Stromal CD8⁺ T-cell Density—A Promising Supplement to TNM Staging in Non–Small Cell Lung Cancer Free

In non–small cell lung cancer (NSCLC), staging according to the tumor–node–metastasis (TNM) system and histologic subtype has been the most relevant clinicopathologic variables for routine prognostication and treatment (1). TNM summarizes data on the extent of tumor burden (T), spread to regional lymph nodes (N) and evidence of metastasis (M). The American Joint Committee of Cancer and the Union Internationale Contre le Cancer (UICC) define and periodically update the TNM classification system (2). In lung cancer, the current 7th edition of the lung cancer staging system is based on an initiative undertaken by the International Association for the Study of Lung Cancer (IASLC; ref. 1). The TNM staging system has shown its value, but provides incomplete prognostic information as clinical outcomes vary among patients in the same TNM stage.

Hence, new strategies to improve outcome prediction and treatment selection are warranted. Extensive literature has demonstrated highly prognostic impact by in situ immune cell infiltrates in tumors. In colorectal cancer, a combination of the density of tumor-infiltrating lymphocytes (TIL; CD3⁺ T cells, pan-lymphocyte marker; CD45RO⁺, memory T cells; CD8⁺ T cells, cytotoxic T cells, CTL) and location (central tumor vs. invasive margins) has defined the Immunoscore as a new component for the classification of colorectal cancer, designated TNM-Immune (TNM-I). An international consortium has been initiated to validate and promote the Immunoscore in the routine clinical colorectal cancer setting (3–6).

The CD8 marker can be found on natural killer and dendritic cells, but is predominantly expressed on the surface on cytotoxic T cells. CD8⁺ T cells are a crucial component of the cellular immune system and are pivotal in cell-mediated antitumor immune responses (7, 8). CD8⁺ T cells undergo a period of massive expansion, activation, and differentiation to cytotoxic T cells with effector functions. Once the pathogenic process is resolved, most effector CD8⁺ cells undergo apoptosis, leaving a subset of long-lived memory cells (9, 10). The association of immune cell infiltrates and prognosis has been reviewed in different malignancies, and in a majority of the studies, memory T cells and cytotoxic T cells are predictive of a favorable clinical outcome (8). In NSCLC, we and others have found CD8⁺ T cells to have significant prognostic effect alone or in combination with other markers (11–16).

Although our group has studied more than 100 prognostic markers related to in situ tumor immunology (11, 13, 14,17, 18), angiogenesis (19–21), and epithelial–mesenchymal transition (22) in NSCLC, stromal CD8⁺ score (CD8⁺ TIL density in the tumor-related stroma) has been one of the markers with the strongest prognostic impact independent of other clinicopathologic variables including TNM classification. Furthermore, cytotoxic CD8⁺ T cells are of increasing interest in lung cancer as novel targeted therapies are aiming to stimulate the immune defense by blocking mechanisms that may inhibit cytotoxic T lymphocytes, e.g., programmed death-1 (PD1), PD-ligand 1 (PD-L1), and cytotoxic T-lymphocyte–associated antigen 4 (CTLA-4; ref. 23).

In the interest of establishing an Immunoscore in resected NSCLC patients, we evaluated our most promising candidate marker, stromal CD8⁺ TIL density, in four different NSCLC cohorts (three Norwegian and one Danish). In the Danish validation set, the impact of tissue microarray (TMA) core localization (central vs. peripheral tumor areas) has been explored (24), allowing us to evaluate the impact of stromal CD8⁺ TILs localization.

Patients surgically resected for stage I–IIIA NSCLC at the University Hospital of North Norway (UNN, Tromso) and Nordland Hospital (NH, Bodo) from 1990 through 2004 were included in this study (19). In the original cohort, 335 patients were included from these two hospitals and results on immunological markers reported in 2008 (11). However, patients have been restaged according to the revised 7th edition of UICC TNM classification and reclassified according to the new pathologic classification of lung cancer, excluding 11 previous bronchioalveolar carcinomas (25, 26). In addition, both cohorts now include follow-up data as of January 2011, hence leaving 155 patients from Tromso and 169 from Bodo. In this study, the Tromso cohort was used as a training cohort to define the optimal prognostic cutoffs for stromal CD8 density. In contrast with the exploratory approach in the Tromso cohort, the cutoffs from the Tromso cohort were set as a predefined scoring system in the validation cohorts (Bodo, Oslo, and Denmark).

