Functional and spatial proteomics profiling reveals intra- and intercellular signaling crosstalk in colorectal cancer
Open accessPublished version of a preprint
Abstract
Precision oncology approaches for patients with colorectal cancer (CRC) continue to lag behind other solid cancers. Functional precision oncology-a strategy that is based on perturbing primary tumor cells from cancer patients-could provide a road forward to personalize treatment. We extend this paradigm to measuring proteome activity landscapes by acquiring quantitative phosphoproteomic data from patient-derived organoids (PDOs). We show that kinase inhibitors induce inhibitor- and patient-specific off-target effects and pathway crosstalk. Reconstruction of the kinase networks revealed that the signaling rewiring is modestly affected by mutations. We show non-genetic heterogeneity of the PDOs and upregulation of stemness and differentiation genes by kinase inhibitors. Using imaging mass-cytometry-based profiling of the primary tumors, we characterize the tumor microenvironment (TME) and determine spatial heterocellular crosstalk and tumor-immune cell interactions. Collectively, we provide a framework for inferring tumor cell intrinsic signaling and external signaling from the TME to inform precision (immuno-) oncology in CRC.
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
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.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method
Livak, K. J., & Schmittgen, T. D. (2001) · Methods · doi:10.1006/meth.2001.1262 · Cited by 180,860 · see citing works
Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F. (2021) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21660 · Cited by 108,699 · 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
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
Yu, G., Wang, L.-G., Han, Y., & He, Q.-Y. (2012) · OMICS: A Journal of Integrative Biology · doi:10.1089/omi.2011.0118 · Cited by 36,259 · see citing works
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179 · see citing works
GSVA: gene set variation analysis for microarray and RNA-Seq data
Hänzelmann, S., Castelo, R., & Guinney, J. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-7 · Cited by 15,440 · see citing works
The Molecular Signatures Database Hallmark Gene Set Collection
Liberzon, A., Birger, C., Thorvaldsdóttir, H., Ghandi, M., Mesirov, J. P., & Tamayo, P. (2015) · Cell Systems · doi:10.1016/j.cels.2015.12.004 · Cited by 13,807 · see citing works
Complex heatmaps reveal patterns and correlations in multidimensional genomic data
Gu, Z., Eils, R., & Schlesner, M. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw313 · Cited by 10,122 · see citing works
The igraph software package for complex network research
Csárdi, G., & Nepusz, T. (2006) · Medical Entomology and Zoology · Cited by 10,078 · see citing works
Hallmarks of Cancer: New Dimensions
Hanahan, D. (2022) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-1059 · Cited by 9,887 · see citing works
PD-1 Blockade in Tumors with Mismatch-Repair Deficiency
Le, D. T., Uram, J. N., Wang, H., Bartlett, B. R., Kemberling, H., Eyring, A. D., Skora, A. D., Luber, B. S., Azad, N. S., Laheru, D., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1500596 · Cited by 9,377 · see citing works
SCANPY: large-scale single-cell gene expression data analysis
Wolf, F. A., Angerer, P., & Theis, F. J. (2018) · Genome Biology · doi:10.1186/s13059-017-1382-0 · Cited by 8,881 · see citing works
Comprehensive molecular characterization of human colon and rectal cancer
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11252 · Cited by 8,499 · see citing works
UniProt: a worldwide hub of protein knowledge
The UniProt Consortium (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1049 · Cited by 7,698 · see citing works
Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade
Le, D. T., Durham, J. N., Smith, K. N., Wang, H., Bartlett, B. R., Aulakh, L. K., Lu, S., Kemberling, H., Wilt, C., Luber, B. S., et al. (2017) · Science · doi:10.1126/science.aan6733 · Cited by 6,645 · 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
