Spatial immunophenotypes predict response to anti-PD1 treatment and capture distinct paths of T cell evasion in triple negative breast cancer
Open accessAbstract
Only a subgroup of triple-negative breast cancer (TNBC) responds to immune checkpoint inhibitors (ICI). To better understand lack of response to ICI, we analyze 681 TNBCs for spatial immune cell contextures in relation to clinical outcomes and pathways of T cell evasion. Excluded, ignored and inflamed phenotypes can be captured by a gene classifier that predicts prognosis of various cancers as well as anti-PD1 response of metastatic TNBC patients in a phase II trial. The excluded phenotype, which is associated with resistance to anti-PD1, demonstrates deposits of collagen-10, enhanced glycolysis, and activation of TGFβ/VEGF pathways; the ignored phenotype, also associated with resistance to anti-PD1, shows either high density of CD163+ myeloid cells or activation of WNT/PPARγ pathways; whereas the inflamed phenotype, which is associated with response to anti-PD1, revealed necrosis, high density of CLEC9A+ dendritic cells, high TCR clonality independent of neo-antigens, and enhanced expression of T cell co-inhibitory receptors.
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Spatial immunophenotypes assigned in triple-negative breast cancer through a spatial phenotype classifier predicted responses to treatment.
“The spatial immunophenotypes were assigned in triple-negative breast cancer through a spatial phenotype classifier, which predicted responses to treatment.”
From The technological landscape and applications of single-cell multi-omics (2023) · cites this paper as [165]
Integration of spatial phenotypes and immunity effectors panel with multiplexed immunofluorescent imaging, scRNA-seq and TCR repertoire analysis elucidated T cell evasion pathways in response to ICB in triple-negative breast cancer.
“Another study integrated the spatial phenotypes and immunity effectors panel of Akoya Biosciences with multiplexed immunofluorescent imaging, scRNA-seq and TCR repertoire analysis to elucidate T cell evasion pathways in response to ICB in triple-negative breast cancer165.”
From The technological landscape and applications of single-cell multi-omics (2023) · cites this paper as [165]
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Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709 · see citing works
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 · see citing works
Robust enumeration of cell subsets from tissue expression profiles
Newman, A. M., Liu, C. L., Green, M. R., Gentles, A. J., Feng, W., Xu, Y., Hoang, C. D., Diehn, M., & Alizadeh, A. A. (2015) · Nature Methods · doi:10.1038/nmeth.3337 · Cited by 12,116 · see citing works
Signatures of mutational processes in human cancer
Initiative, A. P. C. G., Alexandrov, L. B., ICGC Breast Cancer Consortium, ICGC MMML-Seq Consortium, PedBrain, I., Nik-Zainal, S., Wedge, D. C., Aparicio, S. A. J. R., Behjati, S., Biankin, A. V., et al. (2013) · Nature · doi:10.1038/nature12477 · Cited by 9,660 · see citing works
The cancer genome atlas pan-cancer analysis project
The Cancer Genome Atlas Research Network, Weinstein, J. N., Collisson, E. A., Mills, G. B., Shaw, K. R. M., Ozenberger, B. A., Ellrott, K., Shmulevich, I., Sander, C., & Stuart, J. M. (2013) · Nature Genetics · doi:10.1038/ng.2764 · Cited by 9,092 · see citing works
Adjusting batch effects in microarray expression data using empirical Bayes methods
Johnson, W. E., Li, C., & Rabinovic, A. (2007) · Biostatistics · doi:10.1093/biostatistics/kxj037 · Cited by 8,658 · see citing works
Atezolizumab plus bevacizumab in unresectable hepatocellular carcinoma
