The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging
Open accessAbstract
The immune system is critical in modulating cancer progression, but knowledge of immune composition, phenotype, and interactions with tumor is limited. We used multiplexed ion beam imaging by time-of-flight (MIBI-TOF) to simultaneously quantify in situ expression of 36 proteins covering identity, function, and immune regulation at sub-cellular resolution in 41 triple-negative breast cancer patients. Multi-step processing, including deep-learning-based segmentation, revealed variability in the composition of tumor-immune populations across individuals, reconciled by overall immune infiltration and enriched co-occurrence of immune subpopulations and checkpoint expression. Spatial enrichment analysis showed immune mixed and compartmentalized tumors, coinciding with expression of PD1, PD-L1, and IDO in a cell-type- and location-specific manner. Ordered immune structures along the tumor-immune border were associated with compartmentalization and linked to survival. These data demonstrate organization in the tumor-immune microenvironment that is structured in cellular composition, spatial arrangement, and regulatory-protein expression and provide a framework to apply multiplexed imaging to immune oncology.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Nuclear segmentation was performed with DeepCell (Van Valen et al., 2016) (https://github.com/vanvalenlab/deepcell-tf) as previously described (Keren et al., 2018), using in-house training and validation MIBI imaging datasets from a variety of human clinical tissue types to ensure reproducibility.”
From Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma (2020) · cites this paper as Keren et al., 2018
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
NIH Image to ImageJ: 25 years of image analysis
Schneider, C. A., Rasband, W. S., & Eliceiri, K. W. (2012) · Nature Methods · doi:10.1038/nmeth.2089 · Cited by 64,638
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,989
Adverse Renal Effects of Immune Checkpoint Inhibitors: A Narrative Review
Wanchoo, R., Karam, S., Uppal, N. N., Barta, V. S., Deray, G., Devoe, C., Launay‐Vacher, V., Jhaveri, K. D., & on behalf of Cancer and Kidney International Network Workgroup on Immune Checkpoint Inhibitors (2017) · American Journal of Nephrology · doi:10.1159/000455014 · Cited by 15,320
Chromatin modifications and their function
Kouzarides, T. (2007) · Cell · doi:10.1016/j.cell.2007.02.005 · Cited by 10,883 · cited 1×
“Since H3K9ac was shown to be correlated with open chromatin and H3K27me3 with closed chromatin (Kouzarides, 2007), these global changes in their ratios may indicate that cells on the tumor border are more transcriptionally active than those in the tumor center.”
Combined Nivolumab and Ipilimumab or Monotherapy in Untreated Melanoma
Larkin, J., Chiarion-Sileni, V., Gonzalez, R., Grob, J. J., Cowey, C. L., Lao, C. D., Schadendorf, D., Dummer, R., Smylie, M., Rutkowski, P., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1504030 · Cited by 8,157
Cancer immunotherapy using checkpoint blockade
Ribas, A., & Wolchok, J. D. (2018) · Science · doi:10.1126/science.aar4060 · Cited by 6,791
Myeloid-derived-suppressor cells as regulators of the immune system
Gabrilovich, D. I., & Nagaraj, S. (2009) · Nature Reviews Immunology · doi:10.1038/nri2506 · Cited by 6,753
PD-1 blockade induces responses by inhibiting adaptive immune resistance
Tumeh, P. C., Harview, C. L., Yearley, J. H., Shintaku, I. P., Taylor, E. J. M., Robert, L., Chmielowski, B., Spasic, M., Henry, G., Ciobanu, V., et al. (2014) · Nature · doi:10.1038/nature13954 · Cited by 6,609
Elements of cancer immunity and the cancer–immune set point
Chen, D. S., & Mellman, I. (2017) · Nature · doi:10.1038/nature21349 · Cited by 5,352
Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients
Herbst, R. S., Soria, J.-C., Kowanetz, M., Fine, G. D., Hamid, O., Gordon, M. S., Sosman, J. A., McDermott, D. F., Powderly, J. D., Gettinger, S. N., et al. (2014) · Nature · doi:10.1038/nature14011 · Cited by 5,231
Flagged first, then by citations
Research works printed but not linked: 1
- Haralick, 1973, Textural Features for Image Classification. IEEE Trans. Syst. Man. Cybern, SMC, 3, 610
Cited by
Sorted by citations
Items 901–1,000 of 1,000
Piyadasa, H., Oberlton, B., Kong, A., Fullaway, C. C., Varra, S. R., Sowers, C., & Tsai, A. G. (2023) · Journal of Visualized Experiments · doi:10.3791/65615 · Cited by 1
Breaks for Precision Medicine in Cancer: Development and Prospects of Spatiotemporal Transcriptomics
Yan, S., Guo, Y., Lin, L., & Zhang, W. (2024) · Cancer Biotherapy and Radiopharmaceuticals · doi:10.1089/cbr.2023.0116 · Cited by 1
Tamir, Y., Bussi, Y., Owczarek, C., Luque, L. M., Torrisi, G., Rose, L. A., Kliper-Gross, O., Sander, C., Schumacher, L. J., Parsons, M., et al. (2026) · Cell Reports Methods · doi:10.1016/j.crmeth.2026.101463 · Cited by 1
Machine learning and pathology: a historical perspective
Malpani, S., Paz, R., Mirzabeigi, Y., Mohammadi, S. M. K., Gasca, R., & Arora, H. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-15504-8.00002-8 · Cited by 1
Liver cancer recurrence predicted by immune-cell location and gene expression
Schürch, C. M. (2025) · Nature · doi:10.1038/d41586-025-00734-8 · Cited by 1
AI-Assisted Immunology for Precision Cancer Medicine
Sah, A. K., Verma, M., Mishra, P. S., Rahaman, S. A., Gupta, T., & Mishra, R. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-9725-1.ch010 · Cited by 1
Clemente, L. C., Shi, O., Rojas, F. R., & Parra, E. R. (2022) · Journal of Visualized Experiments · doi:10.3791/64015 · Cited by 1
Artificial intelligence in breast cancer: An opportunity for early diagnosis
Malla, R. R., & Katneni, V. (2023) · Elsevier eBooks · doi:10.1016/b978-0-443-15280-1.00004-2 · Cited by 1
Lazic, D., Kromp, F., Kirr, M., Mívalt, F., Rifatbegovic, F., Halbritter, F., Bernkopf, M., Bileck, A., Ussowicz, M., Ambros, I. M., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.09.30.321539 · Cited by 1
IBEX: An open and extensible method for high content multiplex imaging of diverse tissuesPreprint
Radtke, A. J., Chu, C. J., Yaniv, Z., Li, Y., Marr, J., Beuschel, R. T., Ichise, H., Gola, A., Kabát, J., Lowekamp, B., et al. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.11364 · Cited by 1
Ohara, K., Rendeiro, A. F., Bhinder, B., Eng, K., Ravichandran, H., Pisapia, D. J., Vosoughi, A., Fernandez, E. M., Shohdy, K. S., Manohar, J., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.16.468622 · Cited by 1
SOTIP: a Unified Framework for Microenvironment Modelling with Spatial Omics DataPreprint
Yuan, Z., Li, Y., Shi, M., Yang, F., Gao, J. T., Yao, J., & Zhang, M. Q. (2022) · Research Square · doi:10.21203/rs.3.rs-1263025/v1 · Cited by 1
Seal, S., Wrobel, J., Johnson, A. M., Nemenoff, R. A., Schenk, E. L., Bitler, B. G., Jordan, K. R., & Ghosh, D. (2022) · Research Square · doi:10.21203/rs.3.rs-609920/v2 · Cited by 1
Lu, P., Oetjen, K. A., Oh, S. T., & Thorek, D. L. J. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.03.26.534306 · Cited by 1
Laberiano-Fernández, C., Gan, Q., Wang, S. M., Tamegnon, A., Wistuba, I. I., Yoon, E. C., Roy‐Chowdhuri, S., & Parra, E. R. (2023) · Preprints.org · doi:10.20944/preprints202306.0480.v1 · Cited by 1
Pembrolizumab alters the tumor immune landscape in a patient with dMMR glioblastomaPreprint
Bartkowiak, T., Brockman, A. A., Mobley, B. C., Harmsen, H. J., Moots, P. L., Merrell, R. T., Johnson, D. B., Thompson, R. C., Puduvalli, V. K., & Ihrie, R. A. (2023) · medRxiv · doi:10.1101/2023.12.08.23299732 · Cited by 1
