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2. Durable responses to ATR inhibition with ceralasertib in tumors with genomic defects and high inflammation

Author

Dillon, Magnus T., Guevara, Jeane, Mohammed, Kabir, Patin, Emmanuel C., Smith, Simon A., Dean, Emma, Jones, Gemma N., Willis, Sophie E., Petrone, Marcella, Silva, Carlos, Thway, Khin, Bunce, Catey, Roxanis, Ioannis, Nenclares, Pablo, Wilkins, Anna, McLaughlin, Martin, Jayme-Laiche, Adoracion, Benafif, Sarah, Nintos, Georgios, Kwatra, Vineet, Grove, Lorna, Mansfield, David, Proszek, Paula, Martin, Philip, Moore, Luiza, Swales, Karen E., Banerji, Udai, Saunders, Mark P., Spicer, James, Forster, Martin D., and Harrington, Kevin J.

Subjects
Tumors -- Drug therapy -- Genetic aspects, Inflammation -- Drug therapy -- Genetic aspects, Health care industry
Abstract

BACKGROUND. Phase 1 study of ATR inhibition alone or with radiation therapy (PATRIOT) was a first-in-human phase I study of the oral ATR (ataxia telangiectasia and Rad3-related) inhibitor ceralasertib (AZD6738) in advanced solid tumors. METHODS. The primary objective was safety. Secondary objectives included assessment of antitumor responses and pharmacokinetic (PK) and pharmacodynamic (PD) studies. Sixty-seven patients received 20-240 mg ceralasertib BD continuously or intermittently (14 of a 28-day cycle). RESULTS. Intermittent dosing was better tolerated than continuous, which was associated with dose-limiting hematological toxicity. The recommended phase 2 dose of ceralasertib was 160 mg twice daily for 2 weeks in a 4-weekly cycle. Modulation of target and increased DNA damage were identified in tumor and surrogate PD. There were 5 (8%) confirmed partial responses (PRs) (40-240 mg BD), 34 (52%) stable disease (SD), including 1 unconfirmed PR, and 27 (41%) progressive disease. Durable responses were seen in tumors with loss of AT-rich interactive domain-containing protein 1A (ARID1A) and DNA damageresponse defects. Treatment-modulated tumor and systemic immune markers and responding tumors were more immune inflamed than nonresponding. CONCLUSION. Ceralasertib monotherapy was tolerated at 160 mg BD intermittently and associated with antitumor activity. TRIAL REGISTRATION. Clinicaltrials.gov: NCT02223923, EudraCT: 2013-003994-84. FUNDING. Cancer Research UK, AstraZeneca, UK Department of Health (National Institute for Health Research), Rosetrees Trust, Experimental Cancer Medicine Centre., Introduction ATR (ataxia telangiectasia and Rad3-related) is a critical kinase in the DNA damage response (DDR) (1, 2). Preclinical data have identified multiple cancer-related phenotypes sensitizing tumor cells to monotherapy [...]

Published
2024
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3. Capturing global spatial context for accurate cell classification in skin cancer histology

Author

Zormpas-Petridis, Konstantinos, Failmezger, Henrik, Roxanis, Ioannis, Blackledge, Matthew, Jamin, Yann, and Yuan, Yinyin

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The spectacular response observed in clinical trials of immunotherapy in patients with previously uncurable Melanoma, a highly aggressive form of skin cancer, calls for a better understanding of the cancer-immune interface. Computational pathology provides a unique opportunity to spatially dissect such interface on digitised pathological slides. Accurate cellular classification is a key to ensure meaningful results, but is often challenging even with state-of-art machine learning and deep learning methods. We propose a hierarchical framework, which mirrors the way pathologists perceive tumour architecture and define tumour heterogeneity to improve cell classification methods that rely solely on cell nuclei morphology. The SLIC superpixel algorithm was used to segment and classify tumour regions in low resolution H&E-stained histological images of melanoma skin cancer to provide a global context. Classification of superpixels into tumour, stroma, epidermis and lumen/white space, yielded a 97.7% training set accuracy and 95.7% testing set accuracy in 58 whole-tumour images of the TCGA melanoma dataset. The superpixel classification was projected down to high resolution images to enhance the performance of a single cell classifier, based on cell nuclear morphological features, and resulted in increasing its accuracy from 86.4% to 91.6%. Furthermore, a voting scheme was proposed to use global context as biological a priori knowledge, pushing the accuracy further to 92.8%. This study demonstrates how using the global spatial context can accurately characterise the tumour microenvironment and allow us to extend significantly beyond single-cell morphological classification., Comment: Accepted by MICCAI COMPAY 2018 workshop

