Pre-existing Cell States Control Heterogeneity of Both EGFR and CXCR4 Signaling
Open accessAbstract
Introduction CXCR4 and epidermal growth factor receptor (EGFR) represent two major families of receptors, G-protein coupled receptors and receptor tyrosine kinases, with central functions in cancer. While utilizing different upstream signaling molecules, both CXCR4 and EGFR activate kinases ERK and Akt, although single-cell activation of these kinases is markedly heterogeneous. One hypothesis regarding the origin of signaling heterogeneity proposes that intercellular variations arise from differences in pre-existing intracellular states set by extrinsic noise. While pre-existing cell states vary among cells, each pre-existing state defines deterministic signaling outputs to downstream effectors. Understanding causes of signaling heterogeneity will inform treatment of cancers with drugs targeting drivers of oncogenic signaling. Methods We built a single-cell computational model to predict Akt and ERK responses to CXCR4- and EGFR-mediated stimulation. We investigated signaling heterogeneity through these receptors and tested model predictions using quantitative, live-cell time-lapse imaging. Results We show that the pre-existing cell state predicts single-cell signaling through both CXCR4 and EGFR. Computational modeling reveals that the same set of pre-existing cell states explains signaling heterogeneity through both EGFR and CXCR4 at multiple doses of ligands and in two different breast cancer cell lines. The model also predicts how phosphatidylinositol-3-kinase (PI3K) targeted therapies potentiate ERK signaling in certain breast cancer cells and that low level, combined inhibition of MEK and PI3K ablates potentiated ERK signaling. Conclusions Our data demonstrate that a conserved motif exists for EGFR and CXCR4 signaling and suggest potential clinical utility of the computational model to optimize therapy.
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.
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?
At higher cell densities, more rigorous models such as Maxwell-Stefan diffusion would be more appropriate.
“In this work, we considered a polynomial cell concentration dependence in the diffusivity for modeling nonlinear diffusion, but at higher cell densities, more rigorous models, such as Maxwell-Stefan diffusion would be more appropriate33.”
From Inference of weak-form partial differential equations describing migration and proliferation mechanisms in wound healing experiments on cancer cells (2025) · cites this paper as [33]
The Materials and Methods describe an ordinary-differential-equation model of EGFR and CXCR4 signaling, not a cell-concentration-dependent diffusion model. Searches for Maxwell–Stefan diffusion and polynomial diffusivity found no passage addressing whether a different diffusion model is appropriate at higher cell densities. The passages provide section labels but no page numbers. (LLM, conf=0.78)
Experimental — accuracy not yet measured
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
Ror2 signaling regulates Golgi structure and transport through IFT20 for tumor invasiveness
Nishita, M., Park, S.-Y., Nishio, T., Kamizaki, K., Wang, Z., Tamada, K., Takumi, T., Hashimoto, R., Otani, H., Pazour, G. J., et al. (2017) · Scientific Reports · doi:10.1038/s41598-016-0028-x · Cited by 15,947 · see citing works
mTOR Signaling in Growth, Metabolism, and Disease
Saxton, R. A., & Sabatini, D. M. (2017) · Cell · doi:10.1016/j.cell.2017.02.004 · Cited by 7,555 · see citing works
A methodology for performing global uncertainty and sensitivity analysis in systems biology
Marino, S., Hogue, I. B., Ray, C. J., & Kirschner, D. E. (2008) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2008.04.011 · Cited by 2,999 · see citing works
Prolonged Rapamycin Treatment Inhibits mTORC2 Assembly and Akt/PKB
Sarbassov, D. D., Ali, S. M., Sengupta, S., Sheen, J.-H., Hsu, P. P., Bagley, A. F., Markhard, A. L., & Sabatini, D. M. (2006) · Molecular Cell · doi:10.1016/j.molcel.2006.03.029 · Cited by 2,659 · see citing works
Epidermal Growth Factor Receptor Cell Proliferation Signaling Pathways
Wee, P., & Wang, Z. (2017) · Cancers · doi:10.3390/cancers9050052 · Cited by 2,027 · see citing works
The Ras-ERK and PI3K-mTOR pathways: cross-talk and compensation
Mendoza, M. C., Er, E. E., & Blenis, J. (2011) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2011.03.006 · Cited by 1,817 · see citing works
Emerging functions of the EGFR in cancer
Sigismund, S., Avanzato, D., & Lanzetti, L. (2017) · Molecular Oncology · doi:10.1002/1878-0261.12155 · Cited by 1,497 · see citing works
Blower, S. M., & Dowlatabadi, H. (1994) · International Statistical Review · doi:10.2307/1403510 · Cited by 1,401 · see citing works
Cellular Heterogeneity: Do Differences Make a Difference?