Self-citationFrom Louvain to Leiden: guaranteeing well-connected communities
Traag, V. A., Waltman, L., & van Eck, N. J. (2019) · Scientific Reports · doi:10.1038/s41598-019-41695-z · Cited by 5,635 · see citing works
Dimensionality reduction for visualizing single-cell data using UMAP
Becht, E., McInnes, L., Healy, J., Dutertre, C.-A., Kwok, I. W. H., Ng, L. G., Ginhoux, F., & Newell, E. W. (2019) · Nature Biotechnology · doi:10.1038/nbt.4314 · Cited by 5,358 · see citing works
UniProt: a hub for protein information
The UniProt Consortium (2015) · Nucleic Acids Research · doi:10.1093/nar/gku989 · Cited by 5,106 · see citing works
CellProfiler: image analysis software for identifying and quantifying cell phenotypes
Carpenter, A. E., Jones, T. R., Lamprecht, M. R., Clarke, C., Kang, I. H., Friman, O., Guertin, D. A., Chang, J. H., Lindquist, R. A., Moffat, J., et al. (2006) · Genome biology · doi:10.1186/gb-2006-7-10-r100 · Cited by 5,077 · see citing works
La Manno, G., Soldatov, R., Zeisel, A., Braun, E., Hochgerner, H., Petukhov, V., Lidschreiber, K., Kastriti, M. E., Lönnerberg, P., Furlan, A., et al. (2018) · Nature · doi:10.1038/s41586-018-0414-6 · Cited by 4,118 · see citing works
The nf-core framework for community-curated bioinformatics pipelines
Ewels, P., Peltzer, A., Fillinger, S., Patel, H., Alneberg, J., Wilm, A., Garcia, M., Tommaso, P. D., & Nahnsen, S. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0439-x · Cited by 4,028 · see citing works
Mutation of the mouse klotho gene leads to a syndrome resembling ageing
Kuro-o, M., Matsumura, Y., Aizawa, H., Kawaguchi, H., Suga, T., Utsugi, T., Ohyama, Y., Kurabayashi, M., Kaname, T., Kume, E., et al. (1997) · Nature · doi:10.1038/36285 · Cited by 3,837 · see citing works
Sato, T., Stange, D. E., Ferrante, M., Vries, R. G. J., van Es, J. H., van den Brink, S., van Houdt, W. J., Pronk, A., van Gorp, J., Siersema, P. D., et al. (2011) · Gastroenterology · doi:10.1053/j.gastro.2011.07.050 · Cited by 3,753 · see citing works
Self-citationOrganoid Models and Applications in Biomedical Research
Xinaris, C., Brizi, V., & Remuzzi, G. (2015) · The Nephron journals/Nephron journals · doi:10.1159/000433566 · Cited by 3,517 · see citing works
ilastik: interactive machine learning for (bio)image analysis
Berg, S., Kutra, D., Kroeger, T., Straehle, C., Kausler, B. X., Haubold, C., Schiegg, M., Aleš, J., Beier, T., Rudy, M., et al. (2019) · Nature Methods · doi:10.1038/s41592-019-0582-9 · Cited by 3,277 · see citing works
Generalizing RNA velocity to transient cell states through dynamical modeling
Bergen, V., Lange, M., Peidli, S., Wolf, F. A., & Theis, F. J. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0591-3 · Cited by 2,951 · see citing works
Gillet, L. C., Navarro, P., Tate, S., Röst, H., Selevsek, N., Reiter, L., Bonner, R., & Aebersold, R. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o111.016717 · Cited by 2,877 · see citing works
Self-citationBatlle, E., & Clevers, H. (2017) · Nature Medicine · doi:10.1038/nm.4409 · Cited by 2,769 · see citing works
Self-citationDeep generative modeling for single-cell transcriptomics
Lopez, R., Regier, J., Cole, M. B., Jordan, M. I., & Yosef, N. (2018) · Nature Methods · doi:10.1038/s41592-018-0229-2 · Cited by 2,530 · see citing works
Prospective Derivation of a Living Organoid Biobank of Colorectal Cancer Patients
van de Wetering, M., Francies, H. E., Francis, J. M., Bounova, G., Iorio, F., Pronk, A., van Houdt, W., van Gorp, J., Taylor-Weiner, A., Kester, L., et al. (2015) · Cell · doi:10.1016/j.cell.2015.03.053 · Cited by 2,408 · see citing works
Self-citationPatient-derived organoids model treatment response of metastatic gastrointestinal cancers
Vlachogiannis, G., Hedayat, S., Vatsiou, A., Jamin, Y., Fernández-Mateos, J., Khan, K., Lampis, A., Eason, K., Huntingford, I., Burke, R., et al. (2018) · Science · doi:10.1126/science.aao2774 · Cited by 2,096 · see citing works