Two additional validation cohorts of consecutive NSCLC stage I–IIIA patients from Oslo University Hospital, the Norwegian Radium Hospital (OUS; 2006–2011, n = 295), and Odense University Hospital, Denmark (1992–1999, n = 178), were used.

Exclusion criteria for patients in either the training or validation cohorts were as follows: (i) inadequate paraffin-embedded fixed tissue blocks; (ii) other malignancy within 5 years before NSCLC diagnosis; (iii) radiotherapy or chemotherapy before surgery; and (iv) or less than two cores with tumor stroma evaluable. All study cohorts were approved by the Regional Committee for Medical and Health Research Ethics (Tromso and Bodo: protocol ID: 2011/2503; Oslo: protocol ID 2009/1904; Denmark: protocol ID: 20080018). The reporting of clinicopathologic variables, survival data, and biomarker expression was conducted in accordance with the REMARK guidelines (27).

Lung cancer specimens were histologically reviewed by experienced pathologists. In all cohorts, representative areas of vital tumor tissue were carefully selected and marked on the hematoxylin and eosin stain (H&E) slide and sampled for the TMA blocks. Regardless of cohort, the large majority of the cores showed a mixture of epithelial tumor tissue and tumor-related stroma (Fig. 1). In the Danish cohort, designated cores from the tumor center and from the invasive margin were made (Fig. 1B). In the Norwegian cohorts, the localization of the cores (central tumor vs. invasive margin) was not noted. TMAs were made using a tissue arrayer instrument (Beecher Instruments). The detailed methodology has been previously reported (19, 24). Tromso and Bodo used 0.6-mm cores, whereas Oslo and Denmark used 1.0-mm cores. In all cohorts, multiple 4-μm sections were cut with a Micron microtome before antibody staining for immunohistochemical analysis (Table 1).

CD8⁺ staining is well validated and in routine clinical use at all included hospitals.

In the Norwegian cohorts, Ventana Benchmark, XT automated slide stainer (Ventana Medical System), was used for immunohistochemistry (IHC). For the Tromso/Bodo cohorts, prediluted primary CD8 antibody from Ventana Medical Systems/Roche (clone C8/144, 760-4250) was used, and for the Oslo cohort, prediluted primary CD8 antibody from Roche (clone SP57, 790-4460) was used. The slides were baked for 60°C overnight, deparaffinized in EZ Prep, and submitted to heat-induced epitope retrieval. Cell conditioning-1 protocol (CC1 Mild) for 30 minutes at 95°C epitope retrieval was used for Tromso/Bodo cohorts and CC1 Standard for 60 minutes at 95°C for the Oslo cohort. The endogenous peroxidase activity was quenched using 3% hydrogen peroxide. The primary antibody was applied and the slides were incubated for 32 minutes at 36°C, followed by washing in buffer and visualization. Visualization method was carried out with the Iview DAB Detection Kit for Tromso/Bodo cohorts and the ultraview DAB Detection Kit for the Oslo cohort. 3,3′-diaminobenzidine was used as a chromogen for all cohorts.

In the Danish cohort, Ventana Benchmark, Ultra automated slide stainer (Ventana Medical System), was used. The primary antibody CD8 was from Dako M7103 (clone C8/144B). The slides were baked at 75°C for 4 minutes, deparaffinized in EZ Prep, and submitted to heat-induced epitope retrieval. CC1 Mild for 36 minutes at pH 8.5 and 99°C was used. The endogenous peroxidase activity was quenched using 3% hydrogen peroxide. The primary antibody dilution was applied and the slides were incubated for 32 minutes at 36°C, followed by washing in buffer and visualization using the OptiView DAB Detection Kit with 3,3′-diaminobenzidine as a chromogen.

