No abstract

Purpose Next-generation sequencing (NGS) has transformed genetic research and is poised to revolutionize clinical diagnosis. However, the vast amount of data and inevitable discovery of incidental findings require novel analytic approaches. We therefore implemented for the first time a strategy that utilizes an a priori structured framework and a conservative threshold for selecting clinically relevant incidental findings. Methods We categorized 2016 genes linked with Mendelian diseases into “bins” based on clinical utility and validity, and used a computational algorithm to analyze 80 whole genome sequences in order to explore the use of such an approach in a simulated real-world setting. Results The algorithm effectively reduced the number of variants requiring human review and identified incidental variants with likely clinical relevance. Incorporation of the Human Gene Mutation Database (HGMD) improved the yield for missense mutations, but also revealed that a substantial proportion of purported disease-causing mutations were misleading. Conclusions This approach is adaptable to any clinically relevant bin structure, scalable to the demands of a clinical laboratory workflow, and flexible with respect to advances in genomics. We anticipate that application of this strategy will facilitate pre-test informed consent, laboratory analysis, and post-test return of results in a clinical context.

The overall prevalence with which endogenous tumor Ags induce host T cell responses is unclear. Even when such responses are detected, they do not usually result in spontaneous remission of the cancer. We hypothesized that this might be associated with a predominant phenotype and/or cytokine profile of tumor-specific responses that is different from protective T cell responses to other chronic Ags, such as CMV. We detected significant T cell responses to CEA, HER-2/neu, and/or MAGE-A3 in 17 of 21 breast cancer patients naive to immunotherapy. The pattern of T cell cytokines produced in response to tumor-associated Ags (TAAs) in breast cancer patients was significantly different from that produced in response to CMV or influenza in the same patients. Specifically, there was a higher proportion of IL-2-producing CD8+ T cells, and a lower proportion of IFN-γ-producing CD4+ and/or CD8+ T cells responding to TAAs compared with CMV or influenza Ags. Finally, the phenotype of TAA-responsive CD8+ T cells in breast cancer patients was almost completely CD28+CD45RA− (memory phenotype). CMV-responsive CD8+ T cells in the same patients were broadly distributed among phenotypes, and contained a high proportion of terminal effector cells (CD27−CD28−CD45RA+) that were absent in the TAA responses. Taken together, these results suggest that TAA-responsive T cells are induced in breast cancer patients, but those T cells are phenotypically and functionally different from CMV- or influenza-responsive T cells. Immunotherapies directed against TAAs may need to alter these T cell signatures to be effective.