Altschuler, S. J., & Wu, L. F. (2010) · Cell · doi:10.1016/j.cell.2010.04.033 · Cited by 1,214 · see citing works
Targeting the EGFR signaling pathway in cancer therapy
Seshacharyulu, P., Ponnusamy, M. P., Haridas, D., Jain, M., Ganti, A. K., & Batra, S. K. (2012) · Expert Opinion on Therapeutic Targets · doi:10.1517/14728222.2011.648617 · Cited by 920 · see citing works
The Probabilistic Basis of Jaccard's Index of Similarity
Real, R., & Vargas, J. M. (1996) · Systematic Biology · doi:10.1093/sysbio/45.3.380 · Cited by 802 · see citing works
Brown, R., James, C., Henderson, L. A., & Macefield, V. G. (2012) · Frontiers in Physiology · doi:10.3389/fphys.2012.00394 · Cited by 730 · see citing works
Spencer, S. L., Cappell, S. D., Tsai, F., Overton, K. W., Wang, C. L., & Meyer, T. (2013) · Cell · doi:10.1016/j.cell.2013.08.062 · Cited by 673 · see citing works
A review on CXCR4/CXCL12 axis in oncology: No place to hide
Domańska, U., Kruizinga, R. C., Nagengast, W. B., Timmer‐Bosscha, H., Huls, G. A., de Vries, E. G. E., & Walenkamp, A. (2012) · European Journal of Cancer · doi:10.1016/j.ejca.2012.05.005 · Cited by 631 · see citing works
High-Sensitivity Measurements of Multiple Kinase Activities in Live Single Cells
Regot, S., Hughey, J., Bajar, B. T., Carrasco, S., & Covert, M. W. (2014) · Cell · doi:10.1016/j.cell.2014.04.039 · Cited by 542 · see citing works
Serra, V., Scaltriti, M., Prudkin, L., Eichhorn, P. J. A., Ibrahim, Y. H., Chandarlapaty, S., Markman, B., Rodríguez, O., Guzmán, M., Rodriguez, S., et al. (2011) · Oncogene · doi:10.1038/onc.2010.626 · Cited by 533 · see citing works
Rapamycin and mTOR kinase inhibitors
Ballou, L. M., & Lin, R. Z. (2008) · Journal of Chemical Biology · doi:10.1007/s12154-008-0003-5 · Cited by 444 · see citing works
Radiotherapy and the Tumor Stroma: The Importance of Dose and Fractionation
Hellevik, T., & Martínez-Zubiaurre, I. (2014) · Frontiers in Oncology · doi:10.3389/fonc.2014.00001 · Cited by 442 · see citing works
Shimizu, T., Tolcher, A. W., Papadopoulos, K. P., Beeram, M., Rasco, D. W., Smith, L. S., Gunn, S., Smetzer, L., Mays, T. A., Kaiser, B., et al. (2012) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-11-2381 · Cited by 431 · see citing works
Targeting the ERK signaling pathway in cancer therapy
Kohno, M., & Pouysségur, J. (2006) · Annals of Medicine · doi:10.1080/07853890600551037 · Cited by 422 · see citing works
Regulation of Raf-Akt Cross-talk
Moelling, K., Schad, K., Bosse, M., Zimmermann, S., & Schweneker, M. (2002) · Journal of Biological Chemistry · doi:10.1074/jbc.m111974200 · Cited by 389 · see citing works
Burke, P., Schooler, K., & Wiley, H. S. (2001) · Molecular Biology of the Cell · doi:10.1091/mbc.12.6.1897 · Cited by 384 · see citing works
Origins of regulated cell-to-cell variability
Snijder, B., & Pelkmans, L. (2011) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3044 · Cited by 346 · see citing works
The Akt pathway in oncology therapy and beyond (Review)
Nițulescu, G. M., van de Venter, M., Nițulescu, G., Ungurianu, A., Juzenas, P., Peng, Q., Olaru, O. T., Grădinaru, D., Tsatsakis, A. M., Tsoukalas, D., et al. (2018) · International Journal of Oncology · doi:10.3892/ijo.2018.4597 · Cited by 329 · see citing works
Phosphatidylinositol-3-OH Kinase or RAS Pathway Mutations in Human Breast Cancer Cell Lines
