Abstract

Background

   Due to the relatively insidious early symptoms of lung adenocarcinoma
   (LUAD), most LUAD patients are at an advanced stage at the time of
   diagnosis and lose the best chance of surgical resection. Mounting
   evidence suggested that the tumor microenvironment (TME) was highly
   correlated with tumor occurrence, progress, and prognosis. However, TME
   in advanced LUAD remained to be studied and reliable prognostic
   signatures based on TME in advanced LUAD also had not been
   well-established. This study aimed to understand the cell composition
   and function of TME and construct a gene signature associated with TME
   in advanced LUAD.

Methods

   The immune, stromal, and ESTIMATE scores of each sample from The Cancer
   Genome Atlas (TCGA) database were, respectively, calculated using an
   ESTIMATE algorithm. The LASSO and Cox regression model were applied to
   select prognostic genes and to construct a gene signature associated
   with TME. Two independent datasets from the Gene Expression Omnibus
   (GEO) were used for external validation. Twenty-two subsets of
   tumor-infiltrating immune cells (Tiics) were analyzed using the
   CIBERSORT algorithm.

Results

   Favorable overall survival (OS) and progression-free survival (PFS)
   were found in patients with high immune score (p = 0.048 and p = 0.028;
   respectively) and stromal score (p = 0.024 and p = 0.025;
   respectively). Based on the immune and stromal scores, 453
   differentially expressed genes (DEGs) were identified. Using the LASSO
   and Cox regression model, a seven-gene signature containing AFAP1L2,
   CAMK1D, LOXL2, PIK3CG, PLEKHG1, RARRES2, and SPP1 was identified to
   construct a risk stratification model. The OS and PFS of the high-risk
   group were significantly worse than that of the low-risk group (p <
   0.001 and p < 0.001; respectively). The receiver operating
   characteristic (ROC) curve analysis confirmed the good potency of the
   seven-gene signature. Similar findings were validated in two
   independent cohorts. In addition, the proportion of macrophages M2 and
   Tregs was higher in high-risk patients (p = 0.041 and p = 0.022,
   respectively).

Conclusion

   Our study established and validated a seven-gene signature associated
   with TME, which might serve as a prognosis stratification tool to
   predict survival outcomes of advanced LUAD patients. In addition,
   macrophages M2 polarization may lead to worse prognosis in patients
   with advanced LUAD.

   Keywords: tumor microenvironment, immune, lung adenocarcinoma, stromal,
   TCGA

Introduction

   Lung cancer ranks first in the incidence and mortality of all malignant
   tumors worldwide ([31]Bray et al., 2018). The 5-year survival rate of
   lung cancer patients is less than 20% ([32]Herbst et al., 2018). Lung
   adenocarcinoma (LUAD) is the most common histological subtype of
   non-small cell lung cancer (NSCLC), which accounts for about 40% of all
   lung malignancies and usually occurs in the outer area of the lung
   ([33]Chen et al., 2014). Clinical studies have shown that nearly 70% of
   LUAD patients are discovered in stage III–IV, and 57% of LUAD patients
   have already developed distant metastasis at the time of initial
   diagnosis, and have lost the best opportunity for surgical resection
   ([34]Jemal et al., 2017).

   In recent years, significant progress has been made in the research of
   molecular genetics and immunotherapy of lung cancer, and molecular
   typing based on genetic characteristics has brought the treatment of
   advanced lung cancer into the era of personalized molecular targeted
   therapy ([35]Subramanian and Govindan, 2008). EGFR-Inhibitor and
   BRAF(V600E)-mutant, rearrangements of ALK or ROS1 genes, as well as
   immune checkpoint inhibitor antibodies against PD-1 or PD-L1 have been
   approved for the treatment of advanced LUAD ([36]Vargas and Harris,
   2016; [37]Hirsch et al., 2017). At present, the TNM staging system is
   still the most effective tool to judge the survival of patients and
   guide clinical treatment strategies, but the evaluation effect for
   advanced survival is not good ([38]Goldstraw et al., 2016). Therefore,
   looking for a new survival predictor for advanced LUAD patients is
   particularly important for personalized treatment of clinical
   decision-making and prognostic health management.

   Tumor microenvironment (TME) refers to the surrounding microenvironment
   of tumor cells, including immune cells, stromal cells, endothelial
   cells, inflammatory cells, and fibroblasts ([39]Neal et al., 2018).
   Among them, immune cells and stromal cells are two major non-tumor cell
   components, which have been considered important for the diagnosis and
   prognostic evaluation of cancer patients ([40]Gajewski et al., 2013).
   Therefore, understanding the cell composition and function of TME will
   bring a new dawn to patients with advanced LUAD in terms of immunity
   and targeted therapy and improvement of prognosis.

   The continuous improvement and development of public databases, such as
   The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus
   (GEO) database, provide reliable data resources for TME research
   ([41]Cancer Genome Atlas Research Network, Weinstein et al., 2013;
   [42]NCBI Resource Coordinators, 2016). [43]Yoshihara et al. (2013)
   first proposed the ESTIMATE algorithm in 2013. This algorithm uses the
   unique properties of the transcription profile of cancer samples to
   infer infiltrating stromal/immune cells. According to reports,
   researchers have explored the tumor characteristics and prognosis
   assessment of liver cancer ([44]Li et al., 2019), breast cancer
   ([45]Bai et al., 2019), and clear cell renal cell carcinoma ([46]Luo et
   al., 2020) based on the ESTIMATE algorithm. However, the value of
   immune and stromal scores for advanced LUAD has not been verified.

   In the present study, the immune and stromal scores were estimated
   using the ESTIMATE algorithm based on the transcription profile of LUAD
   patients with stage III–IV. A robust gene signature based on
   immune-stromal score was subsequently developed for prognosis
   stratification in advanced LUAD. Finally, we explored the relationship
   between high-/low-risk advanced LUAD patients and immune cell
   infiltration based on the CIBERSORT method, so as to provide some
   references for combined immunotherapy and targeted therapy for advanced