The utility of tetraspanin CD9 as a biomarker for metastatic clear cell renal cell carcinoma

An updated review on the development of a nanomaterial-based field-effect transistor-type biosensors to detect exosomes for cancer diagnosis

Cancer, a life-threatening genetic disease caused by abnormalities in normal cell growth regulatory functions, poses a significant challenge that current medical technologies cannot fully overcome. The current desired breakthrough is to diagnose cancer as early as possible and increase survival rates through treatments tailored to the prognosis and appropriate follow-up. From a perspective that reflects this contemporary paradigm of cancer diagnostics, exosomes are emerging as promising biomarkers. Exosomes, serving as mobile biological information repositories of cancer cells, have been known to create a microtumor environment in surrounding cells, and significant insight into the clinical significance of cancer diagnosis targeting them has been reported. Therefore, there are growing interests in constructing a system that enables continuous screening with a focus on patient-friendly and flexible diagnosis, aiming to improve cancer screening rates through exosome detection. This review focuses on a proposed exosome-embedded biological information-detecting platform employing a field-effect transistor (FET)-based biosensor that leverages portability, cost-effectiveness, and rapidity to minimize the stages of sacrifice attributable to cancer. The FET-applied biosensing technique, stemming from variations in an electric field, is considered an early detection system, offering high sensitivity and a prompt response frequency for the qualitative and quantitative analysis of biomolecules. Hence, an in-depth discussion was conducted on the understanding of various exosome-based cancer biomarkers and the clinical significance of recent studies on FET-based biosensors applying them.

Machine learning-driven mast cell gene signatures for prognostic and therapeutic prediction in prostate cancer

Background

The role of Mast cells has not been thoroughly explored in the context of prostate cancer's (PCA) unpredictable prognosis and mixed immunotherapy outcomes. Our research aims to employs a comprehensive computational methodology to evaluate Mast cell marker gene signatures (MCMGS) derived from a global cohort of 1091 PCA patients. This approach is designed to identify a robust biomarker to assist in prognosis and predicting responses to immunotherapy.

Methods

This study initially identified mast cell-associated biomarkers from prostate adenocarcinoma (PRAD) patients across six international cohorts. We employed a variety of machine learning techniques, including Random Forest, Support Vector Machine (SVM), Lasso regression, and the Cox Proportional Hazards Model, to develop an effective MCMGS from candidate genes. Subsequently, an immunological assessment of MCMGS was conducted to provide new insights into the evaluation of immunotherapy responses and prognostic assessments. Additionally, we utilized Gene Set Enrichment Analysis (GSEA) and pathway analysis to explore the biological pathways and mechanisms associated with MCMGS.

Results

MCMGS incorporated 13 marker genes and was successful in segregating patients into distinct high- and low-risk categories. Prognostic efficacy was confirmed by survival analysis incorporating MCMGS scores, alongside clinical parameters such as age, T stage, and Gleason scores. High MCMGS scores were correlated with upregulated pathways in fatty acid metabolism and β-alanine metabolism, while low scores correlated with DNA repair mechanisms, homologous recombination, and cell cycle progression. Patients classified as low-risk displayed increased sensitivity to drugs, indicating the utility of MCMGS in forecasting responses to immune checkpoint inhibitors.

Conclusion

The combination of MCMGS with a robust machine learning methodology demonstrates considerable promise in guiding personalized risk stratification and informing therapeutic decisions for patients with PCA.

Antioxidant Iron Oxide Nanoparticles: Their Biocompatibility and Bioactive Properties