Körkaya, H., Alkan, F. K., Caglayan, A., Alkan, H., Benson, E. M., Gunduz, Y. E., Şensoy, Ö., Durdağı, S., Zarbaliyev, E., Dyson, G. E., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-3959342/v1 · Cited by 1
Traxel, S., Schmidt, F., Beerli, C., Vuong, D.-V., Speck, R. F., & Bredl, S. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.01.615826 · Cited by 1
Bridges, K., Pizzurro, G. A., Baysoy, A., Baskaran, J. P., Xu, Z. Z., Mathew, V., Tripple, V., LaPorte, M., Park, K., Damsky, W., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.28.620093 · Cited by 1
Avraham‐Davidi, I., Mages, S., Klughammer, J., Moriel, N., Imada, S., Hofree, M., Murray, E. M., Chen, J. H., Pelka, K., Mehta, A., et al. (2025) · eLife · doi:10.7554/elife.104815.1 · Cited by 2
Context-dependent spatial multicellular network motifs for single-cell spatial biologyPreprint
Zamir, A., Amitay, Y., Tamir, Y., Keren, L., & Zaritsky, A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.05.651422 · Cited by 1
Gavasso, S., Haugsøen, J. B., Kleftogiannis, D., Gerking, Y., Anandan, S., Herdlevær, I., Olsen, H., Brun, M., Blaser, N., Gjertsen, B. T., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.01.662494 · Cited by 1
Avraham‐Davidi, I., Mages, S., Klughammer, J., Moriel, N., Imada, S., Hofree, M., Murray, E. M., Chen, J. H., Pelka, K., Mehta, A., et al. (2025) · eLife · doi:10.7554/elife.104815.2 · Cited by 1
Glass, D. R., Dornisch, E. M., Yin, H., Ludmann, S. A., Samudre, A., Kuhl, S., Malone, J., Chander, A., Kaul, N., Phalen, C. G., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.13.717827 · Cited by 1
Hacking the ‘Cellular Immunology Agency’: T cells caught in the act
Spitzer, M. H. (2019) · Nature Immunology · doi:10.1038/s41590-019-0354-9
Helal, T., Bakkach, J., Elghazawy, H. I., Aref, A., Kelany, M., Abdallah, L., Abdelbakey, F., Ali, D., Ali, D., Ahmed, M. H., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-139711/v1
CNS myeloid cell heterogeneity at the single-cell level
Böttcher, C., Sankowski, R., Priller, J., & Prinz, M. (2019) · e-Neuroforum · doi:10.1515/nf-2018-0034
Imaging Glial Cells in Alzheimer’s Disease: From Light Microscopy to Multiplexed Ion Beam Imaging
Morris-Janzen, D., & Oliveria, J. P. (2019) · Health Science Inquiry · doi:10.29173/hsi12
FOXes at play in the lymphoma landscape
Younes, S. F., & Natkunam, Y. (2020) · Leukemia & lymphoma/Leukemia and lymphoma · doi:10.1080/10428194.2020.1834099
Quantitative engineering biology in the tumormicroenvironment
Ma, W., Wei, T., Fu, X., & Li, X. (2020) · Chinese Science Bulletin (Chinese Version) · doi:10.1360/tb-2020-0489
Measuring the Stability of Learned FeaturesPreprint
Sankaran, K. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.10388
Proteomic biomarker technology for cancer immunotherapy
Fankhauser, R. G., DePatie, N., Berryman, R., Lucero, O. M., & Kulkarni, R. P. (2021) · Elsevier eBooks · doi:10.1016/b978-0-323-90949-5.00007-3
Spatial mapping of the tumor immune microenvironment
Wu, Y.-C., Pagacz, J., Emery, S. C., Kron, S. J., & Lee, S. S.-Y. (2021) · Elsevier eBooks · doi:10.1016/b978-0-323-90949-5.00009-7
Nowak, J. A., Lau, M. C., Borowsky, J., Väyrynen, J. P., Haruki, K., Zhao, M. M., Costa, A. D., Gu, S., da Silva, A., Arima, K., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-847464/v1
Huang, J.-R., Song, J., Li, X., Liu, S., Huang, W., Shen, Z., Cheng, Y., Kou, S., Gao, Z., Tian, Y., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-987733/v1
Advances in Single-Cell Sequencing Technology and its Applications in Triple-Negative Breast CancerPreprint
Li, M., Wang, M., Xie, Y., Yan, T., & Li, Y. (2021) · Research Square · doi:10.21203/rs.3.rs-1034157/v1
Metodología para la censura de cuentas y de gestión para el crédito bancario.
