Characterization of the tumor immune-microenvironment of lung adenocarcinoma associated with usual interstitial pneumonia

Accepted Manuscript Title: Characterization of the tumor immune-microenvironment of lung adenocarcinoma associated with usual interstitial pneumonia Authors: Takuya Ueda, Keiju Aokage, Sachiyo Mimaki, Kenta Tane, Tomohiro Miyoshi, Masato Sugano, Motohiro Kojima, Satoshi Fujii, Takeshi Kuwata, Atsushi Ochiai, Masahiko Kusumoto, Kenji Suzuki, Katsuya Tsuchihara, Hiroyoshi Nishikawa, Koichi Goto, Masahiro Tsuboi, Genichiro Ishii PII: DOI: Reference:

S0169-5002(18)30633-0 https://doi.org/10.1016/j.lungcan.2018.11.006 LUNG 5832

To appear in:

Lung Cancer

Received date: Revised date: Accepted date:

15 August 2018 12 October 2018 5 November 2018

Please cite this article as: Ueda T, Aokage K, Mimaki S, Tane K, Miyoshi T, Sugano M, Kojima M, Fujii S, Kuwata T, Ochiai A, Kusumoto M, Suzuki K, Tsuchihara K, Nishikawa H, Goto K, Tsuboi M, Ishii G, Characterization of the tumor immunemicroenvironment of lung adenocarcinoma associated with usual interstitial pneumonia, Lung Cancer (2018), https://doi.org/10.1016/j.lungcan.2018.11.006 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Title: Characterization of the tumor immune-microenvironment of lung adenocarcinoma associated with usual interstitial pneumonia

Takuya Ueda MD, PhD1,2,3,4), Keiju Aokage MD, PhD2), Sachiyo Mimaki MD, PhD5),

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Kenta Tane MD, PhD2), Tomohiro Miyoshi MD, PhD2), Masato Sugano MD, PhD3), Motohiro Kojima MD, PhD1), Satoshi Fujii MD, PhD1), Takeshi Kuwata MD, PhD3),

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Atsushi Ochiai MD, PhD6), Masahiko Kusumoto MD, PhD7), Kenji Suzuki MD, PhD4),

Katsuya Tsuchihara MD, PhD5), Hiroyoshi Nishikawa MD, PhD8), Koichi Goto9),

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Masahiro Tsuboi MD, PhD2), Genichiro Ishii MD, PhD1)

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1) Division of Pathology, Exploratory Oncology Research & Clinical Trial Center,

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National Cancer Center, Kashiwa, Chiba, Japan

2) Department of Thoracic Surgery, National Cancer Center Hospital, Kashiwa, Chiba,

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Japan

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3) Department of Pathology and Clinical Laboratories, National Cancer Center Hospital East, Kashiwa, Japan.

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4) Departments of General Thoracic Surgery, Juntendo University School of Medicine,

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Tokyo, Japan

5) Division of Translational Research, Research Center for Innovate Oncology, National

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Cancer Center, Kashiwa, Japan 6) Exploratory Oncology Research & Clinical Trial Center, National Cancer Center, Kashiwa, Chiba, Japan 7) Department of Diagnostic Radiology, National Cancer Center Hospital East, Chiba, Japan

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8) Division of Cancer Immunology, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, Kashiwa, Chiba, Japan 9) Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa,

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Japan

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Corresponding author: Keiju Aokage, MD, PhD or Genichiro Ishii, MD, PhD, Division of Pathology, Exploratory Oncology Research and Clinical Trial Center, National Cancer

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Center, 6-5-1, Kashiwanoha, Kashiwa, Chiba 277-8577, Japan.

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E-mail address: [email protected] or [email protected]

Highlights

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・UIP-ADC patients had worse prognosis than non-UIP ADC patients.

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・UIP-ADC patients exhibited reduced levels of CD8+ TILs.

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・The CD8+/Foxp3+ T cell ratio was significantly reduced in UIP-ADC.

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・The tumor microenvironment of UIP-ADC acquires an immunosuppressive state.

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This study was supported in part by JSPS KAKENHI (16H05311).

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Abstract Background: Lung cancer with usual interstitial pneumonia (UIP) pattern is a disease with poor prognosis. This study aimed to characterize the tumor microenvironment of lung adenocarcinoma associated with UIP (UIP-ADC).