Negative and positive staining controls were placed simultaneously with all TMAs. In all cohorts, slides were counterstained with hematoxylin to visualize the nuclei. For each cohort, staining was done in one single experiment.

To validate different IHC procedures, new TMA slides from Denmark were stained and reevaluated with the same IHC procedure as for the Oslo cohort.

In all cohorts, samples were anonymized and independently scored by two experienced pathologists in the Norwegian cohorts (K. Al-Shibli and S. Al-Saad in the Tromso and Bodo cohorts; S. Al-Saad and E. Richardsen in the Oslo cohort) and one experienced pathologist (K.E. Olsen) and one oncologist (M. Poehl) in the Danish cohort. The second scoring of the Danish cohort (validating the staining procedure/scoring) was done by S. Al-Saad and E. Richardsen. In case of disagreement, the slides were reexamined and the observers reached a consensus. By light microscopy, the tissue sections were scored for the degree of infiltration of CD8⁺ lymphocytes. The percentages of CD8⁺ lymphocytes compared with the total amount of nucleated cells in the stromal compartments were assessed. Based on experiences from one of our previous studies (11), scoring cutoff points at 5%, 25%, or 50% for each core according to the degree of cell densities were used in the training set (Tromso cohort): 0% to 5% = 0, 5% to 25% = 1, 25% to 50% = 2, and >50% = 3. In this training cohort, only 2 patients had an average or maximum score evaluated as 0; hence, scores 0 and 1 were merged and the following cutoffs were used in the validation sets: low density: ≤25%; intermediate density: >25% to ≤50%; high density: >50%. These percentages are also easy to follow and reproduce in daily practice. Both the average and the maximum score from each patient were assessed in the training set, resulting in an optimal significant prognostic impact (P = 0.004, endpoint DSS), when using a maximum score. Hence, the maximum score was used in the validation sets.

The Kaplan–Meier method was used to analyze the association between marker expression and survival endpoints. Disease-specific survival (DSS) was determined from the date of surgery to the time of lung cancer death, overall survival (OS) from the date of surgery to death, and disease-free survival (DFS) as the time from the date of surgery to time of first relapse. The statistical significance of differences between survival curves was assessed with the log-rank test. The χ² test was used to examine the association between molecular marker expression and various clinicopathologic variables. In the second IHC score of the Danish cohort, each observer was compared for interobserver reliability by use of a two-way random effect model with absolute agreement definition. The intraclass correlation coefficient (reliability coefficient, ICC) was obtained from these results. Variables with a P value of <0.25 from univariate analyses entered the multivariate analysis, using the Cox proportional hazards model (backward stepwise, probability for stepwise entry and removal was set at 0.05 and 0.10). P values < 0.05 were considered statistically significant.

Demographic, clinical, and histopathologic variables for each cohort and in the total material are listed in Table 1 and Supplementary Tables S1–S3. Median age in the total material was 65.2 (range, 27.5–84.7) years (Table 1). The majority of patients were men (64%), but there was a higher rate of women in the cohort with the most recent inclusion period (Oslo, 49% women). The Oslo cohort also had the highest frequency of adenocarcinomas (63%) compared with 48% in the total population.

The stromal CD8⁺ TIL density score distribution in each cohort is shown in Table 1. There was no significant difference in the stromal CD8⁺ density score (low vs. intermediate vs. high) between the different cohorts (P = 0.18). In the total material, there was no significant correlation between stromal CD8⁺ density and the clinicopathologic variables.

As shown in Supplementary Table S1, tumor differentiation (P < 0.001), pStage (P < 0.001), T stage (P < 0.001), and N stage (P < 0.001) were significant prognostic indicators for DSS in the total material (Supplementary Tables S2 and S3 show the results with DFS and OS as endpoints). Figure 2 presents the prognostic impact of stromal CD8⁺ density in the total material with three different endpoints: DFS (P < 0.001), DSS (P < 0.001), and OS (P < 0.001). Five-year survival rates for stromal CD8⁺ high, intermediate, and low score in the total material were as follows: DFS: 68%, 59%, and 43%; DSS: 74%, 63%, and 49%; OS: 61%, 50%, and 41%, respectively. The prognostic impact in each cohort with DFS and DSS as endpoint is shown in Fig. 3. Using OS as endpoint, the prognostic impact of stromal CD8 density in each cohort was as follows: Tromso (P = 0.004), Bodo (P = 0.28), Oslo (P = 0.22), and Odense (P = 0.11), all showing the same tendency as with DFS and DSS as endpoints.

