Prospective molecular profiling of melanoma metastases suggests classifiers of immune responsiveness

Abstract

We amplified RNAs from 63 fine needle aspiration (FNA) samples from 37 s.c. melanoma metastases from 25 patients undergoing immunotherapy for hybridization to a 6108-gene human cDNA chip. By prospectively following the history of the lesions, we could correlate transcript patterns with clinical outcome. Cluster analysis revealed a tight relationship among autologous synchronously sampled tumors compared with unrelated lesions (average Pearson's r = 0.83 and 0.7, respectively, P < 0.0003). As reported previously, two subgroups of metastatic melanoma lesions were identified that, however, had no predictive correlation with clinical outcome. Ranking of gene expression data from pretreatment samples identified approximately 30 genes predictive of clinical response (P < 0.001). Analysis of their annotations denoted that approximately half of them were related to T-cell regulation, suggesting that immune responsiveness might be predetermined by a tumor microenvironment conducive to immune recognition.

Fig. 1

Evolving molecular portraits of metastatic melanoma. Eisen's hierarchical clustering dendrogram of all samples studied applied to 4293 genes allowed by high-stringency filtering (Cy5:Cy3 ratios with a 3-fold change, signal intensity >500 unless other channel >3000 and 75% of the target pixel >1 SD above background). Control samples included: FB, fibroblast cell line derived from a melanoma metastasis; RCC, renal cancer cell line). The minus sign denotes that the melanocyte strain was cultured without growth factors for 48 h. P11-Mel, melanoma cell line derived from P11-a1 FNA; Ocu Mel, FNA of a hepatic metastasis from an ocular melanoma. FNA samples are color coded and numbered according to the identity of the patient (P). The letter after the number refers to lesion identity, whereas the following number refers to the order in which the FNA of that lesion was obtained (0, pretreatment; 1, first FNA after treatment; 2, second). The blue arrow points to the tight clustering of the melanoma cell line with the lesion from which it originated and underlines the ability of FNA-based global transcript analysis to identify clonal relatedness independently of infiltrating normal cells. Most often autologous FNAs clustered together; exceptions are underlined by colored lines consistent with the color assigned to the patient. In particular, the green line at the bottom of the cluster points shows molecular portrait changes in FNAs from P25 in a period spanning 9 months. P25-b1-nr and P25-a2-nr were excised shortly after the FNAs, and representative H&E stains are shown below for P25-b1-nr. Three different histological phenotypes were identified: epithelioid cell melanoma (60% of the lesion); pleiomorphic transition zone (20%); and chondrosarcomatous metaplasia (20%). This neoplastic metaplasia (19) could not be identified in previous samples from the same or other lesions.

Fig. 2

Putative predictors of immune responsiveness. A, highest ranking genes differentially expressed in posttreatment FNAs compared with pretreatment FNAs in lesions that regressed with treatment (top panel). The relative expression of gene markers of specific immune cell populations is represented in the bottom panel separated by a white line. B, highest ranking genes that identify pretreatment lesions with potential for clinical regression separated from immune resistant lesions by a yellow vertical line (A). The relative expression of genes markers of specific immune cell populations is represented in the bottom panel separated by a white line. In both pictures, ratios are displayed according to the central method for display using a normalization factor as recommended by Ross et al. (20).