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214 results on '"Roufosse, Candice"'

1. URCDM: Ultra-Resolution Image Synthesis in Histopathology

Author

Cechnicka, Sarah, Ball, James, Baugh, Matthew, Reynaud, Hadrien, Simmonds, Naomi, Smith, Andrew P. T., Horsfield, Catherine, Roufosse, Candice, and Kainz, Bernhard

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Diagnosing medical conditions from histopathology data requires a thorough analysis across the various resolutions of Whole Slide Images (WSI). However, existing generative methods fail to consistently represent the hierarchical structure of WSIs due to a focus on high-fidelity patches. To tackle this, we propose Ultra-Resolution Cascaded Diffusion Models (URCDMs) which are capable of synthesising entire histopathology images at high resolutions whilst authentically capturing the details of both the underlying anatomy and pathology at all magnification levels. We evaluate our method on three separate datasets, consisting of brain, breast and kidney tissue, and surpass existing state-of-the-art multi-resolution models. Furthermore, an expert evaluation study was conducted, demonstrating that URCDMs consistently generate outputs across various resolutions that trained evaluators cannot distinguish from real images. All code and additional examples can be found on GitHub., Comment: arXiv admin note: text overlap with arXiv:2312.01152

Published
2024

2. Ultra-Resolution Cascaded Diffusion Model for Gigapixel Image Synthesis in Histopathology

Author

Cechnicka, Sarah, Reynaud, Hadrien, Ball, James, Simmonds, Naomi, Horsfield, Catherine, Smith, Andrew, Roufosse, Candice, and Kainz, Bernhard

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Diagnoses from histopathology images rely on information from both high and low resolutions of Whole Slide Images. Ultra-Resolution Cascaded Diffusion Models (URCDMs) allow for the synthesis of high-resolution images that are realistic at all magnification levels, focusing not only on fidelity but also on long-distance spatial coherency. Our model beats existing methods, improving the pFID-50k [2] score by 110.63 to 39.52 pFID-50k. Additionally, a human expert evaluation study was performed, reaching a weighted Mean Absolute Error (MAE) of 0.11 for the Lower Resolution Diffusion Models and a weighted MAE of 0.22 for the URCDM., Comment: MedNeurIPS 2023 poster

Published
2023

3. Cosmic kidney disease: an integrated pan-omic, physiological and morphological study into spaceflight-induced renal dysfunction

Author

Siew, Keith, Nestler, Kevin A., Nelson, Charlotte, D’Ambrosio, Viola, Zhong, Chutong, Li, Zhongwang, Grillo, Alessandra, Wan, Elizabeth R., Patel, Vaksha, Overbey, Eliah, Kim, JangKeun, Yun, Sanghee, Vaughan, Michael B., Cheshire, Chris, Cubitt, Laura, Broni-Tabi, Jessica, Al-Jaber, Maneera Yousef, Boyko, Valery, Meydan, Cem, Barker, Peter, Arif, Shehbeel, Afsari, Fatemeh, Allen, Noah, Al-Maadheed, Mohammed, Altinok, Selin, Bah, Nourdine, Border, Samuel, Brown, Amanda L., Burling, Keith, Cheng-Campbell, Margareth, Colón, Lorianna M., Degoricija, Lovorka, Figg, Nichola, Finch, Rebecca, Foox, Jonathan, Faridi, Pouya, French, Alison, Gebre, Samrawit, Gordon, Peter, Houerbi, Nadia, Valipour Kahrood, Hossein, Kiffer, Frederico C., Klosinska, Aleksandra S., Kubik, Angela, Lee, Han-Chung, Li, Yinghui, Lucarelli, Nicholas, Marullo, Anthony L., Matei, Irina, McCann, Colleen M., Mimar, Sayat, Naglah, Ahmed, Nicod, Jérôme, O’Shaughnessy, Kevin M., Oliveira, Lorraine Christine De, Oswalt, Leah, Patras, Laura Ioana, Lai Polo, San-huei, Rodríguez-Lopez, María, Roufosse, Candice, Sadeghi-Alavijeh, Omid, Sanchez-Hodge, Rebekah, Paul, Anindya S., Schittenhelm, Ralf Bernd, Schweickart, Annalise, Scott, Ryan T., Choy Lim Kam Sian, Terry Chin, da Silveira, Willian A., Slawinski, Hubert, Snell, Daniel, Sosa, Julio, Saravia-Butler, Amanda M., Tabetah, Marshall, Tanuwidjaya, Erwin, Walker-Samuel, Simon, Yang, Xiaoping, Yasmin, Zhang, Haijian, Godovac-Zimmermann, Jasminka, Sarder, Pinaki, Sanders, Lauren M., Costes, Sylvain V., Campbell, Robert A. A., Karouia, Fathi, Mohamed-Alis, Vidya, Rodriques, Samuel, Lynham, Steven, Steele, Joel Ricky, Baranzini, Sergio, Fazelinia, Hossein, Dai, Zhongquan, Uruno, Akira, Shiba, Dai, Yamamoto, Masayuki, A.C.Almeida, Eduardo, Blaber, Elizabeth, Schisler, Jonathan C., Eisch, Amelia J., Muratani, Masafumi, Zwart, Sara R., Smith, Scott M., Galazka, Jonathan M., Mason, Christopher E., Beheshti, Afshin, and Walsh, Stephen B.

Published
2024
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4. Realistic Data Enrichment for Robust Image Segmentation in Histopathology

Author

Cechnicka, Sarah, Ball, James, Reynaud, Hadrien, Arthurs, Callum, Roufosse, Candice, and Kainz, Bernhard

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Poor performance of quantitative analysis in histopathological Whole Slide Images (WSI) has been a significant obstacle in clinical practice. Annotating large-scale WSIs manually is a demanding and time-consuming task, unlikely to yield the expected results when used for fully supervised learning systems. Rarely observed disease patterns and large differences in object scales are difficult to model through conventional patient intake. Prior methods either fall back to direct disease classification, which only requires learning a few factors per image, or report on average image segmentation performance, which is highly biased towards majority observations. Geometric image augmentation is commonly used to improve robustness for average case predictions and to enrich limited datasets. So far no method provided sampling of a realistic posterior distribution to improve stability, e.g. for the segmentation of imbalanced objects within images. Therefore, we propose a new approach, based on diffusion models, which can enrich an imbalanced dataset with plausible examples from underrepresented groups by conditioning on segmentation maps. Our method can simply expand limited clinical datasets making them suitable to train machine learning pipelines, and provides an interpretable and human-controllable way of generating histopathology images that are indistinguishable from real ones to human experts. We validate our findings on two datasets, one from the public domain and one from a Kidney Transplant study., Comment: 11 pages, 2 figures, 1 table

Published
2023

5. Description and Cross-Sectional Analyses of 25,880 Adults and Children in the UK National Registry of Rare Kidney Diseases Cohort