Gil, J. M. (1980) · Revista española de financiación y contabilidad
Reddy, R., Yang, L., Liu, J. J., Liu, Z., & Wang, J. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.01.11.475923
Liu, L., Yu, X., Li, Z., He, X., Zha, J., Lin, Z., Hong, Y., Zheng, H., Lai, Q., Ding, K., et al. (2022) · Research Square · doi:10.21203/rs.3.rs-1524378/v1
He, C., Zhu, M., Huang, H., Chen, D., Ren, H., Li, W., Gao, D., & Gu, Y. (2022) · Research Square · doi:10.21203/rs.3.rs-1499943/v1
Bumann, D. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.734438619.793566050
Jokela, T. A., Carlson, E. G., & LaBarge, M. A. (2022) · Springer eBooks · doi:10.1007/978-3-030-98950-7_25
An in situ Quantitative Map of Initial Human Colorectal HIV TransmissionPreprint
Baharlou, H., Canete, N. P., Vine, E. E., Hu, K., Yuan, D., Sandgren, K. J., Bertram, K. M., Nasr, N., Rhodes, J. W., Gosselink, M. P., et al. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4099798
Nanobiotherapeutic strategies to target immune microenvironment of triple-negative breast cancer.
Chang, Q., Chang, L., Li, M., Fan, L., Bao, S., Wang, X., & Liu, L. (2022) · PubMed Central
Spatial Transcriptomics in Inflammation: Dissecting the Immune Response in 3D in Complex Tissues
Hu, K. H. (2023) · Progress in inflammation research · doi:10.1007/978-3-031-23661-7_8
Bootstrap Confidence Regions for Learned Feature Embeddings
Sankaran, K. (2023) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2023.2197478
Nirmal, A. J., Maliga, Z., Vallius, T., Quattrochi, B., Chen, A. A., Jacobson, C. A., Pelletier, R. J., Yapp, C., Arias-Camison, R., Chen, Y., et al. (2023) · doi:10.1158/2159-8290.c.6549601
Nirmal, A. J., Maliga, Z., Vallius, T., Quattrochi, B., Chen, A. A., Jacobson, C. A., Pelletier, R. J., Yapp, C., Arias-Camison, R., Chen, Y., et al. (2023) · doi:10.1158/2159-8290.22541281
Spatial Technologies: A Game Changer for Studying the Tumor Microenvironment
Lee, R. Y., Lau, M. C., Goh, D. L. M., Wee, F. Y. T., Lim, J. C. T., & YEONG, J. P. S. (2023) · Springer eBooks · doi:10.1007/978-3-030-80962-1_96-1 · Cited by 1
Zhang, H., AbdulJabbar, K., Moore, D. A., Akarca, A. U., Enfield, K. S. S., Jamal‐Hanjani, M., Raza, S. E. A., Veeriah, S., Salgado, R., McGranahan, N., et al. (2023) · doi:10.1158/0008-5472.c.6626121.v1
Spatial Technologies: A Game Changer for Studying the Tumor Microenvironment
Lee, R. Y., Lau, M. C., Goh, D. L. M., Wee, F. Y. T., Lim, J. C. T., & YEONG, J. P. S. (2023) · Springer eBooks · doi:10.1007/978-3-030-80962-1_96-2
Single Cell Spatial Analysis and Biomarker Discovery in Hodgkin LymphomaPreprint
Xu, A. M., Jiang, A., Aoki, T., Gamboa, A., Chong, L. C., Colombo, A., Yin, Y., Lownik, J. C., Takata, K., Hav, M., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.05.24.542195
Cancer patient stratification based on patterns of immune infiltration
Schaafsma, E., Zhang, B., Zhao, Y., & Cheng, C. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-824010-6.00027-7
Yaegashi, L. B. (2023) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.5.2023.tde-10052023-112429
Hypoxia coordinates the spatial landscape of myeloid cells within glioblastoma to affect outcomePreprint