Finn, R. S., Qin, S., Ikeda, M., Galle, P. R., Ducreux, M., Kim, T.-Y., Kudo, M., Breder, V., Merle, P., Kaseb, A. O., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa1915745 · Cited by 7,470 · see citing works
Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome
Galon, J., Costes, A., Sanchez-Cabo, F., Kirilovsky, A., Mlecnik, B., Lagorce-Pagès, C., Tosolini, M., Camus, M., Berger, A., Wind, P., et al. (2006) · Science · doi:10.1126/science.1129139 · Cited by 6,516 · see citing works
Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy
Sharma, P., Hu-Lieskovan, S., Wargo, J. A., & Ribas, A. (2017) · Cell · doi:10.1016/j.cell.2017.01.017 · Cited by 5,588 · see citing works
TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells
Mariathasan, S., Turley, S. J., Nickles, D., Castiglioni, A., Yuen, K., Wang, Y., Kadel III, E. E., Koeppen, H., Astarita, J. L., Cubas, R., et al. (2018) · Nature · doi:10.1038/nature25501 · Cited by 5,400 · see citing works
Tumor mutational load predicts survival after immunotherapy across multiple cancer types
Samstein, R. M., Lee, C.-H., Shoushtari, A. N., Hellmann, M. D., Shen, R., Janjigian, Y. Y., Barron, D. A., Zehir, A., Jordan, E. J., Omuro, A., et al. (2019) · Nature Genetics · doi:10.1038/s41588-018-0312-8 · Cited by 4,071 · see citing works
Genomic and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic Melanoma
Hugo, W., Zaretsky, J. M., Sun, L., Song, C., Moreno, B. H., Hu-Lieskovan, S., Berent-Maoz, B., Pang, J., Chmielowski, B., Cherry, G., et al. (2016) · Cell · doi:10.1016/j.cell.2016.02.065 · Cited by 3,448 · see citing works
Approaches to treat immune hot, altered and cold tumours with combination immunotherapies
Galon, J., & Bruni, D. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-018-0007-y · Cited by 3,414 · see citing works
Pembrolizumab plus axitinib versus sunitinib for advanced renal-cell carcinoma
Rini, B. I., Plimack, E. R., Stus, V., Gafanov, R., Hawkins, R., Nosov, D., Pouliot, F., Alekseev, B., Soulières, D., Melichar, B., et al. (2019) · New England Journal of Medicine · doi:10.1056/nejmoa1816714 · Cited by 3,403 · see citing works
Pembrolizumab for Early Triple-Negative Breast Cancer
Schmid, P., Cortes, J., Pusztai, L., McArthur, H., Kümmel, S., Bergh, J., Denkert, C., Park, Y. H., Hui, R., Harbeck, N., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa1910549 · Cited by 3,270 · see citing works
Mutations Associated with Acquired Resistance to PD-1 Blockade in Melanoma
Zaretsky, J. M., Garcia-Diaz, A., Shin, D. S., Escuin-Ordinas, H., Hugo, W., Hu-Lieskovan, S., Torrejon, D. Y., Abril-Rodriguez, G., Sandoval, S., Barthly, L., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1604958 · Cited by 3,237 · see citing works
The prognostic landscape of genes and infiltrating immune cells across human cancers
Gentles, A. J., Newman, A. M., Liu, C. L., Bratman, S. V., Feng, W., Kim, D., Nair, V. S., Xu, Y., Khuong, A., Hoang, C. D., et al. (2015) · Nature Medicine · doi:10.1038/nm.3909 · Cited by 3,097 · see citing works
Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer
Wang, Y., Klijn, J. G. M., Zhang, Y., Sieuwerts, A. M., Look, M. P., Yang, F., Talantov, D., Timmermans, M. A. M., Gelder, M. E. M., Yu, J. X., et al. (2005) · The Lancet · doi:10.1016/s0140-6736(05)17947-1 · Cited by 2,848 · see citing works
Self-citationMelanoma-intrinsic β-catenin signalling prevents anti-tumour immunity
Spranger, S., Bao, R., & Gajewski, T. F. (2015) · Nature · doi:10.1038/nature14404 · Cited by 2,830 · see citing works
B cells and tertiary lymphoid structures promote immunotherapy response
Helmink, B. A., Reddy, S. M., Gao, J., Zhang, S., Basar, R., Thakur, R., Yizhak, K., Sade-Feldman, M., Blando, J., Han, G., et al. (2020) · Nature · doi:10.1038/s41586-019-1922-8 · Cited by 2,731 · see citing works
T cell exclusion, immune privilege, and the tumor microenvironment
