Cancer Prognostic Biomarkers Research Articles

GDF10 and IDO1 as a thyroid cancer prognostic biomarker associated with immune infiltration

ObjectionThe aim of this work is to screen the immune-related genes to predict the prognosis and provide a new direction of treatment for patients with thyroid cancer (THCA). MethodsThe mRNA and clinical features of THCA patients were collected from the Cancer Genome Atlas (TCGA) databases. The immune-related genes were obtained from the ImmPort databases. The bio-information methods were performed to screen the differential expression genes (DEGs) and genes related to immunity between the THCA patients and normal individuals. On this basis, the hub prognosis immunity genes were screened by Veen. The related genes were obtained by constructing the protein-protein interaction network. The enrichment analyses were performed based on the protein and protein interaction (PPI) related genes. The hub immune checkpoint was screened by correlation analysis. Finally, the hub gene and the immunity checkpoint-miRNA (or transcription factor, drug) interaction network were constructed. A drug-sensitive analysis also was performed. ResultsThe GDF10 was screened. The PPI genes were enriched in the TGF-beta signaling pathway, signaling pathways regulating, the pluripotency of stem cells, Cytokine-cytokine receptor interaction, and so on. The hub immunity checkpoint IDO1 was obtained. The joint indicator of two hub genes was positively related to the thyroid differentiation score. Three interaction factors were found to be related to the two hub genes, and 7 kinds of drugs screened act on the two hub genes at the same time. ConclusionThis work indicated that immune-related gene GDF10 and immune checkpoint IDO1 are important for the prognosis prediction of THCA patients, and immunity is involved in the proliferation, and differentiation of tumor cells.

Identification of a Group of Therapeutic Targets and Prognostic Biomarker for Triple Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is a highly heterogeneous disease. Mining differentially expressed genes of TNBC is helpful to explore new therapeutic targets. This study aimed to investigate diagnostic biomarker genes in TNBC compared to normal tissue. Additionally, we explored the functions and prognostic value of these key genes as well as potential targeted drugs that could affect these genes. Differential gene expression analysis was conducted using the R software with data from the Gene Expression Omnibus (GEO) database. Then, the identified differentially expressed genes (DEGs) were used to construct a protein-protein interaction (PPI) network using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. The mRNA expression levels of key genes were analyzed using the UALCAN database with data from The Cancer Genome Atlas (TCGA). Enrichment and survival analyses were performed using R software. In addition, potential compounds showing sensitivity to key genes were identified by gene set cancer analysis (GSCA). Compared with normal tissues, a total of 203 DEGs were upregulated in TNBC. These DEGs participated in various biological processes including nuclear division, microtubule binding, cell cycle, and the p53 signaling pathway. Through the PPI network analysis, ten key genes were identified, among which four genes showed significant correlation with poor progression-free interval (PFI) in patients with TNBC. Moreover, the four survival-related genes were found to act as sensitive therapeutic targets. The identified four key genes were considered new biomarkers for diagnosis and prognosis and also potential therapeutic targets for TNBC.

Characterization of KIF20B as a novel prognostic biomarker and therapeutic target for breast cancer.

Despite advances in treatment and early detection, breast cancer remains one of the most common types of cancer and is the second leading cause of cancer death after lung cancer in women. Therefore, there is an urgent need to develop new biomarkers and therapeutic targets for the treatment of breast cancer. Based on gene expression profiles and subsequent screening performed in a preliminary study, kinesin family member 20B (KIF20B) was selected as a candidate target molecule, because it was highly and frequently expressed in all subtypes of breast cancer and barely detected in normal tissues. Reverse transcription‑quantitative PCR and western blotting revealed that KIF20B mRNA and protein expression levels were upregulated in most breast cancer cell lines but were scarcely expressed in normal mammary epithelial cells. Immunohistochemical staining of a tissue microarray showed that KIF20B was detected in 145 out of 251 (57.8%) breast cancer tissues. Strong KIF20B expression was significantly related to advanced pathological N stage. Moreover, patients with breast cancer and strong KIF20B expression exhibited a significantly worse prognosis than those with weak or negative KIF20B expression (P<0.0001, log‑rank test). In multivariate analysis, strong expression was an independent prognostic factor for patients with breast cancer. Furthermore, knockdown of KIF20B expression by small interfering RNA inhibited breast cancer cell proliferation and induced apoptosis. In addition, Matrigel cell invasion assays revealed that the invasiveness of breast cancer cells was significantly decreased by KIF20B silencing. Since KIF20B is an oncoprotein that is strongly expressed in highly malignant clinical breast cancer and serves a pivotal role in breast cancer cell proliferation, survival and invasion, KIF20B could be considered a candidate biomarker for prognostic prediction and a potential molecular target for developing new therapeutics, such as small molecule inhibitors, for a wide variety of breast cancers.

