Stratification of resectable lung adenocarcinoma by molecular and pathological risk estimators

Development and validation of a robust immune-related prognostic signature in early-stage lung adenocarcinoma

Background

The incidence of stage I and stage II lung adenocarcinoma (LUAD) is likely to increase with the introduction of annual screening programs for high-risk individuals. We aimed to identify a reliable prognostic signature with immune-related genes that can predict prognosis and help making individualized management for patients with early-stage LUAD.

Methods

The public LUAD cohorts were obtained from the large-scale databases including 4 microarray data sets from the Gene Expression Omnibus (GEO) and 1 RNA-seq data set from The Cancer Genome Atlas (TCGA) LUAD cohort. Only early-stage patients with clinical information were included. Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set). The prognostic signature was developed using the overlapped prognostic genes based on a risk score method. Kaplan–Meier curve with log-rank test and time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic value and performance of this signature, respectively. Furthermore, the robustness of this prognostic signature was further validated in TCGA-LUAD and GSE72094 cohorts.

Results

A prognostic immune signature consisting of 21 immune-related genes was constructed using the training set. The prognostic signature significantly stratified patients into high- and low-risk groups in terms of overall survival (OS) in training data set, including GSE30219 (HR = 4.31, 95% CI 2.29–8.11; P = 6.16E−06), GSE31210 (HR = 11.91, 95% CI 4.15–34.19; P = 4.10E−06), GSE50081 (HR = 3.63, 95% CI 1.90–6.95; P = 9.95E−05), the combined data set (HR = 3.15, 95% CI 1.98–5.02; P = 1.26E−06) and the validation data set, including TCGA-LUAD (HR = 2.16, 95% CI 1.49–3.13; P = 4.54E−05) and GSE72094 (HR = 2.95, 95% CI 1.86–4.70; P = 4.79E−06). Multivariate cox regression analysis demonstrated that the 21-gene signature could serve as an independent prognostic factor for OS after adjusting for other clinical factors. ROC curves revealed that the immune signature achieved good performance in predicting OS for early-stage LUAD. Several biological processes, including regulation of immune effector process, were enriched in the immune signature. Moreover, the combination of the signature with tumor stage showed more precise classification for prognosis prediction and treatment design.

Conclusions

Our study proposed a robust immune-related prognostic signature for estimating overall survival in early-stage LUAD, which may be contributed to make more accurate survival risk stratification and individualized clinical management for patients with early-stage LUAD.

A Grading System for Invasive Pulmonary Adenocarcinoma: A Proposal From the International Association for the Study of Lung Cancer Pathology Committee

INTRODUCTION

A grading system for pulmonary adenocarcinoma has not been established. The International Association for the Study of Lung Cancer pathology panel evaluated a set of histologic criteria associated with prognosis aimed at establishing a grading system for invasive pulmonary adenocarcinoma.

METHODS

A multi-institutional study involving multiple cohorts of invasive pulmonary adenocarcinomas was conducted. A cohort of 284 stage I pulmonary adenocarcinomas was used as a training set to identify histologic features associated with patient outcomes (recurrence-free survival [RFS] and overall survival [OS]). Receiver operating characteristic curve analysis was used to select the best model, which was validated (n = 212) and tested (n = 300, including stage I-III) in independent cohorts. Reproducibility of the model was assessed using kappa statistics.

RESULTS

The best model (area under the receiver operating characteristic curve [AUC] = 0.749 for RFS and 0.787 for OS) was composed of a combination of predominant plus high-grade histologic pattern with a cutoff of 20% for the latter. The model consists of the following: grade 1, lepidic predominant tumor; grade 2, acinar or papillary predominant tumor, both with no or less than 20% of high-grade patterns; and grade 3, any tumor with 20% or more of high-grade patterns (solid, micropapillary, or complex gland). Similar results were seen in the validation (AUC = 0.732 for RFS and 0.787 for OS) and test cohorts (AUC = 0.690 for RFS and 0.743 for OS), confirming the predictive value of the model. Interobserver reproducibility revealed good agreement (k = 0.617).

CONCLUSIONS

A grading system based on the predominant and high-grade patterns is practical and prognostic for invasive pulmonary adenocarcinoma.

Establishing a Dedicated Lung Cancer Biobank at the University Center Hospital of Nice (France). Why and How?

Lung cancer is the major cause of death from cancer in the world and its incidence is increasing in women. Despite the progress made in developing immunotherapies and therapies targeting genomic alterations, improvement in the survival rate of advanced stages or metastatic patients remains low. Thus, urgent development of effective therapeutic molecules is needed. The discovery of novel therapeutic targets and their validation requires high quality biological material and associated clinical data. With this aim, we established a biobank dedicated to lung cancers. We describe here our strategy and the indicators used and, through an overall assessment, present the strengths, weaknesses, opportunities and associated risks of this biobank.

A novel protein-based prognostic signature improves risk stratification to guide clinical management in early-stage lung adenocarcinoma patients

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.

