Tumor-associated immune responses have polarized effects in regulating tumor growth. Although a clear association has been shown between the tumor immune response and clinical outcome in colorectal and ovarian cancers, the role of immune markers for stratifying prognosis in non–small cell lung cancer (NSCLC) is less defined. Herein, we review the prognostic significance of published immune markers in the tumor microenvironment and peripheral blood of NSCLC patients. To identify prognostic immune genes, we reviewed all published gene-profiling studies in NSCLC and delineated the significance of immune genes by doing subanalysis on the microarray database of the NIH Director's Challenge study. This first comprehensive review of prognostic immune markers provides a foundation for further investigating immune responses in NSCLC. Clin Cancer Res; 17(16); 5247–56. ©2011 AACR.

Translational Relevance

Recurrence in lung cancer continues to pose a major clinical challenge, with rates of recurrence as high as 40% among early-stage patients who undergo resection with curative intent. This number highlights the need for additional prognostic markers and therapeutic targets. The host immune response to tumor is a critical component in tumor progression and a prognostic marker in colorectal and ovarian cancers. In this first comprehensive review of immune markers of non–small cell lung cancer (NSCLC) in (i) the tumor microenvironment, (ii) peripheral blood, and (iii) gene-profiling studies, we identify those immune markers that are prognostic. This review provides a foundation for future studies investigating tumor immunology in NSCLC.

Immune responses within the tumor microenvironment are increasingly implicated as a determining factor in tumor progression and aggressiveness. Understanding these responses has allowed investigators to use immune markers to stratify prognosis of colorectal and ovarian cancer patients (1, 2). High levels of intratumoral effector memory cells in colorectal cancer and CD3+ T cells in ovarian cancer are associated with prolonged survival.

Published studies investigating immune markers as prognosticators in non–small cell lung cancer (NSCLC) are heterogeneous in histology (adenocarcinoma, squamous cell, and large cell) and stage (I–IV). In this review, we have identified prognostic immune markers in the tumor microenvironment and peripheral blood, as well as tumor expression of immune genes. The immune genes, from 17 published NSCLC gene-profiling studies, were evaluated for prognostic significance in the NIH Director's Challenge microarray (3), the largest multicenter gene-profiling study to date.

Tumor-infiltrating lymphocytes

The interaction between tumor and immune cells in the tumor microenvironment is influenced by the type of immune cells [CD8+, CD4+, CD20+, and forkhead box P3 (FoxP3+); see Table 1], their density (as counted microscopically), and location (tumor nest and stroma; ref. 4). Among T lymphocytes, which comprise 80% of tumor-infiltrating lymphocytes (TIL) in NSCLC (5), CD8+ cytotoxic lymphocytes form the effector arm of adaptive immunity and are thought to have protective roles against tumors. However, 5 investigations in NSCLC show no correlation between CD8+ TIL infiltration and survival (6–10). Pertinent to NSCLC patients is the fact that CD8+ T-cell predominance is a characteristic of smoking-related chronic obstructive pulmonary disease (11), and it is thought to drive the progression of emphysema (12). In mouse models, activation of CD8+ T cells is impaired in the presence of cigarette smoke (13, 14), perhaps explaining this finding in NSCLC patients. In fact, studies that report correlation between CD8+ TILs and prognosis contradict each other (15, 16). Ruffini and colleagues showed, in their investigation of 1,290 NSCLC tumors, that TILs, mostly CD8+, were associated with prolonged survival, but only in a subset of squamous cell carcinomas (n = 549; ref. 15). This finding is contrasted by Wakabayashi and colleagues, who correlated tumoral CD8+ and shorter overall survival (OS) in NSCLC, especially in adenocarcinoma (16). Examining the functional significance of CD8+ T cells, Trojan and colleagues analyzed the mRNA ratio of IFN-γ to CD8, in which IFN-γ is an effector cytokine secreted by cytotoxic T cells, specifically in peritumoral areas and within tumor nests. Although the number of peritumoral CD8+ T cells correlated with the IFN-γ/CD8 ratio, this association was not observed intratumorally (8). This study suggests that, whereas the CD8+ T cells are able to infiltrate the tumor, they are not able to mount a robust antitumor response once within the tumor nest.

Table 1.

