Search

Your search keyword '"Rahman, Arman"' showing total 158 results
Start Over Author "Rahman, Arman"
158 results on '"Rahman, Arman"'

2. Feature Fusion of Raman Chemical Imaging and Digital Histopathology using Machine Learning for Prostate Cancer Detection

Author

Doherty, Trevor, McKeever, Susan, Al-Attar, Nebras, Murphy, Tiarnan, Aura, Claudia, Rahman, Arman, O'Neill, Amanda, Finn, Stephen P, Kay, Elaine, Gallagher, William M., Watson, R. William G., Gowen, Aoife, and Jackman, Patrick

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Machine Learning, Quantitative Biology - Quantitative Methods
Abstract

The diagnosis of prostate cancer is challenging due to the heterogeneity of its presentations, leading to the over diagnosis and treatment of non-clinically important disease. Accurate diagnosis can directly benefit a patient's quality of life and prognosis. Towards addressing this issue, we present a learning model for the automatic identification of prostate cancer. While many prostate cancer studies have adopted Raman spectroscopy approaches, none have utilised the combination of Raman Chemical Imaging (RCI) and other imaging modalities. This study uses multimodal images formed from stained Digital Histopathology (DP) and unstained RCI. The approach was developed and tested on a set of 178 clinical samples from 32 patients, containing a range of non-cancerous, Gleason grade 3 (G3) and grade 4 (G4) tissue microarray samples. For each histological sample, there is a pathologist labelled DP - RCI image pair. The hypothesis tested was whether multimodal image models can outperform single modality baseline models in terms of diagnostic accuracy. Binary non-cancer/cancer models and the more challenging G3/G4 differentiation were investigated. Regarding G3/G4 classification, the multimodal approach achieved a sensitivity of 73.8% and specificity of 88.1% while the baseline DP model showed a sensitivity and specificity of 54.1% and 84.7% respectively. The multimodal approach demonstrated a statistically significant 12.7% AUC advantage over the baseline with a value of 85.8% compared to 73.1%, also outperforming models based solely on RCI and median Raman spectra. Feature fusion of DP and RCI does not improve the more trivial task of tumour identification but does deliver an observed advantage in G3/G4 discrimination. Building on these promising findings, future work could include the acquisition of larger datasets for enhanced model generalization., Comment: 19 pages, 8 tables, 18 figures

Published
2021
Full Text
View/download PDF

3. Precision Oncology, Artificial Intelligence, and Novel Therapeutic Advancements in the Diagnosis, Prevention, and Treatment of Cancer: Highlights from the 59th Irish Association for Cancer Research (IACR) Annual Conference

Author

Lynch, Seodhna M., primary, Heeran, Aisling B., additional, Burke, Caoimbhe, additional, Lynam-Lennon, Niamh, additional, Eustace, Alex J., additional, Dean, Kellie, additional, Robson, Tracy, additional, Rahman, Arman, additional, and Marcone, Simone, additional

Published
2024
Full Text
View/download PDF

5. Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Author

Pathologie, Cancer, Jahangir, Chowdhury Arif, Page, David B., Broeckx, Glenn, Gonzalez, Claudia A., Burke, Caoimbhe, Murphy, Clodagh, Reis-Filho, Jorge S., Ly, Amy, Harms, Paul W., Gupta, Rajarsi R., Vieth, Michael, Hida, Akira I., Kahila, Mohamed, Kos, Zuzana, van Diest, Paul J., Verbandt, Sara, Thagaard, Jeppe, Khiroya, Reena, Abduljabbar, Khalid, Acosta Haab, Gabriela, Acs, Balazs, Adams, Sylvia, Almeida, Jonas S., Alvarado-Cabrero, Isabel, Azmoudeh-Ardalan, Farid, Badve, Sunil, Baharun, Nurkhairul Bariyah, Bellolio, Enrique R., Bheemaraju, Vydehi, Blenman, Kim R.M., Botinelly Mendonça Fujimoto, Luciana, Burgues, Octavio, Chardas, Alexandros, Cheang, Maggie Chon U., Ciompi, Francesco, Cooper, Lee A.D., Coosemans, An, Corredor, Germán, Dantas Portela, Flavio Luis, Deman, Frederik, Demaria, Sandra, Dudgeon, Sarah N., Elghazawy, Mahmoud, Fernandez-Martín, Claudio, Fineberg, Susan, Fox, Stephen B., Giltnane, Jennifer M., Gnjatic, Sacha, Gonzalez-Ericsson, Paula I., Grigoriadis, Anita, Halama, Niels, Hanna, Matthew G., Harbhajanka, Aparna, Hart, Steven N., Hartman, Johan, Hewitt, Stephen, Horlings, Hugo M., Husain, Zaheed, Irshad, Sheeba, Janssen, Emiel A.M., Kataoka, Tatsuki R., Kawaguchi, Kosuke, Khramtsov, Andrey I., Kiraz, Umay, Kirtani, Pawan, Kodach, Liudmila L., Korski, Konstanty, Akturk, Guray, Scott, Ely, Kovács, Anikó, Lænkholm, Anne Vibeke, Lang-Schwarz, Corinna, Larsimont, Denis, Lennerz, Jochen K., Lerousseau, Marvin, Li, Xiaoxian, Madabhushi, Anant, Maley, Sai K., Manur Narasimhamurthy, Vidya, Marks, Douglas K., McDonald, Elizabeth S., Mehrotra, Ravi, Michiels, Stefan, Kharidehal, Durga, Minhas, Fayyaz ul Amir Afsar, Mittal, Shachi, Moore, David A., Mushtaq, Shamim, Nighat, Hussain, Papathomas, Thomas, Penault-Llorca, Frederique, Perera, Rashindrie D., Pinard, Christopher J., Pinto-Cardenas, Juan Carlos, Pruneri, Giancarlo, Pusztai, Lajos, Rajpoot, Nasir Mahmood, Rapoport, Bernardo Leon, Rau, Tilman T., Ribeiro, Joana M., Rimm, David, Vincent-Salomon, Anne, Saltz, Joel, Sayed, Shahin, Hytopoulos, Evangelos, Mahon, Sarah, Siziopikou, Kalliopi P., Sotiriou, Christos, Stenzinger, Albrecht, Sughayer, Maher A., Sur, Daniel, Symmans, Fraser, Tanaka, Sunao, Taxter, Timothy, Tejpar, Sabine, Teuwen, Jonas, Thompson, E. Aubrey, Tramm, Trine, Tran, William T., van der Laak, Jeroen, Verghese, Gregory E., Viale, Giuseppe, Wahab, Noorul, Walter, Thomas, Waumans, Yannick, Wen, Hannah Y., Yang, Wentao, Yuan, Yinyin, Bartlett, John, Loibl, Sibylle, Denkert, Carsten, Savas, Peter, Loi, Sherene, Specht Stovgaard, Elisabeth, Salgado, Roberto, Gallagher, William M., Rahman, Arman, Pathologie, Cancer, Jahangir, Chowdhury Arif, Page, David B., Broeckx, Glenn, Gonzalez, Claudia A., Burke, Caoimbhe, Murphy, Clodagh, Reis-Filho, Jorge S., Ly, Amy, Harms, Paul W., Gupta, Rajarsi R., Vieth, Michael, Hida, Akira I., Kahila, Mohamed, Kos, Zuzana, van Diest, Paul J., Verbandt, Sara, Thagaard, Jeppe, Khiroya, Reena, Abduljabbar, Khalid, Acosta Haab, Gabriela, Acs, Balazs, Adams, Sylvia, Almeida, Jonas S., Alvarado-Cabrero, Isabel, Azmoudeh-Ardalan, Farid, Badve, Sunil, Baharun, Nurkhairul Bariyah, Bellolio, Enrique R., Bheemaraju, Vydehi, Blenman, Kim R.M., Botinelly Mendonça Fujimoto, Luciana, Burgues, Octavio, Chardas, Alexandros, Cheang, Maggie Chon U., Ciompi, Francesco, Cooper, Lee A.D., Coosemans, An, Corredor, Germán, Dantas Portela, Flavio Luis, Deman, Frederik, Demaria, Sandra, Dudgeon, Sarah N., Elghazawy, Mahmoud, Fernandez-Martín, Claudio, Fineberg, Susan, Fox, Stephen B., Giltnane, Jennifer M., Gnjatic, Sacha, Gonzalez-Ericsson, Paula I., Grigoriadis, Anita, Halama, Niels, Hanna, Matthew G., Harbhajanka, Aparna, Hart, Steven N., Hartman, Johan, Hewitt, Stephen, Horlings, Hugo M., Husain, Zaheed, Irshad, Sheeba, Janssen, Emiel A.M., Kataoka, Tatsuki R., Kawaguchi, Kosuke, Khramtsov, Andrey I., Kiraz, Umay, Kirtani, Pawan, Kodach, Liudmila L., Korski, Konstanty, Akturk, Guray, Scott, Ely, Kovács, Anikó, Lænkholm, Anne Vibeke, Lang-Schwarz, Corinna, Larsimont, Denis, Lennerz, Jochen K., Lerousseau, Marvin, Li, Xiaoxian, Madabhushi, Anant, Maley, Sai K., Manur Narasimhamurthy, Vidya, Marks, Douglas K., McDonald, Elizabeth S., Mehrotra, Ravi, Michiels, Stefan, Kharidehal, Durga, Minhas, Fayyaz ul Amir Afsar, Mittal, Shachi, Moore, David A., Mushtaq, Shamim, Nighat, Hussain, Papathomas, Thomas, Penault-Llorca, Frederique, Perera, Rashindrie D., Pinard, Christopher J., Pinto-Cardenas, Juan Carlos, Pruneri, Giancarlo, Pusztai, Lajos, Rajpoot, Nasir Mahmood, Rapoport, Bernardo Leon, Rau, Tilman T., Ribeiro, Joana M., Rimm, David, Vincent-Salomon, Anne, Saltz, Joel, Sayed, Shahin, Hytopoulos, Evangelos, Mahon, Sarah, Siziopikou, Kalliopi P., Sotiriou, Christos, Stenzinger, Albrecht, Sughayer, Maher A., Sur, Daniel, Symmans, Fraser, Tanaka, Sunao, Taxter, Timothy, Tejpar, Sabine, Teuwen, Jonas, Thompson, E. Aubrey, Tramm, Trine, Tran, William T., van der Laak, Jeroen, Verghese, Gregory E., Viale, Giuseppe, Wahab, Noorul, Walter, Thomas, Waumans, Yannick, Wen, Hannah Y., Yang, Wentao, Yuan, Yinyin, Bartlett, John, Loibl, Sibylle, Denkert, Carsten, Savas, Peter, Loi, Sherene, Specht Stovgaard, Elisabeth, Salgado, Roberto, Gallagher, William M., and Rahman, Arman

Published
2024

6. Image-based multiplex immune profiling of cancer tissues:translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Author

