Pancreatic ductal adenocarcinoma (PDAC) is expected to be the second most deadly cancer by 2040, owing to the high incidence of metastatic disease and limited responses to treatment^1,2. Less than half of all patients respond to the primary treatment for PDAC, chemotherapy^3,4, and genetic alterations alone cannot explain this⁵. Diet is an environmental factor that can influence the response to therapies, but its role in PDAC is unclear. Here, using shotgun metagenomic sequencing and metabolomic screening, we show that the microbiota-derived tryptophan metabolite indole-3-acetic acid (3-IAA) is enriched in patients who respond to treatment. Faecal microbiota transplantation, short-term dietary manipulation of tryptophan and oral 3-IAA administration increase the efficacy of chemotherapy in humanized gnotobiotic mouse models of PDAC. Using a combination of loss- and gain-of-function experiments, we show that the efficacy of 3-IAA and chemotherapy is licensed by neutrophil-derived myeloperoxidase. Myeloperoxidase oxidizes 3-IAA, which in combination with chemotherapy induces a downregulation of the reactive oxygen species (ROS)-degrading enzymes glutathione peroxidase 3 and glutathione peroxidase 7. All of this results in the accumulation of ROS and the downregulation of autophagy in cancer cells, which compromises their metabolic fitness and, ultimately, their proliferation. In humans, we observed a significant correlation between the levels of 3-IAA and the efficacy of therapy in two independent PDAC cohorts. In summary, we identify a microbiota-derived metabolite that has clinical implications in the treatment of PDAC, and provide a motivation for considering nutritional interventions during the treatment of patients with cancer.

Nuclei detection and segmentation in hematoxylin and eosin-stained (H&E) tissue images are important clinical tasks and crucial for a wide range of applications. However, it is a challenging task due to nuclei variances in staining and size, overlapping boundaries, and nuclei clustering. While convolutional neural networks have been extensively used for this task, we explore the potential of Transformer-based networks in combination with large scale pre-training in this domain. Therefore, we introduce a new method for automated instance segmentation of cell nuclei in digitized tissue samples using a deep learning architecture based on Vision Transformer called CellViT. CellViT is trained and evaluated on the PanNuke dataset, which is one of the most challenging nuclei instance segmentation datasets, consisting of nearly 200,000 annotated nuclei into 5 clinically important classes in 19 tissue types. We demonstrate the superiority of large-scale in-domain and out-of-domain pre-trained Vision Transformers by leveraging the recently published Segment Anything Model and a ViT-encoder pre-trained on 104 million histological image patches - achieving state-of-the-art nuclei detection and instance segmentation performance on the PanNuke dataset with a mean panoptic quality of 0.50 and an F₁-detection score of 0.83. The code is publicly available at https://github.com/TIO-IKIM/CellViT.

The bromodomain and extraterminal (BET) inhibitor JQ1 synergizes with the histone deacetylase inhibitor SAHA to suppress tumor growth in mouse models of pancreatic cancer. Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal human cancers and shows resistance to any therapeutic strategy used. Here we tested small-molecule inhibitors targeting chromatin regulators as possible therapeutic agents in PDAC. We show that JQ1, an inhibitor of the bromodomain and extraterminal (BET) family of proteins, suppresses PDAC development in mice by inhibiting both MYC activity and inflammatory signals. The histone deacetylase (HDAC) inhibitor SAHA synergizes with JQ1 to augment cell death and more potently suppress advanced PDAC. Finally, using a CRISPR-Cas9–based method for gene editing directly in the mouse adult pancreas, we show that de-repression of p57 (also known as KIP2 or CDKN1C) upon combined BET and HDAC inhibition is required for the induction of combination therapy–induced cell death in PDAC. SAHA is approved for human use, and molecules similar to JQ1 are being tested in clinical trials. Thus, these studies identify a promising epigenetic-based therapeutic strategy that may be rapidly implemented in fatal human tumors.

The clinical relevance of comprehensive molecular analysis in rare cancers is not established. We analyzed the molecular profiles and clinical outcomes of 1,310 patients (rare cancers, 75.5%) enrolled in a prospective observational study by the German Cancer Consortium that applies whole-genome/exome and RNA sequencing to inform the care of adults with incurable cancers. On the basis of 472 single and six composite biomarkers, a cross-institutional molecular tumor board provided evidence-based management recommendations, including diagnostic reevaluation, genetic counseling, and experimental treatment, in 88% of cases. Recommended therapies were administered in 362 of 1,138 patients (31.8%) and resulted in significantly improved overall response and disease control rates (23.9% and 55.3%) compared with previous therapies, translating into a progression-free survival ratio >1.3 in 35.7% of patients. These data demonstrate the benefit of molecular stratification in rare cancers and represent a resource that may promote clinical trial access and drug approvals in this underserved patient population.Significance: Rare cancers are difficult to treat; in particular, molecular pathogenesis–oriented medical therapies are often lacking. This study shows that whole-genome/exome and RNA sequencing enables molecularly informed treatments that lead to clinical benefit in a substantial proportion of patients with advanced rare cancers and paves the way for future clinical trials.See related commentary by Eggermont et al., p. 2677.This article is highlighted in the In This Issue feature, p. 2659

Fibroblast activation protein (FAP), a membrane-anchored peptidase, is highly expressed in cancer-associated fibroblasts (CAFs) in more than 90% of epithelial tumors and contributes to progression and worse prognosis of different cancers. Therefore, FAP is considered a promising target for radionuclide-based approaches for diagnosis and treatment of tumors and for the diagnosis of non-malignant diseases associated with a remodeling of the extracellular matrix. Accordingly, a variety of quinolone-based FAP inhibitors (FAPI) coupled to chelators were developed displaying specific binding to human and murine FAP with a rapid and almost complete internalization. Due to a high tumor uptake and a very low accumulation in normal tissues as well as a rapid clearance from the circulation, a high-contrast is obtained for FAPI-PET/CT imaging even at 10 minutes after tracer administration. Moreover, FAPI-PET/CT provides advantages over FDG-PET/CT in several tumor entities for initial staging and detection of tumor recurrence and metastases including peritonitis carcinomatosa.