Drost, J., & Clevers, H. (2018) · Nature Reviews Cancer · doi:10.1038/s41568-018-0007-6 · Cited by 1,790 · see citing works
Self-citationA compendium of mutational cancer driver genes
Martínez-Jiménez, F., Muiños, F., Sentís, I., Deu-Pons, J., Reyes-Salazar, I., Arnedo-Pac, C., Mularoni, L., Pich, O., Bonet, J., Kranas, H., et al. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-020-0290-x · Cited by 1,278 · see citing works
Tumor Interferon Signaling Regulates a Multigenic Resistance Program to Immune Checkpoint Blockade
Benci, J. L., Xu, B., Qiu, Y., Wu, T. J., Dada, H., Twyman-Saint Victor, C., Cucolo, L., Lee, D. S. M., Pauken, K. E., Huang, A. C., et al. (2016) · Cell · doi:10.1016/j.cell.2016.11.022 · Cited by 1,216 · see citing works
Data‐independent acquisition‐based SWATH‐MS for quantitative proteomics: a tutorial
Ludwig, C., Gillet, L. C. J., Rosenberger, G., Amon, S., Collins, B. C., & Aebersold, R. H. (2018) · Molecular Systems Biology · doi:10.15252/msb.20178126 · Cited by 999 · see citing works
Self-citationSadanandam, A., Lyssiotis, C. A., Homicsko, K., Collisson, E. A., Gibb, W. J., Wullschleger, S., Ostos, L. C. G., Lannon, W. A., Grotzinger, C., Del Rio, M., et al. (2013) · Nature Medicine · doi:10.1038/nm.3175 · Cited by 960 · see citing works
Quantitative Proteomics of the Cancer Cell Line Encyclopedia
Nusinow, D. P., Szpyt, J., Ghandi, M., Rose, C. M., McDonald, E. R., Kalocsay, M., Jané-Valbuena, J., Gelfand, E., Schweppe, D. K., Jedrychowski, M., et al. (2020) · Cell · doi:10.1016/j.cell.2019.12.023 · Cited by 957 · see citing works
MSIsensor: microsatellite instability detection using paired tumor-normal sequence data
Niu, B., Ye, K., Zhang, Q., Lu, C., Xie, M., McLellan, M. D., Wendl, M. C., & Ding, L. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt755 · Cited by 822 · see citing works
Ooft, S. N., Weeber, F., Dijkstra, K. K., McLean, C. M., Kaing, S., van Werkhoven, E., Schipper, L., Hoes, L., Vis, D. J., van de Haar, J., et al. (2019) · Science Translational Medicine · doi:10.1126/scitranslmed.aay2574 · Cited by 813 · see citing works
Self-citationProteogenomic Analysis of Human Colon Cancer Reveals New Therapeutic Opportunities
Vasaikar, S., Huang, C., Wang, X., Petyuk, V. A., Savage, S. R., Wen, B., Dou, Y., Zhang, Y., Shi, Z., Arshad, O. A., et al. (2019) · Cell · doi:10.1016/j.cell.2019.03.030 · Cited by 799 · see citing works
Colorectal carcinoma: Pathologic aspects.
Fleming, M., Ravula, S., Tatishchev, S. F., & Wang, H. L. (2012) · PubMed Central · doi:10.3978/j.issn.2078-6891.2012.030 · Cited by 734 · see citing works
Intra-tumour diversification in colorectal cancer at the single-cell level
Roerink, S. F., Sasaki, N., Lee-Six, H., Young, M. D., Alexandrov, L. B., Behjati, S., Mitchell, T. J., Großmann, S., Lightfoot, H. W., Egan, D. A., et al. (2018) · Nature · doi:10.1038/s41586-018-0024-3 · Cited by 554 · see citing works
Self-citationUltra‐high sensitivity mass spectrometry quantifies single‐cell proteome changes upon perturbation
Brunner, A., Thielert, M., Vasilopoulou, C., Ammar, C., Coscia, F., Mund, A., Hoerning, O. B., Bache, N., Apalategui, A., Lubeck, M., et al. (2022) · Molecular Systems Biology · doi:10.15252/msb.202110798 · Cited by 544 · see citing works
Benci, J. L., Johnson, L. R., Choa, R., Xu, Y., Qiu, J., Zhou, Z., Xu, B., Ye, D., Nathanson, K. L., June, C. H., et al. (2019) · Cell · doi:10.1016/j.cell.2019.07.019 · Cited by 541 · see citing works
Genetic Mechanisms of Immune Evasion in Colorectal Cancer
Grasso, C. S., Giannakis, M., Wells, D. K., Hamada, T., Mu, X. J., Quist, M., Nowak, J. A., Nishihara, R., Qian, Z. R., Inamura, K., et al. (2018) · Cancer Discovery · doi:10.1158/2159-8290.cd-17-1327 · Cited by 535 · cited 1× · see citing works
“Genomic characterization including CRC driver genes [49] and a 538 panel of immune-related genes frequently mutated in CRC [50] reaffirmed previously reported so539 matic alterations [50] and showed that the biobank is representative of CRC (Figure 2A, Supplemen540 tary Figure 1B).”
