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Molecular profiling from liquid biopsy, in particular cell-free DNA (cfDNA), represents an attractive alternative to tissue biopsies for the detection of actionable targets and tumor monitoring. In addition to PCR-based assays, Next Generation Sequencing (NGS)-based cfDNA assays are now commercially available and are being increasingly adopted in clinical practice. However, the validity of these products as well as the clinical utility of cfDNA in the management of patients with cancer has yet to be proven. Within framework of the Innovative Medicines Initiative (IMI) program CANCER-ID we evaluated the use of commercially available reference materials designed for ctDNA testing and cfDNA derived from Diagnostic Leukaphereses (DLA) for inter- and intra-assay as well as intra- and inter-laboratory comparisons. In three experimental setups, a broad range of assays including ddPCR, MassARRAY and various NGS-based assays were tested. We demonstrate that both reference materials with predetermined VAFs and DLA samples are extremely useful for the performance assessment of mutation analysis platforms. Moreover, our data indicate a substantial variability of NGS assays with respect to sensitivity and specificity highlighting the importance of extensive validation of the test performance before offering these tests in clinical routine practice.

Leukemic cutaneous T‐cell lymphomas (L‐CTCL) are lymphoproliferative disorders of skin‐homing mature T‐cells causing severe symptoms and high mortality through chronic inflammation, tissue destruction, and serious infections. Despite numerous genomic sequencing efforts, recurrent driver mutations have not been identified, but chromosomal losses and gains are frequent and dominant. We integrated genomic landscape analyses with innovative pharmacologic interference studies to identify key vulnerable nodes in L‐CTCL. We detected copy number gains of loci containing the STAT3/5 oncogenes in 74% ( n  = 17/23) of L‐CTCL, which correlated with the increased clonal T‐cell count in the blood. Dual inhibition of STAT3/5 using small‐molecule degraders and multi‐kinase blockers abolished L‐CTCL cell growth in vitro and ex vivo , whereby PAK kinase inhibition was specifically selective for L‐CTCL patient cells carrying STAT3/5 gains. Importantly, the PAK inhibitor FRAx597 demonstrated encouraging anti‐leukemic activity in vivo by inhibiting tumor growth and disease dissemination in intradermally xenografted mice. We conclude that STAT3/5 and PAK kinase interaction represents a new therapeutic node to be further explored in L‐CTCL. Synopsis L‐CTCL remains a poorly understood rare T‐cell cancer entity. Frequently amplified STAT3/5 oncogenes and related kinase action relevant for T‐cell survival were identified as vulnerable nodes for targeting, thereby improving the prospects of a translatable targeted drug for L‐CTCL. Copy number gain of STAT3/5 , which frequently co‐occurs with loss of STAT1 and SOCS1 , contributes to increased clonal expansion in leukemic cutaneous T‐cell lymphoma. STAT3/5 can be blocked directly or indirectly, through upstream kinase inhibition, particularly involving PAK‐mediated STAT3/5 nuclear translocation. PAK kinase inhibition is selective for L‐CTCL patient cells carrying STAT3/5 gains and reduces growth of intradermally xenografted tumors. Graphical Abstract L‐CTCL remains a poorly understood rare T‐cell cancer entity. Frequently amplified STAT3/5 oncogenes and related kinase action relevant for T‐cell survival were identified as vulnerable nodes for targeting, thereby improving the prospects of a translatable targeted drug for L‐CTCL.

Analyses of cell-free DNA (cfDNA) are increasingly being employed for various diagnostic and research applications. Many technologies aim to increase resolution, e.g. for detecting early-stage cancer or minimal residual disease. However, these efforts may be confounded by inherent base composition biases of cfDNA, specifically the over - and underrepresentation of guanine (G) and cytosine (C) sequences. Currently, there is no universally applicable tool to correct these effects on sequencing read-level data. Here, we present GCparagon, a two-stage algorithm for computing and correcting GC biases in cfDNA samples. In the initial step, length and GC base count parameters are determined. Here, our algorithm minimizes the inclusion of known problematic genomic regions, such as low-mappability regions, in its calculations. In the second step, GCparagon computes weights counterbalancing the distortion of cfDNA attributes (correction matrix). These fragment weights are added to a binary alignment map (BAM) file as alignment tags for individual reads. The GC correction matrix or the tagged BAM file can be used for downstream analyses. Parallel computing allows for a GC bias estimation below 1 min. We demonstrate that GCparagon vastly improves the analysis of regulatory regions, which frequently show specific GC composition patterns and will contribute to standardized cfDNA applications.

