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2. Somatic cancer genetics in the UK: real-world data from phase I of the Cancer Research UK Stratified Medicine Programme

Author

Lindsay, Colin R., Shaw, Emily C., Blackhall, Fiona, Blyth, Kevin G., Brenton, James D., Chaturvedi, Anshuman, Clarke, Noel, Dick, Craig, Evans, Thomas R.J., Hall, Geoff, Hanby, Andrew M., Harrison, David J., Johnston, Stephen R.D., Mason, Malcolm D., Morton, Dion, Newton-Bishop, Julia, Nicholson, Andrew G., Oien, Karin A., Popat, Sanjay, Rassl, Doris, Sharpe, Rowena, Taniere, Phillipe, Walker, Ian, Wallace, William A., West, Nicholas P., Butler, Rachel, Gonzalez de Castro, David, Griffiths, Mike, Johnson, Peter W.M., Rehal, Pauline, Butler, Samantha, Smith, Matthew, Doak, Rachel, Tanska, Anna, Halford, Graham, James, Lisa, Kotara, Chris, Masson, Gareth, Clokie, Sam, Bell, Jennie, Macdonald, Fiona, De Castro, David Gonzalez, Thompson, Lisa, Mair, Debbie, Lillis, Suzanne, Wren, Dorte, Hollifield, Robert, Dover, Keeda, Maurya, Manisha, Brooks, Damian, Gomez, Belen, Grady, Lisa, Jones, Thomas, Hooper, Chantal, Webster, Daphne, Travis, Jolyon, Ogwuru, Stephanie, Gazdova, Jana, Collins, Denise, Chapman, Elaine, Leavey, Lisa, Proszek, Paula, Hulkki, Sanna, Collins, V.Peter, Ibrahim, Ash, Brown, Kat, Burge, Jo, Burnett, Karen, Devonshire, Ginny, Moseley, Ellen, Haynes, Bev, Hodgkin, Charlotte, Jimenez-linan, Merche, Jones, Linda, Kenyon, Gilly, Mahler-araujo, Betania, Payne, Karen, Piper, Jo, Richardson, Sue, Rytina, Ed, Warren, Anne, Coker, Liz, Godsall, Gemma, Arends, Mark, O’Neill, Amanda, Rintoul, Katy, Goymer, Donna, Taylor, Julie, Matthews, Claire, Bhayani, Harshil, Osalador, Tina, Niwaz, Zakiya, Higgins, Anna, Bamsey, Olivia, Salter, Janine, Renouf, Louise, Noel-Storr, Glenn, Roberts, Helen, Gierejko, Kasia, Knapman, Paola, Wotherspoon, Andrew, Stamp, Gordon, Attygailye, Ayoma, Hazell, Steve, Osin, Peter, Nerurkar, Ash, Francis, Steven, Runde, Marion, Arch, Jo, Chitnis, Xavier, Siu, Bernard, Townsend, Debra, Hennelly, Laura, Taylor, Natalie, Johnson, Bernadette, Banerjee, Susie, Pyle, Lynda, Hamill, Monica, Gyertson, Jenny, George, Angela, Patel, Krishna, Pearce, Karla, Edmonds, Kim, Sarker, Sarah, Eeles, Rosalind, Bancroft, Liz, Thomas, Sarah, Kano, Yukie, Rowland, Lisa, Brooks, Karen, O’brien, Mary, Bhosle, Jaishree, Priest, Kathy, Ayite, Bee