In silico transcriptomic mapping of integrins and immune activation in Basal-like and HER2+ breast cancer

Rojas, Katerin Ingrid; Baliu-Piqué, Mariona; Manzano, Aránzazu; Sáiz-Ladera, Cristina; García-Barberán, Vanesa; Cimas, Francisco J.; Pérez‐Segura, Pedro; Pandiella, Atanasio; Győrffy, Balázs; Ocaña, Alberto

doi:10.1007/s13402-020-00583-9

Cited by 18 publications

(15 citation statements)

References 47 publications

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“…IL10 mediates immunosuppressive signals through its interaction with IL10 receptors, leading to inhibition of synthesis of proinflammatory cytokines ( 70 )⁠. Integrins, such as ITGB2, play significant roles in cellular adhesion and cell surface signaling, and also participate in leukocyte adhesion and extravasation to inflame tissues, and mediate the formation of immunological synapses ( 71 )⁠.…”

Section: Discussionmentioning

confidence: 99%

Adrenocortical Carcinoma Steroid Profiles: In Silico Pan-Cancer Analysis of TCGA Data Uncovers Immunotherapy Targets for Potential Improved Outcomes

et al. 2021

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Despite progress in understanding the biology of adrenocortical carcinoma (ACC), treatment options have not dramatically changed in the last three decades, nor have we learned how to avoid some of its long-term side effects. Our goal was to improve the understanding of immune pathways that may include druggable targets to enhance immune responses of patients with ACC, focusing on immune evasion and the activation of immune cells against ACC. Our strategy was aimed at improving insight regarding gene expression without steroid interference. Using approaches based on high and low steroid phenotypes (HSP and LSP, respectively), we characterized immune pathways using The Cancer Genome Atlas (TCGA) ACC cohort data. Although previous studies have suggested that patients with ACC receive minimal benefit from immunotherapy, high expression of immune modulators was noted in patients with LSP, suggesting the activation of these biomarkers may be an important adjuvant therapy target after clearance of excess glucocorticoids. In addition, patients with LSP ACC had higher immune cell infiltration than patients with HSP ACC and other cancer subtypes. Our findings can be summarized as follows (1): we confirmed and improved the definition of two immune response pathways to ACC (HSP and LSP) based on in silico transcriptome analysis (2), we demonstrated the steroid profile should be considered, otherwise analyses of ACC immune characteristics can generate confounding results (3), among the overexpressed immunotherapy targets, we demonstrated that LSP was rich in PDCD1LG2 (PD-L2) and both HSP and LSP overexpressed CD276 (B7-H3), which was associated with resistance to anti-PD1 therapy and may have accounted for the modest results of previous clinical trials, and (4) identification of patients with LSP or HSP ACC can be used to help determine whether immunotherapy should be used. In conclusion, we highlighted the differences between LSP and HSP, drawing attention to potential therapeutic targets (CD276, PDCD1, and PDCD1LG2). Treatments to reduce immune evasion, as well as the use of other natural and pharmacological immune activators, should include prior pharmacological inhibition of steroidogenesis. Attempts to combine these with tumor cell proliferation inhibitors, if they do not affect cells of the immune system, may produce interesting results.

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Section: Discussionmentioning

confidence: 99%

Adrenocortical Carcinoma Steroid Profiles: In Silico Pan-Cancer Analysis of TCGA Data Uncovers Immunotherapy Targets for Potential Improved Outcomes

et al. 2021

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“…As shown in Fig. 5 C, a negative correlation existed between risk classification and the numbers of B cells ( P -value = 7.192 × 10–6), macrophages ( P -value = 0.022) and CD4+ T cells ( P -value = 0.027) [ 22 , 23 ]. To estimate whether there is a difference between the tumour immune microenvironment in the two groups of patients, 999 tumour patients were divided into a low-risk group and a high-risk group, which contained 500 and 499 patients, respectively.…”

