HPCAL1 Human

What is HPCAL1 and what are its basic structural characteristics?

HPCAL1 (Hippocalcin-like 1), also known as VILIP3, is a neuronal calcium sensor protein belonging to the visinin-like protein family. Structurally, HPCAL1 contains three EF-hand calcium-binding motifs that undergo conformational changes upon calcium binding. The protein is encoded by the HPCAL1 gene located on human chromosome 2 .

Unlike simple calcium-binding proteins, HPCAL1 functions as a calcium-sensing transducer, converting calcium signals into biochemical responses. The protein is approximately 22 kDa in size and shares significant homology with hippocalcin, with which it shares functional characteristics and evolutionary conservation .

Methodologically, researchers can study HPCAL1 structure through X-ray crystallography or NMR spectroscopy to better understand its calcium-binding domains and potential interaction surfaces with target proteins.

How is HPCAL1 expression distributed in human tissues?

HPCAL1 demonstrates tissue-specific expression patterns with predominant expression in:

• Central nervous system (brain regions)

• Retina

• Lower expression levels in other tissues

Immunohistochemistry data from the Human Protein Atlas reveals differential expression patterns across tissues, with notable expression in normal neural tissues compared to other body sites . In pathological conditions, HPCAL1 expression can be significantly altered - for instance, it shows increased expression in glioblastoma and cholangiocarcinoma tissues compared to their normal counterparts .

To methodologically assess HPCAL1 tissue distribution, researchers typically employ:

• RT-qPCR for mRNA quantification

• Western blotting for protein detection

• Immunohistochemistry for spatial localization in tissue sections

• Single-cell RNA sequencing for cell-type specific expression patterns

What mechanisms regulate HPCAL1 expression in normal and pathological conditions?

HPCAL1 expression is regulated through multiple mechanisms:

Transcriptional regulation:

• Evidence suggests calcium-dependent transcriptional regulation, with calcium influx potentially upregulating HPCAL1 expression in some cell types

• Potential transcription factors remain to be fully characterized

Epigenetic regulation:

• DNA methylation affects HPCAL1 expression, with studies showing it as a highly plastic epigenetic marker in prostate cancer

• Methylation changes have been observed in CNT-induced lung cancer

Post-translational modifications:

• PRKCQ (protein kinase C theta)-mediated phosphorylation on Thr149 is critical for HPCAL1 function in autophagy

Research methods to study HPCAL1 regulation include:

• Promoter analysis using luciferase reporter assays

• ChIP-seq for identifying transcription factor binding sites

• Bisulfite sequencing for DNA methylation analysis

• Phosphoproteomics for identification of phosphorylation sites

How does calcium binding affect HPCAL1 function and localization?

Calcium binding induces significant conformational changes in HPCAL1 that affect its:

Protein conformation and activity:

• Ca²⁺ binding to EF-hand domains triggers exposure of hydrophobic surfaces

• This conformational change enables interaction with target proteins

• Studies suggest HPCAL1 mediates ferroptosis through a noncanonical function in autophagy, rather than its classic calcium-binding activity

Subcellular localization:

• Ca²⁺-bound HPCAL1 can translocate to membranes through calcium-myristoyl switch mechanisms

• This translocation is essential for its role in membrane-dependent processes

Methodological approaches to study calcium-dependent functions include:

• Ca²⁺ imaging techniques with fluorescent indicators

• Calcium chelators to manipulate intracellular calcium levels

• Site-directed mutagenesis of calcium-binding domains

• Subcellular fractionation combined with western blotting to track localization

How does HPCAL1 expression correlate with prognosis in different cancer types?

HPCAL1 exhibits context-dependent roles in different cancer types with significant prognostic implications:

Cholangiocarcinoma (CCA):

Table: Association between HPCAL1 expression and clinical parameters in CCA patients

Glioblastoma (GBM):

• Higher HPCAL1 expression correlates with poorer prognosis

• Data from multiple databases (GEPIA, UALCAN, HPA) confirmed the detrimental effect of high HPCAL1 expression on patient survival:

  • GEPIA: P = 0.013

  • UALCAN: P = 0.0025

  • HPA: P = 0.000057

Hepatocellular Carcinoma:

• Contradictory to other cancers, HPCAL1 appears to function as a tumor suppressor in HCC

• Lower expression correlates with worse outcomes

Methodologically, researchers can assess HPCAL1's prognostic value through:

• Kaplan-Meier survival analysis with log-rank tests

• Univariate and multivariate Cox regression analyses

• ROC curve analysis for determining optimal cut-off values

• Meta-analysis of data from multiple patient cohorts

What molecular mechanisms underlie HPCAL1's role in cancer progression?