Haley, M., Bere, L. D., Minshull, J., Georgaka, S., Garcia-Martin, N., Howell, G. J., Coope, D. J., Roncaroli, F., King, A. T., Wedge, D. C., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.30.547190
Visualizing and Subtyping Tumor Ecosystem
Saw, P. E., & Song, E. (2023) · Springer eBooks · doi:10.1007/978-981-99-1183-7_27
Ak, Ç., Sayar, Z., Thibault, G., Burlingame, E. A., Eng, J. R., Chitsazan, A., Adey, A., Boniface, C. T., Spellman, P. T., THOMAS, G. V., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.18.553854
Chandio, N. N. (2023) · Journal of Development and Social Sciences · doi:10.47205/jdss.2023(4-ii)71
Neue Methoden der multiparametrischen Gewebediagnostik
Mayer, A., & Haist, M. (2023) · Die Onkologie · doi:10.1007/s00761-023-01425-7
Nawrocki, S. T., Olea, J., Celi, C. V., Dadrastoussi, H., Wu, K., Tsao-Wei, D. D., Colombo, A., Coffey, M. C., Hernandez, E. F., Chen, X., et al. (2023) · doi:10.1158/1078-0432.c.6982800
Analytical Tools to Quantitate Immune Mediated Effects
Pavelko, K. D., & Villasboas, J. C. (2024) · Wiley eBooks · doi:10.1002/9781119824572.ch26
Durkee, M. S., Ai, J., Casella, G., Cao, T., Andrade, M. S., Clark, M. R., & Giger, M. L. (2024) · SPIE Medical Imaging: Digital and Computational Pathology · doi:10.1117/12.3008522
Li, Z., Li, Y., Wang, X., & Yang, Q. (2021) · Figshare · doi:10.6084/m9.figshare.13532704
Li, Z., Li, Y., Wang, X., & Yang, Q. (2021) · Figshare · doi:10.6084/m9.figshare.13532716
Li, Z., Li, Y., Wang, X., & Yang, Q. (2021) · Figshare · doi:10.6084/m9.figshare.13532701
Li, Z., Li, Y., Wang, X., & Yang, Q. (2021) · Figshare · doi:10.6084/m9.figshare.13532698
Li, Z., Li, Y., Wang, X., & Yang, Q. (2021) · Figshare · doi:10.6084/m9.figshare.13532722
Zhang, D., Ni, Y., Wang, Y., Feng, J., Zhuang, N., Li, J., Liu, L., Shen, W., Ji, Z., Zheng, W., et al. (2023) · Figshare · doi:10.6084/m9.figshare.23722305
Torcasso, M. S., Howard, F. M., Zha, Y., Ai, J., Clark, M. R., & Giger, M. L. (2024) · International Workshop on Breast Imaging (IWBI) · doi:10.1117/12.3027025
Spatial quantification of cellular metabolism in tissues by metabolic regulome profiling
Glauner, T. A., Truxa, S., Cetin, M., Schlüter, K., Calafato, D., & Hartmann, F. J. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-822213-3.00006-1
Porpiglia, E., & Blau, H. M. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-822213-3.00003-6
Munch, Y., Abel, E., Hav, M., Padmanabhan, R., Pawlowski, S. W., Gubbens, A. J., Bendall, S. C., Kimmey, S. C., & Tarolli, J. G. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-822209-6.00007-2
Combined nucleic acid and protein quantification in the native tissue microenvironment
Zhu, B., Markovic, M., & Jiang, S. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-822209-6.00006-0
Cui, Y., & Yuan, Z. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.04.606512
Takle, S. T., Grøndal, S. M., Lien, M. E., Lianto, P., Deng, W., Lillestøl, R., Lønning, P. E., Lorens, J. B., Knappskog, S., & Halberg, N. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.08.607253
CLEAR-IT: Contrastive Learning to Capture the Immune Composition of Tumor MicroenvironmentsPreprint
