No abstract

A number of common driver mutations have been identified in melanoma, but other genetic or epigenetic aberrations are also likely to play a role in the pathogenesis of melanoma and present potential therapeutic targets. Translocations of the anaplastic lymphoma kinase (ALK), for example, have been reported in spitzoid melanocytic neoplasms leading to kinase-fusion proteins that result in immunohistochemically detectable ALK expression. In this study, we sought to determine whether ALK was also expressed in non-spitzoid primary and metastatic cutaneous melanomas. ALK immunohistochemistry (IHC) was performed on 603 melanomas (303 primary and 300 metastatic tumors) from 600 patients. ALK IHC expression was identified in 7 primary and 9 metastatic tumors. In 5 of 7 primary tumors and in 6 of 9 metastatic lesions, the majority of tumor cells were immunoreactive for ALK. In the other two primary and three metastatic lesions, positive staining was identified in less than half of the tumor cells. ALK-positivity was found in the presence or absence of BRAF or NRAS mutations. In contrast to prior observations with ALK-positive Spitz tumors, none of the ALK-positive melanomas harbored a translocation. Instead, the ALK-positive melanomas predominantly expressed the recently described ALK isoform, ALKATI, which lacks the extracellular and transmembrane domains of wild-type ALK, consists primarily of the intracellular tyrosine kinase domain, and originates from an alternative transcriptional initiation (ATI) site within the ALK gene. The findings are clinically relevant as patients with metastatic melanoma who have ALK expression may potentially benefit from treatment with ALK kinase inhibitors.

BackgroundAccurate inference of genetic ancestry is of fundamental interest to many biomedical, forensic, and anthropological research areas. Genetic ancestry memberships may relate to genetic disease risks. In a genome association study, failing to account for differences in genetic ancestry between cases and controls may also lead to false-positive results. Although a number of strategies for inferring and taking into account the confounding effects of genetic ancestry are available, applying them to large studies (tens thousands samples) is challenging. The goal of this study is to develop an approach for inferring genetic ancestry of samples with unknown ancestry among closely related populations and to provide accurate estimates of ancestry for application to large-scale studies.MethodsIn this study we developed a novel distance-based approach, Ancestry Inference using Principal component analysis and Spatial analysis (AIPS) that incorporates an Inverse Distance Weighted (IDW) interpolation method from spatial analysis to assign individuals to population memberships.ResultsWe demonstrate the benefits of AIPS in analyzing population substructure, specifically related to the four most commonly used tools EIGENSTRAT, STRUCTURE, fastSTRUCTURE, and ADMIXTURE using genotype data from various intra-European panels and European-Americans. While the aforementioned commonly used tools performed poorly in inferring ancestry from a large number of subpopulations, AIPS accurately distinguished variations between and within subpopulations.ConclusionsOur results show that AIPS can be applied to large-scale data sets to discriminate the modest variability among intra-continental populations as well as for characterizing inter-continental variation. The method we developed will protect against spurious associations when mapping the genetic basis of a disease. Our approach is more accurate and computationally efficient method for inferring genetic ancestry in the large-scale genetic studies.Electronic supplementary materialThe online version of this article (10.1186/s12864-017-4166-8) contains supplementary material, which is available to authorized users.

No abstract

Supplementary data are available at Bioinformatics online.

LINKED CONTENT This article is linked to Thwaites et al papers. To view these articles, visit https://doi.org/10.1111/apt.17126 and https://doi.org/10.1111/apt.17268