Summary of tumor-infiltrating immune cells in lung cancer with respect to their phenotypes and location

RoleAuthorNo. pointsStagesObservation and/or conclusionSurvival advantage
TIL Johnson et al. (7) 95 I, 54 (57%)   
   II, 17 (18%) High CD3+ and S100+ in tumor correlated with longer OS  
   III, 20 (21%)   
 Hiraoka et al. (9) 109 I, 67 (61%) Concurrent high CD4+ and CD8+ in stroma correlated with longer survival  
   II–III, 42 (39%)   
 Kikuchi et al. (10) 161 I, 95 (59%) HLA class I expression correlates with longer OS in stage I  
   II–IV, 66 (41%) HLA class I expression correlated with CD8+ cells  
 Ruffini et al. (15) 1,290 I, 714 (55%)   
   II, 265 (21%) TIL (mostly CD8+) in tumor correlated with better OS  
   IIIA, 214 (17%)   
 Wakabayashi et al. (16) 178 I, 107 (60%) High CD4+ in stroma correlated with longer OS 5-year OS 64% versus 43% 
   II, 23 (13%) High CD8+ in tumor correlated with shorter OS 5-year OS 47% versus 60% 
   IIIA, 48 (27%)   
 Al-Shibli et al. (17) 335 I, 212 (63%) High CD4+ in stroma correlated with longer DSS 5-year DSS 63% versus 42% 
   II, 91 (27%) High CD8+ in stroma correlated with longer DSS 5-year DSS 75% versus 53% 
   IIIA, 32 (10%) High CD20+ in stroma correlated with longer DSS 5-year DSS 61% versus 32% 
 Pelletier et al. (18) 113 I, 66 (58%)   
   II, 20 (18%) Peritumoral CD20+ correlated with longer survival  
   III, 29 (26%)   
Ti-BALT Dieu-Nosjean et al. (19) 74 I, 62 (84%) IIA, 12 (16%) High mature DCs in tertiary lymphoid structures correlated with longer survival 4-year DFS 88% versus 51% 
      
Treg Shimizu et al. (20) 100 I, 68 (68%) High FoxP3+ correlated with shorter time to recurrence  
   II, 14 (14%) COX-2 expression correlated with shorter time to recurrence  
   III, 18 (18%) COX-2 expression correlated with FoxP3+ infiltration  
 Petersen et al. (23) 64 I, 64 High proportion of FoxP3+ among TIL in tumor correlated with shorter DFS Median DSS of 53 months, 63 months, and >72 months for high, intermediate, and low risk group 
      
TAM Chen et al. (25) 35 I, 14 (40%) TAM in stroma correlated with shorter OS  
   II, 4 (11%) TAM-tumor interaction upregulated IL-8 mRNA expression Median OS 16 months versus 45 months 
   III, 17 (49%)   
 Zeni et al. (26) 47 I, 24 (51%) IL-10 high TAMs associated with shorter OS  
   II–IV, 23 (49%) IL-10 high TAMs associated with advanced stage  
 Ho et al. (27) 68 I, 24 (35%)   
   II, 15 (22%) III, 29 (43%) Increased high TREM-1 macrophages correlated with shorter DFS and OS Median DFS 22 months versus not reached 
     Median OS 29 months versus not reached 
 Kim et al. (28) 144 I, 79 (55%)   
   II, 25 (17%) TAM in tumor correlated with longer OS 5-year OS 64% versus 39% 
   III, 38 (26%)   
 Welsh et al. (29) 175 I, 79 (45%)   
   II, 44 (25%) High TAM in tumor correlated with longer OS 5-year OS of 53% versus 8% 
   IIIA, 34 (19%)   
 Ohri et al. (32) 40 I, 26 (65%)   
   II, 8 (20%) Increased M1 in long survivors  
   III, 6 (15%)   
 Ohtaki et al. (33) 170 IA, 95 (56%) IB–IIIA, 75 (44%) High stromal CD204+ (M2) associated with shorter survival 5-year OS of 61% versus 89% 
RoleAuthorNo. pointsStagesObservation and/or conclusionSurvival advantage
TIL Johnson et al. (7) 95 I, 54 (57%)   
   II, 17 (18%) High CD3+ and S100+ in tumor correlated with longer OS  
   III, 20 (21%)   
 Hiraoka et al. (9) 109 I, 67 (61%) Concurrent high CD4+ and CD8+ in stroma correlated with longer survival  
   II–III, 42 (39%)   
 Kikuchi et al. (10) 161 I, 95 (59%) HLA class I expression correlates with longer OS in stage I  
   II–IV, 66 (41%) HLA class I expression correlated with CD8+ cells  
 Ruffini et al. (15) 1,290 I, 714 (55%)   
   II, 265 (21%) TIL (mostly CD8+) in tumor correlated with better OS  
   IIIA, 214 (17%)   
 Wakabayashi et al. (16) 178 I, 107 (60%) High CD4+ in stroma correlated with longer OS 5-year OS 64% versus 43% 
   II, 23 (13%) High CD8+ in tumor correlated with shorter OS 5-year OS 47% versus 60% 
   IIIA, 48 (27%)   
 Al-Shibli et al. (17) 335 I, 212 (63%) High CD4+ in stroma correlated with longer DSS 5-year DSS 63% versus 42% 
   II, 91 (27%) High CD8+ in stroma correlated with longer DSS 5-year DSS 75% versus 53% 
   IIIA, 32 (10%) High CD20+ in stroma correlated with longer DSS 5-year DSS 61% versus 32% 
 Pelletier et al. (18) 113 I, 66 (58%)   
   II, 20 (18%) Peritumoral CD20+ correlated with longer survival  
   III, 29 (26%)   
Ti-BALT Dieu-Nosjean et al. (19) 74 I, 62 (84%) IIA, 12 (16%) High mature DCs in tertiary lymphoid structures correlated with longer survival 4-year DFS 88% versus 51% 
      