Joyce, J. A., & Fearon, D. T. (2015) · Science · doi:10.1126/science.aaa6204 · Cited by 2,494 · see citing works
iRECIST: guidelines for response criteria for use in trials testing immunotherapeutics
Seymour, L., Bogaerts, J., Perrone, A., Ford, R., Schwartz, L. H., Mandrekar, S., Lin, N. U., Litière, S., Dancey, J., Chen, A., et al. (2017) · The Lancet Oncology · doi:10.1016/s1470-2045(17)30074-8 · Cited by 2,472 · see citing works
Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab
Riaz, N., Havel, J. J., Makarov, V., Desrichard, A., Urba, W. J., Sims, J. S., Hodi, F. S., Martín-Algarra, S., Mandal, R., Sharfman, W. H., et al. (2017) · Cell · doi:10.1016/j.cell.2017.09.028 · Cited by 2,401 · see citing works
Tertiary lymphoid structures improve immunotherapy and survival in melanoma
Cabrita, R., Lauss, M., Sanna, A., Donia, M., Skaarup Larsen, M., Mitra, S., Johansson, I., Phung, B., Harbst, K., Vallon-Christersson, J., et al. (2020) · Nature · doi:10.1038/s41586-019-1914-8 · Cited by 2,374 · see citing works
Landscape of somatic mutations in 560 breast cancer whole-genome sequences
Nik-Zainal, S., Davies, H., Staaf, J., Ramakrishna, M., Glodzik, D., Zou, X., Martincorena, I., Alexandrov, L. B., Martin, S., Wedge, D. C., et al. (2016) · Nature · doi:10.1038/nature17676 · Cited by 2,218 · see citing works
Self-citationDenkert, C., von Minckwitz, G., Darb-Esfahani, S., Lederer, B., Heppner, B. I., Weber, K. E., Budczies, J., Huober, J., Klauschen, F., Furlanetto, J., et al. (2018) · The Lancet Oncology · doi:10.1016/s1470-2045(17)30904-x · Cited by 2,157 · see citing works
Sotiriou, C. P., Wirapati, P., Loi, S., Harris, A. L., Fox, S., Smeds, J., Nordgren, H., Farmer, P. J., Praz, V., Haibe‐Kains, B., et al. (2006) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djj052 · Cited by 2,060 · see citing works
MiXCR: software for comprehensive adaptive immunity profiling
Bolotin, D. A., Poslavskii, S., Mitrophanov, I., Shugay, M., Mamedov, I. Z., Putintseva, E. V., & Chudakov, D. M. (2015) · Nature Methods · doi:10.1038/nmeth.3364 · Cited by 1,730 · see citing works
IL-17-producing γδ T cells and neutrophils conspire to promote breast cancer metastasis
Coffelt, S. B., Kersten, K., Doornebal, C. W., Weiden, J., Vrijland, K., Hau, C.-S., Verstegen, N. J. M., Ciampricotti, M., Hawinkels, L. J. A. C., Jonkers, J., et al. (2015) · Nature · doi:10.1038/nature14282 · Cited by 1,703 · see citing works
Spranger, S., Spaapen, R. M., Zha, Y., Williams, J., Meng, Y., Ha, T. T., & Gajewski, T. F. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3006504 · Cited by 1,677 · see citing works
Tumour-intrinsic resistance to immune checkpoint blockade
Kalbasi, A. K., & Ribas, A. (2019) · Nature reviews. Immunology · doi:10.1038/s41577-019-0218-4 · Cited by 1,491 · see citing works
Spranger, S., Dai, D., Horton, B., & Gajewski, T. F. (2017) · Cancer Cell · doi:10.1016/j.ccell.2017.04.003 · Cited by 1,441 · see citing works
A Cancer Cell Program Promotes T Cell Exclusion and Resistance to Checkpoint Blockade
Jerby-Arnon, L., Shah, P., Cuoco, M. S., Rodman, C., Su, M.-J., Melms, J. C., Leeson, R., Kanodia, A., Mei, S., Lin, J.-R., et al. (2018) · Cell · doi:10.1016/j.cell.2018.09.006 · Cited by 1,429 · see citing works
Improved Docking of Polypeptides with Glide
Tubert-Brohman, I., Sherman, W., Repasky, M., & Beuming, T. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci400128m · Cited by 1,308 · see citing works
Loi, S., Michiels, S., Salgado, R., Sirtaine, N., José, V., Fumagalli, D., Kellokumpu‐Lehtinen, P., Bono, P., Kataja, V. V., Desmedt, C., et al. (2014) · Annals of Oncology · doi:10.1093/annonc/mdu112 · Cited by 1,257 · see citing works
