CD39 transforming cancer therapy by modulating tumor microenvironment.

CD39 is a pivotal enzyme in cancer, regulating immune response and tumor progression via extracellular ATP and adenosine in the tumor microenvironment (TME). Beyond its established immunoregulatory function, CD39 influences cancer cell angiogenesis and metabolism, opening new frontiers for therapeutic interventions. Current research faces gaps in understanding CD39's full impact across cancer types, with ongoing debates about its potential beyond modulating immune evasion. This review distills CD39's multifaceted roles, examining its dual actions and implications for cancer prognosis and treatment. We analyze the latest therapeutic strategies, highlighting the need for an integrated approach that combines molecular insights with TME dynamics to innovate cancer care. This synthesis underscores CD39's integral role, charting a course for precision oncology that seeks to unravel controversies and harness CD39's therapeutic promise for improved cancer outcomes.

Cytokines and soluble mediators as architects of tumor microenvironment reprogramming in cancer therapy.

Navigating the intricate landscape of the tumor microenvironment (TME) unveils a pivotal arena for cancer therapeutics, where cytokines and soluble mediators emerge as double-edged swords in the fight against cancer. This review ventures beyond traditional perspectives, illuminating the nuanced interplay of these elements as both allies and adversaries in cancer dynamics. It critically evaluates the evolving paradigms of TME reprogramming, spotlighting innovative strategies that target the sophisticated network of cytokines and mediators. Special focus is placed on unveiling the therapeutic potential of novel cytokines and mediators, particularly their synergistic interactions with extracellular vesicles, which represent underexplored conduits for therapeutic targeting. Addressing a significant gap in current research, we explore the untapped potential of these biochemical players in orchestrating immune responses, tumor proliferation, and metastasis. The review advocates for a paradigm shift towards exploiting these dynamic interactions within the TME, aiming to transcend conventional treatments and pave the way for a new era of precision oncology. Through a critical synthesis of recent advancements, we highlight the imperative for innovative approaches that harness the full spectrum of cytokine and mediator activities, setting the stage for breakthrough therapies that offer heightened specificity, reduced toxicity, and improved patient outcomes.

A novel risk signature based on liquid-liquid phase separation-related genes reveals prognostic and tumour microenvironmental features in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma(ccRCC) is one of the most common malignancies. However, there are still many barriers to its underlying causes, early diagnostic techniques and therapeutic approaches. MATERIALS AND METHODS: The Cancer Genome Atlas (TCGA)- Kidney renal clear cell (KIRC) cohort differentially analysed liquid-liquid phase separation (LLPS)-related genes from the DrLLPS website. Univariate and multivariate Cox regression analyses and LASSO regression analyses were used to construct prognostic models. The E-MTAB-1980 cohort was used for external validation. Then, potential functions, immune infiltration analysis, and mutational landscapes were analysed for the high-risk and low-risk groups. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) experiments as well as single-cell analyses validated the genes key to the model. RESULTS: We screened 174 LLPS-related genes in ccRCC and constructed a risk signature consisting of five genes (CLIC5, MXD3, NUF2, PABPC1L, PLK1). The high-risk group was found to be associated with worse prognosis in different subgroups. A nomogram constructed by combining age and tumour stage had a strong predictive power for the prognosis of ccRCC patients. In addition, there were differences in pathway enrichment, immune cell infiltration, and mutational landscapes between the two groups. The results of qRT-PCR in renal cancer cell lines and renal cancer tissues were consistent with the biosignature prediction. Three single-cell data of GSE159115, GSE139555, and GSE121636 were analysed for differences in the presence of these five genes in different cells. CONCLUSIONS: We developed a risk signature constructed based on the five LLPS-related genes and can have a high ability to predict the prognosis of ccRCC patients, further providing a strong support for clinical decision-making.

Expression and function of VISTA on myeloid cells.

