Mass Spectrometry-Based Proteomic Discovery of Prognostic Biomarkers in Adrenal Cortical Carcinoma

ELK4 targets CHMP6 to inhibit ferroptosis and enhance malignant properties of skin cutaneous melanoma cells

Ferroptosis, a key factor in tumor progression, is poorly understood at the molecular level. This study investigates how ELK4 and CHMP6 regulate skin cutaneous melanoma (SKCM) cell proliferation and ferroptosis. Analysis of TCGA data reveals high expression of ELK4 and CHMP6 in SKCM. Overexpression of ELK4 or CHMP6 enhances cell proliferation, invasion, and migration while reducing ROS and Fe2 + levels. It also increases GPX4 and xCT expression and decreases ACSL4 levels in SKCM cells. The opposite effects are observed with ELK4 or CHMP6 knockdown. ELK4 binds to the CHMP6 promoter, promoting CHMP6 transcription. Knockdown of CHMP6 reverses the oncogenic effects of ELK4 overexpression. In conclusion, ELK4 enhances proliferation, invasion, and migration while inhibiting ferroptosis in SKCM cells by upregulating CHMP6 transcription. This study sheds light on the intricate mechanisms involved in SKCM progression and identifies potential therapeutic targets in melanoma treatment.

Proteomic profiling of cerebrospinal fluid reveals TKT as a potential biomarker for medulloblastoma

Cerebrospinal fluid (CSF) plays an important role in brain tumors, including medulloblastoma (MBL). Recent advancements in mass spectrometry systems and 'Omics' data analysis methods enable unbiased, high proteome depth research. We conducted proteomic profiling of the total CSF in MBL patients with the purpose of finding a potential diagnostic biomarker for MBL. We quantified 1112 proteins per CSF sample. Feature selection identified four elevated soluble proteins (SPTBN1, HSP90AA1, TKT, and NME1-NME2) in MBL CSF. Validation with ELISA confirmed that TKT was significantly elevated in MBL. Additionally, TKT-positive extracellular vesicles were significantly enriched in MBL CSF and correlated with the burden of leptomeningeal seeding. Our results provide insights into the proteomics data of the total CSF of MBL patients. Furthermore, we identified the significance of TKT within the total CSF and its presence within circulating EVs in the CSF. We suggest that TKT may serve as a biomarker for MBL.

Systematic Proteome Profiling of Maternal Plasma for Development of Preeclampsia Biomarkers

Preeclampsia (PE) is a hypertensive disorder of pregnancy with various clinical symptoms. However, traditional markers for the disease including high blood pressure and proteinuria are poor indicators of the related adverse outcomes. Here, we performed systematic proteome profiling of plasma samples obtained from pregnant women with PE to identify clinically effective diagnostic biomarkers. Proteome profiling was performed using TMT-based liquid chromatography-mass spectrometry (LC-MS/MS) followed by subsequent verification by multiple reaction monitoring (MRM) analysis on normal and PE maternal plasma samples. Functional annotations of differentially expressed proteins (DEPs) in PE were predicted using bioinformatic tools. The diagnostic accuracies of the biomarkers for PE were estimated according to the area under the receiver-operating characteristics curve (AUC). A total of 1307 proteins were identified, and 870 proteins of them were quantified from plasma samples. Significant differences were evident in 138 DEPs, including 71 upregulated DEPs and 67 downregulated DEPs in the PE group, compared with those in the control group. Upregulated proteins were significantly associated with biological processes including platelet degranulation, proteolysis, lipoprotein metabolism, and cholesterol efflux. Biological processes including blood coagulation and acute-phase response were enriched for down-regulated proteins. Of these, 40 proteins were subsequently validated in an independent cohort of 26 PE patients and 29 healthy controls. APOM, LCN2, and QSOX1 showed high diagnostic accuracies for PE detection (AUC >0.9 and p < 0.001, for all) as validated by MRM and ELISA. Our data demonstrate that three plasma biomarkers, identified by systematic proteomic profiling, present a possibility for the assessment of PE, independent of the clinical characteristics of pregnant women.

