Soluble Syndecan-1 Levels Are Associated with Survival in Platinum-Treated Bladder Cancer Patients

A novel immune cell signature for predicting glioblastoma after radiotherapy prognosis and guiding therapy

Background: Glioblastoma, a highly aggressive brain tumor, poses a significant clinical challenge, particularly in the context of radiotherapy. In this study, we aimed to explore infiltrating immune cells and identify immune-related genes associated with glioblastoma radiotherapy prognosis. Subsequently, we constructed a signature based on these genes to discern differences in molecular and tumor microenvironment immune characteristics, ultimately informing potential therapeutic strategies for patients with varying risk profiles. Methods: We leveraged UCSC Xena and CGGA gene expression profiles from post-radiotherapy glioblastoma as verification cohorts. Infiltration ratios were stratified into high and low groups based on the median value. Differential gene expression was determined through Limma differential analysis. A signature comprising four genes was constructed, guided by Gene Ontology (GO) functional enrichment results and Kaplan-Meier survival analysis. We evaluated differences in cell infiltration levels, Immune Score, Stromal Score, and ESTIMATE Score and their Pearson correlations with the signature. Spearman's correlation was computed between the signature and patient drug sensitivity (IC50), predicted using Genomics of Drug Sensitivity in Cancer (GDSC) and CCLE databases. Results: Notably, the infiltration of central memory CD8+T cells exhibited a significant correlation with glioblastoma radiotherapy prognosis. Samples were dichotomized into high- and low-risk groups based on the optimal signature threshold (2.466642). Kaplan-Meier (K-M) survival analysis revealed that the high-risk group experienced a significantly poorer prognosis (p = .0068), with AUC values exceeding 0.82 at 1, 3, and 5 years, underscoring the robust predictive potential of the signature scoring system. Independent validation sets substantiated the validity of the signature. Statistically significant differences in tumor microenvironments (p < .05) were observed between high- and low-risk groups, and these differences were significantly correlated with the signature (p < .05). Furthermore, there were significant correlations between high and low-risk groups regarding immune checkpoint expressions, Immune Prognostic Score (IPS), and Tumor Immune Dysfunction and Exclusion (TIDE) scores. Conclusion: The immune cell signature, comprising SDC-1, PLAUR, FN1, and CXCL13, holds promise as a predictive tool for assessing glioblastoma prognosis following radiotherapy. This signature also offers valuable guidance for tailoring treatment strategies, emphasizing its potential clinical relevance in improving patient outcomes.

Circulating syndecan-1 and glypican-4 predict 12-month survival in metastatic colorectal cancer patients

Cell surface syndecans and glypicans play important roles in the development and prognosis of colorectal cancer (CRC). Their soluble forms from proteoglycan shedding can be detected in blood and have been proposed as new prognostic biomarkers in several cancer entities. However, studies on circulating syndecan-1 (SDC1) and glypican-4 (GPC4) in CRC are limited. We, therefore, evaluated the impact of plasma SDC1 and GPC4 on the prognosis of metastatic (m)CRC patients. The present study included 93 patients with mCRC. The endpoints were progression-free survival (PFS) and overall survival (OS) at 12 months. SDC1 and GPC4 levels were measured in plasma using enzyme-linked immunosorbent assays. Plasma levels of SDC1 and GPC4 were significantly correlated. Significant correlations of these two markers were also found with carcinoembryonic antigen (CEA). Kaplan-Meier curve analyses indicated that PFS and OS probabilities significantly decreased with increasing levels of SDC1 and GPC4, respectively. Multivariable Cox regression analyses showed that both markers were significantly associated with PFS and OS independently from clinicopathological characteristics including CEA. Respective adjusted hazard ratios (HR) together with corresponding 95% confidence intervals for one standard deviation change of SDC1 were 1.32 [1.02-1.84] for PFS and 1.48 [1.01-2.15] for OS. Adjusted HRs [95% confidence intervals] of GPC4 were 1.42 [1.07-1.89] for PFS and 2.40 [1.51-3.81] for OS. Results from area under the receiver operating characteristic curve analyses suggest that GPC4 and SDC1 add additional prognostic values to CEA for OS. In conclusion, we showed significant associations of circulating SDC1 and GPC4 with poor survival of mCRC patients.

Harnessing Human Papillomavirus’ Natural Tropism to Target Tumors

Human papillomaviruses (HPV) are small non-enveloped DNA tumor viruses established as the primary etiological agent for the development of cervical cancer. Decades of research have elucidated HPV’s primary attachment factor to be heparan sulfate proteoglycans (HSPG). Importantly, wounding and exposure of the epithelial basement membrane was found to be pivotal for efficient attachment and infection of HPV in vivo. Sulfation patterns on HSPG’s become modified at the site of wounds as they serve an important role promoting tissue healing, cell proliferation and neovascularization and it is these modifications recognized by HPV. Analogous HSPG modification patterns can be found on tumor cells as they too require the aforementioned processes to grow and metastasize. Although targeting tumor associated HSPG is not a novel concept, the use of HPV to target and treat tumors has only been realized in recent years. The work herein describes how decades of basic HPV research has culminated in the rational design of an HPV-based virus-like infrared light activated dye conjugate for the treatment of choroidal melanoma.