The frequencies of recurrences, lung cancer–related deaths, and overall deaths in each cohort were as follows: Tromso: 51%, 45%, and 79%; Bodo: 42%, 41%, and 82%; Oslo: 37%, 28%, and 41%; Denmark: 52%, 51%, and 82%, respectively.

When stratified by histology and pStage, CD8⁺ density had significant prognostic impact in all subgroups with DSS as endpoint (Table 2). Using OS as endpoint, all subgroups showed significant prognostic impact, except only showing a tendency in pStage II (P = 0.09), adenocarcinomas (P = 0.09), and large-cell carcinoma (LCC; P = 0.06). Using DFS as endpoint, stromal CD8⁺ density showed significant prognostic impact in all subgroups, except within pStage I (P = 0.07) and LCC (P = 0.29).

In the Danish population, we were able to stratify the stromal CD8 density according to the central parts of the tumor versus the tumor periphery/invasive margins. As shown in Supplementary Fig. S1, the prognostic impact of stromal CD8⁺ density with DSS as endpoint was highly significant at the tumor margins (P = 0.008) in contrast with the central tumor (P = 0.67). CD8⁺ density in the tumor periphery/invasive margins showed 5-year survival rates of 80% (high density), 61% (intermediate density), and 42% (low density). The prognostic impact of stromal CD8 density in the invasive margin was also significant for DFS (P = 0.021) and tended toward significance for OS (P = 0.09).

Results from the multivariate analysis are presented in Table 3. All clinicopathologic variables with P < 0.25 and stromal CD8⁺ density from the univariate analyses were entered into the multivariate analysis. However, as pStage is based on a combination of T stage and N stage, multivariate analysis was done including pStage and not T stage or N stage (Table 3). Pathologic stage, differentiation, and stromal CD8⁺ density were identified as independent prognostic factors regardless of endpoints (DSS, DFS, or OS).

TMAs from the Danish cohort were reevaluated with the same IHC procedure and scored by the same pathologists as for the Oslo cohort. The interobserver reliability coefficient between the scorers was good (ICC = 0.89, P > 0.001). At a patient level (maximum score for each patient), the correlation coefficient, r, was 0.68, kappa value was 0.57, and P < 0.001 when comparing the results from the first and the second staining/scoring. The prognostic impact of stromal CD8⁺ density in the validation of the Danish cohort, using the same predefined cutoffs, was similar to the original results: DFS, P = 0.009 versus P = 0.024; DSS, P = 0.005 versus P = 0.009; OS, P = 0.066 versus P = 0.11.

In this large study of 797 NSCLC patients, stromal CD8⁺ TIL density was a strong independent prognostic factor for DFS, DSS, and OS in the total material. There is a significant prognostic impact or at least the same trend in all four cohorts. Subgroup analyses revealed a significant prognostic impact within each pStage. In the Danish cohort, marker localization was further addressed and the prognostic impact of stromal CD8⁺ TILs was related to an invasive margin/tumor periphery location.

The strength of this study lies in the number of cohorts and validated NSCLC patients. The cutoff was predefined for validation sets. Cutoff points of 25% and 50% are easy to follow and reproduce in daily practice, supported by the fact that the distribution of low, intermediate, and high score was similar in all cohorts and also independent of the core size. Finally, CD8 IHC staining has limited technical challenges, is well validated, and established as a routine marker at most pathologic departments.