Published
2018

4. Ubiquitylation of MLKL at lysine 219 positively regulates necroptosis-induced tissue injury and pathogen clearance

Author

Garcia, Laura Ramos, Tenev, Tencho, Newman, Richard, Haich, Rachel O., Liccardi, Gianmaria, John, Sidonie Wicky, Annibaldi, Alessandro, Yu, Lu, Pardo, Mercedes, Young, Samuel N., Fitzgibbon, Cheree, Fernando, Winnie, Guppy, Naomi, Kim, Hyojin, Liang, Lung-Yu, Lucet, Isabelle S., Kueh, Andrew, Roxanis, Ioannis, Gazinska, Patrycja, Sims, Martin, Smyth, Tomoko, Ward, George, Bertin, John, Beal, Allison M., Geddes, Brad, Choudhary, Jyoti S., Murphy, James M., Aurelia Ball, K., Upton, Jason W., and Meier, Pascal

Published
2021
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7. Integrated Pharmacodynamic Analysis Identifies Two Metabolic Adaption Pathways to Metformin in Breast Cancer

Author

Lord, Simon R., Cheng, Wei-Chen, Liu, Dan, Gaude, Edoardo, Haider, Syed, Metcalf, Tom, Patel, Neel, Teoh, Eugene J., Gleeson, Fergus, Bradley, Kevin, Wigfield, Simon, Zois, Christos, McGowan, Daniel R., Ah-See, Mei-Lin, Thompson, Alastair M., Sharma, Anand, Bidaut, Luc, Pollak, Michael, Roy, Pankaj G., Karpe, Fredrik, James, Tim, English, Ruth, Adams, Rosie F., Campo, Leticia, Ayers, Lisa, Snell, Cameron, Roxanis, Ioannis, Frezza, Christian, Fenwick, John D., Buffa, Francesca M., and Harris, Adrian L.

Published
2018
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8. Clinical whole-genome sequencing from routine formalin-fixed, paraffin-embedded specimens: pilot study for the 100,000 Genomes Project

Author

Robbe, Pauline, Popitsch, Niko, Knight, Samantha J.L., Antoniou, Pavlos, Becq, Jennifer, He, Miao, Kanapin, Alexander, Samsonova, Anastasia, Vavoulis, Dimitrios V., Ross, Mark T., Kingsbury, Zoya, Cabes, Maite, Ramos, Sara D.C., Page, Suzanne, Dreau, Helene, Ridout, Kate, Jones, Louise J., Tuff-Lacey, Alice, Henderson, Shirley, Mason, Joanne, Buffa, Francesca M., Verrill, Clare, Maldonado-Perez, David, Roxanis, Ioannis, Collantes, Elena, Browning, Lisa, Dhar, Sunanda, Damato, Stephen, Davies, Susan, Caulfield, Mark, Bentley, David R., Taylor, Jenny C., Turnbull, Clare, and Schuh, Anna

Published
2018
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10. Integrated Multimodal Analyses of DNA Damage Response and Immune Markers as Predictors of Response in Metastatic Triple-Negative Breast Cancer in the TNT Trial (NCT00532727)

Author

Tovey, Holly, primary, Sipos, Orsolya, additional, Parker, Joel S., additional, Hoadley, Katherine A., additional, Quist, Jelmar, additional, Kernaghan, Sarah, additional, Kilburn, Lucy, additional, Salgado, Roberto, additional, Loi, Sherene, additional, Kennedy, Richard D., additional, Roxanis, Ioannis, additional, Gazinska, Patrycja, additional, Pinder, Sarah E., additional, Bliss, Judith, additional, Perou, Charles M., additional, Haider, Syed, additional, Grigoriadis, Anita, additional, Tutt, Andrew, additional, and Cheang, Maggie Chon U., additional

Published
2023
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11. Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes

Author

Graham, Rosalind, primary, Gazinska, Patrycja, additional, Zhang, Birong, additional, Khiabany, Atousa, additional, Sinha, Shubhankar, additional, Alaguthurai, Thanussuyah, additional, Flores-Borja, Fabian, additional, Vicencio, Jose, additional, Beuron, Fabienne, additional, Roxanis, Ioannis, additional, Matkowski, Rafal, additional, Liam-Or, Revadee, additional, Tutt, Andrew, additional, Ng, Tony, additional, Al-Jamal, Khuloud T., additional, Zhou, You, additional, and Irshad, Sheeba, additional

Published
2023
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13. Abstract 6094: Longitudinal analysis of PARP inhibitor and platinum resistance in BRCA1/2m breast cancer using liquid biopsy

Author

Harvey-Jones, Elizabeth, primary, Raghunandan, Maya, additional, Robbez-Masson, Luisa, additional, Thanussuyah, Alaguthurai, additional, Liccardo, Roberta, additional, Yablonovitch, Arielle, additional, Cai, Mingyang, additional, Drusbosky, Leylah, additional, Dorschner, Michael, additional, Pardo, Lorena Magraner, additional, Marlow, Rebecca, additional, Konde, Asha, additional, Trendell, Jennifer, additional, Alexander, John, additional, Haider, Syed, additional, Starling, Chris, additional, Roxanis, Ioannis, additional, Yen, Jennifer, additional, Pettitt, Stephen J., additional, Lord, Christopher J., additional, and Tutt, Andrew N., additional

Published
2023
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14. Abstract PD9-06: Histopathological and molecular immune landscape and DNA damage response signatures to predict response to carboplatin and docetaxel in TNT trial TNBC cohort

Author

Tovey, Holly, primary, Sipos, Orsolya, additional, Hoadley, Katherine A, additional, Parker, Joel S, additional, Quist, Jelmar, additional, Kernaghan, Sarah, additional, Kilburn, Lucy, additional, Salgado, Roberto, additional, Loi, Sherene, additional, Kennedy, Richard D, additional, Roxanis, Ioannis, additional, Gazinska, Patrycja, additional, Pinder, Sarah E., additional, Bliss, Judith, additional, Perou, Charles M., additional, Haider, Syed, additional, Tutt, Andrew, additional, Grigoriadis, Anita, additional, and Cheang, Maggie Chon U, additional

Published
2023
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15. Abstract P6-10-05: Mutations in the RNA Splicing Factor SF3B1 drive endocrine therapy resistance and confer a targetable replication stress response defect through PARP inhibition

Author

Bland, Phil, primary, Saville, Harry, additional, Read, Abigail, additional, Wai, Patty, additional, Muirhead, Gareth, additional, Curnow, Lucinda, additional, Nieminuszczy, Jadwiga, additional, Ravindran, Nivedita, additional, John, Marie, additional, Hedayat, Somaieh, additional, Barker, Holly, additional, Wright, James, additional, Yu, Lu, additional, Mavrommati, Ioanna, additional, Peck, Barrie, additional, Allen, Mark, additional, Gazinska, Patrycja, additional, Pemberton, Helen, additional, Gulati, Aditi, additional, Nash, Sarah, additional, Noor, Farzana, additional, Guppy, Naomi, additional, Roxanis, Ioannis, additional, Barlow, Samantha, additional, Kalirai, Helen, additional, Coupland, Sarah, additional, Broderick, Ronan, additional, Alsafadi, Samar, additional, Houy, Alexandre, additional, Stern, Marc-Henri, additional, Pettit, Stephen, additional, Choudhary, Jyoti, additional, Haider, Syed, additional, Niedzwiedz, Wojciech, additional, Lord, Christopher, additional, and Natrajan, Rachael, additional

Published
2023
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16. Dynamic Changes in the NK-, Neutrophil-, and B-cell Immunophenotypes Relevant in High Metastatic Risk Post Neoadjuvant Chemotherapy–Resistant Early Breast Cancers

Author

Gazinska, Patrycja, primary, Milton, Charlotte, additional, Iacovacci, Jacopo, additional, Ward, Joseph, additional, Buus, Richard, additional, Alaguthurai, Thanussuyah, additional, Graham, Rosalind, additional, Akarca, Ayse, additional, Lips, Esther, additional, Naidoo, Kalnisha, additional, Wesseling, Jelle, additional, Marafioti, Teresa, additional, Cheang, Maggie, additional, Gillett, Cheryl, additional, Wu, Yin, additional, Khan, Aadil, additional, Melcher, Alan, additional, Salgado, Roberto, additional, Dowsett, Mitch, additional, Tutt, Andrew, additional, Roxanis, Ioannis, additional, Haider, Syed, additional, and Irshad, Sheeba, additional

