Immune cell infiltration pattern in non-small cell lung cancer PDX models is a model immanent feature and correlates with a distinct molecular and phenotypic make-up

Oswald, Eva; Bug, Daniel; Grote, Anne; Lashuk, Kanstantsin; Bouteldja, Nassim; Lenhard, Dorothée; Löhr, Anne; Behnke, Anke; Knauff, Volker; Edinger, Anna; Klingner, Kerstin; Gaedicke, Simone; Niedermann, Gabriele; Merhof, Dorit; Feuerhake, Friedrich; Schueler, Julia

doi:10.1136/jitc-2021-004412

Cited by 6 publications

(11 citation statements)

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“…Evidence shows that the tumor microenvironment significantly affects tumor diagnosis, survival outcomes, and clinical treatment sensitivity (21,23,(33)(34)(35). In recent years, related immunological studies have found that immune cell infiltration plays a key role in the tumor microenvironment in the formation, occurrence and development (31,(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47). The most concerned are the immune checkpoint protein PD-1 and its ligands PD-L1 and PDCD1LG2, tumor transforming growth factor B1 (TGFB1) and its receptors TGFB1R (48)(49)(50)(51)(52)(53)(54).…”

Section: Introductionmentioning

confidence: 99%

Cuproptosis key gene FDX1 is a prognostic biomarker and associated with immune infiltration in glioma

Zhou

Zhang

et al. 2022

Front. Med.

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Recent studies have found that the protein encoded by the FDX1 gene is involved in mediating Cuproptosis as a regulator of protein lipoylation and related to immune response process of tumors. However, the specific biological function of FDX1 in glioma is currently unclear. To explore the potential function of FDX1, this study explored the correlation between the expression of FDX1 in cancers and survival prognosis by analyzing the public databases of GEPIA and Cbioportal. Immune infiltration was analyzed by the TIMER2.0 database in tumors. The possible biological processes and functions of FDX1-related in glioma were annotated through gene enrichment. Relationship between Cuproptosis and autophagy was explored through gene co-expression studies. Summary and conclusions of this study: (1) FDX1 is highly expressed in gliomas and associated with poor prognosis in low-grade gliomas (LGG). (2) Gene annotation indicates that FDX1 is mainly involved in the tumor protein lipoylation and cell death. (3) FDX1 expression is positively correlated with the infiltration of immune cells. (4) LIPT2 and NNAT, two other genes involved in lipoylation, may be unidentified marker gene for Cuproptosis. And the Cuproptosis genes related to FDX1 were positively correlated with the expression of autophagy marker genes Atg5, Atg12, and BECN-1. This evidence suggests that there may be some interaction between FDX1 mediated Cuproptosis and autophagy. In summary, FDX1 may serve as a potential immunotherapy target and prognostic marker for Glioma.

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Section: Introductionmentioning

confidence: 99%

Cuproptosis key gene FDX1 is a prognostic biomarker and associated with immune infiltration in glioma

Zhou

Zhang

et al. 2022

Front. Med.

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“…Glycosylation can affect the structure and function of PD‐L1: N‐linked glycosylation of PD‐L1 maintains its protein stability and promotes evasion of T‐cell immunity 14 . PCa is an immunologically “cold” tumor with low immune cell infiltration, and the role of PD‐L1 in PCa is controversial 39,40 . Therefore, the glycosylation signature developed in the present study could have important implications for immunotherapy of PCa, although the mechanism needs to be further explored.…”

Section: Discussionmentioning

confidence: 95%

“…14 PCa is an immunologically "cold" tumor with low immune cell infiltration, and the role of PD-L1 in PCa is controversial. 39,40 Therefore, the glycosylation signature developed in the present study could have important implications for immunotherapy of PCa, although the mechanism needs to be further explored.…”

Section: Discussionmentioning

confidence: 98%

A glycosylation signature for predicting the progression and immunotherapeutic response of prostate cancer

