Robert M. Flight

Background/Objectives: Metabolism-level interpretation of metabolomics datasets requires aggregation analyses across metabolites. One highly used aggregation analysis is pathway enrichment analysis (PEA), which involves detecting pathways enriched with metabolites that are differential between experimental groups. Annotating metabolites with pathway associations is a prerequisite for PEA. While several knowledge bases define pathways and include metabolite-pathway annotations, these definitions are often partially or even grossly incomplete due to limitations in current metabolic knowledge and its curation, which greatly limits the effectiveness of PEA. Methods: In this work, we used our novel multitask classification, graph convolutional-like neural network to generate high-quality metabolite-pathway annotations for pathways defined across KEGG, MetaCyc, and Reactome. We then included these predicted metabolite-pathway annotations when performing PEA on 990 datasets deposited in Metabolomics Workbench. Results: We demonstrate an 8-fold increase in the median number of enriched pathways detected across these datasets compared to using only knowledge base-derived annotations. Conclusions: The significant increase in enriched pathways has the potential to substantially improve the biological and biomedical interpretability of metabolomics datasets.

The recount3 online resource provides tens of thousands of uniformly processed RNA-seq samples across human and mouse from major sequencing repositories like the Sequence Read Archive. While access to these datasets has traditionally been centered in the R/Bioconductor ecosystem, the growing prominence of Python in bioinformatics and machine learning necessitates native, efficient tooling for Python users. Therefore, we present the recount3 Python package with robust application programming interface (API) and command-line interface (CLI) for discovering, downloading, and materializing recount3 resources. The software orchestrates uniform resource locator (URL) resolution, persistent on-disk caching, and the automatic parsing of data into analysis-ready data structures, including Pandas DataFrames and BiocPy RangedSummarizedExperiment objects. The recount3 Python package drastically lowers the barrier to entry for large-scale utilization of RNA-seq data in Python-based computational pipelines, bridging the gap between massive public transcriptomic data and modern machine learning ecosystems.

TVB-3664 treatment enhances irinotecan induced cytotoxicity in PDOs

TVB-3664 treatment increases protein acetylation and decreases ATM protein expression

Effect of FASN inhibition in normal vs tumor samples

Addition of exogenous lipids rescues ATM expression in TVB-3664 treated colon cancer cells

Characteristics of patients in Cohort 2 from whom tumor samples and adjacent normal colon tissues were obtained

Different combination treatments of TVB-3664, irinotecan and olaparib were well tolerated in vivo

Altered lipid metabolism is a potential targetable metabolic vulnerability in colorectal cancer. Fatty acid synthase (FASN), the rate-limiting enzyme of de novo lipogenesis, is an important regulator of colorectal cancer progression, but the FASN inhibitor TVB-2640 showed only modest efficacy in reducing tumor burden in preclinical studies, suggesting that combination strategies might be required to prolong patient survival. In this study, by using samples from a window trial of TVB-2640 treatment in patients with colorectal cancer, we found that FASN inhibition induced DNA damage but impaired the DNA damage response (DDR). In colon cancer cell lines and patient-derived organoids, FASN inhibition potentiated chemotherapy-induced double-strand DNA breaks and apoptotic cell death by altering histone acetylation. In addition, FASN inhibitor treatment blocked DDR by decreasing ATM expression and CHK2 phosphorylation. Mechanistically, FASN inhibition decreased activation of the DDR pathway by attenuating BRCA1 and ATM recruitment to γH2AX foci in an acetylation-dependent manner. Moreover, FASN inhibition–mediated DNA repair deficiency induced synthetic lethality with PARP inhibition in colon cancer cells. Importantly, combining FASN inhibition with the chemotherapeutic drug irinotecan synergistically decreased xenograft tumor growth and delayed tumor relapse, which was potentiated by the PARP inhibitor olaparib as maintenance treatment. Taken together, this study describes a therapeutic strategy in which FASN inhibitors can be utilized to delay tumor recurrence after chemotherapy, which is a major challenge in patients with colorectal cancer.Significance:FASN inhibition attenuates DNA damage repair to potentiate the efficacy of chemotherapy and to promote synthetic lethality with PARP inhibitors, offering a potential combination strategy to reduce tumor recurrence in colorectal cancer.

Characteristics of patient tumors from which PDOs were derived