, Severn, Jo, Beedham, Helen, Lucas, Nicky, Tye, Kim, Lorentzos, Alison, Webb, Janine, Kerr, Sarah, Corestav, Lisa, Bottero, Diego, Jell, Laura, Thomas, Janet, Marriott, Cheryl, Rajah, Neil, Cole, Andy, Ly, Dieu, Taniere, Philippe, O’sullivan, Brendan, Swift, Clare, Hughes, Frances, Neil, Desley, Hanby, Andrew, Banks, Roz, Ajayi, Dolapo, Barclay, Alison, Bishop, Julia Newton, Beirne, Debbie, Bernard, Andrew, Berry, Maxine, Bentley, Jo, Bishop, Tim, Chambers, Amy, Clarke, Jude, Crossley, Anne, Gahir, Narinder, Gibson, Debbie, Good, Rona, Grosios, Konstantina, Harnden, Pat, Hasler, Kate, Hindmarch, Damien, Jackson, Sharon, Johnstone, Colin, Jones, Anne-marie, Lambert, Gil, Lane, Sally, Mcnicholas, Nicola, Millican-Slater, Rebecca, Moriaty, Cath, Newsham, Alex, O’connell, Kara, Ripley, Lisa, Sebag-Montefiore, David, Simpson, Mary, Speirs, Val, Sugden, Joh, Tate, Lauren, Tidswell, Emma, Twelves, Chris, Walker, Christy, Waterhouse, Barry, Waugh, Martin, White, Louise, Wright, Elizabeth, Rogan, Jane, Ashton, Garry, Abbey, Caron, Greenhalgh, Michelle, Nonaka, Daisuke, Shing, Elwyn, Gibbard, Carmen, Burton, Georgina, Fawkes, Naomi, Marsden, Angela, Waddington, Rachael, Harrison, Phil, Moghadam, Shahrzad, Murray, Kate, Brown, Sarah, Mitchinson, Christy, Booton, Richard, Shah, Rajesh, Harrison, David, Oniscu, Anca, Wallace, William, Rae, Frances, Marshall, Craig, Mcleod, Linda, Charles, Morag, Sutherland, Sarah Jane, Dawson, Carol, Mitchell, Paul, Maclellan, Alex, Muir, Sandra, Johnstone, Lynne, O’connor, John, Johnstone, Shirley, Mcpherson, Jim, Hair, Jane, Pignatelli, Massimo, Armstrong, Roma, Oien, Karin, Evans, Jeff, Burgoyne, Margaret, Blessing, Karen, Duthie, Fraser, Moyes, Colin, Mallon, Elizabeth, Millan, David, Roberts, Fiona, Seywright, Morag, Fraser, Siobhan, Ford, Ian, Kean, Sharon, Flood, Marion, Grant, David, Mcdonald, Claire, Moffat, Tom, Mclelland, Hugh, Kyle, Alistair, Cameron, Graham, Wright, Martin, Kenny, Stephen, Mcauslan, Karen, Jones, Andrew, Fitzsimons, Ted, Graham, Fiona, Bell, Alexandra, Duffy, Phil, Fisher, Alec, Smith, Alexis, Shannon, Elaine, Woods, Bryan, Hutchison, Colin, Booth, Angela, Duffy, Lyndsay, Mcculloch, Gillian, Sadiq, Hudda, Deakin, Susan, Haywood, Steven, Mason, Malcolm, Chester, John, Parry-jones, Alison, Macarthur, Abby, Williams, Suzanne, Griffiths, David, Morgan, Fiona, and Bailey, Hazel