Jahangir, Chowdhury Arif, Page, David B., Broeckx, Glenn, Gonzalez, Claudia A., Burke, Caoimbhe, Murphy, Clodagh, Reis-Filho, Jorge S., Ly, Amy, Harms, Paul W., Gupta, Rajarsi R., Vieth, Michael, Hida, Akira I., Kahila, Mohamed, Kos, Zuzana, van Diest, Paul J., Verbandt, Sara, Thagaard, Jeppe, Khiroya, Reena, Abduljabbar, Khalid, Acosta Haab, Gabriela, Acs, Balazs, Adams, Sylvia, Almeida, Jonas S., Alvarado-Cabrero, Isabel, Azmoudeh-Ardalan, Farid, Badve, Sunil, Baharun, Nurkhairul Bariyah, Bellolio, Enrique R., Bheemaraju, Vydehi, Blenman, Kim R.M., Botinelly Mendonça Fujimoto, Luciana, Burgues, Octavio, Chardas, Alexandros, Cheang, Maggie Chon U., Ciompi, Francesco, Cooper, Lee A.D., Coosemans, An, Corredor, Germán, Dantas Portela, Flavio Luis, Deman, Frederik, Demaria, Sandra, Dudgeon, Sarah N., Elghazawy, Mahmoud, Fernandez-Martín, Claudio, Fineberg, Susan, Fox, Stephen B., Giltnane, Jennifer M., Gnjatic, Sacha, Gonzalez-Ericsson, Paula I., Grigoriadis, Anita, Halama, Niels, Hanna, Matthew G., Harbhajanka, Aparna, Hart, Steven N., Hartman, Johan, Hewitt, Stephen, Horlings, Hugo M., Husain, Zaheed, Irshad, Sheeba, Janssen, Emiel A.M., Kataoka, Tatsuki R., Kawaguchi, Kosuke, Khramtsov, Andrey I., Kiraz, Umay, Kirtani, Pawan, Kodach, Liudmila L., Korski, Konstanty, Akturk, Guray, Scott, Ely, Kovács, Anikó, Lænkholm, Anne Vibeke, Lang-Schwarz, Corinna, Larsimont, Denis, Lennerz, Jochen K., Lerousseau, Marvin, Li, Xiaoxian, Madabhushi, Anant, Maley, Sai K., Manur Narasimhamurthy, Vidya, Marks, Douglas K., McDonald, Elizabeth S., Mehrotra, Ravi, Michiels, Stefan, Kharidehal, Durga, Minhas, Fayyaz ul Amir Afsar, Mittal, Shachi, Moore, David A., Mushtaq, Shamim, Nighat, Hussain, Papathomas, Thomas, Penault-Llorca, Frederique, Perera, Rashindrie D., Pinard, Christopher J., Pinto-Cardenas, Juan Carlos, Pruneri, Giancarlo, Pusztai, Lajos, Rajpoot, Nasir Mahmood, Rapoport, Bernardo Leon, Rau, Tilman T., Ribeiro, Joana M., Rimm, David, Vincent-Salomon, Anne, Saltz, Joel, Sayed, Shahin, Hytopoulos, Evangelos, Mahon, Sarah, Siziopikou, Kalliopi P., Sotiriou, Christos, Stenzinger, Albrecht, Sughayer, Maher A., Sur, Daniel, Symmans, Fraser, Tanaka, Sunao, Taxter, Timothy, Tejpar, Sabine, Teuwen, Jonas, Thompson, E. Aubrey, Tramm, Trine, Tran, William T., van der Laak, Jeroen, Verghese, Gregory E., Viale, Giuseppe, Wahab, Noorul, Walter, Thomas, Waumans, Yannick, Wen, Hannah Y., Yang, Wentao, Yuan, Yinyin, Bartlett, John, Loibl, Sibylle, Denkert, Carsten, Savas, Peter, Loi, Sherene, Specht Stovgaard, Elisabeth, Salgado, Roberto, Gallagher, William M., Rahman, Arman, Jahangir, Chowdhury Arif, Page, David B., Broeckx, Glenn, Gonzalez, Claudia A., Burke, Caoimbhe, Murphy, Clodagh, Reis-Filho, Jorge S., Ly, Amy, Harms, Paul W., Gupta, Rajarsi R., Vieth, Michael, Hida, Akira I., Kahila, Mohamed, Kos, Zuzana, van Diest, Paul J., Verbandt, Sara, Thagaard, Jeppe, Khiroya, Reena, Abduljabbar, Khalid, Acosta Haab, Gabriela, Acs, Balazs, Adams, Sylvia, Almeida, Jonas S., Alvarado-Cabrero, Isabel, Azmoudeh-Ardalan, Farid, Badve, Sunil, Baharun, Nurkhairul Bariyah, Bellolio, Enrique R., Bheemaraju, Vydehi, Blenman, Kim R.M., Botinelly Mendonça Fujimoto, Luciana, Burgues, Octavio, Chardas, Alexandros, Cheang, Maggie Chon U., Ciompi, Francesco, Cooper, Lee A.D., Coosemans, An, Corredor, Germán, Dantas Portela, Flavio Luis, Deman, Frederik, Demaria, Sandra, Dudgeon, Sarah N., Elghazawy, Mahmoud, Fernandez-Martín, Claudio, Fineberg, Susan, Fox, Stephen B., Giltnane, Jennifer M., Gnjatic, Sacha, Gonzalez-Ericsson, Paula I., Grigoriadis, Anita, Halama, Niels, Hanna, Matthew G., Harbhajanka, Aparna, Hart, Steven N., Hartman, Johan, Hewitt, Stephen, Horlings, Hugo M., Husain, Zaheed, Irshad, Sheeba, Janssen, Emiel A.M., Kataoka, Tatsuki R., Kawaguchi, Kosuke, Khramtsov, Andrey I., Kiraz, Umay, Kirtani, Pawan, Kodach, Liudmila L., Korski, Konstanty, Akturk, Guray, Scott, Ely, Kovács, Anikó, Lænkholm, Anne Vibeke, Lang-Schwarz, Corinna, Larsimont, Denis, Lennerz, Jochen K., Lerousseau, Marvin, Li, Xiaoxian, Madabhushi, Anant, Maley, Sai K., Manur Narasimhamurthy, Vidya, Marks, Douglas K., McDonald, Elizabeth S., Mehrotra, Ravi, Michiels, Stefan, Kharidehal, Durga, Minhas, Fayyaz ul Amir Afsar, Mittal, Shachi, Moore, David A., Mushtaq, Shamim, Nighat, Hussain, Papathomas, Thomas, Penault-Llorca, Frederique, Perera, Rashindrie D., Pinard, Christopher J., Pinto-Cardenas, Juan Carlos, Pruneri, Giancarlo, Pusztai, Lajos, Rajpoot, Nasir Mahmood, Rapoport, Bernardo Leon, Rau, Tilman T., Ribeiro, Joana M., Rimm, David, Vincent-Salomon, Anne, Saltz, Joel, Sayed, Shahin, Hytopoulos, Evangelos, Mahon, Sarah, Siziopikou, Kalliopi P., Sotiriou, Christos, Stenzinger, Albrecht, Sughayer, Maher A., Sur, Daniel, Symmans, Fraser, Tanaka, Sunao, Taxter, Timothy, Tejpar, Sabine, Teuwen, Jonas, Thompson, E. Aubrey, Tramm, Trine, Tran, William T., van der Laak, Jeroen, Verghese, Gregory E., Viale, Giuseppe, Wahab, Noorul, Walter, Thomas, Waumans, Yannick, Wen, Hannah Y., Yang, Wentao, Yuan, Yinyin, Bartlett, John, Loibl, Sibylle, Denkert, Carsten, Savas, Peter, Loi, Sherene, Specht Stovgaard, Elisabeth, Salgado, Roberto, Gallagher, William M., and Rahman, Arman

Abstract

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer.

Published
2024

7. Image‐based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno‐oncology Biomarker Working Group on Breast Cancer

Author

Jahangir, Chowdhury Arif, primary, Page, David B, additional, Broeckx, Glenn, additional, Gonzalez, Claudia A, additional, Burke, Caoimbhe, additional, Murphy, Clodagh, additional, Reis‐Filho, Jorge S, additional, Ly, Amy, additional, Harms, Paul W, additional, Gupta, Rajarsi R, additional, Vieth, Michael, additional, Hida, Akira I, additional, Kahila, Mohamed, additional, Kos, Zuzana, additional, van Diest, Paul J, additional, Verbandt, Sara, additional, Thagaard, Jeppe, additional, Khiroya, Reena, additional, Abduljabbar, Khalid, additional, Acosta Haab, Gabriela, additional, Acs, Balazs, additional, Adams, Sylvia, additional, Almeida, Jonas S, additional, Alvarado‐Cabrero, Isabel, additional, Azmoudeh‐Ardalan, Farid, additional, Badve, Sunil, additional, Baharun, Nurkhairul Bariyah, additional, Bellolio, Enrique R, additional, Bheemaraju, Vydehi, additional, Blenman, Kim RM, additional, Botinelly Mendonça Fujimoto, Luciana, additional, Burgues, Octavio, additional, Chardas, Alexandros, additional, Cheang, Maggie Chon U, additional, Ciompi, Francesco, additional, Cooper, Lee AD, additional, Coosemans, An, additional, Corredor, Germán, additional, Dantas Portela, Flavio Luis, additional, Deman, Frederik, additional, Demaria, Sandra, additional, Dudgeon, Sarah N, additional, Elghazawy, Mahmoud, additional, Fernandez‐Martín, Claudio, additional, Fineberg, Susan, additional, Fox, Stephen B, additional, Giltnane, Jennifer M, additional, Gnjatic, Sacha, additional, Gonzalez‐Ericsson, Paula I, additional, Grigoriadis, Anita, additional, Halama, Niels, additional, Hanna, Matthew G, additional, Harbhajanka, Aparna, additional, Hart, Steven N, additional, Hartman, Johan, additional, Hewitt, Stephen, additional, Horlings, Hugo M, additional, Husain, Zaheed, additional, Irshad, Sheeba, additional, Janssen, Emiel AM, additional, Kataoka, Tatsuki R, additional, Kawaguchi, Kosuke, additional, Khramtsov, Andrey I, additional, Kiraz, Umay, additional, Kirtani, Pawan, additional, Kodach, Liudmila L, additional, Korski, Konstanty, additional, Akturk, Guray, additional, Scott, Ely, additional, Kovács, Anikó, additional, Lænkholm, Anne‐Vibeke, additional, Lang‐Schwarz, Corinna, additional, Larsimont, Denis, additional, Lennerz, Jochen K, additional, Lerousseau, Marvin, additional, Li, Xiaoxian, additional, Madabhushi, Anant, additional, Maley, Sai K, additional, Manur Narasimhamurthy, Vidya, additional, Marks, Douglas K, additional, McDonald, Elizabeth S, additional, Mehrotra, Ravi, additional, Michiels, Stefan, additional, Kharidehal, Durga, additional, Minhas, Fayyaz ul Amir Afsar, additional, Mittal, Shachi, additional, Moore, David A, additional, Mushtaq, Shamim, additional, Nighat, Hussain, additional, Papathomas, Thomas, additional, Penault‐Llorca, Frederique, additional, Perera, Rashindrie D, additional, Pinard, Christopher J, additional, Pinto‐Cardenas, Juan Carlos, additional, Pruneri, Giancarlo, additional, Pusztai, Lajos, additional, Rajpoot, Nasir Mahmood, additional, Rapoport, Bernardo Leon, additional, Rau, Tilman T, additional, Ribeiro, Joana M, additional, Rimm, David, additional, Vincent‐Salomon, Anne, additional, Saltz, Joel, additional, Sayed, Shahin, additional, Hytopoulos, Evangelos, additional, Mahon, Sarah, additional, Siziopikou, Kalliopi P, additional, Sotiriou, Christos, additional, Stenzinger, Albrecht, additional, Sughayer, Maher A, additional, Sur, Daniel, additional, Symmans, Fraser, additional, Tanaka, Sunao, additional, Taxter, Timothy, additional, Tejpar, Sabine, additional, Teuwen, Jonas, additional, Thompson, E Aubrey, additional, Tramm, Trine, additional, Tran, William T, additional, van der Laak, Jeroen, additional, Verghese, Gregory E, additional, Viale, Giuseppe, additional, Wahab, Noorul, additional, Walter, Thomas, additional, Waumans, Yannick, additional, Wen, Hannah Y, additional, Yang, Wentao, additional, Yuan, Yinyin, additional, Bartlett, John, additional, Loibl, Sibylle, additional, Denkert, Carsten, additional, Savas, Peter, additional, Loi, Sherene, additional, Specht Stovgaard, Elisabeth, additional, Salgado, Roberto, additional, Gallagher, William M, additional, and Rahman, Arman, additional

Published
2024
Full Text
View/download PDF

10. Artificial intelligence in digital histopathology for predicting patient prognosis and treatment efficacy in breast cancer.

