CTSV (cathepsin V) promotes bladder cancer progression by increasing NF-κB activity

Integration of Single-Cell RNA Sequencing and Bulk RNA Sequencing to Identify an Immunogenic Cell Death-Related 5-Gene Prognostic Signature in Hepatocellular Carcinoma

Introduction

Immunogenic cell death (ICD) can enhance the potency of immunotherapy in cancer treatment. Nevertheless, it is ambiguous how ICD-related genes (ICDRGs) contribute to hepatocellular carcinoma (HCC).

Methods

Single-cell RNA sequencing (scRNA-seq) data were used to distinguish malignant cells from normal cells in the HCC tumor microenvironment(TME). Bulk RNA sequencing data was employed to acquire the landscape of the 33 ICDRGs. Unsupervised clustering identified two ICD molecular subtypes. The cellular infiltration characteristics and biological behavior in different subtypes were analyzed by ssGSEA. Subsequently, differentially expressed genes (DEGs) between the two subtypes were determined, based on which patients were classified into three gene clusters. Then, the prognostic model was constructed by Lasso-Cox analysis. Finally, we investigated the expression of risk genes in cancer cell line encyclopedia (CCLE) and validated the function of NKX3-2 in vitro experiments.

Results

ICD scores and ICDRGs expression in malignant cells were significantly lower than in normal cells by scRNA-seq analysis. ICD-high subtype was characterized by ICD-related gene overexpression and high levels of immune infiltration abundance and immune checkpoints; Three DEGs-related gene clusters were likewise strongly linked to stromal and immunological activation. In the ICD-related prognostic model consisting of NKX3-2, CHODL, MMP1, NR0B1, and CTSV, the low-risk group patients had a better endpoint and displayed increased susceptibility to immunotherapy and chemotherapeutic drugs like 5-Fluorouracil, afatinib, bortezomib, cediratinib, lapatinib, dasatinib, gefitinib and crizotinib. Moreover, NKX3-2 amplification in HCC samples has been verified by experiments, and its disruption suppressed the proliferation and invasion of tumor cells.

Conclusion

Our study highlighted the potential of the ICDRGs risk score as a prognostic indicator to aid in the accurate diagnosis and immunotherapy sensitivity of HCC.

The causal relationship between cathepsins and digestive system tumors: a Mendelian randomization study

Background

Multiple studies have confirmed the significant role of cathepsins in the development and progression of digestive system tumors. However, further investigation is needed to determine the causal relationships.

Methods

We conducted a two-sample bidirectional Mendelian randomization (MR) study using pooled data from a genome-wide association study (GWAS) to assess the causal associations between nine cathepsins (cathepsin B, E, F, G, H, L2, O, S, and Z) and six types of digestive system tumors, including hepatocellular carcinoma (HCC), pancreatic cancer (PCa), biliary tract cancer (BTC), colorectal cancer (CRC), gastric carcinoma (GC), and esophageal cancer (EC). We employed the following methods including inverse variance weighting (IVW), MR-Egger, weighted median (WM), Cochran's Q, MR-PRESSO, MR-Egger intercept test and leave-one-out sensitivity analysis. The STROBE-MR checklist for the reporting of MR studies was used in this study.

Results

The risk of HCC increased with high levels of cathepsin G (IVW: p = 0.029, odds ratio (OR) = 1.369, 95% confidence interval (CI) = 1.033-1.814). Similarly, BTC was associated with elevated cathepsin B levels (IVW: p = 0.025, OR = 1.693, 95% CI = 1.070-2.681). Conversely, a reduction in PCa risk was associated with increased cathepsin H levels (IVW: p = 0.027, OR = 0.896, 95% CI = 0.812-0.988). Lastly, high levels of cathepsin L2 were found to lower the risk of CRC (IVW: p = 0.034, OR = 0.814, 95% CI = 0.674-0.985).

Conclusion

Our findings confirm the causal relationship between cathepsins and digestive system tumors, which can offer valuable insights for the diagnosis and treatment of digestive system tumors.

Cathepsin V is correlated with the prognosis and tumor microenvironment in liver cancer

Recent studies have shown that high cell cycle activity negatively correlates with antitumor immunity in certain cancer types. However, a similar correlation has not been proven in liver cancer. We downloaded transcriptomic profiles of the cancer genome atlas-liver hepatocellular carcinoma (TCGA-LIHC) and assessed the cell cycle distribution of samples using single sample gene set enrichment analysis (ssGSEA), termed the cell cycle score (CCS). We obtained cell cycle-related differentially expressed prognostic genes and identified CENPA, CDC20, and CTSV using LASSO regression. We studied the effect of CTSV on clinical features and immune alterations in liver cancer based on TCGA-LIHC data. In vitro and in vivo experiments were performed to validate the role of CTSV in liver cancer using liver cancer cell lines and tissues. We found that the CCS closely correlated with the clinical features and prognosis of patients in TCGA-LIHC. Analysis of differentially expressed genes (DEGs), univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression identified cathepsin V (CTSV) with prognostic significance in LIHC. Importantly, single-gene survival analysis of CTSV using microarray and sequencing data indicated that high levels of CTSV expression correlated with an unfavorable prognosis in various cancers. Gene set enrichment analysis revealed that high CTSV expression closely correlated with decreased expression of metabolic genes and increased expression of cell cycle genes. Furthermore, difference and correlation analyses of the relationship between CTSV expression and immune infiltrates, determined using CIBERSORT and TIMER algorithms, revealed that CTSV expression correlated with macrophages and CD4+ T cells. In vitro and in vivo experiments revealed that knockdown of CTSV inhibited liver cancer cells proliferation. Immunohistochemical staining showed that high CTSV expression correlated with macrophage infiltration in liver cancer tissues, predicted a poor prognosis, and is associated with the effectiveness of hepatocellular carcinoma treatment. In couclusion, CTSV is a novel cell cycle-associated gene with clinical significance in HCC.