Treg Shimizu et al. (20) 100 I, 68 (68%) High FoxP3+ correlated with shorter time to recurrence  
   II, 14 (14%) COX-2 expression correlated with shorter time to recurrence  
   III, 18 (18%) COX-2 expression correlated with FoxP3+ infiltration  
 Petersen et al. (23) 64 I, 64 High proportion of FoxP3+ among TIL in tumor correlated with shorter DFS Median DSS of 53 months, 63 months, and >72 months for high, intermediate, and low risk group 
      
TAM Chen et al. (25) 35 I, 14 (40%) TAM in stroma correlated with shorter OS  
   II, 4 (11%) TAM-tumor interaction upregulated IL-8 mRNA expression Median OS 16 months versus 45 months 
   III, 17 (49%)   
 Zeni et al. (26) 47 I, 24 (51%) IL-10 high TAMs associated with shorter OS  
   II–IV, 23 (49%) IL-10 high TAMs associated with advanced stage  
 Ho et al. (27) 68 I, 24 (35%)   
   II, 15 (22%) III, 29 (43%) Increased high TREM-1 macrophages correlated with shorter DFS and OS Median DFS 22 months versus not reached 
     Median OS 29 months versus not reached 
 Kim et al. (28) 144 I, 79 (55%)   
   II, 25 (17%) TAM in tumor correlated with longer OS 5-year OS 64% versus 39% 
   III, 38 (26%)   
 Welsh et al. (29) 175 I, 79 (45%)   
   II, 44 (25%) High TAM in tumor correlated with longer OS 5-year OS of 53% versus 8% 
   IIIA, 34 (19%)   
 Ohri et al. (32) 40 I, 26 (65%)   
   II, 8 (20%) Increased M1 in long survivors  
   III, 6 (15%)   
 Ohtaki et al. (33) 170 IA, 95 (56%) IB–IIIA, 75 (44%) High stromal CD204+ (M2) associated with shorter survival 5-year OS of 61% versus 89% 

In contrast to CD8+ lymphocytes, stromal CD4+ (16, 17), CD20+ (17, 18), and colocalization of stromal CD8+ and CD4+ cells (9) have all shown association with improved survival. The significance of immune cell colocalization is highlighted in a study by Dieu-Nosjean and colleagues, who showed the presence of tertiary de novo lymphoid structure in the tumor microenvironment, which they named the tumor-induced bronchus-associated lymphoid tissue (Ti-BALT; ref. 19). In their investigation of 74 stage I to IIA NSCLCs, the presence of mature dendritic cells [DC; lysosome-associated membrane protein (Lamp+)] in Ti-BALT correlates with higher density of T and B lymphocytes and, more importantly, prolonged OS and disease-free survival (DFS; 4-year DFS of 51% versus 88%). The investigators postulated that effector immune cell colocalization within Ti-BALT could play a role in activating an antitumor immune response.

