Philipp Jakob Jost

Circulating tumor DNA fraction (ctFraction) has emerged as an important biomarker for assessing tumor burden and monitoring treatment response in patients with cancer. In this study, we compared ctFraction estimates generated by ichorCNA, Fragle low-pass whole-genome sequencing (Fragle LP-WGS), Fragle off-target, and OTTER, a proprietary algorithm from Tempus AI. Plasma samples from 33 patients with advanced solid tumors were analyzed using a ctDNA assay targeting 150 cancer-associated genes, and ctFraction estimates generated by the different methods were compared. Fragle off-target demonstrated the highest concordance with Fragle LP-WGS (rho = 0.903), followed by OTTER (rho = 0.698) and ichorCNA (rho = 0.696), while OTTER and ichorCNA showed strong agreement (rho = 0.826). Mean VAF (mVAF) significantly correlated with all ctFraction estimates, with the strongest association observed for ichorCNA (rho = 0.910), followed by OTTER (rho = 0.865), Fragle LP-WGS (rho = 0.680), and Fragle off-target (rho = 0.658). Longitudinal analysis of 20 patients at baseline and after two cycles of treatment demonstrated strong correlations between changes in ctFraction (ΔctFraction) and mean ΔVAF for both ichorCNA and Fragle off-target (r = 0.955 and r = 0.906, respectively). Overall, these findings demonstrate that ctFraction estimates derived from copy-number- and fragmentomic-based approaches show strong concordance across advanced solid tumors and significantly correlate with mVAF, a commonly used measure of ctDNA abundance. Fragle off-target, in particular, provides an efficient strategy for ctFraction estimation directly from existing targeted sequencing data, eliminating the need for additional sequencing. Larger prospective studies are warranted to further evaluate Fragle off-target clinical utility for treatment monitoring and outcome prediction.

Microsatellite instability (MSI) is a predictive biomarker in several tumor types. However, many next-generation sequencing-based callers require matched normal samples, reference panels, or pretrained models, limiting their portability across assays and sequencing centers. We developed PROMIS (PROfiling of Microsatellite InStability), a tumor-only, reference-free pipeline that uses a discrete mixture model to characterize intrasample repeat-length distributions at predefined microsatellite loci. Locus-level classifications are then aggregated into a continuous MSI score. We benchmarked PROMIS in colorectal (CRC), endometrial (UCEC), and gastric (STAD) cancers from The Cancer Genome Atlas. PROMIS achieved an overall area under the receiver operating characteristic curve (AUC) of 0.995 and cohort-specific AUCs of 1.00 in CRC and stomach adenocarcinoma and 0.999 in uterine corpus endometrial carcinoma, comparable to established tools despite not using matched normals or pretrained models. Subsampling demonstrated robust performance with substantially fewer loci. In silico dilution showed progressively reduced MSI–microsatellite-stable discrimination, with the pooled AUC declining from 0.83 at 10% tumor fraction to 0.53 at 1%. At low tumor fractions, tumor-type-specific baseline microsatellite variability increasingly influenced PROMIS scores. Finally, in prostate and CRC cell-free DNA cohorts, including Illumina TSO500 data and an 18-gene panel, PROMIS yielded MSI scores concordant with orthogonal tissue- and panel-based classifications across the evaluated Illumina-based sequencing contexts. Accordingly, the present validation should be considered limited to Illumina-based sequencing platforms. PROMIS is intended to complement existing genomic profiling workflows by enabling MSI assessment from sequencing data already generated for broader molecular analyses. Prospective clinical validation remains necessary before clinical implementation.

Evasion of programmed cell death is a critical hallmark of cancer. However, the contribution of inflammatory forms of cell death in lung carcinogenesis and their effects on the composition of the tumor-immune microenvironment remain unclear. Our multi-omics analyses of samples from patients with primary lung adenocarcinoma revealed that necrosome signaling is repressed because of reduced expression of receptor-interacting protein kinase 3 ( RIPK3 ). Distinct methylation signatures, both in the RIPK3 promoter and nonpromoter regions, correlated with lower transcription levels of RIPK3 . This resulted in limited expression of inflammatory genes, advanced histologic features, reduced immune cell invasion, and decreased patient survival. Mechanistically, we confirmed the tumor-suppressive role of necrosome signaling through the genetic deletion of Ripk3 in two independent, clinically relevant mouse models of lung adenocarcinoma. Functionally, RIPK3 shaped a diverse immune environment by promoting the invasion of innate and adaptive immune cells in patient samples and experimental mice. Thus, RIPK3-mediated inflammatory signaling enhances a diverse immune microenvironment and hinders progression in lung adenocarcinoma.

Acute myeloid leukemia (AML) is characterized by frequent relapse, which is driven by resistant leukemic stem or progenitor cells (LSCs). Here, we reported on a tumor-suppressive mechanism that can be harnessed to simultaneously clear LSCs and promote healthy hematopoiesis. Genetic deletion of the tumor necrosis factor (TNF) superfamily member lymphotoxin alpha ( Lta ) blocked cell death and accelerated leukemogenesis in murine AML models. Accordingly, exposure of leukemic cells to exogenous recombinant lymphotoxin alpha (LTα ₃ ) induced myeloid differentiation and, in part, cell death in AML progenitors. In syngeneic and patient-derived xenograft mouse models, exposure to recombinant LTα ₃ resulted in deep and durable remissions. LTα ₃ repressed leukemia by depleting tumor necrosis factor receptor (TNFR)–associated factor 2 (TRAF2) through activation of TNF receptors TNFR1 and TNFR2. In contrast with conventional therapies, LTα ₃ exerted only minimal toxicity on the healthy hematopoiesis but instead promoted hematopoietic progenitors. Leveraging this endogenous tumor-suppressive mechanism may decouple treatment efficacy on malignant cells from undesired bone marrow suppression.

Kaplan-Meier estimates of recurrence-free survival (A, C) and overall survival (B, D) of patients with KIT exon 11 deletion mutation (A, B) and patients with KIT exon 11 indel mutation (C, D)

Representativeness of Study Participants