PPIH Human, His

What is human PPIH and what are its primary cellular functions?

PPIH is a member of the cyclophilin (Cyp) family, characterized by its peptidyl-prolyl cis-trans isomerase (PPIase) and chaperone activities. It plays a crucial role in protein folding and is significantly involved in pre-mRNA splicing and the assembly of the U4/U5/U6 tri-snRNP complex. Due to its involvement in these processes, PPIH has also been referred to as Cyp-H, USA-Cyp, or U4/U6-20K in scientific literature . The protein functions as a critical regulator of cellular physiology across various inflammatory contexts and has been implicated in multiple disease processes .

How is PPIH expression distributed across different human tissues and cancer types?

Analytical studies have revealed significant upregulation of PPIH in multiple cancer types compared to normal tissues. Particularly notable overexpression has been documented in hepatocellular carcinoma (HCC), cholangiocarcinoma (CHOL), gastric adenocarcinoma, colorectal cancer (COAD), and breast cancer (BC) . Immunohistochemical validation confirms that PPIH protein expression patterns in cancer samples consistently correspond with elevated mRNA levels, suggesting regulation at the transcriptional level rather than post-transcriptional mechanisms .

What is the significance of using histidine-tagged PPIH in research?

Histidine-tagged PPIH represents a crucial tool for biochemical and structural studies of this protein. The histidine tag (His-tag) enables efficient purification through immobilized metal affinity chromatography (IMAC), allowing researchers to isolate the protein with high purity for functional assays, crystallography studies, and protein-protein interaction analyses. When studying PPIH's interaction with the spliceosome or potential binding partners, the His-tag provides a consistent method for pull-down experiments while minimizing interference with the protein's native structure and function.

How does PPIH contribute to cancer development and progression?

Gene Set Enrichment Analysis (GSEA) has revealed that high PPIH expression in cancer cells correlates with enrichment of pathways related to base excision repair, cytosolic DNA sensing, DNA replication, homologous recombination, mismatch repair, primary immunodeficiency, proteasome function, pyrimidine metabolism, ribosome activity, RNA polymerase, and spliceosome function . These findings suggest that PPIH influences cancer progression primarily through cell cycle regulation and spliceosome pathways . Additional research indicates PPIH expression positively correlates with stemness, DNA damage repair, P53 signaling, tumor proliferation, E2F targeting, G2M checkpoint, glycolysis, mitotic spindle, and MYC targeting pathways . Experimental validation through PPIH knockdown demonstrates reduced cancer cell viability, proliferation, and invasion while promoting apoptosis .

Can PPIH serve as a diagnostic biomarker for cancer, and how effective is it?

PPIH demonstrates exceptional potential as a diagnostic biomarker, particularly for cholangiocarcinoma (CHOL). Receiver Operating Characteristic (ROC) curve analysis revealed impressive diagnostic performance with area under the ROC curve (AUC) values of 0.914 (95% CI: 0.800–0.995) in the GSE32958 dataset and 0.963 (95% CI: 0.936–0.984) in the GSE76311 dataset . Comparative analysis with established biomarkers (PTPRS, UBE2C, CEACAM5, and THBS2) indicated that PPIH exhibits superior diagnostic performance for CHOL . The table below summarizes the diagnostic performance of PPIH compared to other biomarkers:

How does PPIH influence immune cell infiltration in tumors?

Analysis of the tumor microenvironment revealed that PPIH expression significantly impacts immune cell infiltration patterns. In cholangiocarcinoma, PPIH expression positively correlates with T helper 2 (Th2) cell infiltration scores, suggesting that PPIH may modulate anti-tumor immunity through Th2 cell levels . In hepatocellular carcinoma, increasing PPIH expression is associated with enhanced regulatory T cell (Treg) infiltration and decreased natural killer (NK) cell and T helper 17 (Th17) cell infiltration . Notably, substantial infiltration of exhausted T cells was observed in the high-PPIH expression group . These findings indicate that PPIH may contribute to an immunosuppressive tumor microenvironment, potentially facilitating tumor immune evasion.

What methodologies are recommended for studying PPIH's impact on the immune microenvironment?

For comprehensive analysis of PPIH's influence on the immune microenvironment, a multi-algorithmic approach is recommended. The studies utilized CIBERSORT, quantiseq, and single-sample Gene Set Enrichment Analysis (ssGSEA) algorithms to estimate tumor microenvironment components . This computational approach should be complemented with experimental validation through flow cytometry analysis of tumor-infiltrating immune cells in models with PPIH knockdown or overexpression. Additionally, multiplex immunohistochemistry on tissue sections from patients with varying PPIH expression levels can provide spatial context to immune cell infiltration patterns. For mechanistic insights, co-culture experiments with cancer cells (PPIH-modified) and various immune cell populations can elucidate direct interactions and immunomodulatory effects.

What immune-related pathways are associated with PPIH expression?

ssGSEA analysis revealed significant enrichment of DNA damage repair and cell cycle-related pathways in samples with high PPIH expression, whereas matrix pathway and various metabolism pathways (including BCAA metabolism, cholesterol metabolism, and LMRG metabolism) showed significant downregulation . Further analysis indicated elevated expression of immunomodulatory molecules in the high-PPIH expression group, including ENTTPD1, IDO1, HMGB1, antigen presentation components, coinhibitors, ligands, and receptor-associated molecules . These findings suggest PPIH may play a complex role in modulating multiple immune-related pathways within the tumor microenvironment.

