate with important clinical parameters including encapsulation invasion and tumor grade, suggesting its involvement in more aggressive disease phenotypes .

Functional studies: In vitro experiments demonstrated that SSR2 knockdown significantly inhibits cell proliferation, migration, and invasion abilities while promoting apoptosis and cell cycle arrest in HCC cell lines . These findings directly implicate SSR2 in tumorigenic processes.

Molecular mechanisms: SSR2 knockdown suppresses epithelial-mesenchymal transition (EMT) in HCC cells, providing a mechanistic explanation for how SSR2 contributes to metastatic potential . The ability to modulate EMT, a critical process for cancer cell dissemination, underscores SSR2's importance in disease progression.

How does SSR2 expression correlate with patient survival outcomes in cancer?

SSR2 expression demonstrates significant prognostic value across multiple cancer types, with consistent associations between high expression and poor patient outcomes:

In melanoma: High expression levels of SSR2 are associated with unfavorable disease outcomes in primary melanoma patients . This correlation is particularly pronounced in therapy-resistant melanoma, where SSR2 appears to play a crucial role in adaptive resistance mechanisms .

Statistical quantification: Survival analyses typically employ Kaplan-Meier methods with log-rank tests to compare high versus low SSR2 expression groups . These analyses consistently demonstrate significant survival differences, with high SSR2 expression patients showing markedly shorter survival times across multiple independent cohorts .

Hazard ratios: Cox proportional hazards models quantify the increased risk associated with high SSR2 expression, typically showing hazard ratios greater than 1, confirming SSR2 as a risk factor for poor outcomes .

These findings collectively establish SSR2 as a clinically relevant biomarker with significant implications for patient prognosis across different cancer types, particularly in HCC and melanoma.

What mechanisms underlie SSR2's contribution to cancer metastasis?

SSR2 promotes cancer metastasis through several interconnected molecular mechanisms:

Epithelial-Mesenchymal Transition (EMT) regulation: Research has demonstrated that SSR2 knockdown suppresses EMT in HCC cells, a critical process for cancer metastasis . Western blot analysis showed that silencing SSR2 alters the expression of EMT markers, likely shifting cancer cells from a mesenchymal (migratory) state back toward an epithelial (stationary) state .

Enhanced migration and invasion: Functional studies using transwell assays have confirmed that SSR2 is critical for the migration and invasion capabilities of cancer cells . When SSR2 is silenced, these metastasis-related behaviors are significantly reduced .

ER stress adaptation: SSR2's role in the unfolded protein response (UPR) pathway may provide cancer cells with adaptive mechanisms to survive the stresses associated with metastatic spread . This stress adaptation function may be particularly important during the colonization phase of metastasis .

Therapy resistance promotion: In melanoma, SSR2 upregulation has been observed upon development of resistance to BRAF inhibitors, suggesting SSR2 contributes to therapy-resistant phenotypes that are often more aggressive and metastatic .

Clinical correlation with invasive features: SSR2 expression is significantly associated with encapsulation invasion in HCC patients, providing direct clinical evidence of its relationship with invasive disease features .

These mechanistic insights reveal SSR2 as a multifaceted promoter of cancer metastasis, influencing fundamental cellular processes that enable cancer cells to detach from primary tumors, survive in circulation, and establish distant metastases.

What techniques are most effective for analyzing SSR2 expression in patient samples?

Multiple complementary techniques can be employed for comprehensive analysis of SSR2 expression in patient samples:

Immunohistochemistry (IHC): This technique has been successfully used to analyze SSR2 protein expression in tissue microarrays constructed from HCC tumor and adjacent tissues . IHC allows visualization of SSR2 expression patterns within the tissue architecture and enables semi-quantitative scoring based on staining intensity and percentage of positive cells . The approach permits direct comparison between tumor and corresponding non-tumor tissues within the same patient.