A lot of nanomaterials have been applied to various nano-biotechnological fields, such as contrast agents, drug or gene delivery systems, cosmetics, and so on. Despite the expanding usage of nanomaterials, concerns persist regarding their potential toxicity. To address this issue, many scientists have tried to develop biocompatible nanomaterials containing phytochemicals as a promising solution. In this study, we synthesized biocompatible nanomaterials by using gallic acid (GA), which is a phytochemical, and coating it onto the surface of iron oxide nanoparticles (IONPs). Importantly, the GA-modified iron oxide nanoparticles (GA-IONPs) were successfully prepared through environmentally friendly methods, avoiding the use of harmful reagents and extreme conditions. The presence of GA on the surface of IONPs improved their stability and bioactive properties. In addition, cell viability assays proved that GA-IONPs possessed excellent biocompatibility in human dermal papilla cells (HDPCs). Additionally, GA-IONPs showed antioxidant activity, which reduced intracellular reactive oxygen species (ROS) levels in an oxidative stress model induced by hydrogen peroxide (H2O2). To investigate the impact of GA-IONPs on exosome secretions from oxidative stress-induced cells, we analyzed the number and characteristics of exosomes in the culture media of HDPCs after H2O2 stimulation or GA-IONP treatment. Our analysis revealed that both the number and proportions of tetraspanins (CD9, CD81, and CD63) in exosomes were similar in the control group and the GA-IONP-treated groups. In contrast, exosome secretion was increased, and the proportion of tetraspanin was changed in the H2O2-treated group compared to the control group. It demonstrated that treatment with GA-IONPs effectively attenuated exosome secretion induced by H2O2-induced oxidative stress. Therefore, this GA-IONP exhibited outstanding promise for applications in the field of nanobiotechnology.

Exosomes, new biomarkers in early cancer detection

Exosomes are endosomal-derived vesicles, playing a major role in cell-to-cell communication. Multiple cells secret these vesicles to induce and inhibit different cellular and molecular pathways. Cancer-derived exosomes have been shown to affect development of cancer in different stages and contribute to the recruitment and reprogramming of both proximal and distal tissues. The growing interest in defining the clinical relevance of these nano-sized particles in cancers, has led to the identification of either tissue- or disease-specific exosomal contents, such as nucleic acids, proteins and lipids as a source of new biomarkers which propose the diagnostic potentials of exosomes in early detection of cancers. In this review, we have discussed some aspects of exosomes including their contents, applications and isolation techniques in the field of early cancer detection. Although, exosomes are considered as ideal biomarkers in cancer diagnosis, due to their unique characteristics, there is still a long way in the development of exosome-based assays.

CD9 Tetraspanin: A New Pathway for the Regulation of Inflammation?

CD9 belongs to the tetraspanin superfamily. Depending on the cell type and associated molecules, CD9 has a wide variety of biological activities such as cell adhesion, motility, metastasis, growth, signal transduction, differentiation, and sperm-egg fusion. This review focuses on CD9 expression by hematopoietic cells and its role in modulating cellular processes involved in the regulation of inflammation. CD9 is functionally very important in many diseases and is involved either in the regulation or in the mediation of the disease. The role of CD9 in various diseases, such as viral and bacterial infections, cancer and chronic lung allograft dysfunction, is discussed. This review focuses also on its interest as a biomarker in diseases. Indeed CD9 is primarily known as a specific exosome marker however, its expression is now recognized as an anti-inflammatory marker of monocytes and macrophages. It was also described as a marker of murine IL-10-competent Breg cells and IL-10-secreting CD9⁺ B cells were associated with better allograft outcome in lung transplant patients, and identified as a new predictive biomarker of long-term survival. In the field of cancer, CD9 was both identified as a favorable prognostic marker or as a predictor of metastatic potential depending on cancer types. Finally, this review discusses strategies to target CD9 as a therapeutic tool. Because CD9 can have opposite effects depending on the situation, the environment and the pathology, modulating CD9 expression or blocking its effects seem to be a new promising therapeutic strategy.

CD9 expression indicates a poor outcome in acute lymphoblastic leukemia

OBJECTIVE

We undertook a single-center retrospective study to determine the relationship between CD9 and acute lymphoblastic leukemia (ALL).

MATERIALS AND METHODS

In total, 112 newly diagnosed patients in our center were enrolled in the study. Their clinical information was collected and the patients werefollowed over the course of the study. Flow cytometry was used to detect the expression of CD9.

RESULTS

CD9 expression was more common in B cell acute lymphoblastic leukemia (B-ALL) and patients > 40 years old. CD9-positive patients exhibited a higher BCR-ABL fusion gene positive rate and higher neutrophil counts than CD9 negative patients (P= 0.004 and P= 0.004, respectively). Response to induction chemotherapy was not dependent on CD9 expression. CD9-positive patients had a lower 2-year overall survival rate than CD9-negative patients.

CONCLUSION

CD9 expression predicts some clinical characteristics and indicates an unfavorable prognosis in ALL patients.