Expression signature, prognosis value and immune characteristics of cathepsin F in non-small cell lung cancer identified by bioinformatics assessment

Reduced expression of cathepsin F predicts poor prognosis in patients with clear cell renal cell carcinoma

Abnormalities in the extracellular matrix (ECM) play important roles in the regulation and progression of clear cell renal cell carcinoma (ccRCC). The cysteine cathepsin is one of the major proteases involved in ECM remodeling and has been shown to be aberrantly expressed in multiple cancer types. However, the clinical significance and biological function of distinct cysteine cathepsins in ccRCC remain poorly understood. In this study, several bioinformatics databases, including UALCAN, TIMER, GEPIA and the Human Protein Atlas datasets, were used to analyze the expression and prognostic value of different cysteine cathepsin family members in ccRCC. We found that the expression level of CTSF was downregulated in tumor tissues and closely related to the poor survival of ccRCC patients. Further in vitro experiments suggested that CTSF overexpression suppressed the proliferation and migration of ccRCC cells. Moreover, the expression of CTSF was shown to be associated with several immune-infiltrating cells and immunomodulators in ccRCC. These results indicated that CTSF might be a promising diagnostic and prognostic marker in ccRCC.

Unveiling the Roles of Cysteine Proteinases F and W: From Structure to Pathological Implications and Therapeutic Targets

Cysteine cathepsins F and W are members of the papain-like cysteine protease family, which have distinct structural features and functional roles in various physiological and pathological processes. This review provides a comprehensive overview of the current understanding of the structure, biological functions, and pathological implications of cathepsins F and W. Beginning with an introduction to these proteases, we delve into their structural characteristics and elucidate their unique features that dictate their enzymatic activities and substrate specificity. We also explore the intricate involvement of cathepsins F and W in malignancies, highlighting their role as potential biomarkers and therapeutic targets in cancer progression. Furthermore, we discuss the emerging roles of these enzymes in immune response modulation and neurological disorders, shedding light on their implications in autoimmune and neurodegenerative diseases. Finally, we review the landscape of inhibitors targeting these proteases, highlighting their therapeutic potential and challenges in clinical translation. This review brings together the diverse facets of cysteine cathepsins F and W, providing insights into their roles in health and disease and guiding future investigations for therapeutic advances.

ZEPPI: Proteome-scale sequence-based evaluation of protein-protein interaction models

We introduce ZEPPI (Z-score Evaluation of Protein-Protein Interfaces), a framework to evaluate structural models of a complex based on sequence coevolution and conservation involving residues in protein-protein interfaces. The ZEPPI score is calculated by comparing metrics for an interface to those obtained from randomly chosen residues. Since contacting residues are defined by the structural model, this obviates the need to account for indirect interactions. Further, although ZEPPI relies on species-paired multiple sequence alignments, its focus on interfacial residues allows it to leverage quite shallow alignments. ZEPPI can be implemented on a proteome-wide scale and is applied here to millions of structural models of dimeric complexes in the Escherichia coli and human interactomes found in the PrePPI database. PrePPI's scoring function is based primarily on the evaluation of protein-protein interfaces, and ZEPPI adds a new feature to this analysis through the incorporation of evolutionary information. ZEPPI performance is evaluated through applications to experimentally determined complexes and to decoys from the CASP-CAPRI experiment. As we discuss, the standard CAPRI scores used to evaluate docking models are based on model quality and not on the ability to give yes/no answers as to whether two proteins interact. ZEPPI is able to detect weak signals from PPI models that the CAPRI scores define as incorrect and, similarly, to identify potential PPIs defined as low confidence by the current PrePPI scoring function. A number of examples that illustrate how the combination of PrePPI and ZEPPI can yield functional hypotheses are provided.

ALAS2 overexpression alleviates oxidative stress-induced ferroptosis in aortic aneurysms via GATA1 activation

Background

Aortic aneurysm, characterized by abnormal dilation of the aorta, poses significant health risks. This study aims to investigate the interaction between 5-aminolevulinate synthase 2 (ALAS2) and GATA-binding protein 1 (GATA1) in ferroptosis and oxidative stress responses in aortic aneurysm.

