Dataset Information

Landscape of Mitochondria Genome and Clinical Outcomes in Stage 1 Lung Adenocarcinoma.

ABSTRACT: Risk factors including genetic effects are still being investigated in lung adenocarcinoma (LUAD). Mitochondria play an important role in controlling imperative cellular parameters, and anomalies in mitochondrial function might be crucial for cancer development. The mitochondrial genomic aberrations found in lung adenocarcinoma and their associations with cancer development and progression are not yet clearly characterized. Here, we identified a spectrum of mitochondrial genome mutations in early-stage lung adenocarcinoma and explored their association with prognosis and clinical outcomes. Next-generation sequencing was used to reveal the mitochondrial genomes of tumor and conditionally normal adjacent tissues from 61 Stage 1 LUADs. Mitochondrial somatic mutations and clinical outcomes including relapse-free survival (RFS) were analyzed. Patients with somatic mutations in the D-loop region had longer RFS (adjusted hazard ratio, adjHR = 0.18, p = 0.027), whereas somatic mutations in mitochondrial Complex IV and Complex V genes were associated with shorter RFS (adjHR = 3.69, p = 0.012, and adjHR = 6.63, p = 0.002, respectively). The risk scores derived from mitochondrial somatic mutations were predictive of RFS (adjHR = 9.10, 95%CI: 2.93-28.32, p < 0.001). Our findings demonstrated the vulnerability of the mitochondrial genome to mutations and the potential prediction ability of somatic mutations. This research may contribute to improving molecular guidance for patient treatment in precision medicine.

SUBMITTER: Raghav L

PROVIDER: S-EPMC7140061 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Landscape of Mitochondria Genome and Clinical Outcomes in Stage 1 Lung Adenocarcinoma.

Raghav Lovely L Chang Ya-Hsuan YH Hsu Yi-Chiung YC Li Yu-Cheng YC Chen Chih-Yi CY Yang Tsung-Ying TY Chen Kun-Chieh KC Hsu Kuo-Hsuan KH Tseng Jeng-Sen JS Chuang Cheng-Yen CY Lee Mei-Hsuan MH Wang Chih-Liang CL Chen Huei-Wen HW Yu Sung-Liang SL Su Sheng-Fang SF Yuan Shin-Sheng SS Chen Jeremy J W JJW Ho Shinn-Ying SY Li Ker-Chau KC Yang Pan-Chyr PC Chang Gee-Chen GC Chen Hsuan-Yu HY

Cancers 20200323 3

Risk factors including genetic effects are still being investigated in lung adenocarcinoma (LUAD). Mitochondria play an important role in controlling imperative cellular parameters, and anomalies in mitochondrial function might be crucial for cancer development. The mitochondrial genomic aberrations found in lung adenocarcinoma and their associations with cancer development and progression are not yet clearly characterized. Here, we identified a spectrum of mitochondrial genome mutations in earl ...[more]

PMID: 32210009

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Project description:PurposeTP53 mutation, one of the most frequent mutations in early-stage lung adenocarcinoma (LUAD), triggers a series of alterations in the immune landscape, progression, and clinical outcome of early-stage LUAD. Our study was designed to unravel the effects of TP53 mutation on the immunophenotype of early-stage LUAD and formulate a TP53-associated immune prognostic model (IPM) that can estimate prognosis in early-stage LUAD patients.Materials and methodsImmune-associated differentially expressed genes (DEGs) between TP53 mutated (TP53MUT ) and TP53 wild-type (TP53WT ) early-stage LUAD were comprehensively analyzed. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis identified the prognostic immune-associated DEGs. We constructed and validated an IPM based on the TCGA and a meta-GEO composed of GSE72094, GSE42127, and GSE31210, respectively. The CIBERSORT algorithm was analyzed for assessing the percentage of immune cell types. A nomogram model was established for clinical application.ResultsTP53 mutation occurred in approximately 50.00% of LUAD patients, stimulating a weakened immune response in early-stage LUAD. Sixty-seven immune-associated DEGs were determined between TP53WT and TP53MUT cohort. An IPM consisting of two prognostic immune-associated DEGs (risk score = 0.098 * ENTPD2 expression + 0.168 * MIF expression) was developed through 397 cases in the TCGA and further validated based on 623 patients in a meta-GEO. The IPM stratified patients into low or high risk of undesirable survival and was identified as an independent prognostic indicator in multivariate analysis (HR = 2.09, 95% CI: 1.43-3.06, p < 0.001). Increased expressions of PD-L1, CTLA-4, and TIGIT were revealed in the high-risk group. Prognostic nomogram incorporating the IPM and other clinicopathological parameters (TNM stage and age) achieved optimal predictive accuracy and clinical utility.ConclusionThe IPM based on TP53 status is a reliable and robust immune signature to identify early-stage LUAD patients with high risk of unfavorable survival.

