Identification and Validation of Eight Lysosomes-Related Genes Signatures and Correlation with Immune Cell Infiltration in Lung Adenocarcinoma

Song, Dingli; Zhao, Lili; Zhao, Guang Sheng; Qiu, Hao; Ren, Hong Guang; Zhang, Boxiang

doi:10.2139/ssrn.4318397

Cited by 3 publications

(3 citation statements)

References 33 publications

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“…First, as a retrospective dataset, prospective analysis based on immune homeostasis characteristics is required. 36 Second, all expression data are derived from public datasets, and the results must be confirmed using new methods and fresh specimens. 30 Third, we assessed the potential to indirectly predict OS outcomes in LUAD, and more studies are needed to confirm this conclusion.…”

Section: Discussionmentioning

confidence: 99%

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Identification and analysis of prognostic immune cell homeostasis characteristics in lung adenocarcinoma

Sun,

Ma,

Chen

et al. 2024

Clinical Respiratory J

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BackgroundLung adenocarcinoma (LUAD) is one of the most invasive malignant tumor of the respiratory system. It is also the common pathological type leading to the death of LUAD. Maintaining the homeostasis of immune cells is an important way for anti‐tumor immunotherapy. However, the biological significance of maintaining immune homeostasis and immune therapeutic effect has not been well studied.MethodsWe constructed a diagnostic and prognostic model for LUAD based on B and T cells homeostasis‐related genes. Minimum absolute contraction and selection operator (LASSO) analysis and multivariate Cox regression are used to identify the prognostic gene signatures. Based on the overall survival time and survival status of LUAD patients, a 10‐gene prognostic model composed of ABL1, BAK1, IKBKB, PPP2R3C, CCNB2, CORO1A, FADD, P2RX7, TNFSF14, and ZC3H8 was subsequently identified as prognostic markers from The Cancer Genome Atlas (TCGA)‐LUAD to develop a prognostic signature. This study constructed a gene prognosis model based on gene expression profiles and corresponding survival information through survival analysis, as well as 1‐year, 3‐year, and 5‐year ROC curve analysis. Enrichment analysis attempted to reveal the potential mechanism of action and molecular pathway of prognostic genes. The CIBERSORT algorithm calculated the infiltration degree of 22 immune cells in each sample and compared the difference of immune cell infiltration between high‐risk group and low‐risk group. At the cellular level, PCR and CKK8 experiments were used to verify the differences in the expression of the constructed 10‐gene model and its effects on cell viability, respectively. The experimental results supported the significant biological significance and potential application value of the molecular model in the prognosis of lung cancer. Enrichment analyses showed that these genes were mainly related to lymphocyte homeostasis.ConclusionWe identified a novel immune cell homeostasis prognostic signature. Targeting these immune cell homeostasis prognostic genes may be an alternative for LUAD treatment. The reliability of the prediction model was confirmed at bioinformatics level, cellular level, and gene level.

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Section: Discussionmentioning

confidence: 99%

“…However, the study has some limitations. First, as a retrospective dataset, prospective analysis based on immune homeostasis characteristics is required 36 . Second, all expression data are derived from public datasets, and the results must be confirmed using new methods and fresh specimens 30 .…”

Section: Discussionmentioning

confidence: 99%

Identification and analysis of prognostic immune cell homeostasis characteristics in lung adenocarcinoma

Sun,

Ma,

Chen

et al. 2024

Clinical Respiratory J

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“…Furthermore, the study found that higher levels of type interferon-2 (IFN), response, HLA (human leukocyte antigen), as a major histocompatibility complex (MHC) product in humans modulate the immune response to cancer by presenting antigens. It has been shown that type-2 IFN can directly trigger apoptosis and cell cycle arrest by impairing autophagosome-lysosomal fusion in cancer cells having an important role in tumor development, which may be related to immune cells and cytokines, [12].…”

Section: Discussionmentioning

confidence: 99%

The Beneficial Relationship between Restrictive Diet and Autophagy in Preventing Cancer Cells

Udristioiu

2024

Preprint

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Background: A diet rich in red meat, and poor in fruits and vegetables, can hinder the body's ability to detoxify, therefore, an alternative vegetarian diet maintained over a certain period, determines the elimination of excess toxins and accumulated residues, helping the body to regenerate and recharge energy. Following this simple rule, there are a multitude of benefits for our health. Significance of the autophagy process: An even better regeneration of the body takes place during the black fast, in which senescent cells, (dead cells that no longer exercise any function, but instead produce inflammation in the body), are eliminated by autophagy, and in their place, the cells are stimulated stem. Aging can be associated with various pathological conditions if autophagy is not promoted by a healthy lifestyle. In elderly people, cells can show DNA mutations and accumulations of protein aggregates that impair the body's physiological processes. Several studies have shown that the activation of autophagy slows down the ageing process. Conclusions: Aging, and its associated conditions of illness, are due to genomic instability caused by DNA damage, telomere shortening and epigenome changes that modulate gene expression.

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Molecular Subtypes and Prognostic Models for Predicting Prognosis of Lung Adenocarcinoma based on MiRNA-related Genes

Wei,

Zhong,

et al. 2024

CMC

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Background: MicroRNAs (miRNAs) are crucial in cancer development and progression, and therapies targeting miRNAs demonstrate great therapeutic promise. Aim: We sought to predict the prognosis and therapeutic response of lung adenocarcinoma (LUAD) by classifying molecular subtypes and constructing a prognostic model based on miRNA-related genes. Method: This study was based on miRNA-mRNA action pairs and ceRNA networks in the Cancer Genome Atlas (TCGA) database. Three molecular subtypes were determined based on 64 miRNA-associated target genes identified in the ceRNA network. The S3 subtype had the best prognosis, and the S2 subtype had the worst prognosis. The S2 subtype had a higher tumor mutational load (TMB) and a lower immune score. The S2 subtype was more suitable for immunotherapy and sensitive to chemotherapy. The least absolute shrinkage and selection operator (LASSO) algorithm was performed to determine eight miRNA-associated target genes for the construction of prognostic models. Result: High-risk patients had a poorer prognosis, lower immune score, and lower response to immunotherapy. Robustness was confirmed in the Gene-Expression Omnibus (GEO) database cohort (GSE31210, GSE50081, and GSE37745 datasets). Overall, our study deepened the understanding of the mechanism of miRNA-related target genes in LUAD and provided new ideas for classification. Conclusion: Such miRNA-associated target gene characterization could be useful for prognostic prediction and contribute to therapeutic decision-making in LUAD.

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Identification and Validation of Eight Lysosomes-Related Genes Signatures and Correlation with Immune Cell Infiltration in Lung Adenocarcinoma

Cited by 3 publications

References 33 publications

Identification and analysis of prognostic immune cell homeostasis characteristics in lung adenocarcinoma

Identification and analysis of prognostic immune cell homeostasis characteristics in lung adenocarcinoma

The Beneficial Relationship between Restrictive Diet and Autophagy in Preventing Cancer Cells

Molecular Subtypes and Prognostic Models for Predicting Prognosis of Lung Adenocarcinoma based on MiRNA-related Genes

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