Regulatory T cells

Regulatory T cells (Treg) suppress the host immune response and are thought to promote tumor growth. The protumor association of Treg tumor infiltration was examined by Shimizu and colleagues in a study of stage I to III 100 NSCLC tumors, showing that tumor-infiltrating FoxP3+ Tregs correlate with cyclooxygenase-2 (COX-2) expression and increased tumor recurrence (20). This finding is supported by preclinical findings from Sharma and colleagues, who showed that tumor-derived COX-2 and its product prostaglandin E2 (PGE2) induced in vitro lymphocyte expression of FoxP3. In vivo, inhibition of COX-2 reduced Treg activity, attenuated FoxP3 expression in TILs, and decreased tumor burden (21). Furthermore, urinary PGE-M, the major metabolite of PGE2, was proposed as a biomarker to predict response to COX-2 inhibitors in NSCLC patients (22). Petersen and colleagues showed that the Treg/TIL combination risk index (the ratio of FoxP3+ to CD3+) correlates with disease-specific survival (DSS) in patients with stage I NSCLC (23). Patients with high-risk tumors (30% of tumors) experienced worse DSS (median 53 months) when compared with patients with intermediate (63 months) and low-risk tumors (>72 months), who had low FoxP3 and high CD3.

Tumor-associated macrophages

Tumor-associated macrophages (TAM) show both pro- and antitumor effects in the tumor microenvironment (24). Antitumor TAMs in NSCLC are of the M1 phenotype and accumulate intratumorally, whereas protumor TAMs of the M2 phenotype accumulate in the stroma and express interleukin-8 (IL-8), IL-10, and triggering receptor expressed on myeloid cells (TREM-1). IL-8 is an angiogenic factor, and the angiogenic role of TAM in NSCLC has been shown by correlating macrophage density with intratumor microvessel counts and poor patient outcomes (25). By doing reverse transcriptase (RT)-PCR for IL-8 in resected specimens, the study concludes that TAMs lead to poor patient outcome by their angiogenic role through IL-8 production. IL-10 is an immunosuppressive cytokine, and its expression by TAM has been observed more commonly in stages II, III, and IV, thus correlating with decreased OS (26). TAM expression of TREM-1, which can initiate and amplify an inflammatory response, is increased in malignant pleural effusions of NSCLC patients (27). Furthermore, in 68 stage I to III NSCLC patients, an increased level of TREM-1 high TAMs in resected specimens was an independent predictor of shorter OS.

In contrast to these findings, TAMs have also been associated with prolonged survival in a study of 144 stage I to IV NSCLCs (28). Recent studies have shed light on these contradictory findings, in which TAMs have been classified according to their location and phenotype. In an investigation of 175 stage I to III NSCLC tumors, Welsh and colleagues found that CD68+ macrophages in the stroma are associated with poor prognosis (5-year OS of 27% versus 35%), whereas intratumoral macrophages are associated with increased survival (5-year OS of 53% versus 8%; ref. 29).

Phenotypically, TAMs are comprised of 2 distinct types: M1, proinflammatory with antitumor activity, and M2, which are immunosuppressive, angiogenic, and protumor (30, 31). In a nested case–control study, 20 long-survival patients (median 93 months) had high tumor infiltration of the M1 phenotype compared with 20 poor-survival patients (median 8 months). M1 was characterized by the expression of human leukocyte antigen (HLA)-DR, inducible nitric oxide synthase (iNOS), myeloid-related protein (MRP) 8/14, and tumor necrosis factor (TNF)-α (32). Contrasting the antitumor association of M1 TAMs, high numbers of CD204+ M2 TAMs in stroma have been shown to correlate with decreased OS (33). CD204+ TAMs are also associated with increased tumor expression of IL-10 and monocyte chemoattractant protein (MCP)-1, 2 molecules that are known to attract macrophages.

Tumor-associated neutrophils

Similar to TAMs, tumor-associated neutrophils (TAN) also have polarized functions. Although no published studies have investigated the role of TAN in human NSCLC, recent preclinical work by Fridlender and colleagues showed that in mouse models of lung cancer, TGF-β induces a population of TAN with protumor function (N2), whereas TGF-β blockade results in antitumor neutrophils (N1; ref. 34). Depletion of these N1 neutrophils resulted in increased tumor growth.