Section: Resultsmentioning

confidence: 99%

Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer

2021

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Background Autophagy inhibits tumorigenesis by limiting inflammation. LncRNAs regulate gene expression at various levels as RNAs; thus, both autophagy and lncRNAs are closely related to the occurrence and development of tumours. Methods A total of 232 autophagy-related genes were used to construct a coexpression network to extract autophagy-related lncRNAs. A prognostic signature was constructed by multivariate regression analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was applied to analyse enrichment in cancer-related pathways. Immune infiltration analysis was used to analyse the relationship between the prognostic signature and the tumour microenvironment. Results Nine autophagy-related lncRNAs were used to construct a prognostic model for non-small-cell lung cancer. The median risk score was used to discriminate the high- and low-risk groups, and the low-risk group was found to have better survival. Because KEGG pathway analysis showed that the prognostic signature was enriched in some immune pathways, further analysis of immune infiltration was conducted, and it was found that the prognostic signature did play a unique role in the immune microenvironment. Additionally, the prognostic signature was associated with clinical factors. Conclusion We constructed a prognostic model of autophagy-related lncRNAs that can predict the prognosis of non-small-cell lung cancer.

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“…Apart from mediating cell-cell and cell-ECM adhesion, integrins also play a pivotal role in signal transduction and modulate various cellular processes ( Zhang and Wang, 2012 ). ITGA8 has been proven to be correlated with favorable outcomes in patients with basal-like and HER2+ breast cancer and colon cancer ( Gong et al, 2019 ; Rojas et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Integrative Analysis Constructs an Extracellular Matrix-Associated Gene Signature for the Prediction of Survival and Tumor Immunity in Lung Adenocarcinoma

Xiao

Huang

et al. 2022

Front. Cell Dev. Biol.

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Background: Lung adenocarcinoma (LUAD) accounts for the majority of lung cancers, and the survival of patients with advanced LUAD is poor. The extracellular matrix (ECM) is a fundamental component of the tumor microenvironment (TME) that determines the oncogenesis and antitumor immunity of solid tumors. However, the prognostic value of extracellular matrix-related genes (ERGs) in LUAD remains unexplored. Therefore, this study is aimed to explore the prognostic value of ERGs in LUAD and establish a classification system to predict the survival of patients with LUAD.Methods: LUAD samples from The Cancer Genome Atlas (TCGA) and GSE37745 were used as discovery and validation cohorts, respectively. Prognostic ERGs were identified by univariate Cox analysis and used to construct a prognostic signature by Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. The extracellular matrix-related score (ECMRS) of each patient was calculated according to the prognostic signature and used to classify patients into high- and low-risk groups. The prognostic performance of the signature was evaluated using Kaplan–Meier curves, Cox regression analyses, and ROC curves. The relationship between ECMRS and tumor immunity was determined using stepwise analyses. A nomogram based on the signature was established for the convenience of use in the clinical practice. The prognostic genes were validated in multiple databases and clinical specimens by qRT-PCR.Results: A prognostic signature based on eight ERGs (FERMT1, CTSV, CPS1, ENTPD2, SERPINB5, ITGA8, ADAMTS8, and LYPD3) was constructed. Patients with higher ECMRS had poorer survival, lower immune scores, and higher tumor purity in both the discovery and validation cohorts. The predictive power of the signature was independent of the clinicopathological parameters, and the nomogram could also predict survival precisely.Conclusions: We constructed an ECM-related gene signature which can be used to predict survival and tumor immunity in patients with LUAD. This signature can serve as a novel prognostic indicator and therapeutic target in LUAD.

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In silico transcriptomic mapping of integrins and immune activation in Basal-like and HER2+ breast cancer

Cited by 18 publications

References 47 publications

Adrenocortical Carcinoma Steroid Profiles: In Silico Pan-Cancer Analysis of TCGA Data Uncovers Immunotherapy Targets for Potential Improved Outcomes

Adrenocortical Carcinoma Steroid Profiles: In Silico Pan-Cancer Analysis of TCGA Data Uncovers Immunotherapy Targets for Potential Improved Outcomes

Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer

Integrative Analysis Constructs an Extracellular Matrix-Associated Gene Signature for the Prediction of Survival and Tumor Immunity in Lung Adenocarcinoma

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