Epigenetic identification of LTBP4 as a putative tumor suppressor in breast cancer

Aim: To explore the LTBP4's expression, prognostic significance and molecular mechanism of action in breast cancer (BC).Methods: On the basis of omics datasets and experiments, we conducted a synthetical analysis of LTBP4 in BC.Results & conclusion: LTBP4 was downregulated in BC with high promoter methylation and low genetic alteration. DNA methylation was negatively associated with LTBP4 mRNA expression. Higher LTBP4 associated with better survival. LTBP4 was enrichment in extracellular matrix receptor interactions, cell adhesion molecules, cell cycle and MAPK pathway. LTBP4 expression and methylation were positively and negatively associated with tumor infiltrating immune cells, respectively. In conclusion, LTBP4 is a putative tumor suppressor in BC, which expression is regulated by DNA methylation and relates with prognosis.

Protective effect of Cyclo(His-Pro) on peritoneal fibrosis through regulation of HDAC3 expression

Peritoneal dialysis is a common treatment for end-stage renal disease, but complications often force its discontinuation. Preventive treatments for peritoneal inflammation and fibrosis are currently lacking. Cyclo(His-Pro) (CHP), a naturally occurring cyclic dipeptide, has demonstrated protective effects in various fibrotic diseases, yet its potential role in peritoneal fibrosis (PF) remains uncertain. In a mouse model of induced PF, CHP was administered, and quantitative proteomic analysis using liquid chromatography-tandem mass spectrometry was employed to identify PF-related protein signaling pathways. The results were further validated using human primary cultured mesothelial cells. This analysis revealed the involvement of histone deacetylase 3 (HDAC3) in the PF signaling pathway. CHP administration effectively mitigated PF in both peritoneal tissue and human primary cultured mesothelial cells, concurrently regulating fibrosis-related markers and HDAC3 expression. Moreover, CHP enhanced the expression of nuclear factor erythroid 2-related factor 2 (Nrf2) while suppressing forkhead box protein M1 (FOXM1), known to inhibit Nrf2 transcription through its interaction with HDAC3. CHP also displayed an impact on spleen myeloid-derived suppressor cells, suggesting an immunomodulatory effect. Notably, CHP improved mitochondrial function in peritoneal tissue, resulting in increased mitochondrial membrane potential and adenosine triphosphate production. This study suggests that CHP can significantly prevent PF in peritoneal dialysis patients by modulating HDAC3 expression and associated signaling pathways, reducing fibrosis and inflammation markers, and improving mitochondrial function.

Amelioration of Fibrosis via S1P Inhibition Is Regulated by Inactivation of TGF-β and SPL Pathways in the Human Cornea

Human corneal fibrosis can lead to opacity and ultimately partial or complete vision loss. Currently, corneal transplantation is the only treatment for severe corneal fibrosis and comes with the risk of rejection and donor shortages. Sphingolipids (SPLs) are known to modulate fibrosis in various tissues and organs, including the cornea. We previously reported that SPLs are tightly related to both, transforming growth factor beta (TGF-β) signaling and corneal fibrogenesis. The aim of this study was to investigate the effects of sphingosine-1-phosphate (S1P) and S1P inhibition on specific TGF-β and SPL family members in corneal fibrosis. Healthy human corneal fibroblasts (HCFs) were isolated and cultured in EMEM + FBS + VitC (construct medium) on 3D transwells for 4 weeks. The following treatments were prepared in a construct medium: 0.1 ng/mL TGF-β1 (β1), 1 μM sphingosine-1-phosphate (S1P), and 5 μM Sphingosine kinase inhibitor 2 (I2). Five groups were tested: (1) control (no treatment); rescue groups; (2) β1/S1P; (3) β1/I2; prevention groups; (4) S1P/β1; and (5) I2/β1. Each treatment was administered for 2 weeks with one treatment and switched to another for 2 weeks. Using Western blot analysis, the 3D constructs were examined for the expression of fibrotic markers, SPL, and TGF-β signaling pathway members. Scratch assays from 2D cultures were also utilized to evaluate cell migration We observed reduced fibrotic expression and inactivation of latent TGF-β binding proteins (LTBPs), TGF-β receptors, Suppressor of Mothers Against Decapentaplegic homologs (SMADs), and SPL signaling following treatment with I2 prevention and rescue compared to S1P prevention and rescue, respectively. Furthermore, we observed increased cell migration following stimulation with I2 prevention and rescue groups, with decreased cell migration following stimulation with S1P prevention and rescue groups after 12 h and 18 h post-scratch. We have demonstrated that I2 treatment reduced fibrosis and modulated the inactivation of LTBPs, TGF-β receptors, SPLs, and the canonical downstream SMAD pathway. Further investigations are warranted in order to fully uncover the potential of utilizing SphK I2 as a novel therapy for corneal fibrosis.

