Detection of circulating tumor DNA by tumor-informed whole-genome sequencing enables prediction of recurrence in stage III colorectal cancer patients.

INTRODUCTION: Circulating tumor (ctDNA) can be used to detect residual disease after cancer treatment. Detecting low-level ctDNA is challenging, due to the limited number of recoverable ctDNA fragments at any target loci. In response, we applied tumor-informed whole-genome sequencing (WGS), leveraging thousands of mutations for ctDNA detection. METHODS: Performance was evaluated in serial plasma samples (n = 1283) from 144 stage III colorectal cancer patients. Tumor/normal WGS was used to establish a patient-specific mutational fingerprint, which was searched for in 20x WGS plasma profiles. For reproducibility, paired aliquots of 172 plasma samples were analyzed in two independent laboratories. De novo variant calling was performed for serial plasma samples with a ctDNA level > 10 % (n = 17) to explore genomic evolution. RESULTS: WGS-based ctDNA detection was prognostic of recurrence: post-operation (Hazard ratio [HR] 6.75, 95 %CI 3.18-14.3, p < 0.001), post-adjuvant chemotherapy (HR 28.9, 95 %CI 10.1-82.8; p < 0.001), and during surveillance (HR 22.8, 95 %CI 13.7-37.9, p < 0.0001). The 3-year cumulative incidence of ctDNA detection in recurrence patients was 95 %. ctDNA was detected a median of 8.7 months before radiological recurrence. The independently analyzed plasma aliquots showed excellent agreement (Cohens Kappa=0.9, r = 0.99). Genomic characterization of serial plasma revealed significant evolution in mutations and copy number alterations, and the timing of mutational processes, such as 5-fluorouracil-induced mutations. CONCLUSION: Our study supports the use of WGS for sensitive ctDNA detection and demonstrates that post-treatment ctDNA detection is highly prognostic of recurrence. Furthermore, plasma WGS can identify genomic differences distinguishing the primary tumor and relapsing metastasis, and monitor treatment-induced genomic changes.

Whole-genome Mutational Analysis for Tumor-informed Detection of Circulating Tumor DNA in Patients with Urothelial Carcinoma.

BACKGROUND AND OBJECTIVE: Circulating tumor DNA (ctDNA) can be used for sensitive detection of minimal residual disease (MRD). However, the probability of detecting ctDNA in settings of low tumor burden is limited by the number of mutations analyzed and the plasma volume available. We used a whole-genome sequencing (WGS) approach for ctDNA detection in patients with urothelial carcinoma. METHODS: We used a tumor-informed WGS approach for ctDNA-based detection of MRD and evaluation of treatment responses. We analyzed 916 longitudinally collected plasma samples from 112 patients with localized muscle-invasive bladder cancer who received neoadjuvant chemotherapy (NAC) before radical cystectomy. Recurrence-free survival (primary endpoint), overall survival, and ctDNA dynamics during NAC were assessed. KEY FINDINGS AND LIMITATIONS: We found that WGS-based ctDNA detection is prognostic for patient outcomes with a median lead time of 131 d over radiographic imaging. WGS-based ctDNA assessment after radical cystectomy identified recurrence with sensitivity of 91% and specificity of 92%. In addition, genomic characterization of post-treatment plasma samples with a high ctDNA level revealed acquisition of platinum therapy-associated mutational signatures and copy number variations not present in the primary tumors. The sequencing depth is a limitation for studying tumor evolution. CONCLUSIONS AND CLINICAL IMPLICATIONS: Our results support the use of WGS for ultrasensitive ctDNA detection and highlight the possibility of plasma-based tracking of tumor evolution. WGS-based ctDNA detection represents a promising option for clinical use owing to the low volume of plasma needed and the ease of performing WGS, eliminating the need for personalized assay design.

Genomic profiling of HIV-1 integration in microglia cells links viral integration to the topologically associated domains.

HIV-1 encounters the hierarchically organized host chromatin to stably integrate and persist in anatomically distinct latent reservoirs. The contribution of genome organization in HIV-1 infection has been largely understudied across different HIV-1 targets. Here, we determine HIV-1 integration sites (ISs), associate them with chromatin and expression signatures at different genomic scales in a microglia cell model, and profile them together with the primary T cell reservoir. HIV-1 insertions into introns of actively transcribed genes with IS hotspots in genic and super-enhancers, characteristic of blood cells, are maintained in the microglia cell model. Genome organization analysis reveals dynamic CCCTC-binding factor (CTCF) clusters in cells with active and repressed HIV-1 transcription, whereas CTCF removal impairs viral integration. We identify CTCF-enriched topologically associated domain (TAD) boundaries with signatures of transcriptionally active chromatin as HIV-1 integration determinants in microglia and CD4+ T cells, highlighting the importance of host genome organization in HIV-1 infection.