Significance of macrophage infiltration in the prognosis of lung adenocarcinoma patients evaluated by scRNA and bulkRNA analysis

Zhu, Huaiyang; Zheng, Chao‐Hui; Liu, Hongtao; Kong, Fanyun; Kong, Shuai; Chen, Feng; Tian, Yuan

doi:10.3389/fimmu.2022.1028440

Cited by 5 publications

(4 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some studies have suggested that silencing C1QTNF6 in LUAD cells can suppress the proliferation, migration and invasion of LUAD cells [ 51 ]. C1QTNF6 is a prognostic indicator for poor survival across many cancers including LUAD and one of the most relative genes of TAM [ 52 , 53 ]. However, there is still little knowledge about the function of C1QTNF6 in tumors.…”

Section: Discussionmentioning

confidence: 99%

Prediction of prognosis and immunotherapy efficacy based on metabolic landscape in lung adenocarcinoma by bulk, single-cell RNA sequencing and Mendelian randomization analyses

Liu,

Zhang,

Pang

et al. 2024

Aging

View full text Add to dashboard Cite

Immunotherapy has been a remarkable clinical advancement in cancer treatment, but only a few patients benefit from it. Metabolic reprogramming is tightly associated with immunotherapy efficacy and clinical outcomes. However, comprehensively analyzing their relationship is still lacking in lung adenocarcinoma (LUAD). Herein, we evaluated 84 metabolic pathways in TCGA-LUAD by ssGSEA. A matrix of metabolic pathway pairs was generated and a metabolic pathway-pair score (MPPS) model was established by univariable, LASSO, multivariable Cox regression analyses. The differences of metabolic reprogramming, tumor microenvironment (TME), tumor mutation burden and drug sensitivity in different MPPS groups were further explored. WGCNA and 117 machine learning algorithms were performed to identify MPPS-related genes. Single-cell RNA sequencing and in vitro experiments were used to explore the role of C1QTNF6 on TME. The results showed MPPS model accurately predicted prognosis and immunotherapy efficacy of LUAD patients regardless of sequencing platforms. High-MPPS group had worse prognosis, immunotherapy efficacy and lower immune cells infiltration, immune-related genes expression and cancer-immunity cycle scores than low-MPPS group. Seven MPPS-related genes were identified, of which C1QTNF6 was mainly expressed in fibroblasts. High C1QTNF6 expression in fibroblasts was associated with more infiltration of M2 macrophage, Treg cells and less infiltration of NK cells, memory CD8+ T cells. In vitro experiments validated silencing C1QTNF6 in fibroblasts could inhibit M2 macrophage polarization and migration. The study depicted the metabolic landscape of LUAD and constructed a MPPS model to accurately predict prognosis and immunotherapy efficacy. C1QTNF6 was a promising target to regulate M2 macrophage polarization and migration.

show abstract

Section: Discussionmentioning

confidence: 99%

Prediction of prognosis and immunotherapy efficacy based on metabolic landscape in lung adenocarcinoma by bulk, single-cell RNA sequencing and Mendelian randomization analyses

Liu,

Zhang,

Pang

et al. 2024

Aging

View full text Add to dashboard Cite

show abstract

“…In this study, we selected 14 TME-related genes, including BIRC3, CELSR2, CXCL14, IL18, KLRB1, NPY1R, PSMB8, SCUBE2, STC2, CD1C, HLA-DPB1, GIMAP2, IRF1 and TNFAIP8, all of which were implicated in tumor progression and prognosis outcomes. BIRC3 is a member of the apoptosis inhibitor (IAP) family, with pro-survival and antiapoptotic effects in cancer cells ( 48 ). BIRC3 is associated with treatment resistance in BC; IL-1 upregulates BIRC3 and generates doxorubicin resistance in BC cells ( 49 ), thus BIRC3 appears to have important roles in the TME.…”

Section: Discussionmentioning

confidence: 99%

A prognostic mathematical model based on tumor microenvironment-related genes expression for breast cancer patients

Chen,

Wang,

Zhang

et al. 2023

Front. Oncol.

