Prognostic implication of EGFR gene mutations and histological classification in patients with resected stage I lung adenocarcinoma

Prognostic significance of integrating total metabolic tumor volume and EGFR mutation status in patients with lung adenocarcinoma

Background

The objective of this study was to investigate the prognostic significance of total metabolic tumor volume (TMTV) derived from baseline 18F-2-fluoro-2-deoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT), in conjunction with epidermal growth factor receptor (EGFR) mutation status, among patients with lung adenocarcinoma (LUAD).

Methods

We performed a retrospective analysis on 141 patients with LUAD (74 males, 67 females, median age 67 (range 34-86)) who underwent 18F-FDG PET/CT and had their EGFR mutation status determined. Optimal cutoff points for TMTV were determined using time-dependent receiver operating characteristic curve analysis. The survival difference was compared using Cox regression analysis and Kaplan‒Meier curves.

Results

The EGFR mutant patients (n = 79, 56.0%) exhibited significantly higher 2-year progression-free survival (PFS) and overall survival (OS) rates compared to those with EGFR wild-type (n = 62, 44.0%), with rates of 74.2% vs 69.2% (P = 0.029) and 86.1% vs 67.7% (P = 0.009), respectively. The optimal cutoff values of TMTV were 36.42 cm3 for PFS and 37.51 cm3 for OS. Patients with high TMTV exhibited significantly inferior 2-year PFS and OS, with rates of 22.4% and 38.1%, respectively, compared to those with low TMTV, who had rates of 85.8% and 95.0% (both P < 0.001). In both the EGFR mutant and wild-type groups, patients exhibiting high TMTV demonstrated significantly inferior 2-year PFS and OS compared to those with low TMTV. In multivariate analysis, EGFR mutation status (hazard ratio, HR, 0.41, 95% confidence interval, CI [0.18-0.94], P = 0.034) and TMTV (HR 8.08, 95% CI [2.34-28.0], P < 0.001) were independent prognostic factors of OS, whereas TMTV was also an independent prognosticator of PFS (HR 2.59, 95% CI [1.30-5.13], P = 0.007).

Conclusion

Our study demonstrates that the integration of TMTV on baseline 18F-FDG PET/CT with EGFR mutation status improves the accuracy of prognostic evaluation for patients with LUAD.

An association of epidermal growth factor receptor mutation subtypes with prognostic prediction and site-specific recurrence in advanced stage lung cancer patients

BACKGROUND

Concerning the different clinical behavior of epidermal growth factor receptor (EGFR) subtypes in advanced-stage lung cancer patients, the current study aimed to evaluate the clinical, pathological, and prognostic significance of EGFR mutation subtypes, and treatment response in patients with advanced-stage lung cancer.

METHODS AND RESULTS

A retrospective study enrolled a total of 346 patients with advanced-stage lung cancer tested for EGFR mutation. EGFR mutation was analyzed by amplification refractory mutation system-polymerase chain reaction (ARMS-PCR). Statistical analysis was performed using SPSS version 20.0. EGFR mutation was evident in 38% of patients with the highest prevalence of exon 19 deletions. A higher incidence of 19-deletions and 20-insertions were observed in young patients, while a higher incidence of L858R was noted in old age patients. Patients with de-novo T790M failed to improve their OS by any of the treatment modalities. Patients with de-novo T790M mutation have a higher risk of developing lung, liver, and multiple site metastases while patients with L858R mutation have a higher risk of developing brain metastasis. Additionally, patients with 19 deletion mutation did not improve their OS after receiving conventional chemotherapy hence, they demonstrate better survival only after EGFR-TKIs. Multivariate survival analysis predicted chemotherapy as an independent predictor of OS.

CONCLUSION

Besides clinicopathological and prognostic consequences of EGFR mutation and mutation subtypes, patients harboring TKI sensitive, or insensitive mutations reveal different secondary disease development and hence should be treated accordingly for better survival. Current findings may provide the basis for a better treatment strategy.