Author

McCaffrey, Christine, Jahangir, Chowdhury, Murphy, Clodagh, Burke, Caoimbhe, Gallagher, William M., and Rahman, Arman

Abstract

Histological images contain phenotypic information predictive of patient outcomes. Due to the heavy workload of pathologists, the time-consuming nature of quantitatively assessing histological features, and human eye limitations to recognize spatial patterns, manually extracting prognostic information in routine pathological workflows remains challenging. Digital pathology has facilitated the mining and quantification of these features utilizing whole-slide image (WSI) scanners and artificial intelligence (AI) algorithms. AI algorithms to identify image-based biomarkers from the tumor microenvironment (TME) have the potential to revolutionize the field of oncology, reducing delays between diagnosis and prognosis determination, allowing for rapid stratification of patients and prescription of optimal treatment regimes, thereby improving patient outcomes. In this review, the authors discuss how AI algorithms and digital pathology can predict breast cancer patient prognosis and treatment outcomes using image-based biomarkers, along with the challenges of adopting this technology in clinical settings. The integration of AI and digital pathology presents significant potential for analyzing the TME and its diagnostic, prognostic, and predictive value in breast cancer patients. Widespread clinical adoption of AI faces ethical, regulatory, and technical challenges, although prospective trials may offer reassurance and promote uptake, ultimately improving patient outcomes by reducing diagnosis-to-prognosis delivery delays. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

11. Spatial analyses of immune cell infiltration in cancer: current methods and future directions. A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer

Author

Page, David B, primary, Broeckx, Glenn, additional, Jahangir, Chowdhury Arif, additional, Verbandt, Sara, additional, Gupta, Rajarsi R, additional, Thagaard, Jeppe, additional, Khiroya, Reena, additional, Kos, Zuzana, additional, Abduljabbar, Khalid, additional, Acosta Haab, Gabriela, additional, Acs, Balazs, additional, Almeida, Jonas S, additional, Alvarado‐Cabrero, Isabel, additional, Azmoudeh‐Ardalan, Farid, additional, Badve, Sunil, additional, Baharun, Nurkhairul Bariyah, additional, Bellolio, Enrique R, additional, Bheemaraju, Vydehi, additional, Blenman, Kim RM, additional, Botinelly Mendonça Fujimoto, Luciana, additional, Burgues, Octavio, additional, Cheang, Maggie Chon U, additional, Ciompi, Francesco, additional, Cooper, Lee AD, additional, Coosemans, An, additional, Corredor, Germán, additional, Dantas Portela, Flavio Luis, additional, Deman, Frederik, additional, Demaria, Sandra, additional, Dudgeon, Sarah N, additional, Elghazawy, Mahmoud, additional, Ely, Scott, additional, Fernandez‐Martín, Claudio, additional, Fineberg, Susan, additional, Fox, Stephen B, additional, Gallagher, William M, additional, Giltnane, Jennifer M, additional, Gnjatic, Sacha, additional, Gonzalez‐Ericsson, Paula I, additional, Grigoriadis, Anita, additional, Halama, Niels, additional, Hanna, Matthew G, additional, Harbhajanka, Aparna, additional, Hardas, Alexandros, additional, Hart, Steven N, additional, Hartman, Johan, additional, Hewitt, Stephen, additional, Hida, Akira I, additional, Horlings, Hugo M, additional, Husain, Zaheed, additional, Hytopoulos, Evangelos, additional, Irshad, Sheeba, additional, Janssen, Emiel AM, additional, Kahila, Mohamed, additional, Kataoka, Tatsuki R, additional, Kawaguchi, Kosuke, additional, Kharidehal, Durga, additional, Khramtsov, Andrey I, additional, Kiraz, Umay, additional, Kirtani, Pawan, additional, Kodach, Liudmila L, additional, Korski, Konstanty, additional, Kovács, Anikó, additional, Laenkholm, Anne‐Vibeke, additional, Lang‐Schwarz, Corinna, additional, Larsimont, Denis, additional, Lennerz, Jochen K, additional, Lerousseau, Marvin, additional, Li, Xiaoxian, additional, Ly, Amy, additional, Madabhushi, Anant, additional, Maley, Sai K, additional, Manur Narasimhamurthy, Vidya, additional, Marks, Douglas K, additional, McDonald, Elizabeth S, additional, Mehrotra, Ravi, additional, Michiels, Stefan, additional, Minhas, Fayyaz ul Amir Afsar, additional, Mittal, Shachi, additional, Moore, David A, additional, Mushtaq, Shamim, additional, Nighat, Hussain, additional, Papathomas, Thomas, additional, Penault‐Llorca, Frederique, additional, Perera, Rashindrie D, additional, Pinard, Christopher J, additional, Pinto‐Cardenas, Juan Carlos, additional, Pruneri, Giancarlo, additional, Pusztai, Lajos, additional, Rahman, Arman, additional, Rajpoot, Nasir Mahmood, additional, Rapoport, Bernardo Leon, additional, Rau, Tilman T, additional, Reis‐Filho, Jorge S, additional, Ribeiro, Joana M, additional, Rimm, David, additional, Salomon, Anne‐Vincent, additional, Salto‐Tellez, Manuel, additional, Saltz, Joel, additional, Sayed, Shahin, additional, Siziopikou, Kalliopi P, additional, Sotiriou, Christos, additional, Stenzinger, Albrecht, additional, Sughayer, Maher A, additional, Sur, Daniel, additional, Symmans, Fraser, additional, Tanaka, Sunao, additional, Taxter, Timothy, additional, Tejpar, Sabine, additional, Teuwen, Jonas, additional, Thompson, E Aubrey, additional, Tramm, Trine, additional, Tran, William T, additional, van der Laak, Jeroen, additional, van Diest, Paul J, additional, Verghese, Gregory E, additional, Viale, Giuseppe, additional, Vieth, Michael, additional, Wahab, Noorul, additional, Walter, Thomas, additional, Waumans, Yannick, additional, Wen, Hannah Y, additional, Yang, Wentao, additional, Yuan, Yinyin, additional, Adams, Sylvia, additional, Bartlett, John Mark Seaverns, additional, Loibl, Sibylle, additional, Denkert, Carsten, additional, Savas, Peter, additional, Loi, Sherene, additional, Salgado, Roberto, additional, Specht Stovgaard, Elisabeth, additional, Akturk, Guray, additional, and Bouchmaa, Najat, additional

Published
2023
Full Text
View/download PDF

12. Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: a report of the international immuno‐oncology biomarker working group

Author

Thagaard, Jeppe, primary, Broeckx, Glenn, additional, Page, David B, additional, Jahangir, Chowdhury Arif, additional, Verbandt, Sara, additional, Kos, Zuzana, additional, Gupta, Rajarsi, additional, Khiroya, Reena, additional, Abduljabbar, Khalid, additional, Acosta Haab, Gabriela, additional, Acs, Balazs, additional, Akturk, Guray, additional, Almeida, Jonas S, additional, Alvarado‐Cabrero, Isabel, additional, Amgad, Mohamed, additional, Azmoudeh‐Ardalan, Farid, additional, Badve, Sunil, additional, Baharun, Nurkhairul Bariyah, additional, Balslev, Eva, additional, Bellolio, Enrique R, additional, Bheemaraju, Vydehi, additional, Blenman, Kim RM, additional, Botinelly Mendonça Fujimoto, Luciana, additional, Bouchmaa, Najat, additional, Burgues, Octavio, additional, Chardas, Alexandros, additional, Chon U Cheang, Maggie, additional, Ciompi, Francesco, additional, Cooper, Lee AD, additional, Coosemans, An, additional, Corredor, Germán, additional, Dahl, Anders B, additional, Dantas Portela, Flavio Luis, additional, Deman, Frederik, additional, Demaria, Sandra, additional, Doré Hansen, Johan, additional, Dudgeon, Sarah N, additional, Ebstrup, Thomas, additional, Elghazawy, Mahmoud, additional, Fernandez‐Martín, Claudio, additional, Fox, Stephen B, additional, Gallagher, William M, additional, Giltnane, Jennifer M, additional, Gnjatic, Sacha, additional, Gonzalez‐Ericsson, Paula I, additional, Grigoriadis, Anita, additional, Halama, Niels, additional, Hanna, Matthew G, additional, Harbhajanka, Aparna, additional, Hart, Steven N, additional, Hartman, Johan, additional, Hauberg, Søren, additional, Hewitt, Stephen, additional, Hida, Akira I, additional, Horlings, Hugo M, additional, Husain, Zaheed, additional, Hytopoulos, Evangelos, additional, Irshad, Sheeba, additional, Janssen, Emiel AM, additional, Kahila, Mohamed, additional, Kataoka, Tatsuki R, additional, Kawaguchi, Kosuke, additional, Kharidehal, Durga, additional, Khramtsov, Andrey I, additional, Kiraz, Umay, additional, Kirtani, Pawan, additional, Kodach, Liudmila L, additional, Korski, Konstanty, additional, Kovács, Anikó, additional, Laenkholm, Anne‐Vibeke, additional, Lang‐Schwarz, Corinna, additional, Larsimont, Denis, additional, Lennerz, Jochen K, additional, Lerousseau, Marvin, additional, Li, Xiaoxian, additional, Ly, Amy, additional, Madabhushi, Anant, additional, Maley, Sai K, additional, Manur Narasimhamurthy, Vidya, additional, Marks, Douglas K, additional, McDonald, Elizabeth S, additional, Mehrotra, Ravi, additional, Michiels, Stefan, additional, Minhas, Fayyaz ul Amir Afsar, additional, Mittal, Shachi, additional, Moore, David A, additional, Mushtaq, Shamim, additional, Nighat, Hussain, additional, Papathomas, Thomas, additional, Penault‐Llorca, Frederique, additional, Perera, Rashindrie D, additional, Pinard, Christopher J, additional, Pinto‐Cardenas, Juan Carlos, additional, Pruneri, Giancarlo, additional, Pusztai, Lajos, additional, Rahman, Arman, additional, Rajpoot, Nasir Mahmood, additional, Rapoport, Bernardo Leon, additional, Rau, Tilman T, additional, Reis‐Filho, Jorge S, additional, Ribeiro, Joana M, additional, Rimm, David, additional, Roslind, Anne, additional, Vincent‐Salomon, Anne, additional, Salto‐Tellez, Manuel, additional, Saltz, Joel, additional, Sayed, Shahin, additional, Scott, Ely, additional, Siziopikou, Kalliopi P, additional, Sotiriou, Christos, additional, Stenzinger, Albrecht, additional, Sughayer, Maher A, additional, Sur, Daniel, additional, Fineberg, Susan, additional, Symmans, Fraser, additional, Tanaka, Sunao, additional, Taxter, Timothy, additional, Tejpar, Sabine, additional, Teuwen, Jonas, additional, Thompson, E Aubrey, additional, Tramm, Trine, additional, Tran, William T, additional, van der Laak, Jeroen, additional, van Diest, Paul J, additional, Verghese, Gregory E, additional, Viale, Giuseppe, additional, Vieth, Michael, additional, Wahab, Noorul, additional, Walter, Thomas, additional, Waumans, Yannick, additional, Wen, Hannah Y, additional, Yang, Wentao, additional, Yuan, Yinyin, additional, Zin, Reena Md, additional, Adams, Sylvia, additional, Bartlett, John, additional, Loibl, Sibylle, additional, Denkert, Carsten, additional, Savas, Peter, additional, Loi, Sherene, additional, Salgado, Roberto, additional, and Specht Stovgaard, Elisabeth, additional

Published
2023
Full Text
View/download PDF

14. An Insight Analysis of In0.7Ga0.3N Based pn Homo-Junction Solar Cell using SCAPS-1D Simulation Software.

Author

Rahman, Arman, Hossain, Emran, and Hussain, Sakhawat

Abstract

An insight analysis of In0.7Ga0.3N based pn homo-junction solar cell structure has been carried out using simulation software. A novel solar cell structure of n+ buffer contact layer/n window layer/p absorber layer/p+ back absorber layer has been proposed after device optimization. We have found that under the sun spectrum of AM 1.5 of 1 KW/m2 operating at 300 K, the solar cell with low series resistance of 3 Ω cm2, highly doped (1×1019 cm–3) n+ layer as buffer contact layer and p+ layer of 200 nm thick as back absorber layer on top of back metal contact, enable us to achieve an efficient solar cell. We found that doping concentration of in both active n and p layer, with 30 nm and 1.0 of thickness, respectively, would allow us to achieve short circuit current density of , open circuit voltage of 1.0 V, overall efficiency of 28.32% and fill factor value of 80% from the solar cell. If we could further reduce the series resistance of In0.7Ga0.3N pn homo-junction solar cell to ideal one, it may allow us to have even higher overall efficiency and fill factor values of 31 and 86%, respectively. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

