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2.
Front Immunol ; 14: 1129513, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-36999042

RESUMO

Introduction: Despite increased attention on immunotherapy, primarily immune checkpoint blockade, as a therapeutic approach for mesothelioma (MMe), its efficacy and tolerability remain questioned. One potential explanation for different responses to immunotherapy is the gut and intratumor microbiota; however, these remain an underexplored facet of MMe. This article highlights the cancer intratumor microbiota as a novel potential prognostic indicator in MMe. Methods: TCGA data on 86 MMe patients from cBioPortal underwent bespoke analysis. Median overall survival was used to divide patients into "Low Survivors" and "High Survivors". Comparison of these groups generated Kaplan-Meier survival analysis, differentially expressed genes (DEGs), and identification of differentially abundant microbiome signatures. Decontamination analysis refined the list of signatures, which were validated as an independent prognostic indicator through multiple linear regression modelling and Cox proportional hazards modelling. Finally, functional annotation analysis on the list of DEGs was performed to link the data together. Results: 107 genera signatures were significantly associated with patient survival (positively or negatively), whilst clinical characteristic comparison between the two groups demonstrated that epithelioid histology was more common in "High Survivors" versus biphasic in "Low Survivors". Of the 107 genera, 27 had published articles related to cancer, whilst only one (Klebsiella) had MMe-related published articles. Functional annotation analysis of the DEGs between the two groups highlighted fatty acid metabolism as the most enriched term in "High Survivors", whilst for "Low Survivors" the enriched terms primarily related to cell cycle/division. Linking these ideas and findings together is that the microbiome influences, and is influenced by, lipid metabolism. Finally, to validate the independent prognostic value of the microbiome, multiple linear regression modelling as well as Cox proportional hazards modelling were employed, with both approaches demonstrating that the microbiome was a better prognostic indicator than patient age or stage of the cancer. Discussion: The findings presented herein, alongside the very limited literature from scoping searches to validate the genera, highlight the microbiome and microbiota as a potentially rich source of fundamental analysis and prognostic value. Further in vitro studies are needed to elucidate the molecular mechanisms and functional links that may lead to altered survival.


Assuntos
Mesotelioma Maligno , Mesotelioma , Microbiota , Humanos , Prognóstico , Mesotelioma/patologia
3.
Int J Oncol ; 60(2)2022 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-35014681

RESUMO

The oxidoreductase protein disulfide isomerase A1 (PDIA1) functions as a cofactor for many transcription factors including estrogen receptor α (ERα), nuclear factor (NF)­κB, nuclear factor erythroid 2­like 2 (NRF2) and regulates the protein stability of the tumor suppressor p53. Taking this into account we hypothesized that PDIA1, by differentially modulating the gene expression of a diverse subset of genes in the ERα­positive vs. the ERα­negative breast cancer cells, might modify dissimilar pathways in the two types of breast cancer. This hypothesis was investigated using RNA­seq data from PDIA1­silenced MCF­7 (ERα­positive) and MDA­MB­231 (ERα­negative) breast cancer cells treated with either interferon Î³ (IFN­Î³) or etoposide (ETO), and the obtained data were further analyzed using a variety of bioinformatic tools alongside clinical relevance assessment via Kaplan­Meier patient survival curves. The results highlighted the dual role of PDIA1 in suppressing carcinogenesis in the ERα(+) breast cancer patients by negatively regulating the response to reactive oxygen species (ROS) and promoting carcinogenesis by inducing cell cycle progression. In the ERα(­) breast cancer patients, PDIA1 prevented tumor development by modulating NF­κΒ and p53 activity and cell migration and induced breast cancer progression through control of cytokine signaling and the immune response. The findings reported in this study shed light on the differential pathways regulating carcinogenesis in ERα(+) and ERα(­) breast cancer patients and could help identify therapeutic targets selectively effective in ERα(+) vs. ERα(­) patients.


Assuntos
Neoplasias da Mama/tratamento farmacológico , Pró-Colágeno-Prolina Dioxigenase/farmacocinética , Isomerases de Dissulfetos de Proteínas/farmacocinética , Transdução de Sinais/genética , Linhagem Celular Tumoral/efeitos dos fármacos , Feminino , Humanos , Pró-Colágeno-Prolina Dioxigenase/metabolismo , Isomerases de Dissulfetos de Proteínas/metabolismo , Transdução de Sinais/imunologia
4.
Int J Mol Sci ; 22(11)2021 May 22.
Artigo em Inglês | MEDLINE | ID: mdl-34067485