The value of prognostic and predictive parameters in early-stage lung adenocarcinomas: A comparison between biopsies and resections

INTRODUCTION

Since lung adenocarcinoma (LUAD) biopsies are usually small, it is questionable if their prognostic and predictive information is comparable to what is offered by large resection specimens. This study compares LUAD biopsies and resection specimens for their ability to provide prognostic and predictive parameters.

METHODS

We selected 187 biopsy specimens with stage I and II LUAD. In 123 cases, subsequent resection specimens were also available. All specimens were evaluated for growth pattern, nuclear grade, fibrosis, inflammation, and genomic alterations. Findings were compared using non-parametric testing for categorical variables. Model performance was assessed using the area under the curve for both biopsies and resection specimens, and overall (OS) and disease-free survival (DFS) was calculated.

RESULTS

The overall growth pattern concordance between biopsies and resections was 73.9%. The dominant growth pattern correlated with OS and DFS in resected adenocarcinomas and for high-grade growth pattern in biopsies. Multivariate analysis of biopsy specimens revealed that T2-tumors, N1-status, KRAS mutations and a lack of other driver mutations were associated with poorer survival. Model performance using clinical, histological and genetic data from biopsy specimens for predicting OS and DSF demonstrated an AUC of 0.72 and 0.69, respectively.

CONCLUSIONS

Our data demonstrated the prognostic relevance of a high-grade growth pattern in biopsy specimens of LUAD. Combining clinical, histological and genetic information in one model demonstrated a suboptimal performance for DFS prediction and good performance for OS prediction. However, for daily practice, more robust (bio)markers are required to predict prognosis and stratify patients for therapy and follow-up.

Uniportal robotic-assisted thoracoscopic surgery for early-stage lung cancer with the Da Vinci Xi: Initial experience of two cases

BACKGROUND

Minimally invasive surgery (MIS) techniques, currently considered the gold standard in the treatment of early-stage non-small cell lung cancer (NSCLC), are mainly represented by video-assisted thoracoscopic surgery (VATS), both uniportal and multiportal, and by robotic-assisted thoracoscopic surgery (RATS). While multiportal RATS has been accepted as a valid alternative to VATS, carrying the advantages of three-dimensional high-definition visualisation and improved maneuverability, very few reports exist in literature on the application of uniportal RATS (U-RATS). Therefore, we describe our initial experience with this recently developed method in the treatment of early-stage NSCLC.

MATERIALS AND METHODS

U-RATS was conducted through a single 4 cm long antero-lateral mini-thoracotomy (ALMT) in the sixth intercostal space at the mid-axillary line. Three 8 mm robotic trocars were positioned and connected, from back to front, to robotic arms as follows: 30° camera arm, robotic arm 2 (bipolar fenestrated grasper) and 1 (Maryland bipolar forceps). Assistant access was identified as the most anterior part of ALMT.

RESULTS

Case 1: an 82-year-old woman (American Society of Anaesthesiologists [ASA III]) underwent a left S6 segmentectomy for a clinical stage IA2 NSCLC, complicated by an air leak that resolved spontaneously by postoperative day three (POD 3). Case 2: a 75-year-old man (ASA III) underwent an uncomplicated right lower lobectomy for a clinical stage IA3 NSCLC. Case 1 and 2 were discharged on POD 5 and 4, respectively.

CONCLUSIONS

From what emerged in our small series, U-RATS with the Da Vinci Xi surgical system might be considered a safe, reliable, and effective alternative to other MIS techniques. Larger prospective studies are required to validate these findings.

Effect of epidermal growth factor receptor gene mutation on the prognosis of pathological stage II-IIIA (8th edition TNM classification) primary lung cancer after curative surgery

OBJECTIVES

This retrospective study aimed to elucidate the effect of epidermal growth factor receptor (EGFR) gene mutations on the prognosis of patients with pathological stage II-IIIA primary lung cancer after curative surgery.

MATERIALS AND METHODS

We enrolled 539 patients with p-stage II-IIIA (8th edition tumor-node-metastasis [TNM] classification) lung cancer who underwent curative resection at Kanagawa Cancer Center between January 2010 and December 2020 and whose tumors were tested for EGFR mutations. Relapse-free survival (RFS) and overall survival (OS) of patients with EGFR-mutant lung cancer (Mt, n = 126) including EGFR exon 21 L858R point mutation and EGFR exon 19 deletion mutation and EGFR mutation-wild lung cancer (Wt, n = 413) were analyzed using Kaplan-Meier curves and compared using a log-rank test. Cox regression analysis was performed to evaluate the effects of EGFR gene mutations on RFS and OS at each stage.