V-domain containing Ig Suppressor of T cell Activation (VISTA) is predominantly expressed on myeloid cells and functions as a ligand/receptor/soluble molecule. In inflammatory responses and immune responses, VISTA regulates multiple functions of myeloid cells, such as chemotaxis, phagocytosis, T cell activation. Since inflammation and immune responses are critical in many diseases, VISTA is a promising therapeutic target. In this review, we will describe the expression and function of VISTA on different myeloid cells, including neutrophils, monocytes, macrophages, dendritic cells (DCs), myeloid-derived suppressor cells (MDSCs). In addition, we will discuss whether the functions of VISTA on these cells impact the disease processing.

Polysaccharide extracted from the Sargassum fusiforme induces cell cycle arrest and apoptosis of B16F10 melanoma cells through the PI3K/AKT pathway.

BACKGROUND: SARGASSUM FUSIFORME: (S. fusiforme) is a brown alga that has been utilized as a medicine for a long time. Polysaccharides extracted from S. fusiforme demonstrate antitumor activities. METHODS: The impact of S. fusiforme polysaccharides (SFPS 191,212) on the proliferation, apoptosis, and cell cycle kinetics of B16F10 murine melanoma cells were thoroughly investigated in this work. The anticancer activities of the SFPS 191,212 compounds were assayed in the B16F10 cells at both transcriptional and translational levels. RESULTS: The compound exhibited concentration-dependent effects. Moreover, SPFS 191,212 increased the numbers of apoptotic cells and arrested the cell cycle in the S phase of the quantitative real-time PCR. From western blotting, it was verified that the SFPS 191,212 treatment improved the expression of Bax, Caspase-9, and Caspase-3 genes and proteins, while it reduced phosphatidylinositol 3 kinase and Bcl-2 genes and proteins, suggesting the involvement of mitochondria. CONCLUSION: Overall, SFPS 191,212 can be further explored as a potential functional food or adjuvant agent for the prevention or treatment of melanoma.

Chemotherapy induces immune checkpoint VISTA expression in tumor cells via HIF-2alpha.

Tumor cells can evade the innate and adaptive immune systems, which play important roles in tumor recurrence and metastasis. Malignant tumors that recur after chemotherapy are more aggressiveciscis, suggesting an increased ability of the surviving tumor cells to evade innate and adaptive immunity. Therefore, in order to reduce patient mortality, it is important to discover the mechanisms by which tumor cells develop resistance to chemotherapeutics. In the present study we focused on the tumor cells that survived chemotherapy. We found that chemotherapy could promote the expression of VISTA in tumor cells, and that this change was mediated by HIF-2α. In addition, VISTA overexpression on melanoma cells promoted immune evasion, and the application of the VISTA-blocking antibody 13F3 enhanced the therapeutic effect of carboplatin. These results offer an insight into the immune evasion of chemotherapy-resistant tumors, and provide a theoretical basis for the combined application of chemotherapy drugs and VISTA inhibitors to treat tumors.

An efficient multi-threshold image segmentation for skin cancer using boosting whale optimizer.

Due to the terrible manifestations of skin cancer, it seriously disturbs the quality of life status and health of patients, so we needs treatment plans to detect it early and avoid it causing more harm to patients. Medical disease image threshold segmentation technique can well extract the region of interest and effectively assist in disease recognition. Moreover, in multi-threshold image segmentation, the selection of the threshold set determines the image segmentation quality. Among the common threshold selection methods, the selection based on metaheuristic algorithm has the advantages of simplicity, easy implementation and avoidable local optimization. However, different algorithms have different performances for different medical disease images. For example, the Whale Optimization Algorithm (WOA) does not give a satisfactory performance for thresholding skin cancer images. We propose an improved WOA (LCWOA) in which the Levy operator and chaotic random mutation strategy are introduced to enhance the ability of the algorithm to jump out of the local optimum and to explore the search space. Comparing with different existing WOA variants on the CEC2014 function set, our proposed and improved algorithm improves the efficiency of the search. Experimental results show that our method outperforms the extant WOA variants in terms of optimization performances, improving the convergence accuracy and velocity. The method is also applied to solve the threshold selection in the skin cancer image segmentation problem, and LCWOA also gives excellent performance in obtaining optimal segmentation results.

