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498 results on '"Almeida, Jonas S."'

1. Crown-Like Structures in Breast Adipose Tissue: Finding a 'Needle-in-a-Haystack' using Artificial Intelligence and Collaborative Active Learning on the Web

Author

Bhawsar, Praphulla MS, Ramin, Cody, Lenz, Petra, Duggan, Máire A, Harris, Alexandra R, Jenkins, Brittany, Cora, Renata, Abubakar, Mustapha, Gierach, Gretchen, Saltz, Joel, and Almeida, Jonas S

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Crown-like structures (CLS) in breast adipose tissue are formed as a result of macrophages clustering around necrotic adipocytes in specific patterns. As a histologic marker of local inflammation, CLS could have potential diagnostic utility as a biomarker for breast cancer risk. However, given the scale of whole slide images and the rarity of CLS (a few cells in an entire tissue sample), microscope-based manual identification is a challenge for the pathologist. In this report, we describe an artificial intelligence pipeline to solve this needle-in-a-haystack problem. We developed a zero-cost, zero-footprint web platform to enable remote operation on digital whole slide imaging data directly in the web browser, supporting collaborative annotation of the data by multiple experts. The annotated images then allow for incremental training and fine tuning of deep neural networks via active learning. The platform is reusable and requires no backend or installations, thus ensuring the data remains secure and private under the governance of the end user. Using this platform, we iteratively trained a CLS identification model, evaluating the performance after each round and adding examples to the training data to overcome failure cases. The resulting model, with an AUC of 0.90, shows promise as a first-pass screening tool to detect CLS in breast adipose tissue, considerably reducing the workload of the pathologist. Platform available at: https://episphere.github.io/path

Published
2024

2. TMA-Grid: An open-source, zero-footprint web application for FAIR Tissue MicroArray De-arraying

Author

Ge, Aaron, Saha, Monjoy, Duggan, Maire A., Lenz, Petra, Abubakar, Mustapha, García-Closas, Montserrat, Balasubramanian, Jeya, Almeida, Jonas S., and Bhawsar, Praphulla MS

Subjects
Quantitative Biology - Tissues and Organs, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

Background: Tissue Microarrays (TMAs) significantly increase analytical efficiency in histopathology and large-scale epidemiologic studies by allowing multiple tissue cores to be scanned on a single slide. The individual cores can be digitally extracted and then linked to metadata for analysis in a process known as de-arraying. However, TMAs often contain core misalignments and artifacts due to assembly errors, which can adversely affect the reliability of the extracted cores during the de-arraying process. Moreover, conventional approaches for TMA de-arraying rely on desktop solutions.Therefore, a robust yet flexible de-arraying method is crucial to account for these inaccuracies and ensure effective downstream analyses. Results: We developed TMA-Grid, an in-browser, zero-footprint, interactive web application for TMA de-arraying. This web application integrates a convolutional neural network for precise tissue segmentation and a grid estimation algorithm to match each identified core to its expected location. The application emphasizes interactivity, allowing users to easily adjust segmentation and gridding results. Operating entirely in the web-browser, TMA-Grid eliminates the need for downloads or installations and ensures data privacy. Adhering to FAIR principles (Findable, Accessible, Interoperable, and Reusable), the application and its components are designed for seamless integration into TMA research workflows. Conclusions: TMA-Grid provides a robust, user-friendly solution for TMA dearraying on the web. As an open, freely accessible platform, it lays the foundation for collaborative analyses of TMAs and similar histopathology imaging data. Availability: Web application: https://episphere.github.io/tma-grid Code: https://github.com/episphere/tma-grid Tutorial: https://youtu.be/miajqyw4BVk, Comment: NA

Published
2024

3. FastImpute: A Baseline for Open-source, Reference-Free Genotype Imputation Methods -- A Case Study in PRS313

Author

Ge, Aaron, Balasubramanian, Jeya, Wu, Xueyao, Kraft, Peter, and Almeida, Jonas S.