Published
2018
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3. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution

Author

Abbosh, Christopher, Birkbak, Nicolai J., Wilson, Gareth A., Jamal-Hanjani, Mariam, Constantin, Tudor, Salari, Raheleh, Le Quesne, John, Moore, David A., Veeriah, Selvaraju, Rosenthal, Rachel, Marafioti, Teresa, Kirkizlar, Eser, Watkins, Thomas B. K., McGranahan, Nicholas, Ward, Sophia, Martinson, Luke, Riley, Joan, Fraioli, Francesco, Al Bakir, Maise, Grnroos, Eva, Zambrana, Francisco, Endozo, Raymondo, Bi, Wenya Linda, Fennessy, Fiona M., Sponer, Nicole, Johnson, Diana, Laycock, Joanne, Shafi, Seema, Czyzewska-Khan, Justyna, Rowan, Andrew, Chambers, Tim, Matthews, Nik, Turajlic, Samra, Hiley, Crispin, Lee, Siow Ming, Forster, Martin D., Ahmad, Tanya, Falzon, Mary, Borg, Elaine, Lawrence, David, Hayward, Martin, Kolvekar, Shyam, Panagiotopoulos, Nikolaos, Janes, Sam M., Thakrar, Ricky, Ahmed, Asia, Blackhall, Fiona, Summers, Yvonne, Hafez, Dina, Naik, Ashwini, Ganguly, Apratim, Kareht, Stephanie, Shah, Rajesh, Joseph, Leena, Marie Quinn, Anne, Crosbie, Phil A., Naidu, Babu, Middleton, Gary, Langman, Gerald, Trotter, Simon, Nicolson, Marianne, Remmen, Hardy, Kerr, Keith, Chetty, Mahendran, Gomersall, Lesley, Fennell, Dean A., Nakas, Apostolos, Rathinam, Sridhar, Anand, Girija, Khan, Sajid, Russell, Peter, Ezhil, Veni, Ismail, Babikir, Irvin-Sellers, Melanie, Prakash, Vineet, Lester, Jason F., Kornaszewska, Malgorzata, Attanoos, Richard, Adams, Haydn, Davies, Helen, Oukrif, Dahmane, Akarca, Ayse U., Hartley, John A., Lowe, Helen L., Lock, Sara, Iles, Natasha, Bell, Harriet, Ngai, Yenting, Elgar, Greg, Szallasi, Zoltan, Schwarz, Roland F., Herrero, Javier, Stewart, Aengus, Quezada, Sergio A., Peggs, Karl S., Van Loo, Peter, Dive, Caroline, Lin, C. Jimmy, Rabinowitz, Matthew, Aerts, Hugo J. W. L., Hackshaw, Allan, Shaw, Jacqui A., Zimmermann, Bernhard G., Swanton, Charles, Bosshard-Carter, Leticia, Goh, Gerald, Gorman, Pat, Murugaesu, Nirupa, Hynds, Robert E., Horswell, Stuart, Bakir, Maise Al, Mitter, Richard, Escudero, Mickael, Xu, Hang, Goldman, Jacki, Stone, Richard Kevin, Denner, Tamara, Biggs, Jennifer, Costa, Marta, Begum, Sharmin, Phillimore, Ben, Nye, Emma, Graca, Sofia, Joshi, Kroopa, Furness, Andrew, Ben Aissa, Assma, Wong, Yien Ning Sophia, Georgiou, Andy, Simeon, Celia, Hector, Gemma, Smith, Amy, Aranda, Marie, Novelli, Marco, Papadatos-Pastos, Dionysis, Carnell, Dawn, Mendes, Ruheena, George, Jeremy, Navani, Neal, Taylor, Magali, Choudhary, Junaid, Califano, Raffaele, Taylor, Paul, Krysiak, Piotr, Rammohan, Kendadai, Fontaine, Eustace, Booton, Richard, Evison, Matthew, Moss, Stuart, Idries, Faiza, Bishop, Paul, Chaturvedi, Anshuman, Quinn, Anne Marie, Doran, Helen, Leek, Angela, Harrison, Phil, Moore, Katrina, Waddington, Rachael, Novasio, Juliette, Rogan, Jane, Smith, Elaine, Tugwood, Jonathan, Brady, Ged, Rothwell, Dominic G., Chemi, Francesca, Pierce, Jackie, Gulati, Sakshi, Bellamy, Mary, Bancroft, Hollie, Kerr, Amy, Kadiri, Salma, Webb, Joanne, Djearaman, Madava, Quesne, John Le, Thomas, Anne, Walter, Harriet, Monteiro, William, Marshall, Hilary, Nelson, Louise, Bennett, Jonathan, Primrose, Lindsay, Amadi, Anita, Palmer, Shirley, Miller, Joy, Buchan, Keith, Edwards, Alison, Morgan, Fiona, Verjee, Azmina, MacKenzie, Mairead, Wilcox, Maggie, Smith, Sean, Gower, Nicole, Ottensmeier, Christian, Chee, Serena, Johnson, Benjamin, Alzetani, Aiman, Shaw, Emily, Lim, Eric, De Sousa, Paulo, Barbosa, Monica Tavares, Bowman, Alex, Jordan, Simon, Rice, Alexandra, Raubenheimer, Hilgardt, Proli, Chiara, Cufari, Maria Elena, Ronquillo, John Carlo, Kwayie, Angela, Bhayani, Harshil, Hamilton, Morag, Bakar, Yusura, Mensah, Natalie, Ambrose, Lyn, Devaraj, Anand, Buderi, Silviu, Finch, Jonathan, Azcarate, Leire, Chavan, Hema, Green, Sophie, Mashinga, Hillaria, Nicholson, Andrew G., Lau, Kelvin, Sheaff, Michael, Schmid, Peter, Conibear, John, Light, Teresa, Horey, Tracey, Danson, Sarah, Bury, Jonathan, Edwards, John, Hill, Jennifer, Matthews, Sue, Kitsanta, Yota, Suvarna, Kim, Fisher, Patricia, Keerio, Allah Dino, Shackcloth, Michael, Gosney, John, Postmus, Pieter, Feeney, Sarah, Asante-Siaw, Julius, Dentro, Stefan, and Dessimoz, Christophe