The presence of autoantibodies as a potential prognostic biomarker for breast cancer.

The presence of autoantibodies is closely associated with the occurrence and development of cancer. Autoantibodies can be used as biomarkers for early breast cancer diagnosis. However, the relationship between autoantibodies and the prognosis of breast cancer patients remains elusive. This retrospective study aimed to investigate the correlation between the presence of autoantibodies and outcomes in breast cancer patients. This study included a total of 155 patients from People's Hospital of Henan University (Zhengzhou, China) who were diagnosed with breast cancer from January 2017 to December 2021. The enrolled patients' clinicopathological features were collected, and 88 patients were ultimately involved in the analysis. Univariate and multivariate Cox regression analyses were performed to search for the risk factors related to the poor prognosis of breast cancer patients. The association between the presence of autoantibodies and patients' survival was analysed using Kaplan-Meier curves. After screening, there were 38 autoantibody-positive cases and 50 autoantibody-negative cases. Breast cancer patients with autoantibody-positive had a 57% lower risk of death compared with autoantibody-negative patients. Multivariate Cox regression analysis indicated that the presence of autoantibody could be a potential prognostic predictor for breast cancer, independent of age, histological grade, pathological classification, clinical stage, and the expression levels of hormonal receptors. In addition, autoantibody-positive breast cancer patients had longer progression-free survival and overall survival compared with autoantibody-negative cases. Positive autoantibody was found as an independent biomarker of better prognosis in breast cancer patients, providing a new strategy for the prognostic assessment of breast cancer patients.

Nomogram model including LATS2 expression was constructed to predict the prognosis of advanced gastric cancer after surgery.

Gastric cancer is a leading cause of cancer-related deaths worldwide. Prognostic assessments are typically based on the tumor-node-metastasis (TNM) staging system, which does not account for the molecular heterogeneity of this disease. LATS2, a tumor suppressor gene involved in the Hippo signaling pathway, has been identified as a potential prognostic biomarker in gastric cancer. To construct and validate a nomogram model that includes LATS2 expression to predict the survival prognosis of advanced gastric cancer patients following radical surgery, and compare its predictive performance with traditional TNM staging. A retrospective analysis of 245 advanced gastric cancer patients from the Fourth Hospital of Hebei Medical University was conducted. The patients were divided into a training group (171 patients) and a validation group (74 patients) to develop and test our prognostic model. The performance of the model was determined using C-indices, receiver operating characteristic curves, calibration plots, and decision curves. The model demonstrated a high predictive accuracy with C-indices of 0.829 in the training set and 0.862 in the validation set. Area under the curve values for three-year and five-year survival prediction were significantly robust, suggesting an excellent discrimination ability. Calibration plots confirmed the high concordance between the predictions and actual survival outcomes. We developed a nomogram model incorporating LATS2 expression, which significantly outperformed conventional TNM staging in predicting the prognosis of advanced gastric cancer patients postsurgery. This model may serve as a valuable tool for individualized patient management, allowing for more accurate stratification and improved clinical outcomes. Further validation in larger patient cohorts will be necessary to establish its generalizability and clinical utility.

Prognostic significance of LINC01132 in lung cancer and its regulatory role in tumor progression