Subjects
Quantitative Biology - Genomics, Computer Science - Artificial Intelligence
Abstract

Genotype imputation enhances genetic data by predicting missing SNPs using reference haplotype information. Traditional methods leverage linkage disequilibrium (LD) to infer untyped SNP genotypes, relying on the similarity of LD structures between genotyped target sets and fully sequenced reference panels. Recently, reference-free deep learning-based methods have emerged, offering a promising alternative by predicting missing genotypes without external databases, thereby enhancing privacy and accessibility. However, these methods often produce models with tens of millions of parameters, leading to challenges such as the need for substantial computational resources to train and inefficiency for client-sided deployment. Our study addresses these limitations by introducing a baseline for a novel genotype imputation pipeline that supports client-sided imputation models generalizable across any genotyping chip and genomic region. This approach enhances patient privacy by performing imputation directly on edge devices. As a case study, we focus on PRS313, a polygenic risk score comprising 313 SNPs used for breast cancer risk prediction. Utilizing consumer genetic panels such as 23andMe, our model democratizes access to personalized genetic insights by allowing 23andMe users to obtain their PRS313 score. We demonstrate that simple linear regression can significantly improve the accuracy of PRS313 scores when calculated using SNPs imputed from consumer gene panels, such as 23andMe. Our linear regression model achieved an R^2 of 0.86, compared to 0.33 without imputation and 0.28 with simple imputation (substituting missing SNPs with the minor allele frequency). These findings suggest that popular SNP analysis libraries could benefit from integrating linear regression models for genotype imputation, providing a viable and light-weight alternative to reference based imputation., Comment: This paper is 16 pages long and contains 7 figures. For more information and to access related resources: * Web application: https://aaronge-2020.github.io/DeepImpute/ * Code repository: https://github.com/aaronge-2020/DeepImpute

Published
2024

4. ClusterRadar: an Interactive Web-Tool for the Multi-Method Exploration of Spatial Clusters Over Time

Author

Mason, Lee, Hicks, Blánaid, and Almeida, Jonas S.

Subjects
Computer Science - Human-Computer Interaction
Abstract

Spatial cluster analysis, the detection of localized patterns of similarity in geospatial data, has a wide-range of applications for scientific discovery and practical decision making. One way to detect spatial clusters is by using local indicators of spatial association, such as Local Moran's I or Getis-Ord Gi*. However, different indicators tend to produce substantially different results due to their distinct operational characteristics. Choosing a suitable method or comparing results from multiple methods is a complex task. Furthermore, spatial clusters are dynamic and it is often useful to track their evolution over time, which adds an additional layer of complexity. ClusterRadar is a web-tool designed to address these analytical challenges. The tool allows users to easily perform spatial clustering and analyze the results in an interactive environment, uniquely prioritizing temporal analysis and the comparison of multiple methods. The tool's interactive dashboard presents several visualizations, each offering a distinct perspective of the temporal and methodological aspects of the spatial clustering results. ClusterRadar has several features designed to maximize its utility to a broad user-base, including support for various geospatial formats, and a fully in-browser execution environment to preserve the privacy of sensitive data. Feedback from a varied set of researchers suggests ClusterRadar's potential for enhancing the temporal analysis of spatial clusters., Comment: Submitted to IEEE Vis 2024

Published
2024

5. Finding Regions of Interest in Whole Slide Images Using Multiple Instance Learning

Author

Afonso, Martim, Bhawsar, Praphulla M. S., Saha, Monjoy, Almeida, Jonas S., and Oliveira, Arlindo L.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Whole Slide Images (WSI), obtained by high-resolution digital scanning of microscope slides at multiple scales, are the cornerstone of modern Digital Pathology. However, they represent a particular challenge to AI-based/AI-mediated analysis because pathology labeling is typically done at slide-level, instead of tile-level. It is not just that medical diagnostics is recorded at the specimen level, the detection of oncogene mutation is also experimentally obtained, and recorded by initiatives like The Cancer Genome Atlas (TCGA), at the slide level. This configures a dual challenge: a) accurately predicting the overall cancer phenotype and b) finding out what cellular morphologies are associated with it at the tile level. To address these challenges, a weakly supervised Multiple Instance Learning (MIL) approach was explored for two prevalent cancer types, Invasive Breast Carcinoma (TCGA-BRCA) and Lung Squamous Cell Carcinoma (TCGA-LUSC). This approach was explored for tumor detection at low magnification levels and TP53 mutations at various levels. Our results show that a novel additive implementation of MIL matched the performance of reference implementation (AUC 0.96), and was only slightly outperformed by Attention MIL (AUC 0.97). More interestingly from the perspective of the molecular pathologist, these different AI architectures identify distinct sensitivities to morphological features (through the detection of Regions of Interest, RoI) at different amplification levels. Tellingly, TP53 mutation was most sensitive to features at the higher applications where cellular morphology is resolved.

