Fragmentstein-facilitating data reuse for cell-free DNA fragment analysis

SUMMARY

Method development for the analysis of cell-free DNA (cfDNA) sequencing data is impeded by limited data sharing due to the strict control of sensitive genomic data. An existing solution for facilitating data sharing removes nucleotide-level information from raw cfDNA sequencing data, keeping alignment coordinates only. This simplified format can be publicly shared and would, theoretically, suffice for common functional analyses of cfDNA data. However, current bioinformatics software requires nucleotide-level information and cannot process the simplified format. We present Fragmentstein, a command-line tool for converting non-sensitive cfDNA-fragmentation data into alignment mapping (BAM) files. Fragmentstein complements fragment coordinates with sequence information from a reference genome to reconstruct BAM files. We demonstrate the utility of Fragmentstein by showing the feasibility of copy number variant (CNV), nucleosome occupancy, and fragment length analyses from non-sensitive fragmentation data.

AVAILABILITY AND IMPLEMENTATION

Implemented in bash, Fragmentstein is available at https://github.com/uzh-dqbm-cmi/fragmentstein, licensed under GNU GPLv3.

3DPolyS-LE: an accessible simulation framework to model the interplay between chromatin and loop extrusion

SUMMARY

Recent studies suggest that the loop extrusion activity of Structural Maintenance of Chromosomes complexes is central to proper organization of genomes in vivo. Polymer physics-based modeling of chromosome structure has been instrumental to assess which structures such extrusion can create. Only few laboratories however have the technical and computational expertise to create in silico models combining dynamic features of chromatin and loop extruders. Here, we present 3DPolyS-LE, a self-contained, easy to use modeling and simulation framework allowing non-specialists to ask how specific properties of loop extruders and boundary elements impact on 3D chromosome structure. 3DPolyS-LE also provides algorithms to compare predictions with experimental Hi-C data.

AVAILABILITY AND IMPLEMENTATION

Software available at https://gitlab.com/togop/3DPolyS-LE; implemented in Python and Fortran 2003 and supported on any Unix-based operating system (Linux and Mac OS).

SUPPLEMENTARY INFORMATION

Supplementary information are available at Bioinformatics online.

Abstract LB112: Liquid biopsy monitoring reveals high molecular weight cfDNA fragments associated with radiotherapy dose-intensity

Introduction: Radiotherapy aims at delivering a high dose of radiation to a tumor while minimizing the dose absorbed by healthy tissues, minimizing side effects or toxicities. Radiotherapy monitoring currently largely relies on longitudinal imaging with spatial and limited functional information on therapy response. Particularly, discrimination of radiotherapy effect on the tumor versus healthy tissue can be challenging and imaging response may lag behind actual response on the tumor cell level. Liquid biopsy monitoring promises to complement imaging by providing systemic biological information about the effects of radiotherapy. Cell-free DNA (cfDNA) in the blood plasma contains genetic and epigenetic information about cell death processes, and cfDNA monitoring may thus lend itself to observing both tumor response and normal-tissue toxicity during radiotherapy.

Methods: Seven polymetastatic patients, seven healthy volunteers, seven oligometastatic patients (OMD) and seven head-and neck cancer patients (H&N) were recruited for the study. OMD patients received stereotactic body radiation therapy in 5 fractions of 5-10 Gy, heterogeneously prescribed, while H&N underwent homogeneously 2 Gy radiation to a total dose of 70 Gy. Blood samples were collected from all patients at baseline and from patients undergoing radiotherapy twice during and twice after treatment, with samples collected up to six months after treatment. cfDNA was isolated and low-pass (7x) whole-genome sequencing was performed to examine fragment-length distribution and copy number alterations. We applied in silico size selection for 90 to 150 bp long fragments to improve copy number variant detection. Clinical measures and imaging findings were compared to cfDNA fragment analysis.

Results: Samples showing high circulating tumor DNA content in copy number analysis (tMAD>0.03) also showed a higher proportion of short fragments (80-100 bp) compared to the samples of healthy individuals (ANOVA: p=0.0216, Tukey-pairwise: p=0.0287), whereas samples with low circulating tumor content did not (Tukey-pairwise: p=0.7540). We observed rapidly declining tumor fraction under treatment in a patient with prostate cancer and a high tMAD value at baseline. However, in the follow-up sample, residual tumor was detectable in the cfDNA copy number analysis, which was further confirmed by increasing PSA values. We observed a significant increase in the fraction of fragments between 200 and 250 bp in response to the treatment in oligometastatic patients receiving high-intensity radiotherapy, which returned to baseline in the follow-up measurements (ANOVA: p=0.0252, Tukey-pairwise: p=0.3138). A similar trend was observable (ANOVA: p=0.37) in head-and-neck patients, who received lower fractions of radiotherapy.

Conclusions: Applying low-pass whole-genome cfDNA-sequencing, we were able to monitor radiotherapy response in oligometastatic and head-and-neck cancer patients. We have also observed short-term increase in the number fragments between 200 and 250 bp during treatment, which we hypothesize to be a necrotic signal. The minimal invasive nature and the relatively low cost of low-pass cfDNA-sequencing makes it a viable method for frequent monitoring, which may allow prediction of tumor response and patient outcome.

Citation Format: Zsolt Balazs, Ivna Ivankovic, Panagiotis Balermpas, Todor Gitchev, Jonas Willmann, Michael Krauthammer, Nicolaus Andratschke. Liquid biopsy monitoring reveals high molecular weight cfDNA fragments associated with radiotherapy dose-intensity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB112.

Abstract 1912: A versatile computational pipeline for the preprocessing of cell-free DNA fragmentation data

Cell-free DNA (cfDNA) emerges as a promising liquid biopsy biomarker for cancer diagnosis and patient monitoring. Complementing mutation-based assays, cfDNA carries information about epigenetic modifications from decaying cells. This information is encoded in the shape of the cfDNA fragments. Specifically, fragments from cancer tend to be shorter than those originating from other adult cells, enabling a distinction between cancer patients and healthy individuals. Additional cfDNA features such as fragment end motifs and information on nucleosome positioning provide further insight into cancer biology. These cfDNA measures are typically inferred from low-pass whole genome sequencing and subsequent bioinformatics processing. A key bioinformatics step is the alignment of DNA sequencing reads to the reference genome, which critically depends on preprocessing steps such as read trimming and alignment filters. A good understanding of preprocessing settings is thus crucial to derive accurate information from cfDNA. We therefore investigated to what extent preprocessing choices affect cfDNA analysis. To this end, we have built a robust bioinformatics pipeline that evaluates a range of possible preprocessing settings. The pipeline is implemented in a bioinformatics workflow engine, enabling a scalable and reproducible workflow. We are currently evaluating the effect of preprocessing on global and regional fragmentation patterns, detection of nucleosome positioning and identification of fragment end motifs. The different preprocessing settings are also evaluated for their ability to distinguish cancer from control samples using cfDNA fragmentation information. We are benchmarking the pipeline using cfDNA datasets from multiple centres to ensure our findings are generalizable over different platforms and experimental procedures. Our investigations will allow us to build a versatile bioinformatics preprocessing pipeline for the analysis of cell-free DNA fragmentation data.

Citation Format: Ivna Ivankovic, Zsolt Balázs, Todor Gitchev, Daniel Trejo Banos, Norbert Moldovan, Panagiotis Balermpas, Jonas Willmann, Nicolaus Andratschke, Florent Moulière, Michael Krauthammer. A versatile computational pipeline for the preprocessing of cell-free DNA fragmentation data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1912.