Secretome analysis reveals upregulated granzyme B in human androgen-repressed prostate cancer cells with mesenchymal and invasive phenotype

Granzyme B Promotes Proliferation, Migration and EMT Process in Gastric Cancer

Granzyme B (GZMB), a critical member of the Gr gene family, is known to play an essential role in diverse physiological and pathological processes such as inflammation, acute and chronic inflammatory diseases, and cancer progression. In this study, we delve deeper into the role of GZMB within the context of gastric cancer (GC) to examine its expression patterns and functional implications. To accomplish this, we applied a combination of quantitative real-time polymerase chain reaction, western blotting, and immunohistochemistry techniques. These methodologies allowed us to accurately gauge GZMB expression levels in GC tissues and investigate their correlation with various clinical-pathological variables. Our secondary focus was to discern the regulatory influence of GZMB on GC cell biology. We used an array of assays including cell counting kit-8 (CCK-8), colony formation, 5-ethynyl-2'-deoxyuridine, and migration assays. The effect of GZMB on gastric cancer progression was further validated through a subcutaneous xenograft mouse model. Our findings underscored that GZMB mRNA and protein levels were upregulated in GC tissues, a feature that showed a significant correlation with GC staging. We also discovered that a decrease in GZMB expression via knockdown experiments suppressed the proliferation and migration capabilities of GC cells. This effect was manifested through diminished expression levels of epithelial-mesenchymal transition (EMT) markers. In stark contrast, the overexpression of GZMB through plasmid transfection appeared to enhance the proliferation and migration abilities of GC cells. This was coupled with an upregulation in EMT expression. Our study concludes by emphasizing that GZMB promotes the growth, migration, and EMT processes in gastric cancer. In vitro, cell-based experiments and in vivo xenograft mouse models confirm this. Our findings provide a more comprehensive understanding of GZMB's role in gastric cancer pathogenesis, potentially opening doors for novel therapeutic strategies targeting this molecular pathway.

Inflammation and Immunity Gene Expression Patterns and Machine Learning Approaches in Association with Response to Immune-Checkpoint Inhibitors-Based Treatments in Clear-Cell Renal Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. Despite the rapid evolution of targeted therapies, immunotherapy with checkpoint inhibition (ICI) as well as combination therapies, the cure of metastatic ccRCC (mccRCC) is infrequent, while the optimal use of the various novel agents has not been fully clarified. With the different treatment options, there is an essential need to identify biomarkers to predict therapeutic efficacy and thus optimize therapeutic approaches. This study seeks to explore the diversity in mRNA expression profiles of inflammation and immunity-related circulating genes for the development of biomarkers that could predict the effectiveness of immunotherapy-based treatments using ICIs for individuals with mccRCC. Gene mRNA expression was tested by the RT2 profiler PCR Array on a human cancer inflammation and immunity crosstalk kit and analyzed for differential gene expression along with a machine learning approach for sample classification. A number of mRNAs were found to be differentially expressed in mccRCC with a clinical benefit from treatment compared to those who progressed. Our results indicate that gene expression can classify these samples with high accuracy and specificity.

Cancer secretome: finding out hidden messages in extracellular secretions

Secretome analysis has gained popularity recently as a very well-designed proteomic approach that is being used to study various interactions and their effects on cellular activity. This analysis is especially helpful while studying the effects of the cells on their microenvironment, paracrine and autocrine processes, their therapeutic purposes, and as a new diagnostic perspective. Cancer is a condition rather than a specific type of disease and is still yet to be fully understood. Cancer secretome is a fairly new concept that is being implemented to examine the interactions taking place in the tumor microenvironment and can help to understand the phenomena like induction of tumorigenesis, stimulation of immune cells, etc. The secretome analysis helps to gain a different perspective on the existing knowledge on cancer and its effects. The recent advances in secretome studies are directed toward secreted components as drug targets, biomarkers, and companion tools for diagnostic and prognostic purposes in cancer. This review aims to find the interactors in different types of cancer and understand the existing unstructured secretome data and its application in prognosis, diagnosis, and in biomarker study.

Studies of hormonal regulation, phenotype plasticity, bone metastasis, and experimental therapeutics in androgen-repressed human prostate cancer (ARCaP) model

First established by Dr. Leland W. K. Chung's lab, the androgen-repressed prostate cancer cell (ARCaP) line is derived from the ascitic fluid of a prostate cancer (PCa) patient with widely metastatic disease. Based on its unique characteristic of growth suppression in the presence of androgen, ARCaP cell line has contributed to the research of PCa disease progression toward therapy- and castration-resistant PCa (t-CRPC). It has been widely applied in studies exploring experimental therapeutic reagents including Genistein, Vorinostat and Silibinin. ARCaP cells have showed increased metastatic potential to the bone and soft tissues. In addition, accumulating studies using ARCaP model have demonstrated the epithelial-to-mesenchymal transitional plasticity of PCa using epithelial-like ARCaP_E line treated in vitro with growth factors derived from bone microenvironment. The resulting mesenchymal-like ARCaP_M sub-clone derived from bone-metastasized tumor has high expression of several factors correlated with cancer metastasis, such as N-Cadherin, Vimentin, MCM3, Granzyme B, β2-microglobulin and RANKL. In particular, the increased secretion of RANKL in ARCaP_M further facilitates its capacity of inducing osteoclastogenesis at the bone microenvironment, leading to bone resorption and tumor colonization. Meanwhile, sphingosine kinase 1 (SphK1) acts as a key molecule driver in the neuroendocrine differentiation (NED) of ARCaP sublines, suggesting the unique facet of ARCaP cells for insightful studies in more malignant neuroendocrine prostate cancer (NEPC). Overall, the establishment of ARCaP line has provided a valuable model to explore the mechanisms underlying PCa progression toward metastatic t-CRPC. In this review, we will focus on the contribution of ARCaP model in PCa research covering hormone receptor activity, skeletal metastasis, plasticity of epithelial-to-mesenchymal transition (EMT) and application of therapeutic strategies.