Published
2024

6. Wasm-iCARE: a portable and privacy-preserving web module to build, validate, and apply absolute risk models

Author

Balasubramanian, Jeya Balaji, Choudhury, Parichoy Pal, Mukhopadhyay, Srijon, Ahearn, Thomas, Chatterjee, Nilanjan, García-Closas, Montserrat, and Almeida, Jonas S.

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Objective: Absolute risk models estimate an individual's future disease risk over a specified time interval. Applications utilizing server-side risk tooling, such as the R-based iCARE (R-iCARE), to build, validate, and apply absolute risk models, face serious limitations in portability and privacy due to their need for circulating user data in remote servers for operation. Our objective was to overcome these limitations. Materials and Methods: We refactored R-iCARE into a Python package (Py-iCARE) then compiled it to WebAssembly (Wasm-iCARE): a portable web module, which operates entirely within the privacy of the user's device. Results: We showcase the portability and privacy of Wasm-iCARE through two applications: for researchers to statistically validate risk models, and to deliver them to end-users. Both applications run entirely on the client-side, requiring no downloads or installations, and keeps user data on-device during risk calculation. Conclusions: Wasm-iCARE fosters accessible and privacy-preserving risk tools, accelerating their validation and delivery., Comment: 10 pages, 2 figures

Published
2023

7. mSigSDK -- private, at scale, computation of mutation signatures

Author

Ge, Aaron, Martins, Yasmmin Côrtes, Zhang, Tongwu, Chen, Kailing, Landi, Maria Teresa, Park, Brian, Balasubramanian, Jeya, and Almeida, Jonas S

Subjects
Quantitative Biology - Genomics
Abstract

In our previous work, we demonstrated that it is feasible to perform analysis on mutation signature data without the need for downloads or installations and analyze individual patient data at scale without compromising privacy. Building on this foundation, we developed a Software Development Kit (SDK) called mSigSDK to facilitate the orchestration of distributed data processing workflows and graphic visualization of mutational signature analysis results. We strictly adhered to modern web computing standards, particularly the modularization standards set by the ECMAScript ES6 framework (JavaScript modules). Our approach allows for computation to be entirely performed by secure delegation to the computational resources of the user's own machine (in-browser), without any downloads or installations. The mSigSDK was developed primarily as a companion library to the mSig Portal resource of the National Cancer Institute Division of Cancer Epidemiology and Genetics (NIH/NCI/DCEG), with a focus on its FAIR extensibility as components of other researchers' computational constructs. Anticipated extensions include the programmatic operation of other mutation signature API ecosystems such as SIGNAL and COSMIC, advancing towards a data commons for mutational signature research (Grossman et al., 2016).

Published
2023

8. ImageBox3: No-Server Tile Serving to Traverse Whole Slide Images on the Web

Author

Bhawsar, Praphulla MS, Bremer, Erich, Duggan, Máire A, Chanock, Stephen, Garcia-Closas, Montserrat, Saltz, Joel, and Almeida, Jonas S

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

Whole slide imaging (WSI) has become the primary modality for digital pathology data. However, due to the size and high-resolution nature of these images, they are generally only accessed in smaller sections or tiles via specialized platforms, most of which require extensive setup and/or costly infrastructure. These platforms typically also need a copy of the images to be locally available to them, potentially causing issues with data governance and provenance. To address these concerns, we developed ImageBox3, an in-browser tiling mechanism to enable zero-footprint traversal of remote WSI data. All computation is performed client-side without compromising user governance, operating public and private images alike as long as the storage service supports HTTP range requests (standard in Cloud storage and most web servers). ImageBox3 thus removes significant hurdles to WSI operation and effective collaboration, allowing for the sort of democratized analytical tools needed to establish participative, FAIR digital pathology data commons. Availability: code - https://github.com/episphere/imagebox3; fig1 (live) - https://episphere.github.io/imagebox3/demo/scriptTag ; fig2 (live) - https://episphere.github.io/imagebox3/demo/serviceWorker ; fig 3 (live) - https://observablehq.com/@prafulb/imagebox3-in-observable ., Comment: 9 pages, 3 figures