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Methods: A total of 1,341 consecutive patients with ADC who had undergone complete

surgical resection were enrolled in this study, and the clinicopathological features of UIP-

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ADC were examined. Further, we selected 17 cases of UIP-ADC and non-UIP ADC each (adjusted for age, smoking status, pathological stage, and invasive size of lesion) for

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immunohistochemical analysis, and the biological differences between UIP-ADC and

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non-UIP ADC groups were analyzed.

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Results: UIP-ADC was detected in 18 patients (1.3%). Patients with UIP-ADC had

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shorter cancer-specific survival (CSS) (5 yrs CSS; UIP-ADC 52.9% vs non-UIP ADC 81.8%, p<0.01). Evaluation of tumor-infiltrating lymphocytes (TILs) in cancer stroma

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showed that the number of CD8+ TILs in UIP-ADC group was significantly lower than

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that in the non-UIP ADC group (median number 91 vs 121, p<0.01). In contrast, levels of Foxp3+ TILs were not significantly different between the two groups. The

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CD8+/Foxp3+ T cell ratio was significantly lower in UIP-ADC than in the non-UIP ADC

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population (1.9 vs 2.7, p<0.01). Additionally, among UIP-ADC patients, the CD8+/Foxp3+ T cell ratio was significantly higher in the non-cancerous UIP lesions than

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in the cancer stroma from the same patient (2.4 vs 1.7, p<0.01). Conclusion: In the current study, we have demonstrated that the tumor microenvironment of UIP-ADC acquires an immunosuppressive state, and this could be one of the possible explanations for poor prognosis of this disease.

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Abbreviation List ADC =adenocarcinoma; ALDH-1 = aldehyde dehydrogenase 1; CAFs = cancerassociated fibroblasts; CA IX = carbonic anhydrase IX; CD8 = cluster of differentiation 8; CD204 = cluster of differentiation 204; CSS = cancer specific survival; EGFR =

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epidermal growth factor receptor; Foxp3 = forkhead boxprotein P3; HPF = high power field; IHC = immunohistochemistry; IPF = idiopathic pulmonary fibrosis; LVI =

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lymphovascular invasion; NSCLC = non-small cell lung cancer; OS = overall survival; PD-L1 = programmed cell death ligand 1; RFS = recurrence-free survival; SqCC =

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squamous cell carcinoma; TAMs = tumor associated macrophages; TILs = tumor

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infiltrating lymphocytes; T-regs = regular T-cells, UIP = usual interstitial pneumonia;

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VPI = visceral pleural invasion

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Keyword

adenocarcinoma, idiopathic pulmonary fibrosis, usual interstitial pneumonia, tumor

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microenvironment, tumor infiltrating lymphocytes

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Introduction A malignant tumor is composed of not only cancer cells but also various types of noncancerous stromal cells containing cancer-associated fibroblasts (CAFs), tumorassociated macrophages (TAMs), and tumor infiltrating lymphocytes (TILs); such

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heterogeneous population of cells gives rise to cancer-specific microenvironments (1-5). Recent studies have shed new light on this complex interaction between tumor and host

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immune cells and helped us understand the immune response triggered by this interaction. Several comprehensive studies have evaluated the prognostic impact of TILs in NSCLC

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patients (6-11). Donnem et al found that stromal CD8+ TIL density was an independent prognostic factor in resected NSCLC patient population (6). Using tissue microarrays,

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Schalper et al demonstrated that increased levels of CD3+ and CD8+ TILs were associated

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with better outcome in NSCLC patients, but CD8 was independent of other prognostic variables (7).

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Idiopathic pulmonary fibrosis (IPF), the most common form of idiopathic interstitial

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pneumonia, is characterized by the presence of radiological and/or pathological patterns of usual interstitial pneumonia (UIP). It is considered to be a chronic, progressive,

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irreversible, and a fatal lung disease. The prevalence of lung cancer ranges from 2.7 to

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48% in patients with IPF, and the development of lung cancer is one of the main causes of death in these patients (12-17). A multi-center study conducted in Japan revealed that

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resected lung cancer patients with interstitial lung disease (including patients with UIP pattern) had a poor prognosis, and lung cancer was the main cause of mortality in this cohort. These results highlight the importance of oncologic control for better survival outcomes in patients with IPF (18) . We have previously reported that the establishment of an immunosuppressive tumor

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microenvironment is a characteristic feature of UIP-associated squamous cell carcinoma (UIP-SqCC) (19). However, we know very little about the tumor microenvironment of UIP-ADC, including the relationship between UIP-ADC and TILs. The aim of this study was to elucidate the clinicopathological features of UIP-ADC and further identify its

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unique tumor microenvironment.