Author

Abat, Sharirose, Adalat, Shazia, Agbonmwandolor, Joy, Ahmad, Zubaidah, Alejmi, Abdulfattah, Almasarwah, Rashid, Annear, Nicholas, Asgari, Ellie, Ayers, Amanda, Baharani, Jyoti, Balasubramaniam, Gowrie, Kpodo, Felix Jo-Bamba, Bansal, Tarun, Barratt, Alison, Barratt, Jonathan, Bates, Megan, Bayne, Natalie, Bendle, Janet, Benyon, Sarah, Bergmann, Carsten, Bhandari, Sunil, Bingham, Coralie, Boddana, Preetham, Bond, Sally, Braddon, Fiona, Bramham, Kate, Branson, Angela, Brearey, Stephen, Brocklebank, Vicky, Budwal, Sharanjit, Byrne, Conor, Cairns, Hugh, Camilleri, Brian, Campbell, Gary, Capell, Alys, Carmody, Margaret, Carson, Marion, Cathcart, Tracy, Catley, Christine, Cesar, Karine, Chan, Melanie, Chea, Houda, Chess, James, Cheung, Chee Kay, Chick, Katy-Jane, Chitalia, Nihil, Christian, Martin, Chrysochou, Tina, Clark, Katherine, Clayton, Christopher, Clissold, Rhian, Cockerill, Helen, Coelho, Joshua, Colby, Elizabeth, Colclough, Viv, Conway, Eileen, Cook, H. Terence, Cook, Wendy, Cooper, Theresa, Coward, Richard J., Crosbie, Sarah, Cserep, Gabor, Date, Anjali, Davidson, Katherine, Davies, Amanda, Dhaun, Neeraj, Dhaygude, Ajay, Diskin, Lynn, Dixit, Abhijit, Doctolero, Eunice Ann, Dorey, Suzannah, Downard, Lewis, Drayson, Mark, Dreyer, Gavin, Dutt, Tina, Etuk, Kufreabasi, Evans, Dawn, Finch, Jenny, Flinter, Frances, Fotheringham, James, Francis, Lucy, Gale, Daniel P., Gallagher, Hugh, Game, David, Garcia, Eva Lozano, Gavrila, Madita, Gear, Susie, Geddes, Colin, Gilchrist, Mark, Gittus, Matt, Goggolidou, Paraskevi, Goldsmith, Christopher, Gooden, Patricia, Goodlife, Andrea, Goodwin, Priyanka, Grammatikopoulos, Tassos, Gray, Barry, Griffith, Megan, Gumus, Steph, Gupta, Sanjana, Hamilton, Patrick, Harper, Lorraine, Harris, Tess, Haskell, Louise, Hayward, Samantha, Hegde, Shivaram, Hendry, Bruce, Hewins, Sue, Hewitson, Nicola, Hillman, Kate, Hiremath, Mrityunjay, Howson, Alexandra, Htet, Zay, Huish, Sharon, Hull, Richard, Humphries, Alister, Hunt, David P.J., Hunter, Karl, Hunter, Samantha, Ijeomah-Orji, Marilyn, Inston, Nick, Jayne, David, Jenfa, Gbemisola, Jenkins, Alison, Johnson, Sally, Jones, Caroline A., Jones, Colin, Jones, Amanda, Jones, Rachel, Kamesh, Lavanya, Kanigicherla, Durga, Frankl, Fiona Karet, Karim, Mahzuz, Kaur, Amrit, Kavanagh, David, Kearley, Kelly, Kerecuk, Larissa, Khwaja, Arif, King, Garry, King, Grant, Kislowska, Ewa, Klata, Edyta, Kokocinska, Maria, Lambie, Mark, Lawless, Laura, Ledson, Thomas, Lennon, Rachel, Levine, Adam P., Maggie Lai, Ling Wai, Lipkin, Graham, Lovitt, Graham, Lyons, Paul, Mabillard, Holly, Mackintosh, Katherine, Mahdi, Khalid, Maher, Eamonn, Marchbank, Kevin J., Mark, Patrick B., Masoud, Sherry, Masunda, Bridgett, Mavani, Zainab, Mayfair, Jake, McAdoo, Stephen, Mckinnell, Joanna, Melhem, Nabil, Meyrick, Simon, Moochhala, Shabbir, Morgan, Putnam, Morgan, Ann, Muhammad, Fawad, Murray, Shona, Novobritskaya, Kristina, Ong, Albert CM., Oni, Louise, Osmaston, Kate, Padmanabhan, Neal, Parkes, Sharon, Patrick, Jean, Pattison, James, Paul, Riny, Percival, Rachel, Perkins, Stephen J., Persu, Alexandre, Petchey, William G., Pickering, Matthew C., Pinney, Jennifer, Pitcher, David, Plumb, Lucy, Plummer, Zoe, Popoola, Joyce, Post, Frank, Power, Albert, Pratt, Guy, Pusey, Charles, Rabara, Ria, Rabuya, May, Raju, Tina, Javier, Chadd, Roberts, Ian SD., Roufosse, Candice, Rumjon, Adam, Salama, Alan, Saleem, Moin, Sandford, R.N., Sandu, Kanwaljit S., Sarween, Nadia, Sayer, John A., Sebire, Neil, Selvaskandan, Haresh, Shah, Sapna, Sharma, Asheesh, Sharples, Edward J., Sheerin, Neil, Shetty, Harish, Shroff, Rukshana, Simms, Roslyn, Sinha, Manish, Sinha, Smeeta, Smith, Kerry, Smith, Lara, Srivastava, Shalabh, Steenkamp, Retha, Stott, Ian, Stroud, Katerina, Swift, Pauline, Szklarzewicz, Justyna, Tam, Fred, Tan, Kay, Taylor, Robert, Tischkowitz, Marc, Thomas, Kay, Tse, Yincent, Turnbull, Alison, Turner, A. Neil, Tyerman, Kay, Usher, Miranda, Venkat-Raman, Gopalakrishnan, Walker, Alycon, Walsh, Stephen B., Waters, Aoife, Watt, Angela, Webster, Phil, Wechalekar, Ashutosh, Welsh, Gavin Iain, West, Nicol, Wheeler, David, Wiles, Kate, Willcocks, Lisa, Williams, Angharad, Williams, Emma, Williams, Karen, Wilson, Deborah H., Wilson, Patricia D., Winyard, Paul, Wong, Edwin, Wong, Katie, Wood, Grahame, Woodward, Emma, Woodward, Len, Woolf, Adrian, Wright, David, Downward, Lewis, Griffin, Sian, Hall, Matt, Karet Frankl, Fiona, Maher, Eamonn R., Pinney, Jenny, Tam, Frederick W.K., Wilson, Patricia, Sy, Karla Therese L., Huang, Kui, Ye, Jamie, Nitsch, Dorothea, and Bockenhauer, Detlef

Published
2024
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7. Randomized Trial on the Effect of an Oral Spleen Tyrosine Kinase Inhibitor in the Treatment of IgA Nephropathy

Author

Tam, Frederick W.K., Tumlin, James, Barratt, Jonathan, Rovin, Brad H., Roberts, Ian S.D., Roufosse, Candice, Cook, H. Terence, Bhangal, Gurjeet, Brown, Alison L., Busch, Martin, Dudhiya, Fayaz, Duliege, Anne-Marie, Fraser, Donald J., Gale, Daniel P., Huang, Chiu-Ching, Lai, Ping-Chin, Lee, Meng, Masuda, Esteban S., McAdoo, Stephen P., Rosenkranz, Alexander R., Sommerer, Claudia, Sunder-Plassmann, Gere, Szeto, Cheuk-Chun, Tang, Sydney C.W., Williamson, Don E., Willcocks, Lisa, Vielhauer, Volker, Kim, Min Jeong, Todd, Leslie, Zayed, Hany, Tong-Starksen, Sandra, and Lafayette, Richard

Published
2023
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11. Angiotensin II Type-1 Receptor Antibody in Solid Organ Transplantation – Is It Time to Test?