Published
2022

9. Moving towards FAIR practices in epidemiological research

Author

Garcia-Closas, Montserrat, Ahearn, Thomas U., Gaudet, Mia M., Hurson, Amber N., Balasubramanian, Jeya Balaji, Choudhury, Parichoy Pal, Gerlanc, Nicole M., Patel, Bhaumik, Russ, Daniel, Abubakar, Mustapha, Freedman, Neal D., Wong, Wendy S. W., Chanock, Stephen J., de Gonzalez, Amy Berrington, and Almeida, Jonas S

Subjects
Quantitative Biology - Populations and Evolution
Abstract

Reproducibility and replicability of research findings are central to the scientific integrity of epidemiology. In addition, many research questions require combiningdata from multiple sources to achieve adequate statistical power. However, barriers related to confidentiality, costs, and incentives often limit the extent and speed of sharing resources, both data and code. Epidemiological practices that follow FAIR principles can address these barriers by making resources (F)indable with the necessary metadata , (A)ccessible to authorized users and (I)nteroperable with other data, to optimize the (R)e-use of resources with appropriate credit to its creators. We provide an overview of these principles and describe approaches for implementation in epidemiology. Increasing degrees of FAIRness can be achieved by moving data and code from on-site locations to the Cloud, using machine-readable and non-proprietary files, and developing open-source code. Adoption of these practices will improve daily work and collaborative analyses, and facilitate compliance with data sharing policies from funders and scientific journals. Achieving a high degree of FAIRness will require funding, training, organizational support, recognition, and incentives for sharing resources. But these costs are amply outweighed by the benefits of making research more reproducible, impactful, and equitable by facilitating the re-use of precious research resources by the scientific community.

Published
2022

12. Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor Infiltrating Lymphocytes in Invasive Breast Cancer

Author

Le, Han, Gupta, Rajarsi, Hou, Le, Abousamra, Shahira, Fassler, Danielle, Kurc, Tahsin, Samaras, Dimitris, Batiste, Rebecca, Zhao, Tianhao, Rao, Arvind, Van Dyke, Alison L., Sharma, Ashish, Bremer, Erich, Almeida, Jonas S., and Saltz, Joel

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

Quantitative assessment of Tumor-TIL spatial relationships is increasingly important in both basic science and clinical aspects of breast cancer research. We have developed and evaluated convolutional neural network (CNN) analysis pipelines to generate combined maps of cancer regions and tumor infiltrating lymphocytes (TILs) in routine diagnostic breast cancer whole slide tissue images (WSIs). We produce interactive whole slide maps that provide 1) insight about the structural patterns and spatial distribution of lymphocytic infiltrates and 2) facilitate improved quantification of TILs. We evaluated both tumor and TIL analyses using three CNN networks - Resnet-34, VGG16 and Inception v4, and demonstrated that the results compared favorably to those obtained by what believe are the best published methods. We have produced open-source tools and generated a public dataset consisting of tumor/TIL maps for 1,015 TCGA breast cancer images. We also present a customized web-based interface that enables easy visualization and interactive exploration of high-resolution combined Tumor-TIL maps for 1,015TCGA invasive breast cancer cases that can be downloaded for further downstream analyses., Comment: The American Journal of Pathology

Published
2019

13. Genomic and evolutionary classification of lung cancer in never smokers

Author

Zhang, Tongwu, Joubert, Philippe, Ansari-Pour, Naser, Zhao, Wei, Hoang, Phuc H., Lokanga, Rachel, Moye, Aaron L., Rosenbaum, Jennifer, Gonzalez-Perez, Abel, Martínez-Jiménez, Francisco, Castro, Andrea, Muscarella, Lucia Anna, Hofman, Paul, Consonni, Dario, Pesatori, Angela C., Kebede, Michael, Li, Mengying, Gould Rothberg, Bonnie E., Peneva, Iliana, Schabath, Matthew B., Poeta, Maria Luana, Costantini, Manuela, Hirsch, Daniela, Heselmeyer-Haddad, Kerstin, Hutchinson, Amy, Olanich, Mary, Lawrence, Scott M., Lenz, Petra, Duggan, Maire, Bhawsar, Praphulla M. S., Sang, Jian, Kim, Jung, Mendoza, Laura, Saini, Natalie, Klimczak, Leszek J., Islam, S. M. Ashiqul, Otlu, Burcak, Khandekar, Azhar, Cole, Nathan, Stewart, Douglas R., Choi, Jiyeon, Brown, Kevin M., Caporaso, Neil E., Wilson, Samuel H., Pommier, Yves, Lan, Qing, Rothman, Nathaniel, Almeida, Jonas S., Carter, Hannah, Ried, Thomas, Kim, Carla F., Lopez-Bigas, Nuria, Garcia-Closas, Montserrat, Shi, Jianxin, Bossé, Yohan, Zhu, Bin, Gordenin, Dmitry A., Alexandrov, Ludmil B., Chanock, Stephen J., Wedge, David C., and Landi, Maria Teresa

Published
2021
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14. 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

15. 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

18. 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
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20. Actigraphy-derived measures of sleep and risk of prostate cancer in the UK Biobank.

