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Molecular stratification of metastatic melanoma using gene expression profiling: Prediction of survival outcome and benefit from molecular targeted therapy.

Cirenajwis H, Ekedahl H, Lauss M, Harbst K, Carneiro A, Enoksson J, Rosengren F, Werner-Hartman L, Törngren T, Kvist A, Fredlund E, Bendahl PO, Jirström K, Lundgren L, Howlin J, Borg Å, Gruvberger-Saal SK, Saal LH, Nielsen K, Ringnér M, Tsao H, Olsson H, Ingvar C, Staaf J, Jönsson G - Oncotarget (2015)

Bottom Line: However, this classification does not optimally predict prognosis.In prior studies, we have defined gene expression phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology.We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Sciences, Division of Oncology and Pathology, Lund University, Lund, Sweden.

ABSTRACT
Melanoma is currently divided on a genetic level according to mutational status. However, this classification does not optimally predict prognosis. In prior studies, we have defined gene expression phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology. Herein, we employed a population-based metastatic melanoma cohort and external cohorts to determine the prognostic and predictive significance of the gene expression phenotypes. We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group. Further genetic characterization of melanomas using targeted deep-sequencing revealed similar mutational patterns across these phenotypes. We also used publicly available expression profiling data from melanoma patients treated with targeted or vaccine therapy in order to determine if our signatures predicted therapeutic response. In patients receiving targeted therapy, melanomas resistant to targeted therapy were enriched in the MITF-low proliferative subtype as compared to pre-treatment biopsies (P=0.02). In summary, the melanoma gene expression phenotypes are highly predictive of survival outcome and can further help to discriminate patients responding to targeted therapy.

No MeSH data available.


Related in: MedlinePlus

Gene expression phenotypes and prediction of clinical benefit from molecular targeted therapiesA) Melanoma tumors from patients treated with BRAFi [16] or B) BRAFi/MEKi [17] were classified into the gene expression phenotypes and further analyzed for objective response (RECIST response, %) (4A, upper panel; 4B left panel) and phenotype distribution in pre-treatment and post-relapse biopsies (4A, lower panel; 4B, middle and right panel). C) Gene expression phenotype distribution in patients treated with MAGE-A3 vaccine [14]. The fraction of patients with clinical and no benefit is indicated for each phenotype.
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Figure 4: Gene expression phenotypes and prediction of clinical benefit from molecular targeted therapiesA) Melanoma tumors from patients treated with BRAFi [16] or B) BRAFi/MEKi [17] were classified into the gene expression phenotypes and further analyzed for objective response (RECIST response, %) (4A, upper panel; 4B left panel) and phenotype distribution in pre-treatment and post-relapse biopsies (4A, lower panel; 4B, middle and right panel). C) Gene expression phenotype distribution in patients treated with MAGE-A3 vaccine [14]. The fraction of patients with clinical and no benefit is indicated for each phenotype.

Mentions: In the first dataset (GSE50509, Rizos et al.), 21 patients with BRAF-mutant metastatic melanoma were treated with BRAF inhibitors (BRAFi, dabrafenib or vemurafenib) and evaluated for best objective response (RECIST response, %) and progression-free survival (PFS) [16], followed by gene expression profiling of tumor samples taken pre-treatment and post-relapse. When we classified this dataset into the gene expression phenotypes, we found no clear correlation between the clinical response and the pre-treatment phenotypes owing to small numbers (Figure 4A, upper panel). However, the single MITF-low proliferative sample responded poorly to treatment (RECIST response, %) with only 15 weeks until the patient progressed (patient 30). In contrast, the high-immune response-classified samples had a superior response with more than 25 weeks before progression (except in one case, patient 18) (Figure 4A, upper panel). Interestingly, the phenotype distribution was different in post-relapse samples, with an increased prevalence of MITF-low proliferative-classified cases (P = 0.06, Fisher's exact test; proliferative versus non-proliferative cases, excluding unclassified cases) (Figure 4A, lower panel).