Self-citationSchmid, P., Rugo, H. S., Adams, S., Schneeweiss, A., Barrios, C. H., Iwata, H., Diéras, V., Henschel, V., Molinero, L., Chui, S. Y., et al. (2020) · The Lancet Oncology · doi:10.1016/s1470-2045(19)30689-8 · Cited by 1,216 · see citing works
Keren, L., Bosse, M., Marquez, D., Angoshtari, R., Jain, S., Varma, S., Yang, S.-R., Kurian, A., Van Valen, D., West, R., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.039 · Cited by 1,183 · see citing works
Hegde, P. S., Karanikas, V., & Evers, S. (2016) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-15-1507 · Cited by 1,000 · see citing works
Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab), Savas, P., Virassamy, B., Ye, C., Salim, A., Mintoff, C. P., Caramia, F., Salgado, R., Byrne, D. J., Teo, Z. L., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0078-7 · Cited by 992 · see citing works
Self-citationDesmedt, C., Piette, F., Loi, S., Wang, Y., Lallemand, F., Haibe‐Kains, B., Viale, G., Delorenzi, M., Zhang, Y., Saghatchian, M., et al. (2007) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-06-2765 · Cited by 970 · see citing works
Voorwerk, L., Slagter, M., Horlings, H. M., Sikorska, K., de Vijver, K. K. V., de Maaker, M., Nederlof, I., Kluin, R. J. C., Warren, S., Ong, S., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0432-4 · Cited by 912 · see citing works
Self-citationLoi, S., Drubay, D., Adams, S., Pruneri, G., Francis, P. A., Lacroix-Triki, M., Joensuu, H., Dieci, M. V., Badve, S., Demaria, S., et al. (2019) · Journal of Clinical Oncology · doi:10.1200/jco.18.01010 · Cited by 893 · see citing works
Self-citationThe Humoral Immune System Has a Key Prognostic Impact in Node-Negative Breast Cancer
Schmidt, M., Böhm, D., von Törne, C., Steiner, E., Puhl, A. G., Pilch, H., Lehr, H., Hengstler, J. G., KÖLBL, H., & Gehrmann, M. C. (2008) · Cancer Research · doi:10.1158/0008-5472.can-07-5206 · Cited by 837 · see citing works
Lundegaard, C., Lamberth, K., Harndahl, M. N., Buus, S., Lund, O., & Nielsen, M. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn202 · Cited by 808 · see citing works
Emens, L. A., Cruz, C., Eder, J. P., Braiteh, F., Chung, C. T., Tolaney, S. M., Kuter, I., Nanda, R., Cassier, P. A., Delord, J., et al. (2018) · JAMA Oncology · doi:10.1001/jamaoncol.2018.4224 · Cited by 775 · see citing works
Frozen robust multiarray analysis (fRMA)
McCall, M. N., Bolstad, B. M., & Irizarry, R. A. (2010) · Biostatistics · doi:10.1093/biostatistics/kxp059 · Cited by 592 · see citing works
Spatially distinct tumor immune microenvironments stratify triple-negative breast cancers
Gruosso, T., Gigoux, M., Manem, V. S., Bertos, N., Zuo, D., Perlitch, I., Saleh, S. M. I., Zhao, H., Souleimanova, M., Johnson, R. M., et al. (2019) · Journal of Clinical Investigation · doi:10.1172/jci96313 · Cited by 445 · see citing works
Self-citationLung metastasis genes couple breast tumor size and metastatic spread
Minn, A. J., Gupta, G. P., Padua, D., Bos, P., Nguyen, D. X., Nuyten, D., Kreike, B., Zhang, Y., Wang, Y., Ishwaran, H., et al. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0701138104 · Cited by 400 · see citing works
Trujillo, J., Sweis, R. F., Bao, R., & Luke, J. J. (2018) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-18-0277 · Cited by 392 · see citing works
Mechanisms regulating T-cell infiltration and activity in solid tumors
Lanitis, E., Dangaj, D., Irving, M., & Coukos, G. (2017) · Annals of Oncology · doi:10.1093/annonc/mdx238 · Cited by 369 · see citing works
Recent advances in triple negative breast cancer: the immunotherapy era
Marra, A., Viale, G., & Curigliano, G. (2019) · BMC Medicine · doi:10.1186/s12916-019-1326-5 · Cited by 352 · see citing works
Molecular Drivers of the Non–T-cell-Inflamed Tumor Microenvironment in Urothelial Bladder Cancer
