Search

Abstract The second most common male cancer is prostate cancer (PCa), which has a high tendency for bone metastasis. Long non-coding RNAs, including TMPO-AS1, play a crucial role in PCa progression. However, TMPO-AS1’s function in PCa bone metastasis (BM) and its underlying molecular mechanisms are unclear. Herein, we found that the long transcript of TMPO-AS1 (TMPO-AS1 L ) was upregulated in PCa tissues with bone metastasis, and overexpression of TMPO-AS1 L correlated with advanced clinicopathological features and reduced BM-free survival in patients with PCa. Upregulated TMPO-AS1 L promoted, whereas downregulated TMPO-AS1 L inhibited, the PCa cell bone metastatic capacity in vitro and in vivo. Mechanistically, TMPO-AS1 L was demonstrated to act as a scaffold, that strengthened the interaction of casein kinase 2 alpha 1 (CSNK2A1) and DEAD-box helicase 3 X-linked (DDX3X), and activated the Wnt/β-catenin signaling pathway, thus promoting BM of PCa. Moreover, upregulation of TMPO-AS1 L in PCa resulted from transcription elongation modulated by general transcription factor IIF subunit 2 (GTF2F2). Collectively, our study provides critical insights into the role of TMPO-AS1 L in PCa BM via Wnt/β-catenin signaling, identifying TMPO-AS1 L as a candidate marker of PCa bone metastasis prognosis and therapeutic target.

Abstract Background Epithelial-to-mesenchymal transition (EMT) of malignant cells is a driving force of disease progression in human papillomavirus-negative (HPV-negative) head and neck squamous cell carcinomas (HNSCC). Sustained hyper-activation of epidermal growth factor receptor (EGFR) induces an invasion-promoting subtype of EMT (EGFR-EMT) characterized by a gene signature (“‘EGFR-EMT_Signature’”) comprising 5´-ectonucleotidase CD73. Generally, CD73 promotes immune evasion via adenosine (ADO) formation and associates with EMT and metastases. However, CD73 regulation through EGFR signaling remains under-explored and targeting options are amiss. Methods CD73 functions in EGFR-mediated tumor cell dissemination were addressed in 2D and 3D cellular models of migration and invasion. The novel antagonizing antibody 22E6 and therapeutic antibody Cetuximab served as inhibitors of CD73 and EGFR, respectively, in combinatorial treatment. Specificity for CD73 and its role as effector or regulator of EGFR-EMT were assessed upon CD73 knock-down and over-expression. CD73 correlation to tumor budding was studied in an in-house primary HNSCC cohort. Expression correlations, and prognostic and predictive values were analyzed using machine learning-based algorithms and Kaplan–Meier survival curves in single cell and bulk RNA sequencing datasets. Results CD73/NT5E is induced by the EGF/EGFR-EMT-axis and blocked by Cetuximab and MEK inhibitor. Inhibition of CD73 with the novel antagonizing antibody 22E6 specifically repressed EGFR-dependent migration and invasion of HNSCC cells in 2D. Cetuximab and 22E6 alone reduced local invasion in a 3D-model. Interestingly, combining inefficient low-dose concentrations of Cetuximab and 22E6 revealed highly potent in invasion inhibition, substantially reducing the functional IC50 of Cetuximab regarding local invasion. A role for CD73 as an effector of EGFR-EMT in local invasion was further supported by knock-down and over-expression experiments in vitro and by high expression in malignant cells budding from primary tumors. CD73 expression correlated with EGFR pathway activity, EMT, and partial EMT (p-EMT) in malignant single HNSCC cells and in large patient cohorts. Contrary to published data, CD73 was not a prognostic marker of overall survival (OS) in the TCGA-HNSCC cohort when patients were stratified for HPV-status. However, CD73 prognosticated OS of oral cavity carcinomas. Furthermore, CD73 expression levels correlated with response to Cetuximab in HPV-negative advanced, metastasized HNSCC patients. Conclusions In sum, CD73 is an effector of EGF/EGFR-mediated local invasion and a potential therapeutic target and candidate predictive marker for advanced HPV-negative HNSCC.