Published
2022
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19. ADGRL4/ELTD1 Expression in Breast Cancer Cells Induces Vascular Normalization and Immune Suppression

Author

Sheldon, Helen, primary, Bridges, Esther, additional, Silva, Ildefonso, additional, Masiero, Massimo, additional, Favara, David M., additional, Wang, Dian, additional, Leek, Russell, additional, Snell, Cameron, additional, Roxanis, Ioannis, additional, Kreuzer, Mira, additional, Gileadi, Uzi, additional, Buffa, Francesca M., additional, Banham, Alison, additional, and Harris, Adrian L., additional

Published
2021
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20. Quantitative Assessment and Prognostic Associations of the Immune Landscape in Ovarian Clear Cell Carcinoma

Author

Khalique, Saira, primary, Nash, Sarah, additional, Mansfield, David, additional, Wampfler, Julian, additional, Attygale, Ayoma, additional, Vroobel, Katherine, additional, Kemp, Harriet, additional, Buus, Richard, additional, Cottom, Hannah, additional, Roxanis, Ioannis, additional, Jones, Thomas, additional, von Loga, Katharina, additional, Begum, Dipa, additional, Guppy, Naomi, additional, Ramagiri, Pradeep, additional, Fenwick, Kerry, additional, Matthews, Nik, additional, Hubank, Michael, additional, Lord, Christopher, additional, Haider, Syed, additional, Melcher, Alan, additional, Banerjee, Susana, additional, and Natrajan, Rachael, additional

Published
2021
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21. 3D Functional Genomics Screens Identify CREBBP as a Targetable Driver in Aggressive Triple-Negative Breast Cancer

Author

Peck, Barrie, primary, Bland, Philip, additional, Mavrommati, Ioanna, additional, Muirhead, Gareth, additional, Cottom, Hannah, additional, Wai, Patty T., additional, Maguire, Sarah L., additional, Barker, Holly E., additional, Morrison, Eamonn, additional, Kriplani, Divya, additional, Yu, Lu, additional, Gibson, Amy, additional, Falgari, Giulia, additional, Brennan, Keith, additional, Farnie, Gillian, additional, Buus, Richard, additional, Marlow, Rebecca, additional, Novo, Daniela, additional, Knight, Eleanor, additional, Guppy, Naomi, additional, Kolarevic, Daniela, additional, Susnjar, Snezana, additional, Milijic, Natasa Medic, additional, Naidoo, Kalnisha, additional, Gazinska, Patrycja, additional, Roxanis, Ioannis, additional, Pancholi, Sunil, additional, Martin, Lesley-Ann, additional, Holgersen, Erle M., additional, Cheang, Maggie C.U., additional, Noor, Farzana, additional, Postel-Vinay, Sophie, additional, Quinn, Gerard, additional, McDade, Simon, additional, Krasny, Lukas, additional, Huang, Paul, additional, Daley, Frances, additional, Wallberg, Fredrik, additional, Choudhary, Jyoti S., additional, Haider, Syed, additional, Tutt, Andrew N., additional, and Natrajan, Rachael, additional

Published
2021
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22. A FIJI macro for quantifying pattern in extracellular matrix

Author

Wershof, Esther, primary, Park, Danielle, additional, Barry, David J, additional, Jenkins, Robert P, additional, Rullan, Antonio, additional, Wilkins, Anna, additional, Schlegelmilch, Karin, additional, Roxanis, Ioannis, additional, Anderson, Kurt I, additional, Bates, Paul A, additional, and Sahai, Erik, additional

Published
2021
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24. Superpixel-based conditional random fields (SuperCRF) : incorporating global and local context for enhanced deep learning in melanoma histopathology

Author

Zormpas-Petridis, Konstantinos, Failmezger, Henrik, Raza, Shan E. Ahmed, Roxanis, Ioannis, Jamin, Yann, and Yuan, Yinyin