Hollestelle, A., Elstrodt, F., Nagel, J. H. A., Kallemeijn, W. W., & Schutte, M. E. M. (2007) · Molecular Cancer Research · doi:10.1158/1541-7786.mcr-06-0263 · Cited by 316 · see citing works
Dawson, J. P., Berger, M. B., Lin, C.-C., Schlessinger, J., Lemmon, M. A., & Ferguson, K. M. (2005) · Molecular and Cellular Biology · doi:10.1128/mcb.25.17.7734-7742.2005 · Cited by 298 · see citing works
Wang, Y., Pennock, S., Chen, X., & Wang, Z. (2002) · Molecular and Cellular Biology · doi:10.1128/mcb.22.20.7279-7290.2002 · Cited by 296 · see citing works
Emerging targets in cancer management: role of the CXCL12/CXCR4 axis
Dubrovska, A., Cojoc, M., Peitzsch, C., Trautmann, F., Polishchuk, & Telegeev (2013) · OncoTargets and Therapy · doi:10.2147/ott.s36109 · Cited by 255 · see citing works
Fold Change of Nuclear NF-κB Determines TNF-Induced Transcription in Single Cells
Lee, R., Walker, S. R., Savery, K., Frank, D. A., & Gaudet, S. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.01.026 · Cited by 231 · see citing works
Identification of Stromal Cells in Spleen Which Support Myelopoiesis
Lim, H. K., & O'Neill, H. C. (2019) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2019.00001 · Cited by 169 · see citing works
Hendriks, B. S., Opresko, L. K., Wiley, H. S., & Lauffenburger, D. A. (2003) · PubMed · Cited by 139 · see citing works
Emerging Understanding of Multiscale Tumor Heterogeneity
Gerdes, M. J., Sood, A., Sevinsky, C. J., Pris, A. D., Zavodszky, M. I., & Ginty, F. (2014) · Frontiers in Oncology · doi:10.3389/fonc.2014.00366 · Cited by 118 · see citing works
ETV7 is an essential component of a rapamycin-insensitive mTOR complex in cancer
Harwood, F. C., Geltink, R. I. K., O’Hara, B. P., Cardone, M., Janke, L. J., Finkelstein, D., Entin, I., Paul, L., Houghton, P. J., & Grosveld, G. C. (2018) · Science Advances · doi:10.1126/sciadv.aar3938 · Cited by 118 · see citing works
Parameter uncertainty in biochemical models described by ordinary differential equations
Vanlier, J., Tiemann, C. A., Hilbers, P. A. J., & van Riel, N. A. W. (2013) · Mathematical Biosciences · doi:10.1016/j.mbs.2013.03.006 · Cited by 116 · see citing works
Live-cell measurements of kinase activity in single cells using translocation reporters
Kudo, T., Jeknić, S., Macklin, D. N., Akhter, S., Hughey, J., Regot, S., & Covert, M. W. (2017) · Nature Protocols · doi:10.1038/nprot.2017.128 · Cited by 115 · see citing works
Faes, S., Demartines, N., & Dormond, O. (2017) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2017/1726078 · Cited by 104 · see citing works
On the nature of low- and high-affinity EGF receptors on living cells
Özcan, F., Klein, P., Lemmon, M. A., Lax, I., & Schlessinger, J. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601469103 · Cited by 99 · see citing works
Yuan, T. L., Wulf, G. M., Burga, L. N., & Cantley, L. C. (2011) · Current Biology · doi:10.1016/j.cub.2010.12.047 · Cited by 97 · see citing works
Sobolik, T., Su, Y., Wells, S., Ayers, G. D., Cook, R. S., & Richmond, A. J. (2014) · Molecular Biology of the Cell · doi:10.1091/mbc.e13-07-0360 · Cited by 85 · see citing works
Wendel, C., Hemping-Bovenkerk, A., Krasnyanska, J., Mees, S. T., Kochetkova, M., Stöppeler, S., & Haier, J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030046 · Cited by 73 · see citing works
Mechanical Stress Induces Remodeling of Vascular Networks in Growing Leaves