Author

Martin, Paul James Patrick, Willicombe, Michelle, and Roufosse, Candice

Subjects
HISTOCOMPATIBILITY testing, ANGIOTENSIN II, RECEPTOR antibodies, TRANSPLANTATION of organs, tissues, etc., RECOMMENDER systems
Abstract

Angiotensin II type-1 receptor antibody (AT1R-Ab) has been mooted as a potential effector of both acute and chronic antibody mediated rejection (AMR). A growing body of literature on the topic is now coming under scrutiny in the context of the evolving Banff AMR diagnostic classification system and refinement of recommendations for histocompatibility testing by the Sensitization in Transplantation Assessment of Risk (STAR) workgroup. This mini-review discusses the latest understanding of pathophysiological mechanisms, clinical evidence for the pathogenicity of AT1R-Ab, and methods of laboratory testing. [ABSTRACT FROM AUTHOR]

Published
2024
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13. Description and cross-sectional analyses of 25,880 adults and children in the UK National Registry of Rare Kidney Diseases cohort

Author

Wong, Katie, primary, Pitcher, David, additional, Braddon, Fiona, additional, Downward, Lewis, additional, Steenkamp, Retha, additional, Masoud, Sherry, additional, Annear, Nicholas, additional, Barratt, Jonathan, additional, Bingham, Coralie, additional, Coward, Richard J., additional, Chrysochou, Tina, additional, Game, David, additional, Griffin, Sian, additional, Hall, Matt, additional, Johnson, Sally, additional, Kanigicherla, Durga, additional, Karet Frankl, Fiona, additional, Kavanagh, David, additional, Kerecuk, Larissa, additional, Maher, Eamonn R., additional, Moochhala, Shabbir, additional, Pinney, Jenny, additional, Sayer, John A., additional, Simms, Roslyn, additional, Sinha, Smeeta, additional, Srivastava, Shalabh, additional, Tam, Frederick W.K., additional, Thomas, Kay, additional, Turner, A. Neil, additional, Walsh, Stephen B., additional, Waters, Aoife, additional, Wilson, Patricia, additional, Wong, Edwin, additional, Abat, Sharirose, additional, Adalat, Shazia, additional, Agbonmwandolor, Joy, additional, Ahmad, Zubaidah, additional, Alejmi, Abdulfattah, additional, Almasarwah, Rashid, additional, Asgari, Ellie, additional, Ayers, Amanda, additional, Baharani, Jyoti, additional, Balasubramaniam, Gowrie, additional, Jo-Bamba Kpodo, Felix, additional, Bansal, Tarun, additional, Barratt, Alison, additional, Bates, Megan, additional, Bayne, Natalie, additional, Bendle, Janet, additional, Benyon, Sarah, additional, Bergmann, Carsten, additional, Bhandari, Sunil, additional, Boddana, Preetham, additional, Bond, Sally, additional, Bramham, Kate, additional, Branson, Angela, additional, Brearey, Stephen, additional, Brocklebank, Vicky, additional, Budwal, Sharanjit, additional, Byrne, Conor, additional, Cairns, Hugh, additional, Camilleri, Brian, additional, Campbell, Gary, additional, Capell, Alys, additional, Carmody, Margaret, additional, Carson, Marion, additional, Cathcart, Tracy, additional, Catley, Christine, additional, Cesar, Karine, additional, Chan, Melanie, additional, Chea, Houda, additional, Chess, James, additional, Cheung, Chee Kay, additional, Chick, Katy-Jane, additional, Chitalia, Nihil, additional, Christian, Martin, additional, Clark, Katherine, additional, Clayton, Christopher, additional, Clissold, Rhian, additional, Cockerill, Helen, additional, Coelho, Joshua, additional, Colby, Elizabeth, additional, Colclough, Viv, additional, Conway, Eileen, additional, Cook, H. Terence, additional, Cook, Wendy, additional, Cooper, Theresa, additional, Crosbie, Sarah, additional, Cserep, Gabor, additional, Date, Anjali, additional, Davidson, Katherine, additional, Davies, Amanda, additional, Dhaun, Neeraj, additional, Dhaygude, Ajay, additional, Diskin, Lynn, additional, Dixit, Abhijit, additional, Doctolero, Eunice Ann, additional, Dorey, Suzannah, additional, Downard, Lewis, additional, Drayson, Mark, additional, Dreyer, Gavin, additional, Dutt, Tina, additional, Etuk, Kufreabasi, additional, Evans, Dawn, additional, Finch, Jenny, additional, Flinter, Frances, additional, Fotheringham, James, additional, Francis, Lucy, additional, Gale, Daniel P., additional, Gallagher, Hugh, additional, Garcia, Eva Lozano, additional, Gavrila, Madita, additional, Gear, Susie, additional, Geddes, Colin, additional, Gilchrist, Mark, additional, Gittus, Matt, additional, Goggolidou, Paraskevi, additional, Goldsmith, Christopher, additional, Gooden, Patricia, additional, Goodlife, Andrea, additional, Goodwin, Priyanka, additional, Grammatikopoulos, Tassos, additional, Gray, Barry, additional, Griffith, Megan, additional, Gumus, Steph, additional, Gupta, Sanjana, additional, Hamilton, Patrick, additional, Harper, Lorraine, additional, Harris, Tess, additional, Haskell, Louise, additional, Hayward, Samantha, additional, Hegde, Shivaram, additional, Hendry, Bruce, additional, Hewins, Sue, additional, Hewitson, Nicola, additional, Hillman, Kate, additional, Hiremath, Mrityunjay, additional, Howson, Alexandra, additional, Htet, Zay, additional, Huish, Sharon, additional, Hull, Richard, additional, Humphries, Alister, additional, Hunt, David P.J., additional, Hunter, Karl, additional, Hunter, Samantha, additional, Ijeomah-Orji, Marilyn, additional, Inston, Nick, additional, Jayne, David, additional, Jenfa, Gbemisola, additional, Jenkins, Alison, additional, Jones, Caroline A., additional, Jones, Colin, additional, Jones, Amanda, additional, Jones, Rachel, additional, Kamesh, Lavanya, additional, Frankl, Fiona Karet, additional, Karim, Mahzuz, additional, Kaur, Amrit, additional, Kearley, Kelly, additional, Khwaja, Arif, additional, King, Garry, additional, King, Grant, additional, Kislowska, Ewa, additional, Klata, Edyta, additional, Kokocinska, Maria, additional, Lambie, Mark, additional, Lawless, Laura, additional, Ledson, Thomas, additional, Lennon, Rachel, additional, Levine, Adam P., additional, Maggie Lai, Ling Wai, additional, Lipkin, Graham, additional, Lovitt, Graham, additional, Lyons, Paul, additional, Mabillard, Holly, additional, Mackintosh, Katherine, additional, Mahdi, Khalid, additional, Maher, Eamonn, additional, Marchbank, Kevin J., additional, Mark, Patrick B., additional, Masunda, Bridgett, additional, Mavani, Zainab, additional, Mayfair, Jake, additional, McAdoo, Stephen, additional, Mckinnell, Joanna, additional, Melhem, Nabil, additional, Meyrick, Simon, additional, Morgan, Putnam, additional, Morgan, Ann, additional, Muhammad, Fawad, additional, Murray, Shona, additional, Novobritskaya, Kristina, additional, Ong, Albert CM., additional, Oni, Louise, additional, Osmaston, Kate, additional, Padmanabhan, Neal, additional, Parkes, Sharon, additional, Patrick, Jean, additional, Pattison, James, additional, Paul, Riny, additional, Percival, Rachel, additional, Perkins, Stephen J., additional, Persu, Alexandre, additional, Petchey, William G., additional, Pickering, Matthew C., additional, Pinney, Jennifer, additional, Plumb, Lucy, additional, Plummer, Zoe, additional, Popoola, Joyce, additional, Post, Frank, additional, Power, Albert, additional, Pratt, Guy, additional, Pusey, Charles, additional, Rabara, Ria, additional, Rabuya, May, additional, Raju, Tina, additional, Javier, Chadd, additional, Roberts, Ian SD., additional, Roufosse, Candice, additional, Rumjon, Adam, additional, Salama, Alan, additional, Saleem, Moin, additional, Sandford, R.N., additional, Sandu, Kanwaljit S., additional, Sarween, Nadia, additional, Sebire, Neil, additional, Selvaskandan, Haresh, additional, Shah, Sapna, additional, Sharma, Asheesh, additional, Sharples, Edward J., additional, Sheerin, Neil, additional, Shetty, Harish, additional, Shroff, Rukshana, additional, Sinha, Manish, additional, Smith, Kerry, additional, Smith, Lara, additional, Stott, Ian, additional, Stroud, Katerina, additional, Swift, Pauline, additional, Szklarzewicz, Justyna, additional, Tam, Fred, additional, Tan, Kay, additional, Taylor, Robert, additional, Tischkowitz, Marc, additional, Tse, Yincent, additional, Turnbull, Alison, additional, Turner, A Neil, additional, Tyerman, Kay, additional, Usher, Miranda, additional, Venkat-Raman, Gopalakrishnan, additional, Walker, Alycon, additional, Watt, Angela, additional, Webster, Phil, additional, Wechalekar, Ashutosh, additional, Welsh, Gavin Iain, additional, West, Nicol, additional, Wheeler, David, additional, Wiles, Kate, additional, Willcocks, Lisa, additional, Williams, Angharad, additional, Williams, Emma, additional, Williams, Karen, additional, Wilson, Deborah H., additional, Wilson, Patricia D., additional, Winyard, Paul, additional, Wong, Katie, additional, Wood, Grahame, additional, Woodward, Emma, additional, Woodward, Len, additional, Woolf, Adrian, additional, Wright, David, additional, Sy, Karla Therese L., additional, Huang, Kui, additional, Ye, Jamie, additional, Nitsch, Dorothea, additional, and Bockenhauer, Detlef, additional