Comprehensive Urinary Proteome Profiling Analysis Identifies Diagnosis and Relapse Surveillance Biomarkers for Bladder Cancer

Bladder cancer (BCa) is the predominant malignancy of the urinary system. Herein, a comprehensive urine proteomic feature was initially established for the noninvasive diagnosis and recurrence monitoring of bladder cancer. 279 cases (63 primary BCa, 87 nontumor controls (NT), 73 relapsed BCa (BCR), and 56 nonrelapsed BCa (BCNR)) were collected to screen urinary protein biomarkers. 4761 and 3668 proteins were qualified and quantified by DDA and sequential window acquisition of all theoretical mass spectra (SWATH-MS) analysis in two discovery sets, respectively. Upregulated proteins were validated by multiple reaction monitoring (MRM) in two independent combined sets. Using the multi-support vector machine-recursive feature elimination (mSVM-RFE) algorithm, a model comprising 13 proteins exhibited good performance between BCa and NT with an AUC of 0.821 (95% CI: 0.675-0.967), 90.9% sensitivity (95% CI: 72.7-100%), and 73.3% specificity (95% CI: 53.3-93.3%) in the diagnosis test set. Meanwhile, an 11-marker classifier significantly distinguished BCR from BCNR with 75.0% sensitivity (95% CI: 50.0-100%), 81.8% specificity (95% CI: 54.5-100%), and an AUC of 0.784 (95% CI: 0.609-0.959) in the test cohort for relapse surveillance. Notably, six proteins (SPR, AK1, CD2AP, ADGRF1, GMPS, and C8A) of 24 markers were newly reported. This paper reveals novel urinary protein biomarkers for BCa and offers new theoretical insights into the pathogenesis of bladder cancer (data identifier PXD044896).

Proteomics-Derived Biomarker Panel Facilitates Distinguishing Primary Lung Adenocarcinomas With Intestinal or Mucinous Differentiation From Lung Metastatic Colorectal Cancer

The diagnosis of primary lung adenocarcinomas with intestinal or mucinous differentiation (PAIM) remains challenging due to the overlapping histomorphological, immunohistochemical (IHC), and genetic characteristics with lung metastatic colorectal cancer (lmCRC). This study aimed to explore the protein biomarkers that could distinguish between PAIM and lmCRC. To uncover differences between the two diseases, we used tandem mass tagging-based shotgun proteomics to characterize proteomes of formalin-fixed, paraffin-embedded tumor samples of PAIM (n = 22) and lmCRC (n = 17).Then three machine learning algorithms, namely support vector machine (SVM), random forest, and the Least Absolute Shrinkage and Selection Operator, were utilized to select protein features with diagnostic significance. These candidate proteins were further validated in an independent cohort (PAIM, n = 11; lmCRC, n = 19) by IHC to confirm their diagnostic performance. In total, 105 proteins out of 7871 proteins were significantly dysregulated between PAIM and lmCRC samples and well-separated two groups by Uniform Manifold Approximation and Projection. The upregulated proteins in PAIM were involved in actin cytoskeleton organization, platelet degranulation, and regulation of leukocyte chemotaxis, while downregulated ones were involved in mitochondrial transmembrane transport, vasculature development, and stem cell proliferation. A set of ten candidate proteins (high-level expression in lmCRC: CDH17, ATP1B3, GLB1, OXNAD1, LYST, FABP1; high-level expression in PAIM: CK7 (an established marker), NARR, MLPH, S100A14) was ultimately selected to distinguish PAIM from lmCRC by machine learning algorithms. We further confirmed using IHC that the five protein biomarkers including CDH17, CK7, MLPH, FABP1 and NARR were effective biomarkers for distinguishing PAIM from lmCRC. Our study depicts PAIM-specific proteomic characteristics and demonstrates the potential utility of new protein biomarkers for the differential diagnosis of PAIM and lmCRC. These findings may contribute to improving the diagnostic accuracy and guide appropriate treatments for these patients.

