α-E-Catenin (CTNNA1) Inhibits Cell Proliferation, Invasion and EMT of Bladder Cancer

Multiple programmed cell death patterns and immune landscapes in bladder cancer: Evidence based on machine learning and multi-cohorts

BACKGROUND

Bladder cancer (BLCA) is the most prevalent malignant neoplasm of the urinary tract, and ranks seventh as the most frequent systemic neoplasm in males. Dysregulation of programmed cell death (PCD) has been implicated in various stages of cancer progression, including tumorigenesis, invasion, and metastasis. However, the correlation between multiple PCD modes and BLCA is lacking. Thus, a risk prediction model was built based on 12 models of PCD to predict prognosis and immunotherapy response in patients with BLCA.

METHODS

The RNA sequencing transcriptome data of BLCA were collected from the Cancer Genome Atlas Program (TCGA) and GEO datasets. Univariate Cox and LASSO regression analyzes were performed to identify PCD-related genes (PCDRGs) significant for prognosis. Multivariate Cox regression analysis was used to develop a prognostic model for PCD. Survival analysis and chi-squared test were employed to analyze the survival variations between different risk groups. Univariate and multivariate Cox analyses were performed to evaluate the model as an independent prognostic predictor. A nomogram was formulated using both clinical data and the model to predict the survival rates of BLCA patients. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were performed to analyze and elucidate the molecular mechanisms and pathways operating within different risk score groups. Furthermore, the immune landscape was investigated and the efficacy of various anti-tumor drugs was evaluated for BLCA. Finally, consensus clustering analysis was adopted to explore the association between different PCD clusters and clinical characteristics.

RESULTS

Assessment of the public datasets and multivariate Cox analysis yielded 1254 PCDRGs, of which 10 PCDRGs for BLCA were identified. Based on the PCDRGs, a prognostic model was built for BLCA patient prognosis. Compared with the low-risk group, the high-risk group had a poorer prognosis. The model predicted area under the curve (AUC) values of 0.751, 0.753, and 0.763, respectively, for 1-, 3-, and 5-year survival of BLCA patients. The nomogram further demonstrated the credibility of the prognosis model. The low-risk group patients exhibited lower TIDE scores and higher TMB scores, implying better response of the low-risk group to immunotherapy. The consensus clustering analysis indicated that compared with PCD cluster A, PCD cluster B was significantly more expressed in PCDRGs, suggesting a closer relation of PCD cluster B to PCDRGs. Patients in PCD cluster B had lower risk scores.

CONCLUSION

To summarize, the effects of 12 PCD patterns on BLCA were synthesized and the correlation between PCD and BLCA was explored. These findings provide new and convincing evidence for individualized treatment of BLCA, and help guide the treatment strategy and improve the prognosis of BLCA patients.

Efficacy of GV1001 with gemcitabine/capecitabine in previously untreated patients with advanced pancreatic ductal adenocarcinoma having high serum eotaxin levels (KG4/2015): an open-label, randomised, Phase 3 trial

BACKGROUND

The TeloVac study indicated GV1001 did not improve the survival of advanced pancreatic ductal adenocarcinoma (PDAC). However, the cytokine examinations suggested that high serum eotaxin levels may predict responses to GV1001. This Phase III trial assessed the efficacy of GV1001 with gemcitabine/capecitabine for eotaxin-high patients with untreated advanced PDAC.

METHODS

Patients recruited from 16 hospitals received gemcitabine (1000 mg/m2, D 1, 8, and 15)/capecitabine (830 mg/m2 BID for 21 days) per month either with (GV1001 group) or without (control group) GV1001 (0.56 mg; D 1, 3, and 5, once on week 2-4, 6, then monthly thereafter) at random in a 1:1 ratio. The primary endpoint was overall survival (OS) and secondary end points included time to progression (TTP), objective response rate, and safety.

RESULTS

Total 148 patients were randomly assigned to the GV1001 (n = 75) and control groups (n = 73). The GV1001 group showed improved median OS (11.3 vs. 7.5 months, P = 0.021) and TTP (7.3 vs. 4.5 months, P = 0.021) compared to the control group. Grade >3 adverse events were reported in 77.3% and 73.1% in the GV1001 and control groups (P = 0.562), respectively.

CONCLUSIONS

GV1001 plus gemcitabine/capecitabine improved OS and TTP compared to gemcitabine/capecitabine alone in eotaxin-high patients with advanced PDAC.

CLINICAL TRIAL REGISTRATION

NCT02854072.

