Evolutionary metabolic landscape from preneoplasia to invasive lung adenocarcinoma

Nie, Meng; Yao, Ke; Zhu, Xinsheng; Chen, Na; Xiao, Nan; Wang, Yi; Peng, Bo; Yao, Liang; Zhang, Peng; Hu, Zeping

doi:10.1038/s41467-021-26685-y

Cited by 60 publications

(73 citation statements)

References 66 publications

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“…We showed that the metabolism pathway was shared by ACSL5 , FUT2 , and SERINC2 . A recent study [ 37 ] has reported that the metabolic pathways emerge in premalignant lesions and that metabolite-based clustering showed different survival outcomes, possibly facilitating early detection of high-risk cancers. Our results revealed the candidate genes linked to the evidence that metabolic pathways emerge in premalignant lesions.…”

Section: Discussionmentioning

confidence: 99%

Gene Expression Profiles of Multiple Synchronous Lesions in Lung Adenocarcinoma

Lim

Han

Park

et al. 2021

Cells

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Many studies support a stepwise continuum of morphologic changes between atypical adenomatous hyperplasia (AAH) and lung adenocarcinoma (ADC). Here we characterized gene expression patterns and the association of differentially expressed genes and immune tumor microenvironment behaviors in AAH to ADC during ADC development. Tumor tissues from nine patients with ADC and synchronous multiple ground glass nodules/lesions (GGN/Ls) were analyzed using RNA sequencing. Using clustering, we identified genes differentially and sequentially expressed in AAH and ADC compared to normal tissues. Functional enrichment analysis using gene ontology terms was performed, and the fraction of immune cell types was estimated. We identified up-regulated genes (ACSL5 and SERINC2) with a stepwise change of expression from AAH to ADC and validated those expressions by quantitative PCR and immunohistochemistry. The immune cell profiles revealed increased B cell activities and decreased natural killer cell activities in AAH and ADC. A stepwise change of differential expression during ADC development revealed potential effects on immune function in synchronous precursors and in tumor lesions in patients with lung cancer.

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Section: Discussionmentioning

confidence: 99%

Gene Expression Profiles of Multiple Synchronous Lesions in Lung Adenocarcinoma

Lim

Han

Park

et al. 2021

Cells

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“…These metabolic changes are not homogeneous in tumors; there are differences between types of cancer originating in different tissues and within the same tissue, such as breast cancer, where metabolic alterations have different nuances depending on the intrinsic subtype of breast cancer and the degree of differentiation [ 300 ]. Additionally, in vivo studies reveal the metabolic heterogeneity of cancer throughout tumor progression [ 11 , 301 ], whereby they are more dependent on OXPHOS metabolism in more advanced stages [ 91 ]. Indeed, OXPHOS inhibitors have been proposed for use in treating cancer and are undergoing clinical trials at the time of writing [ 302 ].…”

Section: Discussionmentioning

confidence: 99%

Pathophysiological Integration of Metabolic Reprogramming in Breast Cancer

Corchado-Cobos

García-Sancha

Mendiburu-Eliçabe

et al. 2022

Cancers

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Metabolic changes that facilitate tumor growth are one of the hallmarks of cancer. The triggers of these metabolic changes are located in the tumor parenchymal cells, where oncogenic mutations induce an imperative need to proliferate and cause tumor initiation and progression. Cancer cells undergo significant metabolic reorganization during disease progression that is tailored to their energy demands and fluctuating environmental conditions. Oxidative stress plays an essential role as a trigger under such conditions. These metabolic changes are the consequence of the interaction between tumor cells and stromal myofibroblasts. The metabolic changes in tumor cells include protein anabolism and the synthesis of cell membranes and nucleic acids, which all facilitate cell proliferation. They are linked to catabolism and autophagy in stromal myofibroblasts, causing the release of nutrients for the cells of the tumor parenchyma. Metabolic changes lead to an interstitium deficient in nutrients, such as glucose and amino acids, and acidification by lactic acid. Together with hypoxia, they produce functional changes in other cells of the tumor stroma, such as many immune subpopulations and endothelial cells, which lead to tumor growth. Thus, immune cells favor tissue growth through changes in immunosuppression. This review considers some of the metabolic changes described in breast cancer.

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“…Pathway enrichment analysis displayed significant upregulation of bile acid metabolism, K-RAS signal, and fatty acid metabolism in high-IRS groups. Previous studies already showed that bile acid metabolism and fatty acid metabolism contributed to the tumor invasion (24,25). Oncogenic K-RAS signaling that has been studied extensively promotes tumor progression in several cancers.…”

Section: Discussionmentioning

confidence: 99%

Exploration of Novel Immunological Terms in Lung Cancer With Large Populations: Implications for Immunotherapy

et al. 2022

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BackgroundIdeal biomarkers to predict the response to immunotherapy in lung cancer are still lacking. Therefore, there is a need to explore effective biomarkers in large populations.ObjectiveThe objective of this study is to explore novel immunological classifications that are associated with immunotherapy response through the ssGSEA algorithm.MethodsSix independent lung cancer cohorts were collected for analysis including The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and the EMBL-EBI database. The ssGSEA algorithm was performed to extract immune terms. Then, TCGA samples were involved as a training group and other cohorts were used as a validation group. After LASSO and Cox regression, prognostic associated immune terms were extracted and an immune-related risk score (IRS) signature was constructed. Furthermore, the association between IRS signature and clinical data, genome features, stemness indices analysis, tumor immune microenvironment, immunotherapy efficiency, and targeted therapy response was also investigated.ResultsA total of 1,997 samples were enrolled in this study including six large lung cancer cohorts. Fifty-four immune terms were calculated through the ssGSEA algorithm in combined cohorts. Then, a nine-immune-term risk score model named IRS signature was established to predict the prognosis in combined cohorts. We classified patients into high-risk and low-risk subgroups according to the cutoff point. Subsequently, analysis of clinical data and genome features indicated that the patients in the high-IRS group tend to have advanced clinical features (clinical stage and T classification), as well as a higher level of copy number variation burden, higher tumor burden mutation, and higher tumor stemness indices. Immune landscape analysis demonstrated that high-IRS groups exhibited lower immune cell infiltration and immune-suppressive state. More importantly, the predicted result of the Tumor Immune Dysfunction and Exclusion analysis showed that high-IRS groups might be more insensitive to immunotherapy. Meanwhile, we have also identified that high-IRS groups were associated with better efficiency of several targeted drugs.ConclusionTo summarize, we identified a novel IRS model based on nine immune terms, which was quantified by the ssGSEA algorithm. This model had good efficacy in predicting overall survival and immunotherapy response in non-small cell lung cancer patients, which might be an underlying biomarker.

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Evolutionary metabolic landscape from preneoplasia to invasive lung adenocarcinoma

Cited by 60 publications

References 66 publications

Gene Expression Profiles of Multiple Synchronous Lesions in Lung Adenocarcinoma

Gene Expression Profiles of Multiple Synchronous Lesions in Lung Adenocarcinoma

Pathophysiological Integration of Metabolic Reprogramming in Breast Cancer

Exploration of Novel Immunological Terms in Lung Cancer With Large Populations: Implications for Immunotherapy

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