15. Abstract 5787: Modelling the spatial heterogeneity of CD45-positive tumor infiltrating lymphocytes in early-stage, estrogen receptor-positive breast cancer

Author

Kinsella, Zak, primary, Blümel, Anna, additional, Lucas, Mairi, additional, Lindner, Andreas, additional, Gonzalez, Claudia A., additional, Rahman, Arman, additional, Fay, Joanna, additional, O'Grady, Tony, additional, Murphy, Verena, additional, Crown, John, additional, Kelly, Cathy, additional, Gallagher, William, additional, and O'Connor, Darran, additional

Published
2023
Full Text
View/download PDF

16. Data from Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell–Cell Interactions That Predict Immunotherapy Response

Author

Antoranz, Asier, primary, Van Herck, Yannick, primary, Bolognesi, Maddalena M., primary, Lynch, Seodhna M., primary, Rahman, Arman, primary, Gallagher, William M., primary, Boecxstaens, Veerle, primary, Marine, Jean-Christophe, primary, Cattoretti, Giorgio, primary, van den Oord, Joost J., primary, De Smet, Frederik, primary, Bechter, Oliver, primary, and Bosisio, Francesca M., primary

Published
2023
Full Text
View/download PDF

17. Supplementary Figure from Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell–Cell Interactions That Predict Immunotherapy Response

Author

Antoranz, Asier, primary, Van Herck, Yannick, primary, Bolognesi, Maddalena M., primary, Lynch, Seodhna M., primary, Rahman, Arman, primary, Gallagher, William M., primary, Boecxstaens, Veerle, primary, Marine, Jean-Christophe, primary, Cattoretti, Giorgio, primary, van den Oord, Joost J., primary, De Smet, Frederik, primary, Bechter, Oliver, primary, and Bosisio, Francesca M., primary

Published
2023
Full Text
View/download PDF

18. Supplementary Data from Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell–Cell Interactions That Predict Immunotherapy Response

Author

Antoranz, Asier, primary, Van Herck, Yannick, primary, Bolognesi, Maddalena M., primary, Lynch, Seodhna M., primary, Rahman, Arman, primary, Gallagher, William M., primary, Boecxstaens, Veerle, primary, Marine, Jean-Christophe, primary, Cattoretti, Giorgio, primary, van den Oord, Joost J., primary, De Smet, Frederik, primary, Bechter, Oliver, primary, and Bosisio, Francesca M., primary

Published
2023
Full Text
View/download PDF

19. Supplementary Table from Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell–Cell Interactions That Predict Immunotherapy Response

Author

Antoranz, Asier, primary, Van Herck, Yannick, primary, Bolognesi, Maddalena M., primary, Lynch, Seodhna M., primary, Rahman, Arman, primary, Gallagher, William M., primary, Boecxstaens, Veerle, primary, Marine, Jean-Christophe, primary, Cattoretti, Giorgio, primary, van den Oord, Joost J., primary, De Smet, Frederik, primary, Bechter, Oliver, primary, and Bosisio, Francesca M., primary

Published
2023
Full Text
View/download PDF

20. Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer:A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Author

Thagaard, Jeppe, Broeckx, Glenn, Page, David B, Jahangir, Chowdhury Arif, Verbandt, Sara, Kos, Zuzana, Gupta, Rajarsi, Khiroya, Reena, Abduljabbar, Khalid, Acosta Haab, Gabriela, Acs, Balazs, Akturk, Guray, Almeida, Jonas S, Alvarado-Cabrero, Isabel, Amgad, Mohamed, Azmoudeh-Ardalan, Farid, Badve, Sunil, Baharun, Nurkhairul Bariyah, Balslev, Eva, Bellolio, Enrique R, Bheemaraju, Vydehi, Blenman, Kim Rm, Botinelly Mendonça Fujimoto, Luciana, Bouchmaa, Najat, Burgues, Octavio, Chardas, Alexandros, Chon U Cheang, Maggie, Ciompi, Francesco, Cooper, Lee Ad, Coosemans, An, Corredor, Germán, Dahl, Anders B, Dantas Portela, Flavio Luis, Deman, Frederik, Demaria, Sandra, Doré Hansen, Johan, Dudgeon, Sarah N, Ebstrup, Thomas, Elghazawy, Mahmoud, Fernandez-Martín, Claudio, Fox, Stephen B, Gallagher, William M, Giltnane, Jennifer M, Gnjatic, Sacha, Gonzalez-Ericsson, Paula I, Grigoriadis, Anita, Halama, Niels, Hanna, Matthew G, Harbhajanka, Aparna, Hart, Steven N, Hartman, Johan, Hauberg, Søren, Hewitt, Stephen, Hida, Akira I, Horlings, Hugo M, Husain, Zaheed, Hytopoulos, Evangelos, Irshad, Sheeba, Janssen, Emiel Am, Kahila, Mohamed, Kataoka, Tatsuki R, Kawaguchi, Kosuke, Kharidehal, Durga, Khramtsov, Andrey I, Kiraz, Umay, Kirtani, Pawan, Kodach, Liudmila L, Korski, Konstanty, Kovács, Anikó, Laenkholm, Anne-Vibeke, Lang-Schwarz, Corinna, Larsimont, Denis, Lennerz, Jochen K, Lerousseau, Marvin, Li, Xiaoxian, Ly, Amy, Madabhushi, Anant, Maley, Sai K, Manur Narasimhamurthy, Vidya, Marks, Douglas K, McDonald, Elizabeth S, Mehrotra, Ravi, Michiels, Stefan, Minhas, Fayyaz Ul Amir Afsar, Mittal, Shachi, Moore, David A, Mushtaq, Shamim, Nighat, Hussain, Papathomas, Thomas, Penault-Llorca, Frederique, Perera, Rashindrie D, Pinard, Christopher J, Pinto-Cardenas, Juan Carlos, Pruneri, Giancarlo, Pusztai, Lajos, Rahman, Arman, Rajpoot, Nasir Mahmood, Rapoport, Bernardo Leon, Rau, Tilman T, Reis-Filho, Jorge S, Ribeiro, Joana M, Rimm, David, Roslind, Anne, Vincent-Salomon, Anne, Salto-Tellez, Manuel, Saltz, Joel, Sayed, Shahin, Scott, Ely, Siziopikou, Kalliopi P, Sotiriou, Christos, Stenzinger, Albrecht, Sughayer, Maher A, Sur, Daniel, Fineberg, Susan, Symmans, Fraser, Tanaka, Sunao, Taxter, Timothy, Tejpar, Sabine, Teuwen, Jonas, Thompson, E Aubrey, Tramm, Trine, Tran, William T, van der Laak, Jeroen, van Diest, Paul J, Verghese, Gregory E, Viale, Giuseppe, Vieth, Michael, Wahab, Noorul, Walter, Thomas, Waumans, Yannick, Wen, Hannah Y, Yang, Wentao, Yuan, Yinyin, Zin, Reena Md, Adams, Sylvia, Bartlett, John, Loibl, Sibylle, Denkert, Carsten, Savas, Peter, Loi, Sherene, Salgado, Roberto, Specht Stovgaard, Elisabeth, Thagaard, Jeppe, Broeckx, Glenn, Page, David B, Jahangir, Chowdhury Arif, Verbandt, Sara, Kos, Zuzana, Gupta, Rajarsi, Khiroya, Reena, Abduljabbar, Khalid, Acosta Haab, Gabriela, Acs, Balazs, Akturk, Guray, Almeida, Jonas S, Alvarado-Cabrero, Isabel, Amgad, Mohamed, Azmoudeh-Ardalan, Farid, Badve, Sunil, Baharun, Nurkhairul Bariyah, Balslev, Eva, Bellolio, Enrique R, Bheemaraju, Vydehi, Blenman, Kim Rm, Botinelly Mendonça Fujimoto, Luciana, Bouchmaa, Najat, Burgues, Octavio, Chardas, Alexandros, Chon U Cheang, Maggie, Ciompi, Francesco, Cooper, Lee Ad, Coosemans, An, Corredor, Germán, Dahl, Anders B, Dantas Portela, Flavio Luis, Deman, Frederik, Demaria, Sandra, Doré Hansen, Johan, Dudgeon, Sarah N, Ebstrup, Thomas, Elghazawy, Mahmoud, Fernandez-Martín, Claudio, Fox, Stephen B, Gallagher, William M, Giltnane, Jennifer M, Gnjatic, Sacha, Gonzalez-Ericsson, Paula I, Grigoriadis, Anita, Halama, Niels, Hanna, Matthew G, Harbhajanka, Aparna, Hart, Steven N, Hartman, Johan, Hauberg, Søren, Hewitt, Stephen, Hida, Akira I, Horlings, Hugo M, Husain, Zaheed, Hytopoulos, Evangelos, Irshad, Sheeba, Janssen, Emiel Am, Kahila, Mohamed, Kataoka, Tatsuki R, Kawaguchi, Kosuke, Kharidehal, Durga, Khramtsov, Andrey I, Kiraz, Umay, Kirtani, Pawan, Kodach, Liudmila L, Korski, Konstanty, Kovács, Anikó, Laenkholm, Anne-Vibeke, Lang-Schwarz, Corinna, Larsimont, Denis, Lennerz, Jochen K, Lerousseau, Marvin, Li, Xiaoxian, Ly, Amy, Madabhushi, Anant, Maley, Sai K, Manur Narasimhamurthy, Vidya, Marks, Douglas K, McDonald, Elizabeth S, Mehrotra, Ravi, Michiels, Stefan, Minhas, Fayyaz Ul Amir Afsar, Mittal, Shachi, Moore, David A, Mushtaq, Shamim, Nighat, Hussain, Papathomas, Thomas, Penault-Llorca, Frederique, Perera, Rashindrie D, Pinard, Christopher J, Pinto-Cardenas, Juan Carlos, Pruneri, Giancarlo, Pusztai, Lajos, Rahman, Arman, Rajpoot, Nasir Mahmood, Rapoport, Bernardo Leon, Rau, Tilman T, Reis-Filho, Jorge S, Ribeiro, Joana M, Rimm, David, Roslind, Anne, Vincent-Salomon, Anne, Salto-Tellez, Manuel, Saltz, Joel, Sayed, Shahin, Scott, Ely, Siziopikou, Kalliopi P, Sotiriou, Christos, Stenzinger, Albrecht, Sughayer, Maher A, Sur, Daniel, Fineberg, Susan, Symmans, Fraser, Tanaka, Sunao, Taxter, Timothy, Tejpar, Sabine, Teuwen, Jonas, Thompson, E Aubrey, Tramm, Trine, Tran, William T, van der Laak, Jeroen, van Diest, Paul J, Verghese, Gregory E, Viale, Giuseppe, Vieth, Michael, Wahab, Noorul, Walter, Thomas, Waumans, Yannick, Wen, Hannah Y, Yang, Wentao, Yuan, Yinyin, Zin, Reena Md, Adams, Sylvia, Bartlett, John, Loibl, Sibylle, Denkert, Carsten, Savas, Peter, Loi, Sherene, Salgado, Roberto, and Specht Stovgaard, Elisabeth

Abstract

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer.