Published
2024
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14. The Banff 2022 Kidney Meeting Work Plan:Data-driven refinement of the Banff Classification for renal allografts

Author

Roufosse, Candice, Naesens, Maarten, Haas, Mark, Lefaucheur, Carmen, Mannon, Roslyn B., Afrouzian, Marjan, Alachkar, Nada, Aubert, Olivier, Bagnasco, Serena M., Batal, Ibrahim, Bellamy, Chris O.C., Broecker, Verena, Budde, Klemens, Clahsen-Van Groningen, Marian, Coley, Shana M., Cornell, Lynn D., Dadhania, Darshana, Demetris, Anthony J., Einecke, Gunilla, Farris, Alton B., Fogo, Agnes B., Friedewald, John, Gibson, Ian W., Horsfield, Catherine, Huang, Edmund, Husain, Syed A., Jackson, Annette M., Kers, Jesper, Kikić, Željko, Klein, Amanda, Kozakowski, Nicolas, Liapis, Helen, Mangiola, Massima, Montgomery, Robert A., Nankinvell, Brian, Neil, Desley A.H., Nickerson, Peter, Rabant, Marion, Randhawa, Parmjeet, Riella, Leonardo V., Rosales, Ivy, Royal, Virginie, Sapir-Pichhadze, Ruth, Sarder, Pinaki, Sarwal, Minnie, Schinstock, Carrie, Stegall, Mark, Solez, Kim, van der Laak, Jeroen, Wiebe, Chris, Colvin, Robert B., Loupy, Alexandre, Mengel, Michael, Roufosse, Candice, Naesens, Maarten, Haas, Mark, Lefaucheur, Carmen, Mannon, Roslyn B., Afrouzian, Marjan, Alachkar, Nada, Aubert, Olivier, Bagnasco, Serena M., Batal, Ibrahim, Bellamy, Chris O.C., Broecker, Verena, Budde, Klemens, Clahsen-Van Groningen, Marian, Coley, Shana M., Cornell, Lynn D., Dadhania, Darshana, Demetris, Anthony J., Einecke, Gunilla, Farris, Alton B., Fogo, Agnes B., Friedewald, John, Gibson, Ian W., Horsfield, Catherine, Huang, Edmund, Husain, Syed A., Jackson, Annette M., Kers, Jesper, Kikić, Željko, Klein, Amanda, Kozakowski, Nicolas, Liapis, Helen, Mangiola, Massima, Montgomery, Robert A., Nankinvell, Brian, Neil, Desley A.H., Nickerson, Peter, Rabant, Marion, Randhawa, Parmjeet, Riella, Leonardo V., Rosales, Ivy, Royal, Virginie, Sapir-Pichhadze, Ruth, Sarder, Pinaki, Sarwal, Minnie, Schinstock, Carrie, Stegall, Mark, Solez, Kim, van der Laak, Jeroen, Wiebe, Chris, Colvin, Robert B., Loupy, Alexandre, and Mengel, Michael

Abstract

The XVIth Banff Meeting for Allograft Pathology was held in Banff, Alberta, Canada, from September 19 to 23, 2022, as a joint meeting with the Canadian Society of Transplantation. In addition to a key focus on the impact of microvascular inflammation and biopsy-based transcript analysis on the Banff Classification, further sessions were devoted to other aspects of kidney transplant pathology, in particular T cell–mediated rejection, activity and chronicity indices, digital pathology, xenotransplantation, clinical trials, and surrogate endpoints. Although the output of these sessions has not led to any changes in the classification, the key role of Banff Working Groups in phrasing unanswered questions, and coordinating and disseminating results of investigations addressing these unanswered questions was emphasized. This paper summarizes the key Banff Meeting 2022 sessions not covered in the Banff Kidney Meeting 2022 Report paper and also provides an update on other Banff Working Group activities relevant to kidney allografts.

