Nonclassical HLAs, HLA-E and HLA-G, are known to affect clinical outcome in various tumor types. We examined the clinical impact of HLA-E and HLA-G expression in early breast cancer patients, and related the results to tumor expression of classical HLA class I. Our study population (n = 677) consisted of all early breast cancer patients primarily treated with surgery in our center between 1985 and 1995. Tissue microarray sections of arrayed tumor and normal control material were immunohistochemically stained for HLA-E and HLA-G. For evaluation of HLA-E and HLA-G and the combined variable, HLA-EG, a binary score was used. Expression of classical HLA class I molecules was determined previously. HLA-E, HLA-G, and HLA-EG on breast tumors were classified as expression in 50, 60, and 23% of patients, respectively. Remarkably, only in patients with loss of classical HLA class I tumor expression, expression of HLA-E (p = 0.027), HLA-G (p = 0.035), or HLA-EG (p = 0.001) resulted in a worse relapse-free period. An interaction was found between classical and nonclassical HLA class I expression (p = 0.002), suggestive for a biological connection. We have demonstrated that, next to expression of classical HLA class I, expression of HLA-E and HLA-G is an important factor in the prediction of outcome of breast cancer patients. These results provide further evidence that breast cancer is immunogenic, but also capable of evading tumor eradication by the host’s immune system, by up- or downregulation of HLA class Ia and class Ib loci.

There has been strong evidence that tumor progression is controlled by the host’s immune system (1). However, because of their intrinsic genetic unstable nature, tumor cells may acquire properties to escape from immune recognition (2). These poorly immunogenic clones frequently have lost expression of classical HLA class I (HLA-A, HLA-B, and HLA-C), which enables them to escape CTL attack. However, in that case, they may be vulnerable to NK cell elimination. Expression of nonclassical HLA class I molecules (HLA-E and HLA-G), which play a pivotal role in immune surveillance by NK cells, may therefore also determine outcome of tumor–immune interaction (3). Under normal circumstances, expression of the HLA-E molecule is found in most tissues that express HLA-A, -B, -C, or -G molecules and is thought to provide an important “self-signal” to the immune system by accommodating and presenting peptide fragments from leader sequences of these molecules (3, 4). HLA-G expression, in contrast, has very restricted tissue expression and has been mostly found in extravillous trophoblastic cells, where it mediates semiallograft immunotolerance during pregnancy (5). Expression of HLA-E and HLA-G on the cell surface can respectively bind with the inhibitory receptors CD94/NKG2A and KIR2DL4/p49 of NK cells and thereby cause inhibition of their proliferation and cytotoxic effector functions (6, 7). HLA-E also binds activating CD94/NKG2C receptors, present on T and NK cells, however, with a 6-fold lower affinity (8).

Tumors may acquire or upregulate expression of HLA-E and HLA-G as protective property against immune recognition and elimination of tumors (3). HLA-E is regularly expressed in various healthy tissues and correlates with expression of classical HLA class I molecules. This physiological correlation with classical HLA class I molecules has been found to be disturbed in tumors, suggesting that malignant cells which escape T cell immune recognition by downregulation of classical HLA class I expression, may further escape immune recognition by upregulation of HLA-E (9). In addition, expression of HLA-G protects against “missing self” recognition of NK. Expression of this molecule, which is rarely found in healthy tissues, is frequently observed in pathological conditions such as in tumors (10, 11). Previous studies showed that both HLA-E and HLA-G had increased expression in different types of tumor (1215). Studies on the prognostic value of HLA-E expression in colorectal and cervix cancer showed that expression of this molecule correlated to tumor progression and had a trend toward a worse clinical outcome. The prognostic value of HLA-G expression has been investigated in colorectal, gastric, esophageal squamous cell carcinoma, and non-small cell lung cancer and revealed it to be an independent prognostic factor for poor clinical outcome (1619). In addition, expression of HLA-G has also been found in breast cancer; however, no statistically significant associations were found with outcome of patients (2022).

The prognostic effect of HLA-E and HLA-G expression in breast cancer is unknown. The purpose of this study was to analyze the prognostic relevance of expression of HLA-E and HLA-G in a large cohort of early breast cancer patients. Previously, we determined classical HLA class I expression in the same patient cohort. Therefore, we were able to stratify patients based on classical HLA class I expression of tumors and to analyze the impact of HLA-E and HLA-G expression on clinical outcome of early breast cancer patients.

