FOLH1 Human

What is FOLH1 and why is there a nomenclature shift from PSMA?

FOLH1 (Folate Hydrolase-1) is a transmembrane receptor and enzyme encoded by the FOLH1 gene. Historically, it has been referred to as Prostate-Specific Membrane Antigen (PSMA), but this terminology is increasingly considered a misnomer as it falsely implies exclusive expression to the prostate . The scientific community is moving toward using "FOLH1" as it describes the enzyme's function rather than suggesting tissue specificity, aligning with the International Union of Biochemistry and Molecular Biology guidelines recommending that enzyme nomenclature be based on the chemical reactions they catalyze . This shift promotes gender and disease inclusivity in scientific nomenclature, as FOLH1 expression has been documented in numerous non-prostate tissues and various cancer types affecting all genders .

Where is FOLH1 physiologically expressed in normal human tissues?

FOLH1 is physiologically expressed in several normal human tissues:

• The apical/luminal surface of the duodenum

• Proximal renal tubular cells

• Prostate gland epithelial cells

• Parotid glands

• A subpopulation of astrocytes in the central nervous system

Interestingly, while salivary glands show avid uptake of FOLH1-targeted radiopharmaceuticals in molecular imaging studies, immunohistochemistry studies have observed minimal FOLH1 expression in these tissues, suggesting that radiopharmaceutical uptake might be primarily non-specific in salivary gland tissue .

What is the enzymatic function of FOLH1 in human cells?

FOLH1 functions as a folate hydrolase that utilizes water to break down (hydrolyze) glutamate residues from dietary folate . It is a membrane-bound metallopeptidase that plays a role in folate metabolism. In research applications, understanding this enzymatic function is crucial when designing inhibitors or substrates for FOLH1-targeted imaging or therapeutic purposes. The enzyme's physiological role relates to folate processing, which has implications for cellular proliferation and DNA synthesis - functions that may be exploited in rapidly dividing cancer cells.

How does FOLH1 expression vary across different cancer histological subtypes?

FOLH1 expression varies significantly across cancer histological subtypes. In renal cell carcinoma (RCC), clear cell RCC (ccRCC) shows significantly higher FOLH1 expression compared to non-clear cell RCC variants (19.37 versus 3.48 TPM, p < 0.001) . Among RCC subtypes:

• Clear cell RCC: Highest expression (median 19.37 TPM)

• Papillary RCC: Lower expression (part of non-ccRCC group with median 3.48 TPM)

• Chromophobe RCC: Lower expression (part of non-ccRCC group with median 3.48 TPM)

Additionally, FOLH1 is expressed on:

• Surface membrane of prostate cancer cells

• Adenoid cystic carcinoma cells

• Intracellularly in a subset of OCT4+ melanoma cells (possible cancer stem cells)

• Luminally in virtually every solid tumor-associated vasculature

What is the relationship between FOLH1 expression and tumor angiogenesis?

FOLH1 expression demonstrates a strong correlation with angiogenic processes in tumors. In RCC, FOLH1 expression is correlated with angiogenic gene expression (Spearman = 0.76, p < 0.001) and endothelial cell abundance (Spearman = 0.76, p < 0.001) . Research by Nguyen et al. demonstrated that solid tumor substrates induce neoendothelial FOLH1 expression in preclinical models, confirming that FOLH1 is specific to tumor-associated vessel formation rather than angiogenic vessels of other etiologies .

FOLH1 expression has been validated in the neovasculature of Merkel cell carcinoma (MCC), with 60-77% of patients in an 81-person cohort showing FOLH1 expression in tumor-associated blood vessels . This pattern of vascular expression appears to be a common feature across multiple solid tumor types, making FOLH1 a potential universal target for anti-angiogenic therapy approaches.

How does FOLH1 expression correlate with genetic alterations in cancer?