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Materials and methods Patients

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Between January 2004 and December 2013, 1,640 consecutive lung ADC patients

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underwent complete surgical resections. Further, we excluded 299 patients based on the

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following criteria: (a) more than two lesions at the time of diagnosis, (b) received

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preoperative chemotherapy or preoperative thoracic radiation, (c) diagnosed with adenocarcinoma in situ or minimally invasive carcinoma. Finally, 1,341 patients were

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enrolled in this study; out of these, 18 patients were diagnosed with UIP-ADC (1.3%).

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Patients who underwent preoperative treatment for UIP, such as steroids and immunosuppressive agents, were also not included in this study. The presence of EGFR

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mutation was examined in 846 patients. Among these patients, 353 patients were found

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to carry EGFR-positive mutations (1 UIP-ADC, 352 non-UIP ADC). Institutional Review Board-approved informed consent was obtained from all the patients (IRB approval

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number; 2017-196).

Histological diagnosis Histological diagnosis was based on the 4th edition of World Health Organization histological classification (20) and the disease stages were categorized following the

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guidelines of the 8th edition of TNM classification (21). Diagnosis of UIP pattern was performed following the 2002 American Thoracic Society/European Respiratory Society (22) and the 2011 IPF guidelines (23). We defined

also discontinuous with the UIP lesions (Supplementary Figure 1).

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Evaluation of clinicopathological factors

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UIP-ADC as the tumorous lesions located not only within or adjacent to UIP lesions but

The clinical characteristics of patients were reviewed from the available medical records. The following clinicopathological factors were investigated retrospectively to

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assess their impact on patient’s survival: age, gender, smoking history, mode of surgery,

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tumor location, tumor size, invasive component size, pathologic stage, pathologic nodal

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involvement, lymphovascular invasion (LVI), visceral pleural invasion (VPI), and

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predominant subtype.

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Antibodies and immunohistochemistry (IHC) Among 493 patients with EGFR-negative mutations, we selected 17 cases of UIP-ADC

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and non-UIP ADC each (matched by age, pack year smoking, pathologic stage, and

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invasive component size adjustment) with the propensity-score matched using the following algorithm: 1:1 optimal match without caliper and replacement. There were no

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significant differences in clinicopathological features between the two groups (Supplementary Table 1). Immunohistochemical staining was performed as described previously (24). The primary antibodies used in this study are summarized in Supplementary Table 2. All stained tissue sections were scored semi-quantitatively and viewed independently under a light microscope by two pathologists (T.U. and G.I.). We

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used the scoring system as previously reported by our institute (19). The percentage of stained area and the intensity of each lesion were calculated and multiplied, producing scores between 0 and 200. For CD204, we selected a hot spot within a section, counted the number of CD204+ macrophages in the cancer stroma in five high-power microscopic

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fields (×400 magnification, 0.0625 mm2), and calculated the average numbers.

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Evaluation of TILs

All slides stained with CD8 or Foxp3 antibodies were examined using high-resolution digital slide scanner (Nanozoomer 2.0-HT, Hamamatsu Photonics, Hamamatsu City,

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Japan). Five independent areas with a size of 0.0625 mm2, containing the greatest abundance of lymphocytes in the tumor nest, were selected, and the average numbers of

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positive lymphocytes were calculated. Further, the numbers of CD8+ and Foxp3+ cells

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were scored for the same field (Supplementary Figure 2).

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Evaluation of lymphocytes in UIP stroma We evaluated the infiltrating lymphocytes not only in the cancer stroma but also in the

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non-cancerous fibrous lesion (UIP stroma). Among 17 patients with UIP-ADC

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(representing the IHC cohort), 5 patients were excluded due to the lack of evaluable histological data of UIP stroma. Seven independent areas (0.0625 mm2 each), containing

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the greatest abundance of lymphocytes in the UIP stroma, were selected and the average numbers of positive lymphocytes were calculated. The numbers of CD8+ and Foxp3+ cells were also evaluated for the same field.