Cryptotanshinone Inhibits Bladder Cancer Cell Malignant Progression in a Lipopolysaccharide-Induced Inflammatory Microenvironment through NLRP3 Inhibition

Background

Bladder cancer (BC) is one of the most common malignancies of the urogenital system. This study assessed the nucleotide-binding oligomerization domain and leucine-rich repeat and pyrin domain-containing protein 3 (NLRP3) in BC as well as the effects of cryptotanshinone on changes in BC malignant behaviors and NLRP3 expression under a lipopolysaccharide (LPS)-induced inflammatory microenvironment.

Methods

BC tissue specimens from 62 patients were collected for immunohistochemical detection of NLRP3 protein. BC and normal urothelial cell lines were cultured for the detection of NLRP3 mRNA and protein. Then, BC cells were pretreated with LPS to mimic the inflammatory tumor microenvironment. Next, these cells were incubated with a low or high dose of cryptotanshinone to assess its effects on tumor cell malignant behaviors as well as transfected with NLRP3 cDNA to confirm the role of NLRP3 in BC cells in vitro.

Results

High NLRP3 expression was associated with larger tumor diameters (>2 cm), muscle invasion, and metastasis. The levels of NLRP3 mRNA and protein were greater in BC cells than in normal urothelial cells. LPS pretreatment significantly promoted NLRP3 and inflammatory cytokine expression in BC cells, and induced cell viability, migration, and invasion. However, cryptotanshinone was able to reduce the LPS-induced increase of NLRP3 and inflammatory cytokine expression as well as the BC cell malignant progression. NLRP3 overexpression using NLRP3 cDNA further promoted BC cell malignant progression after LPS stimulation and reversed cryptotanshinone-reduced LPS-induced BC cell malignant behaviors.

Conclusion

NLRP3 might possess oncogenic activity in BC, and the antitumor activity of cryptotanshinone in BC in vitro might be related to its inhibition of NLRP3 expression.

Construction of a Liver Cancer Prognostic Model Based on Interferon-Gamma-Related Genes for Revealing the Immune Landscape

Inferferon-gamma (LFN-γ) exerts anti-tumor effects, but there is currently no reliable and comprehensive study on prognostic function of IFN-γ-related genes in liver cancer. In this study, IFN-γ-related differentially expressed genes (DEGs) in liver cancer were identified through GO/KEGG databases and open-access literature. Based on these genes, individuals with liver cancer were clustered. A prognostic model was built based on the intersection genes between differential genes in clusters and in liver cancer. Then, model predictive performance was analyzed and validated in GEO dataset. Regression analysis was fulfilled on the model, and a nomogram was utilized to evaluate model ability as an independent prognostic factor and its clinical application value. An immune-related analysis was conducted on both the H- and L-groups, with an additional investigation into link of model genes to drug sensitivity. Significant differential expression of IFN-γ-related genes was observed between the liver cancer and control groups. Subsequently, individuals with liver cancer were classified into two subtypes based on these genes, which displayed a notable difference in survival between the two subtypes. A 10-gene liver cancer prognostic model was constructed, with good prognostic performance and was an independent prognosticator for patient analysis. L-group patients possessed higher immune infiltration levels, immune checkpoint expression levels, and immunophenoscore, as well as lower TIDE scores. Drugs that had high correlations with the feature genes included SPANXB1: PF-04217903, SGX-523, MMP1: PF-04217903, DUSP13: Imatinib, TFF1: KHK-Indazole, and Fulvestrant. We built a 10-gene liver cancer prognostic model. It was found that L-group patients were more suitable for immunotherapy. This study provided valuable information on the prognosis of liver cancer.