What are effective methodologies for analyzing PPIH expression in clinical samples?

For PPIH expression analysis in clinical samples, a multi-modal approach is recommended. RNA-sequencing or qRT-PCR provides quantitative measurement of PPIH mRNA levels, while immunohistochemistry validates protein expression patterns in tissue samples. The studies referenced successfully employed immunohistochemical techniques to confirm that PPIH protein expression in cholangiocarcinoma samples consistently corresponded with elevated mRNA levels . For protein quantification, western blotting with specific anti-PPIH antibodies provides semi-quantitative measurement, while mass spectrometry offers more precise quantification and potential identification of post-translational modifications. When designing experiments, include appropriate controls and utilize tissue microarrays when available to efficiently analyze multiple samples simultaneously.

How should PPIH knockdown experiments be designed and validated?

When designing PPIH knockdown experiments, consider both transient (siRNA) and stable (shRNA or CRISPR-Cas9) approaches depending on the research question. For transient knockdown, test multiple siRNA sequences targeting different regions of PPIH mRNA to identify the most effective construct. For stable knockdown, design guide RNAs targeting exonic regions while avoiding potential off-target effects. Validation of knockdown efficiency should employ both mRNA quantification (qRT-PCR) and protein assessment (western blot, immunofluorescence). Functional validation should include cell viability assays, proliferation analysis, invasion/migration studies, and apoptosis measurement, as these parameters were significantly affected by PPIH knockdown in previous research . Additionally, consider in vivo validation in appropriate mouse models, as PPIH knockdown has been shown to repress tumor growth and modify the immune microenvironment .

What bioinformatic tools and databases are most valuable for PPIH research?

For comprehensive PPIH research, the following bioinformatic resources proved valuable in the referenced studies:

• Expression analysis: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases

• Survival analysis: Kaplan-Meier plotter and univariate Cox regression analysis

• Immune infiltration analysis: CIBERSORT, quantiseq, and ssGSEA algorithms

• Pathway analysis: Gene Set Enrichment Analysis (GSEA), KEGG pathway analysis

• Copy number variation (CNV) analysis: CNV loading analysis for genomic rearrangements

• Methylation analysis: MethSurv for global methylation patterns

Integration of multiple databases and analytical methods provides more robust findings. When conducting bioinformatic analyses, validate key findings across multiple datasets and complement computational predictions with experimental validation whenever possible.

How might PPIH function as a therapeutic target in cancer treatment?

Based on the accumulated evidence, PPIH presents several promising avenues for therapeutic targeting. The significant overexpression of PPIH in multiple cancer types, coupled with its association with poor prognosis and involvement in critical cellular pathways, positions it as a potential anticancer target . Small molecule inhibitors could be designed to disrupt PPIH's peptidyl-prolyl isomerase activity or its interaction with spliceosome components. Another approach involves developing RNA interference (RNAi) therapeutics targeting PPIH mRNA, as knockdown experiments have already demonstrated anticancer effects including reduced cell viability, proliferation, and invasion while promoting apoptosis . Additionally, PPIH's role in modulating the immune microenvironment suggests potential for combination therapies with immune checkpoint inhibitors, particularly in addressing the immunosuppressive effects associated with high PPIH expression.

What are the key considerations when studying PPIH's role in the spliceosome?

When investigating PPIH's function in the spliceosome, researchers should focus on several critical aspects. First, characterize PPIH's specific interactions within the U4/U5/U6 tri-snRNP complex using co-immunoprecipitation, yeast two-hybrid systems, or proximity ligation assays. Next, employ RNA immunoprecipitation sequencing (RIP-seq) to identify the RNA targets bound by PPIH. RNA splicing assays should be conducted in cells with PPIH knockdown or overexpression to determine how alterations in PPIH levels affect alternative splicing patterns, particularly of cancer-relevant genes. Additionally, structural biology approaches including X-ray crystallography or cryo-electron microscopy can elucidate the precise structural interactions of His-tagged PPIH within the spliceosome complex. Finally, investigate whether PPIH-mediated alterations in splicing contribute to specific oncogenic splice variants that may drive cancer progression.

How do somatic mutations and copy number variations impact PPIH function?

Analysis of copy number variation (CNV) loading revealed a striking increase in gene amplification and deletion in the high PPIH expression group . These genomic rearrangements may contribute to dysregulated PPIH expression in cancer. For comprehensive investigation of how somatic mutations and CNVs impact PPIH function, researchers should:

• Conduct targeted sequencing of the PPIH gene in tumor samples to identify recurrent mutations

• Use CRISPR-based approaches to introduce specific mutations and assess their functional consequences

• Analyze correlation between PPIH CNVs and expression levels across multiple cancer types

• Investigate whether specific PPIH mutations alter its interaction with spliceosome components

• Determine if PPIH mutations or CNVs correlate with altered splicing patterns in cancer cells

This approach would provide valuable insights into the genetic mechanisms underlying PPIH dysregulation in cancer and potentially identify patient subgroups that might benefit from PPIH-targeted therapies.