RESULTS

There were 56/256 patients with p-stage II EGFR-Mt/Wt and 70/157 patients with p-stage IIIA EGFR-Mt/Wt. The 5-year RFS rate of patients with EGFR-Mt/Wt was 46.6%/52.0% (p = 0.787) for p-stage II and 17.4%/29.7% (p = 0.929) for p-stage IIIA. The 5-year OS rate was 92.0%/65.7% (p = 0.001) for p-stage II and 56.0%/39.3% (p = 0.016) for p-stage IIIA. EGFR-Mt was not an independent prognostic factor for OS of patients with p-stage IIIA lung cancer (hazard ratio [HR], 0.95; 95% confidence interval [CI], 0.51-1.76; p = 0.872); however, EGFR-Mt was an independent favorable prognostic factor for OS of patients with p-stage II lung cancer (HR, 0.59; 95% CI, 0.36-0.96; p = 0.034).

CONCLUSION

The OS of lung cancer patients with p-stage II or IIIA, classified according to the 8th edition TNM classification, was remarkably favorable. Incorporating EGFR mutations to the anatomical TNM classification may lead to a more accurate prognosis prediction.

Immunotherapy and Vaccination in Surgically Resectable Non-Small Cell Lung Cancer (NSCLC)

Early-stage NSCLC (stages I and II, and some IIIA diseases) accounts for approximately 30% of non-small cell lung cancer (NSCLC) cases, with surgery being its main treatment modality. The risk of disease recurrence and cancer-related death, however, remains high among NSCLC patients after complete surgical resection. In previous studies on the long-term follow-up of post-operative NSCLC, the results showed that the five-year survival rate was about 65% for stage IB and about 35% for stage IIIA diseases. Platinum-based chemotherapy with or without radiation therapy has been used as a neoadjuvant therapy or post-operative adjuvant therapy in NSCLC, but the improvement of survival is limited. Immune checkpoint inhibitors (ICIs) have effectively improved the 5-year survival of advanced NSCLC patients. Cancer vaccination has also been explored and used in the prevention of cancer or reducing disease recurrence in resected NSCLC. Here, we review studies that have focused on the use of immunotherapies (i.e., ICIs and vaccination) in surgically resectable NSCLC. We present the results of completed clinical trials that have used ICIs as neoadjuvant therapies in pre-operative NSCLC. Ongoing clinical trials investigating ICIs as neoadjuvant and adjuvant therapies are also summarized.

Prognostic value of positron emission tomography in resected stage IA non-small cell lung cancer

OBJECTIVES

To investigate the role of PET in predicting the prognosis of resected stage IA non-small cell lung cancer (NSCLC) and planning individualized therapeutic strategies.

METHODS

We retrospectively reviewed the data of patients who underwent surgical resection for lung cancer between January 2004 and December 2014. The clinical data, imaging characteristics of nodules, surgical approaches, and outcomes were analyzed.

RESULTS

We evaluated 998 cases; 637 patients with pathological stage I disease were categorized as follows: stage IA1 (251 cases), stage IA2 (250 cases), and stage IA3 (136 cases). The mean follow-up period was 109 months. Significant differences were observed in sex, tumor differentiation, epidermal growth factor receptor mutation, smoking habits, lymphovascular space invasion, tumor size, maximum standard uptake value (SUVmax), and carcinoembryonic antigen level among the groups. Multivariable Cox regression revealed that ground-glass opacity ratio (hazard ratio (HR) = 0.001) and tumor SUVmax independently predicted the postoperative risk of relapse for stage IA3 NSCLC. The HR for SUVmax > 4 was 8.986 (p < 0.001). The 5-year overall survival (OS) rates were 87.2%, 92.9%, and 82.7%, and the 5-year disease-free survival (DFS) rates were 93.2%, 84.2%, and 70.51% for stage IA1, IA2, and IA3 NSCLC, respectively (both p < 0.001). OS and DFS rates were poor in stage IA3 NSCLC patients with an SUVmax uptake > 4 (OS, 71.0% and 92.2%; DFS, 50.2% and 87.3%, for SUVmax > 4 and ≤ 4, respectively; both p = 0.001).