Published
2024

19. The Banff 2022 Kidney Meeting Work Plan: Data-driven refinement of the Banff Classification for renal allografts

Author

Roufosse, Candice, primary, Naesens, Maarten, additional, Haas, Mark, additional, Lefaucheur, Carmen, additional, Mannon, Roslyn B., additional, Afrouzian, Marjan, additional, Alachkar, Nada, additional, Aubert, Olivier, additional, Bagnasco, Serena M., additional, Batal, Ibrahim, additional, Bellamy, Chris O.C., additional, Broecker, Verena, additional, Budde, Klemens, additional, Clahsen-Van Groningen, Marian, additional, Coley, Shana M., additional, Cornell, Lynn D., additional, Dadhania, Darshana, additional, Demetris, Anthony J., additional, Einecke, Gunilla, additional, Farris, Alton B., additional, Fogo, Agnes B., additional, Friedewald, John, additional, Gibson, Ian W., additional, Horsfield, Catherine, additional, Huang, Edmund, additional, Husain, Syed A., additional, Jackson, Annette M., additional, Kers, Jesper, additional, Kikić, Željko, additional, Klein, Amanda, additional, Kozakowski, Nicolas, additional, Liapis, Helen, additional, Mangiola, Massima, additional, Montgomery, Robert A., additional, Nankinvell, Brian, additional, Neil, Desley A.H., additional, Nickerson, Peter, additional, Rabant, Marion, additional, Randhawa, Parmjeet, additional, Riella, Leonardo V., additional, Rosales, Ivy, additional, Royal, Virginie, additional, Sapir-Pichhadze, Ruth, additional, Sarder, Pinaki, additional, Sarwal, Minnie, additional, Schinstock, Carrie, additional, Stegall, Mark, additional, Solez, Kim, additional, van der Laak, Jeroen, additional, Wiebe, Chris, additional, Colvin, Robert B., additional, Loupy, Alexandre, additional, and Mengel, Michael, additional

Published
2023
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20. The Banff 2022 Kidney Meeting Report: Re-Appraisal of Microvascular Inflammation and the Role of Biopsy-Based Transcript Diagnostics

Author

Naesens, Maarten, primary, Roufosse, Candice, additional, Haas, Mark, additional, Lefaucheur, Carmen, additional, Mannon, Roslyn B., additional, Adam, Benjamin A., additional, Aubert, Olivier, additional, Böhmig, Georg A., additional, Callemeyn, Jasper, additional, Groningen, Marian Clahsen-van, additional, Cornell, Lynn D., additional, Demetris, Anthony J., additional, Drachenberg, Cinthia B., additional, Einecke, Gunilla, additional, Fogo, Agnes B., additional, Gibson, Ian W., additional, Halloran, Philip, additional, Hidalgo, Luis G., additional, Horsfield, Catherine, additional, Huang, Edmund, additional, Kikić, Željko, additional, Kozakowski, Nicolas, additional, Nankivell, Brian, additional, Rabant, Marion, additional, Randhawa, Parmjeet, additional, Riella, Leonardo V., additional, Sapir-Pichhadze, Ruth, additional, Schinstock, Carrie, additional, Solez, Kim, additional, Tambur, Anat R., additional, Thaunat, Olivier, additional, Wiebe, Chris, additional, Zielinski, Dina, additional, Colvin, Robert, additional, Loupy, Alexandre, additional, and Mengel, Michael, additional

Published
2023
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22. An acidic microenvironment in Tuberculosis increases extracellular matrix degradation by regulating macrophage inflammatory responses

Author

Whittington, Ashley M., primary, Turner, Frances S., additional, Baark, Friedrich, additional, Templeman, Sam, additional, Kirwan, Daniela E., additional, Roufosse, Candice, additional, Krishnan, Nitya, additional, Robertson, Brian D., additional, Chong, Deborah L. W., additional, Porter, Joanna C., additional, Gilman, Robert H., additional, and Friedland, Jon S., additional

Published
2023
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29. Syk Activation in Circulating and Tissue Innate Immune Cells in Antineutrophil Cytoplasmic Antibody–Associated Vasculitis

Author

Prendecki, Maria, primary, Gulati, Kavita, additional, Pisacano, Noelle, additional, Pinheiro, Damilola, additional, Bhatt, Tejal, additional, Mawhin, Marie‐Anne, additional, Toulza, Frederic, additional, Masuda, Esteban S., additional, Cowburn, Andrew, additional, Lodge, Katharine M., additional, Tam, Frederick W. K., additional, Roufosse, Candice, additional, Pusey, Charles D., additional, and McAdoo, Stephen P., additional

Published
2022
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30. Steroid Sparing Maintenance Immunosuppression in Highly Sensitised Patients Receiving Alemtuzumab Induction.

Author

Santos, Eva, Spensley, Katrina, Gunby, Nicola, Clarke, Candice, Anand, Arthi, Roufosse, Candice, and Willicombe, Michelle

Subjects
ALEMTUZUMAB, STEROIDS, IMMUNOSUPPRESSION, GRAFT survival, MYCOPHENOLIC acid
Abstract

This analysis reports on the outcomes of two different steroid sparing immunosuppression protocols used in the management of 120 highly sensitised patients (HSPs) with cRF>85% receiving Alemtuzumab induction, 53 maintained on tacrolimus (FK) monotherapy and 67 tacrolimus plus mycophenolate mofetil (FK + MMF). There was no difference in the median cRF or mode of sensitisation between the two groups, although the FK + MMF cohort received more poorly matched grafts. There was no difference in one-year patient or allograft survival, however rejection free survival was inferior with FK monotherapy compared with FK + MMF at 65.4% and 91.4% respectively, p < 0.01. DSA-free survival was comparable. Whilst there was no difference in rates of BK between the cohorts, CMVfree survival was inferior in the FK + MMF group at 86.0% compared with 98.1% in the FK group, p = 0.026. One-year post-transplant diabetes free survival was 89.6% and 100.0% in the FK and FK + MMF group respectively, p = 0.027, the difference attributed to the use of prednisolone to treat rejection in the FK cohort, p = 0.006. We report good outcomes in HSPs utilising a steroid sparing protocol with Alemtuzumab induction and FK + MMF maintenance and provide granular data on immunological and infectious complications to inform steroid avoidance in these patient groups. [ABSTRACT FROM AUTHOR]

