Profile of immune cells in axillary lymph nodes predicts disease-free survival in breast cancer - PubMed (original) (raw)

Comparative Study

Profile of immune cells in axillary lymph nodes predicts disease-free survival in breast cancer

Holbrook E Kohrt et al. PLoS Med. 2005 Sep.

Abstract

Background: While lymph node metastasis is among the strongest predictors of disease-free and overall survival for patients with breast cancer, the immunological nature of tumor-draining lymph nodes is often ignored, and may provide additional prognostic information on clinical outcome.

Methods and findings: We performed immunohistochemical analysis of 47 sentinel and 104 axillary (nonsentinel) nodes from 77 breast cancer patients with 5 y of follow-up to determine if alterations in CD4, CD8, and CD1a cell populations predict nodal metastasis or disease-free survival. Sentinel and axillary node CD4 and CD8 T cells were decreased in breast cancer patients compared to control nodes. CD1a dendritic cells were also diminished in sentinel and tumor-involved axillary nodes, but increased in tumor-free axillary nodes. Axillary node, but not sentinel node, CD4 T cell and dendritic cell populations were highly correlated with disease-free survival, independent of axillary metastasis. Immune profiling of ALN from a test set of 48 patients, applying CD4 T cell and CD1a dendritic cell population thresholds of CD4 > or = 7.0% and CD1a > or = 0.6%, determined from analysis of a learning set of 29 patients, provided significant risk stratification into favorable and unfavorable prognostic groups superior to clinicopathologic characteristics including tumor size, extent or size of nodal metastasis (CD4, p < 0.001 and CD1a, p < 0.001). Moreover, axillary node CD4 T cell and CD1a dendritic cell populations allowed more significant stratification of disease-free survival of patients with T1 (primary tumor size 2 cm or less) and T2 (5 cm or larger) tumors than all other patient characteristics. Finally, sentinel node immune profiles correlated primarily with the presence of infiltrating tumor cells, while axillary node immune profiles appeared largely independent of nodal metastases, raising the possibility that, within axillary lymph nodes, immune profile changes and nodal metastases represent independent processes.

Conclusion: These findings demonstrate that the immune profile of tumor-draining lymph nodes is of novel biologic and clinical importance for patients with early stage breast cancer.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1

Figure 1. Lymph Node Profile of Sentinel and Axillary Lymph Nodes

Mean and standard error of CD4 and CD8 T cell, CD1a dendritic cell populations as percent of lymph node, and CD4:CD8 cell ratio are shown for (A) SLN (n = 29), ALN (n = 29), and control lymph nodes (n = 10); (E) tumor-involved ALNs (n = 9), tumor-free ALNs (n = 7) from patients with a positive ALND, tumor-free ALNs from patients with a negative ALND (n = 13), and controls (n = 10); (I) SLNs and ALNs stratified by disease recurrence during 5 y of follow-up (11 of 29 with recurrent disease); (L) tumor-involved ALNs stratified by disease recurrence (n = 9); (M) tumor-free ALNs from patients with a positive ALND stratified by disease recurrence (n = 7); and (N) tumor-free ALNs from patients with a negative ALND stratified by disease recurrence (n = 13). Representative 200× images of lymphocyte population (brown staining) and infiltrating tumor (purple staining) by IHC, including CD8 T cells in (B) SLNs, (C) ALNs, and (D) controls; (F) CD4 T cells in tumor-involved ALNs, (G) tumor-free ALNs from patients with a positive ALND, (H) tumor-free ALNs from patients with a negative ALND; and (J) CD1a dendritic cells in ALNs from patients disease-free versus (K) patients who developed recurrence.

Figure 2

Figure 2. Disease-free Survival Analysis of Women with Breast Cancer According to Immune profile Characteristics, Learning Set ALN Series 2, and Test Set

KM curves are shown for (A) median DFS applied to the learning set ALN series 2 (n = 27) and test set (n = 48) according to size of CD4 T cell and CD1a dendritic cell populations within learning set ALN series 2 (second, randomly selected ALN per individual); (B) DFS stratified by size of CD4 T cell and CD1a dendritic cell populations within test set ALNs; and (C) DFS applied to the learning set (n = 29) and test set (n = 48) according to size of ALN CD4 T cell and ALN CD1a dendritic cell populations. Thresholds for ALN CD4 T cell and ALN CD1a dendritic cell populations were determined by ROC curves as applied to the learning set (ALN series 1). Median duration of DFS are indicated; – indicates a median DFS greater than follow-up period, 5 y. Of 29 individuals in learning set ALN series 1, 11 had recurrent disease, and of 27 individuals in learning set ALN series 2, 11 had recurrent disease. Of 48 individuals in the test set of ALNs, 22 had recurrent disease. For ALN selection from the learning set (C), a single ALN was randomly selected from series 1 or series 2 per individual. Adjusted _p_-values were determined by the permuted log-rank statistic for comparison of DFS between groups.

Figure 3

Figure 3. DFS Analysis of Women with Breast Cancer According to Tumor and Immune profile Characteristics, Learning Set ALN Series 1

KM curves are shown for (A) median DFS applied to the learning set, n = 29, according to percent of SLN occupied by infiltrating tumor (determined by IHC), and stratified by tumor stage; (B) DFS according to size of CD4 T cell and CD1a dendritic cell populations within learning set ALN series 1 (first, arbitrarily selected ALN per individual); and (C) DFS stratified both by percent of SLN infiltrated by tumor and tumor stage, and by both axillary node CD4 T cell population and by tumor stage. A comparison of survival by all subgroups and a separate comparison of stratified T2 alone are included (* in [C]). Thresholds for percent tumor infiltration within SLN, ALN CD4 T cell, and ALN CD1a dendritic cell populations were determined by ROC curves as applied to the learning set (SLN and ALN series 1). Median duration of DFS are indicated; – indicates a median DFS greater than follow-up period, 5 y. Of 29 individuals, 11 had recurrent disease. Adjusted _p-_values were determined by the permuted log-rank statistic for comparison of disease-free survival between groups. TI, tumor infiltration.

Figure 4

Figure 4. DFS Analysis of Women with Breast Cancer According to Tumor Stage, T1 and T2, and Immune Profile Characteristics, Learning and Test Sets

KM curves are shown for (A) median DFS applied to the learning set (n = 29) and test set (n = 48) according to tumor stage; (B) DFS stratified by size of ALN CD4 T cell and ALN CD1a dendritic cell populations among individuals with T1 tumors; and (C) DFS stratified by size of ALN CD4 T cell and ALN CD1a dendritic cell populations among individuals with T2 tumors. Thresholds for ALN CD4 T cell and ALN CD1a dendritic cell populations were determined by receiver-operating-characteristic curves as applied to the learning set (ALN series 1). Median duration of DFS are indicated; – indicates a median DFS greater than follow-up period, 5 y. Of 77 individuals, 33 had disease recurrence. Of 41 from individuals with T1 tumors, 15 had recurrent disease. Of 33 individuals with T2 tumors, 15 had disease recurrence. For ALN selection from the learning set, a single ALN was randomly selected from series 1 or series 2 per individual. Adjusted _p_-values were determined by the permuted log-rank statistic for comparison of DFS between groups.

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