Ovarian cancer is a leading cause of death for women worldwide in part due to ineffective screening methods. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model with the combined features, we detected ovarian cancer with specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I-IV, respectively.
View Article and Find Full Text PDFCirculating cell-free DNA (cfDNA) is emerging as an avenue for cancer detection, but the characteristics of cfDNA fragmentation in the blood are poorly understood. We evaluate the effect of DNA methylation and gene expression on genome-wide cfDNA fragmentation through analysis of 969 individuals. cfDNA fragment ends more frequently contained CCs or CGs, and fragments ending with CGs or CCGs are enriched or depleted, respectively, at methylated CpG positions.
View Article and Find Full Text PDFGenetic changes in repetitive sequences are a hallmark of cancer and other diseases, but characterizing these has been challenging using standard sequencing approaches. We developed a de novo kmer finding approach, called ARTEMIS (Analysis of RepeaT EleMents in dISease), to identify repeat elements from whole-genome sequencing. Using this method, we analyzed 1.
View Article and Find Full Text PDFSomatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. We analyzed whole-genome sequencing data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional mutation type-specific frequencies in tissue and cell-free DNA from patients with cancer that were associated with replication timing and other chromatin features. A machine-learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected >90% of patients with lung cancer, including those with stage I and II disease.
View Article and Find Full Text PDFBackground: The diagnostic workup of individuals suspected of having lung cancer can be complex and protracted because conventional symptoms of lung cancer have low specificity and sensitivity.
Research Question: Among individuals with symptoms of lung cancer, can a blood-based approach to analyze cell-free DNA (cfDNA) fragmentation (the DNA evaluation of fragments for early interception [DELFI] score) enhance evaluation for the possible presence of lung cancer?
Study Design And Methods: Adults were referred to Bispebjerg Hospital (Copenhagen, Denmark) for diagnostic evaluation of initial imaging anomalies and symptoms consistent with lung cancer. Numbers and types of symptoms were extracted from medical records.
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.
View Article and Find Full Text PDFIn this study, we incorporate analyses of genome-wide sequence and structural alterations with pre- and on-therapy transcriptomic and T cell repertoire features in immunotherapy-naive melanoma patients treated with immune checkpoint blockade. Although tumor mutation burden is associated with improved treatment response, the mutation frequency in expressed genes is superior in predicting outcome. Increased T cell density in baseline tumors and dynamic changes in regression or expansion of the T cell repertoire during therapy distinguish responders from non-responders.
View Article and Find Full Text PDFDespite progress in immunotherapy, identifying patients that respond has remained a challenge. Through analysis of whole-exome and targeted sequence data from 5,449 tumors, we found a significant correlation between tumor mutation burden (TMB) and tumor purity, suggesting that low tumor purity tumors are likely to have inaccurate TMB estimates. We developed a new method to estimate a corrected TMB (cTMB) that was adjusted for tumor purity and more accurately predicted outcome to immune checkpoint blockade (ICB).
View Article and Find Full Text PDFWith the advent of precision oncology, there is an urgent need to develop improved methods for rapidly detecting responses to targeted therapies. Here, we have developed an ultrasensitive measure of cell-free tumor load using targeted and whole-genome sequencing approaches to assess responses to tyrosine kinase inhibitors in patients with advanced lung cancer. Analyses of 28 patients treated with anti-EGFR or HER2 therapies revealed a bimodal distribution of cell-free circulating tumor DNA (ctDNA) after therapy initiation, with molecular responders having nearly complete elimination of ctDNA (>98%).
View Article and Find Full Text PDFDespite the initial successes of immunotherapy, there is an urgent clinical need for molecular assays that identify patients more likely to respond. Here, we report that ultrasensitive measures of circulating tumor DNA (ctDNA) and T-cell expansion can be used to assess responses to immune checkpoint blockade in metastatic lung cancer patients ( = 24). Patients with clinical response to therapy had a complete reduction in ctDNA levels after initiation of therapy, whereas nonresponders had no significant changes or an increase in ctDNA levels.
View Article and Find Full Text PDFTo improve our understanding of ovarian cancer, we performed genome-wide analyses of 45 ovarian cancer cell lines. Given the challenges of genomic analyses of tumors without matched normal samples, we developed approaches for detection of somatic sequence and structural changes and integrated these with epigenetic and expression alterations. Alterations not previously implicated in ovarian cancer included amplification or overexpression of ASXL1 and H3F3B, deletion or underexpression of CDC73 and TGF-beta receptor pathway members, and rearrangements of YAP1-MAML2 and IKZF2-ERBB4.
View Article and Find Full Text PDF