Abstract Background The microvascular endothelium inherently controls nutrient delivery, oxygen supply, and immune surveillance of malignant tumors, thus representing both biological prerequisite and therapeutic vulnerability in cancer. Recently, cellular senescence emerged as a fundamental characteristic of solid malignancies. In particular, tumor endothelial cells have been reported to acquire a senescence-associated secretory phenotype, which is characterized by a pro-inflammatory transcriptional program, eventually promoting tumor growth and formation of distant metastases. We therefore hypothesize that senescence of tumor endothelial cells (TEC) represents a promising target for survival prognostication and prediction of immunotherapy efficacy in precision oncology. Methods Published single-cell RNA sequencing datasets of different cancer entities were analyzed for cell-specific senescence, before generating a pan-cancer endothelial senescence-related transcriptomic signature termed EC.SENESCENCE.SIG. Utilizing this signature, machine learning algorithms were employed to construct survival prognostication and immunotherapy response prediction models. Machine learning-based feature selection algorithms were applied to select key genes as prognostic biomarkers. Results Our analyses in published transcriptomic datasets indicate that in a variety of cancers, endothelial cells exhibit the highest cellular senescence as compared to tumor cells or other cells in the vascular compartment of malignant tumors. Based on these findings, we developed a TEC-associated, senescence-related transcriptomic signature (EC.SENESCENCE.SIG) that positively correlates with pro-tumorigenic signaling, tumor-promoting dysbalance of immune cell responses, and impaired patient survival across multiple cancer entities. Combining clinical patient data with a risk score computed from EC.SENESCENCE.SIG, a nomogram model was constructed that enhanced the accuracy of clinical survival prognostication. Towards clinical application, we identified three genes as pan-cancer biomarkers for survival probability estimation. As therapeutic perspective, a machine learning model constructed on EC.SENESCENCE.SIG provided superior pan-cancer prediction for immunotherapy response than previously published transcriptomic models. Conclusions We here established a pan-cancer transcriptomic signature for survival prognostication and prediction of immunotherapy response based on endothelial senescence.

Abstract Rationale The M2-like tumor-associated macrophages (TAMs) are independent prognostic factors in melanoma. Methods We performed weighted gene co-expression network analysis (WGCNA) to identify the module most correlated with M2-like TAMs. The Cancer Genome Atlas (TCGA) patients were classified into two clusters that differed based on prognosis and biological function, with consensus clustering. A prognostic model was established based on the differentially expressed genes (DEGs) of the two clusters. We investigated the difference in immune cell infiltration and immune response-related gene expression between the high and low risk score groups. Results The risk score was defined as an independent prognostic value in melanoma. VARS1 was a hub gene in the M2-like macrophage-associated WGCNA module that the DepMap portal demonstrated was necessary for melanoma growth. Overexpressing VARS1 in vitro increased melanoma cell migration and invasion, while downregulating VARS1 had the opposite result. VARS1 overexpression promoted M2 macrophage polarization and increased TGF-β1 concentrations in tumor cell supernatant in vitro. VARS1 expression was inversely correlated with immune-related signaling pathways and the expression of several immune checkpoint genes. In addition, the VARS1 expression level helped predict the response to anti-PD-1 immunotherapy. Pan-cancer analysis demonstrated that VARS1 expression negatively correlated with CD8 T cell infiltration and the immune response-related pathways in most cancers. Conclusion We established an M2-like TAM-related prognostic model for melanoma and explored the role of VARS1 in melanoma progression, M2 macrophage polarization, and the development of immunotherapy resistance.