The patient population comprised all nonmetastasized breast cancer patients primarily treated with surgery in the Leiden University Medical Center between 1985 and 1994 (n = 677). Patients with bilateral tumors or a prior history of cancer (other than basal cell carcinoma or cervical carcinoma in situ) were excluded. The following data were known: age, tumor grade, histological type, Tumor-Node-Metastasis stage, local and systemic therapy, locoregional/distant tumor recurrence, secondary tumor, survival, and expression of estrogen receptor (ER), progesterone receptor, and human epidermal growth factor receptor 2 (HER2) (23). All tumors were graded according to current pathological standards by a pathologist (V.T.H.B.M.S). In addition, for about half the cohort of patients (n = 266) a tissue microarray (TMA) of paired histologically normal breast tissue was available. Normal breast tissue originated from the cancer-affected breast but localized more distal from the tumor tissue.

MEM-E/02 (Abcam, Cambridge, U.K.) and 4H84 (Nuclilab, Ede, The Netherlands) Abs were used to recognize HLA-E and HLA-G, respectively. MEM-E/02 reacts specifically with the denatured H chain of human HLA-E24. The 4H84 Ab recognizes denatured HLA-G molecules and has been described to react with classical HLA class I molecules (2527). Tissue sections of 4 μm were cut from a previously constructed TMA of formalin-fixed paraffin-embedded tumors (23). Tissue sections were deparaffinized and rehydrated. For Ag retrieval, 0.01 M Trizma EDTA buffer (pH 6) was used for 10 min at maximum power in a microwave oven. Endogenous peroxidase was blocked for 20 min in 0.3% hydrogen-peroxide methanol. Sections were incubated overnight with primary mAbs using predetermined optimal concentrations. After 30 min of incubation with secondary Ab Envision anti-mouse (K4001; DakoCytomation, Glostrup, Denmark), sections were visualized using diaminobenzidine solution. Tissue section were counterstained with hematoxylin and then dehydrated and finally mounted in malinol. For each primary Ab, all slides were stained simultaneously to avoid interassay variation. For each staining, placenta tissue slides served as positive control. Negative controls were placenta tissue slides that did undergo the whole immunohistochemical staining without primary Abs. Sections of paired normal tissue TMA were stained with MEM-E/02 and 4H84 to assess frequency of staining in normal breast tissue samples.

Tumor staining for classical HLA class I using the mouse mAbs HCA2 and HC10 (anti–HLA-A and anti–HLA-B/C, respectively) was described previously (28).

Microscopic analysis of HLA-E and HLA-G was assessed by two independent observers (A.S., E.M.d.K.) in a blinded manner. Both markers were scored in a binary manner, considering any specific staining of tumor cells as positive expression and no staining as no expression. A combined variable of HLA-E and HLA-G scores was created: HLA-EG. HLA-EG expression was considered positive when both HLA-E and HLA-G were expressed and negative when either HLA-E or HLA-G was not expressed.

Statistical analyses were performed using the statistical package SPSS (version 16.0 for Windows; SPPS, Chicago, IL). Cohen’s κ coefficient was used to assess interobserver agreement in quantification. This revealed a substantial agreement in classification for HLA-E (κ = 0.72) and a very good agreement in classification for HLA-G (κ = 0.90). The χ2 test was used to evaluate associations between various clinicopathological parameters and HLA-E and HLA-G expression. Relapse-free period (RFP) was the time from date of surgery until an event (locoregional recurrence and/or a distance recurrence, whichever came first). Overall survival (OS) was defined as date of surgery until death. The Kaplan-Meier method was used for survival plotting and log-rank test for comparison of survival curves. RFP is reported as cumulative incidence function, after accounting for death as competing risk (29). Cox regression was used for univariate and multivariate analysis for RFP and OS. Significant variables (p < 0.1) in univariate analysis were included in multivariate analysis. To analyze the independent prognostic effect of HLA-E and HLA-G on clinical outcome, tumors were stratified based on a previously determined expression characteristics of classical HLA class I molecules.

We finally analyzed whether the specificity of the anti–HLA-G Ab would interfere with the results of our survival analyses by separately analyzing the set of patients in which those who stained positive for this Ab on normal breast tissue were excluded.