View full text Add to dashboard Cite

BackgroundTumor microenvironment (TME) status is closely related to breast cancer (BC) prognosis and systemic therapeutic effects. However, to date studies have not considered the interactions of immune and stromal cells at the gene expression level in BC as a whole. Herein, we constructed a predictive model, for adjuvant decision-making, by mining TME molecular expression information related to BC patient prognosis and drug treatment sensitivity.MethodsClinical information and gene expression profiles were extracted from The Cancer Genome Atlas (TCGA), with patients divided into high- and low-score groups according to immune/stromal scores. TME-related prognostic genes were identified using Kaplan-Meier analysis, functional enrichment analysis, and protein-protein interaction (PPI) networks, and validated in the Gene Expression Omnibus (GEO) database. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to construct and verify a prognostic model based on TME-related genes. In addition, the patients’ response to chemotherapy and immunotherapy was assessed by survival outcome and immunohistochemistry (IPS). Immunohistochemistry (IHC) staining laid a solid foundation for exploring the value of novel therapeutic target genes.ResultsBy dividing patients into low- and high-risk groups, a significant distinction in overall survival was found (p < 0.05). The risk model was independent of multiple clinicopathological parameters and accurately predicted prognosis in BC patients (p < 0.05). The nomogram-integrated risk score had high prediction accuracy and applicability, when compared with simple clinicopathological features. As predicted by the risk model, regardless of the chemotherapy regimen, the survival advantage of the low-risk group was evident in those patients receiving chemotherapy (p < 0.05). However, in patients receiving anthracycline (A) therapy, outcomes were not significantly different when compared with those receiving no-A therapy (p = 0.24), suggesting these patients may omit from A-containing adjuvant chemotherapy. Our risk model also effectively predicted tumor mutation burden (TMB) and immunotherapy efficacy in BC patients (p < 0.05).ConclusionThe prognostic score model based on TME-related genes effectively predicted prognosis and chemotherapy effects in BC patients. The model provides a theoretical basis for novel driver-gene discover in BC and guides the decision-making for the adjuvant treatment of early breast cancer (eBC).

show abstract

“…Thus, the presence of M2-type TAM is associated with pro-tumour activity, whereas the presence of M1-type TAM is associated with anti-tumour activity [38]. The association between TAM and tumour prognosis has been extensively studied, with numerous studies reported in colorectal, gastric, lung, ovarian, breast, pancreatic, and other cancers [39][40][41][42][43]. There is growing evidence that ferroptosis contributes to in ammatory and immune responses.…”

Section: Discussionmentioning

confidence: 99%

Identification and verification of the effect of ferroptosis risk genes on gastric cancer cells and ferroptosis-related immune landscape analysis

Wang,

Wan,

Zhao

et al. 2023

Preprint

View full text Add to dashboard Cite

Gastric cancer is a highly prevalent tumour globally, and the prognosis after treatment is generally poor. Ferroptosis is a regulated type of programmed cell death that plays an important role in several cellular functions. This study utilised differentially expressed genes that were related to ferroptosis in gastric cancer for molecular subtyping. The genes of interest were acquired using WGCNA, and thereafter, the LASSO algorithm was employed to construct a risk prognostic model for ferroptosis-related genes(FRGs). We validated this model using PCA, ROC and other methods. We subsequently analysed immune cell infiltration amongst different ferroptosis-related risk score(FRRS) groups, and found that the high-FRRS group exhibited a markedly enhanced level of macrophage M2 content. Finally, ASCL2 was selected as the study object to validate the prognostic model of ferroptosis-related risk gene(FRRG) by screening the mutation status. The experimental results demonstrated that inhibiting ASCL2 expression in vitro resulted in a significant reduction of glutathione levels, accumulation of intracellular divalent iron ions, and mitochondrial morphological condensation and membrane thickening. In vivo, inhibition of ASCL2 expression inhibited gastric cancer cell growth and led to a significant reduction in intra-tumour glutathione. Validation and experimentation confirm that FRRS can serve as an independent prognostic factor, enabling risk stratification of patients, and that FRRGs have the potential to be used as therapeutic targets through inducing ferroptosis in cancer cells.

show abstract

Significance of macrophage infiltration in the prognosis of lung adenocarcinoma patients evaluated by scRNA and bulkRNA analysis

Cited by 5 publications

References 58 publications

Prediction of prognosis and immunotherapy efficacy based on metabolic landscape in lung adenocarcinoma by bulk, single-cell RNA sequencing and Mendelian randomization analyses

Prediction of prognosis and immunotherapy efficacy based on metabolic landscape in lung adenocarcinoma by bulk, single-cell RNA sequencing and Mendelian randomization analyses

A prognostic mathematical model based on tumor microenvironment-related genes expression for breast cancer patients

Identification and verification of the effect of ferroptosis risk genes on gastric cancer cells and ferroptosis-related immune landscape analysis

Contact Info

Product

Resources

About