Abstract Background Epidermal growth factor receptor (EGFR) is both a driver oncogene and a therapeutic target in advanced head and neck squamous cell carcinoma (HNSCC). However, response to EGFR treatment is inconsistent and lacks markers for treatment prediction. This study investigated EGFR-induced epithelial-to-mesenchymal transition (EMT) as a central parameter in tumor progression and identified novel prognostic and therapeutic targets, and a candidate predictive marker for EGFR therapy response. Methods Transcriptomic profiles were analyzed by RNA sequencing (RNA-seq) following EGFR-mediated EMT in responsive human HNSCC cell lines. Exclusive genes were extracted via differentially expressed genes (DEGs) and a risk score was determined through forward feature selection and Cox regression models in HNSCC cohorts. Functional characterization of selected prognostic genes was conducted in 2D and 3D cellular models, and findings were validated by immunohistochemistry in primary HNSCC. Results An EGFR-mediated EMT gene signature composed of n = 171 genes was identified in responsive cell lines and transferred to the TCGA-HNSCC cohort. A 5-gene risk score comprising DDIT4, FADD, ITGB4, NCEH1, and TIMP1 prognosticated overall survival (OS) in TCGA and was confirmed in independent HNSCC cohorts. The EGFR-mediated EMT signature was distinct from EMT hallmark and partial EMT (pEMT) meta-programs with a differing enrichment pattern in single malignant cells. Molecular characterization showed that ITGB4 was upregulated in primary tumors and metastases compared to normal mucosa and correlated with EGFR/MAPK activity in tumor bulk and single malignant cells. Preferential localization of ITGB4 together with its ligand laminin 5 at tumor-stroma interfaces correlated with increased tumor budding in primary HNSCC tissue sections. In vitro, ITGB4 knock-down reduced EGFR-mediated migration and invasion and ITGB4-antagonizing antibody ASC8 impaired 2D and 3D invasion. Furthermore, a logistic regression model defined ITGB4 as a predictive marker of progression-free survival in response to Cetuximab in recurrent metastatic HNSCC patients. Conclusions EGFR-mediated EMT conveyed through MAPK activation contributes to HNSCC progression upon induction of migration and invasion. A 5-gene risk score based on a novel EGFR-mediated EMT signature prognosticated survival of HNSCC patients and determined ITGB4 as potential therapeutic and predictive target in patients with strong EGFR-mediated EMT.

Microvascular immunothrombotic dysregulation is a critical process in the pathogenesis of severe systemic inflammatory diseases. The mechanisms controlling immunothrombosis in inflamed microvessels, however, remain poorly understood. Here, we report that under systemic inflammatory conditions the matricellular glycoproteinvitronectin (VN) establishes an intravascular scaffold, supporting interactions of aggregating platelets with immune cells and the venular endothelium. Blockade of the VN receptor glycoprotein (GP)IIb/IIIa interfered with this multicellular interplay and effectively prevented microvascular clot formation. In line with these experimental data, particularly VN was found to be enriched in the pulmonary microvasculature of patients with non-infectious (pancreatitis-associated) or infectious (coronavirus disease 2019 (COVID-19)-associated) severe systemic inflammatory responses. Targeting the VN-GPIIb/IIIa axis hence appears as a promising, already feasible strategy to counteract microvascular immunothrombotic dysregulation in systemic inflammatory pathologies.

Ulceration and immune status are independent prognostic factors for survival in melanoma patients. Herein univariate Cox regression analysis revealed 53 ulcer-immunity-related DEGs. We performed consensus clustering to divide The Cancer Genome Atlas (TCGA) cohort (n = 467) into three subtypes with different prognosis and biological functions, followed by validation in three merged Gene Expression Omnibus (GEO) cohorts (n = 399). Multiomics approach was used to assess differences among the subtypes. Cluster 3 showed relatively lesser amplification and expression of immune checkpoint genes. Moreover, Cluster 3 lacked immune-related pathways and immune cell infiltration, and had higher proportion of non-responders to immunotherapy. We also constructed a prognostic model based on ulceration and immune related genes in melanoma. EIF3B was a hub gene in the intersection between genes specific to Cluster 3 and those pivotal for melanoma growth (DepMap, https://depmap.org/portal/download/). High EIF3B expression in TCGA and GEO datasets was related to worst prognosis. In vitro models revealed that EIF3B knockdown inhibited melanoma cell migration and invasion, and decreased TGF-β1 level in supernatant compared with si-NC cells. EIF3B expression was negatively correlated with immune-related signaling pathways, immune cell gene signatures, and immune checkpoint gene expression. Moreover, its low expression could predict partial response to anti-PD-1 immunotherapy. To summarize, we established a prognostic model for melanoma and identified the role of EIF3B in melanoma progression and immunotherapy resistance development.