Spengler, D., Korovin, S., Prakash, K., Bankhead, P., Debets, R., Smith, C., & Balcioglu, H. E. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.20.608738
Chen, J. H., Elmelech, L., Tang, A. L., & Hacohen, N. (2024) · Current Opinion in Immunology · doi:10.1016/j.coi.2024.102463
Ishar, J., Tam, Y. M., Mages, S., & Klughammer, J. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012504
A Multimodal Study of the Response to Neoadjuvant Chemotherapy in Patients with Breast CancerPreprint
Peng, J., Chen, R., Liang, Y., Wang, Y., Lyu, S., Song, J., Ye, Z., Liu, W., & Liu, Z. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4997928
Delmastro, A. C., Liu, C. C., Ding, X., Tan, S. Y., Averbukh, I., Bosse, M. M., Keyes, T., Sharma, S., Deutsch, G. H., Angelo, M., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.22.624756
Torcasso, M. S., Ai, J., Casella, G., Cao, T., Chang, A., Halper-Stromberg, A., Jabrì, B., Clark, M. R., & Giger, M. L. (2024) · Journal of medical imaging · doi:10.1117/1.jmi.11.6.067502
Biomechanical regulation of anti-tumor immune responses in the TME
Kersten, K., & Weaver, V. M. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-14064-8.00031-x
Improve accuracy of cell segmentation based on a cascaded network for edge enhancement
Gong, S., Karl, Z., Yu, Z., & Shen, M. (2025) · Advanced Fiber Laser Conference (AFL) · doi:10.1117/12.3058681
HRCHY-CytoCommunity identifies hierarchical tissue organization in cell-type spatial mapsPreprint
Wang, Z., Xu, Y., Hu, Y., & Gao, L. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.03.27.645631
Analysis of the tumor microenvironment using imaging mass cytometry data
Loncová, Z., Trajanoski, Z., & Rieder, D. (2025) · Methods in cell biology · doi:10.1016/bs.mcb.2025.03.006
Multi-cellular phenotypic dynamics during the progression of breast tumorsPreprint
Gsell, L., Watson, S. S., Sutevski, I., Massara, M., Soukup, K., Eroğlu, A., Mold, J. E., Cougnoux, A., Joyce, J. A., & Hausser, J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.16.649085
Cells Keep Diverse Company in Diseased Tissues
Campbell, K. R., & Goeva, A. (2025) · Cancer Research · doi:10.1158/0008-5472.can-25-2070
Some recent developments in functional covariates on time-to-event data: a review
Li, Y., & Zhao, X. (2025) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918.2025.2501084
SpatioMark: quantifying the impact of spatial proximity on cell phenotype
Iyengar, S. S., Qin, A. R., Robertson, N. B., Harman, A. N., & Patrick, E. (2025) · Bioinformatics · doi:10.1093/bioinformatics/btaf409 · Cited by 1
Unraveling the UCHL5-ALK5 Axis: A Novel Therapeutic Strategy for Triple-Negative Breast CancerPreprint
Wang, X., Wang, N., Dou, D., Guo, G., Duan, X., Xue, B., Xiong, Y., Chi, J., Sun, Y., Han, L., et al. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5392840
Shalom, I., Somer, J., Miyara, S., Mayo, A., Mannor, S., & Alon, U. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.02.673328
Spatial Technologies: A Game Changer for Studying the Tumor Microenvironment
Lee, R. Y., Lau, M. C., Goh, D. L. M., Wee, F. Y. T., Lim, J. C. T., & YEONG, J. P. S. (2025) · Springer eBooks · doi:10.1007/978-3-032-00761-2_96
