Biology subjects

Dick, C.

Publications and source records attributed to Dick, C..

4 recordsLinked to original sources

bioRxiv2025

Self-supervised AI reveals a lethal discohesive phenotype in lung adenocarcinoma

Applications of artificial intelligence (AI) to histopathology are now common, but most require supervision which inherently limits their scope. By using self-supervised learning (SSL), we discover and quantify the full range of histopathological appearances in a disease, and associate them with clinicopathological ground truths such as prognosis. We used this approach to discover under-appreciated morphologies of lung adenocarcinoma (LUAD), using a highly characterised resected tumour cohort of over 4000 slides from over 1000 patients. By constructing an authoritative lexicon of recurrent LUAD appearances, we ab initio discovered several stromal morphologies strongly predictive of outcome. With multimodal data integration and external dataset validation, we propose that epithelial discohesion is lethal, but only in the context of immunologically cold stroma. Both these morphological features are independent of current prognostic schema. Crucially, we describe these features in the context of real-world diagnostic histopathology, giving them immediate clinical translatability. Statement of SignificanceHistopathology relies heavily on epithelial morphology, often neglecting the stroma. We use self-supervised AI to identify under-appreciated morphologies in LUAD linked to poor outcome and validate these observations in an external cohort, demonstrating the utility of self-supervised AI as a powerful biological discovery tool.

cancer biology↗

bioRxiv2022

Phylogenetic and Ecological Trends in Specialization: Disentangling the Drivers of Ectoparasite Host Specificity

O_LIEcological specialization reflects both evolutionary and ecological processes. For parasitic taxa, ecological specialization can be assessed as the degree to which a parasite species will associate with certain host species, a property known as host specificity. C_LIO_LIEctoparasitic bat flies have been previously reported as highly host specific, presumably due to a history of coevolution with their bat hosts. However, there is conflicting evidence of coevolution between bats and bat flies. Resource-driven competition between parasite individuals and between species may also be important in explaining patterns of bat fly specificity. C_LIO_LITo test the importance of evolutionary and ecological factors on bat fly specificity, we collected and identified 21 bat fly species from 16 host bat species from the State of Rio de Janeiro in Brazil. We generated a bat fly species phylogeny from molecular data, estimated d specialization values (a metric of specificity), and used linear and cophylogenetic models to compare the importance of various drivers of parasite ecological specialization. C_LIO_LIWe found that bat fly co-occurrence frequency (a proxy for interspecific competition) and mean infection intensity (a proxy for intraspecific competition) best predicted patterns of bat fly specialization. Co-occurrence frequency had a significantly negative association with specialization, while mean infection intensity has a significantly positive association with specialization. Coevolutionary congruence had a small effect size and did not significantly predict parasite specialization. C_LIO_LIWe found multiple shifts toward more generalized host niches across the bat fly phylogeny. Our results suggest that ecological processes such as resource-driven competition may be more important than evolutionary processes in shaping bat fly host specialization networks. C_LIO_LIBat flies showed variable degrees of host specialization, parasitized phylogenetically distant host species, and showed low phylogenetic congruence to their hosts. This suggests that as a group, bat flies may show flexibility in their host preference phenotypes and may change their host associations in the face of environmental disturbance. C_LI

ecology↗

bioRxiv2019

The CUL5 ubiquitin ligase complex mediates resistance to CDK9 and MCL1 inhibitors in lung cancer cells

Overexpression of anti-apoptotic proteins MCL1 and Bcl-xL is a frequent event in blood and solid cancers. Inhibitors targeting MCL1 are in clinical development, however many cancer models are intrinsically resistant to this approach. To discover mechanisms underlying resistance to MCL1 inhibition, we performed multiple flow-cytometry based genome-wide CRISPR screens that interrogate two drugs directly or indirectly targeting MCL1. Remarkably, both screens identified three components (CUL5, RNF7 and UBE2F) of a cullin-RING ubiquitin ligase complex (CRL5) that resensitized cells to MCL1 inhibition. We find that levels of the BH3-only pro-apoptotic proteins Bim and Noxa are proteasomally regulated by the CRL5 complex. Accumulation of Noxa caused by depletion of CRL5 components particularly skewed the balance in favor of apoptosis when cells were challenged with an MCL1 inhibitor. Discovery of a novel role of CRL5 in apoptosis and resistance to MCL1 inhibitors exposes new drug targets and the potential to improve combination treatments.

cancer biology↗

bioRxiv2018

The ERBB network facilitates KRAS-driven lung tumorigenesis

KRAS is the most frequently mutated driver oncogene in human adenocarcinoma of the lung. There are presently no clinically proven strategies for treatment of KRAS-driven lung cancer. Activating mutations in KRAS are thought to confer independence from upstream signaling, however recent data suggest that this independence may not be absolute. Here we show that initiation and progression of KRAS-driven lung tumors requires input from ERBB family RTKs: Multiple ERBB RTKs are expressed and active from the earliest stages of KRAS driven lung tumor development, and treatment with a multi-ERBB inhibitor suppresses formation of KRasG12D-driven lung tumors. We present evidence that ERBB activity amplifies signaling through the core RAS pathway, supporting proliferation of KRAS mutant tumor cells in culture and progression to invasive disease in vivo. Importantly, brief pharmacological inhibition of the ERBB network significantly enhances the therapeutic benefit of MEK inhibition in an autochthonous tumor setting. Our data suggest that lung cancer patients with KRAS-driven disease may benefit from inclusion of multi-ERBB inhibitors in rationally designed treatment strategies.\n\nOne Sentence SummaryG12 Mutant KRAS requires tonic ERBB network activity for initiation and maintenance of lung cancer

cancer biology↗