Recombinant Human RING finger protein 112 (RNF112)

What is the molecular structure and functional domain organization of RNF112?

RNF112 belongs to the RING finger protein family, characterized by a catalytic RING domain essential for its E3 ubiquitin ligase activity. This domain contains characteristic cysteine and histidine residues that coordinate zinc ions, forming a cross-brace structure critical for binding E2-ubiquitin conjugating enzymes. Research has demonstrated that mutations in the RING domain (RNF112-Mut) abolish ubiquitination activity while preserving protein-binding capability, indicating the domain's specific role in the catalytic process rather than substrate recognition .

What is the primary cellular function of RNF112?

RNF112 functions primarily as an E3 ubiquitin ligase that facilitates the proteasomal degradation of specific target proteins. Current research has identified Forkhead box M1 (FOXM1) as a key substrate of RNF112 in gastric cancer cells. By mediating FOXM1 ubiquitination, RNF112 suppresses the FOXM1 transcriptional network, thereby inhibiting cancer cell proliferation and invasion . Gene set enrichment analysis reveals that RNF112 negatively regulates multiple signaling pathways associated with cell cycle progression and migration, including DNA repair mechanisms, E2F targets, G2M checkpoint regulation, mTORC1 signaling, and Myc targets .

How is RNF112 expression regulated in normal and pathological conditions?

RNF112 expression is subject to regulation by various environmental factors and chemical compounds. According to research data, exposure to compounds such as 17α-ethynylestradiol increases RNF112 expression, while 4-nitrophenol and 6-propyl-2-thiouracil decrease its expression . Epigenetic mechanisms also play a role, as evidenced by increased methylation of the RNF112 exon following exposure to 4,4'-sulfonyldiphenol (bisphenol S) . In pathological contexts, particularly gastric cancer, RNF112 appears to function as a tumor suppressor, with its expression levels correlating inversely with cancer progression markers .

How does the RNF112-FOXM1 axis influence gastric cancer progression?

The RNF112-FOXM1 axis represents a critical regulatory pathway in gastric cancer progression. Mechanistic studies reveal that RNF112 directly binds to and ubiquitinates FOXM1, targeting it for proteasomal degradation . This degradation results in downregulation of the FOXM1 transcriptional network, which normally promotes cancer cell proliferation and invasion. RNA-Seq analysis of MGC803 gastric cancer cells has demonstrated that RNF112 overexpression and FOXM1 depletion affect similar downstream pathways involved in cell proliferation and migration . Xenograft tumor models further confirm that RNF112 overexpression significantly decreases tumor growth and weight, while RNF112 depletion produces the opposite effect . These findings collectively establish RNF112 as a tumor suppressor that functions by antagonizing FOXM1-driven oncogenic programs.

What molecular mechanisms are essential for RNF112-mediated tumor suppression?

The tumor-suppressive function of RNF112 depends critically on its ubiquitin ligase activity. Research using a catalytically inactive RNF112 mutant (RNF112-Mut) has demonstrated that while substrate binding remains intact, the mutant fails to ubiquitinate and degrade FOXM1 . Consequently, RNF112-Mut cannot interfere with FOXM1 downstream gene expression and loses its tumor-suppressive properties in gastric cancer models . This indicates that the enzymatic activity of RNF112, rather than mere binding to FOXM1, is essential for its anti-tumor effects. Furthermore, in vivo studies using a tail vein–lung metastasis model have shown that RNF112 dramatically represses the formation of lung metastatic lesions, highlighting its role in suppressing not only primary tumor growth but also metastatic spread .

How can the RNF112-FOXM1 interaction be therapeutically targeted?

The well-established small-molecule compound RCM-1 (Robert Costa Memorial drug-1) significantly enhances the interaction between RNF112 and FOXM1 . Mechanistically, RCM-1 promotes the cytoplasmic localization of FOXM1, facilitating its interaction with RNF112 . This enhanced interaction leads to increased FOXM1 ubiquitination and subsequent degradation, resulting in promising anticancer effects both in vitro and in vivo . These findings suggest that targeting the RNF112-FOXM1 axis, particularly by enhancing their interaction or increasing RNF112's ubiquitin ligase activity toward FOXM1, represents a viable therapeutic strategy for gastric cancer and potentially other malignancies where FOXM1 overexpression drives disease progression.

What are the optimal methods for detecting and quantifying RNF112 in biological samples?

For accurate detection and quantification of RNF112 in biological samples, several methodological approaches are available:

When using the Human RNF112 ELISA Kit, researchers should ensure proper sample preparation, include appropriate controls, and generate a reliable standard curve for accurate quantification . For comprehensive analysis, combining protein detection methods with transcriptomic approaches can provide insights into both RNF112 expression levels and its functional impact on downstream gene networks .

How can researchers effectively modulate RNF112 expression or activity in experimental models?