Protein Signatures of Parathyroid Adenoma according to Tumor Volume and Functionality

BACKGRUOUND

Parathyroid adenoma (PA) is a common endocrine disease linked to multiple complications, but the pathophysiology of the disease remains incompletely understood. The study aimed to identify the key regulator proteins and pathways of PA according to functionality and volume through quantitative proteomic analyses.

METHODS

We conducted a retrospective study of 15 formalin-fixed, paraffin-embedded PA samples from tertiary hospitals in South Korea. Proteins were extracted, digested, and the resulting peptides were analyzed using liquid chromatography-tandem mass spectrometry. Pearson correlation analysis was employed to identify proteins significantly correlated with clinical variables. Canonical pathways and transcription factors were analyzed using Ingenuity Pathway Analysis.

RESULTS

The median age of the participants was 52 years, and 60.0% were female. Among the 8,153 protein groups analyzed, 496 showed significant positive correlations with adenoma volume, while 431 proteins were significantly correlated with parathyroid hormone (PTH) levels. The proteins SLC12A9, LGALS3, and CARM1 were positively correlated with adenoma volume, while HSP90AB2P, HLA-DRA, and SCD5 showed negative correlations. DCPS, IRF2BPL, and FAM98A were the main proteins that exhibited positive correlations with PTH levels, and SLITRK4, LAP3, and AP4E1 had negative correlations. Canonical pathway analysis demonstrated that the RAN and sirtuin signaling pathways were positively correlated with both PTH levels and adenoma volume, while epithelial adherence junction pathways had negative correlations.

CONCLUSION

Our study identified pivotal proteins and pathways associated with PA, offering potential therapeutic targets. These findings accentuate the importance of proteomics in understanding disease pathophysiology and the need for further research.

Ablation of Mitochondrial RCC1-L Induces Nigral Dopaminergic Neurodegeneration and Parkinsonian-like Motor Symptoms

Mitochondrial dysfunction has been linked to both idiopathic and familial forms of Parkinson's disease (PD). We have previously identified RCC1-like (RCC1L) as a protein of the inner mitochondrial membrane important to mitochondrial fusion. Herein, to test whether deficits in RCC1L mitochondrial function might be involved in PD pathology, we have selectively ablated the Rcc1l gene in the dopaminergic (DA) neurons of mice. A PD-like phenotype resulted that includes progressive movement abnormalities, paralleled by progressive degeneration of the nigrostriatal tract. Experimental and control groups were examined at 2, 3-4, and 5-6 months of age. Animals were tested in the open field task to quantify anxiety, exploratory drive, locomotion, and immobility; and in the cylinder test to quantify rearing behavior. Beginning at 3-4 months, both female and male Rcc1l knockout mice show rigid muscles and resting tremor, kyphosis and a growth deficit compared with heterozygous or wild type littermate controls. Rcc1l knockout mice begin showing locomotor impairments at 3-4 months, which progress until 5-6 months of age, at which age the Rcc1l knockout mice die. The progressive motor impairments were associated with progressive and significantly reduced tyrosine hydroxylase immunoreactivity in the substantia nigra pars compacta (SNc), and dramatic loss of nigral DA projections in the striatum. Dystrophic spherical mitochondria are apparent in the soma of SNc neurons in Rcc1l knockout mice as early as 1.5-2.5 months of age and become progressively more pronounced until 5-6 months. Together, the results reveal the RCC1L protein to be essential to in vivo mitochondrial function in DA neurons. Further characterization of this mouse model will determine whether it represents a new model for in vivo study of PD, and the putative role of the human RCC1L gene as a risk factor that might increase PD occurrence and severity in humans.