Subjects
QA76, RC
Abstract

Computational pathology-based cell classification algorithms are revolutionizing the study of the tumor microenvironment and can provide novel predictive/prognosis biomarkers crucial for the delivery of precision oncology. Current algorithms used on hematoxylin and eosin slides are based on individual cell nuclei morphology with limited local context features. Here, we propose a novel multi-resolution hierarchical framework (SuperCRF) inspired by the way pathologists perceive regional tissue architecture to improve cell classification and demonstrate its clinical applications. We develop SuperCRF by training a state-of-art deep learning spatially constrained- convolution neural network (SC-CNN) to detect and classify cells from 105 high-resolution (20×) H&E-stained slides of The Cancer Genome Atlas melanoma dataset and subsequently, a conditional random field (CRF) by combining cellular neighborhood with tumor regional classification from lower resolution images (5, 1.25×) given by a superpixel-based machine learning framework. SuperCRF led to an 11.85% overall improvement in the accuracy of the state-of-art deep learning SC-CNN cell classifier. Consistent with a stroma-mediated immune suppressive microenvironment, SuperCRF demonstrated that (i) a high ratio of lymphocytes to all lymphocytes within the stromal compartment (p = 0.026) and (ii) a high ratio of stromal cells to all cells (p < 0.0001 compared to p = 0.039 for SC-CNN only) are associated with poor survival in patients with melanoma. SuperCRF improves cell classification by introducing global and local context-based information and can be implemented in combination with any single-cell classifier. SuperCRF provides valuable tools to study the tumor microenvironment and identify predictors of survival and response to therapy.

Published
2019

27. Nuclear HER4 mediates acquired resistance to trastuzumab and is associated with poor outcome in HER2 positive breast cancer

Author

Ji-Liang Li, Carla Strina, Gabriela Kramer-Marek, Syed Haider, Merel Gijsen, Esther Bridges, Daniele Generali, Jacek Capala, Anthony Kong, Daniele Andreis, Adrian L. Harris, Mariarosa Cappelletti, Siti Norasikin Mohd Nafi, Roxanis Ioannis, Nafi, Siti Norasikin Mohd, Generali, Daniele, Kramer Marek, Gabriela, Gijsen, Merel, Strina, Carla, Cappelletti, Mariarosa, Andreis, Daniele, Haider, Syed, Li, Ji Liang, Bridges, Esther, Capala, Jacek, Ioannis, Roxani, Harris, Adrian L., and Kong, Anthony

Subjects
animal structures, Receptor, ErbB-4, Receptor, ErbB-2, Resistance, Antineoplastic Agents, Breast Neoplasms, Drug resistance, Mice, Breast cancer, Downregulation and upregulation, Trastuzumab, Cell Line, Tumor, HER2, Medicine, Neoplasm, Animals, Humans, HER4, skin and connective tissue diseases, neoplasms, Cell Nucleus, Oncology, Medicine (all), Gene knockdown, business.industry, medicine.disease, Prognosis, 3. Good health, Drug Resistance, Neoplasm, Immunology, Neratinib, Cancer research, MCF-7 Cells, Heterografts, Female, business, Tyrosine kinase, medicine.drug, Research Paper
Abstract

The role of HER4 in breast cancer is controversial and its role in relation to trastuzumab resistance remains unclear. We showed that trastuzumab treatment and its acquired resistance induced HER4 upregulation, cleavage and nuclear translocation. However, knockdown of HER4 by specific siRNAs increased trastuzumab sensitivity and reversed its resistance in HER2 positive breast cancer cells. Preventing HER4 cleavage by a γ-secretase inhibitor and inhibiting HER4 tyrosine kinase activity by neratinib decreased trastuzumab-induced HER4 nuclear translocation and enhanced trastuzumab response. There was also increased nuclear HER4 staining in the tumours from BT474 xenograft mice and human patients treated with trastuzumab. Furthermore, nuclear HER4 predicted poor clinical response to trastuzumab monotherapy in patients undergoing a window study and was shown to be an independent poor prognostic factor in HER2 positive breast cancer. Our data suggest that HER4 plays a key role in relation to trastuzumab resistance in HER2 positive breast cancer. Therefore, our study provides novel findings that HER4 activation, cleavage and nuclear translocation influence trastuzumab sensitivity and resistance in HER2 positive breast cancer. Nuclear HER4 could be a potential prognostic and predictive biomarker and understanding the role of HER4 may provide strategies to overcome trastuzumab resistance in HER2 positive breast cancer.

