Immune signatures predict prognosis in localized cancer

Abstract

The host immune response can impact cancer growth, prognosis, and response to therapy. In colorectal cancer, the presence of cells involved with T-cell-mediated adaptive immunity predicts survival better than the current staging method. We used the expression of genes recently associated with host immune responses (T(H1)-mediated adaptive immunity, inflammation, and immune suppression) to perform hierarchical clustering of multiple large cohorts of cancer specimens to determine if immune-related gene expression resulted in clinical significant groupings of tumors. Microarray data from prostate cancer (n = 79), breast cancer (n = 132), lung cancer (n = 84), glioblastoma multiforme (n = 120), and lymphoma (n = 127) were analyzed. Among adenocarcinomas, the T(H1)-mediated adaptive immunity genes were consistently associated with better prognosis, while genes associated with inflammation and immune suppression were variably associated with outcome. Specifically, increased expression of the T(H1)-mediated adaptive immunity genes was associated with good prognosis in breast cancer patients under 45 years of age (p = .04, hazard ratio [HR] = 0.42) and in prostate cancer patients (p = .03, HR = 0.36) but not in lung cancer patients (p = 0.45, HR = 1.37). In lymphoma, patients with increased expression of inflammation and immune suppression genes had better prognosis than those expressing the T(H1)-mediated adaptive immunity genes (p = .01, HR = 0.43) and in glioblastoma multiforme, the expression of inflammation genes conferred improved prognosis than those expressing immune suppression genes (p = 0.05, HR = 0.62). In aggregate, the gene expression signatures implicating specific components of the immune response hold prognostic import across solid tumors.

Figure 1

Hierarchical clustering of prostate adenocarcinoma samples based on immune genes revealed four distinct clusters. Cluster 4 with increased expression of adaptive immunity and inflammation genes was identified to have improved prognosis (p = .03). Red represents high expression, and blue represents low expression.

Figure 2

Hierarchical clustering of breast adenocarcinoma samples (age <45 years) based on immune genes revealed two distinct clusters. Cluster 2 with increased expression of adaptive immunity genes was identified to have improved prognosis (p = .04). Red represents high expression, and blue represents low expression.

Figure 3

Hierarchical clustering of breast adenocarcinoma samples (age <45 yaers) based on immune genes revealed four distinct clusters. Cluster 1 with increased expression of adaptive immunity genes was identified to have improved prognosis (p = .01).

Figure 4

Hierarchical clustering of breast adenocarcinoma samples (age <45 years) based on immune genes revealed three distinct clusters. Cluster 3 with increased expression of adaptive immunity genes was identified to have improved prognosis (p = .02).

Figure 5

Hierarchical clustering of breast adenocarcinoma samples (all ages) based on immune genes revealed four distinct clusters. No cluster was identified to have improved prognosis.

Figure 6

Hierarchical clustering of breast adenocarcinoma samples (age >65 years) based on immune genes revealed two distinct clusters. No cluster was identified to have improved prognosis.

Figure 7

Hierarchical clustering of lung adenocarcinoma samples based on immune genes revealed three distinct clusters. No cluster was identified to have improved prognosis.

Figure 8

Hierarchical clustering of lymphoma samples based on immune genes revealed four distinct clusters. Cluster 3 with increased expression of adaptive immunity genes was found to have poorer prognosis (p = .01).

Figure 9

Hierarchical clustering of glioblastoma multiforme samples based on immune genes revealed three distinct clusters. Cluster 3 with increased inflammation gene was identified to have improved prognosis (p = .05).