An improved transformer network for skin cancer classification.

BACKGROUND: Use of artificial intelligence to identify dermoscopic images has brought major breakthroughs in recent years to the early diagnosis and early treatment of skin cancer, the incidence of which is increasing year by year worldwide and poses a great threat to human health. Achievements have been made in the research of skin cancer image classification by using the deep backbone of the convolutional neural network (CNN). This approach, however, only extracts the features of small objects in the image, and cannot locate the important parts. OBJECTIVES: As a result, researchers of the paper turn to vision transformers (VIT) which has demonstrated powerful performance in traditional classification tasks. The self-attention is to improve the value of important features and suppress the features that cause noise. Specifically, an improved transformer network named SkinTrans is proposed. INNOVATIONS: To verify its efficiency, a three step procedure is followed. Firstly, a VIT network is established to verify the effectiveness of SkinTrans in skin cancer classification. Then multi-scale and overlapping sliding windows are used to serialize the image and multi-scale patch embedding is carried out which pay more attention to multi-scale features. Finally, contrastive learning is used which makes the similar data of skin cancer encode similarly so that the encoding results of different data are as different as possible. MAIN RESULTS: The experiment is carried out based on two datasets, namely (1) HAM10000: a large dataset of multi-source dermatoscopic images of common skin cancers; (2)A clinical dataset of skin cancer collected by dermoscopy. The model proposed has achieved 94.3% accuracy on HAM10000 and 94.1% accuracy on our datasets, which verifies the efficiency of SkinTrans. CONCLUSIONS: The transformer network has not only achieved good results in natural language but also achieved ideal results in the field of vision, which also lays a good foundation for skin cancer classification based on multimodal data. This paper is convinced that it will be of interest to dermatologists, clinical researchers, computer scientists and researchers in other related fields, and provide greater convenience for patients.

Multi-level thresholding segmentation for pathological images: Optimal performance design of a new modified differential evolution.

The effective analytical processing of pathological images is crucial in promoting the development of medical diagnostics. Based on this matter, in this research, a multi-level thresholding segmentation (MLTS) method based on modified different evolution (MDE) is proposed. The MDE is the primary benefit offered by the suggested MLTS technique, which is a novel proposed evolutionary algorithm in this article with significant convergence accuracy and the capability to leap out of the local optimum (LO). This optimizer came into being mostly as a result of the incorporation of the movement mechanisms of white holes, black holes, and wormholes into various evolutions. Thus, the developed MLTS approach may provide high-quality segmentation results and is less susceptible to segmentation process stagnation. To validate the efficacy of the presented approaches, first, the performance of MDE is validated using 30 benchmark functions, and then the proposed segmentation method is empirically compared with other comparable methods using standard pictures. On the basis of breast cancer and skin cancer pathology images, the developed segmentation method is compared to other competing methods and experimentally validated in further detail. By analyzing experimental data, the key compensations of MDE are proven, and it is experimentally shown that the unique MDE-based MLTS approach can achieve good performance in terms of many performance assessment indices. Consequently, the proposed method may offer an efficient segmentation procedure for pathological medical images.

Value of a Signature of Immune-Related Genes in Predicting the Prognosis of Melanoma and Its Responses to Immune Checkpoint Blocker Therapies.