Peripheral blood lymphocytes

The universal availability of peripheral blood lymphocyte count has led to its investigation as a prognostic marker in NSCLC. In resected NSCLC patients (n = 177; 72% stages I and II), increasing total lymphocyte counts were associated with lower hazard ratios (HR) for death [HR 0.62, confidence interval (CI), 0.43–0.9; P = 0.012; ref. 35]. The same study further identified neutrophil to lymphocyte ratio (NLR) as a superior predictor of survival compared with pathologic stage (P = 0.001; ref. 35). Specifically, an NLR of >3.81 was found to be a significant predictor of survival in patients with stage I NSCLC. As for the tumor-promoting Tregs, they have been observed at an increased level in the peripheral blood of NSCLC patients compared with normal healthy volunteers (36, 37). These reports correlate with elevated serum and plasma levels of TGF-β and IL-10, both known promoters of Treg development, in NSCLC patients compared with healthy controls (38, 39). Peripheral blood levels of Tregs, TGF-β, and IL-10, however, have not been investigated in predicting clinical outcome of NSCLC patients.

Myeloid-derived suppressor cells

Myeloid-derived suppressor cells (MDSC) represent a heterogeneous population of myeloid cells comprising immature macrophages, granulocytes, and DCs at early stages of differentiation that have protumor effects. MDSCs are mobilized from bone marrow into the peripheral blood by tumor-derived factors and accumulate in the tumor microenvironment, in which they exert their protumor effect by inhibiting T-cell proliferation and activation (40). Similar to Tregs, increased levels of MDSCs, marked by CD11b+/CD14−/CD15+/CD33+, were observed in the peripheral blood of advanced stage NSCLC patients (n = 87) compared with healthy controls (41). In addition, high levels of MDSCs were associated with decreased levels of CD8+ T cells, further supporting the protumor effect of MDSCs. No study to date, however, has investigated the prognostic significance of MDSCs in the tumor microenvironment of patient samples.

Stromal CD4+ lymphocytes, especially colocalized with CD8+ lymphocytes, stromal CD20+ B lymphocytes, Ti-BALT, and intratumoral macrophages (M1), are associated with prolonged survival in NSCLC. In contrast, FoxP3+ Tregs, stromal macrophages (M2), and their associated cytokines, IL-8, IL-10, and TREM-1, are associated with poor prognosis. Tumor expression and secretion of COX-2 and IL-10, respectively, lead to shorter survival. These prognostically significant findings are summarized in Fig. 1.

Figure 1.

Prognostic immune markers in NSCLC. T cells and B cells are associated with longer survival when found in the stroma along with Ti-BALT, which contains Lamp+ DCs. In contrast, FoxP3+ Tregs in the tumor are associated with shorter survival. Antitumor M1 macrophages are characterized by HLA-DR, iNOS, MRP, and TNF-α. Protumor M2 macrophages express CD204. M2 expression of IL-8, IL-10, and TREM-1 (delineated by arrows) has been shown to correlate with shorter survival. Tumoral expression of COX-2 recruits FoxP3+ Treg cells, whereas expression of IL-10 and MCP-1 recruits M2 macrophages. In the peripheral blood, immune suppression is associated with poor clinical outcomes revealed by low total lymphocyte counts (TLC) and elevated NLRs.

Figure 1.

Prognostic immune markers in NSCLC. T cells and B cells are associated with longer survival when found in the stroma along with Ti-BALT, which contains Lamp+ DCs. In contrast, FoxP3+ Tregs in the tumor are associated with shorter survival. Antitumor M1 macrophages are characterized by HLA-DR, iNOS, MRP, and TNF-α. Protumor M2 macrophages express CD204. M2 expression of IL-8, IL-10, and TREM-1 (delineated by arrows) has been shown to correlate with shorter survival. Tumoral expression of COX-2 recruits FoxP3+ Treg cells, whereas expression of IL-10 and MCP-1 recruits M2 macrophages. In the peripheral blood, immune suppression is associated with poor clinical outcomes revealed by low total lymphocyte counts (TLC) and elevated NLRs.

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In the large, multisite, blinded validation study examining lung adenocarcinoma (NIH Director's Challenge), 1 of the four prognostic gene clusters contained genes related to immunologic function (3). Further pathway analysis showed immune function to be important in stratifying lung adenocarcinomas into prognostic subgroups (42). In addition to the NIH Director's Challenge study, we reviewed all published genomic studies done on lung cancer between 2000 and 2010 that used mRNA microarray or RT-PCR. From the 17 studies reviewed (total of 1,615 patients; Supplementary Table S1; refs. 3, 43–58), we identified the prognostic genes related to immune and/or inflammatory response (search and/or selection criteria shown in Supplementary Fig. S1), resulting in a list of 84 genes (Supplementary Table S2).