Whole exome sequencing

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We have previously reported the whole exome sequencing data for 97 Japanese patients with lung adenocarcinoma tumor/normal pairs (25). The sequencing read data were deposited in National Bioscience Database Center (NBDC) under research ID hum0004.v1 and data ID JGAD00000000001 (25). Using these data, we further analyzed

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the number of single nucleotide variants (SNVs) in cancer cells of UIP-ADC patients.

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Statistical analysis

Overall survival (OS), cancer-specific survival (CSS), and recurrence-free survival

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(RFS) curves were plotted according to the Kaplan-Meier method and compared using

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the log-rank test in a univariate analysis. For the predictors of CSS, univariate and multivariate analyses were conducted using the Cox proportional hazard model. Two

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category comparisons were performed using one of these tests: chi-square test, Fisher’s exact test or Mann-Whitney U test. P-values less than 0.05 were considered statistically

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significant.

Results

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Patient characteristics

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Compared with the non-UIP ADC group, most of the patients with UIP-ADC were older (p=0.01) and smokers (p<0.01). The mean value of pack year smoking in UIP-ADC

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group was significantly higher than that in non-UIP ADC group (45 vs 12.5, p<0.01). UIP-ADC occurred more frequently in the lower lobe of the lung (66.8 vs 31.6%, p<0.01), and tumor size was larger in the UIP-ADC group than in the non-UIP ADC group (4.2 vs 2.5cm, p<0.01). Consistently, relative to the non-UIP ADC group, invasive component size was greater in UIP-ADC group (3.6 vs 2.0cm, p<0.01). The rate of EGFR mutation

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was significantly lower in UIP-ADC than in the non-UIP group (5.6 vs 42.7%, p<0.01) (Table 1).

Correlation between prognosis and UIP-ADC

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The median follow-up time for this cohort was 5.1 yrs. As shown in Figure 1, patients

with UIP-ADC had a significantly shorter OS and RFS than those with non-UIP ADC (5

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yrs OS 31.8 vs 76.5%, p<0.01; 5 yrs RFS 18.0 vs 65.8%, p<0.01). Additionally, we

observed that UIP-ADC group had significantly shorter CSS than the non-UIP ADC

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Prognostic factors for cancer-specific survival

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group (5 yrs CSS 52.9 vs 81.8%, p<0.01).

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In the univariate analysis, gender, smoking status, tumor size, invasive component size, nodal involvement, and VPI, and the presence of UIP pattern were significant prognostic

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factors for CSS. Further, in the multivariate analysis, invasive component size, VPI, nodal

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CSS (Table 2).

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involvement, and the presence of UIP-pattern were independent prognostic factors for

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Immunohistochemical staining results PD-L1 expression in patients with UIP-ADC was significantly lower than that in

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patients in the non-UIP ADC group (median score 0 vs 0, p=0.02). Other antibodies used for staining cancer cells and cancer stromal cells did not show an association with UIPADC (Figure 2). Details of these staining in cancer cells and stromal cells were as follows; ALDH-1(p=0.67, median score 20 vs 10), CAIX (p=0.27, median score 0 vs 10), Laminin5γ2 (p=0.27, median score 10 vs 0), Podoplanin CAFs (p=0.16, median score 10

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vs 10), CA IX CAFs (p=0.08, median score 0 vs 0), CD204 TAMs (p=0.13, median number 23 vs 27).

Evaluation of stromal TILs

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Representative images of CD8+ TILs and Foxp3+ TILs are shown in Figure 3A-D.

While the number of CD8+ TILs in UIP-ADC was significantly lower than that in non-

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UIP ADC (median number 91 vs 121, p<0.01), the number of Foxp3+ TILs was not

significantly different between the two groups (p=0.44). The CD8+/Foxp3+ T cell ratio

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was significantly reduced in UIP-ADC relative to non-UIP ADC group (p<0.01, 1.9 vs

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2.7) (Figure 3E). Univariate analysis was performed for IHC cohort (n=34) according to Cox proportional hazard model (Supplementary Table 3), and the results showed that

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increasing number of CD8+ TILs was a positive prognostic factor for CSS (p<0.01, HR

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0.961, 95% CI 0.936-0.987). Similarly, CD8+/Foxp3+ T cell ratio appeared to be a

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positive prognostic factor for CSS (p=0.08, HR 0.422, 95% CI 0.158-1.123); however,

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the number of Foxp3+ TILs did not have any prognostic value for CSS (p=0.19).