Non-invasive diagnosis of early cutaneous squamous cell carcinoma

Early cutaneous squamous cell carcinoma (cSCC) can be challenging to diagnose using clinical criteria as it could present similar to actinic keratosis (AK) or Bowen's disease (BD), precursors of cSCC. Currently, histopathological assessment of an invasive biopsy is the gold standard for diagnosis. A non-invasive diagnostic approach would reduce patient and health system burden. Therefore, this study used non-invasive sampling by tape-stripping coupled with data-independent acquisition mass spectrometry (DIA-MS) proteomics to profile the proteome of histopathologically diagnosed AK, BD and cSCC, as well as matched normal samples. Proteomic data were analysed to identify proteins and biological functions that are significantly different between lesions. Additionally, a support vector machine (SVM) machine learning algorithm was used to assess the usefulness of proteomic data for the early diagnosis of cSCC. A total of 696 proteins were identified across the samples studied. A machine learning model constructed using the proteomic data classified premalignant (AK + BD) and malignant (cSCC) lesions at 77.5% accuracy. Differential abundance analysis identified 144 and 21 protein groups that were significantly changed in the cSCC, and BD samples compared to the normal skin, respectively (adj. p < 0.05). Changes in pivotal carcinogenic pathways such as LXR/RXR activation, production of reactive oxygen species, and Hippo signalling were observed that may explain the progression of cSCC from premalignant lesions. In summary, this study demonstrates that DIA-MS analysis of tape-stripped samples can identify non-invasive protein biomarkers with the potential to be developed into a complementary diagnostic tool for early cSCC.

Revisiting Concurrent Radiation Therapy, Temozolomide, and the Histone Deacetylase Inhibitor Valproic Acid for Patients with Glioblastoma-Proteomic Alteration and Comparison Analysis with the Standard-of-Care Chemoirradiation

BACKGROUND

Glioblastoma (GBM) is the most common brain tumor with an overall survival (OS) of less than 30% at two years. Valproic acid (VPA) demonstrated survival benefits documented in retrospective and prospective trials, when used in combination with chemo-radiotherapy (CRT).

PURPOSE

The primary goal of this study was to examine if the differential alteration in proteomic expression pre vs. post-completion of concurrent chemoirradiation (CRT) is present with the addition of VPA as compared to standard-of-care CRT. The second goal was to explore the associations between the proteomic alterations in response to VPA/RT/TMZ correlated to patient outcomes. The third goal was to use the proteomic profile to determine the mechanism of action of VPA in this setting.

MATERIALS AND METHODS

Serum obtained pre- and post-CRT was analyzed using an aptamer-based SOMAScan® proteomic assay. Twenty-nine patients received CRT plus VPA, and 53 patients received CRT alone. Clinical data were obtained via a database and chart review. Tests for differences in protein expression changes between radiation therapy (RT) with or without VPA were conducted for individual proteins using two-sided t-tests, considering p-values of <0.05 as significant. Adjustment for age, sex, and other clinical covariates and hierarchical clustering of significant differentially expressed proteins was carried out, and Gene Set Enrichment analyses were performed using the Hallmark gene sets. Univariate Cox proportional hazards models were used to test the individual protein expression changes for an association with survival. The lasso Cox regression method and 10-fold cross-validation were employed to test the combinations of expression changes of proteins that could predict survival. Predictiveness curves were plotted for significant proteins for VPA response (p-value < 0.005) to show the survival probability vs. the protein expression percentiles.

RESULTS

A total of 124 proteins were identified pre- vs. post-CRT that were differentially expressed between the cohorts who received CRT plus VPA and those who received CRT alone. Clinical factors did not confound the results, and distinct proteomic clustering in the VPA-treated population was identified. Time-dependent ROC curves for OS and PFS for landmark times of 20 months and 6 months, respectively, revealed AUC of 0.531, 0.756, 0.774 for OS and 0.535, 0.723, 0.806 for PFS for protein expression, clinical factors, and the combination of protein expression and clinical factors, respectively, indicating that the proteome can provide additional survival risk discrimination to that already provided by the standard clinical factors with a greater impact on PFS. Several proteins of interest were identified. Alterations in GALNT14 (increased) and CCL17 (decreased) (p = 0.003 and 0.003, respectively, FDR 0.198 for both) were associated with an improvement in both OS and PFS. The pre-CRT protein expression revealed 480 proteins predictive for OS and 212 for PFS (p < 0.05), of which 112 overlapped between OS and PFS. However, FDR-adjusted p values were high, with OS (the smallest p value of 0.586) and PFS (the smallest p value of 0.998). The protein PLCD3 had the lowest p-value (p = 0.002 and 0.0004 for OS and PFS, respectively), and its elevation prior to CRT predicted superior OS and PFS with VPA administration. Cancer hallmark genesets associated with proteomic alteration observed with the administration of VPA aligned with known signal transduction pathways of this agent in malignancy and non-malignancy settings, and GBM signaling, and included epithelial-mesenchymal transition, hedgehog signaling, Il6/JAK/STAT3, coagulation, NOTCH, apical junction, xenobiotic metabolism, and complement signaling.

CONCLUSIONS

Differential alteration in proteomic expression pre- vs. post-completion of concurrent chemoirradiation (CRT) is present with the addition of VPA. Using pre- vs. post-data, prognostic proteins emerged in the analysis. Using pre-CRT data, potentially predictive proteins were identified. The protein signals and hallmark gene sets associated with the alteration in the proteome identified between patients who received VPA and those who did not, align with known biological mechanisms of action of VPA and may allow for the identification of novel biomarkers associated with outcomes that can help advance the study of VPA in future prospective trials.