Melanoma is becoming increasingly common worldwide, with high rates of transformation into malignancy compared to other skin lesions. The prognosis of patients with melanoma at an advanced stage is highly unsatisfying despite the development of immunotherapy, target therapy, or combinative therapy. The major barrier to exploiting immune checkpoint therapies and achieving the best benefits clinically is resistance that can easily develop if regimens are not selected appropriately. In this study, we investigated the possibility of using immune-related genes to predict patient survival and their responses to immune checkpoint blocker therapies with the expression profiles available at The Cancer Genome Atlas (TCGA) Program plus expression data from the Gene Expression Omnibus (GEO) for validation. A five gene signature that is highly correlated with the local infiltration of cytotoxic lymphocytes in the tumor microenvironment was identified, and a scoring model was developed with stepwise regression after multivariate Cox analyses. The score calculated strongly correlates with Breslow depth, and this model effectively predicts the prognosis of patients with melanoma, whether primary or metastasized. It also depicts the heterogenous immune-related nature of melanoma by revealing different predicted responses to immune checkpoint blocker therapies through its correlation to tumor immune dysfunction and exclusion (TIDE) score.

Adverse and unconventional reactions related to immune checkpoint inhibitor therapy for cancer.

Immunotherapy is an emerging method for the treatment of cancer. Immune checkpoint inhibitors (ICIs) are monoclonal antibodies that block immune checkpoint pathways and release the body's anti-tumor immunity. They consist mainly of antibodies against cytotoxic T lymphocyte associated antigen-4 (CTLA-4), programmed death receptor 1 (PD-1), and programmed death ligand 1 (PD-L1). Although ICI therapy has been shown to be effective at treating cancer, it can also destroy immune tolerance and lead to organ toxicity. These unwanted side effects are known as immune related adverse events (irAEs). ICI treatment can also cause unconventional reactions such as pseudoprogression and hyperprogression. Pseudoprogression looks like an increase in the tumor parenchyma but is actually a temporary inflammation in the tumor; hyperprogression refers to the acceleration of tumor growth after the start of immunotherapy. Understanding the mechanisms of these two phenomena and distinguishing their differences are necessary for the effective prevention and treatment of unconventional reactions.

Performance optimization of salp swarm algorithm for multi-threshold image segmentation: Comprehensive study of breast cancer microscopy.

Multi-threshold image segmentation (MIS) is now a well known image segmentation technique, and many researchers have applied intelligent algorithms to it, but these methods suffer from local optimal drawbacks. This paper presented a novel approach to improve the Salp Swarm Algorithm (SSA), namely EHSSA, and applied it to MIS. Knowing the inaccuracies and discussions on implementation of this method, a new efficient mechanism is proposed to improve global search capability of the algorithm and avoid falling into a local optimum. Moreover, the excellence of the proposed algorithm was proved by comparative experiments at IEEE CEC2014. Afterward, the performance of EHSSA was demonstrated by testing a set of images selected from the Berkeley segmentation data set 500 (BSDS500), and the experimental results were analyzed by evaluating the parameters, which proved the efficiency of the proposed algorithm in MIS. Furthermore, EHSSA was applied to the microscopic image segmentation of breast cancer. Medical image segmentation is the study of how to quickly extract objects of interest (human organs) from various images to perform qualitative and quantitative analysis of diseased tissues and improve the accuracy of their diagnosis, which assists the physician in making more informed decisions and patient rehabilitation. The results of this set of experiments also proved its superior performance. For any info about this paper, readers can refer to https://aliasgharheidari.com.

Serum IL-8 and VEGFA are Two Promising Diagnostic Biomarkers of Asthma-COPD Overlap Syndrome.