FOLH1 expression levels correlate with distinct genetic alteration patterns in renal cell carcinoma. When comparing tumors with high versus low FOLH1 expression:

• VHL mutations are more common in tumors with higher FOLH1 expression (Q4) compared to those with lower expression (Q1)

• PBRM1 mutations are less frequent in FOLH1-high expression tumors compared to FOLH1-low expression tumors

• SETD2 mutations are less commonly associated with high FOLH1 expression (6% in Q4 vs. 9% in Q1, p < 0.05)

• pTERT mutations are less common in FOLH1-high (Q4) tumors (5%) compared to FOLH1-low (Q1) tumors (19%, p < 0.01)

These genetic associations suggest that FOLH1 expression may be influenced by or connected to specific oncogenic pathways, particularly those involving VHL mutations and subsequent hypoxia-inducible factor stabilization, which could explain the link to angiogenesis.

What techniques are most effective for detecting and quantifying FOLH1 expression in human tissues?

Several complementary techniques can be used to detect and quantify FOLH1 expression:

• RNA Sequencing (RNA-Seq):

  • Whole-transcriptome sequencing can quantify FOLH1 mRNA expression levels in terms of transcripts per million (TPM)

  • Requires microdissection to enrich tumor elements prior to nucleic acid isolation

  • Can be performed using hybrid-capture methods and platforms like Illumina NovaSeq

• Immunohistochemistry (IHC):

  • Uses antibodies such as 3E6 (DAKO) mouse IgG1 monoclonal anti-human FOLH1

  • Should include proper controls: isotype antibody as negative control and anti-CD31 as positive control for vasculature

  • Can be scored based on intensity (0 to 3+/4+) and percentage of staining (0-100%)

  • Allows visualization of specific cellular localization (membrane, cytoplasmic, luminal)

• Next-Generation Sequencing (NGS):

  • Can be used to identify genetic alterations that may correlate with FOLH1 expression

  • Platforms such as NextSeq or NovaSeq can be employed with targeted panels or whole-exome approaches

• Gene Expression Signature Analysis:

  • FOLH1 expression can be analyzed in the context of broader expression signatures (e.g., angiogenic, T-effector, myeloid)

  • Tools like MCP-Counter can estimate immune cell infiltration in relation to FOLH1 expression

How should researchers stratify FOLH1 expression levels for meaningful comparative analyses?

Based on the literature, researchers should consider the following approach to stratify FOLH1 expression:

• Quartile-Based Stratification:

  • Define FOLH1-high tumors as those in the ≥75th percentile of RNA transcripts per million (TPM)

  • Define FOLH1-low tumors as those in the <25th percentile of expression

  • This approach allows for more granularity in data analysis across quartiles of FOLH1 expression

• Immunohistochemistry Intensity Scoring:

  • Negative (-)

  • Weak positive (+)

  • Moderate positive (++)

  • Strong positive (+++)

  • Maximum positive (++++, characterized as staining equivalent to that seen in prostate cancer)

• Statistical Considerations:

  • Use Mann-Whitney U test for continuous data comparisons

  • Apply Chi-square or Fisher's exact test for categorical data

  • Consider Spearman correlation to assess relationships between FOLH1 expression and other variables

Multiple independent reviewers should evaluate staining to address inter-observer variability, with majority agreement used in cases of measurement differences .

What experimental controls are critical when studying FOLH1 in tissue samples?

When studying FOLH1 in tissue samples, the following controls are critical:

• Positive Controls:

  • Prostate cancer tissue (known to express high levels of FOLH1)

  • Anti-CD31 staining to identify all vasculature (for comparison with FOLH1-positive vessels)

  • Normal tissues with known FOLH1 expression (duodenum, prostate)

• Negative Controls:

  • Isotype-matched antibody controls (e.g., mouse IgG1 isotype antibody at corresponding concentrations)

  • Tissues known to have minimal FOLH1 expression

  • Technical controls omitting primary antibody

• Internal Controls and Validation:

  • Multiple antibody clones to confirm specificity

  • RNA-seq validation of protein expression findings

  • Multi-institutional cohorts to address potential batch effects

  • Independent pathologist review to address subjective interpretation

• Methodological Controls:

  • Microdissection to ensure enrichment of tumor elements prior to molecular analysis

  • Inclusion of normal adjacent tissue for comparison

  • Standardized protocols across samples to minimize technical variation

How does FOLH1 expression relate to clinical outcomes in various cancer types?