Published
2014

28. Paracrine effect of GTP cyclohydrolase and angiopoietin-1 interaction in stromal fibroblasts on tumor Tie2 activation and breast cancer growth

Author

Chen, Liye, primary, Zeng, Xin, additional, Kleibeuker, Esther, additional, Buffa, Francesca, additional, Barberis, Alessandro, additional, Leek, Russell D., additional, Roxanis, Ioannis, additional, Zhang, Wei, additional, Worth, Andrew, additional, Beech, John S., additional, Harris, Adrian L., additional, and Cai, Shijie, additional

Published
2016
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31. ADAM10 mediates trastuzumab resistance and is correlated with survival in HER2 positive breast cancer

Author

Feldinger, Katharina, primary, Generali, Daniele, additional, Kramer-Marek, Gabriela, additional, Gijsen, Merel, additional, Ng, Tzi Bun, additional, Wong, Jack Ho, additional, Strina, Carla, additional, Cappelletti, Mariarosa, additional, Andreis, Daniele, additional, Li, Ji-Liang, additional, Bridges, Esther, additional, Turley, Helen, additional, Leek, Russell, additional, Roxanis, Ioannis, additional, Capala, Jacek, additional, Murphy, Gillian, additional, Harris, Adrian L., additional, and Kong, Anthony, additional

Published
2014
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32. Neratinib overcomes trastuzumab resistance in HER2 amplified breast cancer

Author

Canonici, Alexandra, primary, Gijsen, Merel, additional, Mullooly, Maeve, additional, Bennett, Ruth, additional, Bouguern, Noujoude, additional, Pedersen, Kasper, additional, O’Brien, Neil A, additional, Roxanis, Ioannis, additional, Li, Ji-Liang, additional, Bridge, Esther, additional, Finn, Richard, additional, Slamon, Dennis, additional, McGowan, Patricia, additional, Duffy, Michael J., additional, O’Donovan, Norma, additional, Crown, John, additional, and Kong, Anthony, additional

Published
2013
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36. Integrated Pharmacodynamic Analysis Identifies Two Metabolic Adaption Pathways to Metformin in Breast Cancer

Author

Lord, Simon R., Cheng, Wei-Chen, Liu, Dan, Gaude, Edoardo, Haider, Syed, Metcalf, Tom, Patel, Neel, Teoh, Eugene J., Gleeson, Fergus, Bradley, Kevin, Wigfield, Simon, Zois, Christos, McGowan, Daniel R., Ah-See, Mei-Lin, Thompson, Alastair M., Sharma, Anand, Bidaut, Luc, Pollak, Michael, Roy, Pankaj G., Karpe, Fredrik, James, Tim, English, Ruth, Adams, Rosie F., Campo, Leticia, Ayers, Lisa, Snell, Cameron, Roxanis, Ioannis, Frezza, Christian, Fenwick, John D., Buffa, Francesca M., Harris, Adrian L., Lord, Simon R., Cheng, Wei-Chen, Liu, Dan, Gaude, Edoardo, Haider, Syed, Metcalf, Tom, Patel, Neel, Teoh, Eugene J., Gleeson, Fergus, Bradley, Kevin, Wigfield, Simon, Zois, Christos, McGowan, Daniel R., Ah-See, Mei-Lin, Thompson, Alastair M., Sharma, Anand, Bidaut, Luc, Pollak, Michael, Roy, Pankaj G., Karpe, Fredrik, James, Tim, English, Ruth, Adams, Rosie F., Campo, Leticia, Ayers, Lisa, Snell, Cameron, Roxanis, Ioannis, Frezza, Christian, Fenwick, John D., Buffa, Francesca M., and Harris, Adrian L.

Abstract

Late-phase clinical trials investigating metformin as a cancer therapy are underway. However, there remains controversy as to the mode of action of metformin in tumors at clinical doses. We conducted a clinical study integrating measurement of markers of systemic metabolism, dynamic FDG-PET-CT, transcriptomics, and metabolomics at paired time points to profile the bioactivity of metformin in primary breast cancer. We show metformin reduces the levels of mitochondrial metabolites, activates multiple mitochondrial metabolic pathways, and increases 18-FDG flux in tumors. Two tumor groups are identified with distinct metabolic responses, an OXPHOS transcriptional response (OTR) group for which there is an increase in OXPHOS gene transcription and an FDG response group with increased 18-FDG uptake. Increase in proliferation, as measured by a validated proliferation signature, suggested that patients in the OTR group were resistant to metformin treatment. We conclude that mitochondrial response to metformin in primary breast cancer may define anti-tumor effect.

