Fragmentomic analysis of circulating tumor DNA-targeted cancer panels.

BACKGROUND: The isolation of cell-free DNA (cfDNA) from the bloodstream can be used to detect and analyze somatic alterations in circulating tumor DNA (ctDNA), and multiple cfDNA-targeted sequencing panels are now commercially available for Food and Drug Administration (FDA)-approved biomarker indications to guide treatment. More recently, cfDNA fragmentation patterns have emerged as a tool to infer epigenomic and transcriptomic information. However, most of these analyses used whole-genome sequencing, which is insufficient to identify FDA-approved biomarker indications in a cost-effective manner. PATIENTS AND METHODS: We used machine learning models of fragmentation patterns at the first coding exon in standard targeted cancer gene cfDNA sequencing panels to distinguish between cancer and non-cancer patients, as well as the specific tumor type and subtype. We assessed this approach in two independent cohorts: a published cohort from GRAIL (breast, lung, and prostate cancers, non-cancer, n = 198) and an institutional cohort from the University of Wisconsin (UW; breast, lung, prostate, bladder cancers, n = 320). Each cohort was split 70%/30% into training and validation sets. RESULTS: In the UW cohort, training cross-validated accuracy was 82.1%, and accuracy in the independent validation cohort was 86.6% despite a median ctDNA fraction of only 0.06. In the GRAIL cohort, to assess how this approach performs in very low ctDNA fractions, training and independent validation were split based on ctDNA fraction. Training cross-validated accuracy was 80.6%, and accuracy in the independent validation cohort was 76.3%. In the validation cohort where the ctDNA fractions were all <0.05 and as low as 0.0003, the cancer versus non-cancer area under the curve was 0.99. CONCLUSIONS: To our knowledge, this is the first study to demonstrate that sequencing from targeted cfDNA panels can be utilized to analyze fragmentation patterns to classify cancer types, dramatically expanding the potential capabilities of existing clinically used panels at minimal additional cost.

X-linked inhibitor of apoptosis deficiency in the TRAMP mouse prostate cancer model.

Deregulation of apoptotic pathways plays a central role in cancer pathogenesis. X-linked inhibitor of apoptosis protein (XIAP), is an antiapoptotic molecule, whose elevated expression has been observed in tumor specimens from patients with prostate carcinoma. Studies in human cancer cell culture models and xenograft tumor models have demonstrated that loss of XIAP sensitizes cancer cells to apoptotic stimuli and abrogates tumor growth. In view of these findings, XIAP represents an attractive antiapoptotic therapeutic target for prostate cancer. To examine the role of XIAP in an immunocompetent mouse cancer model, we have generated transgenic adenocarcinoma of the mouse prostate (TRAMP) mice that lack XIAP. We did not observe a protective effect of Xiap deficiency in TRAMP mice as measured by tumor onset and overall survival. In fact, there was an unexpected trend toward more aggressive disease in the Xiap-deficient mice. These findings suggest that alternative mechanisms of apoptosis resistance are playing a significant oncogenic role in the setting of Xiap deficiency. Our study has implications for XIAP-targeting therapies currently in development. Greater understanding of these mechanisms will aid in combating resistance to XIAP-targeting treatment, in addition to optimizing selection of patients who are most likely to respond to such treatment.