Various approaches can be employed to modulate RNF112 expression or activity in experimental settings:

Research has successfully employed siRNA library screening to identify RNF112 as an E3 ligase targeting FOXM1 . For functional studies, comparing wildtype RNF112 with the catalytically inactive RNF112-Mut has proven valuable in distinguishing between scaffold functions and enzymatic activities of the protein . When using pharmacological approaches, careful dose-response studies and specificity controls are essential to accurately interpret experimental outcomes.

What experimental designs are most effective for studying RNF112-mediated protein ubiquitination?

Studying RNF112-mediated ubiquitination requires carefully designed experimental approaches:

• In vitro ubiquitination assays:

  • Purified components (E1, E2, RNF112, substrate, ubiquitin)

  • ATP-dependent reaction

  • Detection by Western blot using anti-ubiquitin antibodies

• Cell-based ubiquitination assays:

  • Co-expression of RNF112 and substrate (e.g., FOXM1)

  • Treatment with proteasome inhibitors (e.g., MG132) to prevent degradation

  • Immunoprecipitation followed by ubiquitin detection

  • Comparison with catalytic dead RNF112-Mut as control

• Validation approaches:

  • Protein stability/half-life measurements

  • Proteasomal degradation inhibition

  • Domain mapping to identify ubiquitination sites

Research has successfully used these approaches to demonstrate that RNF112 directly ubiquitinates FOXM1, leading to its proteasomal degradation and subsequent suppression of cancer cell proliferation and invasion . Including appropriate controls, particularly the catalytically inactive RNF112-Mut, is crucial for distinguishing specific effects from non-specific interactions.

What are the most relevant in vitro and in vivo models for studying RNF112 in cancer research?

Several experimental models have proven valuable for studying RNF112 in cancer research:

For comprehensive analysis, a multi-model approach is recommended, beginning with mechanistic studies in cell lines and progressing to in vivo models to validate physiological relevance. The xenograft and metastasis models have been particularly informative, demonstrating that RNF112 not only suppresses primary tumor growth but also inhibits metastatic spread .

How should researchers interpret RNF112 expression data across different experimental systems?

When interpreting RNF112 expression data, researchers should consider several factors:

• Baseline expression levels: Different cell lines and tissues may exhibit varying baseline expression of RNF112

• Context-dependent effects: The impact of RNF112 may depend on FOXM1 expression levels and other pathway components

• Temporal dynamics: Expression patterns may change during disease progression or cell cycle phases

• Technical considerations:

  • RNA vs. protein levels may not correlate due to post-transcriptional regulation

  • Antibody specificity for detection methods

  • Subcellular localization affecting functional interactions

Gene set enrichment analysis has revealed that signaling pathways associated with cell cycle and proliferation were inhibited in patients with high RNF112 expression but activated in those with high FOXM1 expression . This inverse relationship provides a critical context for interpreting RNF112 expression data in experimental and clinical samples.

What data analysis approaches are recommended for RNF112-focused cancer studies?

For robust data analysis in RNF112-focused cancer studies, researchers should consider:

• Transcriptional network analysis:

  • RNA-Seq to identify downstream genes affected by RNF112 modulation

  • Gene set enrichment analysis to identify affected pathways

  • Comparison with FOXM1-regulated genes to establish mechanistic connections

• Protein interaction analysis:

  • Co-immunoprecipitation coupled with mass spectrometry to identify interaction partners

  • Proximity ligation assays to confirm interactions in situ

  • Domain mapping to identify interaction interfaces

• Clinical correlation analysis:

  • Multivariate survival analysis incorporating RNF112 and FOXM1 expression

  • Stratification of patients based on RNF112/FOXM1 expression ratios

  • Integration with other prognostic markers

Research has successfully employed these approaches to establish RNF112 as a tumor suppressor operating through FOXM1 ubiquitination and degradation, with significant implications for gastric cancer progression and potential therapeutic interventions .

What evidence supports RNF112 as a therapeutic target in cancer?

Multiple lines of evidence support RNF112 as a potential therapeutic target in cancer:

• Functional validation in preclinical models:

  • RNF112 overexpression decreases tumor growth and weight in xenograft models

  • RNF112 represses lung metastatic lesions in tail vein–lung metastasis models

  • RNF112 inhibits proliferation and invasion of gastric cancer cells

• Mechanistic understanding:

  • RNF112 directly ubiquitinates FOXM1, a well-established oncogenic transcription factor

  • The ubiquitin ligase activity of RNF112 is essential for its tumor-suppressive function

  • FOXM1 degradation leads to downregulation of multiple cancer-promoting pathways

• Pharmacological proof-of-concept:

  • RCM-1 enhances RNF112-FOXM1 interaction and promotes FOXM1 ubiquitination

  • RCM-1 exerts promising anticancer effects in vitro and in vivo

These findings collectively establish the RNF112/FOXM1 axis as both a prognostic biomarker and therapeutic target in gastric cancer .