HPCAL1 contributes to cancer progression through multiple mechanisms that vary by cancer type:

In Glioblastoma:

• Promotes cell proliferation by enhancing Wnt/β-catenin signaling

• Increases ERK phosphorylation, leading to GSK3β inhibition through Ser9 phosphorylation

• This inhibition reduces β-catenin degradation, promoting nuclear translocation and transcription of oncogenes like CCND1 and c-myc

In Cholangiocarcinoma:

• Functional enrichment analyses suggest involvement in:

  • Actinin binding

  • Rap1 signaling pathway

  • Clathrin coat processes

• These pathways are critical for tumor cell growth, invasion, and metastasis

In Hepatocellular Carcinoma:

• Negatively regulates de novo lipid and cholesterol biosynthesis

• Directly binds to RUVBL1, inhibiting the assembly of TEL2-TTI1-TTI2 (TTT)-RUVBL complex

• This leads to mTOR signaling suppression, acting as a tumor suppressor

In Ferroptosis:

• Functions as an autophagy receptor for selective degradation of CDH2 (cadherin 2)

• HPCAL1-dependent CDH2 depletion increases susceptibility to ferroptotic death

• This occurs through reduced membrane tension and increased lipid peroxidation

Methodological approaches to study these mechanisms include:

• Co-immunoprecipitation for protein-protein interaction studies

• Luciferase reporter assays for pathway activation measurements

• Knockout/knockdown studies using CRISPR/Cas9 or shRNA

• Rescue experiments to confirm mechanistic associations

How does HPCAL1 interact with the autophagy machinery in ferroptosis?

HPCAL1 serves as a specialized autophagy receptor in ferroptosis through specific molecular interactions:

Mechanism of HPCAL1-mediated selective autophagy:

• HPCAL1 contains a non-classical LC3-interacting region (LIR) motif located between amino acids 46-51

• This motif enables direct interaction with autophagosomal proteins

• PRKCQ-mediated phosphorylation of HPCAL1 on Thr149 is essential for its autophagy receptor function

• HPCAL1 selectively targets CDH2 (cadherin 2) for autophagic degradation

Consequences on ferroptosis:

• CDH2 degradation reduces membrane tension

• This altered tension favors lipid peroxidation, a key event in ferroptosis

• Knockdown of HPCAL1 inhibits RSL3- or erastin-induced cell death in multiple cancer cell lines

• This protection is reversed by ferroptosis inhibitors (ferrostatin-1 and deferoxamine), confirming specificity to ferroptotic pathways

Research methods to investigate this interaction include:

• Proximity ligation assays to detect HPCAL1-LC3 interactions

• Site-directed mutagenesis of the LIR motif

• Autophagy flux assays using LC3-II/I ratio measurements

• Pharmacological modulation with autophagy inhibitors

What is the relationship between HPCAL1 and Wnt/β-catenin signaling in cancer?

HPCAL1 positively regulates Wnt/β-catenin signaling through a multi-step process:

HPCAL1-mediated Wnt pathway activation:

• HPCAL1 enhances ERK pathway activation, demonstrated by increased ERK phosphorylation

• Activated ERK phosphorylates GSK3β at Ser9, inhibiting its activity

• Inhibited GSK3β reduces β-catenin phosphorylation and subsequent degradation

• This leads to β-catenin accumulation and nuclear translocation

• Nuclear β-catenin activates transcription of oncogenes like CCND1 and c-myc

Experimental evidence:

• HPCAL1 knockdown significantly decreased phosphorylation of GSK3β at Ser9

• HPCAL1 overexpression increased ERK phosphorylation

• GSK3β knockdown enhanced cell proliferation and promoted CCND1 and c-myc transcription

• ERK inhibition reversed the proliferation triggered by HPCAL1 overexpression

Methodological approaches to study this pathway include:

• Western blotting for phosphorylation status of key proteins

• Nuclear/cytoplasmic fractionation to track β-catenin localization

• TCF/LEF reporter assays to measure Wnt pathway activation

• Inhibitor studies targeting specific components of the pathway

What are the optimal methods for detecting and quantifying HPCAL1 expression in clinical samples?