Sweis, R. F., Spranger, S., Bao, R., Paner, G. P., Stadler, W. M., Steinberg, G. D., & Gajewski, T. F. (2016) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-15-0274 · Cited by 351 · see citing works
Lim, S., Li, C., Xia, W., Lee, H., Chang, S.-S., Shen, J., Hsu, J. L., Raftery, D., Djukovic, D., Gu, H., et al. (2016) · Cancer Research · doi:10.1158/0008-5472.can-15-2478 · Cited by 263 · see citing works
tcR: an R package for T cell receptor repertoire advanced data analysis
Nazarov, V. I., Pogorelyy, M. V., Komech, E. A., Zvyagin, I. V., Bolotin, D. A., Shugay, M., Chudakov, D. M., Lebedev, Y. B., & Mamedov, I. Z. (2015) · BMC Bioinformatics · doi:10.1186/s12859-015-0613-1 · Cited by 223 · see citing works
Checkpoint inhibitors in triple‐negative breast cancer (TNBC): Where to go from here
Kwa, M. J., & Adams, S. (2018) · Cancer · doi:10.1002/cncr.31272 · Cited by 213 · see citing works
on behalf of the MATCH study group, Smid, M., van den Braak, R. R. J. C., van de Werken, H. J. G., van Riet, J., van Galen, A., de Weerd, V., van der Vlugt‐Daane, M., Bril, S. I., Lalmahomed, Z. S., et al. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2246-7 · Cited by 208 · see citing works
Self-citationDNA methyltransferase expression in triple-negative breast cancer predicts sensitivity to decitabine
Yu, J., Qin, B., Moyer, A. M., Nowsheen, S., Liu, T., Qin, S., Zhuang, Y., Liu, D., Lu, W., Kalari, K. R., et al. (2018) · Journal of Clinical Investigation · doi:10.1172/jci97924 · Cited by 203 · see citing works
Knudson, K. M., Hicks, K. C., Luo, X., Chen, J.-Q., Schlom, J., & Gameiro, S. R. (2018) · OncoImmunology · doi:10.1080/2162402x.2018.1426519 · Cited by 195 · see citing works
Castagnoli, L., Cancila, V., Cordoba-Romero, S. L., Faraci, S., Talarico, G., Belmonte, B., Iorio, M. V., Milani, M., Volpari, T., Chiodoni, C., et al. (2019) · Oncogene · doi:10.1038/s41388-019-0700-2 · Cited by 184 · see citing works
Li, T., Huang, H., Shi, G., Zhao, L., Li, T., Zhang, Z., Liu, R., Hu, Y., Liu, H., Yu, J., et al. (2018) · Cell Death and Disease · doi:10.1038/s41419-018-0877-2 · Cited by 179 · see citing works
Breast cancer genomics and immuno-oncological markers to guide immune therapies
Hammerl, D., Smid, M., Timmermans, A. M., Sleijfer, S., Martens, J. W. M., & Debets, R. (2017) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2017.11.003 · Cited by 152 · see citing works
Self-citationNasser, M. W., Wani, N. A., Ahirwar, D. K., Powell, C. A., Ravi, J., Elbaz, M., Zhao, H., Padilla, L., Zhang, X., Shilo, K., et al. (2015) · Cancer Research · doi:10.1158/0008-5472.can-14-2161 · Cited by 151 · see citing works
Infiltration of CD8 + T cells into tumor cell clusters in triple-negative breast cancer
Li, X., Gruosso, T., Zuo, D., Ömeroğlu, A., Meterissian, S. H., Guiot, M., Salazar, A., Park, M., & Levine, H. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1817652116 · Cited by 134 · see citing works
Smid, M., Rodríguez-González, F. G., Sieuwerts, A. M., Salgado, R., der Smissen, W. J. C. P., van der Vlugt‐Daane, M., van Galen, A., Nik‐Zainal, S., Staaf, J., Brinkman, A. B., et al. (2016) · Nature Communications · doi:10.1038/ncomms12910 · Cited by 104 · see citing works
Self-citationHigh expression of COL10A1 is associated with poor prognosis in colorectal cancer
Huang, H., Li, T., Ye, G., Zhao, L., Zhang, Z., Mo, D., Wang, Y., Zhang, C., Deng, H., Li, G., et al. (2018) · OncoTargets and Therapy · doi:10.2147/ott.s160196 · Cited by 81 · see citing works
COL10A1 Expression is Elevated in Diverse Solid Tumor Types and is Associated with Tumor Vasculature
Chapman, K. B., Prendes, M. J., Sternberg, H., Kidd, J. L., Funk, W. D., Wagner, J., & West, M. D. (2012) · Future Oncology · doi:10.2217/fon.12.79 · Cited by 73 · see citing works
TCR-engineered T cells to treat tumors: Seeing but not touching?