Published
2023

21. Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Author

Pathologie, Cancer, Thagaard, Jeppe, Broeckx, Glenn, Page, David B, Jahangir, Chowdhury Arif, Verbandt, Sara, Kos, Zuzana, Gupta, Rajarsi, Khiroya, Reena, Abduljabbar, Khalid, Acosta Haab, Gabriela, Acs, Balazs, Akturk, Guray, Almeida, Jonas S, Alvarado-Cabrero, Isabel, Amgad, Mohamed, Azmoudeh-Ardalan, Farid, Badve, Sunil, Baharun, Nurkhairul Bariyah, Balslev, Eva, Bellolio, Enrique R, Bheemaraju, Vydehi, Blenman, Kim Rm, Botinelly Mendonça Fujimoto, Luciana, Bouchmaa, Najat, Burgues, Octavio, Chardas, Alexandros, Chon U Cheang, Maggie, Ciompi, Francesco, Cooper, Lee Ad, Coosemans, An, Corredor, Germán, Dahl, Anders B, Dantas Portela, Flavio Luis, Deman, Frederik, Demaria, Sandra, Doré Hansen, Johan, Dudgeon, Sarah N, Ebstrup, Thomas, Elghazawy, Mahmoud, Fernandez-Martín, Claudio, Fox, Stephen B, Gallagher, William M, Giltnane, Jennifer M, Gnjatic, Sacha, Gonzalez-Ericsson, Paula I, Grigoriadis, Anita, Halama, Niels, Hanna, Matthew G, Harbhajanka, Aparna, Hart, Steven N, Hartman, Johan, Hauberg, Søren, Hewitt, Stephen, Hida, Akira I, Horlings, Hugo M, Husain, Zaheed, Hytopoulos, Evangelos, Irshad, Sheeba, Janssen, Emiel Am, Kahila, Mohamed, Kataoka, Tatsuki R, Kawaguchi, Kosuke, Kharidehal, Durga, Khramtsov, Andrey I, Kiraz, Umay, Kirtani, Pawan, Kodach, Liudmila L, Korski, Konstanty, Kovács, Anikó, Laenkholm, Anne-Vibeke, Lang-Schwarz, Corinna, Larsimont, Denis, Lennerz, Jochen K, Lerousseau, Marvin, Li, Xiaoxian, Ly, Amy, Madabhushi, Anant, Maley, Sai K, Manur Narasimhamurthy, Vidya, Marks, Douglas K, McDonald, Elizabeth S, Mehrotra, Ravi, Michiels, Stefan, Minhas, Fayyaz Ul Amir Afsar, Mittal, Shachi, Moore, David A, Mushtaq, Shamim, Nighat, Hussain, Papathomas, Thomas, Penault-Llorca, Frederique, Perera, Rashindrie D, Pinard, Christopher J, Pinto-Cardenas, Juan Carlos, Pruneri, Giancarlo, Pusztai, Lajos, Rahman, Arman, Rajpoot, Nasir Mahmood, Rapoport, Bernardo Leon, Rau, Tilman T, Reis-Filho, Jorge S, Ribeiro, Joana M, Rimm, David, Roslind, Anne, Vincent-Salomon, Anne, Salto-Tellez, Manuel, Saltz, Joel, Sayed, Shahin, Scott, Ely, Siziopikou, Kalliopi P, Sotiriou, Christos, Stenzinger, Albrecht, Sughayer, Maher A, Sur, Daniel, Fineberg, Susan, Symmans, Fraser, Tanaka, Sunao, Taxter, Timothy, Tejpar, Sabine, Teuwen, Jonas, Thompson, E Aubrey, Tramm, Trine, Tran, William T, van der Laak, Jeroen, van Diest, Paul J, Verghese, Gregory E, Viale, Giuseppe, Vieth, Michael, Wahab, Noorul, Walter, Thomas, Waumans, Yannick, Wen, Hannah Y, Yang, Wentao, Yuan, Yinyin, Zin, Reena Md, Adams, Sylvia, Bartlett, John, Loibl, Sibylle, Denkert, Carsten, Savas, Peter, Loi, Sherene, Salgado, Roberto, Specht Stovgaard, Elisabeth, Pathologie, Cancer, Thagaard, Jeppe, Broeckx, Glenn, Page, David B, Jahangir, Chowdhury Arif, Verbandt, Sara, Kos, Zuzana, Gupta, Rajarsi, Khiroya, Reena, Abduljabbar, Khalid, Acosta Haab, Gabriela, Acs, Balazs, Akturk, Guray, Almeida, Jonas S, Alvarado-Cabrero, Isabel, Amgad, Mohamed, Azmoudeh-Ardalan, Farid, Badve, Sunil, Baharun, Nurkhairul Bariyah, Balslev, Eva, Bellolio, Enrique R, Bheemaraju, Vydehi, Blenman, Kim Rm, Botinelly Mendonça Fujimoto, Luciana, Bouchmaa, Najat, Burgues, Octavio, Chardas, Alexandros, Chon U Cheang, Maggie, Ciompi, Francesco, Cooper, Lee Ad, Coosemans, An, Corredor, Germán, Dahl, Anders B, Dantas Portela, Flavio Luis, Deman, Frederik, Demaria, Sandra, Doré Hansen, Johan, Dudgeon, Sarah N, Ebstrup, Thomas, Elghazawy, Mahmoud, Fernandez-Martín, Claudio, Fox, Stephen B, Gallagher, William M, Giltnane, Jennifer M, Gnjatic, Sacha, Gonzalez-Ericsson, Paula I, Grigoriadis, Anita, Halama, Niels, Hanna, Matthew G, Harbhajanka, Aparna, Hart, Steven N, Hartman, Johan, Hauberg, Søren, Hewitt, Stephen, Hida, Akira I, Horlings, Hugo M, Husain, Zaheed, Hytopoulos, Evangelos, Irshad, Sheeba, Janssen, Emiel Am, Kahila, Mohamed, Kataoka, Tatsuki R, Kawaguchi, Kosuke, Kharidehal, Durga, Khramtsov, Andrey I, Kiraz, Umay, Kirtani, Pawan, Kodach, Liudmila L, Korski, Konstanty, Kovács, Anikó, Laenkholm, Anne-Vibeke, Lang-Schwarz, Corinna, Larsimont, Denis, Lennerz, Jochen K, Lerousseau, Marvin, Li, Xiaoxian, Ly, Amy, Madabhushi, Anant, Maley, Sai K, Manur Narasimhamurthy, Vidya, Marks, Douglas K, McDonald, Elizabeth S, Mehrotra, Ravi, Michiels, Stefan, Minhas, Fayyaz Ul Amir Afsar, Mittal, Shachi, Moore, David A, Mushtaq, Shamim, Nighat, Hussain, Papathomas, Thomas, Penault-Llorca, Frederique, Perera, Rashindrie D, Pinard, Christopher J, Pinto-Cardenas, Juan Carlos, Pruneri, Giancarlo, Pusztai, Lajos, Rahman, Arman, Rajpoot, Nasir Mahmood, Rapoport, Bernardo Leon, Rau, Tilman T, Reis-Filho, Jorge S, Ribeiro, Joana M, Rimm, David, Roslind, Anne, Vincent-Salomon, Anne, Salto-Tellez, Manuel, Saltz, Joel, Sayed, Shahin, Scott, Ely, Siziopikou, Kalliopi P, Sotiriou, Christos, Stenzinger, Albrecht, Sughayer, Maher A, Sur, Daniel, Fineberg, Susan, Symmans, Fraser, Tanaka, Sunao, Taxter, Timothy, Tejpar, Sabine, Teuwen, Jonas, Thompson, E Aubrey, Tramm, Trine, Tran, William T, van der Laak, Jeroen, van Diest, Paul J, Verghese, Gregory E, Viale, Giuseppe, Vieth, Michael, Wahab, Noorul, Walter, Thomas, Waumans, Yannick, Wen, Hannah Y, Yang, Wentao, Yuan, Yinyin, Zin, Reena Md, Adams, Sylvia, Bartlett, John, Loibl, Sibylle, Denkert, Carsten, Savas, Peter, Loi, Sherene, Salgado, Roberto, and Specht Stovgaard, Elisabeth

Published
2023

22. Spatial analyses of immune cell infiltration in cancer: current methods and future directions. A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Author

Pathologie, Cancer, Page, David B, Broeckx, Glenn, Jahangir, Chowdhury Arif, Verbandt, Sara, Gupta, Rajarsi R, Thagaard, Jeppe, Khiroya, Reena, Kos, Zuzana, Abduljabbar, Khalid, Acosta Haab, Gabriela, Acs, Balazs, Almeida, Jonas S, Alvarado-Cabrero, Isabel, Azmoudeh-Ardalan, Farid, Badve, Sunil, Baharun, Nurkhairul Bariyah, Bellolio, Enrique R, Bheemaraju, Vydehi, Blenman, Kim Rm, Botinelly Mendonça Fujimoto, Luciana, Burgues, Octavio, Cheang, Maggie Chon U, Ciompi, Francesco, Cooper, Lee Ad, Coosemans, An, Corredor, Germán, Dantas Portela, Flavio Luis, Deman, Frederik, Demaria, Sandra, Dudgeon, Sarah N, Elghazawy, Mahmoud, Ely, Scott, Fernandez-Martín, Claudio, Fineberg, Susan, Fox, Stephen B, Gallagher, William M, Giltnane, Jennifer M, Gnjatic, Sacha, Gonzalez-Ericsson, Paula I, Grigoriadis, Anita, Halama, Niels, Hanna, Matthew G, Harbhajanka, Aparna, Hardas, Alexandros, Hart, Steven N, Hartman, Johan, Hewitt, Stephen, Hida, Akira I, Horlings, Hugo M, Husain, Zaheed, Hytopoulos, Evangelos, Irshad, Sheeba, Janssen, Emiel Am, Kahila, Mohamed, Kataoka, Tatsuki R, Kawaguchi, Kosuke, Kharidehal, Durga, Khramtsov, Andrey I, Kiraz, Umay, Kirtani, Pawan, Kodach, Liudmila L, Korski, Konstanty, Kovács, Anikó, Laenkholm, Anne-Vibeke, Lang-Schwarz, Corinna, Larsimont, Denis, Lennerz, Jochen K, Lerousseau, Marvin, Li, Xiaoxian, Ly, Amy, Madabhushi, Anant, Maley, Sai K, Manur Narasimhamurthy, Vidya, Marks, Douglas K, McDonald, Elizabeth S, Mehrotra, Ravi, Michiels, Stefan, Minhas, Fayyaz Ul Amir Afsar, Mittal, Shachi, Moore, David A, Mushtaq, Shamim, Nighat, Hussain, Papathomas, Thomas, Penault-Llorca, Frederique, Perera, Rashindrie D, Pinard, Christopher J, Pinto-Cardenas, Juan Carlos, Pruneri, Giancarlo, Pusztai, Lajos, Rahman, Arman, Rajpoot, Nasir Mahmood, Rapoport, Bernardo Leon, Rau, Tilman T, Reis-Filho, Jorge S, Ribeiro, Joana M, Rimm, David, Salomon, Anne-Vincent, Salto-Tellez, Manuel, Saltz, Joel, Sayed, Shahin, Siziopikou, Kalliopi P, Sotiriou, Christos, Stenzinger, Albrecht, Sughayer, Maher A, Sur, Daniel, Symmans, Fraser, Tanaka, Sunao, Taxter, Timothy, Tejpar, Sabine, Teuwen, Jonas, Thompson, E Aubrey, Tramm, Trine, Tran, William T, van der Laak, Jeroen, van Diest, Paul J, Verghese, Gregory E, Viale, Giuseppe, Vieth, Michael, Wahab, Noorul, Walter, Thomas, Waumans, Yannick, Wen, Hannah Y, Yang, Wentao, Yuan, Yinyin, Adams, Sylvia, Bartlett, John Mark Seaverns, Loibl, Sibylle, Denkert, Carsten, Savas, Peter, Loi, Sherene, Salgado, Roberto, Specht Stovgaard, Elisabeth, Akturk, Guray, Bouchmaa, Najat, Pathologie, Cancer, Page, David B, Broeckx, Glenn, Jahangir, Chowdhury Arif, Verbandt, Sara, Gupta, Rajarsi R, Thagaard, Jeppe, Khiroya, Reena, Kos, Zuzana, Abduljabbar, Khalid, Acosta Haab, Gabriela, Acs, Balazs, Almeida, Jonas S, Alvarado-Cabrero, Isabel, Azmoudeh-Ardalan, Farid, Badve, Sunil, Baharun, Nurkhairul Bariyah, Bellolio, Enrique R, Bheemaraju, Vydehi, Blenman, Kim Rm, Botinelly Mendonça Fujimoto, Luciana, Burgues, Octavio, Cheang, Maggie Chon U, Ciompi, Francesco, Cooper, Lee Ad, Coosemans, An, Corredor, Germán, Dantas Portela, Flavio Luis, Deman, Frederik, Demaria, Sandra, Dudgeon, Sarah N, Elghazawy, Mahmoud, Ely, Scott, Fernandez-Martín, Claudio, Fineberg, Susan, Fox, Stephen B, Gallagher, William M, Giltnane, Jennifer M, Gnjatic, Sacha, Gonzalez-Ericsson, Paula I, Grigoriadis, Anita, Halama, Niels, Hanna, Matthew G, Harbhajanka, Aparna, Hardas, Alexandros, Hart, Steven N, Hartman, Johan, Hewitt, Stephen, Hida, Akira I, Horlings, Hugo M, Husain, Zaheed, Hytopoulos, Evangelos, Irshad, Sheeba, Janssen, Emiel Am, Kahila, Mohamed, Kataoka, Tatsuki R, Kawaguchi, Kosuke, Kharidehal, Durga, Khramtsov, Andrey I, Kiraz, Umay, Kirtani, Pawan, Kodach, Liudmila L, Korski, Konstanty, Kovács, Anikó, Laenkholm, Anne-Vibeke, Lang-Schwarz, Corinna, Larsimont, Denis, Lennerz, Jochen K, Lerousseau, Marvin, Li, Xiaoxian, Ly, Amy, Madabhushi, Anant, Maley, Sai K, Manur Narasimhamurthy, Vidya, Marks, Douglas K, McDonald, Elizabeth S, Mehrotra, Ravi, Michiels, Stefan, Minhas, Fayyaz Ul Amir Afsar, Mittal, Shachi, Moore, David A, Mushtaq, Shamim, Nighat, Hussain, Papathomas, Thomas, Penault-Llorca, Frederique, Perera, Rashindrie D, Pinard, Christopher J, Pinto-Cardenas, Juan Carlos, Pruneri, Giancarlo, Pusztai, Lajos, Rahman, Arman, Rajpoot, Nasir Mahmood, Rapoport, Bernardo Leon, Rau, Tilman T, Reis-Filho, Jorge S, Ribeiro, Joana M, Rimm, David, Salomon, Anne-Vincent, Salto-Tellez, Manuel, Saltz, Joel, Sayed, Shahin, Siziopikou, Kalliopi P, Sotiriou, Christos, Stenzinger, Albrecht, Sughayer, Maher A, Sur, Daniel, Symmans, Fraser, Tanaka, Sunao, Taxter, Timothy, Tejpar, Sabine, Teuwen, Jonas, Thompson, E Aubrey, Tramm, Trine, Tran, William T, van der Laak, Jeroen, van Diest, Paul J, Verghese, Gregory E, Viale, Giuseppe, Vieth, Michael, Wahab, Noorul, Walter, Thomas, Waumans, Yannick, Wen, Hannah Y, Yang, Wentao, Yuan, Yinyin, Adams, Sylvia, Bartlett, John Mark Seaverns, Loibl, Sibylle, Denkert, Carsten, Savas, Peter, Loi, Sherene, Salgado, Roberto, Specht Stovgaard, Elisabeth, Akturk, Guray, and Bouchmaa, Najat