Tumor material was available and incorporated in the TMA of 86% (574 of 677) of the patients. Paired normal breast tissue was available on TMA in 46% (266 of 574) of the patients. Median age of patients was 57 y (range, 23–96 y). Median follow-up of patients alive was 19 y (range, 14–23 y). Clinicopathological and treatment characteristics are shown in Table I.

Table I.
Correlations between HLA-E and HLA-G expression and well-established prognostic factors using χ2 test
HLA-E
HLA-G
Total
No Expression
Expression
No Expression
Expression
N%N%N%p ValueN%N%p Value
Age (y)       0.378     0.221 
 <40 48 8.4 17 6.9 28 11.4  22 7.4 16 7.9  
 40–50 145 25.3 64 25.9 59 24.0  74 24.7 59 29.2  
 50–60 132 23.0 57 23.1 56 22.8  61 20.4 50 24.8  
 ≥60 249 43.4 109 44.1 103 41.9  142 47.5 77 38.1  
Grade       <0.001     0.242 
 I 80 14.2 44 18.1 29 12.0  40 13.4 23 11.8  
 II 282 49.9 132 54.3 105 43.6  158 53.0 92 47.2  
 III 203 35.9 67 27.6 107 44.4  100 33.6 80 41.0  
Histological type       0.094     0.465 
 Ductal 513 90.6 214 87.7 225 93.4  266 89.0 180 92.3  
 Lobular 53 9.4 30 12.3 16 6.6  33 10.1 15 7.7  
Tumor stage       0.094     0.616 
 pT1 211 38.0 96 40.2 87 36.6  112 38.8 67 34.4  
 pT2 272 49.0 108 45.2 128 53.8  142 49.1 103 52.8  
 pT3/4 72 13.0 35 14.6 23 9.7  35 12.1 25 12.8  
Nodal stage       0.332     0.151 
 pN0 307 55.1 138 57.7 129 53.5  159 54.3 112 57.7  
 pN1–3 250 44.9 101 42.3 112 46.5  134 45.7 82 42.3  
ER       0.004     0.095 
 Negative 203 37.6 72 31.4 106 44.7  100 35.3 82 42.9  
 Positive 337 62.4 157 68.6 131 55.3  183 64.7 109 57.1  
Progesterone receptor       0.021     0.499 
 Negative 223 41.6 81 35.1 106 45.9  115 41.1 84 44.2  
 Positive 313 58.4 150 64.9 125 54.1  165 58.9 106 55.8  
Her2 overexpression       0.008     0.014 
 No overexpression 435 80.9 200 87.7 186 78.5  236 84.6 145 75.5  
 Overexpression 103 19.1 28 12.3 51 21.5  43 15.4 47 24.5  
Classical HLA-I       0.003     <0.001 
 Negative 112 21.3 68 30.1 40 17.9  78 28.4 28 14.6  
 Positive 401 69.9 158 69.9 183 82.1  197 71.6 164 85.4  
Local therapy       0.407     0.661 
 MAST−RT 223 38.9 109 44.1 92 37.4  116 38.8 78 38.6  
 MAST+RT 108 18.8 41 16.6 50 20.3  52 17.4 43 21.3  
 BCS-RT 0.9 0.8 0.4  0.7 1.0  
 BCS+RT 238 41.5 95 38.5 103 41.9  129 43.1 79 39.1  
Systemic therapy       0.076     0.004 
 Chemotherapy 112 19.5 37 15.0 57 23.2  43 14.4 52 25.7  
 Endocrine therapy 75 13.1 42 17.0 32 13.0  52 17.4 20 9.9  
 Both 18 3.1 2.8 10 4.1  12 4.0 3.0  
 None 369 64.3 161 65.2 147 59.8  192 64.2 124 61.4  
Total 574 100 247 100 246 100  299 100 202 100  
HLA-E
HLA-G
Total
No Expression
Expression
No Expression
Expression
N%N%N%p ValueN%N%p Value
Age (y)       0.378     0.221 
 <40 48 8.4 17 6.9 28 11.4  22 7.4 16 7.9  
 40–50 145 25.3 64 25.9 59 24.0  74 24.7 59 29.2  
 50–60 132 23.0 57 23.1 56 22.8  61 20.4 50 24.8  
 ≥60 249 43.4 109 44.1 103 41.9  142 47.5 77 38.1  
Grade       <0.001     0.242 
 I 80 14.2 44 18.1 29 12.0  40 13.4 23 11.8  
 II 282 49.9 132 54.3 105 43.6  158 53.0 92 47.2  
 III 203 35.9 67 27.6 107 44.4  100 33.6 80 41.0  
Histological type       0.094     0.465 
 Ductal 513 90.6 214 87.7 225 93.4  266 89.0 180 92.3  
 Lobular 53 9.4 30 12.3 16 6.6  33 10.1 15 7.7  
Tumor stage       0.094     0.616 
 pT1 211 38.0 96 40.2 87 36.6  112 38.8 67 34.4  
 pT2 272 49.0 108 45.2 128 53.8  142 49.1 103 52.8  
 pT3/4 72 13.0 35 14.6 23 9.7  35 12.1 25 12.8  
Nodal stage       0.332     0.151 
 pN0 307 55.1 138 57.7 129 53.5  159 54.3 112 57.7  
 pN1–3 250 44.9 101 42.3 112 46.5  134 45.7 82 42.3  
ER       0.004     0.095 
 Negative 203 37.6 72 31.4 106 44.7  100 35.3 82 42.9  
 Positive 337 62.4 157 68.6 131 55.3  183 64.7 109 57.1  
Progesterone receptor       0.021     0.499 
 Negative 223 41.6 81 35.1 106 45.9  115 41.1 84 44.2  
 Positive 313 58.4 150 64.9 125 54.1  165 58.9 106 55.8  
Her2 overexpression       0.008     0.014 
 No overexpression 435 80.9 200 87.7 186 78.5  236 84.6 145 75.5  
 Overexpression 103 19.1 28 12.3 51 21.5  43 15.4 47 24.5  
Classical HLA-I       0.003     <0.001 
 Negative 112 21.3 68 30.1 40 17.9  78 28.4 28 14.6  
 Positive 401 69.9 158 69.9 183 82.1  197 71.6 164 85.4  
Local therapy       0.407     0.661 
 MAST−RT 223 38.9 109 44.1 92 37.4  116 38.8 78 38.6  
 MAST+RT 108 18.8 41 16.6 50 20.3  52 17.4 43 21.3  
 BCS-RT 0.9 0.8 0.4  0.7 1.0  
 BCS+RT 238 41.5 95 38.5 103 41.9  129 43.1 79 39.1  
Systemic therapy       0.076     0.004 
 Chemotherapy 112 19.5 37 15.0 57 23.2  43 14.4 52 25.7  
 Endocrine therapy 75 13.1 42 17.0 32 13.0  52 17.4 20 9.9  
 Both 18 3.1 2.8 10 4.1  12 4.0 3.0  
 None 369 64.3 161 65.2 147 59.8  192 64.2 124 61.4  
Total 574 100 247 100 246 100  299 100 202 100  