α-catenin interaction with YAP/FoxM1/TEAD-induced CEP55 supports liver cancer cell migration

BACKGROUND

Adherens junctions (AJs) facilitate cell-cell contact and contribute to cellular communication as well as signaling under physiological and pathological conditions. Aberrant expression of AJ proteins is frequently observed in human cancers; however, how these factors contribute to tumorigenesis is poorly understood. In addition, for some factors such as α-catenin contradicting data has been described. In this study we aim to decipher how the AJ constituent α-catenin contributes to liver cancer formation.

METHODS

TCGA data was used to detect transcript changes in 23 human tumor types. For the detection of proteins, liver cancer tissue microarrays were analyzed by immunohistochemistry. Liver cancer cell lines (HLF, Hep3B, HepG2) were used for viability, proliferation, and migration analyses after RNAinterference-mediated gene silencing. To investigate the tumor initiating potential, vectors coding for α-catenin and myristoylated AKT were injected in mice by hydrodynamic gene delivery. A BioID assay combined with mass spectrometry was performed to identify α-catenin binding partners. Results were confirmed by proximity ligation and co-immunoprecipitation assays. Binding of transcriptional regulators at gene promoters was investigated using chromatin-immunoprecipitation.

RESULTS

α-catenin mRNA was significantly reduced in many human malignancies (e.g., colon adenocarcinoma). In contrast, elevated α-catenin expression in other cancer entities was associated with poor clinical outcome (e.g., for hepatocellular carcinoma; HCC). In HCC cells, α-catenin was detectable at the membrane as well as cytoplasm where it supported tumor cell proliferation and migration. In vivo, α-catenin facilitated moderate oncogenic properties in conjunction with AKT overexpression. Cytokinesis regulator centrosomal protein 55 (CEP55) was identified as a novel α-catenin-binding protein in the cytoplasm of HCC cells. The physical interaction between α-catenin and CEP55 was associated with CEP55 stabilization. CEP55 was highly expressed in human HCC tissues and its overexpression correlated with poor overall survival and cancer recurrence. Next to the α-catenin-dependent protein stabilization, CEP55 was transcriptionally induced by a complex consisting of TEA domain transcription factors (TEADs), forkhead box M1 (FoxM1), and yes-associated protein (YAP). Surprisingly, CEP55 did not affect HCC cell proliferation but significantly supported migration in conjunction with α-catenin.

CONCLUSION

Migration-supporting CEP55 is induced by two independent mechanisms in HCC cells: stabilization through interaction with the AJ protein α-catenin and transcriptional activation via the FoxM1/TEAD/YAP complex.

Changes in the expression of cancer- and metastasis-related genes and proteins after metformin treatment under different metabolic conditions in endometrial cancer cells

Research question

Hyperinsulinemia and elevated estrogen levels are known risk factors for endometrial cancer (EC) development and are associated with obesity, type 2 diabetes mellitus (T2DM), insulin resistance, among others. Metformin, an insulin-sensitizing drug, displays anti-tumor effects in cancer patients, including EC, but the mechanism of action is still not completely understood. In the present study, the effects of metformin on gene and protein expression were investigated in pre- and postmenopausal EC in vitro models in order to identify candidates that are potentially involved in the drug's anti-cancer mechanism.

Design

After treating the cells with metformin (0.1 and 1.0 mmol/L), changes in the expression of >160 cancer- and metastasis-related gene transcripts were evaluated with RNA arrays. A total of 19 genes and 7 proteins were selected for a follow-up expression analysis, including further treatment conditions, in order to evaluate the influence of hyperinsulinemia and hyperglycemia on metformin-induced effects.

Results

Changes in the expression of BCL2L11, CDH1, CDKN1A, COL1A1, PTEN, MMP9 and TIMP2 were analyzed on gene and protein level. The consequences resulting from the detected expression changes as well as the influence of varying environmental influences are discussed in detail. With the presented data, we contribute to a better understanding of the direct anti-cancer activity of metformin as well as its underlying mechanism of action in EC cells.

Conclusions

Although further research will be necessary to confirm the data, the influence of different environmental settings on metformin-induced effects could be highlighted with the presented data. Additionally, gene and protein regulation were not similar in the pre- and postmenopausal in vitro models.

