No abstract

Accurate identification of tumor-derived somatic variants in plasma circulating cell-free DNA (cfDNA) requires understanding the various biologic compartments contributing to the cfDNA pool. We sought to define the technical feasibility of a high-intensity sequencing assay of cfDNA and matched white-blood cell (WBC) DNA covering a large genomic region (508 genes, 2Mb, >60,000X raw-depth) in a prospective study of 124 metastatic cancer patients, with contemporaneous matched tumor tissue biopsies, and 47 non-cancer controls. The assay displayed a high sensitivity and specificity, allowing for de novo detection of tumor-derived mutations and inference of tumor mutational burden, microsatellite instability, mutational signatures and sources of somatic mutations identified in cfDNA. The vast majority of cfDNA mutations (81.6% in controls and 53.2% in cancer patients) had features consistent with clonal hematopoiesis (CH). This cfDNA sequencing approach revealed that CH constitutes a pervasive biological phenomenon emphasizing the importance of matched cfDNA-WBC sequencing for accurate variant interpretation.

Predicting outcomes in men with newly diagnosed prostate cancer is challenging. This study demonstrates that a new molecular test, the Genomic Prostate Score, which can be performed on a patient's original prostate needle biopsy, can predict the aggressiveness of the cancer and help men make decisions regarding the need for immediate treatment of their cancer.

Non-invasive approaches for cell-free DNA (cfDNA) assessment provide an opportunity for cancer detection and intervention. Here, we use a machine learning model for detecting tumor-derived cfDNA through genome-wide analyses of cfDNA fragmentation in a prospective study of 365 individuals at risk for lung cancer. We validate the cancer detection model using an independent cohort of 385 non-cancer individuals and 46 lung cancer patients. Combining fragmentation features, clinical risk factors, and CEA levels, followed by CT imaging, detected 94% of patients with cancer across stages and subtypes, including 91% of stage I/II and 96% of stage III/IV, at 80% specificity. Genome-wide fragmentation profiles across ~13,000 ASCL1 transcription factor binding sites distinguished individuals with small cell lung cancer from those with non-small cell lung cancer with high accuracy (AUC = 0.98). A higher fragmentation score represented an independent prognostic indicator of survival. This approach provides a facile avenue for non-invasive detection of lung cancer.

There is a high degree of concordance among local IHC, central IHC, and central RT-PCR by the proprietary gene assay for ER and PR status. Although ER expression is marginally associated with relapse in ER-positive patients treated with chemohormonal therapy, recurrence score is a highly significant predictor of recurrence.