BCS, breast conservative surgery; MAST, mastectomy.

Microscopical quantification was successful in 86% (493 of 574) of tumors for HLA-E and in 87% (501 of 574) for HLA-G. Respectively, 14 and 13% of tumors were damaged or lost on the TMA slides, a problem associated with preparation, staining, and mounting of TMA slides. Two groups, expression versus no expression, were defined for HLA-E and HLA-G (Fig. 1A–D). Expression was found in 50% (247 of 493) and in 60% (299 of 501) of tumors for HLA-E and HLA-G, respectively (Table I). Expression of HLA-EG was found in 23% (100 of 428) of tumors. HLA-G stained positive in 1% (3 of 266) of normal tissue samples (Fig. 1E, 1F), whereas HLA-E showed positive staining in all normal tissue samples (Fig. 1G).

FIGURE 1.

Representative examples of immunohistochemical stainings (original magnification ×10) with MEM-E/02 and 4H84 Abs on mammary tissues, performed according to standard protocols (details in 1Materials and Methods) HLA-E–negative tumor (A), HLA-E–positive tumor (B), HLA-G–negative tumor (C), HLA-G–positive tumor (D), HLA-G–negative normal tissue (E), HLA-G–positive normal tissue (F), and HLA-E–positive normal tissue (G).

FIGURE 1.

Representative examples of immunohistochemical stainings (original magnification ×10) with MEM-E/02 and 4H84 Abs on mammary tissues, performed according to standard protocols (details in 1Materials and Methods) HLA-E–negative tumor (A), HLA-E–positive tumor (B), HLA-G–negative tumor (C), HLA-G–positive tumor (D), HLA-G–negative normal tissue (E), HLA-G–positive normal tissue (F), and HLA-E–positive normal tissue (G).