BackgroundThe application of long non-coding RNAs (lncRNAs) in cancer has been the focus of research in recent years. This study aimed to discuss the expression and functional mechanism of lncRNA LINC01132 (LINC01132) in lung cancer and explore its prognostic significance in tumors.MethodsThe expression of LINC01132 in lung cancer patients was verified using GSE98929 screening and real-time quantitative polymerase chain reaction (RT-qPCR) detection. The prognostic potential of LINC01132 was evaluated by performing the chi-square analysis of clinical indicators, Kaplan–Meier analysis, and Cox proportional hazard model. Cell Counting Kit-8 (CCK-8), flow cytometry, and Transwell assay were used to characterize the biological functions of the lung cancer cells. The targeting relationship between LINC01132 and microRNA-125a-3p (miR-125a-3p), miR-125a-3p and SMAD2 was predicted by bioinformatics and verified by luciferase activity assay.ResultsLINC01132 was upregulated in lung cancer tissues and cells, which was an independent risk factor for survival and prognostic outcomes of lung cancer patients. Silencing LINC01132 suppressed the proliferation and migration of lung cancer cells and accelerated cell death. The target of LINC01132 was miR-125a-3p, and miR-125a-3p inhibitor could eliminate the inhibitory effect of LINC01132 knockdown on the cells. Additionally, SMAD2 is a downstream target of miR-125a-3p, and knockdown of SMAD2 reversed the effects of miR-125a-3p inhibitor on cell migration and invasion.ConclusionLINC01132 may regulate the progression of lung cancer by targeting the miR-125a-3p /SMAD2 axis and serve as a prognostic biomarker for lung cancer.

JAM3: A prognostic biomarker for bladder cancer via epithelial-mesenchymal transition regulation.

Understanding the intricate relationship between prognosis, immune function, and molecular markers in bladder cancer (BC) demands sophisticated analytical methods. To identify novel biomarkers for predicting prognosis and immune function in BC patients, we combined weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) regression analysis. This was conducted using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Ultimately, we screened the junctional adhesion molecule 3 (JAM3) as an independent risk factor in BC. High levels of JAM3 were linked to adverse clinical parameters, such as higher T and N stages. Additionally, a JAM3-based nomogram model accurately predicted 1-, 3- and 5-year survival rates of BC patients, indicating potential clinical utility. Functional enrichment analysis revealed that high JAM3 expression activated the calcium signaling pathway, the extracellular matrix (ECM)-receptor interaction, and the PI3K-Akt signaling pathway, and was positively correlated with genes associated with epithelial-mesenchymal transition (EMT). Subsequently, we found that overexpression of JAM3 promoted the migration and invasion abilities in BC cells, regulating the expression levels of N-cadherin, matrix metallopeptidase 2 (MMP2), and Claudin-1 thereby promoting EMT levels. Additionally, we showed that JAM3 was negatively correlated with anti-tumor immune cells such as CD8+ T cells, while positively correlated with pro-tumor immune cells such as M2 macrophages, suggesting its involvement in immune cell infiltration. The immune checkpoint CD200 also showed a positive correlation with JAM3. Our findings revealed that elevated JAM3 levels are predictive of poor prognosis and immune cell infiltration in BC patients by regulating the EMT process.

Immune-related signature identifies IL1R2 as an immunological and prognostic biomarker in pancreatic cancer.

Pancreatic cancer is one of the most aggressive malignancies, a robust prognostic signature and novel biomarkers are urgently needed for accurate stratification of the patients and optimization of clinical decision-making. A list of bioinformatic analysis were applied in public dataset to construct an immune-related signature. Furthermore, the most pivotal gene in the signature was identified. The potential mechanism of the core gene function was revealed through GSEA, CIBERSORT, ESTIMATE, immunophenoscore (IPS) algorithm, single-cell analysis, and functional experiment. An immune-related prognostic signature and associated nomogram were constructed and validated. Among the genes constituting the signature, interleukin 1 receptor type II (IL1R2) was identified as the gene occupying the most paramount position in the risk signature. Meanwhile, knockdown of IL1R2 significantly inhibited the proliferation, invasion, and migration ability of pancreatic cancer cells. Additionally, high IL1R2 expression was associated with reduced CD8+ T cell infiltration in pancreatic cancer microenvironment, which may be due to high programmed cell death-ligand-1 (PD-L1) expression in cancer cells. Finally, the IPS algorithm proved that patients with high IL1R2 expression possessed a higher tumor mutation burden and a higher probability of benefiting from immunotherapy. In conclusion, our study constructed an efficient immune-related prognostic signature and identified the key role of IL1R2 in the development of pancreatic cancer, as well as its potential to serve as a biomarker for immunotherapy efficacy prediction for pancreatic cancer.

Anoikis-related genes as potential prognostic biomarkers in gastric cancer: A multilevel integrative analysis and predictive therapeutic value.