Differential Gene Expression of fresh tissue and patient-derived explants' matricellular proteins augment inflammatory breast cancer metastasis: the possible role of IL-6 and MCP-1

BACKGROUND

Matricellular proteins comprising matrisome and adhesome are responsible for structure integrity and interactions between cells in the tumour microenvironment of breast cancer. Changes in the gene expression of matrisome and adhesome augment metastasis. Since inflammatory breast cancer (IBC) is characterized by high metastatic behaviour. Herein, we compared the gene expression profile of matrisome and adhesome in non-IBC and IBC in fresh tissue and ex vivo patient-derived explants (PDEs) and we also compared the secretory inflammatory mediators of PDEs in non-IBC and IBC to identify secretory cytokines participate in cross-talk between cells via interactions with matrisome and adhisome.

METHODS

Fifty patients (31 non-IBC and 19 IBC) were enrolled in the present study. To test their validation in clinical studies, PDEs were cultured as an ex vivo model. Gene expression and cytokine array were used to identify candidate genes and cytokines contributing to metastasis in the examined fresh tissues and PDEs. Bioinformatics analysis was applied on identified differentially expressed genes using GeneMANIA and Metascape gene annotation and analysis resource to identify pathways involved in IBC metastasis.

RESULTS

Normal and cancer fresh tissues and PDEs of IBC were characterized by overexpression of CDH1 and MMP14 and downregulation of CTNNA1 and TIMP1 compared with non-IBC. The secretome of IBC cancer PDEs is characterized by significantly high expression of interleukin 6 and monocyte chemoattractant protein-1 (CCL2) compared with non-IBC.

CONCLUSION

Genes expressed by adhisome and matrisome play a significant role in IBC metastasis and should be considered novel target therapy.

Different impacts of TP53 mutations on cell cycle-related gene expression among cancer types

Functional properties caused by TP53 mutations are involved in cancer development and progression. Although most of the mutations lose normal p53 functions, some of them, gain-of-function (GOF) mutations, exhibiting novel oncogenic functions. No reports have analyzed the impact of TP53 mutations on the gene expression profile of the p53 signaling pathway across cancer types. This study is a cross-cancer type analysis of the effects of TP53 mutations on gene expression. A hierarchical cluster analysis of the expression profile of the p53 signaling pathway classified 21 cancer types into two clusters (A1 and A2). Changes in the expression of cell cycle-related genes and MKI67 by TP53 mutations were greater in cluster A1 than in cluster A2. There was no distinct difference in the effects between GOF and non-GOF mutations on the gene expression profile of the p53 signaling pathway.

The Role of CTNNA1 in Malignancies: An Updated Review

Catenin alpha 1 (CTNNA1), encoding α-catenin, is involved in several physiological activities, such as adherens junction synthesis and signal transduction. Recent studies have suggested additional functions for CTNNA1 malignancies. This review systematically summarizes the varying functions of CTNNA1 in different tumors and briefly describes the diverse pathways and mechanisms involved in different types of tumors. CTNNA1 is abnormally expressed in leukemia and solid tumor such as cancers of digestive system, genitourinary system and breast, and it's related to the occurrence, development, and prognosis of tumors. In addition, the possible physiological processes involving CTNNA1, such as methylation, miRNA interference, or regulatory axes, similar to those of CDH1, SETD2, and hsa-miR-30d-5p/GJA1 are also summarized here. The precise mechanism of CTNNA1 in most cancers remains uncertain; hence, additional pre-clinical studies of CTNNA1 are warranted for potential early tumor diagnosis, prognosis, and treatment.

Hereditary Diffuse Gastric Cancer: A 2022 Update

Gastric cancer is ranked fifth among the most commonly diagnosed cancers, and is the fourth leading cause of cancer-related deaths worldwide. The majority of gastric cancers are sporadic, while only a small percentage, less than 1%, are hereditary. Hereditary diffuse gastric cancer (HDGC) is a rare malignancy, characterized by early-onset, highly-penetrant autosomal dominant inheritance mainly of the germline alterations in the E-cadherin gene (CDH1) and β-catenin (CTNNA1). In the present study, we provide an overview on the molecular basis of HDGC and outline the essential elements of genetic counseling and surveillance. We further provide a practical summary of current guidelines on clinical management and treatment of individuals at risk and patients with early disease.