Subjects
Lung cancer -- Genetic aspects -- Development and progression, DNA sequencing -- Methods, Phylogeny -- Observations, Cancer metastasis -- Genetic aspects, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

The early detection of relapse following primary surgery for non-small-cell lung cancer and the characterization of emerging subclones, which seed metastatic sites, might offer new therapeutic approaches for limiting tumour recurrence. The ability to track the evolutionary dynamics of early-stage lung cancer non-invasively in circulating tumour DNA (ctDNA) has not yet been demonstrated. Here we use a tumour-specific phylogenetic approach to profile the ctDNA of the first 100 TRACERx (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy (Rx)) study participants, including one patient who was also recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and analyse the tumour-volume detection limit. Through blinded profiling of postoperative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients who are very likely to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastasis, providing a new approach for ctDNA-driven therapeutic studies., Author(s): Christopher Abbosh [1]; Nicolai J. Birkbak [1, 2]; Gareth A. Wilson [1, 2]; Mariam Jamal-Hanjani [1]; Tudor Constantin [3]; Raheleh Salari [3]; John Le Quesne [4]; David A. Moore [...]

Published
2017
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5. Blood-based mutation testing: concordance with tissue-based testing and mutational changes on progression.

Author

Germetaki, Theodora, Nicholls, Camille, Adams, Richard A, Braun, Michael, Rogan, Jane, Moghadam, Sharzad, Lenfert, Eva, Lukas, Antje, Edelstein, Daniel L, Jones, Frederick S, and Saunders, Mark P

Abstract

Aim: To determine the concordance between plasma and tissue RAS mutation status in metastatic colorectal cancer patients to gauge whether blood-based testing is a viable alternative. We also evaluated the change in mutation status on progression. Materials/methods:RAS testing was performed on plasma from patients commencing first-line therapy (OncoBEAM™ RAS CEIVD kit). Results were then compared with formalin-fixed paraffin embedded tumor samples. Results: The overall percentage agreement (concordance) was 86.0% (86/100), which demonstrates that blood-based testing is an alternative to tissue-based testing. Reproducibility was 100% between three laboratories and 20% showed changes in their RAS mutational status on progression. Conclusion: These results show good concordance between tissue and plasma samples and suggest the need for longitudinal plasma testing during treatment to guide management decisions. [ABSTRACT FROM AUTHOR]

Published
2020
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6. The HER3 pathway as a potential target for inhibition in patients with biliary tract cancers.

Author

Lamarca, Angela, Galdy, Salvatore, Barriuso, Jorge, Moghadam, Sharzad, Beckett, Elizabeth, Rogan, Jane, Backen, Alison, Billington, Catherine, McNamara, Mairéad G., Hubner, Richard A., Cramer, Angela, and Valle, Juan W.

Subjects
BILIARY tract cancer, CANCER patients, EPIDERMAL growth factor receptors, GENE expression, FLUORESCENCE in situ hybridization
Abstract

Introduction: Expression of human epidermal growth factor receptor (HER)2 and HER3 have been investigated in small BTC studies using variable scoring systems. Methods: HER2 and HER3 overexpression/amplification were explored following internationally agreed guidelines using immunohistochemistry (IHC) and fluorescent in-situ hybridisation (FISH), respectively. Logistic regression and survival analysis (Kaplan Meier, Log rank test and Cox Regression) were used for statistical analysis. Results: Sixty-seven eligible patients with Stage I/II (31.3%) or III/IV (68.7%) disease at diagnosis were included. Membrane HER2 overexpression/amplification was identified in 1 patient (1%). HER3 overexpression was predominantly cytoplasmic; the rate of overexpression/amplification of HER3 in membrane and cytoplasm was 16% [ampullary cancer (AMP) (1/13; 8%), gallbladder cancer (GBC) (1/10; 10%), intra-hepatic cholangiocarcinoma (ICC) (6/26; 23%), extra-hepatic cholangiocarcinoma (ECC) (3/18; 17%)] and 24% [AMP (1/13; 8%), GBC (1/10; 10%), ICC (10/26; 38%), ECC (4/18; 22%)], respectively. Conclusions: A significant subset of patients with BTC expressed HER3. Inhibition of HER3 warrants further investigation. A better understanding of the downstream effects of HER3 in BTC requires further mechanistic investigations to identify new biomarkers and improve patient selection for future clinical trials. [ABSTRACT FROM AUTHOR]

Published
2018
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7. Optimizing sharing of hospital biobank samples.