FOLH1 expression has demonstrated correlations with clinical outcomes across different cancer types:

What are the current methodological approaches for targeting FOLH1 in experimental therapeutics?

Several methodological approaches are being explored for targeting FOLH1 in experimental therapeutics:

• Antibody-Drug Conjugates:

  • Conjugating cytotoxic agents (e.g., auristatin) to anti-FOLH1 antibodies like J591

  • This approach has shown a 700-fold increase in therapeutic index and improved median survival in prostate cancer xenografts

• Radioligand Therapy:

  • Using radiolabeled antibodies or small molecules targeting FOLH1

  • 177Lu-J591 (lutetium-177 conjugated to J591 antibody) has shown to be well-tolerated and non-immunogenic in clinical studies

  • Can be fractionated to optimize therapeutic effect while minimizing toxicity

• Targeted Brachytherapy:

  • Systemic targeting of disseminated disease with antibody-based brachytherapy

  • Particularly relevant for cancers with FOLH1 expression in tumor neo-vasculature, like Merkel cell carcinoma

• Combination Approaches:

  • Combining FOLH1-targeted therapies with immune checkpoint inhibitors

  • Investigating synergistic effects with conventional antiangiogenic therapies like cabozantinib in RCC

How can FOLH1 expression analysis be integrated into clinical research protocols?

Researchers can integrate FOLH1 expression analysis into clinical research protocols through the following approaches:

• Baseline Tissue Assessment:

  • Incorporate FOLH1 IHC and/or RNA expression analysis in baseline tumor biopsies

  • Stratify patients based on FOLH1 expression levels (using quartile-based or categorical systems)

  • Consider both tumor cell and neo-vascular FOLH1 expression

• Companion Diagnostics Development:

  • Develop standardized IHC protocols with clear scoring criteria

  • Validate RNA-seq based expression cutoffs for potential companion diagnostic applications

  • Ensure inter-laboratory reproducibility through round-robin testing

• Correlative Studies in Clinical Trials:

  • Include FOLH1 expression as an exploratory endpoint in trials of angiogenesis inhibitors

  • Analyze treatment duration, response rates, and survival outcomes based on FOLH1 expression

  • For example, the correlation between high FOLH1 expression and longer duration on cabozantinib treatment in RCC

• Longitudinal Assessment:

  • Consider serial biopsies to assess changes in FOLH1 expression during treatment

  • Correlate expression changes with treatment response or resistance development

  • Explore circulating biomarkers that might reflect FOLH1 status without invasive procedures

What are the hypothesized biological mechanisms linking FOLH1 to tumor angiogenesis?

The biological mechanisms linking FOLH1 to tumor angiogenesis appear to involve several pathways:

• Tumor Microenvironment Induction:

  • Research by Nguyen et al. demonstrated that the substrate of solid tumors induces neoendothelial FOLH1 expression in preclinical models

  • This suggests that factors secreted by tumor cells specifically trigger FOLH1 expression in forming neo-vessels

• Correlation with Angiogenic Signaling:

  • Strong correlation between FOLH1 expression and angiogenic gene signatures (Spearman = 0.76, p < 0.001)

  • Similarly strong correlation with endothelial cell abundance (Spearman = 0.76, p < 0.001)

  • This suggests FOLH1 may be co-regulated with other angiogenic factors or directly involved in angiogenic signaling

• VHL-HIF Pathway Connection:

  • The association between VHL mutations and higher FOLH1 expression in RCC suggests a potential link through hypoxia-inducible factor (HIF) stabilization

  • This hints at hypoxia-driven regulation of FOLH1 expression, consistent with its role in tumor neo-vasculature

• Specificity to Tumor Vessels:

  • FOLH1 expression appears specific to tumor-associated vessels rather than angiogenic vessels of other etiology

  • This specificity suggests unique regulatory mechanisms in the tumor microenvironment that distinguish tumor angiogenesis from other forms of neovascularization

How might differences in FOLH1 expression between primary and metastatic sites impact research approaches?