Researchers employ multiple complementary techniques for HPCAL1 detection, each with specific advantages:

mRNA expression analysis:

• RT-qPCR: Provides quantitative measurement of HPCAL1 transcript levels

  • Requires proper reference gene selection (GAPDH, β-actin often used)

  • RNA quality assessment is critical (RIN > 7 recommended)

• RNA sequencing: Enables global transcriptomic context around HPCAL1

  • Allows for isoform-specific analysis

  • Provides data on alternative splicing events

Protein detection methods:

• Western blotting: Quantifies total protein expression

  • Recommended antibodies: Anti-HPCAL1 antibodies (validate specificity)

  • Loading controls: β-actin, GAPDH, or total protein staining

• Immunohistochemistry (IHC): Visualizes spatial distribution in tissues

  • Scoring system: 0 (absent), 1 (weak), 2 (moderate), 3 (strong) intensity

  • Cut-off values: Studies suggest 4.5 as optimal threshold for high vs. low expression in CCA

• Immunofluorescence: Enables co-localization studies with other proteins

Public database mining:

• TCGA, GEO, HPA databases provide reference expression data

• Bioinformatic tools for correlation with clinical parameters

Standardization considerations:

• Pre-analytical variables (fixation time, processing methods)

• Analytical variables (antibody validation, protocol optimization)

• Control tissues (brain tissue as positive control)

What experimental models are most appropriate for studying HPCAL1 function?

Various experimental models offer complementary insights into HPCAL1 function:

In vitro models:

• Cell lines with differential HPCAL1 expression:

  • Neuronal: SH-SY5Y, primary neurons

  • Cancer: HT-1080, Calu-1 (ferroptosis studies)

  • GBM cell lines (glioblastoma studies)

  • CCA cell lines (cholangiocarcinoma studies)

• Genetic manipulation approaches:

  • CRISPR/Cas9 for complete knockout

  • shRNA for stable knockdown (>95% reduction achieved in studies)

  • Overexpression models using lentiviral vectors

  • Site-directed mutagenesis for specific domain/residue analysis

In vivo models:

• Genetically engineered mouse models:

  • Hpcal1 knockout mice (CRISPR/Cas9-mediated deletion of exons 2-3)

  • Liver-specific Hpcal1 deletion models

• Xenograft models for cancer studies

• Orthotopic models for tissue-specific functions

• MYC/Trp53-/- liver cancer model created via hydrodynamic tail-vein injections

Functional assays:

• Calcium binding assays: Calcium overlay, intrinsic fluorescence

• Protein-protein interaction: Co-IP, proximity ligation, yeast two-hybrid

• Cell death assays: For ferroptosis studies (propidium iodide staining, HMGB1 release)

• Proliferation assays: For cancer studies

How can HPCAL1 be leveraged as a diagnostic or prognostic biomarker in clinical settings?

HPCAL1 shows promise as a biomarker across several clinical applications:

Diagnostic applications:

• Cholangiocarcinoma: Differential expression between tumor and normal bile duct tissue

  • IHC staining can differentiate CCA from normal tissues with high specificity

• Glioblastoma: Elevated expression compared to normal brain tissues

  • ROC analysis showed significant diagnostic value

• Pancreatic cancer: Identified as a potential serum biomarker

Prognostic applications:

• Cholangiocarcinoma:

  • AUC values for predicting survival: 0.753 (1-year) and 0.714 (3-year)

  • Independent prognostic factor in multivariate analysis

  • Correlates with TNM stage and lymph node invasion

• Glioblastoma:

  • High expression correlates with significantly shorter survival

  • Especially pronounced in female patients (P=0.0087)

Implementation approaches:

• Tissue-based detection: IHC scoring systems (0-3 scale with defined cutoffs)

• Development of antibody panels combining HPCAL1 with other markers

• Integration into existing prognostic nomograms

• Potential for liquid biopsy applications (circulating tumor DNA methylation)

Methodological considerations for clinical translation:

• Standardization of detection protocols

• Validation in large, multicenter cohorts

• Analysis of sensitivity/specificity in diverse patient populations

• Integration with established clinical risk factors

What are the potential therapeutic implications of targeting HPCAL1 or its associated pathways?