Quantitative PCR (qPCR): This method provides sensitive quantification of SSR2 mRNA expression levels . Studies have employed qPCR to validate elevated SSR2 transcript levels in tumor tissues compared to adjacent normal tissues . The technique requires high-quality RNA extraction and appropriate normalization to reference genes for accurate results.

RNA-Seq and transcriptomic analysis: High-throughput RNA sequencing enables comprehensive analysis of SSR2 expression within the broader transcriptomic context . This approach allows identification of differentially expressed genes (DEGs) associated with SSR2 expression levels by comparing SSR2-high versus SSR2-low patient cohorts . RNA-Seq data can also be used for pathway enrichment analysis to understand the biological significance of SSR2 expression patterns.

Public database mining: Leveraging cancer genomics databases such as TCGA and GEPIA provides access to large-scale expression data across multiple cancer types . These resources enable boxplot and scatter plot visualizations of SSR2 expression based on disease state, TNM classification, pathological stage, and other clinical variables . This approach is particularly valuable for initial discovery and hypothesis generation.

For optimal results, researchers should employ multiple complementary techniques. In published studies, the combination of public database mining, qPCR validation in patient samples, IHC on tissue microarrays, and correlation with clinical parameters has provided robust characterization of SSR2's expression patterns and clinical significance in cancer .

What are the optimal methods for studying SSR2 knockdown effects in cancer models?

Several approaches can be employed to study SSR2 knockdown effects in cancer models, each with specific advantages:

RNA interference (RNAi): siRNA transfection has been successfully used to silence SSR2 expression in cancer cell lines . Published studies typically transfect specific siRNAs targeting SSR2 using transfection reagents like Lipofectamine 2000 . This approach provides efficient transient knockdown lasting 48-72 hours, ideal for short-term functional experiments. Western blotting is commonly used to validate knockdown efficiency at the protein level .

Functional assays post-knockdown: Following SSR2 silencing, several functional assays have proven effective:

• Cell proliferation: IncuCyte live-cell imaging systems can continuously monitor growth curves of SSR2-knockdown versus control cells .

• Migration and invasion: Transwell assays effectively quantify these metastasis-related capabilities after SSR2 silencing .

• Apoptosis and cell cycle: Flow cytometry with appropriate staining (Annexin V/PI for apoptosis; PI for cell cycle) can assess these parameters .

• EMT marker expression: Western blotting for epithelial markers (E-cadherin) and mesenchymal markers (N-cadherin, vimentin) reveals SSR2's impact on EMT .

Model selection considerations: Research has demonstrated successful SSR2 knockdown experiments in:

• HCC cell lines: Studies have utilized established hepatocellular carcinoma cell lines .

• Melanoma models: Particularly relevant for investigating therapy resistance connections .

• BRAF inhibitor-resistant cell lines: These models reveal SSR2's role in therapy resistance .

Validation approaches: Multiple validation strategies should be employed:

• Using multiple independent siRNA sequences targeting different regions of SSR2 to confirm specificity.

• Rescue experiments with siRNA-resistant SSR2 expression constructs to verify on-target effects.

• Complementary approaches (e.g., CRISPR-Cas9 for more permanent knockout) to confirm findings from transient knockdown.

These methodological approaches have successfully revealed SSR2's functional roles in cancer cell proliferation, migration, invasion, and EMT, establishing it as an important factor in cancer progression .

How can researchers investigate the relationship between SSR2 and the unfolded protein response (UPR)?

Investigating the relationship between SSR2 and the unfolded protein response (UPR) requires specialized experimental approaches that capture both regulatory mechanisms and functional consequences:

UPR induction models:

• Chemical inducers: Treat cells with established UPR activators such as tunicamycin (inhibits N-linked glycosylation), thapsigargin (disrupts calcium homeostasis), or DTT (reduces disulfide bonds) .

• Physiological stressors: Create ER stress conditions through glucose deprivation, hypoxia, or amino acid limitation .