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TILs in non-cancerous UIP stroma

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To evaluate whether UIP stroma affects the immunosuppressive state of the UIP-ADC population, we compared the CD8+ and Foxp3+ T cell status in cancerous and non-

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cancerous lesion from the same patient (Figure 4). Further, we compared the number of CD8+ lymphocytes in the cancer stroma and UIP stroma and observed no significant differences between them (p=0.20). However, the number of Foxp3+ lymphocytes in cancer stroma was significantly elevated, as compared to that in UIP stroma (Supplementary Figure 3). We also noticed a significant decline in the CD8+/Foxp3+ T

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cell ratio in cancer stroma but not in the UIP stroma (p<0.01).

Number of SNVs in UIP-ADC Using whole genome sequencing data, we identified 4 patients with UIP-ADC (25).

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Overall, the median number of SNVs in the cancer cells was 46, and these numbers were 67.5 and 45.0 for UIP-ADC and non-UIP ADC groups, respectively. However, we did

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not detect significant differences between two groups (p=0.28). Further, for the smoker

subgroup (n=54), the median number of SNVs was 67.5 and 93.0 in UIP-ADC and non-

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UIP ADC populations (p=0.60), respectively (Supplementary Figure 4).

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Discussion

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To our knowledge, this is the first report about the tumor microenvironment of UIPADC that focuses on the tumor immunity and prognostic aspects of UIP-ADC. In the

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current study, we found that patients with UIP-ADC had shorter OS, RFS, and CSS than

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those in non-UIP ADC group. Based on IHC staining of TILs, UIP-ADC patients exhibited reduced levels of CD8+ TILs and a low CD8+/Foxp3+ T cell ratio than the non-

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UIP ADC patients. In addition, increasing number of CD8+ TILs and a high CD8+/Foxp3+

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T cell ratio were found to be positive prognostic factors for CSS in the IHC cohort. These results demonstrate that unlike non-UIP ADC, the tumor microenvironment of UIP-ADC

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favors an immunosuppressive state, possibly explaining for poor prognosis in these patients. We

have

recently

reported

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clinicopathological

features

and

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microenvironment of UIP-SqCC (19). Patients with UIP-SqCC had shorter RFS than those with non-UIP SqCC. Patients with UIP-SqCC display high levels of PD-L1

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expression and low CD8+/Foxp3+ T cell ratio. Generally, binding of PD-L1 to PD-1 causes exhaustion of effector T cells and immune escape of tumor cells, leading to the poor prognosis (26). In contrast to our previous report (19), the current study showed that PD-L1 expression in cancer cells was lower in UIP-ADC group than in non-UIP ADC

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group. This discrepancy may be due to the difference in the numbers of CD8+ TILs

between UIP-ADC and non-UIP ADC. Several mechanisms, including epigenetic

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regulation, oncogenic signaling, and acquired immune responses, have been proposed for

the upregulation of PD-L1 in tumor cells (27). The acquired immune response is activated

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through upregulation of PD-L1 by endogenous anti-tumor immunity factors in the tumor

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microenvironment, such as interferon gamma (IFN-γ, produced by activated cytotoxic

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T lymphocytes). Possibly, a low number of CD8+ TILs might have resulted in low

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expression of PD-L1 in tumor cells of UIP-ADC patients. It has previously been shown that neoantigen burden is closely related to the non-

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synonymous SNV (nsSNV) burden (28). The efficacy of checkpoint inhibitors is most

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marked in tumor types with a high nsSNV burden, including melanoma and NSCLC. Furthermore, in these tumor types, nsSNV and neoantigen burdens correlate with

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response to checkpoint inhibitors (29-32). In this study, the number of SNVs was not

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significantly different between UIP-ADC and non-UIP ADC groups. Therefore, we could not assess if UIP-ADC would exhibit a better response to immunotherapy.