HPCAL1 and its signaling networks present several therapeutic opportunities:

Direct HPCAL1 targeting approaches:

• Small molecule inhibitors:

  • Drug screening has identified compounds that suppress HPCAL1 expression

  • iHPCAL1 compound identified as a ferroptosis inhibitor that suppresses HPCAL1

• RNA interference strategies:

  • siRNA/shRNA approaches have shown efficacy in preclinical models

  • Potential for nanoparticle-based delivery to specific tissues

Targeting downstream pathways:

• In glioblastoma: Wnt/β-catenin pathway inhibitors

  • GSK3β modulators or direct β-catenin inhibitors

  • ERK pathway inhibitors (given HPCAL1's role in ERK activation)

• In cholangiocarcinoma: Rap1 signaling pathway inhibitors

• In ferroptosis contexts: Modulators of the autophagy machinery

  • Compounds affecting the HPCAL1-CDH2 interaction

Context-dependent considerations:

• Tumor-specific approaches given HPCAL1's opposing roles in different cancers

• For HCC: HPCAL1 activation might be beneficial (tumor suppressor function)

• For GBM and CCA: HPCAL1 inhibition would be the therapeutic goal

Preclinical evidence:

• Genetic inhibition of HPCAL1 prevented ferroptosis-induced tumor suppression in mouse models

• HPCAL1 inhibition suppressed proliferation of GBM cells both in vitro and in vivo

Methodological approaches for therapeutic development:

• Target validation through genetic and pharmacological approaches

• Structure-based drug design targeting calcium-binding domains

• Phenotypic screening with patient-derived models

• Combination strategies with established therapeutic agents

What are the major controversies and contradictions in the current understanding of HPCAL1 function?

Several significant contradictions and knowledge gaps exist in HPCAL1 research:

Contradictory roles in different cancers:

• Oncogenic function in cholangiocarcinoma and glioblastoma

• Tumor suppressor role in hepatocellular carcinoma

• These discrepancies suggest highly context-dependent functions that require mechanistic explanation

Calcium-dependent versus calcium-independent functions:

• Classic understanding positions HPCAL1 as a calcium sensor

• Recent evidence indicates HPCAL1 mediates ferroptosis through noncanonical functions in autophagy rather than its classic calcium-binding activity

• The relationship between calcium binding and these noncanonical functions remains unclear

Subcellular localization contradictions:

• Originally characterized as primarily cytosolic

• Evidence now suggests membrane association and potential nuclear functions

• Quantitative data on distribution across compartments is limited

Autophagy connection controversies:

• HPCAL1 as both an autophagy receptor and a potential autophagy substrate

• Question of whether HPCAL1 directly interacts with core autophagy machinery or requires adaptor proteins

• Specificity for CDH2 versus potential targeting of other substrates

Methodological approaches to resolve these contradictions:

• Single-cell analysis to account for cellular heterogeneity

• Tissue-specific conditional knockout models

• Comprehensive interactome studies under different physiological conditions

• Domain-specific mutational analysis

What emerging technologies are advancing HPCAL1 research, and what are the next frontiers?

Several cutting-edge technologies are transforming HPCAL1 research:

Advanced imaging technologies:

• Super-resolution microscopy for visualizing subcellular localization

• FRET-based calcium sensors to study dynamic HPCAL1-calcium interactions in real-time

• Live-cell imaging of HPCAL1-GFP fusion proteins to track trafficking

Omics approaches:

• Spatial transcriptomics for tissue-specific expression patterns

• Proteomics for comprehensive interactome mapping

  • Studies have identified ~600 different HPCAL1-binding proteins

• Phosphoproteomics to identify regulatory phosphorylation events

• Single-cell multi-omics for heterogeneity characterization

Structural biology advances:

• Cryo-EM for visualizing HPCAL1 in complex with interaction partners

• Hydrogen-deuterium exchange mass spectrometry for conformational dynamics

• AlphaFold and related AI approaches for structure prediction

Emerging therapeutic technologies:

• PROTAC (proteolysis targeting chimeras) approach for targeted HPCAL1 degradation

• CRISPR-based gene editing for precise modification of HPCAL1 regulatory elements