• Therapeutic stress: BRAF inhibitor treatment in melanoma cells has been shown to induce ER stress and affect SSR2 expression .

• Time-course experiments: Distinguish between acute and chronic UPR activation effects on SSR2 expression.

Gene regulation analysis:

• XBP1s-SSR2 axis: Research has established X-Box Binding Protein 1s (XBP1s) as a transcriptional regulator of SSR2 . This can be investigated through:

  • ChIP assays to detect XBP1s binding to the SSR2 promoter

  • Reporter assays with SSR2 promoter constructs

  • XBP1s overexpression or knockdown experiments to manipulate this axis

• UPR branch specificity: Selectively activate or inhibit individual UPR branches (IRE1α-XBP1, PERK-eIF2α, ATF6) to determine which specifically regulates SSR2 .

Functional relationship studies:

• SSR2 manipulation during ER stress: Compare UPR outcomes (cell survival, protein aggregation, etc.) with and without SSR2 knockdown during ER stress conditions .

• Recovery experiments: Assess how SSR2 affects the resolution of ER stress during recovery phases.

• Protein translocation efficiency: Measure how SSR2 levels affect protein processing during ER stress using pulse-chase experiments.

Cancer-specific context:

• Therapy resistance models: Study how BRAF inhibitor resistance in melanoma connects to the SSR2-UPR relationship .

• Patient sample correlation: Analyze correlations between SSR2 expression and UPR markers in patient samples.

• Combinatorial targeting: Test how targeting both SSR2 and UPR components affects cancer cell survival.

These approaches have revealed what research describes as an "ER stress-UPR-Transcription Factor XBP1s-SSR2 response axis" in human cells, establishing SSR2 as an important component of the cellular response to ER stress, particularly in cancer contexts .

What evidence supports SSR2 as a potential therapeutic target in cancer?

Multiple lines of evidence establish SSR2 as a promising therapeutic target in cancer:

Differential expression and dependency:

• SSR2 is significantly overexpressed in multiple cancer types, including hepatocellular carcinoma and melanoma .

• Research explicitly notes that SSR2 shows "dispensability for survival in normal human cells," suggesting a potential therapeutic window between cancer and normal cells .

• BRAF inhibitor-resistant melanoma cells demonstrate particular dependency on SSR2 for survival .

Functional impact of targeting:

• SSR2 knockdown significantly inhibits cancer cell proliferation, migration, and invasion capabilities .

• Silencing SSR2 promotes apoptosis and cell cycle arrest in cancer cells .

• These effects directly impact key hallmarks of cancer, suggesting therapeutic potential.

Clinical correlations:

• High SSR2 expression strongly correlates with poor prognosis in cancer patients .

• SSR2 is associated with aggressive clinical features including encapsulation invasion and higher tumor grade .

• These correlations suggest targeting SSR2 could impact clinically relevant disease aspects.

Therapy resistance connections:

• SSR2 upregulation occurs upon development of resistance to BRAF inhibitors in melanoma .

• Therapy-resistant cells show increased dependency on SSR2 for survival .

• This indicates SSR2 targeting could address a major clinical challenge in cancer treatment.

Mechanistic rationale:

• SSR2's role in epithelial-mesenchymal transition (EMT) makes it relevant for anti-metastatic strategies .

• Its position in the UPR pathway suggests targeting SSR2 could disrupt adaptive responses that cancer cells depend on .

• Research explicitly concludes that "Targeting SSR2 might be feasible for curbing the progression and metastasis of HCC" .

These findings collectively establish SSR2 as a cancer-relevant target with potential advantages of differential requirements between cancer and normal cells, functional impacts on key cancer processes, and relevance to therapy resistance mechanisms .

What experimental approaches should be used to validate SSR2 as a drug target?