Background: Asthma-COPD overlap (ACO; previously referred to as asthma-COPD overlap syndrome) is characterized by persistent airflow limitation consistent with COPD, together with several distinguishing features of asthma. Asthma-COPD overlap syndrome is a condition of mixing symptoms of asthma and COPD, because of its complexity, it is difficult to find effective diagnostic markers in clinic. Purpose: Our aims were to detect the expression of serum cytokines in patients with asthma, explore the diagnostic potential of differential serum cytokines in ACOS. Patients and Methods: Ninety asthmatic patients were divided into ACOS group and non-ACOS group according to the major and minor criteria of ACOS, 15 kinds of cytokines including IL-3, IL-4, IL-8, IL-9, IL-13, IL-17A, VEGFA, VEGFC, VEGFD, bFGF, Fit-1 PIGF, Tie-2 were detected by MSD, and IL-27 and TGF-beta were determined by ELISA assay. Results: The serum levels of IL-9, VEGFA and PIGF in patients with ACOS were significantly higher than those in non-ACOS group (P<0.05, respectively), while the level of IL-8 and IL-17A in subjects with ACOS was lower than that in the non-ACOS group (P<0.05, respectively). We analyzed the correlation between several difference factors and FEV1/FVC% in the ACOS group, found VEGFA was negatively correlated with FEV1/FVC%, while IL-8 and IL-17A were positively correlated with FEV1/FVC%. Finally, three correlation factors were analyzed by ROC curve for the occurrence of ACOS. Conclusion: The results suggested that IL-8 was highly sensitive and VEGFA was highly specificity, both of which could be used as biomarkers for the diagnosis of ACOS.

Evidence from a large-scale meta-analysis indicates eczema reduces the incidence of glioma.

We investigated the relationship between eczema and the risk of primary glioma. Relevant studies were selected through electronic searches of PubMed and EMBASE. A meta-analysis of 12 case-control studies and one cohort study was performed. A fixed effect model was applied to analyze 13 studies consisting of 10,897 glioma cases and 56,081 controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the strength of the associations. The data demonstrate that eczema significantly reduces the risk of glioma (OR = 0.69, 95% CI = 0.61-0.78, P < 0.001). Additional studies with larger patient cohorts are required to validate our findings.

TRAF4 enhances oral squamous cell carcinoma cell growth, invasion and migration by Wnt-ß-catenin signaling pathway.

Oral squamous cell carcinoma (OSCC) ranks as the fifth most common cancer worldwide with poor prognosis. Recently, tumor necrosis factor receptor-associated factor 4 (TRAF4) has attracted increasing attenuation due to its overexpression in certain cancers. However, its function and underlying mechanism in OSCC remains elusive. In this study, the high expression of TRAF4 mRNA and protein levels was noted in OSCC cell lines. Its overexpression with pcDNA3.1-TRAF4 vector transfection dramatically promoted cell proliferation and inhibited cell apoptosis, indicating a pivotal role of TRAF4 in OSCC cell growth. Simultaneously, TRAF4 elevation also increased cell invasion and migration. Mechanism analysis confirmed that TRAF4 up-regulation induced the expression of ß-catenin and the downstream target molecules of cyclinD1, c-myc, Bcl-2, MMP-9 and MMP-2, indicating that TRAF4 could induce the activation of Wnt/ß-catenin pathway. After pretreatment with ß-catenin siRNA, the pathway was remarkably silenced. Simultaneously, cell growth, invasion and migration induced by TRAF4 were strikingly abrogated, suggesting that TRAF4 may promote OSCC cell growth, invasion and migration by Wnt/ß-catenin pathway. Together, this study confirmed that TRAF4 acts as an oncogene for the development and progression of OSCC. Therefore, our study may support a promising therapeutic target for the treatment of OSCC.

Preparation of novel (-)-gossypol nanoparticles and the effect on growth inhibition in human prostate cancer PC-3 cells in vitro.

The aim of the present study was to investigate the antitumor effects and possible mechanism of (-)-gossypol nanoparticles, loaded with vv polyethylene glycol-maleimide (mPEG-Mal), in vitro. Emulsification-volatilization was used to prepare the loaded (-)-gossypol nanoparticles. The toxicity of blank nanoparticles on human prostate cancer PC-3 cells and human prostate RWPE-1 cells was measured. The antitumor effects of the nanoparticles on PC-3 cells were evaluated by an MTT assay, acridine orange staining and transmission electron microscopy in vitro, and the results were compared with those of free (-)-gossypol. In addition, the mRNA expression levels of Bcl-2 and Bak were measured using semi-quantitative reverse transcription polymerase chain reaction. The growth inhibition activity of the loaded (-)-gossypol nanoparticles was found to be dose- and time-dependent, and similar to the activity of free (-)-gossypol. The nanoparticles induced apoptotic morphological changes on the PC-3 cells, downregulating the mRNA expression level of Bcl-2 and upregulating the mRNA expression level of Bak. Blank nanoparticles exhibited no evident toxicity on PC-3 and RWPE-1 cells at a high dose. Therefore, the mPEG-Mal loaded (-)-gossypol nanoparticles demonstrated a favorable antitumor activity and no toxicity. The nanoparticles were able to induce the apoptosis of prostate cancer cells; thus, may be a potential antitumor nanodrug.

