Biology subjects

Boyle, T.

Publications and source records attributed to Boyle, T..

4 recordsLinked to original sources

bioRxiv2026

Ex Vivo Culture of Patient-Derived Primary, Metastatic, and Post-Mortem Lung Cancer Reveals Targetable States of EMT and Metabolic Plasticity

Lung cancer is a highly heterogeneous disease and remains the leading cause of cancer-related mortality worldwide. While mouse models and patient-derived organoids have advanced our understanding of lung cancer, key interactions within the tumor microenvironment (TME) remain poorly characterized. We developed microtumor models from lung adenocarcinoma (LUAD) and small cell lung cancer (SCLC) using mouse and patient samples, including surgical resections and rapid autopsy specimens. Microtumors preserve structural, cellular, and molecular features of the native TME, enabling mechanistic studies of tumor progression ex vivo. Multi-omics analyses of LUAD microtumors revealed progression-associated changes, including increased epithelial-to-mesenchymal transition (EMT) and metabolic reprogramming toward fatty acid synthesis. Pharmacologic inhibition of fatty acid synthesis through ACC1/2 reduced proliferation in patient-derived microtumors, identifying a targetable vulnerability. This platform provides a robust system for studying tumor progression, therapeutic response, and resistance mechanisms in lung cancer, including culturing postmortem specimens that are not accessible in current models.

cancer biology↗

bioRxiv2024

Trastuzumab deruxtecan combination strongly enhances responses and overcomes sotorasib resistance in KRASG12C-mutant NSCLC

IntroductionRecent advances in the treatment of KRAS-mutant non-small cell lung cancer (NSCLC) have led to the development of KRASG12C inhibitors, such as sotorasib and adagrasib. However, resistance and disease progression remain significant challenges. In this study, we investigated the therapeutic potential of combining trastuzumab deruxtecan (T-DXd), an anti-HER2 antibody-drug conjugate, with sotorasib in KRASG12C-mutant NSCLC, while also evaluating HER2 expression in NSCLC samples. MethodsThe HER2 expression dependence of xenograft responses to sotorasib, T-DXd, and their combination was evaluated in therapy-naive and sotorasib-treated tumors by immunohistochemistry (IHC). Also, we analyzed 191 clinical (pre- or on-treatment) and rapid autopsy (post-treatment) samples from 31 patients with driver-positive and driver-negative advanced stage NSCLC, assessing HER2 expression using interpretation guidelines developed for breast cancer (BC) and gastroesophageal adenocarcinoma (GEA). ResultsIn the majority of preclinical models, including sotorasib-resistant tumors, the sotorasib-T-DXd combination induced stronger and more durable responses compared to monotherapies. The strong effect of the combination therapy was likely attributable to sotorasib-induced adaptive HER2 upregulation; stronger HER2 expression in sotorasib-treated tumors was linked with stronger responses. Although HER2 expression was higher in samples from patients with KRASG12C-mutant NSCLC compared to NSCLC with other driver mutations or no drivers, the difference was not statistically significant. HER2 IHC score discrepancy was also observed between BC and GEA interpretation guidelines. ConclusionsOur results support the potential clinical utility of the sotorasib-T-DXd combination, including tumors with intrinsic and acquired resistance to sotorasib monotherapy. Since the strengths of the responses depend on HER2 expression levels, successful clinical implementation necessitates optimizing patient selection. Our results highlight the complexities of accurate HER2 interpretation in NSCLC and highlight the need for standardized testing methods.

cancer biology↗

bioRxiv2022

Disassembly of embryonic keratin filaments promotes pancreatic cancer

Keratin 17 (K17), an oncofetal intermediate filament protein, is one of the most abundantly expressed proteins in pancreatic ductal adenocarcinomas (PDACs) of the most aggressive molecular subtype. The mechanistic roles of this protein in malignancy, however, are largely unexplored. Here we show that K17 expression and disassembly enhances tumor growth and metastatic potential and shortens survival. Using mass spectrometry in K17 isolated from patients tumors, we identified a hotspot phosphorylation site in serines 10-13. Site-mutagenesis revealed that phosphorylation of this hotspot is sufficient to disassemble K17 and promote its nuclear translocation. In silico and pharmacologic inhibition studies uncovered the role of the PKC/MEK/RSK pathway in the phosphorylation and disassembly of K17. Murine models bearing tumors expressing phosphomimetic mutations at the serine hotspot displayed enhanced metastases, compared to mice bearing tumors expressing wild-type K17 or phosphorylation-resistant K17. Lastly, we found that detergent-soluble nuclear K17 promotes the expression of metastasis promoting genes in both patient and murine tumors. These results suggest that phosphorylation at specific serines is sufficient to promote pancreatic cancer metastasis and shorter survival, and that these sites could provide novel, druggable therapeutic domains to enhance PDAC patient survival.

cancer biology↗

bioRxiv2020

Hypoxia-related radiomics predict immunotherapy response: A multi-cohort study of NSCLC

Checkpoint blockade immunotherapy provides improved long-term survival in a subset of advanced stage non-small cell lung cancer (NSCLC) patients. However, highly predictive biomarkers of immunotherapy response are unmet clinical need. In this study, we utilized pre-treatment clinical factors and quantitative image-based biomarkers (radiomics) to identify a parsimonious model that predicts survival outcomes among NSCLC patients treated with immunotherapy. The NSCLC patients treated with single or double agent immunotherapy were included in three different cohorts: Training (N = 180), test (N = 90) and validation (N = 62) cohorts. The models were created based on overall survival (OS) and were additionally assessed for progression-free survival (PFS). Including most predictive radiomic features and clinical covariates, Classification and Regression Tree analysis was applied to stratify patients into survival risk-groups in the training cohort. The risk groups were later generated in the test and validation cohorts. Four independent NSCLC cohorts (total N = 446) were utilized for further validation of the radiomic signature. The biological underpinnings of the most informative radiomics were assessed using gene expression data from a radiogenomics dataset and validated by immunohistochemistry data (IHC). A parsimonious clinical-radiomics model was found to be significantly associated with OS and PFS after stratifying patients into groups of low-, moderate-, high-, and very-high risk of death and progression. This trained model was further tested and validated in two independent cohorts. When the extreme phenotypes were compared, the very-high risk group was found to be associated with extremely poor OS in both the test (hazard ratio [HR] = 5.35, 95% confidence interval [CI]: 2.14 - 13.36; 1-year OS = 11.1%) and validation (HR = 13.81, 95% CI: 2.58 - 73.93; 1-year OS = %47.6) cohorts when compared to the low risk group (HRs = 1.00; 1-year OS = 85.0% & 80.2%). Similar findings were observed for PFS. The final radiomic feature (GLCM inverse difference) was associated with OS in four independent NSCLC cohorts and was found to be positively associated with the hypoxia-related carbonic anhydrase, CAIX, by gene expression profiling and immunohistochemistry. We validated a novel clinical-radiomics model that is associated with OS and PFS among NSCLC patients treated with immunotherapy and identified a highly vulnerable subset of patients that are unlikely to respond to immunotherapy. The most informative radiomic feature was associated with CAIX, a marker of tumor hypoxia, tumor acidosis, and treatment resistance.

bioinformatics↗