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In the whole cohort of patients, HLA-E, HLA-G, and HLA-EG showed no statistically significant difference in outcome between expression versus no expression for RFP (log-rank p values, respectively: 0.52, 0.95, and 0.72) or OS (log-rank p values, respectively: 0.86, 0.74, and 0.27) (Figs. 2A, 2D, 2G, 3A, 3D, 3G).

FIGURE 2.

Relapses over time related with HLA-E (A–C), HLA-G (D–F), and HLA-EG (G–I) tumor expression, among the total population (A, D, G), patients with classical HLA class I tumor expression (B, E, H), and patients with loss of classical HLA class I tumor expression (C, F, I). Remarkably, only in patients with loss of classical HLA class I expression, HLA-E, HLA-G, and HLA-EG affect relapses over time. Log-rank p values are shown in each graph.

FIGURE 2.

Relapses over time related with HLA-E (A–C), HLA-G (D–F), and HLA-EG (G–I) tumor expression, among the total population (A, D, G), patients with classical HLA class I tumor expression (B, E, H), and patients with loss of classical HLA class I tumor expression (C, F, I). Remarkably, only in patients with loss of classical HLA class I expression, HLA-E, HLA-G, and HLA-EG affect relapses over time. Log-rank p values are shown in each graph.

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FIGURE 3.

Kaplan Meier analysis of OS related with HLA-E (A–C), HLA-G (D–F), and HLA-EG (G–I) tumor expression, among the total population (A, D, G), patients with classical HLA class I tumor expression (B, E, H), and patients with loss of classical HLA class I tumor expression (C, F, I). Remarkably, only in patients with loss of classical HLA class I expression, HLA-E, HLA-G, and HLA-EG affect OS. Log-rank p values are shown in each graph.

FIGURE 3.

Kaplan Meier analysis of OS related with HLA-E (A–C), HLA-G (D–F), and HLA-EG (G–I) tumor expression, among the total population (A, D, G), patients with classical HLA class I tumor expression (B, E, H), and patients with loss of classical HLA class I tumor expression (C, F, I). Remarkably, only in patients with loss of classical HLA class I expression, HLA-E, HLA-G, and HLA-EG affect OS. Log-rank p values are shown in each graph.

Close modal

Next, we stratified patients based on classical HLA class I tumor expression, classified as expression versus loss. Among the subgroup of classical HLA class I expression results were similar as in the whole cohort of patients: for HLA-E, HLA-G, or HLA-EG, a statistically significant difference was not found for different expression levels in outcome for RFP (log-rank p values, respectively: 0.73, 0.69, and 0.51) or OS (log-rank p values, respectively: 0.64, 0.74, and 0.22) (Figs. 2B, 2E, 2H, 3B, 3E, 3H). Interestingly, among the subgroup of patients with loss of tumor expression of classical HLA class I, HLA-E and HLA-G expression showed significant differences for RFP (log-rank p values, respectively: 0.03 and 0.04) and OS (log-rank p values, respectively: 0.03 and 0.12) between both expression groups (Figs. 2C, 2F, 3C, 3F). Of the patients with no tumor expression of HLA-E or HLA-G, respectively, 60 and 56% of patients were relapse free after 10 y, whereas of the patients with tumor expression of HLA-E or HLA-G, respectively, 35 and 39% of patients were relapse free after 10 y. The combination variable HLA-EG showed, similarly to HLA-E and HLA-G separately, differences in outcome between expression and no expression among the subgroup of classical HLA class I loss, but at a much higher level of significance than each separately (log-rank p values: RFP, 0.001; OS, 0.007) (Figs. 2I, 3I). Among the patients with no expression of HLA-EG, 55% were relapse free after 10 y, compared with 17% for expression of HLA-EG. Cox proportional multivariate analysis was performed for relapses over time including the following factors: tumor stage, lymph node status, ER status, HER2 expression, local therapy, endocrine therapy, and HLA-EG. This analysis revealed that lymph node status and HLA-EG (p = 0.011; hazard ratio [HR], 2.87; 95% CI, 1.28–6.43) were independent factors for RFP among the subgroup of classical HLA class I loss patients (Table II). These data showed that HLA-EG possesses a specific prognostic effect but only among classical HLA class I loss patients. To prove that classical HLA class I and HLA-EG were significantly cooperating variables, an interaction term was introduced in Cox regression analysis. This analysis showed a statistically significant interaction (p = 0.002) between the two markers, suggesting that there is a biological connection between classical HLA class I and HLA-EG.