Bar‐Sinai, Y., Julien, J.-D., Sharon, E., Armon, S., Nakayama, N., Adda-Bedia, M., & Boudaoud, A. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004819 · Cited by 71 · see citing works
NF-κB Dynamics Discriminate between TNF Doses in Single Cells
Zhang, Q., Gupta, S., Schipper, D. L., Kowalczyk, G. J., Mancini, A. E., Faeder, J. R., & Lee, R. (2017) · Cell Systems · doi:10.1016/j.cels.2017.10.011 · Cited by 71 · see citing works
Distinct cellular states determine calcium signaling response
Yao, J. J., Pilko, A., & Wollman, R. (2016) · Molecular Systems Biology · doi:10.15252/msb.20167137 · Cited by 70 · see citing works
Epidermal growth factor promotes breast cancer cell chemotaxis in CXCL12 gradients
Mosadegh, B., Saadi, W. M., Wang, S., & Jeon, N. L. (2008) · Biotechnology and Bioengineering · doi:10.1002/bit.21851 · Cited by 67 · see citing works
CXCR4, but not CXCR7, Discriminates Metastatic Behavior in Non–Small Cell Lung Cancer Cells
Choi, Y. H., Burdick, M. D., Strieter, B. A., Mehrad, B., & Strieter, R. M. (2013) · Molecular Cancer Research · doi:10.1158/1541-7786.mcr-12-0334 · Cited by 65 · see citing works
Pinilla‐Macua, I., Watkins, S. C., & Sorkin, A. D. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1520301113 · Cited by 59 · see citing works
English, E. J., Wedemeyer, S. A., & Marchese, A. (2018) · Journal of Biological Chemistry · doi:10.1074/jbc.ra118.001872 · Cited by 53 · see citing works
CXCR7 Controls Competition for Recruitment of β-Arrestin 2 in Cells Expressing Both CXCR4 and CXCR7
Coggins, N. L., Trakimas, D. R., Chang, S. L., Ehrlich, A., Ray, P., Luker, K. E., Linderman, J. J., & Luker, G. D. (2014) · PLoS ONE · doi:10.1371/journal.pone.0098328 · Cited by 53 · see citing works
Self-citationADAM‐mediated amphiregulin shedding and EGFR transactivation
Kasina, S., Scherle, P., Hall, C. L., & Macoska, J. A. (2009) · Cell Proliferation · doi:10.1111/j.1365-2184.2009.00645.x · Cited by 51 · see citing works
High Intra- and Inter-Tumoral Heterogeneity of RAS Mutations in Colorectal Cancer
Jeantet, M., Tougeron, D., Tachon, G., Cortes, U., Archambaut, C., Fromont, G., & Karayan, L. (2016) · International Journal of Molecular Sciences · doi:10.3390/ijms17122015 · Cited by 51 · see citing works
Kim, E., Kim, J., Smith, M. A., Haura, E. B., & Anderson, A. R. A. (2018) · PLoS Biology · doi:10.1371/journal.pbio.2002930 · Cited by 44 · see citing works
Redefining Signaling Pathways with an Expanding Single-Cell Toolbox
Gaudet, S., & Miller‐Jensen, K. (2016) · Trends in biotechnology · doi:10.1016/j.tibtech.2016.02.009 · Cited by 41 · see citing works
Meyer, R., D’Alessandro, L. A., Kar, S., Kramer, B. A., She, B., Kaschek, D., Hahn, B., Wrangborg, D., Karlsson, J., Kvarnström, M., et al. (2012) · Frontiers in Physiology · doi:10.3389/fphys.2012.00451 · Cited by 41 · see citing works
MnemoCity Task: Assessment of Childrens Spatial Memory Using Stereoscopy and Virtual Environments
Rodríguez-Andrés, D., Juan, M. ‐., Méndez-López, M., Pérez-Hernández, E., & Lluch, J. (2016) · PLoS ONE · doi:10.1371/journal.pone.0161858 · Cited by 40 · see citing works
Masoudi, N., Tavazoie, S., Glenwinkel, L., Ryu, L., Kim, K., & Hobert, O. (2018) · PLoS Biology · doi:10.1371/journal.pbio.2004979 · Cited by 40 · see citing works
CXCL12/SDF-1α induces migration via SRC-mediated CXCR4-EGFR cross-talk in gastric cancer cells