As shown in Fig. 2, 7 overlapping immune genes are identified from the 17 reviewed studies, and 2 genes are from a well-investigated chemokine axis in NSCLC, C-C motif chemokine 19 (CCL19)/C-C chemokine receptor type 7 (CCR7). CCR7 is a chemokine receptor expressed on naïve T cells, DCs, natural killer cells, and B cells, and its interaction with its ligands, CCL19 and C-C motif chemokine 21 (CCL21), plays a central role in lymphocyte trafficking and homing to lymph nodes (59, 60). In lung cancer, CCR7 expression on tumor cells by mRNA has been shown as an independent predictor of lymph node metastasis in an investigation of 71 NSCLC patients (61). It has been hypothesized that, when expressed on tumor cells, the homing mechanism of CCR7 contributes to the tumor's increased potential for lymphatic metastasis.

Figure 2.

Prognostic genes associated with immunity and inflammation. Prognostic immune/inflammatory genes from published gene profile studies on lung cancer are represented. Each published study is denoted by a circle with the number of overlapping immune genes between studies shown in parentheses, with overlapping immune genes shown in boxes.

Figure 2.

Prognostic genes associated with immunity and inflammation. Prognostic immune/inflammatory genes from published gene profile studies on lung cancer are represented. Each published study is denoted by a circle with the number of overlapping immune genes between studies shown in parentheses, with overlapping immune genes shown in boxes.

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Although CCR7 may increase the metastatic potential of tumor cells, investigators have attempted to exploit the effect of this chemokine axis on the immune cells to promote tumor regression. CCL19, or Epstein-Barr virus–induced molecule 1 ligand chemokine (ELC), which is expressed in the T-cell zone of lymph nodes and DCs, is known to attract immune cells that express CCR7. Although no clinical study has investigated the role of CCL19 in NSCLC, its ability to promote tumor infiltration of T cells and DCs has been shown in preclinical models to decrease tumor burden. Intratumoral injection of CCL19 led to increased influx of CD4+ and CD8+ T cells and DCs, increase in antitumor factors such as IFN-γ and IL-12, and a decrease in the immunosuppressive molecule TGF-β (62, 63).

CCL21, the other ligand of CCR7, has been investigated as a potential adjunct to DC-based therapy, owing to its ability in promoting colocalized tumor infiltration of DCs and lymphocyte effector cells (64). Intratumoral injection of DCs transduced to express CCL21 reduced tumor burden in a mouse model of spontaneous bronchoalveolar carcinoma. On the basis of these findings, a phase I clinical trial is currently investigating the intratumoral injection of CCL-21–expressing DCs in stage IIIb to IV NSCLC patients refractory to standard therapy (65).

A Cox proportional hazards model was used to evaluate the association between DFS and the expression profiles of the 84 identified prognostic immune genes in the Director's Challenge data set (3). This analysis revealed 17 genes that were significantly associated with recurrence (Table 2). We employed the Ingenuity Pathway analysis to examine the networks shared by the 17 genes (Fig. 3). STAT3 was a common signal transduction pathway highlighted in this analysis, which has been implicated in cancer inflammation and immunity (66).

Figure 3.

Ingenuity Pathway analysis of 17 significant immune genes. The data set containing gene identifiers was uploaded into the application. Each identifier was mapped to its corresponding object in Ingenuity's Knowledge Base. A P value cut-off of 0.05 was set to identify molecules whose expression was significantly differentially regulated. These molecules, called Network Eligible molecules, were overlaid onto a global molecular network developed from information contained in Ingenuity's Knowledge Base. Networks of Network Eligible Molecules were then algorithmically generated on the basis of their connectivity.

Figure 3.

Ingenuity Pathway analysis of 17 significant immune genes. The data set containing gene identifiers was uploaded into the application. Each identifier was mapped to its corresponding object in Ingenuity's Knowledge Base. A P value cut-off of 0.05 was set to identify molecules whose expression was significantly differentially regulated. These molecules, called Network Eligible molecules, were overlaid onto a global molecular network developed from information contained in Ingenuity's Knowledge Base. Networks of Network Eligible Molecules were then algorithmically generated on the basis of their connectivity.

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Table 2.