Table II.
Cox univariate and multivariate analysis for RFPs
Univariate
Multivariate
NHR95% CIp ValueHR95% CIp Value
Age (y)        
 <40 1.00  0.580    
 40-50 37 1.23 0.426–3.544     
 50-60 31 1.54 0.526–4.508     
 >60 46 1.02 0.349–2.949     
Grade        
 I 28 1.00  0.068    
 II 55 1.29 0.661–2.507     
 III 35 2.09 1.048–4.172     
 Histological type        
 Ductal 102 1.00  0.884    
 Other 16 0.95 0.470–1.917     
Tumor stage        
 pT1 46 1.00  0.006 1.00  0.679 
 pT2 55 1.71 0.994–2.953  1.25 0.590–2.644  
 pT3/4 16 2.99 1.526–5.870  0.88 0.260–2.964  
Nodal stage        
 pN− 64 1.00  <0.001 1.00  <0.001 
 pN+ 56 4.10 2.482–6.783  3.60 1.812–7.165  
ER status        
 Negative 37 1.00  0.057 1.00  0.237 
 Positive 83 0.62 0.376–1.014  0.70 0.385–1.266  
Progesterone receptor status        
 Negative 44 1.00  0.202    
 Positive 73 0.73 0.445–1.186     
HER2        
 No overexpression 102 1.00  0.075 1.00  0.069 
 Overexpression 10 1.73 0.947–3.176  2.21 0.939–5.217  
Ki67        
 Ki67− 91 1.00  0.841    
 Ki67+ 26 0.94 0.523–1.695     
Local therapy        
 MAST−RT 46 1.00  <0.001 1.00  0.320 
 MAST+RT 25 2.97 1.631–5.422  2.15 0.796–5.813  
 BCS 51 0.96 0.542–1.703  1.23 0.572–2.663  
Endocrine therapy        
 ET+ 15 1.00  0.048 1.00  0.471 
 ET− 107 0.52 0.273–0.994  0.74 0.318–1.698  
Chemotherapy        
 CT+ 23 1.00  0.130    
 CT− 99 0.65 0.371–1.136     
HLA-EG        
 No expression 81 1.00  0.002 1.00  0.011 
 Expression 12 3.08 1.512–6.251  2.87 1.278–6.430  
Univariate
Multivariate
NHR95% CIp ValueHR95% CIp Value
Age (y)        
 <40 1.00  0.580    
 40-50 37 1.23 0.426–3.544     
 50-60 31 1.54 0.526–4.508     
 >60 46 1.02 0.349–2.949     
Grade        
 I 28 1.00  0.068    
 II 55 1.29 0.661–2.507     
 III 35 2.09 1.048–4.172     
 Histological type        
 Ductal 102 1.00  0.884    
 Other 16 0.95 0.470–1.917     
Tumor stage        
 pT1 46 1.00  0.006 1.00  0.679 
 pT2 55 1.71 0.994–2.953  1.25 0.590–2.644  
 pT3/4 16 2.99 1.526–5.870  0.88 0.260–2.964  
Nodal stage        
 pN− 64 1.00  <0.001 1.00  <0.001 
 pN+ 56 4.10 2.482–6.783  3.60 1.812–7.165  
ER status        
 Negative 37 1.00  0.057 1.00  0.237 
 Positive 83 0.62 0.376–1.014  0.70 0.385–1.266  
Progesterone receptor status        
 Negative 44 1.00  0.202    
 Positive 73 0.73 0.445–1.186     
HER2        
 No overexpression 102 1.00  0.075 1.00  0.069 
 Overexpression 10 1.73 0.947–3.176  2.21 0.939–5.217  
Ki67        
 Ki67− 91 1.00  0.841    
 Ki67+ 26 0.94 0.523–1.695     
Local therapy        
 MAST−RT 46 1.00  <0.001 1.00  0.320 
 MAST+RT 25 2.97 1.631–5.422  2.15 0.796–5.813  
 BCS 51 0.96 0.542–1.703  1.23 0.572–2.663  
Endocrine therapy        
 ET+ 15 1.00  0.048 1.00  0.471 
 ET− 107 0.52 0.273–0.994  0.74 0.318–1.698  
Chemotherapy        
 CT+ 23 1.00  0.130    
 CT− 99 0.65 0.371–1.136     
HLA-EG        
 No expression 81 1.00  0.002 1.00  0.011 
 Expression 12 3.08 1.512–6.251  2.87 1.278–6.430  

BCS, breast conservative surgery; MAST, mastectomy.