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

Analysis of the characteristics of immune infiltration in endometrial carcinoma and its relationship with prognosis based on bioinformatics

To explore immune-related molecules that affect the prognosis of endometrial carcinoma (EC) using bioinformatic data mining. The expression data related to EC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. After differential expression analysis, the intersection with immune related genes in the ImmPort database was used to obtain immune related differentially expressed genes (IRDEGs). The correlation between clinicopathological information and the prognosis of IRDEGs was further analyzed to obtain prognosis related differentially expressed immune genes (PRDEIG). Gene correlation analysis and Gene Set Enrichment Analysis (GSEA) enrichment analysis showed that PRDEIG was enriched in cancer-related functional pathways. We then analyzed the relationship between PRDEIG and immune cell infiltration, and further analyzed the mRNA and protein expression of PRDEIG in EC using TCGA and the human protein expression atlas (THPA) databases. After the intersection of the differential expression analysis results and immune-related genes, 4 IRDEGs were obtained: osteoglycin (OGN), LTBP4, CXCL12, and SPP1. After analyzing the relationship between 4 IRDEGs and clinicopathological parameters and prognosis of patients with EC, revealed that only OGN was not only related to tumor immunity, but also affected the prognosis of patients with EC. Gene correlation and GSEA enrichment of OGN were analyzed. The results showed that OGN was significantly enriched in 6 functional pathways: epithelial mesenchymal transition, KRAS signaling up, myogenesis, UV response, allograft rejection and apical junction. In addition, it was also found that OGN was significantly correlated with a variety of immune cells. The results of TCGA and THPA database showed that the mRNA and protein expression levels of OGN decreased in EC. OGN may affect the epithelial mesenchymal transformation (EMT) of tumor by affecting the infiltration of tumor immune cells.

Proteomic profiling of protein expression changes after 3 months-exercise in ESRD patients on hemodialysis

The prevalence of chronic kidney disease (CKD) is steadily increasing, and it is a global health burden. Exercise has been suggested to improve physical activity and the quality of life in patients with CKD, eventually reducing mortality. This study investigated the change in physical performance after exercise in dialysis-dependent patients with CKD and analyzed differentially expressed proteins before and after the exercise. Plasma samples were collected at enrollment and after 3 months of exercise. Liquid chromatography with tandem mass spectrometry analysis and data-independent acquisition results were analyzed to determine the significantly regulated proteins. A total of 37 patients on dialysis were recruited, and 16 were randomized to exercise for 3 months. The hand grip strength and the walking speed significantly improved in the exercise group. Proteome analysis revealed 60 significantly expressed proteins after 3 months of exercise. In the protein functional analysis, the significantly expressed proteins were involved in the immune response. Also, some of the key significantly expressed proteins [(M Matrix metallopeptidase 9 (MMP-9), Activin A Receptor Type 1B (ACVR1B), Fetuin B (FETUB)] were validated via an enzyme-linked immunosorbent assay. Our results showed that exercise in dialysis-dependent patients with CKD could improve their physical performance. These results indicated that this beneficial effect of exercise in these populations could be associated with immune response.

The Impact of Artificial Intelligence in the Odyssey of Rare Diseases

Emerging machine learning (ML) technologies have the potential to significantly improve the research and treatment of rare diseases, which constitute a vast set of diseases that affect a small proportion of the total population. Artificial Intelligence (AI) algorithms can help to quickly identify patterns and associations that would be difficult or impossible for human analysts to detect. Predictive modeling techniques, such as deep learning, have been used to forecast the progression of rare diseases, enabling the development of more targeted treatments. Moreover, AI has also shown promise in the field of drug development for rare diseases with the identification of subpopulations of patients who may be most likely to respond to a particular drug. This review aims to highlight the achievements of AI algorithms in the study of rare diseases in the past decade and advise researchers on which methods have proven to be most effective. The review will focus on specific rare diseases, as defined by a prevalence rate that does not exceed 1-9/100,000 on Orphanet, and will examine which AI methods have been most successful in their study. We believe this review can guide clinicians and researchers in the successful application of ML in rare diseases.