BackgroundJoanito, I., Wirapati, P., Zhao, N., Nawaz, Z., Yeo, G., Lee, F., Eng, C. L. P., Macalinao, D. C., Kahraman, M., Srinivasan, H., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01100-4 · Cited by 434 · see citing works
A repository of assays to quantify 10,000 human proteins by SWATH-MS
Rosenberger, G., Koh, C. C., Guo, T., Röst, H. L., Kouvonen, P., Collins, B. C., Heusel, M., Liu, Y., Caron, E., Vichalkovski, A., et al. (2014) · Scientific Data · doi:10.1038/sdata.2014.31 · Cited by 413 · see citing works
Self-citationAn ex vivo tumor fragment platform to dissect response to PD-1 blockade in cancer
Voabil, P., de Bruijn, M., Roelofsen, L. M., Hendriks, S. H., Brokamp, S., van den Braber, M., Broeks, A., Sanders, J., Herzig, P., Zippelius, A., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01398-3 · Cited by 380 · see citing works
The dynamic control of signal transduction networks in cancer cells
Kölch, W., Halász, M., Granovskaya, M., & Kholodenko, B. Ν. (2015) · Nature reviews. Cancer · doi:10.1038/nrc3983 · Cited by 341 · see citing works
A Curated Resource for Phosphosite-specific Signature Analysis
Krug, K., Mertins, P., Zhang, B., Hornbeck, P. V., Raju, R., Ahmad, R., Szucs, M. J., Mundt, F., Forestier, D., Jané‐Valbuena, J., et al. (2018) · Molecular & Cellular Proteomics · doi:10.1074/mcp.tir118.000943 · Cited by 329 · see citing works
Patient-derived organoids as a predictive biomarker for treatment response in cancer patients
Wensink, G. E., Elias, S. G., Mullenders, J., Koopman, M., Boj, S. F., Kranenburg, O. W., & Roodhart, J. M. L. (2021) · npj Precision Oncology · doi:10.1038/s41698-021-00168-1 · Cited by 323 · see citing works
Holland, C. H., Tanevski, J., Perales-Patón, J., Gleixner, J., Kumar, M. P., Mereu, E., Joughin, B. A., Stegle, O., Lauffenburger, D. A., Heyn, H., et al. (2020) · Genome Biology · doi:10.1186/s13059-020-1949-z · Cited by 323 · see citing works
Letai, A. G., Bhola, P. D., & Welm, A. L. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.12.004 · Cited by 282 · see citing works
Solo: Doublet Identification in Single-Cell RNA-Seq via Semi-Supervised Deep Learning
Bernstein, N. J., Fong, N. L., Lam, I., Roy, M. A., Hendrickson, D. G., & Kelley, D. R. (2020) · Cell Systems · doi:10.1016/j.cels.2020.05.010 · Cited by 280 · see citing works
Precision oncology in metastatic colorectal cancer — from biology to medicine
Nicolantonio, F. D., Vitiello, P. P., Marsoni, S., Siena, S., Tabernero, J. M., Trusolino, L., Bernards, R., & Bardelli, A. (2021) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-021-00495-z · Cited by 238 · see citing works
van Unen, V., Höllt, T., Pezzotti, N., Li, N., Reinders, M. J. T., Eisemann, E., Koning, F., Vilanova, A., & Lelieveldt, B. P. F. (2017) · Nature Communications · doi:10.1038/s41467-017-01689-9 · Cited by 229 · see citing works
Phosphoproteome Integration Reveals Patient-Specific Networks in Prostate Cancer
Drake, J. M., Paull, E., Graham, N. A., Lee, J. K., Smith, B. A., Titz, B., Stoyanova, T. I., Faltermeier, C. M., Uzunangelov, V., Carlin, D. E., et al. (2016) · Cell · doi:10.1016/j.cell.2016.07.007 · Cited by 226 · see citing works
SIGNOR 2.0, the SIGnaling Network Open Resource 2.0: 2019 update
Licata, L., Surdo, P. L., Iannuccelli, M., Palma, A., Micarelli, E., Perfetto, L., Peluso, D., Calderone, A., Castagnoli, L., & Cesareni, G. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz949 · Cited by 212 · see citing works
Mitogen‐activated protein kinase activity drives cell trajectories in colorectal cancer