The analysis of circulating cell-free DNA (cfDNA) holds immense promise as a non-invasive diagnostic tool across various human conditions. However, extracting biological insights from cfDNA fragments entails navigating complex and diverse bioinformatics methods, encompassing not only DNA sequence variation but also epigenetic characteristics like nucleosome footprints, fragment length, and methylation patterns. We introduce LBFextract, a comprehensive package designed to streamline feature extraction from cfDNA data, with the aim of enhancing the reproducibility and comparability of liquid biopsy studies. LBFextract facilitates the integration of preprocessing and postprocessing steps through alignment fragment tags and a hook mechanism. It incorporates various methods, including coverage-based and fragment length-based approaches, alongside two novel feature extraction methods: an entropy-based method to infer TF activity from fragmentomics data and a technique to amplify signals from nucleosome dyads. Additionally, it implements a method to extract condition-specific differentially active TFs based on these features for biomarker discovery. We demonstrate the use of LBFextract for the subtype classification of advanced prostate cancer patients using coverage signals at transcription factor binding sites from cfDNA. We show that LBFextract can generate robust and interpretable features that can discriminate between different clinical groups. LBFextract is a versatile and user-friendly package that can facilitate the analysis and interpretation of liquid biopsy data. LBFextract is freely accessible at https://github.com/Isy89/LBF. It is implemented in Python and compatible with Linux and Mac operating systems. Code and data to reproduce these analyses have been uploaded to 10.5281/zenodo.10964406. For further information, contact isaac.lazzeri@medunigraz.at, samantha.hasenleithner@medunigraz.at, martin.kircher@bih-charite.de. For additional details see Supplementary Information. For usage of the package, refer to https://lbf.readthedocs.io/.

Background: Cancer patients are highly prone to infectious diseases. While undergoing antineoplastic treatment, the risk of severe symptoms upon infection increases, necessitating efficient protective measures, such as vaccination. For patients receiving radiotherapy, there is no specific information about humoral immunity. During the COVID-19 pandemic, serial antibody measurements were therefore offered to cancer patients, following SARS-CoV-2 vaccination while obtaining radiotherapy. Methods: Out of 74 enrolled patients, 46 met the inclusion criteria. Two cohorts were allocated, depending on an association with chemotherapy or pure radiotherapy. An additional healthy control cohort of 16 healthcare workers was enrolled. All participants followed a two-fold BNT162b2 vaccine schedule. SARS-CoV-2 binding antibodies were measured serially in a 7-day cycle for 35 days and over the long-term, using the Elecsys® Anti-SARS-CoV-2 immunoassay. Results: Cancer patients under pure radiotherapy have a comparable humoral vaccination response and long-term persistency of antibodies to healthy controls. Patients receiving additional chemotherapy show a significantly delayed immune response and decreased antibody titers. The vaccine was well tolerated in all cohorts. Conclusions: Pure radiotherapy in cancer patients does not interfere with the vaccine-induced humoral immune response or other immunogenetic aspects, whereas previous or simultaneous chemotherapy does. Findings are of particular relevance for future epidemic or pandemic scenarios.

•One of the largest prospective studies on covid-19 vaccination in cancer patients.•Wide array of solid tumour entities.•High vaccination acceptance in this prioritised collective.•Most oncologic patients showed a measurable humoral response after vaccination.•Risk factors for non– and low humoral responders in uni/multivariate analysis. SARS-CoV-2 infection has been and, in some parts, still is a threat to oncologic patients, making it crucial to understand perception of vaccination and immunologic responses in this vulnerable patient segment. SARS-CoV-2 vaccines in relation to malignant disease characteristics and therapies have so far not been studied consecutively in larger oncologic patient populations. This study captures SARS-CoV-2 vaccination willingness and humoral immune response in a large consecutive oncologic patient collective at the beginning of 2021. 1142 patients were consecutively recruited over 5.5 months at a tertiary department for radiation oncology and were assessed for vaccination willingness via a standardized interview. In already vaccinated patients total SARS-CoV-2 S antibody titres against the spike protein (Anti-SARS-CoV-2 S) and were evaluated 35 days or later after the first dose of SARS-CoV-2 vaccine. Vaccination willingness was high with a rate of 90 %. The most frequent reasons for rejection were: undecided/potential vaccination after therapy, distrust in the vaccine and fear of interaction with comorbidities. Factors associated with lower vaccination willingness were: worse general condition, lower age and female sex. 80 % of the participants had been previously vaccinated, 8 % reported previous infection and 16 % received vaccination during antineoplastic therapy. In 97.5 % of the vaccinated patients Anti-SARS-CoV-2 S was detected. In a univariable analysis parameters associated with non-conversion were: lower performance status, spread to the local lymphatics (N + ), hematologic disease and diffuse metastases. All patients with oligometastatic disease achieved positive Anti-SARS-CoV-2 S titres. For patients with two vaccinations several risk factors were identified, that were associated with low antibody concentrations. SARS-CoV-2 vaccination willingness among oncologic patients was high in the first months after its availability, and most patients had already received one or two doses. Over 97 % of vaccinated patients had measurable anti-SARS-CoV-2 S titres. Our data supports early identification of low humoral responders after vaccination and could facilitate the design of future oncologic vaccine trials (clinicaltrials.gov Identifier: NCT04918888).