The differences in FOLH1 expression between primary and metastatic sites present several important research considerations:

• Observed Expression Differences:

  • FOLH1 expression varies by specimen site (primary kidney vs. metastatic sites in RCC)

  • Primary kidney tumors show higher expression compared to metastatic sites (13.6 versus 9.9 TPM, p < 0.001)

• Research Design Implications:

  • Studies should include matched primary and metastatic samples when possible

  • Analysis should be stratified by tumor site to account for this biological heterogeneity

  • Researchers should consider site-specific therapeutic targeting strategies

• Biological Significance:

  • Differences may reflect adaptation to distinct microenvironments

  • May impact the effectiveness of FOLH1-targeted diagnostics or therapeutics depending on disease distribution

  • Could provide insights into metastatic processes and tumor evolution

• Clinical Translation Considerations:

  • May need different thresholds for defining "high" expression based on tumor site

  • Therapeutic targeting might require dose adjustments based on primary versus metastatic location

  • Imaging sensitivity might vary between primary and metastatic lesions

What are the emerging research directions for understanding FOLH1's role beyond current established functions?

Several emerging research directions are expanding our understanding of FOLH1 beyond its established functions:

• Gender-Inclusive Cancer Applications:

  • Extending FOLH1-targeted approaches to gynecological malignancies and other cancers affecting patient genotypes without prostates

  • Addressing potential gender bias in research and therapeutic development by moving away from prostate-specific terminology

• Cancer Stem Cell Biology:

  • Investigating the significance of intracellular FOLH1 expression in OCT4+ melanoma cells, which may represent cancer stem cells

  • Understanding whether FOLH1 plays a functional role in stemness or is merely a marker

• Predictive Biomarker Development:

  • Further exploring FOLH1 as a predictive biomarker for response to specific therapies

  • Building on findings that FOLH1-high clear cell RCC tumors showed longer duration on cabozantinib treatment

• Immune Microenvironment Interactions:

  • Investigating relationships between FOLH1 expression and immune cell infiltration

  • Exploring potential connections between angiogenesis and immunosuppression in the tumor microenvironment

  • Developing combination strategies targeting both FOLH1 and immune checkpoints

• Functional Studies of Enzymatic Activity:

  • Moving beyond expression analysis to understand the functional significance of FOLH1's folate hydrolase activity in tumor biology

  • Exploring whether enzymatic inhibition versus receptor targeting might have different therapeutic implications

  • Investigating potential folate metabolism connections to tumor growth and therapy resistance

What are the advantages and limitations of different FOLH1 detection methods in research settings?

Different FOLH1 detection methods offer distinct advantages and limitations for researchers:

Researchers should select methods based on their specific research questions, available resources, and required level of quantitative precision or spatial resolution.

How can researchers optimize experimental protocols for consistent FOLH1 measurement across different laboratory settings?

To optimize experimental protocols for consistent FOLH1 measurement across different laboratory settings, researchers should implement:

• Standardized Sample Processing:

  • Use consistent fixation protocols for tissues (e.g., 10% neutral buffered formalin for 24-48 hours)

  • Implement standardized microdissection techniques to enrich tumor elements

  • Establish uniform RNA extraction and quality control criteria

• Reference Standards and Controls:

  • Include universal reference standards in each experimental batch

  • Use multi-tier controls (negative, low positive, high positive)

  • Incorporate prostate cancer samples as positive controls for maximum FOLH1 expression

• Protocol Harmonization:

  • For IHC: Standardize antibody clones, dilutions, antigen retrieval methods, and detection systems

  • For RNA-seq: Use consistent library preparation methods and sequencing depth

  • Implement automated platforms where possible (e.g., Agilent DAKO Link 48)

• Multi-Observer Validation:

