학술논문
Representative Sequencing: Unbiased Sampling of Solid Tumor Tissue
Document Type
Article
Author
Litchfield, Kevin; Stanislaw, Stacey; Spain, Lavinia; Gallegos, Lisa L.; Rowan, Andrew; Schnidrig, Desiree; Rosenbaum, Heidi; Harle, Alexandre; Au, Lewis; Hill, Samantha M.; Tippu, Zayd; Thomas, Jennifer; Thompson, Lisa; Xu, Hang; Horswell, Stuart; Barhoumi, Aoune; Jones, Carol; Leith, Katherine F.; Burgess, Daniel L.; Watkins, Thomas B.K.; Lim, Emilia; Birkbak, Nicolai J.; Lamy, Philippe; Nordentoft, Iver; Dyrskjøt, Lars; Pickering, Lisa; Hazell, Stephen; Jamal-Hanjani, Mariam; Abbosh, Chris; Shiu, Kai-Keen; Bridgewater, John; Hochhauser, Daniel; Forster, Martin; Lee, Siow-Ming; Ahmad, Tanya; Papadatos-Pastos, Dionysis; Janes, Sam; Van Loo, Peter; Enfield, Katey; McGranahan, Nicholas; Huebner, Ariana; Quezada, Sergio; Beck, Stephan; Parker, Peter; Walczak, Henning; Enver, Tariq; Hynds, Rob; Falzon, Mary; Proctor, Ian; Sinclair, Ron; Lok, Chi-wah; Rhodes, Zoe; Moore, David; Marafioti, Teresa; Borg, Elaine; Mitchison, Miriam; Khiroya, Reena; Trevisan, Giorgia; Ellery, Peter; Linch, Mark; Brandner, Sebastian; Hiley, Crispin; Veeriah, Selvaraju; Razaq, Maryam; Shaw, Heather; Attard, Gert; Akther, Mita Afroza; Naceur-Lombardelli, Cristina; Manzano, Lizi; Al-Bakir, Maise; Summan, Simranpreet; Kanu, Nnenna; Ward, Sophie; Asghar, Uzma; Lim, Emilia; Gishen, Faye; Tookman, Adrian; Stone, Paddy; Stirling, Caroline; Furness, Andrew; Edmonds, Kim; Hunter, Nikki; Sarker, Sarah; Vaughan, Sarah; Mangwende, Mary; Pearce, Karla; Spain, Lavinia; Shepherd, Scott; Yan, Haixi; Shum, Ben; Carlyle, Eleanor; Hazell, Steve; Fendler, Annika; Byrne, Fiona; Yousaf, Nadia; Popat, Sanjay; Curtis, Olivia; Stamp, Gordon; Toncheva, Antonia; Nye, Emma; Murra, Aida; Korteweg, Justine; Sheikh, Nahid; Josephs, Debra; Chandra, Ashish; Spicer, James; Mahadeva, Ula; Green, Anna; Stewart, Ruby; Iredale, Lara-Rose; Mackay, Tina; Deakin, Ben; Enting, Debra; Rudman, Sarah; Ghosh, Sharmistha; Karapagniotou, Lena; Pintus, Elias; Tutt, Andrew; Howlett, Sarah; Michalarea, Vasiliki; Brenton, James; Caldas, Carlos; Fitzgerald, Rebecca; Jimenez-Linan, Merche; Provenzano, Elena; Cluroe, Alison; Stewart, Grant; Watts, Colin; Gilbertson, Richard; McDermott, Ultan; Tavare, Simon; Beddowes, Emma; Roxburgh, Patricia; Biankin, Andrew; Chalmers, Anthony; Fraser, Sioban; Oien, Karin; Kidd, Andrew; Blyth, Kevin; Krebs, Matt; Blackhall, Fiona; Summers, Yvonne; Dive, Caroline; Marais, Richard; Gomes, Fabio; Carter, Mat; Dransfield, Jo; Le Quesne, John; Fennell, Dean; Shaw, Jacqui; Naidu, Babu; Baijal, Shobhit; Tanchel, Bruce; Langman, Gerald; Robinson, Andrew; Collard, Martin; Cockcroft, Peter; Ferris, Charlotte; Bancroft, Hollie; Kerr, Amy; Middleton, Gary; Webb, Joanne; Kadiri, Salma; Colloby, Peter; Olisemeke, Bernard; Wilson, Rodelaine; Tomlinson, Ian; Jogai, Sanjay; Ottensmeier, Christian; Harrison, David; Loda, Massimo; Flanagan, Adrienne; McKenzie, Mairead; Hackshaw, Allan; Ledermann, Jonathan; Sharp, Abby; Farrelly, Laura; Bridger, Hayley; Larkin, James; Swanton, Charles; Alexander, Nelson R.; Turajlic, Samra
Source
Cell Reports; May 2020, Vol. 31 Issue: 5
Subject
Language
ISSN
22111247
Abstract
Although thousands of solid tumors have been sequenced to date, a fundamental under-sampling bias is inherent in current methodologies. This is caused by a tissue sample input of fixed dimensions (e.g., 6 mm biopsy), which becomes grossly under-powered as tumor volume scales. Here, we demonstrate representative sequencing (Rep-Seq) as a new method to achieve unbiased tumor tissue sampling. Rep-Seq uses fixed residual tumor material, which is homogenized and subjected to next-generation sequencing. Analysis of intratumor tumor mutation burden (TMB) variability shows a high level of misclassification using current single-biopsy methods, with 20% of lung and 52% of bladder tumors having at least one biopsy with high TMB but low clonal TMB overall. Misclassification rates by contrast are reduced to 2% (lung) and 4% (bladder) when a more representative sampling methodology is used. Rep-Seq offers an improved sampling protocol for tumor profiling, with significant potential for improved clinical utility and more accurate deconvolution of clonal structure.