Project description:OBJECTIVE:This study was to define preoperative predictors from radiologic findings for the pathologic risk groups based on long-term surgical outcomes, in the aim to help guide individualized patient management. METHODS:We retrospectively reviewed 321 consecutive patients with clinical stage IA lung adenocarcinoma with ground glass component on computed tomography (CT) scanning. Pathologic diagnosis for resection specimens was based on the 2011 IASLC/ATS/ERS classification of lung adenocarcinoma. Patients were classified into different pathologic risk grading groups based on their lymph node status, local regional recurrence and overall survival. Radiologic characteristics of the pulmonary nodules were re-evaluated by reconstructed three-dimension CT (3D-CT). Univariate and multivariate analysis identifies independent radiologic predictors from tumor diameter, total volume (TV), average CT value (AVG), and solid-to-tumor (S/T) ratio. Receiver operating characteristic curves (ROC) studies were carried out to determine the cutoff value(s) for the predictor(s). Univariate cox regression model was used to determine the clinical significance of the above findings. RESULTS:A total of 321 patients with clinical stage IA lung adenocarcinoma with ground glass components were included in our study. Patients were classified into two pathologic low- and high- risk groups based on their distinguished surgical outcomes. A total of 134 patients fell into the low-risk group. Univariate and multivariate analyses identified AVG (HR: 32.210, 95% CI: 3.020-79.689, P<0.001) and S/T ratio (HR: 12.212, 95% CI: 5.441-27.408, P<0.001) as independent predictors for pathologic risk grading. ROC curves studies suggested the optimal cut-off values for AVG and S/T ratio were-198 (area under the curve [AUC] 0.921), 2.9 (AUC 0.996) and 54% (AUC 0.907), respectively. The tumor diameter and TV were excluded for the low AUCs (0.778 and 0.767). Both the cutoff values of AVG and S/T ratio were correlated with pathologic risk classification (p<0.001). Univariate Cox regression model identified clinical risk classification (RR: 3.011, 95%CI: 0.796-7.882, P = 0.095) as a good predictor for recurrence-free survival (RFS) in patients with clinical stage IA lung adenocarcinoma. Statistical significance of 5-year OS and RFS was noted among clinical low-, moderate- and high-risk groups (log-rank, p = 0.024 and 0.010). CONCLUSIONS:The AVG and the S/T ratio by reconstructed 3D-CT are important preoperative radiologic predictors for pathologic risk grading. The two cutoff values of AVG and S/T ratio are recommended in decision-making for patients with clinical stage IA lung adenocarcinoma with ground glass components.