Published
2023

23. Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer:a report of the international immuno-oncology biomarker working group

Author

Thagaard, Jeppe, Broeckx, Glenn, Page, David B., Jahangir, Chowdhury Arif, Verbandt, Sara, Kos, Zuzana, Gupta, Rajarsi, Khiroya, Reena, Abduljabbar, Khalid, Acosta Haab, Gabriela, Acs, Balazs, Akturk, Guray, Almeida, Jonas S., Alvarado-Cabrero, Isabel, Amgad, Mohamed, Azmoudeh-Ardalan, Farid, Badve, Sunil, Baharun, Nurkhairul Bariyah, Balslev, Eva, Bellolio, Enrique R., Bheemaraju, Vydehi, Blenman, Kim R.M., Botinelly Mendonça Fujimoto, Luciana, Bouchmaa, Najat, Burgues, Octavio, Chardas, Alexandros, Chon U Cheang, Maggie, Ciompi, Francesco, Cooper, Lee A.D., Coosemans, An, Corredor, Germán, Dahl, Anders B., Dantas Portela, Flavio Luis, Deman, Frederik, Demaria, Sandra, Doré Hansen, Johan, Dudgeon, Sarah N., Ebstrup, Thomas, Elghazawy, Mahmoud, Fernandez-Martín, Claudio, Fox, Stephen B., Gallagher, William M., Giltnane, Jennifer M., Gnjatic, Sacha, Gonzalez-Ericsson, Paula I., Grigoriadis, Anita, Halama, Niels, Hanna, Matthew G., Harbhajanka, Aparna, Hart, Steven N., Hartman, Johan, Hauberg, Søren, Hewitt, Stephen, Hida, Akira I., Horlings, Hugo M., Husain, Zaheed, Hytopoulos, Evangelos, Irshad, Sheeba, Janssen, Emiel A.M., Kahila, Mohamed, Kataoka, Tatsuki R., Kawaguchi, Kosuke, Kharidehal, Durga, Khramtsov, Andrey I., Kiraz, Umay, Kirtani, Pawan, Kodach, Liudmila L., Korski, Konstanty, Kovács, Anikó, Laenkholm, Anne Vibeke, Lang-Schwarz, Corinna, Larsimont, Denis, Lennerz, Jochen K., Lerousseau, Marvin, Li, Xiaoxian, Ly, Amy, Madabhushi, Anant, Maley, Sai K., Manur Narasimhamurthy, Vidya, Marks, Douglas K., McDonald, Elizabeth S., Mehrotra, Ravi, Michiels, Stefan, Minhas, Fayyaz ul Amir Afsar, Mittal, Shachi, Moore, David A., Mushtaq, Shamim, Nighat, Hussain, Papathomas, Thomas, Penault-Llorca, Frederique, Perera, Rashindrie D., Pinard, Christopher J., Pinto-Cardenas, Juan Carlos, Pruneri, Giancarlo, Pusztai, Lajos, Rahman, Arman, Rajpoot, Nasir Mahmood, Rapoport, Bernardo Leon, Rau, Tilman T., Reis-Filho, Jorge S., Ribeiro, Joana M., Rimm, David, Roslind, Anne, Vincent-Salomon, Anne, Salto-Tellez, Manuel, Saltz, Joel, Sayed, Shahin, Scott, Ely, Siziopikou, Kalliopi P., Sotiriou, Christos, Stenzinger, Albrecht, Sughayer, Maher A., Sur, Daniel, Fineberg, Susan, Symmans, Fraser, Tanaka, Sunao, Taxter, Timothy, Tejpar, Sabine, Teuwen, Jonas, Thompson, E. Aubrey, Tramm, Trine, Tran, William T., van der Laak, Jeroen, van Diest, Paul J., Verghese, Gregory E., Viale, Giuseppe, Vieth, Michael, Wahab, Noorul, Walter, Thomas, Waumans, Yannick, Wen, Hannah Y., Yang, Wentao, Yuan, Yinyin, Zin, Reena Md, Adams, Sylvia, Bartlett, John, Loibl, Sibylle, Denkert, Carsten, Savas, Peter, Loi, Sherene, Salgado, Roberto, Specht Stovgaard, Elisabeth, Thagaard, Jeppe, Broeckx, Glenn, Page, David B., Jahangir, Chowdhury Arif, Verbandt, Sara, Kos, Zuzana, Gupta, Rajarsi, Khiroya, Reena, Abduljabbar, Khalid, Acosta Haab, Gabriela, Acs, Balazs, Akturk, Guray, Almeida, Jonas S., Alvarado-Cabrero, Isabel, Amgad, Mohamed, Azmoudeh-Ardalan, Farid, Badve, Sunil, Baharun, Nurkhairul Bariyah, Balslev, Eva, Bellolio, Enrique R., Bheemaraju, Vydehi, Blenman, Kim R.M., Botinelly Mendonça Fujimoto, Luciana, Bouchmaa, Najat, Burgues, Octavio, Chardas, Alexandros, Chon U Cheang, Maggie, Ciompi, Francesco, Cooper, Lee A.D., Coosemans, An, Corredor, Germán, Dahl, Anders B., Dantas Portela, Flavio Luis, Deman, Frederik, Demaria, Sandra, Doré Hansen, Johan, Dudgeon, Sarah N., Ebstrup, Thomas, Elghazawy, Mahmoud, Fernandez-Martín, Claudio, Fox, Stephen B., Gallagher, William M., Giltnane, Jennifer M., Gnjatic, Sacha, Gonzalez-Ericsson, Paula I., Grigoriadis, Anita, Halama, Niels, Hanna, Matthew G., Harbhajanka, Aparna, Hart, Steven N., Hartman, Johan, Hauberg, Søren, Hewitt, Stephen, Hida, Akira I., Horlings, Hugo M., Husain, Zaheed, Hytopoulos, Evangelos, Irshad, Sheeba, Janssen, Emiel A.M., Kahila, Mohamed, Kataoka, Tatsuki R., Kawaguchi, Kosuke, Kharidehal, Durga, Khramtsov, Andrey I., Kiraz, Umay, Kirtani, Pawan, Kodach, Liudmila L., Korski, Konstanty, Kovács, Anikó, Laenkholm, Anne Vibeke, Lang-Schwarz, Corinna, Larsimont, Denis, Lennerz, Jochen K., Lerousseau, Marvin, Li, Xiaoxian, Ly, Amy, Madabhushi, Anant, Maley, Sai K., Manur Narasimhamurthy, Vidya, Marks, Douglas K., McDonald, Elizabeth S., Mehrotra, Ravi, Michiels, Stefan, Minhas, Fayyaz ul Amir Afsar, Mittal, Shachi, Moore, David A., Mushtaq, Shamim, Nighat, Hussain, Papathomas, Thomas, Penault-Llorca, Frederique, Perera, Rashindrie D., Pinard, Christopher J., Pinto-Cardenas, Juan Carlos, Pruneri, Giancarlo, Pusztai, Lajos, Rahman, Arman, Rajpoot, Nasir Mahmood, Rapoport, Bernardo Leon, Rau, Tilman T., Reis-Filho, Jorge S., Ribeiro, Joana M., Rimm, David, Roslind, Anne, Vincent-Salomon, Anne, Salto-Tellez, Manuel, Saltz, Joel, Sayed, Shahin, Scott, Ely, Siziopikou, Kalliopi P., Sotiriou, Christos, Stenzinger, Albrecht, Sughayer, Maher A., Sur, Daniel, Fineberg, Susan, Symmans, Fraser, Tanaka, Sunao, Taxter, Timothy, Tejpar, Sabine, Teuwen, Jonas, Thompson, E. Aubrey, Tramm, Trine, Tran, William T., van der Laak, Jeroen, van Diest, Paul J., Verghese, Gregory E., Viale, Giuseppe, Vieth, Michael, Wahab, Noorul, Walter, Thomas, Waumans, Yannick, Wen, Hannah Y., Yang, Wentao, Yuan, Yinyin, Zin, Reena Md, Adams, Sylvia, Bartlett, John, Loibl, Sibylle, Denkert, Carsten, Savas, Peter, Loi, Sherene, Salgado, Roberto, and Specht Stovgaard, Elisabeth

Abstract

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer.

Published
2023

25. 1,4-dihydroxy quininib modulates the secretome of uveal melanoma tumour explants and a marker of oxidative phosphorylation in a metastatic xenograft model

Author

Slater, Kayleigh, primary, Bosch, Rosa, additional, Smith, Kaelin Francis, additional, Jahangir, Chowdhury Arif, additional, Garcia-Mulero, Sandra, additional, Rahman, Arman, additional, O’Connell, Fiona, additional, Piulats, Josep M., additional, O’Neill, Valerie, additional, Horgan, Noel, additional, Coupland, Sarah E., additional, O’Sullivan, Jacintha, additional, Gallagher, William M., additional, Villanueva, Alberto, additional, and Kennedy, Breandán N., additional

Published
2023
Full Text
View/download PDF

27. Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell–Cell Interactions That Predict Immunotherapy Response

Author

Antoranz, Asier, primary, Van Herck, Yannick, additional, Bolognesi, Maddalena M., additional, Lynch, Seodhna M., additional, Rahman, Arman, additional, Gallagher, William M., additional, Boecxstaens, Veerle, additional, Marine, Jean-Christophe, additional, Cattoretti, Giorgio, additional, van den Oord, Joost J., additional, De Smet, Frederik, additional, Bechter, Oliver, additional, and Bosisio, Francesca M., additional

Published
2022
Full Text
View/download PDF

28. CD45-positive tumor infiltrating lymphocytes in early-stage hormone-positive, HER2-negative (ER+/HER2-) breast cancer: Correlation with proliferation and prognostic signature scores.