The 4H84 Ab has been described to occasionally cross-react with classical HLA class I molecules (27). Therefore, we performed additional immunohistochemical analyses to examine whether this cross-reaction would interfere with our survival results.

Expression on paired normal breast tissue of half the cohort was found in 1% (3 of 266) for HLA-G. These three patients who showed weakly positive staining for HLA-G on normal breast tissue, also stained positive for classical HLA class I on normal and tumor tissue, indicating that the 4H48 Ab possibly occasionally cross-reacted with these classical HLA class I molecules. It should be noted, however, that the staining on normal tissue was only modest when compared with tumor staining with the 4H84 Ab (compare Fig. 1F with 1D). To examine whether the occasional cross-reaction of the 4H84 Ab would interfere with our results, we performed a subanalysis by selecting only the tumors of the 266 patients of whom paired normal tissue was available. In this analysis, we excluded the three cases that showed positive staining for HLA-G on normal breast tissue (the presumed cases which showed cross-reaction for the 4H84 Ab) and examined whether survival analyses would reveal similar results as to when these cases would not be excluded. When excluding these three cases, no survival analyses reached statistical significance (log-rank p ≥ 0.426) in neither the total population of patients nor the patient population with expression of classical HLA class I. This was concordant with the results found without exclusion of these cases (log-rank p ≥ 0.693). Importantly, no expression was seen of HLA-G in normal breast tissue of patients whose tumor showed no classical HLA class I expression, but resulted positive for HLA-G expression. Taken together, these results suggests that the occasional cross-reaction of 4H84 with classical HLA class I molecules did not interfere with our results.

Tumor–immune interaction may be of great importance for clinical outcome (2). In this study we showed that in tumors devoid of classical HLA class I expression, HLA-E and HLA-G expression were of statistically significant influence on outcome of breast cancer patients independently of known clinicopathological parameters, with an almost three times higher risk of relapse over time for patients with expression of HLA-EG compared with patients with no expression of HLA-EG. This is the first study, to our knowledge, providing evidence for a prognostic value of nonclassical HLA class I molecule expression in a large cohort of breast cancer patients. In addition, to our knowledge, we are the first to report that such an effect on outcome of patients interplays with expression of classical HLA class I molecules. Importantly, these results can be explained by underlying biology and support and add to previous studies on tumor–immune interaction in breast cancer (3, 1219).

Previous studies have found elevated expression levels of the non-classical HLA class I molecules, HLA-E and HLA-G, in tumor tissues (3, 1219). Normally, HLA-G is not expressed on nonmalignant cells. Corresponding to this fact, we found in our study that 4H84 HLA-G Ab did stain in a considerable number of tumor tissues but in a negligible number of normal mammary tissues. Under normal circumstances, HLA-E surface expression is dependent on the availability of HLA class I signal sequence-derived peptides. Therefore, HLA-E surface expression is usually found to be coexpressed with classical HLA class I, which comes to expression in almost all healthy tissues (3, 4). Corresponding to this fact, we did not find any normal mammary tissue that did not express HLA-E molecules. In some tumor tissue, however, HLA-E expression seems to be independent of the availability of classical HLA class I sequence-derived peptides and can be expressed in cells that lack classical HLA class I expression (9, 30). Indeed, we found cytoplasmic expression of HLA-E in classical HLA class I-negative tumors in our study. The disturbed balances of expression of classical HLA class I, HLA-E and HLA-G, as found in our study, suggest a cooperation between these molecules in evading immune recognition. According to the immunoediting hypothesis, tumors may become shaped through interaction with the immune system, leading to the selective outgrowth of highly tumorigenic clones that escape from immune recognition and elimination (31). Downregulation of classical HLA class I expression in tumors, with simultaneous loss of cell surface expression of HLA-E because of lack of peptide fragments that it can bind, is believed to reflect CTL immune escape (3). However, these tumor cells become highly vulnerable to NK cells, which recognize these “missing self” cells (14). Through a variety of factors, such as epigenetic control, hypoxia, stress, and cytokines, expression of HLA-G and HLA-E may be upregulated and counteract this susceptibility to NK cells (3, 10, 32, 33). Supportive for a specific NK cell inhibition of the nonclassical HLA class I molecules, for both HLA-E and HLA-G an inverse correlation was found with NK cell infiltrate in a colorectal cancer and gastric cancer study, respectively (34, 35). In addition, in various studies using colon cancer and melanoma cell lines it was demonstrated that overexpression of HLA-E and HLA-G respectively directly inhibited NK-mediated cell lysis (3539). The statistical interaction between HLA-E and HLA-G with classical HLA class I molecules, as found in our study, adds to this evidence, suggesting that specifically in tumors devoid of classical HLA class I expression, upregulation of HLA-E and HLA-G expression counteracts the resulting NK cell susceptibility, leading to immune escape of tumor cells. Our study supports and adds to previous findings, suggesting that HLA-E and HLA-G contribute to tumor immune escape, specifically NK cells, a phenomenon that is likely to have impact on clinical outcome of patients.