Author

Freeman, Joshua R, Saint-Maurice, Pedro F, Watts, Eleanor L, Moore, Steven C, Shams-White, Marissa M, Wolff-Hughes, Dana L, Russ, Daniel E, Almeida, Jonas S, Caporaso, Neil E, Hong, Hyokyoung G, Loftfield, Erikka, and Matthews, Charles E

Subjects
SLEEP duration, PROSTATE cancer, DISEASE risk factors, SLEEP quality, PROPORTIONAL hazards models
Abstract

Background Studies of sleep and prostate cancer are almost entirely based on self-report, with limited research using actigraphy. Our goal was to evaluate actigraphy-measured sleep and prostate cancer and to expand on findings from prior studies of self-reported sleep. Methods We prospectively examined 34 260 men without a history of prostate cancer in the UK Biobank. Sleep characteristics were measured over 7 days using actigraphy. We calculated sleep duration, onset, midpoint, wake-up time, social jetlag (difference in weekend-weekday sleep midpoints), sleep efficiency (percentage of time spent asleep between onset and wake-up time), and wakefulness after sleep onset. Cox proportional hazards models were used to estimate covariate-adjusted hazards ratios (HRs) and 95% confidence intervals (CIs). Results Over 7.6 years, 1152 men were diagnosed with prostate cancer. Sleep duration was not associated with prostate cancer risk. Sleep midpoint earlier than 4:00 am was not associated with prostate cancer risk, though sleep midpoint of 5:00 am or later was suggestively associated with lower prostate cancer risk but had limited precision (earlier than 4:00 am vs 4:00-4:59 am HR = 1.00, 95% CI = 0.87 to 1.16; 5:00 am or later vs 4:00-4:59 am HR = 0.79, 95% CI = 0.57 to 1.10). Social jetlag was not associated with greater prostate cancer risk (1 to <2 hours vs <1 hour HR = 1.06, 95% CI = 0.89 to 1.25; ≥2 hours vs <1 hour HR = 0.90, 95% CI = 0.65 to 1.26). Compared with men who averaged less than 30 minutes of wakefulness after sleep onset per day, men with 60 minutes or more had a higher risk of prostate cancer (HR = 1.20, 95% CI = 1.00 to 1.43). Conclusions Of the sleep characteristics studied, higher wakefulness after sleep onset—a measure of poor sleep quality—was associated with greater prostate cancer risk. Replication of our findings between wakefulness after sleep onset and prostate cancer are warranted. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Actigraphy-derived measures of sleep and risk of prostate cancer in the UK Biobank

Author

Freeman, Joshua R, primary, Saint-Maurice, Pedro F, additional, Watts, Eleanor L, additional, Moore, Steven C, additional, Shams-White, Marissa M, additional, Wolff-Hughes, Dana L, additional, Russ, Daniel E, additional, Almeida, Jonas S, additional, Caporaso, Neil E, additional, Hong, Hyokyoung G, additional, Loftfield, Erikka, additional, and Matthews, Charles E, additional

Published
2023
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24. Multivariate phase space reconstruction by nearest neighbor embedding with different time delays

Author

Garcia, Sara P. and Almeida, Jonas S.

Subjects
Nonlinear Sciences - Chaotic Dynamics
Abstract

A recently proposed nearest neighbor based selection of time delays for phase space reconstruction is extended to multivariate time series, with an iterative selection of variables and time delays. A case study of numerically generated solutions of the x- and z coordinates of the Lorenz system, and an application to heart rate and respiration data, are used for illustration., Comment: 4 pages, 3 figures

Published
2006
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25. Nearest neighbor embedding with different time delays

Author

Garcia, Sara P. and Almeida, Jonas S.