37. Investigating the role of ADAM10 and ADAM17 in cetuximab resistance in head and neck squamous cell carcinoma

Author

Kareemaghay, Sedigeh, Seymour, Len, Kong, Anthony, and Roxanis, Ioannis

Subjects
616.99, Medical sciences, Oncology, cetuximab, resistance
Abstract

Epithermal Growth Factor Receptor (EGFR) is overexpressed in up to 90% of head and neck squamous cell carcinoma (HNSCC). Cetuximab is the first and the only anti-EGFR monoclonal antibody which received approval from FDA for the treatment of HNSCC. However, most patients either do not respond to cetuximab or develop acquired resistance. The aim of my D.Phil. study was to investigate the role of ADAM10 and 17 in resistance mechanisms of cetuximab in HNSCC. Chronic exposure to cetuximab led to an activation of HER receptors and downstream signalling pathways in HNSCC cell lines. Higher levels of ADAM10 and 17 and their substrates, BTC and NRG-1 were found in cetuximab resistant cells compared to their parental cells, suggesting the involvement of ADAM-mediated ligands’ release in reactivation of HER receptors. Inhibition or knockdown of ADAM10 and 17 enhanced cetuximab response and reversed cetuximab resistance in HNSCC cells. In addition, results from this study showed that the combination of cetuximab with EGFR-TKIs had greater effect in parental cells and reversed cetuximab resistance in HNSCC cells. Upregulation of ADAM10 and 17 also was observed in HNSCC TMAs compared to normal head and neck TMAs. High nuclear ADAM10 and cytoplasmic ADAM17 expression levels were associated with shorter DFS. By evaluating tumour excision samples from HNSCC patients who underwent a cetuximab window study high ADAM10 and 17 expression levels were found to be associated with poor response to cetuximab. In conclusion cetuximab-induced ADAM-mediated ligands’ release is a potential mechanism of resistance to cetuximab in HNSCC. Thus, targeting ADAM10/17 or subsequent HER activations may represent an important strategy in overcoming resistance to cetuximab in HNSCC. Results from this study also suggest the implication of ADAM10 and 17 as potential prognostic and predictive biomarkers in HNSCC although further validation is required.

Published
2014

39. Superpixel-Based Conditional Random Fields (SuperCRF): Incorporating Global and Local Context for Enhanced Deep Learning in Melanoma Histopathology.

Author

Zormpas-Petridis K, Failmezger H, Raza SEA, Roxanis I, Jamin Y, and Yuan Y

Abstract

Computational pathology-based cell classification algorithms are revolutionizing the study of the tumor microenvironment and can provide novel predictive/prognosis biomarkers crucial for the delivery of precision oncology. Current algorithms used on hematoxylin and eosin slides are based on individual cell nuclei morphology with limited local context features. Here, we propose a novel multi-resolution hierarchical framework (SuperCRF) inspired by the way pathologists perceive regional tissue architecture to improve cell classification and demonstrate its clinical applications. We develop SuperCRF by training a state-of-art deep learning spatially constrained- convolution neural network (SC-CNN) to detect and classify cells from 105 high-resolution (20×) H&E-stained slides of The Cancer Genome Atlas melanoma dataset and subsequently, a conditional random field (CRF) by combining cellular neighborhood with tumor regional classification from lower resolution images (5, 1.25×) given by a superpixel-based machine learning framework. SuperCRF led to an 11.85% overall improvement in the accuracy of the state-of-art deep learning SC-CNN cell classifier. Consistent with a stroma-mediated immune suppressive microenvironment, SuperCRF demonstrated that (i) a high ratio of lymphocytes to all lymphocytes within the stromal compartment ( p = 0.026) and (ii) a high ratio of stromal cells to all cells ( p < 0.0001 compared to p = 0.039 for SC-CNN only) are associated with poor survival in patients with melanoma. SuperCRF improves cell classification by introducing global and local context-based information and can be implemented in combination with any single-cell classifier. SuperCRF provides valuable tools to study the tumor microenvironment and identify predictors of survival and response to therapy., (Copyright © 2019 Zormpas-Petridis, Failmezger, Raza, Roxanis, Jamin and Yuan.)

Published
2019
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