Author

Lucas, Mairi, primary, Kinsella, Zak, additional, Gonzalez, Claudia Aura, additional, Hurley, Camille, additional, Blümel, Anna, additional, Fay, Joanna, additional, O'Grady, Anthony, additional, Murphy, Verena, additional, Jahangir, Chowdhury Arif, additional, Burke, Caoimbhe, additional, Rahman, Arman, additional, Crown, John, additional, Kelly, Catherine Margaret, additional, Gallagher, William M., additional, and O'Connor, Darran, additional

Published
2022
Full Text
View/download PDF

30. Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell-Cell Interactions That Predict Immunotherapy Response

Author

Antoranz, A, Van Herck, Y, Bolognesi, M, Lynch, S, Rahman, A, Gallagher, W, Boecxstaens, V, Marine, J, Cattoretti, G, van den Oord, J, De Smet, F, Bechter, O, Bosisio, F, Antoranz, Asier, Van Herck, Yannick, Bolognesi, Maddalena M, Lynch, Seodhna M, Rahman, Arman, Gallagher, William M, Boecxstaens, Veerle, Marine, Jean-Christophe, Cattoretti, Giorgio, van den Oord, Joost J, De Smet, Frederik, Bechter, Oliver, Bosisio, Francesca M, Antoranz, A, Van Herck, Y, Bolognesi, M, Lynch, S, Rahman, A, Gallagher, W, Boecxstaens, V, Marine, J, Cattoretti, G, van den Oord, J, De Smet, F, Bechter, O, Bosisio, F, Antoranz, Asier, Van Herck, Yannick, Bolognesi, Maddalena M, Lynch, Seodhna M, Rahman, Arman, Gallagher, William M, Boecxstaens, Veerle, Marine, Jean-Christophe, Cattoretti, Giorgio, van den Oord, Joost J, De Smet, Frederik, Bechter, Oliver, and Bosisio, Francesca M

Abstract

While immune checkpoint-based immunotherapy (ICI) shows promising clinical results in patients with cancer, only a subset of patients responds favorably. Response to ICI is dictated by complex networks of cellular interactions between malignant and nonmalignant cells. Although insights into the mechanisms that modulate the pivotal antitumoral activity of cytotoxic T cells (Tcy) have recently been gained, much of what has been learned is based on single-cell analyses of dissociated tumor samples, resulting in a lack of critical information about the spatial distribution of relevant cell types. Here, we used multiplexed IHC to spatially characterize the immune landscape of metastatic melanoma from responders and nonresponders to ICI. Such high-dimensional pathology maps showed that Tcy gradually evolve toward an exhausted phenotype as they approach and infiltrate the tumor. Moreover, a key cellular interaction network functionally linked Tcy and PD-L1+ macrophages. Mapping the respective spatial distributions of these two cell populations predicted response to anti-PD-1 immunotherapy with high confidence. These results suggest that baseline measurements of the spatial context should be integrated in the design of predictive biomarkers to identify patients likely to benefit from ICI. SIGNIFICANCE: This study shows that spatial characterization can address the challenge of finding efficient biomarkers, revealing that localization of macrophages and T cells in melanoma predicts patient response to ICI. See related commentary by Smalley and Smalley, p. 3198.

Published
2022

32. Mapping the immune landscape in metastatic melanoma reveals localized cell-cell interactions correlating to immunotherapy responsiveness

Author

Bosisio, Francesca, primary, Antoranz, Asier, additional, Herck, Yannick Van, additional, Bolognesi, Maddalena, additional, Lynch, Seodhna, additional, Rahman, Arman, additional, Gallagher, William, additional, Boecxstaens, Veerle, additional, Marine, Jean-Christophe, additional, Cattoretti, Giorgio, additional, Oord, Joost van den, additional, De Smet, Frederik, additional, and Bechter, Oliver, additional

Published
2022
Full Text
View/download PDF

33. Prognostic value of the 6-gene OncoMasTR test in hormone receptor–positive HER2-negative early-stage breast cancer: Comparative analysis with standard clinicopathological factors

Author

Lynch, Seodhna M., primary, Russell, Niamh M., additional, Barron, Stephen, additional, Wang, Chan-Ju A., additional, Loughman, Tony, additional, Dynoodt, Peter, additional, Fender, Bozena, additional, Lopez-Ruiz, Cesar, additional, O'Grady, Anthony, additional, Sheehan, Katherine M., additional, Fay, Joanna, additional, Amberger-Murphy, Verena, additional, Saha, Anurati, additional, Klinger, Rut, additional, Gonzalez, Claudia A., additional, Al-Attar, Nebras, additional, Rahman, Arman, additional, O'Leary, Desmond, additional, Lanigan, Fiona T., additional, Bracken, Adrian P., additional, Crown, John, additional, Kelly, Catherine M., additional, O'Connor, Darran P., additional, and Gallagher, William M., additional

Published
2021
Full Text
View/download PDF

34. Future of biomarker evaluation in the realm of artificial intelligence algorithms: application in improved therapeutic stratification of patients with breast and prostate cancer

Author

Fitzgerald, Jenny, primary, Higgins, Debra, additional, Mazo Vargas, Claudia, additional, Watson, William, additional, Mooney, Catherine, additional, Rahman, Arman, additional, Aspell, Niamh, additional, Connolly, Amy, additional, Aura Gonzalez, Claudia, additional, and Gallagher, William, additional

Published
2021
Full Text
View/download PDF

36. A conjugated linoleic acid-enriched beef diet attenuates lipopolysaccharide-induced inflammation in mice in part through PPAR[gamma], -mediated suppression of toll-like receptor 4

Author

Reynolds, Clare M., Draper, Eve, Keogh, Brian, Rahman, Arman, Moloney, Aidan P., Mills, Kingston H.G., Loscher, Christine E., and Roche, Helen M.

Subjects
Beef -- Nutritional aspects, Linoleic acids -- Health aspects, Lipopolysaccharides -- Health aspects, Inflammation, Food/cooking/nutrition
Abstract

Conjugated linoleic acid (CLA) is a PUFA found in beef and dairy products that has immunoregulatory properties. The level of CLA in beef can be enhanced by feeding cattle fresh grass rather than concentrates. This study determined the effect of feeding a high-CLA beef diet on inflammation in an in vivo model of septic shock. Mice were fed a high-CLA beef (4.3% total fatty acid composition) or low-CLA beef diet (0.84% total fatty acid composition) for 6 wk. Lipopolysaccharide (LPS; 3 [micro]g) or sterile PBS was injected i.v. and serum was harvested 6 h after injection. Serum interleukin (IL)-1[beta], IL-12p70, IL-2p40, and interferon-[gamma] concentrations were significantly reduced in response to the LPS challenge in the high-CLA beef diet group. Bone marrow-derived dendritic cells (BMDC) from the high-CLA beef diet group had significantly less IL-12 and more I L-10 in response to ex vivo LPS stimulation. Furthermore, toll-like receptor 4 (TLR4) and CD14 protein and mRNA expression on BMDC was significantly attenuated in the high-CLA compared with the low-CLA beef diet group. Complimentary in vitro experiments to determine the specificity of the effect showed that synthetic cis9, trans11-CLA suppressed surface expression of CD14 and TLR4 on BMDC. Treatment with the PPAR[gamma] inhibitor GW9662 partially reversed TLR4 expression in immature BMDC. The results of this study demonstrate that feeding a diet enriched in high-beef CLA exerts profound antiinflammatory effects in vivo within the context of LPS-induced sepsis. In addition, downregulation of BMDC TLR4 is mediated through induction of PPAR[gamma]. J. Nutr. 139: 2351-2357, 2009. Manuscript received July 15, 2009. Initial review completed August 9, 2009. Revision accepted October 8, 2009. First published online October 21, 2009; doi: 10.3945/jn.109.113035.

Published
2009

37. High Cysteinyl Leukotriene Receptor 1 Expression Correlates with Poor Survival of Uveal Melanoma Patients and Cognate Antagonist Drugs Modulate the Growth, Cancer Secretome, and Metabolism of Uveal Melanoma Cells

Author

Slater, Kayleigh, Heeran, Aisling B., Garcia-Mulero, Sandra, Kalirai, Helen, Sanz-Pamplona, Rebeca, Rahman, Arman, Al-Attar, Nebras, Helmi, Mays, OConnell, Fiona, Bosch, Rosa, Portela, Anna, Villanueva, Alberto, Gallagher, William M., Jensen, Lasse, Piulats, Josep M., Coupland, Sarah E., OSullivan, Jacintha, Kennedy, Breandan N., Slater, Kayleigh, Heeran, Aisling B., Garcia-Mulero, Sandra, Kalirai, Helen, Sanz-Pamplona, Rebeca, Rahman, Arman, Al-Attar, Nebras, Helmi, Mays, OConnell, Fiona, Bosch, Rosa, Portela, Anna, Villanueva, Alberto, Gallagher, William M., Jensen, Lasse, Piulats, Josep M., Coupland, Sarah E., OSullivan, Jacintha, and Kennedy, Breandan N.

Abstract

Simple Summary This research investigates the disease relevance and therapeutic potential of cysteinyl leukotriene receptors in uveal melanoma (UM), a rare eye cancer that often spreads to the liver. Unfortunately, there are no therapies available to stop the spread of UM and patients are often faced with an extremely poor prognosis. We assess whether the cysteinyl leukotriene receptors (CysLT(1) and CysLT(2)) are relevant to the progression of UM. Using UM patient samples, we identified that increased levels of CysLT(1) in tumours is associated with reduced patient survival. Using UM cell lines and zebrafish models, we found that drugs targeting CysLT(1), but not CysLT(2), can alter hallmarks of cancer including cell growth, proliferation, and metabolism. This study is the first to examine the relationship of the CysLT receptors with clinical features of UM. Our data strengthen the importance of CysLT signalling in UM and suggest that antagonism of CysLT(1) may be of therapeutic interest in the disease. Metastatic uveal melanoma (UM) is a rare, but often lethal, form of ocular cancer arising from melanocytes within the uveal tract. UM has a high propensity to spread hematogenously to the liver, with up to 50% of patients developing liver metastases. Unfortunately, once liver metastasis occurs, patient prognosis is extremely poor with as few as 8% of patients surviving beyond two years. There are no standard-of-care therapies available for the treatment of metastatic UM, hence it is a clinical area of urgent unmet need. Here, the clinical relevance and therapeutic potential of cysteinyl leukotriene receptors (CysLT(1) and CysLT(2)) in UM was evaluated. High expression of CYSLTR1 or CYSLTR2 transcripts is significantly associated with poor disease-free survival and poor overall survival in UM patients. Digital pathology analysis identified that high expression of CysLT(1) in primary UM is associated with reduced disease-specific survival (p = 0.012; HR 2.76; 95% CI 1, Funding Agencies|Irish Research CouncilIrish Research Council for Science, Engineering and Technology [EBP/2017/473]; British Pharmacological Society; Breakthrough Cancer Research; European UnionEuropean Union (EU) [734907]; Science Foundation IrelandScience Foundation Ireland [15/IA/3104, 18/SPP/3522]

Published
2020
Full Text
View/download PDF

38. Feature fusion of Raman chemical imaging and digital histopathology using machine learning for prostate cancer detection

Author

Doherty, Trevor, primary, McKeever, Susan, additional, Al-Attar, Nebras, additional, Murphy, Tiarnán, additional, Aura, Claudia, additional, Rahman, Arman, additional, O'Neill, Amanda, additional, Finn, Stephen P., additional, Kay, Elaine, additional, Gallagher, William M., additional, Watson, R. William G., additional, Gowen, Aoife, additional, and Jackman, Patrick, additional

Published
2021
Full Text
View/download PDF

39. High Cysteinyl Leukotriene Receptor 1 Expression Correlates with Poor Survival of Uveal Melanoma Patients and Cognate Antagonist Drugs Modulate the Growth, Cancer Secretome, and Metabolism of Uveal Melanoma Cells