Subjects
Nonlinear Sciences - Chaotic Dynamics
Abstract

A nearest neighbor based selection of time delays for phase space reconstruction is proposed and compared to the standard use of time delayed mutual information. The possibility of using different time delays for consecutive dimensions is considered. A case study of numerically generated solutions of the Lorenz system is used for illustration. The effect of contamination with various levels of additive Gaussian white noise is discussed., Comment: 4 pages, 5 figures, updated to final version

Published
2004
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27. 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
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28. 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
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29. epiDonate – distributed serverless data infrastructure for epidemiological studies

Author

Almeida, Jonas S, Patel, Bhaumik, Russ, Daniel E, Bhawsar, Praphulla, Maurice, Pedro F Saint, Matthews, Charles, Anand, Adit, Ferguson, Martin, Johnson, Davin, Brotzman, Michelle, Gerlanc, Nicole, Chanock, Stephen, de Gonzalez, Amy Berrington, Gaudet, Mia, and Garcia-Closas, Montserrat

Subjects
Articles
Abstract

Motivation: Epidemiological studies face two important challenges: the need to ingest ever more complex data types, and mounting concerns about participant privacy and data governance. These two challenges are compounded by the expectation that data infrastructure will eventually need to facilitate cross-registration of participants by multiple epidemiological studies. Implementation: The portable web-service epiDonate was developed using the serverless model known as FaaS (Function-as-a-Service). The reference implementation uses nodejs. The implementation relies on a simple tokenization scheme, mediated by a public API, that a) distinguishes admin from participant roles, with b) extensible permission configuration operating a read/write structure. General Features: The critical design feature of epiDonate is the absence of business logic on the server-side (the web service). The simplicity removes the need to customize virtual machines and enables ecosystems of multiple web Applications backed by one or more data donation deployments. Availability: https://episphere.github.io/donate

Published
2023

36. 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

37. 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

38. 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

39. 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

40. Benchmarking of alignment-free sequence comparison methods

Author

Zielezinski, Andrzej, Girgis, Hani Z., Bernard, Guillaume, Leimeister, Chris-Andre, Tang, Kujin, Dencker, Thomas, Lau, Anna Katharina, Röhling, Sophie, Choi, Jae Jin, Waterman, Michael S., Comin, Matteo, Kim, Sung-Hou, Vinga, Susana, Almeida, Jonas S., Chan, Cheong Xin, James, Benjamin T., Sun, Fengzhu, Morgenstern, Burkhard, and Karlowski, Wojciech M.

Published
2019
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41. Moving towards FAIR practices in epidemiological research

Author

García-Closas, Montserrat, primary, Ahearn, Thomas U, additional, Gaudet, Mia M, additional, Hurson, Amber N, additional, Balasubramanian, Jeya Balaji, additional, Choudhury, Parichoy Pal, additional, Gerlanc, Nicole M, additional, Patel, Bhaumik, additional, Russ, Daniel, additional, Abubakar, Mustapha, additional, Freedman, Neal D, additional, Wong, Wendy S W, additional, Chanock, Stephen J, additional, de Gonzalez, Amy Berrington, additional, and Almeida, Jonas S, additional

Published
2023
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46. Moving Toward Findable, Accessible, Interoperable, Reusable Practices in Epidemiologic Research.

Author

García-Closas, Montserrat, Ahearn, Thomas U, Gaudet, Mia M, Hurson, Amber N, Balasubramanian, Jeya Balaji, Choudhury, Parichoy Pal, Gerlanc, Nicole M, Patel, Bhaumik, Russ, Daniel, Abubakar, Mustapha, Freedman, Neal D, Wong, Wendy S W, Chanock, Stephen J, Gonzalez, Amy Berrington de, and Almeida, Jonas S

Subjects
PRIVACY, RESEARCH evaluation, METADATA, DATABASE management, COST benefit analysis, SEARCH engines, ACCESS to information, MEDICAL ethics, APPLICATION service providers, INTERPROFESSIONAL relations, ELECTRONIC health records, CONSORTIA, EPIDEMIOLOGICAL research
Abstract