  • Have multiple pathologists independently score IHC results

  • Use majority agreement in cases of measurement differences

  • Consider digital pathology and automated scoring algorithms to reduce subjectivity

• Inter-Laboratory Validation:

  • Conduct round-robin testing across research sites

  • Share reference materials between laboratories

  • Establish proficiency testing programs for FOLH1 assessment

• Detailed Protocol Documentation:

  • Publish comprehensive protocols with all experimental parameters

  • Specify exact reagents, equipment, and software versions used

  • Document any deviations or optimizations for specific sample types

What statistical approaches are most appropriate for analyzing FOLH1 expression data in heterogeneous tumor samples?

When analyzing FOLH1 expression in heterogeneous tumor samples, researchers should consider these statistical approaches:

• Handling Continuous Expression Data:

  • Use non-parametric tests (Mann-Whitney U) for comparing FOLH1 expression levels between groups, as biological data often violates normality assumptions

  • Apply Spearman rank correlation when assessing relationships between FOLH1 expression and other continuous variables (e.g., angiogenic signatures)

  • Consider log transformation of TPM values if necessary for specific analyses

• Categorical Analysis Approaches:

  • Quartile-based stratification (Q1-Q4) allows for granular analysis across expression levels

  • Chi-square or Fisher's exact test for categorical comparisons (e.g., mutation status vs. FOLH1 expression groups)

  • Consider multiple cutpoints for sensitivity analyses (median, tertiles, quartiles)

• Accounting for Tumor Heterogeneity:

  • Implement mixed models when analyzing multiple samples from the same patient

  • Consider spatial statistics for analyzing IHC patterns within heterogeneous tumors

  • Use computational deconvolution methods to estimate cell type-specific expression in bulk RNA-seq data

• Survival Analysis Methods:

  • Apply Kaplan-Meier estimates with log-rank tests for time-to-event outcomes (e.g., survival, time on treatment)

  • Use Cox proportional hazards models to adjust for covariates while assessing FOLH1's prognostic impact

  • Consider time-dependent covariate analyses if FOLH1 expression changes over time

• Multiple Testing Correction:

  • Apply appropriate multiple testing corrections (e.g., Benjamini-Hochberg for false discovery rate)

  • Report both raw and adjusted p-values for transparency

  • Consider family-wise error rate control for confirmatory analyses

• Power and Sample Size Considerations:

  • Conduct power analyses specifically for FOLH1 expression variability

  • Consider effect sizes observed in previous studies (e.g., HR 0.57 for time on cabozantinib)

  • Ensure adequate representation of relevant subgroups (e.g., different histologies, metastatic sites)

What are the most promising research avenues for understanding FOLH1's regulatory mechanisms in cancer?

The most promising research avenues for understanding FOLH1's regulatory mechanisms include:

• Hypoxia and HIF Pathway Investigations:

  • Given the correlation with VHL mutations in RCC, direct assessment of HIF-1α and HIF-2α regulation of FOLH1 expression

  • Chromatin immunoprecipitation studies to identify potential hypoxia response elements in the FOLH1 promoter

  • Manipulation of oxygen tension in experimental models to assess direct effects on FOLH1 expression

• Tumor Microenvironment Factors:

  • Identification of specific tumor-derived factors that induce FOLH1 expression in neovasculature

  • Co-culture systems with endothelial cells and various tumor types to elucidate paracrine signaling mechanisms

  • Spatially resolved transcriptomics to map expression patterns relative to hypoxic regions and stromal interfaces

• Epigenetic Regulation:

  • Exploration of DNA methylation patterns in the FOLH1 promoter across different cancer types

  • Histone modification profiling to understand chromatin-level regulation

  • Investigation of microRNA-mediated post-transcriptional regulation of FOLH1

• Lineage-Specific Expression Mechanisms:

  • Comparative analysis of regulatory elements active in clear cell versus non-clear cell RCC

  • Single-cell RNA sequencing to identify cell-type-specific expression patterns and regulatory networks

  • CRISPR-based screening to identify transcription factors critical for FOLH1 expression

• Post-Translational Regulation:

  • Characterization of FOLH1 protein stability, trafficking, and membrane localization mechanisms

  • Identification of post-translational modifications affecting enzymatic activity or receptor function

  • Exploration of protein-protein interactions that might regulate FOLH1 activity or localization

How can researchers address current methodological challenges in FOLH1-targeted therapeutic development?