Molecular stratification of metastatic melanoma using gene expression profiling: Prediction of survival outcome and benefit from molecular targeted therapy.

Cirenajwis H, Ekedahl H, Lauss M, Harbst K, Carneiro A, Enoksson J, Rosengren F, Werner-Hartman L, Törngren T, Kvist A, Fredlund E, Bendahl PO, Jirström K, Lundgren L, Howlin J, Borg Å, Gruvberger-Saal SK, Saal LH, Nielsen K, Ringnér M, Tsao H, Olsson H, Ingvar C, Staaf J, Jönsson G - Oncotarget (2015)

Gene expression phenotypes and prediction of clinical benefit from molecular targeted therapiesA) Melanoma tumors from patients treated with BRAFi [16] or B) BRAFi/MEKi [17] were classified into the gene expression phenotypes and further analyzed for objective response (RECIST response, %) (4A, upper panel; 4B left panel) and phenotype distribution in pre-treatment and post-relapse biopsies (4A, lower panel; 4B, middle and right panel). C) Gene expression phenotype distribution in patients treated with MAGE-A3 vaccine [14]. The fraction of patients with clinical and no benefit is indicated for each phenotype.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4494939&req=5

Figure 4: Gene expression phenotypes and prediction of clinical benefit from molecular targeted therapiesA) Melanoma tumors from patients treated with BRAFi [16] or B) BRAFi/MEKi [17] were classified into the gene expression phenotypes and further analyzed for objective response (RECIST response, %) (4A, upper panel; 4B left panel) and phenotype distribution in pre-treatment and post-relapse biopsies (4A, lower panel; 4B, middle and right panel). C) Gene expression phenotype distribution in patients treated with MAGE-A3 vaccine [14]. The fraction of patients with clinical and no benefit is indicated for each phenotype.
Mentions: In the first dataset (GSE50509, Rizos et al.), 21 patients with BRAF-mutant metastatic melanoma were treated with BRAF inhibitors (BRAFi, dabrafenib or vemurafenib) and evaluated for best objective response (RECIST response, %) and progression-free survival (PFS) [16], followed by gene expression profiling of tumor samples taken pre-treatment and post-relapse. When we classified this dataset into the gene expression phenotypes, we found no clear correlation between the clinical response and the pre-treatment phenotypes owing to small numbers (Figure 4A, upper panel). However, the single MITF-low proliferative sample responded poorly to treatment (RECIST response, %) with only 15 weeks until the patient progressed (patient 30). In contrast, the high-immune response-classified samples had a superior response with more than 25 weeks before progression (except in one case, patient 18) (Figure 4A, upper panel). Interestingly, the phenotype distribution was different in post-relapse samples, with an increased prevalence of MITF-low proliferative-classified cases (P = 0.06, Fisher's exact test; proliferative versus non-proliferative cases, excluding unclassified cases) (Figure 4A, lower panel).

Bottom Line: However, this classification does not optimally predict prognosis.In prior studies, we have defined gene expression phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology.We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Sciences, Division of Oncology and Pathology, Lund University, Lund, Sweden.

ABSTRACT
Melanoma is currently divided on a genetic level according to mutational status. However, this classification does not optimally predict prognosis. In prior studies, we have defined gene expression phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology. Herein, we employed a population-based metastatic melanoma cohort and external cohorts to determine the prognostic and predictive significance of the gene expression phenotypes. We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group. Further genetic characterization of melanomas using targeted deep-sequencing revealed similar mutational patterns across these phenotypes. We also used publicly available expression profiling data from melanoma patients treated with targeted or vaccine therapy in order to determine if our signatures predicted therapeutic response. In patients receiving targeted therapy, melanomas resistant to targeted therapy were enriched in the MITF-low proliferative subtype as compared to pre-treatment biopsies (P=0.02). In summary, the melanoma gene expression phenotypes are highly predictive of survival outcome and can further help to discriminate patients responding to targeted therapy.

No MeSH data available.


Related in: MedlinePlus