Gastric cancer (GC) is a frequent malignancy of the gastrointestinal tract. Exploring the potential anoikis mechanisms and pathways might facilitate GC research. The authors aim to determine the significance of anoikis-related genes (ARGs) in GC prognosis and explore the regulatory mechanisms in epigenetics. After describing the genetic and transcriptional alterations of ARGs, we searched differentially expressed genes (DEGs) from the cancer genome atlasand gene expression omnibusdatabases to identify major cancer marker pathways. The non-negative matrix factorisation algorithm, Lasso, and Cox regression analysis were used to construct a risk model, and we validated and assessed the nomogram. Based on multiple levels and online platforms, this research evaluated the regulatory relationship of ARGs with GC. Overexpression of ARGs is associated with poor prognosis, which modulates immune signalling and promotes anti-anoikis. The consistency of the DEGs clustering with weighted gene co-expression network analysisresults and the nomogram containing 10 variable genes improved the clinical applicability of ARGs. In anti-anoikis mode, cytology, histology, and epigenetics could facilitate the analysis of immunophenotypes, tumour immune microenvironment (TIME), and treatment prognosis. A novel anoikis-related prognostic model for GC is constructed, and the significance of anoikis-related prognostic genes in the TIME and the metabolic pathways of tumours is initially explored.

PCDH8 is a novel prognostic biomarker in thyroid cancer and promotes cell proliferation and viability

Protocadherin 8 (PCDH8), a calcium-dependent transmembrane protein in the protocadherin family, regulates cell adhesion and signal transduction. While some studies have provided indirect evidence that PCDH8 has cancer-promoting properties, this association is controversial. In particular, its involvement in thyroid cancer (THCA) remains unclear. We aimed to elucidate the role of PCDH8 in THCA using bioinformatic analysis. Subsequently, the results were experimentally validated. The analysis conducted using the R programming language and online web tools explored PCDH8 expression levels, prognostic, and clinical implications, and its relationship with the tumor immune microenvironment in THCA. Furthermore, we examined the association between PCDH8 and co-expressed genes, highlighting their involvement in several biological processes relevant to THCA. The potential of PCDH8 as a therapeutic target for this pathology was also explored. Immunohistochemical (IHC) staining was performed on samples from 98 patients with THCA, and experimental validation was carried out. PCDH8 was significantly elevated in cancer tissues and associated with poor prognosis, several clinical factors, and immune cell and checkpoint abundance. Cox regression and survival analyses, together with Receiver Operating Curves (ROC) indicated that PCDH8 was an independent prognostic factor for THCA. Furthermore, PCDH8 impacts cell viability and proliferation, promoting tumorigenesis. Also, it influences tumor cell sensitivity to various drugs. Thus, PCDH8 might be a potential therapeutic target for THCA. IHC, cell culture, MTT, and colony formation experiments further confirmed our findings. This analysis provided insights into the potential carcinogenic role of PCDH8 in THCA, as it impacts cell viability and proliferation. Thus, PCDH8 might play an important role in its prognosis, immune infiltration, and diagnosis.

Searching for the "Holy Grail" of breast cancer recurrence risk: a narrative review of the hunt for a better biomarker and the promise of circulating tumor DNA (ctDNA).

This paper is a narrative review of a major clinical challenge at the heart of breast cancer care: determining which patients are at risk of recurrence, which require systemic therapy, and which remain at risk in the survivorship phase of care despite initial therapy. We review the literature on prognostic and predictive biomarkers in breast cancer with a focus on detection of minimal residual disease. While we have many tools to estimate and refine risk that are used to individualize local and systemic therapy, we know that we continue to over treat many patients and undertreat others. Many patients also experience what is, at least in hindsight, needless fear of recurrence. In this review, we frame this dilemma for the practicing breast oncologist and discuss the search for what we term the "holy grail" of breast cancer evaluation: the ideal biomarker of residual distant disease. We review the history of attempts to address this problem and the up-to-date science on biomarkers, circulating tumor cells and circulating tumor DNA (ctDNA). This review suggests that the emerging promise of ctDNA may help resolve a crticical dilemma at the heart of breast cancer care, and improve prognostication, treatment selection, and outcomes for patients with breast cancer.

The Detection and Negative Reversion of Circulating Tumor Cells as Prognostic Biomarkers for Metastatic Castration-Resistant Prostate Cancer with Bone Metastases Treated by Enzalutamide.