Though CD8 is a routine clinical marker, we reevaluated the Danish population to show that the results were independent of the staining and scoring procedure. Some variation in the score is expected due to the fact that new slides provided are from a different depth of the tumor block. Even though the interobserver correlation coefficient was good, this may also to a limited degree affect the score. However, reassuringly, there was a highly significant correlation between the first and the second Danish staining procedure/scoring as well as a similar prognostic impact. However, as the prognostic impact of the intermediate group varies most between the different cohorts, one may consider a two-category approach in a clinical setting.

The size of the TMA cores may also be an issue, but showing the same trends regardless of core size is reassuring as we are evaluating the percentages of lymphocytes compared with the total amount of nucleated cells in the stromal compartment.

In the colorectal TNM-I, several immune cell combinations have been tried and the most promising combination so far has included CD8 and CD3 with scores from both the central parts of the tumor and the invasive margins (3–6). We have previously addressed the issue of localization by examining the prognostic impact of CD8⁺ TILs within the cancer cell nests (epithelial lymphocytes) and in the tumor-related stroma (stromal lymphocytes; ref. 11). We observed stromal CD8⁺ density to have the most promising prognostic impact. We did not, however, distinguish between stroma centrally in the tumor versus at the tumor periphery/invasive margins. Herein, we were not able to address this issue in the three Norwegian cohorts as the stromal CD8⁺ density localization was not registered. However, this could be examined in the Danish validation set because the localizations were recorded as central tumor versus tumor periphery/invasive margins (24). In our previous study, we found the prognostic impact of stromal CD8⁺ density to be superior to CD8⁺ density in the cancer nests. In this study, the Danish cohort shows that the greatest prognostic impact of stromal CD8⁺ TIL density was observed in the tumor periphery/invasive margins. An obvious question is: would the prognostic impact of the total material would further improve if the stromal CD8⁺ density had been scored only at the invasive margins? In our previous study, we used an average value for the cores of each patient (11). In our test set, we observed that a maximum score resulted in a slightly improved prognostic impact compared with the average score. The cores in the Norwegian cohorts are a mix from the central and the periphery of the tumors, and in most cases, we expect one core from each patient to originate from the tumor periphery. This may explain why the maximum score appears to be the best approach. Nevertheless, CD8⁺ TIL localization in the tumor environment is an important matter that needs to be fully addressed in a prospective study.

Besides the localization of TILs, a pivotal question is which combination of immune cells should be included in an NSCLC immunoscore. The prognostic impact of other immune cells, such as B cells, natural killer cells, myeloid-derived suppressor cells, macrophages, regulatory T cells, and subsets of T-helper populations (Th2, Th17), has been shown to differ depending largely on cancer type and stage (8). In contrast, the presence of T cells, cytotoxic T cells, Th1 cells, and memory T cells has been shown to be strongly associated with beneficial clinical outcome for most cancer types (8). In our previous studies, we have explored most of these immune cells and found CD8⁺ cells as one of the most promising candidates (11, 13,14,17, 18). In this study, we have focused on this marker to explore its robustness with the intention to include it in a subsequent prospective clinical study on NSCLC TNM-I. Based on the colorectal cancer TNM-I and previous NSCLC tumor in situ immunology studies, there are other promising immune markers that should also be taken into account with respect to future prospective NSCLC TNM-I studies. These are CD4 (T-helper cell), CD45RO⁺ (memory T cells), and CD3 (pan T-cell marker; refs. 3–6, 8, 11, 17, 18, 28–30).

To establish an NSCLC TNM-I classification, the immune markers included need to add prognostic or predictive impact in a clinical setting. In this study, pStage showed 5-year survival rates of 74% (stage 1), 53% (stage II), and 39% (stage IIIA), whereas stromal CD8⁺ density demonstrates a comparable significant prognostic impact with 5-year DSS rates of 74% (high density), 63% (intermediate density), and 49% (low density). In the Danish validation set, the stromal CD8⁺ density in the tumor periphery/invasive margins showed 5-year survival rates of 80% (high density), 61% (intermediate density), and 42% (low density). More importantly, CD8⁺ density appears to be a significant prognostic marker within each pStage (Table 2). For instance, among stage IIIA patients in the total material, the 5-year DSS is only 18% in low CD8⁺ density group versus 68% in patients with high stromal CD8⁺ density, demonstrating a large variation among patients within the same pStage. Together with pStage, histology has been the most important clinicopathologic variable in clinical NSCLC decision making. The prognostic impact of stromal CD8⁺ density is also significant across all histologic subgroups using DSS as endpoint. The same tendency is seen with DFS and OS as endpoint.