Prognostic associations of HLA-E and HLA-G have been studied in various types of tumors (1619, 30, 35). In cervical cancer, HLA-E expression increased with the progression of the lesion. One study analyzed the prognostic effect of HLA-E expression in colorectal cancer. A statistically significant association with outcome was noticed where high expression of HLA-E resulted in a worse disease-free survival of patients (35). HLA-G expression showed a positive correlation with higher histological grade and clinical stage in colorectal cancer, gastric cancer, epithelial squamous cell carcinomas, and cutaneaous T cell lymphoma. In addition, expression of HLA-G was an independent prognostic factor for a worse outcome of patients in colorectal cancer, epithelial squamous cell carcinomas, and non-small cell lung cancers (16, 18, 19). We described that tumor expression of HLA-E and HLA-G has an independent prognostic influence in breast cancer patients, resulting in a worse patient outcome. Previously, similar results for disease-free survival were found for breast cancer, albeit that these results did not reach statistical significance (20). This study was similar to ours in terms of patients selection criteria and immunohistochemical staining methods but was probably limited by the small number of breast cancer patients studied (n = 43). The results of our study demonstrate for the first time, to our knowledge, a statistically significant association of HLA-E and HLA-G expression with clinical outcome in a large cohort of breast cancer patients, which is particularly revealed in patients with tumors lacking expression of classical HLA class I molecules. Moreover, patients with tumors with simultaneous expression of HLA-E and HLA-G had an increased risk of relapses compared with patients with tumors expressing either HLA-E or HLA-G, a phenomenon that has been previously described as well (13). In addition, we were able to demonstrate a statistical interaction in outcome analyses, indicating that the effect on outcome of HLA-E and HLA-G expression and the effect on outcome of HLA class I expression do not only operate simultaneously, but that the combined effect on outcome of these molecules is more than additive. These data correspond to the hypothesis that tumor expression of the non-classical HLA class I molecules E and G may indeed serve to protect tumor cells from NK-cell attack, but this is mostly relevant in a situation that NK cells are activated (i.e., in case classical HLA class I molecule expression is downregulated [10]).

Taken together, these results provide insights in breast cancer tumorigenesis and provide further evidence that the immune system is able to recognize and eliminate breast cancer cells. However, it is also evident that breast cancer cells are capable of escaping immune attack. A better understanding of the various phases of tumor–immune interactions in breast cancer (i.e., elimination, equilibrium and finally escape) may lead to a better prediction of clinical outcome of patients. Furthermore, this knowledge may be used for the development of tailored immunotherapeutic treatment modalities.

We thank J. Molenaar for help with the database and colleagues at the research laboratory of the surgery department at the Leiden University Medical Center for help and advice.

Disclosures The authors have no financial conflicts of interest.

This work was supported by Dutch Cancer Society Grant UL 2007-3968.

Abbreviations used in this paper:

BCS

breast conservative surgery

ER

estrogen receptor

HER2

human epidermal growth factor receptor 2

HR

hazard ratio

MAST

mastectomy

OS

overall survival

RFP

relapse-free period

TMA

tissue microarray.

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