What therapeutic strategies could target the RNF112-FOXM1 axis?

Based on current research, several therapeutic strategies could be developed to target the RNF112-FOXM1 axis:

The most established approach involves small molecules like RCM-1 that enhance the RNF112-FOXM1 interaction by promoting FOXM1's cytoplasmic localization, thereby facilitating its ubiquitination and degradation . This approach has demonstrated promising anticancer effects in preclinical models and represents a validated strategy for further therapeutic development.

How can researchers develop better chemical modulators of the RNF112-FOXM1 axis?

Developing improved chemical modulators of the RNF112-FOXM1 axis requires systematic approaches:

• Structure-based design:

  • Structural characterization of RNF112-FOXM1 interaction interfaces

  • Molecular docking studies based on RCM-1's mechanism of action

  • Fragment-based screening for novel chemical scaffolds

• High-throughput screening:

  • Cell-based assays measuring FOXM1 protein levels or activity

  • Proximity-based assays (BRET/FRET) monitoring RNF112-FOXM1 interaction

  • Phenotypic screening in cancer cell models

• Medicinal chemistry optimization:

  • Structure-activity relationship studies starting with RCM-1

  • Optimization for drug-like properties (solubility, stability, bioavailability)

  • Selective targeting to minimize off-target effects

• Validation pipeline:

  • Mechanistic confirmation (ubiquitination assays, localization studies)

  • Cellular efficacy (proliferation, invasion assays)

  • In vivo efficacy in relevant cancer models

The discovery that RCM-1 enhances the RNF112-FOXM1 interaction by promoting FOXM1's cytoplasmic localization provides a mechanistic framework for developing next-generation modulators with improved potency and specificity .

What are the key knowledge gaps in RNF112 biology that require further investigation?

Despite significant advances, several critical knowledge gaps in RNF112 biology remain to be addressed:

• Structural biology:

  • Detailed structural characterization of RNF112 and its domains

  • Structural basis of RNF112-FOXM1 interaction

  • Conformational changes during the ubiquitination process

• Regulatory mechanisms:

  • Transcriptional and post-translational regulation of RNF112

  • Cell cycle-dependent regulation of RNF112 activity

  • Factors affecting RNF112 substrate specificity

• Broader biological functions:

  • RNF112 substrates beyond FOXM1

  • Role in normal physiology and development

  • Functions in non-cancer pathological conditions

• Clinical relevance:

  • Expression and prognostic value across different cancer types

  • Potential biomarker applications

  • Resistance mechanisms to RNF112-targeted therapies

Addressing these knowledge gaps will provide a more comprehensive understanding of RNF112 biology and strengthen the foundation for therapeutic applications.

How can researchers better understand the crosstalk between RNF112 and other cancer-related pathways?

To elucidate the crosstalk between RNF112 and other cancer-related pathways, researchers should consider:

• Integrative omics approaches:

  • Multi-omics analysis (transcriptomics, proteomics, ubiquitinomics)

  • Pathway enrichment analysis and network modeling

  • Systems biology approaches to map regulatory networks

• Genetic interaction studies:

  • CRISPR screens to identify synthetic lethal interactions with RNF112

  • Combinatorial gene modulation to reveal pathway redundancies

  • Epistasis analysis to establish pathway hierarchies

• Pharmacological interaction studies:

  • Combination treatments with pathway-specific inhibitors

  • Drug synergy analysis to identify convergent mechanisms

  • Temporal dynamics of pathway activation/inhibition

Current research has begun to explore this crosstalk, with RNA-Seq analysis revealing that RNF112 affects pathways involved in cell proliferation (DNA repair, E2F targets, G2M checkpoint) and migration (mTORC1 signaling, Myc targets) . Expanding these studies will provide a more comprehensive understanding of how RNF112 interacts with broader cancer-related pathways.

What methodological innovations would advance RNF112 research?

Several methodological innovations could significantly advance RNF112 research:

• Advanced imaging techniques:

  • Super-resolution microscopy to visualize RNF112-substrate interactions

  • Live-cell imaging to track ubiquitination and degradation dynamics

  • Correlative light and electron microscopy for ultrastructural context

• Protein engineering approaches:

  • PROTAC technology to target FOXM1 for degradation

  • Engineered RNF112 variants with enhanced catalytic activity

  • Optogenetic control of RNF112 activity for temporal studies

• Advanced in vivo models:

  • Genetically engineered mouse models with conditional RNF112 expression

  • Patient-derived xenografts to evaluate clinical relevance

  • Humanized models incorporating immune components

• AI-assisted drug discovery:

  • Machine learning for predicting effective RNF112-FOXM1 modulators

  • Virtual screening of large compound libraries

  • Automated analysis of high-content screening data

Implementing these methodological innovations would accelerate the pace of discovery in RNF112 research and facilitate translation to clinical applications.