Genome-wide repeat landscapes in cancer and cell-free DNA.

Genetic 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 1.2 billion kmers in 2837 tissue and plasma samples from 1975 patients, including those with lung, breast, colorectal, ovarian, liver, gastric, head and neck, bladder, cervical, thyroid, or prostate cancer. We identified tumor-specific changes in these patients in 1280 repeat element types from the LINE, SINE, LTR, transposable element, and human satellite families. These included changes to known repeats and 820 elements that were not previously known to be altered in human cancer. Repeat elements were enriched in regions of driver genes, and their representation was altered by structural changes and epigenetic states. Machine learning analyses of genome-wide repeat landscapes and fragmentation profiles in cfDNA detected patients with early-stage lung or liver cancer in cross-validated and externally validated cohorts. In addition, these repeat landscapes could be used to noninvasively identify the tissue of origin of tumors. These analyses reveal widespread changes in repeat landscapes of human cancers and provide an approach for their detection and characterization that could benefit early detection and disease monitoring of patients with cancer.

Early evaluation of the effectiveness and cost-effectiveness of ctDNA-guided selection for adjuvant chemotherapy in stage II colon cancer.

Background: Current patient selection for adjuvant chemotherapy (ACT) after curative surgery for stage II colon cancer (CC) is suboptimal, causing overtreatment of high-risk patients and undertreatment of low-risk patients. Postoperative circulating tumor DNA (ctDNA) could improve patient selection for ACT. Objectives: We conducted an early model-based evaluation of the (cost-)effectiveness of ctDNA-guided selection for ACT in stage II CC in the Netherlands to assess the conditions for cost-effective implementation. Methods: A validated Markov model, simulating 1000 stage II CC patients from diagnosis to death, was supplemented with ctDNA data. Five ACT selection strategies were evaluated: the current guideline (pT4, pMMR), ctDNA-only, and three strategies that combined ctDNA status with pT4 and pMMR status in different ways. For each strategy, the costs, life years, quality-adjusted life years (QALYs), recurrences, and CC deaths were estimated. Sensitivity analyses were performed to assess the impact of the costs of ctDNA testing, strategy adherence, ctDNA as a predictive biomarker, and ctDNA test performance. Results: Model predictions showed that compared to current guidelines, the ctDNA-only strategy was less effective (+2.2% recurrences, -0.016 QALYs), while the combination strategies were more effective (-3.6% recurrences, +0.038 QALYs). The combination strategies were not cost-effective, since the incremental cost-effectiveness ratio was €67,413 per QALY, exceeding the willingness-to-pay threshold of €50,000 per QALY. Sensitivity analyses showed that the combination strategies would be cost-effective if the ctDNA test costs were lower than €1500, or if ctDNA status was predictive of treatment response, or if the ctDNA test performance improved substantially. Conclusion: Adding ctDNA to current high-risk clinicopathological features (pT4 and pMMR) can improve patient selection for ACT and can also potentially be cost-effective. Future studies should investigate the predictive value of post-surgery ctDNA status to accurately evaluate the cost-effectiveness of ctDNA testing for ACT decisions in stage II CC.

Effectiveness and cost-effectiveness of circulating tumour DNA-guided selection for adjuvant chemotherapy in patients with stage II colon cancer Most patients with stage II colon cancer (CC) are cured by surgery. Therefore, guidelines recommend to only offer adjuvant chemotherapy to patients who have a tumor with high-risk features. However, current selection is suboptimal, leading to recurrence of cancer in 13% of low-risk patients and unnecessary administration of chemotherapy in some high-risk patients. Previous studies indicate that a biomarker, so-called circulating tumour DNA (ctDNA), could improve the selection of high-risk patients for adjuvant chemotherapy, as patients who have detectable ctDNA in their blood after surgery are likely to develop a recurrence. Despite its potential, implementation is still pending. Our study assessed the long-term effectiveness and costs associated with various ctDNA-guided strategies for selecting high-risk patients for adjuvant chemotherapy in stage II CC. We used an health-economic model to simulate a cohort of 1000 Dutch patients with stage II CC from diagnosis to death. Next, we compared the health outcomes and costs of the ctDNA-guided strategies to those when selection is based on the Dutch guideline. We found that a combination of the Dutch guideline and ctDNA was the most effective strategy, but not cost-effective. Additional analyses showed that ctDNA-guided selection were cost-effective if the costs of the ctDNA test were below 1500 euros, if the ctDNA test performed significantly better, or if patients with detectable ctDNA responded better to chemotherapy. Thus, while post-surgery ctDNA status is a good indicator for recurrence risk, specific criteria related to ctDNA test performance and costs, in addition to combining ctDNA with current high-risk features, should be met to achieve cost-effective implementation. Looking ahead, future studies should explore how patients with detectable ctDNA respond to chemotherapy for next assessments of the cost-effectiveness of ctDNA-guided strategies in selecting patients with stage II CC for adjuvant chemotherapy.

DNA methylation and gene expression as determinants of genome-wide cell-free DNA fragmentation.

Circulating 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. Higher levels and larger sizes of cfDNA fragments are associated with CpG methylation and reduced gene expression. These effects are validated in mice with isogenic tumors with or without the mutant IDH1, and are associated with genome-wide changes in cfDNA fragmentation in patients with cancer. Tumor-related hypomethylation and increased gene expression are associated with decrease in cfDNA fragment size that may explain smaller cfDNA fragments in human cancers. These results provide a connection between epigenetic changes and cfDNA fragmentation with implications for disease detection.