Data sharing is essential for reproducibility of epidemiologic research, replication of findings, pooled analyses in consortia efforts, and maximizing study value to address multiple research questions. However, barriers related to confidentiality, costs, and incentives often limit the extent and speed of data sharing. Epidemiological practices that follow Findable, Accessible, Interoperable, Reusable (FAIR) principles can address these barriers by making data resources findable with the necessary metadata, accessible to authorized users, and interoperable with other data, to optimize the reuse of resources with appropriate credit to its creators. We provide an overview of these principles and describe approaches for implementation in epidemiology. Increasing degrees of FAIRness can be achieved by moving data and code from on-site locations to remote, accessible ("Cloud") data servers, using machine-readable and nonproprietary files, and developing open-source code. Adoption of these practices will improve daily work and collaborative analyses and facilitate compliance with data sharing policies from funders and scientific journals. Achieving a high degree of FAIRness will require funding, training, organizational support, recognition, and incentives for sharing research resources, both data and code. However, these costs are outweighed by the benefits of making research more reproducible, impactful, and equitable by facilitating the reuse of precious research resources by the scientific community. [ABSTRACT FROM AUTHOR]

Published
2023
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47. PLCOjs, a FAIR GWAS web SDK for the NCI Prostate, Lung, Colorectal and Ovarian Cancer Genetic Atlas project

Author

Ruan, Eric, primary, Nemeth, Erika, additional, Moffitt, Richard, additional, Sandoval, Lorena, additional, Machiela, Mitchell J, additional, Freedman, Neal D, additional, Huang, Wen-Yi, additional, Wong, Wendy, additional, Chen, Kai-Ling, additional, Park, Brian, additional, Jiang, Kevin, additional, Hicks, Belynda, additional, Liu, Jia, additional, Russ, Daniel, additional, Minasian, Lori, additional, Pinsky, Paul, additional, Chanock, Stephen J, additional, Garcia-Closas, Montserrat, additional, and Almeida, Jonas S, additional

Published
2022
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48. Conceptual Alignment Method.

Author

Maass, Wolfgang, Castellanos, Arturo, Tremblay, Monica, Lukyanenko, Roman, Storey, Veda C., and Almeida, Jonas S.

Subjects
ARTIFICIAL intelligence, MACHINE learning, HOSPITAL admission & discharge, MEDICAL care costs, DATA analysis
Abstract

This paper proposes a Conceptual Alignment (CA) Method for conceptual modeling and machine learning. The model consists of a three-step cycle that selects an initial conceptual model, aligns it with machine learning models, and refines both models to reach predictive consistency. Alignment is based on composition methods that can be instantiated by methods that satisfy contribution properties. The Conceptual Alignment Method is applied to a healthcare use case on hospital inpatient discharges. The machine learning model trained for total cost predictions is aligned with a conceptual model. We show how this refined conceptual model is used for explaining the machine learning model for a very large healthcare dataset. [ABSTRACT FROM AUTHOR]

Published
2023

49. MedicaidJS: a FAIR approach to real-time drug analytics.

Author

Agarwal, Kunaal, Kim, Hae Rin, Almeida, Jonas S, and Sandoval, Lorena

Subjects
DRUG analysis, DRUG prices, APPLICATION program interfaces, JAVASCRIPT programming language
Abstract

Motivation As prescription drug prices have drastically risen over the past decade, so has the need for real-time drug tracking resources. In spite of increased public availability to raw data sources, individual drug metrics remain concealed behind intricate nomenclature and complex data models. Some web applications, such as GoodRX, provide insight into real-time drug prices but offer limited interoperability. To overcome both obstacles we pursued the direct programmatic operation of the stateless Application Programming interfaces (HTTP REST APIs) maintained by the Food and Drug Administration (FDA), Medicaid, and National Library of Medicine. These data-intensive resources represent an opportunity to develop Software Development Kits (SDK) to streamline drug metrics without downloads or installations, in a manner that addresses the FAIR principles for stewardship in scientific data—Findability, Accessibility, Interoperability, and Reusability. These principles provide a guideline for continual stewardship of scientific data. Results MedicaidJS SDK was developed to orchestrate API calls to three complementary data resources: Medicaid (data.medicaid.gov), Food and Drug Administration (open.fda.gov), and the National Library of Medicine RxNorm (lhncbc.nlm.nih.gov/RxNav). MedicaidJS synthesizes response data from each platform into a zero-footprint JavaScript modular library that provides data wrangling, analysis, and generation of embeddable interactive visualizations. The SDK is served on github with live examples on observableHQ notebooks. It is freely available and can be embedded into web applications as modules returning structured JSON data with standardized identifiers. Availability and implementation Open source code publicly available at https://github.com/episphere/medicaid , live at episphere.github.io/medicaid , supplementary interactive Observable Notebooks at observablehq.com/@medicaidsdk/medicaidsdk. [ABSTRACT FROM AUTHOR]

Published
2023
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