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Relative to UIP stroma, the CD8+/Foxp3+ T cell ratio was significantly lower in cancer

stroma. Although the number of CD8+ lymphocytes was not significantly different between cancer stroma and UIP stroma, the number of Foxp3+ lymphocytes was higher in cancer stroma than in UIP stroma (Supplementary Figure 3). These results suggest that immune suppressive microenvironment might be generated during the cancer 13

development in patients with UIP-ADC, and the recruitment of a high number of Foxp3+ lymphocytes in cancer stroma is considered to be a major change in the immune suppressive tumor microenvironment. The present study had some limitations worth noting. Firstly, this was a single-center

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retrospective study that included a small sample size population. Patients with IPF are not extremely rare but the cohort included in this study focused exclusively on patients who

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had undergone surgeries. Moreover, this study excluded patients with EGFR mutation for

IHC analysis. We could adjust the driver gene mutation status, however, we cannot

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predict the impact of altered status of molecular biomarkers other than EGFR.

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In conclusion, we demonstrated that patients with UIP-ADC had shorter OS, RFS, and CSS than those with non-UIP ADC. Relative to non-UIP ADC, UIP-ADC had decreased

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levels of CD8+ TILs and a low CD8+/Foxp3+ T cell ratio. Our data also suggested that the immune microenvironment of UIP-associated lung cancer (both squamous cell carcinoma

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and adenocarcinoma) favor an immunosuppressive state. However, further study is

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required to examine whether improving immune tumor microenvironment may result in

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a better prognosis of UIP-associated lung cancer.

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The authors declare that they have no conflict of interest.

Acknowledgments Author contributions: Dr Ueda: contributed to the design and coordination of the study, conduct research, prepare the manuscript, and read and approve the final manuscript.

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Dr Aokage: contributed to the design and coordination of the study, revise the article for important intellectual content, and read and approve the final manuscript. Dr Mimaki: contributed to conduct research, prepare the manuscript and read and approve the final manuscript.

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Dr Tane, Dr Miyoshi, Dr Sugano, Dr Kojima, Dr Fujii, Dr Kuwata, Dr Ochiai, Dr

Kusumoto, Dr Tsuchihara, Dr Nishikawa, Dr Suzuki, Dr Goto and Dr Tsuboi: contributed

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to prepare the manuscript and read and approve the final manuscript.

Dr Ishii: contributed to the design and coordination of the study, revise the article for

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important intellectual content, and read and approve the final manuscript.

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Financial/nonfinancial disclosures: The authors have reported to Lung Cancer that no

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potential conflicts of interest exist with any companies/organizations whose products or

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services may be discussed in this article.

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Other contributions: All work included in the manuscript was performed at National Cancer Center, Kashiwa, Chiba, Japan. The research was approved by the internal review

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board of the institution (IRB approval number; 2017-196). No patient consent was

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required as the research is a retrospective chart review and no personally identifiable

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information was included in the manuscript.