The predictive value of CD8⁺ has not been evaluated in this study, but as cytotoxic CD8⁺ T cells are essential in novel therapies targeting the immune system, e.g., by blocking CD8⁺ T cell–related ligands (PD-L1 and PD-L2) and receptors (PD1 and CTLA-4), this would be of great interest for further investigation (23, 31). As indicated by our previous study (14), the potential predictive impact of stromal CD8⁺ density in an adjuvant NSCLC radiotherapy setting should also be examined. Further, in a recent review, it was indicated that the presence of immune cells largely reflected the underlying biology (3). Hence, immune biomarkers will be both prognostic and predictive more often than non-immuno markers as many treatment modalities affect the immune system.

Even though the stromal CD8⁺ density seems to be reliable, reproducible, clinically relevant, and biologically meaningful, some obstacles must be considered before a prospective clinical study is initiated. TMAs as used in this study are mainly designed to reveal prognostic impact in large populations, whereas the sensitivity and specificity for each patient are crucial in a clinical setting. To better reflect the tumor localization on an individual level, there are some advantages with whole slides as for instance the localization of the cytotoxic T lymphocytes in the central tumor versus invasive margins. The scoring system should be optimized, and the utilization of digital pathology and image analysis software may be advantageous. Further, we have been studying stage I–IIIA NSCLC patients in which resected material was largely accessible. For the majority of NSCLC patients (stage IIIB/IV), only biopsy specimens will be available. In the latter group, the prognostic impact of stromal CD8⁺ density is to our knowledge not clarified and further studies need to be done.

In colorectal cancer, a worldwide task force has started to validate TNM-I in a routine clinical setting, with a goal to implement Immunoscore in colorectal cancer staging. We propose that a similar concept may be useful for NSCLC prognostication and treatment. Stromal CD8⁺ cytotoxic T-cell density seems to be a good candidate marker and should be included in prospective clinical trials in the effort of establishing an Immunoscore for NSCLC.

H.J. Ditzel reports receiving a commercial research grant from Genmab. No potential conflicts of interest were disclosed by the other authors.

Conception and design: T. Donnem, S. Al-Saad, S. Andersen, R.M. Bremnes, L.-T. Busund

Development of methodology: T. Donnem, S.M. Hald, S. Al-Saad, R.M. Bremnes, L.-T. Busund

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): T. Donnem, S.M. Hald, E.-E. Paulsen, S. Al-Saad, O.T. Brustugun, A. Helland, M. Poehl, K.E. Olsen, H.J. Ditzel, O. Hansen, S. Andersen, R.M. Bremnes, L.-T. Busund

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): T. Donnem, S.M. Hald, E.-E. Paulsen, E. Richardsen, S. Al-Saad, T. Kilvaer, O.T. Brustugun, M. Lund-Iversen, M. Poehl, K.E. Olsen, S. Andersen, R.M. Bremnes

Writing, review, and/or revision of the manuscript: T. Donnem, S.M. Hald, E.-E. Paulsen, E. Richardsen, S. Al-Saad, T. Kilvaer, O.T. Brustugun, A. Helland, M. Lund-Iversen, M. Poehl, H.J. Ditzel, O. Hansen, Y. Kiselev, T.M. Sandanger, S. Andersen, F. Pezzella, R.M. Bremnes, L.-T. Busund

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): T. Donnem, S.M. Hald, E. Richardsen, S. Al-Saad, T. Kilvaer, O.T. Brustugun, A. Helland, K.E. Olsen, H.J. Ditzel, Y. Kiselev, S. Andersen, R.M. Bremnes, L.-T. Busund

Study supervision: T. Donnem, R.M. Bremnes, L.-T. Busund

This study was financially supported by the Norwegian Cancer Society and Northern Norway Health Region Authority.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.