Limits...
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

Analysis of the mutational landscape in melanoma tumorsA) Genetic events such as mutations, homozygous deletions and focal amplifications in cancer genes within the context of the gene expression phenotypes. Tumors are ordered according to the gene expression phenotypes and the genes of interest. The mutation frequency plot corresponds to the number of somatically acquired mutations observed in the 1697 investigated cancer-associated genes in each melanoma tumor. B) Mutations in genes involved in the MAPK pathway. Tumors are ordered according to mutations in BRAF, NRAS, NF1, KIT, KRAS and CCND1. C). Genetic events in genes involved in the CDKN2A-RB1 pathway. Tumors are ordered according to genetic events in CDKN2A, CDK4, CCND1 and RB1.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4494939&req=5

Figure 2: Analysis of the mutational landscape in melanoma tumorsA) Genetic events such as mutations, homozygous deletions and focal amplifications in cancer genes within the context of the gene expression phenotypes. Tumors are ordered according to the gene expression phenotypes and the genes of interest. The mutation frequency plot corresponds to the number of somatically acquired mutations observed in the 1697 investigated cancer-associated genes in each melanoma tumor. B) Mutations in genes involved in the MAPK pathway. Tumors are ordered according to mutations in BRAF, NRAS, NF1, KIT, KRAS and CCND1. C). Genetic events in genes involved in the CDKN2A-RB1 pathway. Tumors are ordered according to genetic events in CDKN2A, CDK4, CCND1 and RB1.

Mentions: To further characterize the mutational landscape of the gene expression phenotypes, we used targeted deep sequencing to screen for somatic mutations in 1697 cancer-associated genes in tumors from 146 CMM patients. Among these tumors, the mutation burden demonstrated wide heterogeneity, ranging from 5 up to 768 somatic mutations per tumor (Table 1). A small subset of acral lentiginous melanomas (ALMs, n=6) had a significantly lower mutation burden (range: 6-51 mutations), as compared to metastases of unknown origin, superficial spreading or nodular melanoma (P < 0.001, Kruskal-Wallis test). Moreover, the ALMs were all classified as pigmentation tumors. The mutation burden was not significantly different between the gene expression phenotypes (P=0.5, Kruskal-Wallis test) (Table 1). Furthermore, most melanomas harbored the UV-induced mutational signature C -> T preceded by a pyrimidine (Figure 2).


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)

Analysis of the mutational landscape in melanoma tumorsA) Genetic events such as mutations, homozygous deletions and focal amplifications in cancer genes within the context of the gene expression phenotypes. Tumors are ordered according to the gene expression phenotypes and the genes of interest. The mutation frequency plot corresponds to the number of somatically acquired mutations observed in the 1697 investigated cancer-associated genes in each melanoma tumor. B) Mutations in genes involved in the MAPK pathway. Tumors are ordered according to mutations in BRAF, NRAS, NF1, KIT, KRAS and CCND1. C). Genetic events in genes involved in the CDKN2A-RB1 pathway. Tumors are ordered according to genetic events in CDKN2A, CDK4, CCND1 and RB1.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 2: Analysis of the mutational landscape in melanoma tumorsA) Genetic events such as mutations, homozygous deletions and focal amplifications in cancer genes within the context of the gene expression phenotypes. Tumors are ordered according to the gene expression phenotypes and the genes of interest. The mutation frequency plot corresponds to the number of somatically acquired mutations observed in the 1697 investigated cancer-associated genes in each melanoma tumor. B) Mutations in genes involved in the MAPK pathway. Tumors are ordered according to mutations in BRAF, NRAS, NF1, KIT, KRAS and CCND1. C). Genetic events in genes involved in the CDKN2A-RB1 pathway. Tumors are ordered according to genetic events in CDKN2A, CDK4, CCND1 and RB1.
Mentions: To further characterize the mutational landscape of the gene expression phenotypes, we used targeted deep sequencing to screen for somatic mutations in 1697 cancer-associated genes in tumors from 146 CMM patients. Among these tumors, the mutation burden demonstrated wide heterogeneity, ranging from 5 up to 768 somatic mutations per tumor (Table 1). A small subset of acral lentiginous melanomas (ALMs, n=6) had a significantly lower mutation burden (range: 6-51 mutations), as compared to metastases of unknown origin, superficial spreading or nodular melanoma (P < 0.001, Kruskal-Wallis test). Moreover, the ALMs were all classified as pigmentation tumors. The mutation burden was not significantly different between the gene expression phenotypes (P=0.5, Kruskal-Wallis test) (Table 1). Furthermore, most melanomas harbored the UV-induced mutational signature C -> T preceded by a pyrimidine (Figure 2).

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