McCaffrey, E., Delmastro, A. C., Singh, B., Devi, A., Munson, C. W., Priyanka, Golden, N., Khader, S. A., Angelo, M., Kaushal, D., et al. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2528104123
Schulz, D., Morfouace, M., Fernandez, B. P., Możejko, M., Déglise, S., Daniel, M., Eling, N., Hong, H. S., Tissot, S., Rusakiewicz, S., et al. (2025) · medRxiv · doi:10.1101/2025.11.10.25339890 · Cited by 1
Sherman, M. E., Carter, J. C., Vierkant, R. A., Stallings‐Mann, M. L., Pacheco-Spann, L. M., Winham, S. J., Vachon, C. M., Wang, C., Jensen, M. R., Troester, M. A., et al. (2025) · Cancers · doi:10.3390/cancers17233797
Wu, L., Yao, H., Wang, Y., Liu, H., Lv, H., Jiao, D., & Jiang, J. (2025) · Acta Biomaterialia · doi:10.1016/j.actbio.2025.12.009 · Cited by 1
Panwar, P., Guo, B., Zhou, H., Hicks, S. C., & Ghazanfar, S. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.11.30.691081 · Cited by 1
Wang, S., Zhang, M., Lin, L., Dong, J., Wang, X., Liu, X., Zhang, S., Liu, G., & Kang, X. (2025) · Chemical Engineering Journal · doi:10.1016/j.cej.2025.171773
Additional file 6 of Integrated analysis of immune-related genes in endometrial carcinoma
Wang, Y., Liu, Y., Guan, Y., Li, H., Liu, Y., Zhang, M., Cui, P., Kong, D., Chen, X., & Yin, H. (2020) · Figshare · doi:10.6084/m9.figshare.13047204
Metadata
- Authors
- Keren, L., Bosse, M., Marquez, D., Angoshtari, R., Jain, S., Varma, S., Yang, S.-R., Kurian, A., Van Valen, D., West, R., Bendall, S. C., & Angelo, M.
- Affiliations
- Stanford University (US)
- Stanford Medicine (US)
- Corresponding author
- Bendall, Sean C.
- Angelo, Michael
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2018-09
- Volume
- 174
- Issue
- 6
- Pages
- 1373-1387.e19
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC6132072
- OpenAlex
- W2890156321
- Cited by
- 1,183
- References
- 54
- Citations by year
- 2026: 222 · 2025: 147 · 2024: 141 · 2023: 164 · 2022: 153 · 2021: 167 · 2020: 105 · 2019: 74 · 2018: 9
- FWCI
- 33.83
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- Funders
- Damon Runyon Cancer Research Foundation (DRG-2292-17, DRG-2017-09)
- EMBO Long-Term fellowship (ALTF 1128-2016)
- NIH F32 Postdoctoral Fellowship
- Burroughs Wellcome PDEP award
- The Allen Discovery Center at Stanford University
- Crowdflower A.I.
- NIH (5R01CA18390402, 1DP2OD022550-01, 1-R00-GM104148-01, 5U19AI116484-02, U19 AI104209, 1-DP5-OD019822, 1R01AG056287-01, 1R01AG057915-01, 1U24CA224309-01)
- Bill and Melinda Gates Foundation
- Stanford Cancer Institute (NSF ECCS-1542152)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Keywords
- triple-negative breast cancer, tumor immune microenvironment, MIBI, immune checkpoint molecules, PD-1, PD-L1, IDO, immune cell infiltration, patient survival
- MeSH terms
- Machine Learning, Lymphocyte Activation Gene 3 Protein, Female, Humans, Lymphocytes, Mass Spectrometry, Antigens, CD, Cluster Analysis, Principal Component Analysis, Indoleamine-Pyrrole 2,3,-Dioxygenase, Kaplan-Meier Estimate, Tumor Microenvironment, B7-H1 Antigen, Programmed Cell Death 1 Receptor, Spatial Analysis, Triple Negative Breast Neoplasms
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review