Sequence capture methods for targeted next generation sequencing promise to massively reduce cost of genomics projects compared to untargeted sequencing. However, evaluated capture methods specifically dedicated to biologically relevant genomic regions are rare. Whole exome capture has been shown to be a powerful tool to discover the genetic origin of disease and provides a reduction in target size and thus calculative sequencing capacity of >90-fold compared to untargeted whole genome sequencing. For further cost reduction, a valuable complementing approach is the analysis of smaller, relevant gene subsets but involving large cohorts of samples. However, effective adjustment of target sizes and sample numbers is hampered by the limited scalability of enrichment systems. We report a highly scalable and automated method to capture a 480 Kb exome subset of 115 cancer-related genes using microfluidic DNA arrays. The arrays are adaptable from 125 Kb to 1 Mb target size and/or one to eight samples without barcoding strategies, representing a further 26 - 270-fold reduction of calculative sequencing capacity compared to whole exome sequencing. Illumina GAII analysis of a HapMap genome enriched for this exome subset revealed a completeness of >96%. Uniformity was such that >68% of exons had at least half the median depth of coverage. An analysis of reference SNPs revealed a sensitivity of up to 93% and a specificity of 98.2% or higher.