CONCLUSIONS

SUVmax was a prognostic factor for resected stage IA NSCLC. Postoperative treatment may be considered for IA3 NSCLC with SUVmax > 4.

KEY POINTS

• PET helps surgeons to assess patients with early-stage lung cancer. • This retrospective study revealed that PET plays an influential role in predicting the prognosis of resected lung cancer. • Better prognostication aids better planning of therapeutic strategies with diversification.

[Progress in Survival Prognosis of Segmentectomy for Early-stage Non-small Cell Lung Cancer]

Surgery is currently the most appropriate treatment for early-stage non-small cell lung cancer (NSCLC). Increasing unilateral or bilateral multiple primary lung cancer being found, segmentectomy has attracted wide attention for its unique advantages in the treatment for such tumors. Ground glass opacity dominant early-stage NSCLC is associated with a good prognosis and can be cured by segmentectomy, however, the treatment of solid-dominant NSCLC remains controversial owing to the invasive nature. With the in-depth study on the lymph node metastasis pathway, radiological characteristics and molecular biology of NSCLC, a large part of solid nodules with certain characteristics can also be cured by segmentectomy. This paper reviews the research status and progress about the indication of segmentectomy.
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Effect of epidermal growth factor receptor mutation on early-stage non-small cell lung cancer according to the 8th TNM classification

OBJECTIVE

This study evaluated the effect of EGFR mutation on early-stage non-small cell lung cancer (NSCLC) based on the 8th TNM classification.

MATERIALS AND METHODS

The study retrospectively examined 1231 patients who underwent curative resection for pathological stage 0-I (8th TNM classification) NSCLC and EGFR mutation analysis from January 2006 to December 2018 at Kanagawa Cancer Center. The disease-free survival (DFS), overall survival (OS) and disease-specific survival (DSS) of EGFR-mutant lung cancer (Mt) and EGFR wild-type lung cancer (Wt) patients at each stage were compared between two patient groups using the log-rank test. Cox regression analyses were performed to identify prognostic factors.

RESULTS

The number of stage 0, IA1, IA2, IA3, and IB Mt/Wt patients was 79/92, 202/189, 145/144, 45/75, and 74/186, respectively. There was no statistically significant difference in DFS between Mt and Wt patients at any pathological stage. The 5-year OS of Mt/Wt patients was 96.9 %/98.5 % for stage 0 (p = 0.671), 92.2 %/92.2 % for stage IA1 (p = 0.997), 93.9 %/82.6 % for stage IA2 (p = 0.039), 87.3 %/91.4 % for stage IA3 (p = 0.768), and 85.3 %/69.3 % for stage IB (p = 0.017). The 5-year DSS of Mt/Wt patients was 95.7 %/95.4 % for stage IA2 (p = 0.684) and 93.2 %/77.5 % for stage IB (p = 0.016). In Cox regression analyses, Mt was not identified as a prognostic factor for OS among stage IA2 NSCLC patients (HR, 0.62; 95 % CI, 0.20-1.93; p = 0.413). However, Mt was a favorable prognostic factor for OS (HR, 0.44; 95 % CI, 0.19-1.00; p = 0.049) and DSS (HR, 0.38; 95 % CI, 0.17-0.87; p = 0.022) among stage IB NSCLC patients.

CONCLUSION

EGFR mutation had no effect on the prognosis of stage 0-IA NSCLC but significantly affected the OS and DSS of stage IB NSCLC. Effect of EGFR mutations on postoperative prognosis of patients with stage 0-I NSCLC differed with each stage.