Methods

A weighted gene co-expression network analysis (WGCNA) was performed on the differentially expressed genes (DEGs) within the GSE9106 dataset to identify the key module. Subsequently, protein-protein interaction (PPI) network analysis was performed on the key module. Mouse aortic vascular smooth muscle cells (MOVAS) were treated with hydrogen peroxide (H2O2) to induce oxidative stress, and ferroptosis inducers and inhibitors were added to evaluate their effects on iron content and oxidative stress markers. Through a series of in vitro cellular experiments, we assessed cell viability, expression levels of GATA1 and iron mutation-associated proteins, as well as cellular phenotypes such as inflammatory responses and apoptosis rates.

Results

Three candidate genes (ALAS2, GYPA, and GYPB) were upregulated in the thoracic aortic aneurysm (TAA) samples of the GSE9106 dataset. The H2O2 treatment increased the MOVAS cells' iron content and oxidative stress, upregulated ALAS2 protein levels, and decreased the ferroptosis-related protein levels. ALAS2 overexpression reversed H2O2-induced apoptosis and increased the inflammatory cytokine levels. Additionally, the knockdown of GATA1 partially reversed the protective mechanism of overexpressed ALAS2 on H2O2-induced ferroptosis.

Conclusions

ALAS2 overexpression reduced H2O2-induced oxidative damage and iron-induced apoptosis in MOVAS cells, and GATA1 knockdown partially reversed this protective effect. These findings suggested that the ALAS2 and GATA1 regulatory pathways may be potential therapeutic targets in aortic aneurysms.

Mendelian randomization analyses explore the relationship between cathepsins and lung cancer

Lung cancer, a major contributor to cancer-related fatalities worldwide, involves a complex pathogenesis. Cathepsins, lysosomal cysteine proteases, play roles in various physiological and pathological processes, including tumorigenesis. Observational studies have suggested an association between cathepsins and lung cancer. However, the causal link between the cathepsin family and lung cancer remains undetermined. This study employed Mendelian randomization analyses to investigate this causal association. The univariable Mendelian randomization analysis results indicate that elevated cathepsin H levels increase the overall risk of lung cancer, adenocarcinoma, and lung cancer among smokers. Conversely, reverse Mendelian randomization analyses suggest that squamous carcinoma may lead to increased cathepsin B levels. A multivariable analysis using nine cathepsins as covariates reveals that elevated cathepsin H levels lead to an increased overall risk of lung cancer, adenocarcinoma, and lung cancer in smokers. In conclusion, cathepsin H may serve as a marker for lung cancer, potentially inspiring directions in lung cancer diagnosis and treatment.

Down regulation of Cathepsin W is associated with poor prognosis in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis. Therefore, there has been a focus on identifying new biomarkers for its early diagnosis and the prediction of patient survival. Genome-wide RNA and microRNA sequencing, bioinformatics and Machine Learning approaches to identify differentially expressed genes (DEGs), followed by validation in an additional cohort of PDAC patients has been undertaken. To identify DEGs, genome RNA sequencing and clinical data from pancreatic cancer patients were extracted from The Cancer Genome Atlas Database (TCGA). We used Kaplan-Meier analysis of survival curves was used to assess prognostic biomarkers. Ensemble learning, Random Forest (RF), Max Voting, Adaboost, Gradient boosting machines (GBM), and Extreme Gradient Boosting (XGB) techniques were used, and Gradient boosting machines (GBM) were selected with 100% accuracy for analysis. Moreover, protein-protein interaction (PPI), molecular pathways, concomitant expression of DEGs, and correlations between DEGs and clinical data were analyzed. We have evaluated candidate genes, miRNAs, and a combination of these obtained from machine learning algorithms and survival analysis. The results of Machine learning identified 23 genes with negative regulation, five genes with positive regulation, seven microRNAs with negative regulation, and 20 microRNAs with positive regulation in PDAC. Key genes BMF, FRMD4A, ADAP2, PPP1R17, and CACNG3 had the highest coefficient in the advanced stages of the disease. In addition, the survival analysis showed decreased expression of hsa.miR.642a, hsa.mir.363, CD22, BTNL9, and CTSW and overexpression of hsa.miR.153.1, hsa.miR.539, hsa.miR.412 reduced survival rate. CTSW was identified as a novel genetic marker and this was validated using RT-PCR. Machine learning algorithms may be used to Identify key dysregulated genes/miRNAs involved in the disease pathogenesis can be used to detect patients in earlier stages. Our data also demonstrated the prognostic and diagnostic value of CTSW in PDAC.