Enzalutamide is a second-generation androgen receptor inhibitor that increases overall survival (OS) rates in patients with metastatic castration-resistant prostate cancer (mCRPC). This study evaluates the efficacy of circulating tumor cell (CTC) status as a prognostic biomarker following enzalutamide administration. A retrospective subgroup analysis and prognostic survey were conducted on 43 patients with mCRPC and bone metastases treated in Juntendo University-affiliated hospitals from 2015 to 2022. Patients were treated with 160 mg enzalutamide daily. CTC analyses on blood samples were performed regularly before and every three months after treatment. The relationship between the patients' clinical factors and the OS rate was analyzed using the log-rank test; the median OS was 37 months. Patients with no detected CTCs at baseline showed significantly longer OS than those with detectable CTCs at baseline. Furthermore, patients demonstrating negative reversion of CTCs during enzalutamide treatment had significantly longer OS than patients with CTC-positivity. Two biomarkers-higher hemoglobin at baseline and achieving negative reversion of CTCs-were significantly associated with prolonged OS. This study suggests that patients achieving CTC-negative reversion during treatment for mCRPC with bone metastases exhibit improved long-term OS. Chronological measurement of CTC status might be clinically useful in the treatment of mCRPC.

Targeting GRP75 with a Chlorpromazine Derivative Inhibits Endometrial Cancer Progression Through GRP75-IP3R-Ca2+-AMPK Axis.

Tumors often overexpress glucose-regulated proteins, and agents that interfere with the production or activity of these proteins may represent novel cancer treatments. The chlorpromazine derivative JX57 exhibits promising effects against endometrial cancer with minimal extrapyramidal side effects; however, its mechanisms of action are currently unknown. Here, glucose-regulated protein 75kD (GRP75) is identified as a direct target of JX57 using activity-based protein profiling and loss-of-function experiments. The findings show that GRP75 is necessary for the biological activity of JX57, as JX57 exhibits moderate anticancer properties in GRP75-deficient cancer cells, both in vitro and in vivo. High GRP75 expression is correlated with poor differentiation and poor survival in patients with endometrial cancer, whereas the knockdown of GRP75 can significantly suppress tumor growth. Mechanistically, the direct binding of JX57 to GRP75 impairs the structure of the mitochondria-associated endoplasmic reticulum membrane and disrupts the endoplasmic reticulum-mitochondrial calcium homeostasis, resulting in a mitochondrial energy crisis and AMP-activated protein kinase activation. Taken together, these findings highlight GRP75 as a potential prognostic biomarker and direct therapeutic target in endometrial cancer and suggest that the chlorpromazine derivative JX57 can potentially be a new therapeutic option for endometrial cancer.

Current and Emerging Diagnostic, Prognostic, and Predictive Biomarkers in Head and Neck Cancer.

Head and neck cancers (HNC) are a biologically diverse set of cancers that are responsible for over 660,000 new diagnoses each year. Current therapies for HNC require a comprehensive, multimodal approach encompassing resection, radiation therapy, and systemic therapy. With an increased understanding of the mechanisms behind HNC, there has been growing interest in more accurate prognostic indicators of disease, effective post-treatment surveillance, and individualized treatments. This chapter will highlight the commonly used and studied biomarkers in head and neck squamous cell carcinoma.

Multi-cohort validation of Ascore: an anoikis-based prognostic signature for predicting disease progression and immunotherapy response in bladder cancer

Bladder cancer ranks as the 10th most common cancer worldwide, with deteriorating prognosis as the disease advances. While immune checkpoint inhibitors (ICIs) have shown promise in clinical therapy in both operable and advanced bladder cancer, identifying patients who will respond is challenging. Anoikis, a specialized form of cell death that occurs when cells detach from the extracellular matrix, is closely linked to tumor progression. Here, we aimed to explore the anoikis-based biomarkers for bladder cancer prognosis and immunotherapeutic decisions. Through consensus clustering, we categorized patients from the TCGA-BLCA cohort into two clusters based on anoikis-related genes (ARGs). Significant differences in survival outcome, clinical features, tumor immune environment (TIME), and potential ICIs response were observed between clusters. We then formulated a four-gene signature, termed "Ascore", to encapsulate this gene expression pattern. The Ascore was found to be closely associated with survival outcome and served as an independent prognosticator in both the TCGA-BLCA cohort and the IMvigor210 cohort. It also demonstrated superior predictive capacity (AUC = 0.717) for bladder cancer immunotherapy response compared to biomarkers like TMB and PD-L1. Finally, we evaluated Ascore’s independent prognostic performance as a non-invasive biomarker in our clinical cohort (Gulou-Cohort1) using circulating tumor cells detection, achieving an AUC of 0.803. Another clinical cohort (Gulou-Cohort2) consisted of 40 patients undergoing neoadjuvant anti-PD-1 treatment was also examined. Immunohistochemistry of Ascore in these patients revealed its correlation with the pathological response to bladder cancer immunotherapy (P = 0.004). Impressively, Ascore (AUC = 0.913) surpassed PD-L1 (AUC = 0.662) in forecasting immunotherapy response and indicated better net benefit. In conclusion, our study introduces Ascore as a novel, robust prognostic biomarker for bladder cancer, offering a new tool for enhancing immunotherapy decisions and contributing to the tailored treatment approaches in this field.