Researchers can address current methodological challenges in FOLH1-targeted therapeutic development through:

• Improving Target Specificity:

  • Develop next-generation antibodies or small molecules with enhanced FOLH1 binding specificity

  • Design ligands that preferentially bind to tumor-associated FOLH1 versus physiological expression sites

  • Explore bispecific approaches requiring dual-target engagement for activation

• Reducing Off-Target Effects:

  • Investigate the mechanistic basis for salivary gland uptake of FOLH1-targeted agents despite limited expression

  • Develop competitive binding strategies to block non-specific uptake in non-target tissues

  • Optimize molecular designs to enhance tumor-to-background ratios

• Combination Strategy Development:

  • Design rational combinations with immune checkpoint inhibitors

  • Explore synergies with conventional anti-angiogenic therapies like cabozantinib

  • Develop sequencing strategies to optimize therapeutic window

• Biomarker Refinement:

  • Move beyond simple expression analysis to functional assessment of FOLH1

  • Develop predictive biomarkers for response to FOLH1-targeted therapies

  • Establish standardized cutoffs for patient selection across different cancer types

• Novel Therapeutic Modalities:

  • Explore FOLH1-targeted antibody-drug conjugates with newer payload classes

  • Investigate alpha-emitting radioisotopes for enhanced therapeutic potency

  • Develop FOLH1-targeted CAR-T or other cellular therapies for solid tumors

• Clinical Trial Design Optimization:

  • Implement basket trial approaches across FOLH1-expressing tumor types

  • Design trials with prospective stratification based on FOLH1 expression levels

  • Include paired biopsies to assess pharmacodynamic effects on the tumor microenvironment

What interdisciplinary approaches might yield new insights into FOLH1 biology and therapeutic applications?

Promising interdisciplinary approaches that might yield new insights include:

• Systems Biology Integration:

  • Network analysis incorporating FOLH1 expression, genetic alterations, and clinical outcomes

  • Multi-omics integration (genomics, transcriptomics, proteomics, metabolomics) to place FOLH1 in broader cellular context

  • Mathematical modeling of FOLH1-targeted therapy pharmacokinetics and pharmacodynamics

• Computational Drug Discovery:

  • Structure-based drug design targeting the FOLH1 active site

  • Machine learning approaches to predict optimal FOLH1-targeted compound properties

  • Virtual screening of compound libraries for novel FOLH1 inhibitors or ligands

• Advanced Imaging Technologies:

  • Multiplexed imaging to simultaneously visualize FOLH1, tumor cells, immune cells, and vasculature

  • Intravital microscopy to observe FOLH1-targeted agent trafficking in real-time

  • PET-MRI combination strategies for enhanced anatomical and functional assessment

• Developmental Biology Perspectives:

  • Exploration of FOLH1's role in embryonic vasculogenesis versus pathological angiogenesis

  • Comparative studies across species to identify evolutionarily conserved functions

  • Developmental timing analysis of FOLH1 expression in normal versus neoplastic tissues

• Radiobiology and Physics Collaborations:

  • Optimization of radiation dose delivery through FOLH1-targeted radiopharmaceuticals

  • Monte Carlo simulations for predicting therapeutic efficacy in different tumor geometries

  • Novel instrumentation development for detecting low levels of FOLH1-targeted tracer uptake

• Bioengineering Approaches:

  • Development of FOLH1-responsive nanoparticles for targeted drug delivery

  • Biomaterial scaffolds incorporating FOLH1-targeted elements for tissue engineering

  • Microfluidic systems to study FOLH1 function in controlled tumor microenvironments