Project description:Interleukins (ILs) and interleukin receptors (ILRs) play important role in the antitumor immune response. However, the expression signature and clinical characteristics of the IL(R) family in lung adenocarcinoma (LUAD) remains unclear. The main purpose of this study was to explore the expression profile of IL(R) family genes and construct an IL(R)-based prognostic signature in LUAD. Five public datasets of 1,312 patients with LUAD were enrolled in this study. Samples from The Cancer Genome Atlas (TCGA) were used as the training set, and samples from the other four cohorts extracted from Gene Expression Omnibus (GEO) database were used as the validation set. Additionally, the profile of IL(R) family signature was explored, and the association between this signature and immunotherapy response was also analyzed. Meanwhile, the prognostic value was compared between this IL(R)-based signature and different immunotherapy markers. A signature based on five identified IL(R)s (IL7R, IL5RA, IL20RB, IL11, IL22RA1) was constructed using the TCGA dataset through univariate/multivariable Cox proportional hazards regression and least absolute shrinkage and selection operator (LASSO) Cox analysis. These cases with LUAD were stratified into high- and low-risk group according to the risk score. This signature showed a strong prognostic ability, which was verified by the five independent cohorts and clinical subtypes. The IL(R)-based models presented unique characteristics in terms of immune cell infiltration and immune inflammation profile in tumor microenvironment (TME). Biological pathway analysis confirmed that high-risk patients showed significant T- and B-cell immunosuppression and rapid tumor cell proliferation. More importantly, we researched the relationship between this IL(R)-based signature and immune checkpoints, tumor mutation burden (TMB), tumor purity and ploidy, and tumor immune dysfunction and exclusion (TIDE) score, which confirmed that this signature gave the best prognostic value. We first provided a robust prognostic IL(R)-based signature, which had the potential as a predictor for immunotherapy response to realize individualized treatment of LUAD.

Project description:Background: Image-based screening improves the detection of early-stage lung adenocarcinoma (LUAD)but also highlights the issue of high false-positive diagnoses, which puts patients at a risk of unnecessary over-treatment. Therefore, more precise discrimination criteria are required to ensure that patients with early-stage LUAD receive appropriate treatments. Methods: we integrated 158 early-stage LUAD cases from 2 independent cohorts, including 30 matched resected specimens with complete radiological and pathological information, and 128 retrospective pathological pair-samples with partial follow-up data. This integration allowed us to conduct a correlation analysis between clinical phenotype and transcriptome landscape. Immunohistochemistry was performed using tissue microarrays to examine the expression of phospholipid phosphatase 2 (PLPP2) and lipid-raft markers. Lipidomics analysis was used to determine the changes of lipid components in PLPP2-overexpressed cells. To assess the effects of PLPP2 on the malignant phenotypes of LUAD cells, we conducted mice tumor-bearing experiments and in vitro cellular experiments by knocking down PLPP2 and inhibiting lipid raft synthesis with MβCD, respectively. Results: Bioinformatics analysis indicated that the co-occurrence of lipid raft formation and rapid cell proliferation might exhibit synergistic effects in driving oncogenesis from lung preneoplasia to adenocarcinoma. The enhanced activation of the cell cycle promoted the transition from non-invasive to invasive status in early-stage LUAD, which was related to an increase in lipid rafts within LUAD cells. PLPP2 participated in lipid raft formation by altering the component contents of lipid rafts, such as esters, sphingomyelin, and sphingosine. Furthermore, elevated PLPP2 levels were identified as an independent prognostic risk factor for LUAD patients. Further results from in vivo and in vitro experiments confirmed that PLPP2 could induce excessive cell proliferation by enhancing lipid raft formation in LUAD cells. Conclusions: Our study has revealed the characteristics of gene expression profiles in early-stage LUAD patients with the different radiological and pathological subtypes, as well as deciphered transcriptomic evolution trajectory from preneoplasia to invasive LUAD. Furthermore, it suggests that PLPP2-mediated lipid raft synthesis may be a significant biological event in the initiation of early-stage LUAD, offering a potential target for more precise diagnosis and therapy in clinical settings.

Dataset Information

Landscape of Mitochondria Genome and Clinical Outcomes in Stage 1 Lung Adenocarcinoma.

Publications

Landscape of Mitochondria Genome and Clinical Outcomes in Stage 1 Lung Adenocarcinoma.

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