Validating SSR2 as a drug target requires a comprehensive experimental approach addressing multiple aspects of target suitability:

Target validation in diverse models:

• Expanded knockdown studies: Beyond initial siRNA experiments, implement CRISPR-Cas9 knockout and inducible shRNA systems across diverse cancer cell lines to confirm consistent effects .

• Patient-derived models: Test SSR2 dependency in patient-derived xenografts and primary cell cultures to ensure relevance to human disease .

• Normal cell panels: Systematically evaluate effects of SSR2 silencing across comprehensive panels of normal human cells to confirm the therapeutic window suggested by preliminary data .

• In vivo models: Develop conditional SSR2 knockout mouse models or inducible knockdown xenograft systems to assess systemic effects of SSR2 inhibition.

Mechanism-based studies:

• Structure-function analysis: Determine which domains or activities of SSR2 are critical for its cancer-promoting functions.

• Interaction mapping: Identify key protein-protein interactions that could be targeted with small molecules or peptides .

• Connectivity mapping: Test whether existing drugs produce gene expression signatures similar to SSR2 knockdown to identify potential repurposing opportunities.

Biomarker development:

• Predictive biomarkers: Identify molecular features that predict dependency on SSR2 (e.g., UPR activation status, XBP1s levels) .

• Pharmacodynamic markers: Develop assays to measure target engagement and functional impact of SSR2 inhibition.

• Patient stratification strategies: Determine which cancer subtypes or molecular profiles show highest SSR2 dependency.

Combination approaches:

• Synthetic lethality screens: Identify genes that, when inhibited alongside SSR2, produce enhanced anti-cancer effects.

• Established therapy combinations: Test SSR2 targeting in combination with standard therapies (e.g., BRAF inhibitors in melanoma) .

• Resistance mechanism exploration: Investigate potential resistance mechanisms to SSR2 inhibition to inform combination strategies.

Proof-of-concept therapeutic approaches:

• Antisense oligonucleotides: Design and test ASOs targeting SSR2 in preclinical models.

• Small molecule screening: Develop assays suitable for high-throughput screening to identify SSR2 inhibitors.

• Structure-based drug design: If structural data becomes available, pursue rational design of SSR2 inhibitors.

These multifaceted validation approaches will provide comprehensive evidence regarding SSR2's suitability as a drug target and guide the development of effective therapeutic strategies .

What are the potential challenges and limitations in targeting SSR2 therapeutically?

Developing therapies targeting SSR2 faces several significant challenges that researchers must consider:

Target biology complexity:

• ER membrane localization: SSR2 is embedded in the endoplasmic reticulum membrane, potentially limiting accessibility to certain therapeutic modalities .

• Fundamental cellular process: SSR2's role in protein translocation raises concerns about complete inhibition in normal tissues .

• Redundancy potential: Other components of the SSR complex (SSR1, SSR3, SSR4) might compensate for SSR2 inhibition .

Therapeutic window considerations:

• Differential dependency: While research suggests SSR2 is "dispensable for survival in normal human cells," this requires comprehensive validation across diverse normal cell types .

• Tissue-specific effects: Certain normal tissues with high secretory activity might be more sensitive to SSR2 inhibition.

• Long-term consequences: Chronic SSR2 inhibition effects remain unknown and require careful evaluation.

Technical and delivery challenges:

• Druggability: As a membrane protein, SSR2 may present challenges for small molecule development.

• Delivery methods: For RNA-based approaches (siRNA, antisense), effective delivery to tumor cells remains challenging.

• Tumor penetration: Ensuring therapeutic agents reach all tumor cells, particularly in poorly vascularized regions.

Resistance mechanisms:

• Adaptive UPR responses: Cancer cells might activate alternative UPR pathways to compensate for SSR2 inhibition .

• Protein translocation adaptations: Cells might upregulate alternative protein processing mechanisms.

• Target modifications: Mutations in SSR2 could emerge that prevent therapeutic binding while maintaining function.

Clinical development considerations:

• Patient selection: Identifying which patients would benefit most from SSR2-targeted therapy requires biomarker development.