Published
2023
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31. Incidence, Risk Factors, and Effect on Allograft Survival of Glomerulonephritis Post-transplantation in a United Kingdom Population: Cohort Study

Author

Aguiar, Rute, primary, Bourmpaki, Elli, additional, Bunce, Catey, additional, Coker, Bola, additional, Delaney, Florence, additional, de Jongh, Leonardo, additional, Oliveira, Giovani, additional, Weir, Alistair, additional, Higgins, Finola, additional, Spiridou, Anastasia, additional, Hasan, Syed, additional, Smith, Jonathan, additional, Mulla, Abdulrahim, additional, Glampson, Ben, additional, Mercuri, Luca, additional, Montero, Rosa, additional, Hernandez-Fuentes, Maria, additional, Roufosse, Candice A., additional, Simmonds, Naomi, additional, Clatworthy, Menna, additional, McLean, Adam, additional, Ploeg, Rutger, additional, Davies, Jim, additional, Várnai, Kinga Anna, additional, Woods, Kerrie, additional, Lord, Graham, additional, Pruthi, Rishi, additional, Breen, Cormac, additional, and Chowdhury, Paramit, additional

Published
2022
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32. Proposed Definitions of T Cell-Mediated Rejection and Tubulointerstitial Inflammation as Clinical Trial Endpoints in Kidney Transplantation

Author

Seron, Daniel, Rabant, Marion, Becker, Jan Ulrich, Roufosse, Candice, Bellini, Maria Irene, Boehmig, Georg A., Budde, Klemens, Diekmann, Fritz, Glotz, Denis, Hilbrands, Luuk, Loupy, Alexandre, Oberbauer, Rainer, Pengel, Liset, Schneeberger, Stefan, Naesens, Maarten, Seron, Daniel, Rabant, Marion, Becker, Jan Ulrich, Roufosse, Candice, Bellini, Maria Irene, Boehmig, Georg A., Budde, Klemens, Diekmann, Fritz, Glotz, Denis, Hilbrands, Luuk, Loupy, Alexandre, Oberbauer, Rainer, Pengel, Liset, Schneeberger, Stefan, and Naesens, Maarten

Abstract

The diagnosis of acute T cell-mediated rejection (aTCMR) after kidney transplantation has considerable relevance for research purposes. Its definition is primarily based on tubulointerstitial inflammation and has changed little over time; aTCMR is therefore a suitable parameter for longitudinal data comparisons. In addition, because aTCMR is managed with antirejection therapies that carry additional risks, anxieties, and costs, it is a clinically meaningful endpoint for studies. This paper reviews the history and classifications of TCMR and characterizes its potential role in clinical trials: a role that largely depends on the nature of the biopsy taken (indication vs protocol), the level of inflammation observed (e.g., borderline changes vs full TCMR), concomitant chronic lesions (chronic active TCMR), and the therapeutic intervention planned. There is ongoing variability-and ambiguity-in clinical monitoring and management of TCMR. More research, to investigate the clinical relevance of borderline changes (especially in protocol biopsies) and effective therapeutic strategies that improve graft survival rates with minimal patient morbidity, is urgently required. The present paper was developed from documentation produced by the European Society for Organ Transplantation (ESOT) as part of a Broad Scientific Advice request that ESOT submitted to the European Medicines Agency for discussion in 2020. This paper proposes to move toward refined definitions of aTCMR and borderline changes to be included as primary endpoints in clinical trials of kidney transplantation.

Published
2022

33. Proposed Definitions of Antibody-Mediated Rejection for Use as a Clinical Trial Endpoint in Kidney Transplantation

Author

Roufosse, Candice, Becker, Jan Ulrich, Rabant, Marion, Seron, Daniel, Bellini, Maria Irene, Boehmig, Georg A., Budde, Klemens, Diekmann, Fritz, Glotz, Denis, Hilbrands, Luuk, Loupy, Alexandre, Oberbauer, Rainer, Pengel, Liset, Schneeberger, Stefan, Naesens, Maarten, Roufosse, Candice, Becker, Jan Ulrich, Rabant, Marion, Seron, Daniel, Bellini, Maria Irene, Boehmig, Georg A., Budde, Klemens, Diekmann, Fritz, Glotz, Denis, Hilbrands, Luuk, Loupy, Alexandre, Oberbauer, Rainer, Pengel, Liset, Schneeberger, Stefan, and Naesens, Maarten

Abstract

Antibody-mediated rejection (AMR) is caused by antibodies that recognize donor human leukocyte antigen (HLA) or other targets. As knowledge of AMR pathophysiology has increased, a combination of factors is necessary to confirm the diagnosis and phenotype. However, frequent modifications to the AMR definition have made it difficult to compare data and evaluate associations between AMR and graft outcome. The present paper was developed following a Broad Scientific Advice request from the European Society for Organ Transplantation (ESOT) to the European Medicines Agency (EMA), which explored whether updating guidelines on clinical trial endpoints would encourage innovations in kidney transplantation research. ESOT considers that an AMR diagnosis must be based on a combination of histopathological factors and presence of donor-specific HLA antibodies in the recipient. Evidence for associations between individual features of AMR and impaired graft outcome is noted for microvascular inflammation scores >= 2 and glomerular basement membrane splitting of > 10% of the entire tuft in the most severely affected glomerulus. Together, these should form the basis for AMR-related endpoints in clinical trials of kidney transplantation, although modifications and restrictions to the Banff diagnostic definition of AMR are proposed for this purpose. The EMA provided recommendations based on this Broad Scientific Advice request in December 2020; further discussion, and consensus on the restricted definition of the AMR endpoint, is required.

Published
2022

34. Evolution of the Definition of Rejection in Kidney Transplantation and Its Use as an Endpoint in Clinical Trials

Author

Becker, Jan Ulrich, Seron, Daniel, Rabant, Marion, Roufosse, Candice, Naesens, Maarten, Becker, Jan Ulrich, Seron, Daniel, Rabant, Marion, Roufosse, Candice, and Naesens, Maarten

Abstract

This article outlines the evolving definition of rejection following kidney transplantation. The viewpoints and evidence presented were included in documentation prepared for a Broad Scientific Advice request to the European Medicines Agency (EMA), relating to clinical trial endpoints in kidney transplantation. This request was initiated by the European Society for Organ Transplantation (ESOT) in 2016 and finalized following discussions between the EMA and ESOT in 2020. In ESOT's opinion, the use of biopsy-proven acute rejection as an endpoint for clinical trials in kidney transplantation is no longer accurate, although it is still the approved histopathological endpoint. The spectrum of rejection is now divided into the phenotypes of borderline changes, T cell-mediated rejection, and antibody-mediated rejection, with the latter two phenotypes having further subclassifications. Rejection is also described in relation to graft (dys)function, diagnosed because of protocol (surveillance) or indication (for-cause) biopsies. The ongoing use of outdated terminology has become a potential barrier to clinical research in kidney transplantation. This article presents these perspectives and issues, and provides a foundation on which subsequent articles within this Special Issue of Transplant International build.

