Increased expression of epidermal growth factor-like domain-containing protein 7 is predictive of poor prognosis in patients with hepatocellular carcinoma

Deep Visual Proteomics maps proteotoxicity in a genetic liver disease

Protein misfolding diseases, including α1-antitrypsin deficiency (AATD), pose substantial health challenges, with their cellular progression still poorly understood1-3. We use spatial proteomics by mass spectrometry and machine learning to map AATD in human liver tissue. Combining Deep Visual Proteomics (DVP) with single-cell analysis4,5, we probe intact patient biopsies to resolve molecular events during hepatocyte stress in pseudotime across fibrosis stages. We achieve proteome depth of up to 4,300 proteins from one-third of a single cell in formalin-fixed, paraffin-embedded tissue. This dataset reveals a potentially clinically actionable peroxisomal upregulation that precedes the canonical unfolded protein response. Our single-cell proteomics data show α1-antitrypsin accumulation is largely cell-intrinsic, with minimal stress propagation between hepatocytes. We integrated proteomic data with artificial intelligence-guided image-based phenotyping across several disease stages, revealing a late-stage hepatocyte phenotype characterized by globular protein aggregates and distinct proteomic signatures, notably including elevated TNFSF10 (also known as TRAIL) amounts. This phenotype may represent a critical disease progression stage. Our study offers new insights into AATD pathogenesis and introduces a powerful methodology for high-resolution, in situ proteomic analysis of complex tissues. This approach holds potential to unravel molecular mechanisms in various protein misfolding disorders, setting a new standard for understanding disease progression at the single-cell level in human tissue.

Role of EGFL7 in human cancers: A review

EGFL7 is a proangiogenic factor. It has been widely described with having a vital role in tubulogenesis and regulation of angiogenesis, mainly during embryogenesis and organogenesis. It has been mainly associated with NOTCH pathway, but there are reports showing association with MAPK and integrin pathways. Given its association with angiogenesis and these other pathways, there are several studies associating EGFL7 with carcinogenesis. In fact, most of the studies have pointed to EGFL7 as an oncogene, and some of them suggest EGFL7 expression as a possible biomarker of prognosis or use for a patient's follow-up. Here, we review the molecular pathways which EGFL7 is associated and highlight several studies describing the role of EGFL7 in tumorigenesis, separated by tumor type. Besides its role on angiogenesis, EGFL7 may act in other pathways as oncogene, which makes it a possible biomarker and a candidate to targeted therapy.

The Role of Stem Cell Factor, Epidermal Growth Factor and Angiopoietin-2 in HBV, HCV, HCC and NAFLD

Growth factors play a significant role in the immunopathogenesis of liver diseases, especially in liver fibrosis and cirrhosis. They can also play a role in liver regeneration and tissue repair. The regenerative capacity of the liver has been well established. Molecular mechanisms leading to regeneration involve a complex network of diverse molecules. Chronic liver injury leads to the dysregulation of regenerative mechanisms in the liver that, in addition to molecular oncogenesis, lead to uncontrolled cell proliferation and development of hepatocellular carcinoma (HCC). Stem cell factor (SCF), epidermal growth factor (EGF) and Angiopietin-2 (Ang-2) have been shown to be extremely important in the pathogenesis of liver diseases, and given their role in hepatitis B (HBV) or C virus (HCV), HCC and nonalcoholic fatty liver disease (NAFLD), they seem to be potential targets for future research into antifibrotic drugs. The role of SCF receptor c-kit in the liver is debatable, as it has impact on both liver regeneration and liver disease. EGF is a potential indicator of the survival of patients with HCC and can be a biomarker and therapeutic target structure in HCC. Further research is needed to investigate the potential role of Ang-2 for NAFLD associated with liver damage as a non-invasive circulating biomarker.

EGFL7 expression profile in IDH-wildtype glioblastomas is associated with poor patient outcome

Background

Despite the advances in glioblastoma (GBM) treatment, the average life span of patients is 14 months. Therefore, it is urgent to identity biomarkers of prognosis, treatment response, or development of novel treatment strategies. We previously described the association of high epidermal growth factor-like domain multiple 7 (EGFL7) expression and unfavorable outcome of pilocytic astrocytoma patients. The present study aims to analyze the prognostic potential of EGFL7 in GBM isocitrate dehydrogenase (IDH)-wildtype, using immunohistochemistry and in silico approaches.

Materials and Methods

Spearman's correlation analysis of The Cancer Genome Atlas RNA sequencing data was performed. The genes strongly correlated to EGFL7 expression were submitted to enrichment gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Additionally, EGFL7 expression was associated with patient overall survival. The expression of EGFL7 was analyzed through immunohistochemistry in 74 GBM IDH-wildtype patients' samples, and was associated with clinicopathological data and overall survival.

Results

In silico analysis found 78 genes strongly correlated to EGFL7 expression. These genes were enriched in 40 biological processes and eight KEGG pathways, including angiogenesis/vasculogenesis, cell adhesion, and phosphoinositide 3-kinase-Akt, Notch, and Rap1 signaling pathways. The immunostaining showed high EGFL7 expression in 39 cases (52.7%). High immunolabelling was significantly associated with low Karnofsky Performance Status and poor overall survival. Cox analysis showed that GBMs IDH-wildtype with high EGFL7 expression presented a higher risk of death compared to low expression (hazard ratio, 1.645; 95% confidence interval, 1.021 to 2.650; p = .041).