Biomarker Analysis of Formalin-Fixed Paraffin-Embedded Clinical Tissues Using Proteomics

The relatively recent developments in mass spectrometry (MS) have provided novel opportunities for this technology to impact modern medicine. One of those opportunities is in biomarker discovery and diagnostics. Key developments in sample preparation have enabled a greater range of clinical samples to be characterized at a deeper level using MS. While most of these developments have focused on blood, tissues have also been an important resource. Fresh tissues, however, are difficult to obtain for research purposes and require significant resources for long-term storage. There are millions of archived formalin-fixed paraffin-embedded (FFPE) tissues within pathology departments worldwide representing every possible tissue type including tumors that are rare or very small. Owing to the chemical technique used to preserve FFPE tissues, they were considered intractable to many newer proteomics techniques and primarily only useful for immunohistochemistry. In the past couple of decades, however, researchers have been able to develop methods to extract proteins from FFPE tissues in a form making them analyzable using state-of-the-art technologies such as MS and protein arrays. This review will discuss the history of these developments and provide examples of how they are currently being used to identify biomarkers and diagnose diseases such as cancer.

Modulation of Autophagy in Adrenal Tumors

Adrenal masses are one of the most common tumors in humans. The majority are benign and non-functioning and therefore do not require immediate treatment. In contrast, the rare adrenal malignant tumors are often highly aggressive and with poor prognosis. Besides usually being detected in advanced stages, often already with metastases, one of the reasons of the unfavorable outcome of the patients with adrenal cancer is the absence of effective treatments. Autophagy is one of the intracellular pathways targeted by several classes of chemotherapeutics. Mitotane, the most commonly used drug for the treatment of adrenocortical carcinoma, was recently shown to also modulate autophagy. Autophagy is a continuous programmed cellular process which culminates with the degradation of cellular organelles and proteins. However, being a dynamic mechanism, understanding the autophagic flux can be highly complex. The role of autophagy in cancer has been described paradoxically: initially described as a tumor pro-survival mechanism, different studies have been showing that it may result in other outcomes, namely in tumor cell death. In adrenal tumors, this dual role of autophagy has also been addressed in recent years. Studies reported both induction and inhibition of autophagy as a treatment strategy of adrenal malignancies. Importantly, most of these studies were performed using cell lines. Consequently clinical studies are still required. In this review, we describe what is known about the role of autophagy modulation in treatment of adrenal tumors. We will also highlight the aspects that need further evaluation to understand the paradoxical role of autophagy in adrenal tumors.

Potential of Mitochondrial Ribosomal Genes as Cancer Biomarkers Demonstrated by Bioinformatics Results

Next-generation sequencing and bioinformatics analyses have clearly revealed the roles of mitochondrial ribosomal genes in cancer development. Mitochondrial ribosomes are composed of three RNA components encoded by mitochondrial DNA and 82 specific protein components encoded by nuclear DNA. They synthesize mitochondrial inner membrane oxidative phosphorylation (OXPHOS)-related proteins and participate in various biological activities via the regulation of energy metabolism and apoptosis. Mitochondrial ribosomal genes are strongly associated with clinical features such as prognosis and foci metastasis in patients with cancer. Accordingly, mitochondrial ribosomes have become an important focus of cancer research. We review recent advances in bioinformatics research that have explored the link between mitochondrial ribosomes and cancer, with a focus on the potential of mitochondrial ribosomal genes as biomarkers in cancer.

KIAA1363-A Multifunctional Enzyme in Xenobiotic Detoxification and Lipid Ester Hydrolysis

KIAA1363, annotated as neutral cholesterol ester hydrolase 1 (NCEH1), is a member of the arylacetamide deacetylase (AADAC) protein family. The name-giving enzyme, AADAC, is known to hydrolyze amide and ester bonds of a number of xenobiotic substances, as well as clinical drugs and of endogenous lipid substrates such as diglycerides, respectively. Similarly, KIAA1363, annotated as the first AADAC-like protein, exhibits enzymatic activities for a diverse substrate range including the xenobiotic insecticide chlorpyrifos oxon and endogenous substrates, acetyl monoalkylglycerol ether, cholesterol ester, and retinyl ester. Two independent knockout mouse models have been generated and characterized. However, apart from reduced acetyl monoalkylglycerol ether and cholesterol ester hydrolase activity in specific tissues and cell types, no gross-phenotype has been reported. This raises the question of its physiological role and whether it functions as drug detoxifying enzyme and/or as hydrolase/lipase of endogenous substrates. This review delineates the current knowledge about the structure, function and of the physiological role of KIAA1363, as evident from the phenotypical changes inflicted by pharmacological inhibition or by silencing as well as knockout of KIAA1363 gene expression in cells, as well as mouse models, respectively.