Uhlitz, F., Bischoff, P., Peidli, S., Sieber, A., Obermayer, B., Blanc, E., Trinks, A., Lüthen, M., Ruchiy, Y., Sell, T., et al. (2021) · EMBO Molecular Medicine · doi:10.15252/emmm.202114123 · Cited by 193 · see citing works
MEK inhibitors activate Wnt signalling and induce stem cell plasticity in colorectal cancer
Zhan, T., Ambrosi, G., Wandmacher, A. M., Rauscher, B., Betge, J., Rindtorff, N., Häussler, R. S., Hinsenkamp, I., Bamberg, L., Hessling, B., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09898-0 · Cited by 189 · see citing works
Miller, S. A., Policastro, R. A., Sriramkumar, S., Lai, T., Huntington, T. D., Ladaika, C. A., Kim, D.-H., Hao, C., Zentner, G. E., & O’Hagan, H. M. (2021) · Cancer Research · doi:10.1158/0008-5472.can-20-3562 · Cited by 180 · see citing works
Ijsselsteijn, M. E., van der Breggen, R., Sarasqueta, A. F., Koning, F., & de Miranda, N. F. C. C. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.02534 · Cited by 155 · see citing works
Self-citationKalaora, S., Lee, J. S., Barnea, E., Levy, R., Greenberg, P., Alon, M., Yagel, G., Eli, G. B., Oren, R., Peri, A., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-14639-9 · Cited by 153 · see citing works
Teo, G., Kim, S., Tsou, C., Collins, B. C., Gingras, A., Nesvizhskii, A. I., & Choi, H. (2015) · Journal of Proteomics · doi:10.1016/j.jprot.2015.09.013 · Cited by 145 · see citing works
Prospective experimental treatment of colorectal cancer patients based on organoid drug responses
Ooft, S., Weeber, F., Schipper, L. J., Dijkstra, K. K., McLean, C. M., Kaing, S., van de Haar, J., Prevoo, W., van Werkhoven, E. D., Snæbjörnsson, P., et al. (2021) · ESMO Open · doi:10.1016/j.esmoop.2021.100103 · Cited by 144 · see citing works
Farin, H. F., Mosa, M. H., Ndreshkjana, B., Grebbin, B. M., Ritter, B., Menche, C., Kennel, K. B., Ziegler, P. K., Szabó, L., Bollrath, J., et al. (2023) · Cancer Discovery · doi:10.1158/2159-8290.cd-23-0050 · Cited by 120 · see citing works
Self-citationSpatiotemporal variation of mammalian protein complex stoichiometries
Ori, A., Iskar, M., Buczak, K., Kastritis, P. L., Parca, L., Andrés‐Pons, A., Singer, S., Peer Bork, B., & Beck, M. (2016) · Genome biology · doi:10.1186/s13059-016-0912-5 · Cited by 108 · see citing works
Hijazi, M., Smith, R., Rajeeve, V., Bessant, C., & Cutillas, P. R. (2020) · Nature Biotechnology · doi:10.1038/s41587-019-0391-9 · Cited by 108 · see citing works
Korkut, A., Wang, W., Demir, E., Aksoy, B. A., Jing, X., Molinelli, E. J., Babur, Ö., Bemis, D. L., Sümer, S. O., Solit, D. B., et al. (2015) · eLife · doi:10.7554/elife.04640 · Cited by 99 · see citing works
Eduati, F., Doldàn-Martelli, V., Klinger, B., Cokelaer, T., Sieber, A., Kogera, F., Dorel, M., Garnett, M. J., Blüthgen, N., & Sáez-Rodríguez, J. (2017) · Cancer Research · doi:10.1158/0008-5472.can-17-0078 · Cited by 97 · see citing works
ImaCytE: Visual Exploration of Cellular Micro-Environments for Imaging Mass Cytometry Data
Somarakis, A., van Unen, V., Koning, F., Lelieveldt, B. P. F., & Höllt, T. (2019) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2019.2931299 · Cited by 92 · see citing works
Self-citationBuzzelli, J. N., Ouaret, D., Brown, G., Allen, P. D., & Muschel, R. J. (2018) · Stem Cell Research · doi:10.1016/j.scr.2018.01.016 · Cited by 86 · see citing works
Lupo, B., Sassi, F., Pinnelli, M., Galimi, F., Zanella, E. R., Vurchio, V., Migliardi, G., Gagliardi, P. A., Puliafito, A., Manganaro, D., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aax8313 · Cited by 83 · see citing works
