Non-invasive monitoring of neoadjuvant radiation therapy response in soft tissue sarcomas by multiparametric MRI and quantification of circulating tumor DNA-A study protocol.

BACKGROUND: Wide resection remains the cornerstone of localized soft-tissue sarcomas (STS) treatment. Neoadjuvant radiation therapy (NRT) may decrease the risk of local recurrences; however, its effectiveness for different histological STS subtypes has not been systematically investigated. The proposed prospective study evaluates the NRT response in STS using liquid biopsies and the correlation of multiparametric magnetic resonance imaging (mpMRI) with histopathology and immunohistochemistry. METHODS: Patients with localized high-grade STS, who qualify for NRT, are included in this study. LIQUID BIOPSIES: Quantification of circulating tumor DNA (ctDNA) in patient blood samples is performed by targeted next-generation sequencing. Soft-tissue sarcoma subtype-specific panel sequencing in combination with patient-specific exome sequencing allows the detection of individual structural variants and point mutations. Circulating free DNA is isolated from peritherapeutically collected patient plasma samples and ctDNA quantified therein. Identification of breakpoints is carried out using FACTERA. Bioinformatic analysis is performed using samtools, picard, fgbio, and the MIRACUM Pipeline. MPMRI: Combination of conventional MRI sequences with diffusion-weighted imaging, intravoxel-incoherent motion, and dynamic contrast enhancement. Multiparametric MRI is performed before, during, and after NRT. We aim to correlate mpMRI data with the resected specimen's macroscopical, histological, and immunohistochemical findings. RESULTS: Preliminary data support the notion that quantification of ctDNA in combination with tumor mass characterization through co-registration of mpMRI and histopathology can predict NRT response of STS. CLINICAL RELEVANCE: The methods presented in this prospective study are necessary to assess therapy response in heterogeneous tumors and lay the foundation of future patient- and tumor-specific therapy concepts. These methods can be applied to various tumor entities. Thus, the participation and support of a wider group of oncologic surgeons are needed to validate these findings on a larger patient cohort.

Genotyping of Circulating Free DNA Enables Monitoring of Tumor Dynamics in Synovial Sarcomas.

BACKGROUND: Synovial sarcoma (SS) is a malignant soft tissue tumor of mesenchymal origin that frequently occurs in young adults. Translocation of the SYT gene on chromosome 18 to the SSX genes on chromosome X leads to the formation of oncogenic fusion genes, which lead to initiation and proliferation of tumor cells. The detection and quantification of circulating tumor DNA (ctDNA) can serve as a non-invasive method for diagnostics of local or distant tumor recurrence, which could improve survival rates due to early detection. METHODS: We developed a subtype-specific targeted next-generation sequencing (NGS) approach specifically targeting SS t(X;18)(p11;q11), which fuses SS18 (SYT) in chromosome 18 to SSX1 or SSX2 in chromosome x, and recurrent point mutations. In addition, patient-specific panels were designed from tumor exome sequencing. Both approaches were used to quantify ctDNA in patients' plasma. RESULTS: The subtype-specific assay allowed detection of somatic mutations from 25/25 tumors with a mean of 1.68 targetable mutations. The minimal limit of detection was determined at a variant allele frequency of 0.05%. Analysis of 29 plasma samples from 15 tumor patients identified breakpoint ctDNA in 6 patients (sensitivity: 40%, specificity 100%). The addition of more mutations further increased assay sensitivity. Quantification of ctDNA in plasma samples (n = 11) from one patient collected over 3 years, with a patient-specific panel based on tumor exome sequencing, correlated with the clinical course, response to treatment and tumor volume. CONCLUSIONS: Targeted NGS allows for highly sensitive tumor profiling and non-invasive detection of ctDNA in SS patients, enabling non-invasive monitoring of tumor dynamics.

Artificial Intelligence-Driven Video Analysis for Novel Outcome Measures After Smile Reanimation Surgery.

Background: Since facial paralysis is a dynamic condition, the analysis of still photographs is not sufficient for measurement of facial reanimation outcomes. This study aimed at evaluating an artificial intelligence (AI)-driven software as a novel video assessment tool for smile reanimation surgery and at comparing it with the Terzis score. Methods: Patients with facial paralysis undergoing smile reanimation surgery between January 2008 and April 2020 were eligible for this retrospective study. Inclusion criteria were at least 6 months of follow-up and availability of both pre- and post-operative video documentation. The software output was given as intensity score (IS) values between 0 and 1, representing emotions/action units (AUs) that are absent or fully present, respectively. Results: During the study period, 240 patients underwent facial reanimation surgery, of whom 63 patients met the inclusion criteria. Postoperatively, the median IS of the happiness emotion and lip corner puller AU increased significantly (p < 0.001). There was a positive correlation of Terzis score with the IS of happiness emotion (r = 0.8) and lip corner puller AU (r = 0.74). Conclusions: The novel AI-driven video analysis is strongly correlated with the Terzis score and shows promise for objective functional outcome evaluation after smile reanimation surgery.