Prognostic immune genes of statistical significance following computational analysis and their functions

Gene symbolP value (HR)Gene nameFunction
LIME1 (20q13.3) 0.0007 (1.0036) LCK-interacting transmembrane adaptor 1 Involved in BCR-mediated signaling in B cells 
   Involved in TCR-mediated T-cell signaling in T cells 
IL7R (5p13) 0.0012 (0.9993) IL-7 receptor subunit alpha; CD127 Receptor for IL-7 
   Expressed at high levels on naïve T cells 
CD59 (11p13) 0.0034 (0.9997) CD59 glycoprotein Potent inhibitor of the complement MAC action 
  MAC inhibitory protein  
RHOH (4p13) 0.0102 (0.9977) Rho-related GTP-binding protein RhoH Negative regulator of hematopoietic progenitor cell proliferation, survival, and migration 
CYFIP2 (5q33.3) 0.0109 (0.9989) Cytoplasmic FMR1-interacting protein 2 Involved in T-cell adhesion 
   Stimulates a migratory response in CD4+ lymphocytes, monocytes, and eosinophils 
IL16 (15q26.3) 0.0128 (0.9880) IL-16 Primes CD4+ T cells for IL-2 and IL-15 responsiveness 
  Lymphocyte chemoattractant factor Induces T-lymphocyte expression of IL-2 receptor 
IFI35 (17q21) 0.0184 (1.0007) IFN-induced 35-kDa protein Unknown 
ENPP2 (8q24.1) 0.0192 (0.9996) Ectonucleotide pyrophosphatase family member 2 Involved in several motility-related processes 
  Autotaxin  
CXCR4 (2q21) 0.0247 (0.9997) C-X-C chemokine receptor type 4 Receptor for CXCL12 
  Stromal cell-derived factor 1 receptor  
BMP7 (20q13) 0.0292 (1.0061) Bone morphogenic protein 7 Induces cartilage and bone formation 
CCR7 (17q12–21.2) 0.0311 (0.9986) C-C chemokine receptor type 7 Receptor for MIP-3β 
MS4A1 (11q12) 0.0351 (0.9993) B-lymphocyte antigen CD20 Involved in the regulation of B-cell activation and proliferation 
CCR6 (6q27) 0.0405 (0.9907) C-C chemokine receptor type 6 Receptor for MIP-3α 
CCL19 (9p13) 0.0432 (0.9996) CCL19 protein Plays a role in inflammatory and immunologic responses and also in normal lymphocyte recirculation and homing 
   Plays a role in trafficking of T cells in thymus, and T-cell and B-cell migration to secondary lymphoid organs 
CCL8 (17q11.2) 0.0446 (1.0009) C-C motif chemokine 8 monocyte chemotactic protein 2 Chemotactic factor that attracts monocytes, lymphocytes, basophils, and eosinophils 
CCR2 (3p21.31) 0.0446 (0.9975) C-C chemokine receptor type 2 MCP 1 receptor Receptor for the MCP-1, 3, and 4 
BST2 (19p13.1) 0.0468 (1.0002) Bone marrow stromal antigen 2 tetherin; CD317 Involved in pre–B-cell growth 
 