A novel diagnostic system to evaluate epidermal growth factor receptor impact as a prognostic and therapeutic indicator for lung adenocarcinoma

Many driver pathways for cancer cell proliferation have been reported. Driver pathway activation is often evaluated based on a single hotspot mutation such as EGFR L858R. However, because of complex intratumoral networks, the impact of a driver pathway cannot be predicted based on only a single gene mutation. Here, we developed a novel diagnostic system named the "EGFR impact score" which is based on multiplex mRNA expression profiles, which can predict the impact of the EGFR pathway in lung cancer cells and the effect of EGFR-tyrosine kinase inhibitors on malignancy. The EGFR impact score indicated robust predictive power for the prognosis of early-stage lung cancer because this score can evaluate the impact of the EGFR pathway on the tumor and genomic instability. Additionally, the molecular features of the poor prognostic group resembled those of biomarkers associated with immune checkpoint inhibitors. The EGFR impact score is a novel prognostic and therapeutic indicator for lung adenocarcinoma.

Use of a prognostic risk score that aggregates the FDG-PET/CT SUVmax, tumor size, and histologic group for predicting the prognosis of pStage I lung adenocarcinoma

BACKGROUND

pStage I includes clinicopathologically diverse groups. This study aimed to identify the prognostic factors for pStage I lung adenocarcinoma.

METHODS

We retrospectively reviewed 208 patients with pStage I adenocarcinomas who underwent curative resection in our institute between 2006 and 2013. The maximum standardized uptake value (SUVmax) on [F18]-fluoro-deoxy-D-glucose positron emission tomography-computed tomography (PET/CT) was evaluated. Adenocarcinomas were categorized into the following histologic groups: group 0 (minimally invasive adenocarcinoma and lepidic predominant adenocarcinoma), group 1 (papillary predominant adenocarcinoma), and group 2 (acinar predominant adenocarcinoma and all the remaining subtypes). We assessed the relationship between disease-free survival (DFS) and clinicopathological factors.

RESULTS

Multivariate analysis of DFS demonstrated that SUVmax > 3.0 (p < 0.001), total tumor size > 20 mm (p = 0.016), and histologic groups (p < 0.05) were independent prognostic factors. The prognostic risk score (PRS) was calculated using the following equation: PRS = SUVmax (≤ 3.0: 0 point, > 3.0: 2 points) + total tumor size (≤ 20 mm: 0 point, > 20 mm: 1 point) + histologic group (group 0: 0 point, group 1: 1 point, group 2: 2 points). Patients were divided into the following three risk groups: low-risk (PRS 0-2 points, n = 136), intermediate-risk (PRS 3-4 points, n = 49), and high-risk groups (PRS 5 points, n = 13). The 5-year DFS rates were 93.2%, 50.6%, and 30.8% for the low-, intermediate-, and high-risk groups, respectively (p < 0.001).

CONCLUSIONS

The PRS aggregating the FDG-PET/CT SUVmax, total tumor size, and histologic group predicts the prognosis of pStage I lung adenocarcinoma.

MLW-gcForest: a multi-weighted gcForest model towards the staging of lung adenocarcinoma based on multi-modal genetic data

Background

Lung cancer is one of the most common types of cancer, among which lung adenocarcinoma accounts for the largest proportion. Currently, accurate staging is a prerequisite for effective diagnosis and treatment of lung adenocarcinoma. Previous research has used mainly single-modal data, such as gene expression data, for classification and prediction. Integrating multi-modal genetic data (gene expression RNA-seq, methylation data and copy number variation) from the same patient provides the possibility of using multi-modal genetic data for cancer prediction. A new machine learning method called gcForest has recently been proposed. This method has been proven to be suitable for classification in some fields. However, the model may face challenges when applied to small samples and high-dimensional genetic data.

Results

In this paper, we propose a multi-weighted gcForest algorithm (MLW-gcForest) to construct a lung adenocarcinoma staging model using multi-modal genetic data. The new algorithm is based on the standard gcForest algorithm. First, different weights are assigned to different random forests according to the classification performance of these forests in the standard gcForest model. Second, because the feature vectors generated under different scanning granularities have a diverse influence on the final classification result, the feature vectors are given weights according to the proposed sorting optimization algorithm. Then, we train three MLW-gcForest models based on three single-modal datasets (gene expression RNA-seq, methylation data, and copy number variation) and then perform decision fusion to stage lung adenocarcinoma. Experimental results suggest that the MLW-gcForest model is superior to the standard gcForest model in constructing a staging model of lung adenocarcinoma and is better than the traditional classification methods. The accuracy, precision, recall, and AUC reached 0.908, 0.896, 0.882, and 0.96, respectively.