RESUMO

Immune checkpoint blockade targeting PD-1 (PDCD1)/PD-L1 (CD274) is increasingly used for multiple cancers. However, efficacy and adverse-related events vary significantly. This bioinformatic study interrogated molecular differences pertaining to PDCD1/CD274 and their correlated genes on a pan-cancer basis to identify differences between cancer types. Patient RNA-seq data from fifteen cancer types were accessed on cBioPortal to determine the role of PDCD1/CD274 in patient survival and to identify positively and negatively correlated genes, which were also assessed for clinical relevance. Genes correlating with PDCD1/CD274 across multiple cancers were taken forward for drug repurposing via DRUGSURV and microRNA analysis using miRDB and miRabel. MicroRNAs were also screened for clinical relevance using OncomiR. Forty genes were consistently correlated with PDCD1/CD274 across multiple cancers, with the cancers themselves exhibiting a differential role for the correlated genes in terms of patient survival. Esophageal and renal cancers in particular stood out in this regard as having a unique survival profile. Forty-nine putative microRNAs were identified as being linked to the PDCD1/CD274 network, which were taken forward and further assessed for clinical relevance using OncomiR and previously published literature. One hundred and thirty significant survival associations for 46 microRNAs across fourteen groups of cancers were identified. Finally, a total of 23 putative repurposed drugs targeting multiple components of the PDCD1/CD274 network were identified, which may represent immunotherapeutic adjuvants. Taken together, these results shed light on the varying PDCD1/CD274 networks between individual cancers and signpost a need for more cancer-specific investigations and treatments.


Assuntos
Antígeno B7-H1/genética , Neoplasias/genética , Receptor de Morte Celular Programada 1/genética , Biologia Computacional/métodos , Regulação Neoplásica da Expressão Gênica/genética , Humanos , MicroRNAs/genética
5.
PLoS One ; 12(6): e0178606, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-28582465

RESUMO

Glucocorticoids (GCs) and topoisomerase II inhibitors are used to treat acute lymphoblastic leukaemia (ALL) as they induce death in lymphoid cells through the glucocorticoid receptor (GR) and p53 respectively. Mechanisms underlying ALL cell death and the contribution of the bone marrow microenvironment to drug response/resistance remain unclear. The role of the microenvironment and the identification of chemoresistance determinants were studied by transcriptomic analysis in ALL cells treated with Dexamethasone (Dex), and Etoposide (Etop) grown in the presence or absence of bone marrow conditioned media (CM). The necroptotic (RIPK1) and the apoptotic (caspase-8/3) markers were downregulated by CM, whereas the inhibitory effects of chemotherapy on the autophagy marker Beclin-1 (BECN1) were reduced suggesting CM exerts cytoprotective effects. GCs upregulated the RIPK1 ubiquitinating factor BIRC3 (cIAP2), in GC-sensitive (CEM-C7-14) but not in resistant (CEM-C1-15) cells. In addition, CM selectively affected GR phosphorylation in a site and cell-specific manner. GR is recruited to RIPK1, BECN1 and BIRC3 promoters in the sensitive but not in the resistant cells with phosphorylated GR forms being generally less recruited in the presence of hormone. FACS analysis and caspase-8 assays demonstrated that CM promoted a pro-survival trend. High molecular weight proteins reacting with the RIPK1 antibody were modified upon incubation with the BIRC3 inhibitor AT406 in CEM-C7-14 cells suggesting that they represent ubiquitinated forms of RIPK1. Our data suggest that there is a correlation between microenvironment-induced ALL proliferation and altered response to chemotherapy.


Assuntos
Antineoplásicos/farmacologia , Resistencia a Medicamentos Antineoplásicos/genética , Regulação Neoplásica da Expressão Gênica , Glucocorticoides/farmacologia , Inibidores da Topoisomerase II/farmacologia , Microambiente Tumoral/efeitos dos fármacos , Apoptose/efeitos dos fármacos , Azocinas/farmacologia , Proteína 3 com Repetições IAP de Baculovírus , Proteína Beclina-1/genética , Proteína Beclina-1/metabolismo , Compostos Benzidrílicos/farmacologia , Células da Medula Óssea/metabolismo , Células da Medula Óssea/patologia , Caspase 3/genética , Caspase 3/metabolismo , Caspase 8/genética , Caspase 8/metabolismo , Linhagem Celular , Linhagem Celular Tumoral , Meios de Cultivo Condicionados/farmacologia , Dexametasona/farmacologia , Etoposídeo/farmacologia , Humanos , Proteínas Inibidoras de Apoptose/antagonistas & inibidores , Proteínas Inibidoras de Apoptose/genética , Proteínas Inibidoras de Apoptose/metabolismo , Células K562 , Necrose/induzido quimicamente , Necrose/genética , Necrose/metabolismo , Necrose/patologia , Fosforilação/efeitos dos fármacos , Proteína Serina-Treonina Quinases de Interação com Receptores/genética , Proteína Serina-Treonina Quinases de Interação com Receptores/metabolismo , Receptores de Glucocorticoides/antagonistas & inibidores , Receptores de Glucocorticoides/genética , Receptores de Glucocorticoides/metabolismo , Transdução de Sinais , Transcriptoma , Microambiente Tumoral/genética , Ubiquitina-Proteína Ligases/antagonistas & inibidores , Ubiquitina-Proteína Ligases/genética , Ubiquitina-Proteína Ligases/metabolismo
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