Expression of Kin17 promotes the proliferation of hepatocellular carcinoma cells in vitro and in vivo.

Kin17 protein is ubiquitously expressed in mammals and is correlated with vital biological functions. However, little is known about the role of Kin17 in the proliferation of hepatocellular carcinoma cells. The aim of the present study was to investigate whether the upregulation of Kin17 can promote the growth of hepatocellular carcinoma cells. A series of assays was performed to study the effect of Kin17 in the proliferation of hepatocellular carcinoma cells in vitro and in vivo. The western blotting results revealed that Kin17 expression was increased in hepatocellular carcinoma tissues compared with that of the corresponding normal tissues. Moreover, ectopic upregulation of Kin17 expression promoted the growth of hepatocellular carcinoma cells in vitro and in vivo. These results indicated that Kin17 is involved in the tumorigenesis of hepatocellular carcinoma, and that Kin17 has the potential to serve as a therapeutic target for hepatocellular carcinoma.

Study on in-vivo anti-tumor activity of Verbena officinalis extract.

We investigated the anti-tumor effects of Verbena officinalis extract on H22 tumor-bearing mice and its effect on immune function. Mice model of H22 solid tumor was established, the mice were divided into five groups and administered the extract, later, tumors were removed and inhibition rates were calculated; spleens were removed and spleen indices were calculated, and the sheep red blood cell-delayed-type hypersensitivity (SRBC-DTH) and the serum hemolysin level were determined. The Verbena officinalis extract had anti-tumor effect, with the inhibition rate reaching 38.78%, it also increased the spleen index to a certain extent, in addition, the changes in DTA and HA were not obvious compared with the model group. The Verbena officinalis extract had in vivo anti-tumor effect, while causing no damage on the immune function.

Effects of PTTG down-regulation on proliferation and metastasis of the SCL-1 cutaneous squamous cell carcinoma cell line.

AIMS: To study effects of down-regulation of pituitary tumor-transforming gene (PTTG) on proliferation and metastasis ability of the SCL-1 cutaneous squamous cell carcinoma (CSCC) cell line and explore related mechanisms. METHODS: SCL-1 cells were divided into 3 groups (untreated, siRNA control and PTTG siRNA). Cell proliferation assays were performed using a CCK-8 kit and proliferation and metastasis ability were analyzed using Boyden chambers. In addition, expression of MMP-2 and MMP-9 was detected by r-time qPCR and Western blotting. RESULTS: Down-regulation of PTTG could markedly inhibit cell proliferation in SCL-1 cells, compared to untreated and control siRNA groups (P < 0.05). Real-time qPCR demonstrated that expression levels of PTTG, MMP-2 and MMP-9 in the PTTG siRNA group were 0.8%, 23.2% and 21.3% of untreated levels. Western blotting revealed that expression of PTTG, MMP-2 and MMP-9 proteins in the PTTG siRNA group was obviously down-regulated. The numbers of migrating cells (51.38 ± 4.71) in the PTTG siRNA group was obviously lower than that in untreated group (131.33 ± 6.12) and the control siRNA group (127.72 ± 5.20) (P < 0.05), suggesting that decrease of proliferation and metastasis ability mediated by PTTG knock-down may be closely correlated with down-regulation of MMP-2 and MMP-9 expression. CONCLUSION: Inhibition of PTTG expression may be a new target for therapy of CSCC.