Conclusions

The MLW-gcForest model has great potential in lung adenocarcinoma staging, which is helpful for the diagnosis and personalized treatment of lung adenocarcinoma. The results suggest that the MLW-gcForest algorithm is effective on multi-modal genetic data, which consist of small samples and are high dimensional.

The prognostic implications of EGFR mutation and ALK rearrangement for the long-term outcomes of patients with resected lung adenocarcinomas

Background

To investigate the prognostic impact of epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK) rearrangement for the overall survival (OS) of patients with surgically treated lung adenocarcinomas.

Methods

A total of 689 patients with stage I–III lung adenocarcinomas (male:female = 334:355; median age, 64 years) underwent complete surgical resection between 2007 and 2013. The prognostic impact of EGFR mutation and ALK rearrangement on OS was analyzed using Cox regression analysis. Certain clinicopathological prognostic factors (i.e., age, sex, smoking status, nodule type, solid portion size, pathologic stage, adenocarcinoma subtype, and history of adjuvant chemotherapy) were included for adjustments of the hazard ratio (HR).

Results

EGFR mutation was observed in 438 patients (64%) and ALK rearrangement was seen in 28 patients (4%). Multivariable‐adjusted Cox regression demonstrated that the prognostic effect of EGFR mutation on OS differed by age (HR, exp.[−5.199 + 0.064^*age]). The adjusted HR for EGFR mutation was 0.14 (95% CI: 0.05–0.36; P < 0.001) at 50 years, 0.26 (95% CI: 0.15–0.46; P < 0.001) at 60 years, and 0.50 (95% CI: 0.31–0.81; P = 0.005) at 70 years. However, the effect of ALK rearrangement on OS was without statistical significance (P > 0.05).

Conclusions

EGFR mutation was independently prognostic of the long‐term outcomes of patients with surgically treated lung adenocarcinomas. A more favorable prognostic effect was seen in younger than in older patients. ALK rearrangement was not associated with OS.

Increases in Serial Pretreatment 18F-FDG PET-CT Metrics Predict Survival in Early Stage Non-Small Cell Lung Cancer Treated With Stereotactic Ablative Radiation Therapy

Purpose

Quantitative changes in positron emission tomography with computed tomography imaging metrics over serial scans may be predictive biomarkers. We evaluated the relationship of pretreatment metabolic tumor growth rate (MTGR) and standardized uptake value velocity (SUVV) with disease recurrence or death in patients with early-stage non-small cell lung cancer treated with stereotactic ablative radiation therapy (SABR).

Methods and Materials

Under institutional review board approval, we retrospectively identified patients who underwent positron emission tomography with computed tomography at diagnosis and staging and simulation for SABR. Two cohorts underwent SABR between November 2005 to October 2012 (discovery) and January 2012 to April 2016 (validation). MTGR and SUVV were calculated as the daily change in metabolic tumor volume and maximum standardized uptake value, respectively. Cox proportional hazard models identified predictors of local, regional, and distant recurrence and death for the combined cohort. MTGR and SUVV thresholds dichotomizing risk of death in the discovery cohort were applied to the validation cohort.

Results

A total of 152 lesions were identified in 143 patients (92 lesions in 83 discovery cohort patients). In multivariable models, increasing MTGR trended toward increased hazard of distant recurrence (hazard ratio, 6.98; 95% confidence interval, 0.67-72.61; P = .10). In univariable models, SUVV trended toward risk of death (hazard ratio, 11.8, 95% confidence interval, 0.85-165.1, P = .07). MTGR greater than 0.04 mL/d was prognostic of decreased survival in discovery (P = .048) and validation cohorts (P < .01).

Conclusions

MTGR greater than 0.04 mL/d is prognostic of death in patients with non-small cell lung cancer treated with SABR. Increasing SUVV trends, nonsignificantly, toward increased risk of recurrence and death. MTGR and SUVV may be candidate imaging biomarkers to study in trials evaluating systemic therapy with SABR for patients at high risk of out-of-field recurrence.

