Dataset Information

A novel recurrence-associated metabolic prognostic model for risk stratification and therapeutic response prediction in patients with stage I lung adenocarcinoma.

ABSTRACT:

Objective

The proportion of patients with stage I lung adenocarcinoma (LUAD) has dramatically increased with the prevalence of low-dose computed tomography use for screening. Up to 30% of patients with stage I LUAD experience recurrence within 5 years after curative surgery. A robust risk stratification tool is urgently needed to identify patients who might benefit from adjuvant treatment.

Methods

In this first investigation of the relationship between metabolic reprogramming and recurrence in stage I LUAD, we developed a recurrence-associated metabolic signature (RAMS). This RAMS was based on metabolism-associated genes to predict cancer relapse and overall prognoses of patients with stage I LUAD. The clinical significance and immune landscapes of the signature were comprehensively analyzed.

Results

Based on a gene expression profile from the GSE31210 database, functional enrichment analysis revealed a significant difference in metabolic reprogramming that distinguished patients with stage I LUAD with relapse from those without relapse. We then identified a metabolic signature (i.e., RAMS) represented by 2 genes (ACADM and RPS8) significantly related to recurrence-free survival and overall survival times of patients with stage I LUAD using transcriptome data analysis of a training set. The training set was well validated in a test set. The discriminatory power of the 2 gene metabolic signature was further validated using protein values in an additional independent cohort. The results indicated a clear association between a high risk score and a very poor patient prognosis. Stratification analysis and multivariate Cox regression analysis showed that the RAMS was an independent prognostic factor. We also found that the risk score was positively correlated with inflammatory response, the antigen-presenting process, and the expression levels of many immunosuppressive checkpoint molecules (e.g., PD-L1, PD-L2, B7-H3, galectin-9, and FGL-1). These results suggested that high risk patients had immune response suppression. Further analysis revealed that anti-PD-1/PD-L1 immunotherapy did not have significant benefits for high risk patients. However, the patients could respond better to chemotherapy.

Conclusions

This study is the first to highlight the relationship between metabolic reprogramming and recurrence in stage I LUAD, and is the first to also develop a clinically feasible signature. This signature may be a powerful prognostic tool and help further optimize the cancer therapy paradigm.

SUBMITTER: Liu C

PROVIDER: S-EPMC8330534 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectivesSurgery with curative intent is the standard treatment for stage I lung adenocarcinoma. However, disease recurrence occurs in a third of patients. Prognostic biomarkers are needed to improve postoperative management. Here, we evaluate the utility of Homeobox A9 (HOXA9) promoter methylation, alone or in combination with Blood Vessel Invasion (BVI) assessment, for prognostic stratification of stage I lung adenocarcinoma patients.Materials and methodsWe developed a Droplet Digital PCR (ddPCR) assay to measure HOXA9 promoter methylation in formalin-fixed paraffin-embedded (FFPE) biospecimens generated during routine pathology. The prognostic value of HOXA9 promoter methylation and BVI, alone and in combination, was evaluated by Kaplan-Meier survival and Cox regression analyses in a cohort of 177 stage I lung adenocarcinoma patients from the NCI-MD study.ResultsThe ddPCR assay showed linearity, sensitivity and specificity for measuring HOXA9 promoter methylation down to 0.1% methylated DNA input. The HOXA9 promoter was methylated de novo in FFPE tumors (P < 0.0001). High methylation was independently associated with worse cancer-specific survival (Hazard Ratio [HR], 3.37; P = 0.0002) and identified high-risk stage IA and IB patients. Addition of this molecular marker improved a risk model comprised of clinical and pathologic parameters (age, gender, race, stage, and smoking history; nested likelihood ratio test; P = 0.0004) and increased the C-index from 0.60 (95% CI 0.51-0.69) to 0.68 (0.60-0.76). High methylation tumors displayed high frequency of TP53 mutations and other molecular characteristics associated with aggressiveness. BVI was independently associated with poor outcome (HR, 2.62; P = 0.054). A score that combined BVI with HOXA9 promoter methylation further stratified high-risk patients (trend P = 0.0001 comparing 0, 1 or 2 positive markers).ConclusionsddPCR can be used to quantify HOXA9 promoter methylation in FFPE samples. Alone or combined with BVI in a prognostic classifier, HOXA9 promoter methylation could potentially inform the clinical management of patients with early-stage lung adenocarcinoma.

Project description:Each of the pathological stages (I-IIIa) of surgically resected non-small-cell lung cancer has hidden biological heterogeneity, manifested as heterogeneous outcomes within each stage. Thus, the finding of robust and precise molecular classifiers with which to assess individual patient risk is an unmet medical need. Here, we identified and validated the clinical utility of a new prognostic signature based on three proteins (BRCA1, QKI, and SLC2A1) to stratify early-stage lung adenocarcinoma patients according to their risk of recurrence or death. Patients were staged according to the new International Association for the Study of Lung Cancer (IASLC) staging criteria (8th edition, 2018). A test cohort (n = 239) was used to assess the value of this new prognostic index (PI) based on the three proteins. The prognostic signature was developed by Cox regression with the use of stringent statistical criteria (TRIPOD: Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis). The model resulted in a highly significant predictor of 5-year outcome for disease-free survival (p < 0.001) and overall survival (p < 0.001). The prognostic ability of the model was externally validated in an independent multi-institutional cohort of patients (n = 114, p = 0.021). We also demonstrated that this molecular classifier adds relevant information to the gold standard TNM-based pathological staging, with a highly significant improvement of the likelihood ratio. We subsequently developed a combined PI including both the molecular and the pathological data that improved the risk stratification in both cohorts (p ≤ 0.001). Moreover, the signature may help to select stage I-IIA patients who might benefit from adjuvant chemotherapy. In summary, this protein-based signature accurately identifies those patients with a high risk of recurrence and death, and adds further prognostic information to the TNM-based clinical staging, even when the new IASLC 8th edition staging criteria are applied. More importantly, it may be a valuable tool for selecting patients for adjuvant therapy. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.