Hereditary diffuse gastric cancer (HDGC). An overview

It is estimated that up to 10% of gastric carcinomas show familial aggregation. In contrast, around 1-3 % (approximately 33,000 yearly) are genuinely hereditary. Hereditary diffuse gastric cancer (HDGC) is a rare malignancy characterized by autosomal dominant inheritance of pathological variants of the CDH1 and CTNNA1 genes encoding the adhesion molecules E-cadherin and α-catenin, respectively. The multifocal nature of the disease and the difficulty of visualizing precursor lesions by endoscopy underscore the need to be aware of this malignancy as surgical prevention can be fully protective. Here, we provide an overview of the main epidemiological, clinical, genetic, and pathological features of HDGC, as well as updated guidelines for its diagnosis, genetic testing, counseling, surveillance, and management. We conclude that HDGC is a rare, highly penetrant disease that is difficult to diagnose and manage, so it is necessary to correctly identify it to offer patients and their families' adequate management following the recommendations of the IGCL. A critical point is identifying a mutation in HDGC families to determine whether unaffected relatives are at risk for cancer.

Gene Expression Analysis of Biphasic Pleural Mesothelioma: New Potential Diagnostic and Prognostic Markers

Biphasic is the second most common histotype of pleural mesothelioma (PM). It shares epithelioid and sarcomatoid features and is challenging to diagnose. The aim of this study was to identify biphasic PM markers to improve subtyping and prognosis definition. The expression levels of 117 cancer genes, evaluated using the nanoString system, were compared between the three major histotypes (epithelioid, sarcomatoid, and biphasic), and expression differences within biphasic PM were evaluated in relation to the percentage of epithelioid components. Biphasic PM overexpressed CTNNA1 and TIMP3 in comparison to sarcomatoid, and COL16A1 and SDC1 in comparison to epithelioid PM. CFB, MSLN, CLDN15, SERPINE1, and PAK4 were deregulated among all histotypes, leading to the hypothesis of a gradual expression from epithelioid to sarcomatoid PM. According to gene expression, biphasic PM samples were divided in two clusters with a significant difference in the epithelioid component. ADCY4, COL1A1, and COL4A2 were overexpressed in the biphasic group with a low percentage of epithelioid component. Survival analysis using TCGA data showed that high COL1A1 and COL4A2 expression levels correlate with poor survival in PM patients. Herein, we identified markers with the potential to improve diagnosis and prognostic stratification of biphasic PM, which is still an orphan tumor.

Integrated genome and tissue engineering enables screening of cancer vulnerabilities in physiologically relevant perfusable ex vivo cultures

Genetic screens are powerful tools for both resolving biological function and identifying potential therapeutic targets, but require physiologically accurate systems to glean biologically useful information. Here, we enable genetic screens in physiologically relevant ex vivo cancer tissue models by integrating CRISPR-Cas-based genome engineering and biofabrication technologies. We first present a novel method for generating perfusable tissue constructs, and validate its functionality by using it to generate three-dimensional perfusable dense cultures of cancer cell lines and sustain otherwise ex vivo unculturable patient-derived xenografts. Using this system we enable large-scale CRISPR screens in perfused tissue cultures, as well as emulate a novel point-of-care diagnostics scenario of a clinically actionable CRISPR knockout (CRISPRko) screen of genes with FDA-approved drug treatments in ex vivo PDX cell cultures. Our results reveal differences across in vitro and in vivo cancer model systems, and highlight the utility of programmable tissue engineered models for screening therapeutically relevant cancer vulnerabilities.

Proteomic Screening and Verification of Biomarkers in Different Stages of Mycosis Fungoides: A pilot Study

Mycosis fungoides (MF) is the most common cutaneous T-cell lymphoma; in advanced stages, it can involve multiple organs and has a poor prognosis. Early detection of the disease is still urgent, but there is no optimal therapy for advanced MF. In the present study, quantitative proteomic analyses (label-free quantitation, LFQ) were applied to tissue samples of different stages of MF and tissue samples from controls (eczema patients and healthy donors) to conduct preliminary molecular analysis to clarify the pathogenesis of the disease. Differential protein expression analysis demonstrated that 113 and 305 proteins were associated with the early and advanced stages of MF, respectively. Gene ontology (GO) enrichment analysis was conducted to determine the potential functions of the proteins, which could be classified into three categories: biological process, cellular component, and molecular function. The results revealed that a series of biological processes, including “initiation of DNA replication” and “nucleosome assembly,” were involved in the disease. Moreover, cellular components, including the “desmosome” and “integrin complex,” may affect the invasion and metastasis of MF via molecular functions, including “integrin binding” and “cadherin binding”. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis demonstrated that “focal adhesion DNA replication,” “Toll-like receptor signalling pathway” and other pathways were also involved. A parallel reaction monitoring (PRM) assay was applied to validate the identified differentially expressed proteins. In conclusion, the above proteomic findings may have great diagnostic and prognostic value in diverse malignancies, especially MF. Nevertheless, further studies are still needed to explore the precise mechanisms of MF.