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17. Ozawa Y, Suda T, Naito T, Enomoto N, Hashimoto D, Fujisawa T, et al. Cumulative incidence of and predictive factors for lung cancer in IPF. Respirology. 2009;14(5):723-8. 18. Sato T, Watanabe A, Kondo H, Kanzaki M, Okubo K, Yokoi K, et al. Longterm results and predictors of survival after surgical resection of patients with lung cancer and interstitial lung diseases. The Journal of thoracic and cardiovascular surgery. 2015;149(1):64-9, 70 e1-2. 19. Ueda T, Aokage K, Nishikawa H, Neri S, Nakamura H, Sugano M, et al. Immunosuppressive tumor microenvironment of usual interstitial pneumonia-associated squamous cell carcinoma of the lung. J Cancer Res Clin Oncol. 2018. 20. Travis WD BE, Burke AP, et al. The 2015 World Health Organization (WHO) Classification of Tumors of the Lung, Pleura, Thymus and Heart. Lyon, France, IARC 2015. 21. Goldstraw P, Chansky K, Crowley J, Rami-Porta R, Asamura H, Eberhardt WE, et al. The IASLC Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groupings in the Forthcoming (Eighth) Edition of the TNM Classification for Lung Cancer. J Thorac Oncol. 2016;11(1):39-51. 22. ATS/ERS. American Thoracic Society/European Respiratory Society International Multidisciplinary Consensus Classification of the Idiopathic Interstitial Pneumonias. This joint statement of the American Thoracic Society (ATS), and the European Respiratory Society (ERS) was adopted by the ATS board of directors, June 2001 and by the ERS Executive Committee, June 2001. Am J Respir Crit Care Med;:. 2002(165):277-304. 23. Raghu G, Collard HR, Egan JJ, Martinez FJ, Behr J, Brown KK, et al. An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management. American journal of respiratory and critical care medicine. 2011;183(6):788-824. 24. Ono S, Ishii G, Nagai K, Takuwa T, Yoshida J, Nishimura M, et al. Podoplanin-positive cancer-associated fibroblasts could have prognostic value independent of cancer cell phenotype in stage I lung squamous cell carcinoma: usefulness of combining analysis of both cancer cell phenotype and cancer-associated fibroblast phenotype. Chest. 2013;143(4):963-70. 25. Suzuki A, Mimaki S, Yamane Y, Kawase A, Matsushima K, Suzuki M, et al. Identification and characterization of cancer mutations in Japanese lung adenocarcinoma without sequencing of normal tissue counterparts. PloS one. 2013;8(9):e73484. 26. Wang X, Teng F, Kong L, Yu J. PD-L1 expression in human cancers and its association with clinical outcomes. OncoTargets and therapy. 2016;9:5023-39. 27. Taube JM, Anders RA, Young GD, Xu H, Sharma R, McMiller TL, et al. Colocalization of inflammatory response with B7-h1 expression in human melanocytic lesions supports an adaptive resistance mechanism of immune escape. Sci Transl Med. 2012;4(127):127ra37. 28. Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, Biankin AV, et al. Signatures of mutational processes in human cancer. Nature. 2013;500(7463):415-21. 29. Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in

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non-small cell lung cancer. Science. 2015;348(6230):124-8. 30. Van Allen EM, Miao D, Schilling B, Shukla SA, Blank C, Zimmer L, et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science. 2015;350(6257):207-11. 31. Snyder A, Makarov V, Merghoub T, Yuan J, Zaretsky JM, Desrichard A, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med. 2014;371(23):2189-99. 32. Le DT, Uram JN, Wang H, Bartlett BR, Kemberling H, Eyring AD, et al. PD-1 Blockade in Tumors with Mismatch-Repair Deficiency. N Engl J Med. 2015;372(26):2509-20.

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Figure legends

Figure 1. Kaplan-Meier curves of survival for patients with UIP-ADC and non-UIP ADC. A) Overall survival (OS).

IP T

B) Recurrence-free survival (RFS).

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C) Cancer-specific survival (CSS).

Figure 2. Immunohistochemical scores for UIP-ADC and non-UIP ADC groups.

U

A) Immunohistochemical scores of cancer cells, including ALDH-1, CA IX, Laminin5γ

N

2, PD-L1.

A

B) Immunohistochemical scores of stromal cells, including Podoplanin positive CAFs,

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CA IX positive CAFs, CD204 positive TAMs.

Data are presented as box-and-whisker plots, and p-values were determined using the

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D

Mann-Whitney U test.

Figure 3. Representative views of tumor infiltrating lymphocytes (TILs) in UIP-ADC and

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non-UIP ADC.

CC

A) High-power view of CD8+ TILs in the stroma of UIP-ADC. B) High-power view of Foxp3+ TILs in the stroma of UIP-ADC.

A

C) High-power view of CD8+ TILs in the stroma of non-UIP ADC. D) High-power view of Foxp3+ TILs in the stroma of non-UIP ADC. E) The number of CD8+ TILs, Foxp3+ TILs, and CD8+/Foxp3+ T cell ratio in UIP-ADC and non-UIP ADC groups. P-values were determined using the Mann-Whitney U test.

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Figure 4. The relationship between infiltrating lymphocytes from cancer stroma and noncancerous UIP stroma.

B) High-power view of the area (square) shown in Figure 5A.

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A) Low-power view of UIP stroma (honeycomb lesion) after hematoxylin-eosin staining.

C) High-power view of CD8+ TILs in the same area as shown in Figure 5B.

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D) High-power view of Foxp3+ TILs in the same area as shown in Figure 5B.

E) Changes in CD8+/Foxp3+ T cell ratio between cancer stroma and UIP stroma. P-values

A

CC

EP

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M

A

N

U

were determined using the Wilcoxon signed rank test.