Enhancing scientific discoveries in molecular biology with deep generative models
Lopez, R., Gayoso, A., & Yosef, N. (2020) · Molecular Systems Biology · doi:10.15252/msb.20199198 · Cited by 82 · see citing works
Why geneticists stole cancer research even though cancer is primarily a signaling disease
Yaffe, M. B. (2019) · Science Signaling · doi:10.1126/scisignal.aaw3483 · Cited by 65 · see citing works
Enfield, K. S. S., Martin, S. D., Marshall, E. A., Kung, S. H. Y., Gallagher, P., Milne, K., Chen, Z., Nelson, B. H., Lam, S. C., English, J. C., et al. (2019) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-018-0488-6 · Cited by 51 · see citing works
Disentangling Genetic and Environmental Effects on the Proteotypes of Individuals
Romanov, N., Kuhn, M., Aebersold, R. H., Ori, A., Beck, M., & Peer Bork, B. (2019) · Cell · doi:10.1016/j.cell.2019.03.015 · Cited by 48 · see citing works
Self-citationnextNEOpi: a comprehensive pipeline for computational neoantigen prediction
Rieder, D., Fotakis, G., Außerhofer, M., Geyeregger, R., Paster, W., Trajanoski, Z., & Finotello, F. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab759 · Cited by 48 · see citing works
Self-citationSystematic Pan-Cancer Analysis Identifies CDK1 as an Immunological and Prognostic Biomarker
Yang, Y., Liu, Q., Guo, X., Yuan, Q., Nian, S., Kang, P., Xu, Z., Li, L., & Ye, Y. (2022) · Journal of Oncology · doi:10.1155/2022/8115474 · Cited by 26 · see citing works
Plasticity in Colorectal Cancer: Why Cancer Cells Differentiate
Walter, R. J., Sonnentag, S. J., Orian‐Rousseau, V., & Muñoz‐Sagredo, L. (2021) · Cancers · doi:10.3390/cancers13040918 · Cited by 19 · see citing works
Wu, R., Tang, W., Qiu, K., Li, P., Li, Y., Li, D., & He, Z. (2021) · International Journal of General Medicine · doi:10.2147/ijgm.s330500 · Cited by 11 · see citing works
Flagged first, then by citations
4 of the 88 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Signaling pathways involved in colorectal cancer: pathogenesis and targeted therapy
Li, Q., Geng, S., Luo, H., Wang, W., Mo, Y.-Q., Luo, Q., Wang, L., Song, G.-B., Sheng, J.-P., & Xu, B. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01953-7 · Cited by 546 · see citing works
Xu, Z., Li, W., Dong, X., Chen, Y., Zhang, D., Wang, J. G., Zhou, L., & He, G. (2024) · Clinica Chimica Acta · doi:10.1016/j.cca.2024.119686 · Cited by 69 · see citing works
Current applications of intestinal organoids: a review
Xiang, T., Wang, J., & Li, H. (2024) · Stem Cell Research & Therapy · doi:10.1186/s13287-024-03768-3 · Cited by 62 · see citing works
Current state and future prospects of spatial biology in colorectal cancer
Carranza, F., Diaz, F. C., Ninova, M., & Velazquez-Villarreal, E. I. (2024) · Frontiers in Oncology · doi:10.3389/fonc.2024.1513821 · Cited by 37 · see citing works
Marteau, V., Nemati, N., Handler, K., Raju, D., Kirchmair, A., Rieder, D., Soto, E. K., Fotakis, G., de Lange, G., Carollo, S., et al. (2026) · Cancer Cell · doi:10.1016/j.ccell.2025.12.003 · Cited by 37 · see citing works
Self-citationMeyiah, A., Khan, F. I., Alfaki, D. A., Murshed, K., Raza, A., & Elkord, E. (2025) · Translational Oncology · doi:10.1016/j.tranon.2025.102307 · Cited by 30 · see citing works
Potential of CDC25 phosphatases in cancer research and treatment: key to precision medicine
Dakilah, I., Harb, A. A., Abu‐Gharbieh, E., El‐Huneidi, W., Taneera, J., Hamoudi, R., Semreen, M. H., & Bustanji, Y. K. (2024) · Frontiers in Pharmacology · doi:10.3389/fphar.2024.1324001 · Cited by 23 · see citing works
