bioRxiv Science⌕ Search

bioRxiv · 10.1101/2021.11.02.467008

Wound-like tumor periphery in human breast cancer predicts a convergent drug nonresponse

Abstract

A significant portion of breast cancer patients are nonresponsive to well-established drugs and destined for a poor outcome regardless of molecular subtype. Although several (multiparameter) molecular markers have predicted their resistance to some of these drugs, profound uniparameter markers predictive of a convergent nonresponse to all these drugs remain elusive. We employ co-registered standard-multiphoton histology to representatively sample a few peripheral niches of the primary tumor, so that hundreds of patients can be stratified with either a wound-like or non-wound tumor periphery. With no fitting variable, this simple uniparameter morphological marker is: (a) highly sensitive and specific to predict a multidrug-nonresponsive phenotype that accounts for the majority of recurrence or death, independent of the molecular subtype or related adjuvant drug selection, clinical endpoint (disease-free versus overall survival), and hosting medical center; (b) robust against intratumor heterogeneity and valid at the earliest clinicopathological stage; and (c) dominant in predicting prognosis in the context of routine clinicopathological markers. Considering the mechanistic link between a wound-like extracellular matrix and a microenvironment supporting migratory or mesenchymal tumor cells, we attribute these unusual capabilities to an epithelial-mesenchymal transition nature of the morphological marker long sought after by pathologists.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Li, L., Liao, X., Fu, F., Xi, G., Kang, D., He, J., Guo, W., Qiu, L., Han, Z., Wang, X., Zhan, Q., You, S., Chen, J., Wang, C., Boppart, S. A., Tu, H.. 2021-11-04. Wound-like tumor periphery in human breast cancer predicts a convergent drug nonresponse. https://doi.org/10.1101/2021.11.02.467008

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

NAE1-Dependent Protein Neddylation Preserves Endothelial Identity and Vascular Integrity

Background: Endothelial dysfunction is a central driver of cardiovascular and inflammatory diseases, yet the post-translational mechanisms that preserve endothelial homeostasis remain incompletely understood. Protein neddylation, the covalent conjugation of a ubiquitin-like modifier, regulates diverse cellular processes, yet its physiological role in the vascular endothelium remains unknown. This study investigated whether protein neddylation is required to preserve endothelial identity and vascular homeostasis. Methods: We generated tamoxifen-inducible endothelial-specific Nae1 knockout mice to inhibit neddylation and combined bulk RNA sequencing, single-cell and single-nucleus transcriptomics, quantitative proteomics, biochemical analyses, and gain- and loss-of-function approaches to define the role of endothelial neddylation in vascular homeostasis and inflammatory injury. Results: Endothelial-specific Nae1 deletion caused rapid mortality associated with vascular leakage, platelet accumulation, inflammation, and multi-organ injury. Multi-omics analyses demonstrated profound loss of endothelial identity, characterized by suppression of core endothelial programs and activation of inflammatory, procoagulant, and pyroptotic pathways. Single-cell analyses revealed progressive endothelial dysfunction culminating in depletion of the endothelial population and remodeling of the vascular niche. Mechanistically, endothelial neddylation deficiency activated gasdermin D (GSDMD)- and gasdermin E (GSDME)-dependent pyroptosis, whereas dual inhibition of GSDMD and GSDME markedly attenuated inflammatory transcriptomic remodeling, vascular injury, hepatocyte death, immune cell infiltration, and platelet accumulation. Translational analyses demonstrated reduced endothelial neddylation in experimental endotoxemia and decreased expression of neddylation pathway components in human atherosclerosis and COVID-19 datasets. Conversely, restoration of endothelial neddylation partially reversed inflammatory endothelial transcriptomic reprogramming in vivo. Conclusions: NAE1-dependent protein neddylation is an essential regulator of endothelial identity and vascular integrity. Loss of endothelial neddylation promotes gasdermin-dependent pyroptosis and thrombo-inflammatory vascular injury, whereas restoration of the neddylation pathway mitigates inflammatory endothelial dysfunction. These findings identify endothelial neddylation as a fundamental mechanism maintaining vascular homeostasis and a potential therapeutic target for cardiovascular and inflammatory diseases.

pathology↗

Cetacean "gas-bubble thromboembolic polycystic liver disease": "Budd-Chiari-like syndrome" in dolphins?

Nearly two decades ago, pathologic examination results suggested acoustic factors, such as mid-frequency active naval military sonar (MFAS) could be the cause of acute decompression-like sickness in stranded beaked whales. Acute systemic gas embolism in these beaked whales was published together with enigmatic cystic liver lesions (CLL), characterized by intrahepatic encapsulated gas-filled cysts, tentatively interpreted as "gas-bubble" lesions in various cetacean species. Here we provide a pathologic reinterpretation of CLL in cetaceans. From 1,200 cetaceans necropsied, CLL were only observed in striped dolphins (Stenella coeruleoalba), with a low prevalence (2%), and recapitulated pathologic features of Budd-Chiari syndrome in humans. Our results strongly suggest that CLL are the result of the combination of pre-existing or concomitant hepatic vascular disorder (e.g., severe hepatobiliary trematodiasis) superimposed and exacerbated by gas bubbles, and clearly differ from acute systemic gas embolism in stranded beaked whales linked to MFAS.

pathology↗

Class-Controlled Copy-Paste Based Cell Segmentation for CoNIC Challenge

Muti-class cell segmentation in histopathology images is a challenging task. Here, we propose a copy-paste augmentation-based method for CoNIC challenge. As the challenge train data is severely class imbalanced. To deal with it, we copy all cell objects of train data and paste them to the train image on the fly while training model. The paste strategy is that we paste more cell objects of the insufficient classes and paste less cell objects for the sufficient classes. We experimented the method by stratified splitting train data in 4:1 ratio, the result shows the copy paste method can reach PQ 64.84 and mPQ 53.72, which improved and 0.66 compared to without copy pasted. Moreover, the improvements in those insufficient classes is more obvious.

pathology↗