Gene symbolP value (HR)Gene nameFunction
LIME1 (20q13.3) 0.0007 (1.0036) LCK-interacting transmembrane adaptor 1 Involved in BCR-mediated signaling in B cells 
   Involved in TCR-mediated T-cell signaling in T cells 
IL7R (5p13) 0.0012 (0.9993) IL-7 receptor subunit alpha; CD127 Receptor for IL-7 
   Expressed at high levels on naïve T cells 
CD59 (11p13) 0.0034 (0.9997) CD59 glycoprotein Potent inhibitor of the complement MAC action 
  MAC inhibitory protein  
RHOH (4p13) 0.0102 (0.9977) Rho-related GTP-binding protein RhoH Negative regulator of hematopoietic progenitor cell proliferation, survival, and migration 
CYFIP2 (5q33.3) 0.0109 (0.9989) Cytoplasmic FMR1-interacting protein 2 Involved in T-cell adhesion 
   Stimulates a migratory response in CD4+ lymphocytes, monocytes, and eosinophils 
IL16 (15q26.3) 0.0128 (0.9880) IL-16 Primes CD4+ T cells for IL-2 and IL-15 responsiveness 
  Lymphocyte chemoattractant factor Induces T-lymphocyte expression of IL-2 receptor 
IFI35 (17q21) 0.0184 (1.0007) IFN-induced 35-kDa protein Unknown 
ENPP2 (8q24.1) 0.0192 (0.9996) Ectonucleotide pyrophosphatase family member 2 Involved in several motility-related processes 
  Autotaxin  
CXCR4 (2q21) 0.0247 (0.9997) C-X-C chemokine receptor type 4 Receptor for CXCL12 
  Stromal cell-derived factor 1 receptor  
BMP7 (20q13) 0.0292 (1.0061) Bone morphogenic protein 7 Induces cartilage and bone formation 
CCR7 (17q12–21.2) 0.0311 (0.9986) C-C chemokine receptor type 7 Receptor for MIP-3β 
MS4A1 (11q12) 0.0351 (0.9993) B-lymphocyte antigen CD20 Involved in the regulation of B-cell activation and proliferation 
CCR6 (6q27) 0.0405 (0.9907) C-C chemokine receptor type 6 Receptor for MIP-3α 
CCL19 (9p13) 0.0432 (0.9996) CCL19 protein Plays a role in inflammatory and immunologic responses and also in normal lymphocyte recirculation and homing 
   Plays a role in trafficking of T cells in thymus, and T-cell and B-cell migration to secondary lymphoid organs 
CCL8 (17q11.2) 0.0446 (1.0009) C-C motif chemokine 8 monocyte chemotactic protein 2 Chemotactic factor that attracts monocytes, lymphocytes, basophils, and eosinophils 
CCR2 (3p21.31) 0.0446 (0.9975) C-C chemokine receptor type 2 MCP 1 receptor Receptor for the MCP-1, 3, and 4 
BST2 (19p13.1) 0.0468 (1.0002) Bone marrow stromal antigen 2 tetherin; CD317 Involved in pre–B-cell growth 
 

Abbreviations: BCR, B-cell antigen receptor; TCR, T-cell antigen receptor; MAC, membrane attack complex; MIP-3β, macrophage inflammatory protein 3 beta; MIP-3α, macrophage inflammatory protein 3 alpha.

Although prognostic immune genes are identified in NSCLC, the cells of origin (tumor cells, tumor-infiltrating immune cells, or both) of these genes remain to be explored. One of the 17 prognostic genes, IL-7R, is expressed by both the tumor and immune cells. When expressed on the tumor, IL-7R expression leads to upregulation of VEGF-D in vitro and also shorter OS in NSCLC patients (67). On the other hand, it has been shown in vitro that the expression of IL-7R on CD8+ T cells signifies a long-lived memory phenotype (68). How the expression of these genes modulates the tumor immune microenvironment is a future area of investigation. CXCR4 is the receptor for stromal-derived factor-1alpha (CXCL12). In lung adenocarcinoma, tumor expression of CXCL12 has been shown to correlate with accumulation of CXCR4-expressing immune cells, 30% of which were protumor regulatory T cells (69).

The immune microenvironment surrounding the tumor is influenced by interactions among tumor, immune cells (TILs, TAMs, TANs, and MSDCs), and cytokines, which shift the environment to pro- or antitumor. In NSCLC, stromal CD4+ T lymphocytes, especially colocalized with CD8+ T cells, stromal CD20+ B lymphocytes, Ti-BALT, and intratumoral M1 macrophages predicted prolonged patient survival. FoxP3+ Tregs and stromal M2 macrophages are associated with poor clinical outcome. We examined gene expression profiling studies for insights into the NSCLC tumor microenvironment. In reviewing 17 gene profile studies, we identified 17 prognostic immune genes by comparing their expression to tumor recurrence in lung adenocarcinoma patients. Further studies using RT-PCR and immunohistochemical analysis are necessary to determine the source cell (tumor versus immune) and how they influence the tumor immune microenvironment. Future studies investigating a large patient series uniform in histology and stage and assessing tumor-immune interaction in both tumor nest and tumor-associated stroma may yield significant information.

No potential conflicts of interest were disclosed.

We thank Eduardo Morales (figure) and Erlin Daley (editorial) for their assistance in preparation of the manuscript.

Supported in part by American Association of Cancer Research (AACR) Lung Cancer Translational Research Award; American Association for Thoracic Surgery (AATS),Third Edward D. Churchill Research Scholarship; International Association for the Study of Lung Cancer (IASLC) Young Investigator Award; National Lung Cancer Partnership/LUNGevity Foundation Research Grant; William H. Goodwin and Alice Goodwin and the Commonwealth Foundation for Cancer Research and the Experimental Therapeutics Center; New York State Empire Clinical Research Investigator Program (ECRIP); and Stony Wold-Herbert Fund.

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Supplementary data