Conclusion

This study gives insights regarding the genes that are correlated with EGFL7, as well as biological processes and signaling pathways, which should be further investigated in order to elucidate their role in glioblastoma biology.

Relation among EGFL7, ITGB3, and KLF2 and their clinical implication in multiple myeloma patients: a prospective study

Objective

We aimed to investigate the relationship among epidermal growth factor–like protein-7 (EGFL7), integrin subunit beta 3 (ITGB3), and Kruppel-like factor 2 (KLF2) expressions and their clinical implication in multiple myeloma (MM).

Methods

This prospective study enrolled 72 de novo symptomatic MM patients and 30 controls, and then collected their bone marrow plasma cell samples. Subsequently, the EGFL7, ITGB3, and KLF2 expressions were carried out by reverse transcription quantitative polymerase chain reaction.

Results

EGFL7, ITGB3, and KLF2 expressions were increased in MM patients compared to controls. Besides, EGFL7, ITGB3, and KLF2 inter-correlated with each other in MM patients but not in controls. In MM patients, EGFL7 and ITGB3 (but not KLF2) expressions were positively correlated with ISS stage, while ITGB3 and KLF2 (but not EGFL7) expressions were correlated with increased R-ISS stage. Interestingly, ITGB3 and KLF2 were decreased in induction-treatment complete remission (CR) MM patients compared to non-CR MM patients, while EGFL7 only showed a trend but without statistical significance. Furthermore, ITGB3 high expression was correlated with worse progression-free survival (PFS) and overall survival (OS), while EGFL7 and KLF2 high expressions only associated with pejorative PFS but not OS.

Conclusion

EGFL7, ITGB3, and KLF2 may serve as potential prognostic indicators in MM patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11845-021-02781-2.

Integrative Network Analysis of Differentially Methylated and Expressed Genes for Biomarker Identification in Leukemia

Genome-wide DNA methylation and gene expression are commonly altered in pediatric acute lymphoblastic leukemia (PALL). Integrated network analysis of cytosine methylation and expression datasets has the potential to provide deeper insights into the complex disease states and their causes than individual disconnected analyses. With the purpose of identifying reliable cancer-associated methylation signal in gene regions from leukemia patients, we present an integrative network analysis of differentially methylated (DMGs) and differentially expressed genes (DEGs). The application of a novel signal detection-machine learning approach to methylation analysis of whole genome bisulfite sequencing (WGBS) data permitted a high level of methylation signal resolution in cancer-associated genes and pathways. This integrative network analysis approach revealed that gene expression and methylation consistently targeted the same gene pathways relevant to cancer: Pathways in cancer, Ras signaling pathway, PI3K-Akt signaling pathway, and Rap1 signaling pathway, among others. Detected gene hubs and hub sub-networks were integrated by signature loci associated with cancer that include, for example, NOTCH1, RAC1, PIK3CD, BCL2, and EGFR. Statistical analysis disclosed a stochastic deterministic relationship between methylation and gene expression within the set of genes simultaneously identified as DEGs and DMGs, where larger values of gene expression changes were probabilistically associated with larger values of methylation changes. Concordance analysis of the overlap between enriched pathways in DEG and DMG datasets revealed statistically significant agreement between gene expression and methylation changes. These results support the potential identification of reliable and stable methylation biomarkers at genes for cancer diagnosis and prognosis.

Discrimination of DNA Methylation Signal from Background Variation for Clinical Diagnostics

Advances in the study of human DNA methylation variation offer a new avenue for the translation of epigenetic research results to clinical applications. Although current approaches to methylome analysis have been helpful in revealing an epigenetic influence in major human diseases, this type of analysis has proven inadequate for the translation of these advances to clinical diagnostics. As in any clinical test, the use of a methylation signal for diagnostic purposes requires the estimation of an optimal cutoff value for the signal, which is necessary to discriminate a signal induced by a disease state from natural background variation. To address this issue, we propose the application of a fundamental signal detection theory and machine learning approaches. Simulation studies and tests of two available methylome datasets from autism and leukemia patients demonstrate the feasibility of this approach in clinical diagnostics, providing high discriminatory power for the methylation signal induced by disease, as well as high classification performance. Specifically, the analysis of whole biomarker genomic regions could suffice for a diagnostic, markedly decreasing its cost.

Increased circulating levels of Epidermal Growth Factor-like Domain 7 in pregnant women affected by preeclampsia

Proper placental development is crucial to establish a successful pregnancy. Defective placentation is the major cause of several pregnancy complications, including preeclampsia (PE). We have previously demonstrated that the secreted factor Epidermal Growth Factor-like Domain 7 (EGFL7) is expressed in trophoblast cells of the human placenta and that it regulates trophoblast migration and invasion, suggesting a role in placental development. In the present study, we demonstrate that circulating levels of EGFL7 are undetectable in nonpregnant women, increase during pregnancy and decline toward term. Close to term, circulating levels of EGFL7 are significantly higher in patients affected by PE when compared to normal pregnancies. Consistent with these results, villus explant cultures obtained from placentas affected by PE display increased release of EGFL7 in the culture medium when compared to those from normal placentas. Our results suggest that increased release of placenta-derived EGFL7 and increased circulating levels of EGFL7 are associated with the clinical manifestation of PE.