Advances in precision oncology using patient-derived organoids and functional biomaterials
Singh, H., Mijakovic̀, I., & Singh, P. (2025) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2025.1670328 · Cited by 14 · see citing works
Guedes, J., Woldmar, N., Szasz, A. M., Wieslander, E., Pawłowski, K., Horvatovich, P., Malm, J., Szadai, L., Németh, I. B., Marko-Varga, G., et al. (2025) · Journal of Proteomics · doi:10.1016/j.jprot.2025.105493 · Cited by 11 · see citing works
Paraskar, G., Bhattacharya, S., & Anitha, K. (2025) · ACS Pharmacology & Translational Science · doi:10.1021/acsptsci.4c00686 · Cited by 7 · see citing works
High-dimensional signalling analysis of organoids
Dobric, A., & Tape, C. J. (2025) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2025.102488 · Cited by 6 · see citing works
Studying Immunogenic Cell Death in Human Colorectal Cancer Organoids
Lisandrelli, R., Winkler, M., Trajanoski, Z., & Lamberti, G. (2025) · OncoTargets and Therapy · doi:10.2147/ott.s521346 · Cited by 6 · see citing works
Self-citationProtocol for functional profiling of patient-derived organoids for precision oncology
Nemati, N., Boeck, N., Lamberti, G., Lisandrelli, R., & Trajanoski, Z. (2024) · STAR Protocols · doi:10.1016/j.xpro.2024.102887 · Cited by 6 · see citing works
Self-citationMulti Omics Integration in Colorectal Cancer: From Molecular Insights to Precision Oncology
Liu, Z., Ang, M. Y., & Kue, C. S. (2026) · Cancers · doi:10.3390/cancers18101504 · Cited by 6 · see citing works
NovumRNA: Accurate prediction of non-canonical tumor antigens from RNA sequencing data
Außerhofer, M., Rieder, D., Facciolla, M., Gronauer, R., Lamberti, G., Lisandrelli, R., Pellegatta, S., Trajanoski, Z., & Finotello, F. (2025) · iScience · doi:10.1016/j.isci.2025.113448 · Cited by 3 · see citing works
Self-citationHydrogel design for intestinal organoids: principles governing translational regenerative medicine
Wang, Y., Cao, Z., Li, B., Huang, Y., Wang, G., & Chen, Q. (2025) · Biomaterials Science · doi:10.1039/d5bm00926j · Cited by 3 · see citing works
Heregger, R., Huemer, F., Greil, R., Cañadas-Ortega, M., Posselt, G., Ijsselsteijn, M. E., Plattner, C., Rieder, D., Trajanoski, Z., Krogsdam, A., et al. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1629014 · Cited by 3 · see citing works
Self-citationSingle-cell omics for nutrition research: an emerging opportunity for human-centric investigations
Cassotta, M., Díaz, Y. A., Cianciosi, D., Yang, B., Qi, Z., Chen, G., Villar, S. G., López, L. A. D., Grosso, G., Quiles, J. L., et al. (2025) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2025.2566387 · Cited by 1 · see citing works
Liu, Z., Ang, M. Y., & Kue, C. S. (2026) · doi:10.2196/preprints.95204 · Cited by 1 · see citing works
Single-cell analysis of colon cancer: Novel insight into drug resistance and immunotherapy
Bhamidipati, P., Kocharlakota, S. V., Katneni, V., & Malla, R. R. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-24742-2.00010-1
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
Self-citationChoi, H., Choi, S. M., Wang, S., & Chung, J. W. (2025) · Journal of Digestive Cancer Research · doi:10.52927/jdcr.2025.13.2.168
Zhang, P., Tang, X., Akanyibah, F. A., Du, S., & Mao, F. (2025) · Laboratory Investigation · doi:10.1016/j.labinv.2025.104256 · Cited by 1 · see citing works
The Evolving Landscape of Colorectal Organoids in Tissue Engineering: Research Trends and Hotspots