Transcriptomic Profiling for Prognostic Biomarkers in Early-Stage Squamous Cell Lung Cancer (SqCLC).

Squamous cell lung carcinoma (SqCLC) is associated with high mortality and limited treatment options. Identification of therapeutic targets and prognostic biomarkers is still lacking. This research aims to analyze the transcriptomic profile of SqCLC samples and identify the key genes associated with tumorigenesis, overall survival (OS), and a profile of the tumor-infiltrating immune cells. Differential gene expression analysis, pathway enrichment analysis, and Gene Ontology analysis on RNA-seq data obtained from FFPE tumor samples (N = 23) and healthy tissues (N = 3) were performed (experimental cohort). Validation of the results was conducted on publicly available gene expression data using TCGA LUSC (N = 225) and GTEx healthy donors' cohorts (N = 288). We identified 1133 upregulated and 644 downregulated genes, common for both cohorts. The most prominent upregulated genes were involved in cell cycle and proliferation regulation pathways (MAGEA9B, MAGED4, KRT, MMT11/13), while downregulated genes predominately belonged to immune-related pathways (DEFA1B, DEFA1, DEFA3). Results of the survival analysis, conducted on the validation cohort and commonly deregulated genes, indicated that overexpression of HOXC4 (p < 0.001), LLGL1 (p = 0.0015), and SLC4A3 (p = 0.0034) is associated with worse OS in early-stage SqCLC patients. In contrast, overexpression of GSTZ1 (p = 0.0029) and LILRA5 (p = 0.0086) was protective, i.e., associated with better OS. By applying a single-sample gene-set enrichment analysis (ssGSEA), we identified four distinct immune subtypes. Immune cell distribution suggests that the memory T cells (central and effector) and follicular helper T cells could serve as important stratification parameters.

MICAL2 implies immunosuppressive features and acts as an independent and adverse prognostic biomarker in pancreatic cancer

At present, clinical outcomes of pancreatic cancer patients are still poor. New therapeutic targets for pancreatic cancer are urgently needed. Previous studies have indicated that Microtubule Associated Monooxygenase, Calponin and LIM Domain Containing 2 (MICAL2) is highly expressed in many tumors and promotes tumor progression. However, the role played by MICAL2 in pancreatic cancer remains unclear. Based on gene expression and clinical information from multiple datasets, we used comprehensive bioinformatics analysis in combination with tissue microarray to explore the function and clinical value of MICAL2. The results showed that MICAL2 was highly expressed in pancreatic cancer tissue and exhibited potential diagnostic capability. High expression of MICAL2 was also associated with poor prognosis and acted as an independent prognostic factor. MICAL2, mainly expressed in fibroblasts of pancreatic cancer, was closely related to metastasis and immune-related features, such as epithelial-mesenchymal transformation, extracellular cell matrix degradation, and inflammatory response. Furthermore, higher MICAL2 expression in pancreatic cancer was also associated with an increase in cancer-associated fibroblasts as well as M2 macrophage infiltration, and a reduction in CD8 + T cell infiltration, thereby facilitating the formation of an immunosuppressive microenvironment. Our results helped elucidate the clinical value and function in metastasis and immunity of MICAL2 in pancreatic cancer. These findings provided potential clinical strategies for diagnosis, targeted therapy combination immunotherapy, and prognosis in patients with pancreatic cancer.

Increased PIEZO1 Expression Is Associated with Worse Clinical Outcomes in Hormone-Receptor-Negative Breast Cancer Patients.