Published
2022

35. Proposed Definitions of Antibody-Mediated Rejection for Use as a Clinical Trial Endpoint in Kidney Transplantation

Author

Roufosse, Candice, primary, Becker, Jan Ulrich, additional, Rabant, Marion, additional, Seron, Daniel, additional, Bellini, Maria Irene, additional, Böhmig, Georg A., additional, Budde, Klemens, additional, Diekmann, Fritz, additional, Glotz, Denis, additional, Hilbrands, Luuk, additional, Loupy, Alexandre, additional, Oberbauer, Rainer, additional, Pengel, Liset, additional, Schneeberger, Stefan, additional, and Naesens, Maarten, additional

Published
2022
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37. Proposed Definitions of T Cell-Mediated Rejection and Tubulointerstitial Inflammation as Clinical Trial Endpoints in Kidney Transplantation

Author

Seron, Daniel, primary, Rabant, Marion, additional, Becker, Jan Ulrich, additional, Roufosse, Candice, additional, Bellini, Maria Irene, additional, Böhmig, Georg A., additional, Budde, Klemens, additional, Diekmann, Fritz, additional, Glotz, Denis, additional, Hilbrands, Luuk, additional, Loupy, Alexandre, additional, Oberbauer, Rainer, additional, Pengel, Liset, additional, Schneeberger, Stefan, additional, and Naesens, Maarten, additional

Published
2022
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38. The Banff 2019 Kidney Meeting Report (I): Updates on and clarification of criteria for T cell– and antibody-mediated rejection

Author

Loupy, Alexandre, Haas, Mark, Roufosse, Candice, Naesens, Maarten, Adam, Benjamin, Afrouzian, Marjan, Akalin, Enver, Alachkar, Nada, Bagnasco, Serena, Becker, Jan U., Cornell, Lynn, Clahsen-van Groningen, Marian C., Demetris, Anthony J., Dragun, Duska, Duong van Huyen, Jean-Paul, Farris, Alton B., Fogo, Agnes B., Gibson, Ian W., Glotz, Denis, Gueguen, Juliette, Kikic, Zeljko, Kozakowski, Nicolas, Kraus, Edward, Lefaucheur, Carmen, Liapis, Helen, Mannon, Roslyn B., Montgomery, Robert A., Nankivell, Brian J., Nickeleit, Volker, Nickerson, Peter, Rabant, Marion, Racusen, Lorraine, Randhawa, Parmjeet, Robin, Blaise, Rosales, Ivy A., Sapir-Pichhadze, Ruth, Schinstock, Carrie A., Seron, Daniel, Singh, Harsharan K., Smith, Rex N., Stegall, Mark D., Zeevi, Adriana, Solez, Kim, Colvin, Robert, Mengel, Michael, Universitat Autònoma de Barcelona, Imperial College Healthcare NHS Trust- BRC Funding, and Pathology

Subjects
Graft Rejection, Oncology, medicine.medical_specialty, classification systems: Banff classification, translational research/science, T-Lymphocytes, T cell, Kidney (allograft) function/dysfunction, kidney transplantation/nephrology, kidney (allograft) function/dysfunction, 030230 surgery, Meeting Report, Kidney, clinical research/practice, Kidney transplant, Rejection, Interstitial inflammation, Meeting Reports, 03 medical and health sciences, 0302 clinical medicine, Artificial Intelligence, Internal medicine, mRNA/mRNA expression [Molecular biology], medicine, Immunology and Allergy, molecular biology: mRNA/mRNA expression, Pharmacology (medical), Microvascular inflammation, 11 Medical and Health Sciences, Banff classification [Classification systems], clinical decision-making, Transplantation, Kidney transplantation/nephrology, business.industry, Pathology/histopathology, Kidney Transplantation, Histocompatibility, clinical decision‐making, medicine.anatomical_structure, Antibody mediated rejection, Clinical research/practice, Surgery, Translational research/science, rejection, Solid organ transplantation, business, pathology/histopathology, Clinical decision-making
Abstract

The XV. Banff conference for allograft pathology was held in conjunction with the annual meeting of the American Society for Histocompatibility and Immunogenetics in Pittsburgh, PA (USA) and focused on refining recent updates to the classification, advances from the Banff working groups, and standardization of molecular diagnostics. This report on kidney transplant pathology details clarifications and refinements to the criteria for chronic active (CA) T cell–mediated rejection (TCMR), borderline, and antibody‐mediated rejection (ABMR). The main focus of kidney sessions was on how to address biopsies meeting criteria for CA TCMR plus borderline or acute TCMR. Recent studies on the clinical impact of borderline infiltrates were also presented to clarify whether the threshold for interstitial inflammation in diagnosis of borderline should be i0 or i1. Sessions on ABMR focused on biopsies showing microvascular inflammation in the absence of C4d staining or detectable donor‐specific antibodies; the potential value of molecular diagnostics in such cases and recommendations for use of the latter in the setting of solid organ transplantation are presented in the accompanying meeting report. Finally, several speakers discussed the capabilities of artificial intelligence and the potential for use of machine learning algorithms in diagnosis and personalized therapeutics in solid organ transplantation., This report focuses on the clarification of the criteria for chronic active T cell–mediated rejection and antibody‐mediated rejection and the optimization of the inflammation threshold for the diagnosis of borderline for acute T cell–mediated rejection, and discusses the potential to use machine learning in diagnostics and personalized therapeutics in solid organ transplantation.

Published
2020

39. Automating kidney transplant rejection diagnosis: a simple solution for a complex problem?

Author

Loon, Elisabet Van, Callemeyn, Jasper, and Roufosse, Candice

Subjects
GRAFT rejection, KIDNEY transplantation, ARTIFICIAL intelligence, DECISION trees, PROGNOSTIC tests
Abstract

Yoo and colleagues have developed an automated system called the "Banff automation system" that applies the Banff Classification rules for Kidney Allograft Pathology. The system uses logical operations to reach diagnoses based on histological information, serology, and molecular data. The tool aims to avoid misclassifications and provides a visualized decision tree to illustrate the steps of the Banff rules used. The study highlights potential problems with the Banff Classification and suggests the need for improvements, such as artificial intelligence and consensus on molecular data. The authors caution against using the Banff Classification as a prognostic tool and suggest further evaluation of simplified rules and AI-supported diagnosis. [Extracted from the article]

Published
2023
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40. Syk Activation in Circulating and Tissue Innate Immune Cells in Antineutrophil Cytoplasmic Antibody–Associated Vasculitis.

Author

Prendecki, Maria, Gulati, Kavita, Pisacano, Noelle, Pinheiro, Damilola, Bhatt, Tejal, Mawhin, Marie‐Anne, Toulza, Frederic, Masuda, Esteban S., Cowburn, Andrew, Lodge, Katharine M., Tam, Frederick W. K., Roufosse, Candice, Pusey, Charles D., and McAdoo, Stephen P.