Debets, R., Donnadieu, E., Chouaı̈b, S., & Coukos, G. (2016) · Seminars in Immunology · doi:10.1016/j.smim.2016.03.002 · Cited by 73 · see citing works
Self-citationCancer chromosomes going to POT1
Chang, S. S. (2013) · Nature Genetics · doi:10.1038/ng.2617 · Cited by 64 · see citing works
Hammerl, D., Massink, M. P. G., Smid, M., van Deurzen, C. H. M., Meijers-Heijboer, H. E. J., Waisfisz, Q., Debets, R., & Martens, J. W. M. (2019) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-19-0285 · Cited by 46 · see citing works
Self-citationExpanding the Role for Immunotherapy in Triple-Negative Breast Cancer
Savas, P. S., & Loi, S. (2020) · Cancer Cell · doi:10.1016/j.ccell.2020.04.007 · Cited by 45 · see citing works
Molinero, L. L., Li, Y., Chang, C., Maund, S. L., Berg, M., Harrison, J., Fassò, M., O'Hear, C. E., Hegde, P. S., & Emens, L. A. (2019) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-019-0740-8 · Cited by 34 · see citing works
Lee, J., Zimmer, A. D. S., Lipkowitz, S., Annunziata, C. M., Ho, T. W., Chiou, V. L., Minasian, L. M., Houston, N. D., Ekwede, I., & Kohn, E. C. (2016) · Journal of Clinical Oncology · doi:10.1200/jco.2016.34.15_suppl.3015 · Cited by 31 · see citing works
Lu, F., Lamontagne, J., Sun, A., et al. (2011) · Immunology · doi:10.1111/j.1365-2567.2011.03498.x · Cited by 23 · see citing works
Therapeutic vaccination with 4–1BB co-stimulation eradicates mouse acute myeloid leukemia
Kerage, D., Soon, M. S. F., Doff, B. L., Kobayashi, T., Nissen, M. D., Lam, P. Y., Leggatt, G. R., & Mattarollo, S. R. (2018) · OncoImmunology · doi:10.1080/2162402x.2018.1486952 · Cited by 19 · see citing works
Zhu, Y. X., Fu, H., Liu, Z., et al. (2018) · European Urology Supplements · doi:10.1016/s1569-9056(18)30940-0 · Cited by 3 · see citing works
Re: Evasion of Immunosurveillance by Genomic Alterations of PPARγ/RXRα in Bladder Cancer
Atala, A. (2018) · The Journal of Urology · doi:10.1016/j.juro.2018.02.015 · Cited by 1 · see citing works
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The technological landscape and applications of single-cell multi-omics
Baysoy, A., Bai, Z., Satija, R., & Fan, R. (2023) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-023-00615-w · Cited by 1,037 · see citing works
- Authors
- Hammerl, D., Martens, J. W. M., Timmermans, M., Smid, M., Trapman-Jansen, A. M., Foekens, R., Isaeva, O. I., Voorwerk, L., Balcioglu, H. E., Wijers, R., Nederlof, I., Salgado, R., Horlings, H., Kok, M., & Debets, R.
- Affiliations
- Erasmus MC Cancer Institute (NL)
- The Netherlands Cancer Institute (NL)
- Peter MacCallum Cancer Centre (AU)
- Corresponding author
- Kok, Marleen
- Debets, Reno
- ORCID
- Venue
- Nature Communications
- Published
- 2021-09-27
- Volume
- 12
- Issue
- 1
- Pages
- 5668-5668
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC8476574
- OpenAlex
- W3202723367
- Cited by
- 262
- References
- 77
- Citations by year
- 2026: 63 · 2025: 54 · 2024: 62 · 2023: 49 · 2022: 32 · 2021: 1
- FWCI
- 13.64
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, cc-by)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Pure Amsterdam UMC (submittedVersion, cc-by)
- Funders
- KWF Kankerbestrijding (2014-7087)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Keywords
- triple-negative breast cancer, anti-PD-1 therapy, immune checkpoint inhibitors, treatment response prediction, TCR clonality, tumor necrosis, gene classifier
- MeSH terms
- RNA-Seq, Immune Checkpoint Inhibitors, CD163 Antigen, Adult, Breast, Female, Humans, Mastectomy, Prognosis, Receptors, Cell Surface, T-Lymphocytes, Antigens, Differentiation, Myelomonocytic, Cohort Studies, Antigens, CD, Immunophenotyping, Lymphocytes, Tumor-Infiltrating, Drug Resistance, Neoplasm, Tumor Escape, Neoadjuvant Therapy, Tumor Microenvironment, Wnt Signaling Pathway, Programmed Cell Death 1 Receptor, Spatial Analysis, Triple Negative Breast Neoplasms, Datasets as Topic
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