• Nanoparticle-based delivery systems for tissue-specific targeting

Future research priorities:

• Systematic characterization of HPCAL1 isoforms and their differential functions

• Elucidation of the complete HPCAL1 interactome across different tissues and disease states

• Mechanistic resolution of contradictory functions in different cancer types

• Development of specific pharmacological modulators of HPCAL1 activity

• Integration of HPCAL1 into broader calcium signaling networks in health and disease

Methodological advances enabling these priorities:

• Organoid and patient-derived xenograft models

• CRISPR-based genetic screens for systematic functional analysis

• AI-driven analysis of large-scale multi-omic datasets

• Development of highly specific antibodies and nanobodies for HPCAL1 detection

What are the critical considerations for designing knockout or knockdown experiments for HPCAL1?

Successful genetic manipulation of HPCAL1 requires careful experimental design:

CRISPR/Cas9 knockout strategies:

• Optimal target sites: Exons 2-3 have been successfully targeted

• Guide RNA design considerations:

  • Minimizing off-target effects (use multiple prediction algorithms)

  • Avoiding regions with SNPs or other genetic variations

  • Targeting conserved functional domains (EF-hand motifs)

• Validation methods:

  • PCR with specific primers spanning deletion sites

  • Gene sequencing to confirm exact mutations

  • Western blotting to confirm protein loss (>95% reduction)

RNA interference approaches:

• siRNA considerations:

  • Multiple independent sequences to rule out off-target effects

  • Confirmed effective sequences from published studies:

    • Two rounds of transient transfection showed effective knockdown

• shRNA for stable knockdown:

  • Lentiviral delivery systems for hard-to-transfect cells

  • Inducible systems for temporal control of knockdown

  • Selection of appropriate promoters (U6, H1)

Common pitfalls and solutions:

• Compensatory upregulation of related family members (VILIP1, VILIP2)

  • Solution: Assess expression of related genes

• Incomplete knockdown affecting interpretation

  • Solution: Quantitative assessment of knockdown efficiency

• Cell type-specific differences in knockdown efficiency

  • Solution: Optimization for each cell type

Rescue experiments:

• Expression of siRNA/shRNA-resistant HPCAL1 constructs

• Domain-specific mutants for structure-function analysis

• Consideration of appropriate expression levels to avoid overexpression artifacts

Methodological validation standards:

• Minimum 70-80% knockdown for reliable functional studies

• Multiple independent clones for CRISPR experiments

• Appropriate controls for each step of the process

How can researchers effectively study calcium-dependent activities of HPCAL1?

Investigating the calcium-sensing functions of HPCAL1 requires specialized techniques:

Calcium binding assays:

• Isothermal titration calorimetry (ITC) for binding affinity measurements

• Circular dichroism spectroscopy for conformational changes

• Fluorescence spectroscopy using intrinsic tryptophan fluorescence

• ⁴⁵Ca²⁺ overlay assays for qualitative assessment

Calcium-dependent protein interactions:

• Co-immunoprecipitation in the presence/absence of calcium

• Surface plasmon resonance with controlled calcium concentrations

• Calcium-dependent yeast two-hybrid systems

• In-cell FRET assays with calcium chelators or ionophores

Mutagenesis approaches:

• EF-hand domain mutations to disrupt calcium binding

  • D→A mutations in calcium-coordinating residues

  • Complete EF-hand deletion constructs

• Comparison of wild-type and calcium-binding mutants in functional assays

Calcium modulation in cellular systems:

• Calcium ionophores (A23187, ionomycin) for calcium influx

• Calcium chelators (BAPTA-AM, EGTA) for calcium depletion

• Thapsigargin to deplete ER calcium stores

• Calcium channel modulators for physiological calcium signaling

Live-cell calcium and HPCAL1 imaging:

• Genetically encoded calcium indicators (GCaMPs)

• Simultaneous imaging of calcium and fluorescently tagged HPCAL1

• FRET-based HPCAL1 calcium sensors for real-time conformational changes

• Super-resolution imaging for subcellular localization

Methodological considerations:

• Careful control of calcium concentrations in buffers

• Physiologically relevant calcium ranges (100 nM - 1 μM for cytosolic studies)

• Appropriate controls for calcium-independent effects

• Consideration of other divalent metal ions (Mg²⁺, Zn²⁺)