Profiling of extracellular vesicles of metastatic urothelial cancer patients to discover protein signatures related to treatment outcome

The prognosis of metastatic urothelial carcinoma (mUC) patients is poor, and early prediction of systemic therapy response would be valuable to improve outcome. In this exploratory study, we investigated protein profiles in sequential plasma‐isolated extracellular vesicles (EVs) from a subset of mUC patients treated within a Phase I trial with vinflunine combined with sorafenib. The isolated EVs were of exosome size and expressed exosome markers CD9, TSG101 and SYND‐1. We found, no association between EVs/ml plasma at baseline and progression‐free survival (PFS). Protein profiling of EVs, using an antibody‐based 92‐plex Proximity Extension Assay on the Oncology II^® platform, revealed a heterogeneous protein expression pattern. Qlucore bioinformatic analyses put forward a protein signature comprising of SYND‐1, TNFSF13, FGF‐BP1, TFPI‐2, GZMH, ABL1 and ERBB3 to be putatively associated with PFS. Similarly, a protein signature from EVs that related to best treatment response was found, which included FR‐alpha, TLR 3, TRAIL and FASLG. Several of the markers in the PFS or best treatment response signatures were also identified by a machine learning classification algorithm. In conclusion, protein profiling of EVs isolated from plasma of mUC patients shows a potential to identify protein signatures that may associate with PFS and/or treatment response.

Identification of a novel glycolysis-related signature to predict the prognosis of patients with breast cancer

Background

Breast cancer (BC) has a high incidence and mortality rate in females. Its conventional clinical characteristics are far from accurate for the prediction of individual outcomes. Therefore, we aimed to develop a novel signature to predict the survival of patients with BC.

Methods

We analyzed the data of a training cohort from the Cancer Genome Atlas (TCGA) database and a validation cohort from the Gene Expression Omnibus (GEO) database. After the applications of Gene Set Enrichment Analysis (GSEA) and Cox regression analyses, a glycolysis-related signature for predicting the survival of patients with BC was developed; the signature contained AK3, CACNA1H, IL13RA1, NUP43, PGK1, and SDC1. Furthermore, on the basis of expression levels of the six-gene signature, we constructed a risk score formula to classify the patients into high- and low-risk groups. The receiver operating characteristic (ROC) curve and the Kaplan-Meier curve were used to assess the predicted capacity of the model. Later, a nomogram was developed to predict the outcomes of patients with risk score and clinical features over a period of 1, 3, and 5 years. We further used Human Protein Atlas (HPA) database to validate the expressions of the six biomarkers in tumor and sample tissues, which were taken as control.

Results

We constructed a six-gene signature to predict the outcomes of patients with BC. The patients in the high-risk group showed poor prognosis than those in the low-risk group. The area under the curve (AUC) values were 0.719 and 0.702, showing that the prediction performance of the signature is acceptable. Additionally, Cox regression analysis revealed that these biomarkers could independently predict the prognosis of BC patients with BC without being affected by clinical factors. The expression levels of all six biomarkers in BC tissues were higher than that in normal tissues; however, AK3 was an exception.

Conclusion

We developed a six-gene signature to predict the prognosis of patients with BC. Our signature has been proved to have the ability to make an accurate prediction and might be useful in expanding the hypothesis in clinical research.

Elucidation of Novel Molecular Targets for Therapeutic Strategies in Urothelial Carcinoma: A Literature Review

Urothelial carcinoma therapy is a rapidly evolving and expanding field. Traditional cytotoxic chemotherapy regimens have not produced optimal long-term outcomes, and many urothelial cancer patients have comorbidities that disqualify them as chemotherapy candidates. In recent years, a plethora of novel therapeutic agents that target diverse molecular pathways has emerged as alternative treatment modalities for not only metastatic urothelial carcinoma, but also for muscle-invasive bladder cancer and non-muscle invasive bladder cancer in adjuvant and definitive settings. This review paper aims to discuss the various categories of therapeutic agents for these different types of urothelial cancer, discussing immunotherapy, antibody-drug conjugates, kinase inhibitors, CAR-T cell therapy, peptide vaccination, and other drugs targeting pathways such as angiogenesis, DNA synthesis, mTOR/PI3K/AKT, and EGFR/HER-2.

MMP-7 Serum and Tissue Levels Are Associated with Poor Survival in Platinum-Treated Bladder Cancer Patients

Chemotherapy resistance is a main cause of therapeutic failure and death in bladder cancer. With the approval of immune checkpoint inhibitors, prediction of platinum treatment became of great clinical importance. Matrix metalloproteinase-7 (MMP-7) was shown to be involved in cisplatin resistance. Therefore, tissue and circulating MMP-7 levels were evaluated in 124 bladder cancer patients who received postoperative platinum-based chemotherapy. Tissue MMP-7 levels were analyzed by immunohistochemistry in 72 formalin-fixed, paraffin-embedded chemo-naïve tumor samples, while MMP-7 serum concentrations were determined in 132 serum samples of an independent cohort of 52 patients. MMP-7 tissue and serum levels were correlated with clinicopathological and follow-up data. MMP-7 gene expression was determined by RT-qPCR in 20 urothelial cancer cell lines and two non-malignant urothelial cell lines. MMP-7 was overexpressed in RT-112 and T-24 cells by stable transfection, to assess its functional involvement in platinum sensitivity. High MMP-7 tissue expression and pretreatment serum concentrations were independently associated with poor overall survival (tissue HR = 2.296, 95%CI = 1.235–4.268 and p = 0.009; serum HR = 2.743, 95%CI = 1.258–5.984 and p = 0.011). Therefore, MMP-7 tissue and serum analysis may help to optimize therapeutic decisions. Stable overexpression in RT-112 and T-24 cells did not affect platinum sensitivity.