Differential expression of PD-L1 and IDO1 in association with the immune microenvironment in resected lung adenocarcinomas

Like programmed cell death ligand 1 (PD-L1), indoleamine 2,3-dioxygenase 1 (IDO1) is known to exert immunosuppressive effects and be variably expressed in human lung cancer. However, IDO1 expression has not been well studied in lung adenocarcinoma. PD-L1 and IDO1 expression was evaluated in 261 resected lung adenocarcinomas using tissue microarrays and H-scores (cutoff: 5). We compared IDO1 and PD-L1 expression with clinical features, tumor-infiltrating lymphocytes, HLA class I molecule expression, molecular alterations, and patient outcomes. There was expression of PD-L1 in 89 (34%) and IDO1 in 74 (29%) cases, with co-expression in 49 (19%). Both PD-L1 and IDO1 were significantly associated with smoking, aggressive pathologic features, and abundant CD8+ and T-bet+ (Th1 marker) tumor-infiltrating lymphocytes. PD-L1 expression was also associated with preserved HLA class I molecule expression (p = 0.002). Compared to PD-L1+/IDO1+ and PD-L1+ only cases, significantly fewer IDO1+ only cases had abundant CD8+ and T-bet+ tumor-infiltrating lymphocytes (p < 0.001, respectively). PD-L1 expression was significantly associated with EGFR wild-type (p < 0.001) and KRAS mutants (p = 0.021), whereas isolated IDO1 expression was significantly associated with EGFR mutations (p = 0.007). As for survival, PD-L1 was a significant predictor of decreased progression-free and overall survival by univariate but not multivariate analysis, while IDO1 was not associated with progression-free or overall survival. Interestingly, there was a significant difference in the 5-year progression-free and overall survival (p = 0.004 and 0.038, respectively), where cases without PD-L1 or IDO1 expression had the longest survival, and those with PD-L1 alone had the shortest survival. While PD-L1+/-IDO1 expression is observed in association with HLA class I expression, cytotoxic T lymphocyte/Th1 microenvironments, EGFR wild-type, and KRAS mutations, isolated IDO1 expression does not demonstrate these associations, suggesting that IDO1 may serve a distinct immunosuppressive role in lung adenocarcinomas. Thus, further investigation of IDO1 may demonstrate its role as a potential biomarker for patients who undergo anti-PD-1/PD-L1 therapy.

RNSCLC-PRSP software to predict the prognostic risk and survival in patients with resected T1-3N0-2 M0 non-small cell lung cancer

BACKGROUND

The clinical outcomes of patients with resected T_1-3N_0-2M₀ non-small cell lung cancer (NSCLC) with the same tumor-node-metastasis (TNM) stage are diverse. Although other prognostic factors and prognostic prediction tools have been reported in many published studies, a convenient, accurate and specific prognostic prediction software for clinicians has not been developed. The purpose of our research was to develop this type of software that can analyze subdivided T and N staging and additional factors to predict prognostic risk and the corresponding mean and median survival time and 1-5-year survival rates of patients with resected T_1-3N_0-2M₀ NSCLC.

RESULTS

Using a Cox proportional hazard regression model, we determined the independent prognostic factors and obtained a prognostic index (PI) eq. PI = ∑_βixi.=0.379X₁-0.403X₂-0.267X₅₁-0.167X₆₁-0.298X₆₂ + 0.460X₇₁ + 0.617X₇₂-0.344X₈₁-0.105X₉₁-0.243X₉₂ + 0.305X₁₀₁ + 0.508X₁₀₂ + 0.754X₁₀₃ + 0.143X₁₁₁ + 0.170X₁₁₂ + 0.434X₁₁₃-0.327X₁₂₂-0.247X₁₂₃ + 0.517X₁₃₃ + 0.340X₁₃₄ + 0.457X₁₄₃ + 0.419X₁₄₄ + 0.407X₁₄₅. Using the PI equation, we determined the PI value of every patient. According to the quantile of the PI value, patients were divided into three risk groups: low-, intermediate-, and high-risk groups with significantly different survival rates. Meanwhile, we obtained the mean and median survival times and 1-5-year survival rates of the three groups. We developed the RNSCLC-PRSP software which is freely available on the web at http://www.rnsclcpps.com with all major browsers supported to determine the prognostic risk and associated survival of patients with resected T_1-3N_0-2 M₀ non-small cell lung cancer.