• Combination strategies: Determining optimal therapeutic combinations needs systematic evaluation.

• Safety monitoring: Given SSR2's role in fundamental cellular processes, careful toxicity assessment is essential.

Despite these challenges, the strong association between SSR2 overexpression and poor clinical outcomes, combined with evidence of differential requirements between cancer and normal cells, justifies continued exploration of SSR2 as a therapeutic target . Addressing these limitations through systematic research will be crucial for successful translation to clinical applications.

What are the key unanswered questions about SSR2's role in human cancer?

Despite significant progress in understanding SSR2's involvement in cancer, several critical questions remain unanswered:

Mechanistic questions:

• How does SSR2 specifically influence the epithelial-mesenchymal transition (EMT) at the molecular level?

• What are the direct protein interactors of SSR2 that mediate its pro-tumorigenic effects?

• How does SSR2 contribute to therapy resistance mechanisms beyond BRAF inhibitor resistance in melanoma?

• What is the complete signaling network downstream of SSR2 that promotes cancer progression?

Cancer type specificity:

• Why does SSR2 appear particularly important in hepatocellular carcinoma and melanoma?

• Does SSR2 play similar roles across all cancer types where it's overexpressed?

• Are there cancer contexts where SSR2 is not oncogenic or might have opposite effects?

Clinical translation questions:

• Which patient subpopulations would benefit most from SSR2-targeted therapies?

• What biomarkers can predict dependency on SSR2 in human tumors?

• How does SSR2 expression change during cancer progression from early to advanced stages?

Regulatory mechanisms:

• Beyond XBP1s, what other factors regulate SSR2 expression in cancer?

• Are there cancer-specific alterations (mutations, amplifications) in SSR2 that enhance its function?

• How do epigenetic mechanisms contribute to SSR2 dysregulation in cancer?

Therapeutic implications:

• What is the most effective approach to therapeutically target SSR2?

• How might resistance to SSR2 inhibition develop, and how can it be prevented?

• What combination strategies would maximize the efficacy of SSR2 targeting?

These questions represent important areas for future investigation that would enhance our understanding of SSR2's role in cancer and potentially lead to novel therapeutic strategies targeting this protein .

How might advanced technologies improve our understanding of SSR2 biology?

Advanced technologies offer promising approaches to deepen our understanding of SSR2 biology:

Single-cell omics technologies:

• Single-cell RNA sequencing can reveal heterogeneity in SSR2 expression within tumors and identify cell populations most dependent on SSR2 .

• Single-cell proteomics could map SSR2 protein levels alongside key signaling pathways at cellular resolution.

• Spatial transcriptomics would place SSR2 expression in the context of tumor microenvironment features.

CRISPR-based functional genomics:

• Genome-wide CRISPR screens in SSR2-high versus SSR2-low backgrounds could identify synthetic lethal interactions.

• CRISPR activation/inhibition screens targeting transcription factors might discover additional regulators of SSR2 beyond XBP1s .

• Base editing approaches could introduce specific mutations to dissect structure-function relationships.

Advanced imaging techniques:

• Super-resolution microscopy could visualize SSR2's precise localization and dynamics within the ER membrane.

• Live-cell imaging with fluorescently tagged SSR2 would reveal its behavior during ER stress and cancer cell processes.

• Correlative light and electron microscopy could connect SSR2 distribution with ultrastructural changes in the ER.

Structural biology approaches:

• Cryo-electron microscopy might determine the structure of SSR2 within the complete SSR complex.

• Hydrogen-deuterium exchange mass spectrometry could map conformational changes during protein translocation.

• Integrative structural biology combining multiple techniques would provide a comprehensive structural understanding.

Systems biology integration:

• Multi-omics data integration across transcriptomics, proteomics, and metabolomics could place SSR2 in broader cellular networks .