Author

Slater, Kayleigh, primary, Heeran, Aisling B., additional, Garcia-Mulero, Sandra, additional, Kalirai, Helen, additional, Sanz-Pamplona, Rebeca, additional, Rahman, Arman, additional, Al-Attar, Nebras, additional, Helmi, Mays, additional, O’Connell, Fiona, additional, Bosch, Rosa, additional, Portela, Anna, additional, Villanueva, Alberto, additional, Gallagher, William M., additional, Jensen, Lasse D., additional, Piulats, Josep M., additional, Coupland, Sarah E., additional, O’Sullivan, Jacintha, additional, and Kennedy, Breandán N., additional

Published
2020
Full Text
View/download PDF

41. Triple Combination of Ascorbate, Menadione and the Inhibition of Peroxiredoxin-1 Produces Synergistic Cytotoxic Effects in Triple-Negative Breast Cancer Cells

Author

Bajor, Malgorzata, primary, Graczyk-Jarzynka, Agnieszka, additional, Marhelava, Katsiaryna, additional, Kurkowiak, Malgorzata, additional, Rahman, Arman, additional, Aura, Claudia, additional, Russell, Niamh, additional, Zych, Agata O., additional, Firczuk, Malgorzata, additional, Winiarska, Magdalena, additional, Gallagher, William M., additional, and Zagozdzon, Radoslaw, additional

Published
2020
Full Text
View/download PDF

42. A Machine Learning Platform to Optimize the Translation of Personalized Network Models to the Clinic

Author

Salvucci, Manuela, primary, Rahman, Arman, additional, Resler, Alexa J., additional, Udupi, Girish M., additional, McNamara, Deborah A., additional, Kay, Elaine W., additional, Laurent-Puig, Pierre, additional, Longley, Daniel B., additional, Johnston, Patrick G., additional, Lawler, Mark, additional, Wilson, Richard, additional, Salto-Tellez, Manuel, additional, Van Schaeybroeck, Sandra, additional, Rafferty, Mairin, additional, Gallagher, William M., additional, Rehm, Markus, additional, and Prehn, Jochen H.M., additional

Published
2019
Full Text
View/download PDF

44. Mantra lintrik: ilmu pengasihan Jawa di Desa Gading Kecamatan Jatirejo Kabupaten Mojokerto / Arman Abdul Rahman

Author

Rahman, Arman Abdul and Rahman, Arman Abdul

Abstract

ABSTRAK Rahman Arman Abdul. 2019. Mantra Lintrik Ilmu Pengasihan Jawa di Desa Gading Kecamatan Jatirejo Kabupaten Mojokerto. Skripsi Jurusan Sosiologi Program Studi Pendidikan Sosiologi Universitas Negeri Malang. Pembimbing Drs. Nur Hadi M.Si M.Pd. Kata Kunci mantra lintrik dukun Mantra oleh masyarakat juga dikenal sebagai rapalan atau pengucapan dengan tujuan dan maksud tertentu yang bersifat magis salah satu mantra yang terkenal di masyarakat jawa adalah mantra pengasihan ilmu lintrik yang sampai sekarang masih banyak yang menggunakan mantra tersebut. Masyarakat Desa Gading merupakan contoh yang masih mempercayai tentang adanya mantra pengasihan ilmu lintrik terbukti masih banyak diperbolehkannya praktik perdukunan lintrik tersebut. Rumusan masalah dalam penelitian ini adalah (1) Bagaimana kepercayaan masyarakat terhadap mantra pengasihan ilmu lintrik (2) Mengapa masyarakat masih menggunakan mantra pengasihan ilmu lintrik Metode yang digunakan dalam penelitian ini adalah kualitatif dengan jenis penelitian deskriptif. Lokasi penelitian dipilih pada Desa Gading Kecamatan Jatirejo Kabupaten Mojokerto. Teknik pengumpulan data menggunakan cara observasi wawancara mendalam serta dokumentasi. Data yang didapat kemudian dianalisis dan disajikan. Hasil dari penelitian didapatkan bahwa (1) masyarakat desa Gading masih banyak yang percaya terhadap mantra pengasihan ilmu lintrik terbukti dengan adanya praktik perdukunan lintrik didesa tersebut. (2) Terdapat berbagai permasalahan yang timbul didalam masyarakat yang tidak dapat diselesaikan dengan akal sehat maka jalan satu-satunya adalah meminta bantuan dukun dalam penelitian ditemukan masih banyaknya orang yang memakai jasa dukun lintrik dengan menanggung berbagai macam permasalahan.

Published
2019

46. Additional prognostic value of OncoMasTR multigene prognostic signature to clinicopathological information in patients with HR-positive, HER2-negative, lymph node-negative breast cancer from the TAILORx Tissue Bank, Ireland.

Author

O'Connor, Darran, primary, Kelly, Catherine Margaret, additional, Crown, John, additional, Russell, Niamh, additional, Barron, Stephen, additional, Loughman, Tony, additional, Lynch, Seodhna, additional, O'Grady, Anthony, additional, Sheehan, Katherine M, additional, Fay, Joanna, additional, Saha, Anurati, additional, Dynoodt, Peter, additional, Fender, Bozena, additional, Wang, Chan-Ju Angel, additional, O'Leary, Desmond, additional, Bracken, Adrian P., additional, Rahman, Arman, additional, Gonzalez, Claudia Aura, additional, Attar, Nebras Al, additional, and Gallagher, William M., additional

Published
2019
Full Text
View/download PDF

49. Apelin: A putative novel predictive biomarker for bevacizumab response in colorectal cancer

Author

Zuurbier, Linda, Rahman, Arman, Cordes, Martijn, Scheick, Jennifer, Wong, Tse J., Rustenburg, François, Joseph, Jesu Christopher, Dynoodt, Peter, Casey, Rory, Drillenburg, Paul, Gerhards, Michael F., Barat, Ana, Klinger, Rut, Fender, Bozena, O'Connor, Darran P., Betge, Johannes, Ebert, Matthias P, Gaiser, Timo, Prehn, Jochen H M, Griffioen, Arjan W., van Grieken, Nicole C.T., Ylstra, Bauke, Byrne, Annette T, van der Flier, Laurens G., Gallagher, William M., Postel, Ruben, VU University medical center, Pathology, Medical oncology laboratory, CCA - Imaging and biomarkers, and AGEM - Re-generation and cancer of the digestive system

Subjects
0301 basic medicine, Oncology, Gerontology, Male, Vascular Endothelial Growth Factor A, Colorectal cancer, VEGF receptors, 0302 clinical medicine, Antineoplastic Agents, Immunological, Antineoplastic Combined Chemotherapy Protocols, University medical, Intestinal Mucosa, Aged, 80 and over, biology, Middle Aged, University hospital, Prognosis, VEGF, 3. Good health, Apelin, Bevacizumab, Gene Expression Regulation, Neoplastic, Treatment Outcome, apelin, 030220 oncology & carcinogenesis, Biomarker (medicine), biomarker, Female, Colorectal Neoplasms, medicine.drug, Signal Transduction, Research Paper, Adult, medicine.medical_specialty, colorectal cancer, 03 medical and health sciences, Internal medicine, medicine, Biomarkers, Tumor, Humans, Predictive biomarker, Aged, Neoplasm Staging, business.industry, Gene Expression Profiling, bevacizumab response, medicine.disease, Survival Analysis, 030104 developmental biology, biology.protein, business
Abstract

// Linda Zuurbier 1, * , Arman Rahman 2, * , Martijn Cordes 3 , Jennifer Scheick 4 , Tse J. Wong 4 , Francois Rustenburg 3 , Jesu Christopher Joseph 2 , Peter Dynoodt 2 , Rory Casey 2 , Paul Drillenburg 5 , Michael Gerhards 5 , Ana Barat 6 , Rut Klinger 7 , Bozena Fender 2 , Darran P. O’Connor 8 , Johannes Betge 9 , Matthias P. Ebert 9 , Timo Gaiser 10 , Jochen H.M. Prehn 6 , Arjan W. Griffioen 4 , Nicole C. T. van Grieken 3 , Bauke Ylstra 3 , Annette T. Byrne 6 , Laurens G. van der Flier 1 , William M. Gallagher 2, 7, * and Ruben Postel 1, * 1 SomantiX BV, Utrecht, The Netherlands 2 OncoMark Ltd, Dublin, Ireland 3 Department of Pathology, VU University Medical Center, Amsterdam, The Netherlands 4 Department of Medical Oncology, Angiogenesis Laboratory, VU University Medical Center, Amsterdam, The Netherlands 5 Department of Pathology, Onze Lieve Vrouwe Gasthuis, Amsterdam, The Netherlands 6 Department of Physiology & Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland 7 UCD School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Dublin, Ireland 8 Department of Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin, Ireland 9 Department of Medicine II, University Hospital Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany 10 Institute of Pathology, University Hospital Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany * These authors have contributed equally to this work Correspondence to: Ruben Postel, email: postel@somantix.com William M. Gallagher, email: william.gallagher@ucd.ie Keywords: apelin, biomarker, bevacizumab response, VEGF, colorectal cancer Received: November 08, 2016 Accepted: April 04, 2017 Published: April 21, 2017 ABSTRACT Bevacizumab (bvz) is currently employed as an anti-angiogenic therapy across several cancer indications. Bvz response heterogeneity has been well documented, with only 10-15% of colorectal cancer (CRC) patients benefitting in general. For other patients, clinical efficacy is limited and side effects are significant. This reinforces the need for a robust predictive biomarker of response. To identify such a biomarker, we performed a DNA microarray-based transcriptional profiling screen with primary endothelial cells (ECs) isolated from normal and tumour colon tissues. Thirteen separate populations of tumour-associated ECs and 10 of normal ECs were isolated using fluorescence-activated cell sorting. We hypothesised that VEGF-induced genes were overexpressed in tumour ECs; these genes could relate to bvz response and serve as potential predictive biomarkers. Transcriptional profiling revealed a total of 2,610 differentially expressed genes when tumour and normal ECs were compared. To explore their relation to bvz response, the mRNA expression levels of top-ranked genes were examined using quantitative PCR in 30 independent tumour tissues from CRC patients that received bvz in the adjuvant setting. These analyses revealed that the expression of MMP12 and APLN mRNA was significantly higher in bvz non-responders compared to responders. At the protein level, high APLN expression was correlated with poor progression-free survival in bvz-treated patients. Thus, high APLN expression may represent a novel predictive biomarker for bvz unresponsiveness.

Published
2017
Full Text
View/download PDF

50. STUDENTS' DIFFICULTIES IN WRITTEN EXPRESSION IN THE DEPARTMENTS OF ENGLISH AND ARABIC AT AL-QUDS UNIVERSITY

Author

Ibrahim Moh'd Abdel-rahman Arman, Inas Aref Saleh Naser, and Jamal Subhi Ismail Nafi'

Subjects
education, students' difficulties, Al-Quds University, written expression, humanities, departments of English and Arabic
Abstract

This study aims to identify the nature of students’ difficulties in written expression in the Departments of English and Arabic at Al-Quds University. It also aims to identify the impact of each of the variables gender, level, department and achievement on the degree of students’ writing difficulties in both departments. To achieve the objective of the study, a questionnaire was designed comprising 32 items applied to the study sample which consisted of 128 students from the Departments of Arabic and English at Al-Quds University in Palestine. The results of the study showed that students’ difficulties in written expression were fain in degree; they also revealed statistically significant differences in the averages of students’ difficulties in written expression due to gender in favor of females, and the presence of statistically significant differences in the averages of the difficulties in written expression due to level, and in favor of third and fourth year students; there were also statistically significant differences in the averages due to department and in favor of the Department of Arabic. The results of the study showed that there were no statistically significant differences in the averages of the difficulties of written expression due to level of achievement. Based on the results of the study, the researchers recommended the need to hold language activities in class, such as reading and writing articles and short stories, which overuse words and vocabulary that may help to develop students’ written expression, and there is a need to instate a course for written expression on the graduation plans of the above-mentioned departments, and the importance of taking into account students' tendencies when choosing topics that include written expression.

Published
2016
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results