Ensuring the Safety and Security of Frozen Lung Cancer Tissue Collections through the Encapsulation of Dried DNA

Collected specimens for research purposes may or may not be made available depending on their scarcity and/or on the project needs. Their protection against degradation or in the event of an incident is pivotal. Duplication and storage on a different site is the best way to assure their sustainability. The conservation of samples at room temperature (RT) by duplication can facilitate their protection. We describe a security system for the collection of non-small cell lung cancers (NSCLC) stored in the biobank of the Nice Hospital Center, France, by duplication and conservation of lyophilized (dried), encapsulated DNA kept at RT. Therefore, three frozen tissue collections from non-smoking, early stage and sarcomatoid carcinoma NSCLC patients were selected for this study. DNA was extracted, lyophilized and encapsulated at RT under anoxic conditions using the DNAshell technology. In total, 1974 samples from 987 patients were encapsulated. Six and two capsules from each sample were stored in the biobanks of the Nice and Grenoble (France) Hospitals, respectively. In conclusion, DNA maintained at RT allows for the conservation, duplication and durability of collections of interest stored in biobanks. This is a low-cost and safe technology that requires a limited amount of space and has a low environmental impact.

Cell cycle progression score is a marker for five-year lung cancer-specific mortality risk in patients with resected stage I lung adenocarcinoma

Purpose

The goals of our study were (a) to validate a molecular expression signature (cell cycle progression [CCP] score and molecular prognostic score [mPS; combination of CCP and pathological stage {IA or IB}]) that identifies stage I lung adenocarcinoma (ADC) patients with a higher risk of cancer-specific death following curative-intent surgical resection, and (b) to determine whether mPS stratifies prognosis within stage I lung ADC histological subtypes.

Methods

Formalin-fixed, paraffin-embedded stage I lung ADC tumor samples from 1200 patients were analyzed for 31 proliferation genes by quantitative RT-PCR. Prognostic discrimination of CCP score and mPS was assessed by Cox proportional hazards regression, using 5-year lung cancer–specific mortality as the primary outcome.

Results

In multivariable analysis, CCP score was a prognostic marker for 5-year lung cancer–specific mortality (HR=1.6 per interquartile range; 95% CI, 1.14–2.24; P=0.006). In a multivariable model that included mPS instead of CCP, mPS was a significant prognostic marker for 5-year lung cancer–specific mortality (HR=1.77; 95% CI, 1.18–2.66; P=0.006). Five-year lung cancer–specific survival differed between low-risk and high-risk mPS groups (96% vs 81%; P<0.001). In patients with intermediate-grade lung ADC of acinar and papillary subtypes, high mPS was associated with worse 5-year lung cancer–specific survival (P<0.001 and 0.015, respectively), compared with low mPS.

Conclusion

This study validates CCP score and mPS as independent prognostic markers for lung cancer–specific mortality and provides quantitative risk assessment, independent of known high-risk features, for stage I lung ADC patients treated with surgery alone.

Prognostic and predictive biomarkers post curative intent therapy

Large-scale screening trials have demonstrated that early diagnosis of lung cancer results in a significant reduction in lung cancer mortality. Despite improvements in detecting more lung cancers at early stages, the 5-year survival rates of lung cancers diagnosed before widespread disease is only 30-50%. High rates of recurrence, despite early diagnosis, suggest the need to improve treatment strategies based on the likelihood of recurrence in patient subsets, as well as explore the role of predictive markers for therapy selection in the adjuvant setting. In the era of personalized medicine, there have been a wide array of molecular alterations and signatures studied for their potential prognostic and predictive utility, however most have failed to translate into clinical tools. This review will discuss progress made in clinical management of lung cancer, and recent progress in the development of patient selection tools for the refinement of early stage lung cancers.

Prediction of distant recurrence in resected stage I and II lung adenocarcinoma

OBJECTIVES

Optimal procedures for adjuvant treatment and post-surgical surveillance of resected non-small-cell lung cancer remain under discussion. Pathological features are the main determinant of follow-up therapy but have limited ability to identify patients at risk of recurrence. Increasingly, molecular markers are incorporated into clinical decision-making, including measures of tumor growth. The CCP score is a quantitative, molecular measure of proliferation derived from the RNA expression of 31 cell cycle genes and a component of the molecular prognostic score (mPS). The mPS score is a linear combination of CCP score and pathological stage. CCP score and mPS are independent predictors of survival in resected lung adenocarcinoma.

MATERIALS AND METHODS

CCP scores were determined by RT-qPCR for 318 patients diagnosed with stage I-II lung adenocarcinoma. Association of mPS and CCP score with distant recurrence and lung-cancer specific survival was assessed in Cox proportional hazards regression models adjusted for age, gender, tumor size, pathological stage and pleural invasion. Distant recurrence-free survival and lung-cancer specific survival by mPS risk group were calculated by Kaplan-Meier survival analysis.

RESULTS

CCP scores were obtained for 205 stage I and 84 stage II patients. CCP score and mPS were independent markers of distant recurrence (CCP: HR 1.62, 95%CI 1.15-2.29, p=0.0055; mPS: HR 2.22, 95%CI 1.11-4.44, p=0.023). Patients with low mPS tumors were at significantly reduced risk of distant recurrence (log-rank p=4.2×10^-5). Among stage I patients, stratification by mPS identified a patient group with increased risk of distant recurrence (36%, 95%CI 28-46%, log-rank p=0.0011) CONCLUSIONS: The molecular prognostic score stratifies early-stage, resected lung cancer patients for risk of distant recurrence and could be useful to inform treatment and surveillance decisions.