Subjects
FLOW cytometry, INTERLEUKINS, IMMUNOHISTOCHEMISTRY, ANTINEUTROPHIL cytoplasmic antibodies, PROTEIN-tyrosine kinases, MYELOID cells, VASCULITIS, PHOSPHORYLATION
Abstract

Objective: Syk is a cytoplasmic protein tyrosine kinase that plays a role in signaling via B cell and Fc receptors (FcR). FcR engagement and signaling via Syk is thought to be important in antineutrophil cytoplasm antibody (ANCA) IgG–mediated neutrophil activation. This study was undertaken to investigate the role of Syk in ANCA‐induced myeloid cell activation and vasculitis pathogenesis. Methods: Phosphorylation of Syk in myeloid cells from healthy controls and ANCA‐associated vasculitis (AAV) patients was analyzed using flow cytometry. The effect of Syk inhibition on myeloperoxidase (MPO)–ANCA IgG activation of cells was investigated using functional assays (interleukin‐8 and reactive oxygen species production) and targeted gene analysis with NanoString. Total and phosphorylated Syk at sites of tissue inflammation in patients with AAV was assessed using immunohistochemistry and RNAscope in situ hybridization. Results: We identified increased phosphorylated Syk at critical activatory tyrosine residues in blood neutrophils and monocytes from patients with active AAV compared to patients with disease in remission or healthy controls. Syk was phosphorylated in vitro following MPO‐ANCA IgG stimulation, and Syk inhibition was able to prevent ANCA‐mediated cellular responses. Using targeted gene expression analysis, we identified up‐regulation of FcR‐ and Syk‐dependent signaling pathways following MPO‐ANCA IgG stimulation. Finally, we showed that Syk is expressed and phosphorylated in tissue leukocytes at sites of organ inflammation in AAV. Conclusion: These findings indicate that Syk plays a critical role in MPO‐ANCA IgG–induced myeloid cell responses and that Syk is activated in circulating immune cells and tissue immune cells in AAV; therefore, Syk inhibition may be a potential therapeutic option. [ABSTRACT FROM AUTHOR]

Published
2023
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41. Gene Expression Profiling in Kidney Transplants with Immune Checkpoint Inhibitor–Associated Adverse Events

Author

Adam, Benjamin A., primary, Murakami, Naoka, additional, Reid, Graeme, additional, Du, Katie, additional, Jasim, Ruqaya, additional, Boils, Christie L., additional, Bu, Lihong, additional, Hill, Peter D., additional, Murray, Allan G., additional, Renaudin, Karine, additional, Roufosse, Candice, additional, Weins, Astrid, additional, Wen, Kevin, additional, Riella, Leonardo V., additional, and Mengel, Michael, additional

Published
2021
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44. Application of direct stochastic optical reconstruction microscopy ( dSTORM ) to the histological analysis of human glomerular disease

Author

Garcia, Edwin, primary, Lightley, Jonathan, additional, Kumar, Sunil, additional, Kalita, Ranjan, additional, Gőrlitz, Frederik, additional, Alexandrov, Yuriy, additional, Cook, Terry, additional, Dunsby, Christopher, additional, Neil, Mark AA, additional, Roufosse, Candice A, additional, and French, Paul MW, additional

Published
2021
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45. MO078DEEP LEARNING DIAGNOSIS OF ANTIBODY-MEDIATED REJECTION (AMR) ON GLOMERULAR TRANSECTIONS

Author

Cicalese, Pietro A, primary, Rizvi, Syed A, additional, Roufosse, Candice, additional, Batal, Ibrahim, additional, Hellmich, Martin, additional, Ernst, Angela, additional, Moos, Katharina, additional, Clahsen-van Groningen, Marian, additional, Weidemann, Alexander, additional, Mohan, Chandra, additional, Nguyen, Hien V, additional, and Becker, Jan Ulrich, additional

Published
2021
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46. Diagnostic application of transcripts associated with antibody-mediated rejection in kidney transplant biopsies.

Author

Toulza, Frederic, Dominy, Kathy, Willicombe, Michelle, Beadle, Jack, Santos, Eva, Cook, H Terence, Szydlo, Richard M, McLean, Adam, and Roufosse, Candice

Subjects
RENAL biopsy, GRAFT rejection, KIDNEY transplantation, POLYMERASE chain reaction, GENE expression
Abstract

Background The diagnosis of antibody-mediated rejection (AMR) is reached using the Banff Classification for Allograft Pathology, which now includes gene expression analysis. In this study, we investigate the application of 'increased expression of thoroughly validated gene transcripts/classifiers strongly associated with AMR' as diagnostic criteria. Method We used quantitative real-time polymerase chain reaction for 10 genes associated with AMR in a retrospective cohort of 297 transplant biopsies, including biopsies that met the full diagnostic criteria for AMR, even without molecular data (AMR, n = 27), biopsies that showed features of AMR, but that would only meet criteria for AMR with increased transcripts [suspicious for AMR (AMRsusp), n = 49] and biopsies that would never meet criteria for AMR (No-AMR, n = 221). Results A 10-gene AMR score trained by a receiver-operating characteristic to identify AMR found 16 cases with a high score among the AMRsusp cases (AMRsusp-high) that had significantly worse graft survival than those with a low score (AMRsusp-low; n = 33). In both univariate and multivariate Cox regression analysis, the AMR 10-gene score was significantly associated with an increased hazard ratio (HR) for graft loss (GL) in the AMRsusp group (HR = 1.109, P = 0.004 and HR = 1.138, P = 0.012, respectively), but not in the whole cohort. Net reclassification index and integrated discrimination improvement analyses demonstrated improved risk classification and superior discrimination, respectively, for GL when considering the gene score in addition to histological and serological data, but only in the AMRsusp group, not the whole cohort. Conclusions This study provides evidence that a gene score strongly associated with AMR helps identify cases at higher risk of GL in biopsies that are suspicious for AMR but do not meet full criteria. [ABSTRACT FROM AUTHOR]

Published
2022
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49. Banff 2019 Meeting Report: Molecular diagnostics in solid organ transplantation–Consensus for the Banff Human Organ Transplant (B-HOT) gene panel and open source multicenter validation

Author

Mengel, Michael, primary, Loupy, Alexandre, additional, Haas, Mark, additional, Roufosse, Candice, additional, Naesens, Maarten, additional, Akalin, Enver, additional, Clahsen-van Groningen, Marian C., additional, Dagobert, Jessy, additional, Demetris, Anthony J., additional, Duong van Huyen, Jean-Paul, additional, Gueguen, Juliette, additional, Issa, Fadi, additional, Robin, Blaise, additional, Rosales, Ivy, additional, Von der Thüsen, Jan H., additional, Sanchez-Fueyo, Alberto, additional, Smith, Rex N., additional, Wood, Kathryn, additional, Adam, Benjamin, additional, and Colvin, Robert B., additional

Published
2020
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