• Mathematical modeling of the UPR-XBP1s-SSR2 axis would predict system behaviors under various perturbations .

• Network analysis algorithms applied to large datasets could identify previously unrecognized connections involving SSR2.

Emerging therapeutic technologies:

• Proteolysis-targeting chimeras (PROTACs) could enable targeted degradation of SSR2 protein.

• RNA targeting approaches (including ASOs and siRNAs) with advanced delivery systems could provide precise modulation of SSR2 levels.

• Computational drug design leveraging emerging structural data could accelerate development of SSR2 inhibitors.

These advanced technologies would provide unprecedented insights into SSR2's structure, regulation, interactions, and functions in both normal and cancer contexts, potentially revealing new therapeutic opportunities .

What is the current consensus on SSR2's significance in cancer biology?

The current consensus on SSR2's significance in cancer biology has solidified around several key points:

SSR2 as a cancer-promoting factor:

• Multiple independent studies have established SSR2 overexpression in various cancer types, particularly hepatocellular carcinoma and melanoma .

• Functional studies consistently demonstrate that SSR2 promotes cancer cell proliferation, migration, and invasion while inhibiting apoptosis .

• SSR2 knockdown consistently suppresses cancer cell growth and metastatic potential across different experimental systems .

Clinical significance:

Mechanistic understanding:

• SSR2 functions within the ER stress-UPR-XBP1s regulatory axis, linking cellular stress response to cancer progression .

• It plays a role in regulating epithelial-mesenchymal transition (EMT), a key process in cancer metastasis .

• SSR2 contributes to therapy resistance mechanisms, particularly in BRAF inhibitor-resistant melanoma .

Therapeutic potential:

• Evidence supports a differential requirement for SSR2 between cancer cells and normal cells, suggesting a potential therapeutic window .

• SSR2 dependency appears particularly pronounced in therapy-resistant contexts .

• Multiple studies conclude that SSR2 represents a promising target for cancer therapy development .

What recommendations can be made for researchers beginning work on SSR2?

Researchers beginning work on SSR2 should consider the following evidence-based recommendations:

Experimental design considerations:

• Utilize multiple complementary techniques to assess SSR2 expression, including qPCR, Western blotting, and immunohistochemistry for comprehensive characterization .

• Include appropriate controls when studying SSR2 in cancer: compare with matched normal tissues, use multiple cell lines, and validate findings across different experimental systems .

• Employ multiple independent siRNA sequences or CRISPR guides when targeting SSR2 to ensure specificity and rule out off-target effects .

Key research directions:

• Investigate the relationship between SSR2 and the UPR pathway, particularly the XBP1s-SSR2 axis, as this appears critical to SSR2's function in cancer .

• Explore SSR2's role in therapy resistance mechanisms, which represents a particularly promising area based on melanoma studies .

• Examine SSR2's interactions with other proteins using techniques like co-immunoprecipitation and protein-protein interaction network analysis .

Clinical correlations:

• Analyze SSR2 expression in patient samples alongside clinical data to further validate its prognostic significance across cancer types .

• Stratify patients based on SSR2 expression levels and correlate with response to standard therapies to identify potential predictive value.

• Consider SSR2 expression in the context of other UPR markers to develop more comprehensive prognostic signatures .

Technological approaches:

• Leverage public databases (TCGA, GEPIA) for initial exploration of SSR2 across cancer types before designing wet-lab experiments .

• Consider single-cell approaches to examine heterogeneity in SSR2 expression within tumors .

• Utilize differential gene expression analysis between SSR2-high and SSR2-low samples to identify associated pathways and potential downstream mediators .

Translational considerations:

• Evaluate SSR2 dependency across panels of normal cells to validate the therapeutic window suggested by current research .

• Develop and validate methods to measure SSR2 activity (not just expression) for potential use as pharmacodynamic biomarkers.

• Explore combinatorial approaches, particularly with existing therapies where resistance involves SSR2 upregulation .