CONCLUSIONS

After prognostic factor analysis, prognostic risk grouping and corresponding survival assessment, we developed a novel software program. It is practical and convenient for clinicians to evaluate the prognostic risk and corresponding survival of patients with resected T_1-3N_0-2M₀ NSCLC. Additionally, it has guiding significance for clinicians to make decisions about complementary treatment for patients.

The prognostic effect of the epidermal growth factor receptor gene mutation on recurrence dynamics of lung adenocarcinoma

OBJECTIVES

The prognostic effects of epidermal growth factor receptor (EGFR) gene mutation on lung adenocarcinoma recurrence have not been well established. The relationship between EGFR gene mutation and recurrence dynamics of lung adenocarcinoma was investigated.

METHODS

A total of 527 patients with complete resection for adenocarcinoma were reviewed retrospectively. EGFR gene mutation was analysed by polymerase chain reaction followed by bidirectional direct sequencing in recurred patients. Patients were divided into the EGFR gene mutation group (M) or the wild-type EGFR gene group (W). Recurrence types and disease-free intervals (DFIs) of the 2 groups were compared. DFIs were calculated by the Kaplan-Meier method and compared using the log-rank test and Cox proportional hazard model.

RESULTS

EGFR gene sequencing was performed in 115 recurrent adenocarcinoma patients. Sixty-six patients had EGFR mutations and 49 patients had wild-type EGFR. The median DFI of the 2 groups were significantly different (M: 20.3 months, W: 15.1 months, P = 0.012). EGFR gene mutation was the only prognostic factor for DFI [hazard ratio (HR) = 0.639, 95% confidence interval (CI) = 0.428-0.954, P = 0.029]. The proportion of loco-regional recurrences and distant metastases of both groups were similar (P = 0.50). In subgroup analysis, EGFR gene mutation (HR = 0.534, 95% CI = 0.339-0.839, P = 0.007) was a significant prognostic factor for DFI of distant metastases.

CONCLUSIONS

Lung adenocarcinoma with EGFR gene mutations had longer DFI than those with wild-type EGFR gene, especially with regard to distant metastasis. EGFR gene mutation was a prognostic factor for lung adenocarcinoma.

Tumor-based gene expression biomarkers to predict survival following curative intent resection for stage I lung adenocarcinoma

Background

Prognostic biomarkers are needed in clinical setting to predict outcome after resection for early-stage lung adenocarcinoma. The goal of this study is to validate tumor-based single-gene expression biomarkers with demonstrated prognostic value in order to move them along the clinical translation pipeline.

Methods

Prognostic genes were selected from the literature and the best candidates measured by quantitative real-time polymerase chain reaction (qPCR) in tumors of 233 patients with stage I adenocarcinoma. Significant prognostic genes were then validated in an independent set of 210 patients matching the first set in terms of histology, stage, and clinical data.

Results

Eleven genes with demonstrated prognostic value were selected from the literature. Complementary analyses in public databases and our own microarray dataset led to the investigation of six genes associated with good (BTG2, SELENBP1 and NFIB) or poor outcome (RRM1, EZH2 and FOXM1). In the first set of patients, EZH2 and RRM1 were significantly associated with better survival on top of age, sex and pathological stage (EZH2 p = 3.2e-02, RRM1 p = 5.9e-04). The prognostic values of EZH2 and RRM1 were not replicated in the second set of patients. A trend was observed for both genes in the joint analyses (n = 443) with higher expression associated with worse outcome.

Conclusion

Adenocarcinoma-specific mRNA expression levels of EZH2 and RRM1 are associated with poor post-surgical survival in the first set of patients, but not replicated in a clinically and pathologically matched independent validation set. This study highlights challenges associated with clinical translation of prognostic biomarkers.