20

21

D

TE

EP

CC

A

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SC R

U

N

A

M

22

D

TE

EP

CC

A

IP T

SC R

U

N

A

M

23

D

TE

EP

CC

A

IP T

SC R

U

N

A

M

24

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A

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Table

Table 1. Clinicopathological characteristics of patients with UIP-ADC. UIP (n＝18) non-UIP (n＝1323) p-value

14 (77.8%)

724 (54.7%)

4 (22.2%)

599 (45.3%)

Yes

17 (94.4%)

761 (57.5%)

No

1 (5.6%)

562 (42.5%)

45 (0-98)

12.5 (0-208)

<0.01

950 (71.8%)

0.38

Male Female

Smoking history

PYS (range) I

8 (44.4%)

Stage

II

9 (50.0%)

III

1 (5.6%)

A

N

Pathological

Ⅳ

LN status

Negative

D

Positive

TE

Unknown

0.06

<0.01

158 (11.9%) 207 (15.7%) 8 (0.6%)

3 (16.7%)

280 (21.2%)

15 (83.3%)

1026 (77.6%)

0 (0%)

0.39

17 (1.2%)

Upper lobe

6 (33.2%)

803 (60.7%)

Middle lobe

0 (0%)

102 (7.7%)

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Location

M

0 (0%)

Pathological

0.01

IP T

67 (20-93)

SC R

Gender

73 (55-91)

U

Age (range)

<0.01

12 (66.8%)

418 (31.6%)

Tumor size

range (cm)

4.2 (2.1-10.0)

2.5 (0.6-22.2)

<0.01

Invasive size

range (cm)

3.6 (0.7-7.0)

2.0 (0-12)

<0.01

LVI

Positive

9 (50%)

578 (43.7%)

0.64

Negative

9 (50%)

745 (56.3%)

Positive

8 (44.4%)

395 (29.9%)

Negative

10 (55.6%)

928 (70.1%)

3 (16.7%)

321 (24.4%)

A

CC

Lower lobe

VPI

Predominant subtype Lepidic

25

0.20

0.25

449 (33.9%)

Micropapillary

1 (5.6%)

16 (1.2%)

Acinar

2 (11.1%)

220 (16.6%)

Solid

4 (22.2%)

290 (21.9%)

IMA

1 (5.6%)

23 (1.7%)

Others

1 (5.6%)

4 (0.3%)

Positive

1 (5.6%)

352 (42.7%)

Negative

17 (94.4%)

473 (57.3%)

IP T

6 (33.2%)

<0.01

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EGFR mutation

Papillary

A

CC

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TE

D

M

A

N

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ADC: adenocarcinoma; IMA: invasive mucinous adenocarcinoma; LVI: lymphovascular invasion; PYS: pack-year smoking; UIP: usual interstitial pneumonia; VPI: visceral pleural invasion

26

Table 2. Prognostic factors for cancer specific survival in all patients (n=1341). Multivariate analysis HR 95%CI p-value

Ref. <0.01 1.205 0.837-1.735 0.31

563 Ref. 778 1.865 1.423-2.445 (cont.) 1.242 1.194-1.292 (cont.) 1.472 1.389-1.559

Ref. <0.01 1.223 0.836-1.787 0.29 <0.01 1.100 0.984-1.230 0.09 <0.01 1.150 1.008-1.313 0.03

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Ref. 1.759 1.352-2.287

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603 738

Ref. 3.956 3.066-5.105

Ref. <0.01 2.004 1.495-2.688 <0.01

1041 283

Ref 5.099 3.958-6.569

<0.01 3.094 2.343-4.086 <0.01

1287 54

Ref. 1.278 0.678-2.408

0.45

1323 18

Ref. 3.866 1.907-7.836

Ref. <0.01 2.844 1.386-5.836 <0.01

M

A

N

U

938 403

D

Age Gender Female Male Smoking status Non-smoker Smoker Total tumor size Invasive size VPI Absence Presence Nodal involvement Absence Presence Surgical procedure Standard Limited UIP pattern Absence Presence

Univariate analysis n HR 95%CI p-value (cont.) 1.009 0.994-1.023 0.24

A

CC

EP

TE

cont.: continuous; Limited: segmentectomy or wedge resection; Ref.: reference; Standard: lobectomy or greater lung resection; UIP: usual interstitial pneumonia, VPI: visceral pleural invasion.

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