PIEZO1 plays a crucial role in the human body as a mechanosensory ion channel. It has been demonstrated that PIEZO1 is important in tissue development and regulating many essential physiological processes. Studies have suggested that the PIEZO1 ion channel plays a role in invasion and progression in cancer; elevated levels of PIEZO1 have been correlated with increased migration in breast cancer cells, chemo-resistance and invasion in gastric cancer cells, and increased invasion of osteosarcoma cells. In addition, high PIEZO1 expression levels were correlated with a worse prognosis in glioma patients. On the other hand, studies in lung cancer have attributed high PIEZO1 levels to better patient outcomes. However, the clinical impact of PIEZO1 in breast cancer is not well characterized. Therefore, our goal was to determine the clinical relevance of PIEZO1 in breast cancer. An analysis of breast cancer data from The Cancer Genome Atlas (TCGA) was conducted to investigate PIEZO1 expression levels and correlation to survival, followed by validation in an independent dataset, GSE3494. We also performed gene set enrichment analysis (GSEA) and pathway enrichment analysis. We also analyzed the immune cell composition in breast tumors from TCGA through a CIBERSORT algorithm. Our results demonstrated that the PIEZO1 expression levels are higher in hormone-receptor (HR)-negative than in HR-positive cohorts. High PIEZO1 expression is correlated with a significant decrease in survival in HR-negative cohorts, especially in triple-negative breast cancer (TNBC), suggesting that PIEZO1 could be utilized as a prognostic biomarker in HR-negative breast cancer. GSEA showed that various signaling pathways associated with more invasive phenotypes and resistance to treatments, including epithelial-mesenchymal transition (EMT), hypoxia, and multiple signaling pathways, are enriched in high-PIEZO1 HR-negative tumors. Our results also demonstrated a decrease in CD8+ and CD4+ T cell infiltration in high-PIEZO1 HR-negative tumors. Further investigations are necessary to elucidate the mechanistic roles of PIEZO1 in HR-negative breast cancer.

Activity of Potassium Channels in CD8+ T Lymphocytes: Diagnostic and Prognostic Biomarker in Ovarian Cancer?

CD8+ T cells play a role in the suppression of tumor growth and immunotherapy. Ion channels control the Ca2+-dependent function of CD8+ lymphocytes such as cytokine/granzyme production and tumor killing. Kv1.3 and KCa3.1 K+ channels stabilize the negative membrane potential of T cells to maintain Ca2+ influx through CRAC channels. We assessed the expression of Kv1.3, KCa3.1 and CRAC in CD8+ cells from ovarian cancer (OC) patients (n = 7). We found that the expression level of Kv1.3 was higher in patients with malignant tumors than in control or benign tumor groups while the KCa3.1 activity was lower in the malignant tumor group as compared to the others. We demonstrated that the Ca2+ response in malignant tumor patients is higher compared to control groups. We propose that altered Kv1.3 and KCa3.1 expression in CD8+ cells in OC could be a reporter and may serve as a biomarker in diagnostics and that increased Ca2+ response through CRAC may contribute to the impaired CD8+ function.

Spindle apparatus coiled-coil protein 1 (SPDL1) serves as a novel prognostic biomarker in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) has a poor prognosis, an ineffective diagnosis, and a high degree of aggressiveness. Therefore, novel therapeutic targets for TNBC urgently need to be identified. Through a series of bioinformatics analyses, including analysis of differential gene expression, protein-protein interaction (PPI) network, univariate cox regression, immune infiltration, pathway enrichment, etc, as well as auxiliary immunohistochemistry (IHC) and protein quantitativae analysis, to explore prognostic marker for TNBC. In TNBC tissues, we found that SPDL1 (CCDC99) was considerably overexpressed at both the mRNA and protein levels compared to that in normal and non-TNBC tissues. Additionally, we found that SPDL1-high expression was strongly linked to poor prognosis in TNBC patients. Excessive SPDL1 expression was positively correlated with tumor growth and strongly linked to the cell cycle, DNA replication, and the p53 signaling pathway. In addition, CIBERSORT analysis revealed that SPDL1 can affect the tumor immune microenvironment (TME) in TNBC, encourage the development of TNBC and act as a potential prognostic biomarker for TNBC. Patients with SPDL1-high expression were more sensitive to AZD8055. Notably, we discovered that SPDL1 is highly expressed in the majority of malignancies and may have an impact on the pancancer prognosis. SPDL1 can serve as a novel prognostic marker for TNBC and pancancer patients.