Sun

Fan

Min

et al. 2023

The Journal of Gene Medicine

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Background Glycosylation has been proposed as a new cancer hallmark. However, focusing on specific glycans or glycoproteins may lose much data relevant to glycosylation alterations. The present study aimed to first comprehensively investigate the expression and mutation profiles of glycosylation‐related genes (GRgenes) in prostate cancer (PCa) and then develop a glycosylation signature and explore its role in predicting the progression and immunotherapeutic response of PCa. Methods Based on The Cancer Genome Atlas database, we comprehensively screened potential prognostic GRgenes and analyzed their expression and mutation profiles in PCa. Through consensus clustering analysis, the study cohort was classified to investigate the effect of glycosylation patterns on the prognosis of PCa. Next, we developed a glycosylation signature (i.e., the glycosylation score [Gly_score]) using the differentially expressed genes between glycosylation pattern groups and evaluated its role in predicting the progression and immunotherapeutic response of PCa. Results We identified two distinct glycosylation patterns in PCa and found that GRgene expression patterns rather than mutations are associated with the prognosis of PCa. The high Gly_score group had significantly shorter progression‐free survival, lower PD‐L1 levels, less infiltration of immune cells and lower immunophenoscores than the low Gly_score group. When the patients were grouped according to both the Gly_score and PD‐L1 level, patients with a combination of low Gly_score and low PD‐L1 expression had the best survival outcomes. Conclusions In the present study, for the first time, we developed a glycosylation signature and demonstrated that the proposed glycosylation signature is a promising tool for predicting the prognosis and immunotherapeutic response of PCa.

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“…For example, the alterations in proximal tubule (PT) cells and renal interstitial fibroblasts can reflect the progression of chronic kidney disease [76,77]. Changes in tumor-infiltrating lymphocytes proportions can reflect the clinical efficacy of cancer immunotherapy [78–80]. What’s more, cell type deconvolution provides an important tool for gaining in-depth insights into the pathogenesis of diseases and evaluating drug efficacy during the drug development process [81].…”

Section: Resultsmentioning

confidence: 99%

Deconer: A comprehensive and systematic evaluation toolkit for reference-based cell type deconvolution algorithms using gene expression data

Zhang,

Liu

et al. 2023

Preprint

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In recent years, computational methods for quantifying cell type proportions from transcription data have gained significant attention, particularly those reference-based methods which have demonstrated high accuracy. However, there is currently a lack of comprehensive evaluation and guidance for available reference-based deconvolution methods in cell proportion deconvolution analysis. In this study, we propose a comprehensive evaluation toolkit, called Deconer, specifically designed for reference-based deconvolution methods. Deconer provides various simulated and real gene expression datasets, including both bulk and single-cell sequencing data, and offers multiple visualization interfaces. By utilizing Deconer, we conducted systematic comparisons of 14 reference-based deconvolution methods from different perspectives, including method robustness, accuracy in deconvolving rare components, signature gene selection, and building external reference. We also performed an in-depth analysis of the application scenarios and challenges in cell proportion deconvolution methods. Finally, we provided constructive suggestions for users in selecting and developing cell proportion deconvolution algorithms. This work presents novel insights to researchers, assisting them in choosing appropriate toolkits, applying solutions in clinical contexts, and advancing the development of deconvolution tools tailored to gene expression data.

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Immune cell infiltration pattern in non-small cell lung cancer PDX models is a model immanent feature and correlates with a distinct molecular and phenotypic make-up

Cited by 6 publications

References 50 publications

Cuproptosis key gene FDX1 is a prognostic biomarker and associated with immune infiltration in glioma

Cuproptosis key gene FDX1 is a prognostic biomarker and associated with immune infiltration in glioma

A glycosylation signature for predicting the progression and immunotherapeutic response of prostate cancer

Deconer: A comprehensive and systematic evaluation toolkit for reference-based cell type deconvolution algorithms using gene expression data

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