Cysteine Cathepsins as Therapeutic Targets in Immune Regulation and Immune Disorders

Cysteine cathepsins, as the most abundant proteases found in the lysosomes, play a vital role in several processes-such as protein degradation, changes in cell signaling, cell morphology, migration and proliferation, and energy metabolism. In addition to their lysosomal function, they are also secreted and may remain functional in the extracellular space. Upregulation of cathepsin expression is associated with several pathological conditions including cancer, neurodegeneration, and immune-system dysregulation. In this review, we present an overview of cysteine-cathepsin involvement and possible targeting options for mitigation of aberrant function in immune disorders such as inflammation, autoimmune diseases, and immune response in cancer.

LAG-3 as a Potent Target for Novel Anticancer Therapies of a Wide Range of Tumors

LAG-3 (Lymphocyte activation gene 3) protein is a checkpoint receptor that interacts with LSEC-tin, Galectin-3 and FGL1. This interaction leads to reduced production of IL-2 and IFN-γ. LAG-3 is widely expressed in different tumor types and modulates the tumor microenvironment through immunosuppressive effects. Differential expression in various tumor types influences patient prognosis, which is often associated with coexpression with immune checkpoint inhibitors, such as TIM-3, PD-1 and CTLA-4. Here, we discuss expression profiles in different tumor types. To date, many clinical trials have been conducted using LAG-3 inhibitors, which can be divided into anti-LAG-3 monoclonal antibodies, anti-LAG-3 bispecifics and soluble LAG-3-Ig fusion proteins. LAG-3 inhibitors supress T-cell proliferation and activation by disallowing for the interaction between LAG-3 to MHC-II. The process enhances anti-tumor immune response. In this paper, we will review the current state of knowledge on the structure, function and expression of LAG-3 in various types of cancer, as well as its correlation with overall prognosis, involvement in cell-based therapies and experimental medicine. We will consider the role of compounds targeting LAG-3 in clinical trials both as monotherapy and in combination, which will provide data relating to the efficacy and safety of proposed drug candidates.

Glycosylated Cathepsin V Serves as a Prognostic Marker in Lung Cancer

Dysregulation of cysteine cathepsin protease activity is pivotal in tumorigenic transformation. However, the role of cathepsin protease in lung cancer remains unknown. Here, we analyzed GEO database and found that lung cancer presented high expression of cathepsin V (CTSV). We then performed immunohistochemistry assay in 73 paired lung cancer tissues and normal lung tissues and confirmed that CTSV is overexpressed in lung cancer and correlates with poor prognosis. The mass spectrometry experiment showed that the N-glycosylation locus of CTSV are N221 and N292, glycosylated CTSV (band 43 kDa) was particularly expressed in lung cancer samples and correlated with lymph node metastasis. Mechanistic studies showed that only glycosylated CTSV (43-kDa band) are secreted to extracellular matrix (ECM) and promoted the metastasis of lung cancer. Importantly, the Elisa detection in serum of 12 lung cancer patients and 12 healthy donors showed that the level of CTSV in serum distinguished lung cancer patients from healthy donors. Together, our findings reveal the clinical relevance of CTSV glycosylation and CTSV drives the metastasis of lung cancer, suggesting that the glycosylated CTSV in serum is a promising biomarker for lung cancer.