Author

Riegman, Peter H. J., de Jong, Bas, Daidone, Maria Grazia, Söderström, Tommy, Thompson, James, Hall, Jacqueline A., Mendy, Maimuna, ten Hoeve, Jelle, Broeks, Annegien, Reed, Wenche, Morente, Manuel M., Antonio López-Guerrero, José, Collins, V. Peter, Rogan, Jane, and Ringborg, Ulrik

Subjects
BIOBANKS, BIOLOGICAL specimens, CANCER research, BIOINFORMATICS, ACQUISITION of data
Abstract

The article explores the technical guidelines, standards, and ways for sharing hospital biobank samples. Topics discussed include efforts of the European Platform for Translational Cancer Research for creating a European infrastructure for translational cancer research; use of bioinformatics for data collection from the samples; and importance of managing high-quality samples.

Published
2015
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10. Increased peri-ductal collagen micro-organization may contribute to raised mammographic density.

Author

McConnell, James C., O'Connell, Oliver V., Brennan, Keith, Weiping, Lisa, Howe, Miles, Joseph, Leena, Knight, David, O'Cualain, Ronan, Lim, Yit, Leek, Angela, Waddington, Rachael, Rogan, Jane, Astley, Susan M., Gandhi, Ashu, Kirwan, Cliona C., Sherratt, Michael J., and Streuli, Charles H.

Subjects
COLLAGEN, EXTRACELLULAR matrix proteins, CONNECTIVE tissues, TISSUES, BIOMATERIALS, PROTEIN metabolism, BREAST abnormalities, ANIMAL experimentation, BREAST, MAMMOGRAMS, BREAST tumors, CELL adhesion molecules, MICROSCOPY, PROTEINS, RATS, RESEARCH funding, PROTEOMICS, METABOLISM
Abstract

Background: High mammographic density is a therapeutically modifiable risk factor for breast cancer. Although mammographic density is correlated with the relative abundance of collagen-rich fibroglandular tissue, the causative mechanisms, associated structural remodelling and mechanical consequences remain poorly defined. In this study we have developed a new collaborative bedside-to-bench workflow to determine the relationship between mammographic density, collagen abundance and alignment, tissue stiffness and the expression of extracellular matrix organising proteins.Methods: Mammographic density was assessed in 22 post-menopausal women (aged 54-66 y). A radiologist and a pathologist identified and excised regions of elevated non-cancerous X-ray density prior to laboratory characterization. Collagen abundance was determined by both Masson's trichrome and Picrosirius red staining (which enhances collagen birefringence when viewed under polarised light). The structural specificity of these collagen visualisation methods was determined by comparing the relative birefringence and ultrastructure (visualised by atomic force microscopy) of unaligned collagen I fibrils in reconstituted gels with the highly aligned collagen fibrils in rat tail tendon. Localised collagen fibril organisation and stiffness was also evaluated in tissue sections by atomic force microscopy/spectroscopy and the abundance of key extracellular proteins was assessed using mass spectrometry.Results: Mammographic density was positively correlated with the abundance of aligned periductal fibrils rather than with the abundance of amorphous collagen. Compared with matched tissue resected from the breasts of low mammographic density patients, the highly birefringent tissue in mammographically dense breasts was both significantly stiffer and characterised by large (>80 μm long) fibrillar collagen bundles. Subsequent proteomic analyses not only confirmed the absence of collagen fibrosis in high mammographic density tissue, but additionally identified the up-regulation of periostin and collagen XVI (regulators of collagen fibril structure and architecture) as potential mediators of localised mechanical stiffness.Conclusions: These preliminary data suggest that remodelling, and hence stiffening, of the existing stromal collagen microarchitecture promotes high mammographic density within the breast. In turn, this aberrant mechanical environment may trigger neoplasia-associated mechanotransduction pathways within the epithelial cell population. [ABSTRACT FROM AUTHOR]

Published
2016
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11. Reinventing YIG Technology for Microwave Filter Applications.

Author

Linstrom, Bill, Barnard, Jackson, and Rogan, Jane

Subjects
*COGNITIVE radio, *MICROWAVE filters, *BANDPASS filters, *CAVITY resonator filters, *TRAVELING-wave tubes
Abstract

The article focuses on Reinventing YIG Technology for Microwave Filter Applications.

Published
2022

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