Gan, H., Huang, P., Wang, J., Gao, L., & Li, T. (2026) · Tissue Engineering Part C Methods · doi:10.1177/19373384261417822
Spatial proteomics: technical evolution and applications in cancer research
Tian, X., Huang, D., & Hu, J. (2026) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2026.1914317
Wan, K., Tang, K., Wang, L., Tian, Q., Zheng, M., Qian, C., & 刘丽梅 (2026) · MedComm · doi:10.1002/mco2.71028
Ramachandran, P., Chen, C. S. Y., Lee, C. S., Aye, T. T., Kunjukunju, A., Elias, M. H., Mydin, A. R., & Low, T. Y. (2026) · Expert Review of Proteomics · doi:10.1080/14789450.2026.2750129
- Authors
- Plattner, C., Lamberti, G., Blattmann, P., Kirchmair, A., Rieder, D., Loncova, Z., Sturm, G., Scheidl, S., Ijsselsteijn, M., Fotakis, G., Noureen, A., Lisandrelli, R., Böck, N., Nemati, N., Krogsdam, A., Daum, S., Finotello, F., Somarakis, A., Schäfer, A., Wilflingseder, D., Gonzalez Acera, M., Öfner, D., Huber, L. A., Clevers, H., Becker, C., Farin, H. F., Greten, F. R., Aebersold, R., de Miranda, N. F. C. C., & Trajanoski, Z.
- Affiliations
- Innsbruck Medical University (AT)
- ETH Zurich (CH)
- Leiden University Medical Center (NL)
- Hubrecht Institute for Developmental Biology and Stem Cell Research (NL)
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- Goethe University Frankfurt (DE)
- Corresponding author
- Trajanoski, Zlatko
- ORCID
- Plattner, Christina
- Lamberti, Giorgia
- Blattmann, Peter
- Kirchmair, Alexander
- Rieder, Dietmar
- Sturm, Gregor
- Scheidl, Stefan
- Ijsselsteijn, Marieke
- Fotakis, Georgios
- Noureen, Asma
- Nemati, Niloofar
- Krogsdam, Anne
- Daum, Sophia
- Finotello, Francesca
- Somarakis, Antonios
- Schäfer, Alexander
- Wilflingseder, Doris
- Öfner, Dietmar
- Huber, Lukas A.
- Clevers, Hans
- Becker, Christoph
- Farin, Henner F.
- Greten, Florian R.
- Aebersold, Ruedi
- Trajanoski, Zlatko
- Venue
- iScience
- Publisher
- Elsevier BV
- Published
- 2023-12
- Volume
- 26
- Issue
- 12
- Pages
- 108399
- ISSN
- 2589-0042 (ISSN-L)
- PMC
- PMC10692669
- OpenAlex
- W4388342914
- Cited by
- 27
- References
- 88
- Citations by year
- 2026: 7 · 2025: 14 · 2024: 6
- FWCI
- 2.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- iScience (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Leiden Repository (Leiden University) (publishedVersion, cc-by)
- KNAW research portal (Royal Academy of Art and Sciences (KNAW)) (publishedVersion, other-oa)
- Leiden Repository (Leiden University) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
- ETH Zürich Research Collection
- Funders
- European Research Council
- DFG
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (310030E-173572)
- Vienna Science and Technology Fund (LS16-025)
- HORIZON EUROPE European Innovation Council
- Innovative Medicines Initiative (imSAVAR 853988)
- Österreichische Krebshilfe Tirol (FF18015)
- ERC (EPIC 786295)
- H2020 EIC FTI (INCITE 964955)
- Österreichischen Akademie der Wissenschaften
- Austrian Science Fund (I3291, I3978, T974-B30)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Health Sciences › Medicine › Oncology › Colorectal Cancer Treatments and Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- colorectal cancer, patient-derived organoids, phosphoproteomics, kinase inhibitors, off-target effects, pathway crosstalk, tumor heterogeneity, stemness genes, tumor microenvironment, spatial proteomics, imaging mass cytometry, tumor-immune cell interactions, precision oncology, functional proteomics
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