Cheng, Y., Qu, J., Che, X., Xu, L., Song, N., Ma, Y., Gong, J., Qu, X., & Liu, Y. (2017) · Oncology Letters · doi:10.3892/ol.2017.6389 · Cited by 37 · see citing works
Role of CXCL12 and CXCR4 in normal cerebellar development and medulloblastoma
Ozawa, P. M. M., Ariza, C. B., Ishibashi, C. M., Fujita, T. C., Hirata, B. K. B., Oda, J. M. M., & Watanabe, M. A. E. (2014) · International Journal of Cancer · doi:10.1002/ijc.29333 · Cited by 35 · see citing works
Rodriguez-Nieves, J. A., Patalano, S. C., Almanza, D., Gharaee‐Kermani, M., & Macoska, J. A. (2016) · PLoS ONE · doi:10.1371/journal.pone.0159490 · Cited by 32 · see citing works
Short-term cellular memory tunes the signaling responses of the chemokine receptor CXCR4
Spinosa, P. C., Humphries, B. A., Lewin Mejia, D., Buschhaus, J. M., Linderman, J. J., Luker, G. D., & Luker, K. E. (2019) · Science Signaling · doi:10.1126/scisignal.aaw4204 · Cited by 31 · see citing works
Self-citationRandom mutations, selected mutations: A PIN opens the door to new genetic landscapes
Klein, C. A. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609000103 · Cited by 29 · see citing works
Iwamoto, K., Shindo, Y., & Takahashi, K. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005222 · Cited by 28 · see citing works
Cell, Isoform, and Environment Factors Shape Gradients and Modulate Chemotaxis
Chang, S. L., Cavnar, S. P., Takayama, S., Luker, G. D., & Linderman, J. J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0123450 · Cited by 27 · see citing works
Self-citationvan Mourik, S., ter Braak, C. J. F., Stigter, J. D., & Molenaar, J. (2014) · PeerJ · doi:10.7717/peerj.433 · Cited by 24 · see citing works
Cintas, C., & Guillermet‐Guibert, J. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2017.00330 · Cited by 17 · see citing works
Kuo, Y., Chiang, E. I., Chao, C.-Y., Rodriguez, R. L., Chou, P.-Y., Tsai, S.-Y., Pai, M., & Tang, F. (2016) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-16-0011 · Cited by 16 · see citing works
Opposite feedback from mTORC1 to H-ras and K-ras4B downstream of SREBP1
Posada, I. M. D., Lectez, B. L. P., Siddiqui, F. A., Oetken-Lindholm, C., Sharma, M., & Abankwa, D. (2017) · Scientific Reports · doi:10.1038/s41598-017-09387-8 · Cited by 13 · see citing works
Clathrin Heavy Chain Knockdown Impacts CXCR4 Signaling and Post-translational Modification
DeNies, M. S., Rosselli‐Murai, L. K., Schnell, S. D., & Liu, A. P. (2019) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2019.00077 · Cited by 11 · see citing works
A Two-Pulse Cellular Stimulation Test Elucidates Variability and Mechanisms in Signaling Pathways
Sumit, M., Jović, A., Neubig, R. R., Takayama, S., & Linderman, J. J. (2019) · Biophysical Journal · doi:10.1016/j.bpj.2019.01.022 · Cited by 9 · see citing works
Self-citation
Flagged first, then by citations
1 of the 69 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
C-X-C chemokine receptor type 7 antibody enhances neural plasticity after ischemic stroke
Zhang, X.-Q., Zhang, X., Dong, B.-C., Li, M., Wang, Y., Xiao, T., & Zhao, S.-S. (2022) · Neural Regeneration Research · doi:10.4103/1673-5374.363835 · Cited by 10 · see citing works
Kinnunen, P. C., Humphries, B. A., Luker, G. D., Luker, K. E., & Linderman, J. J. (2024) · npj Systems Biology and Applications · doi:10.1038/s41540-024-00369-x · Cited by 10 · see citing works
Self-citationHo, K. K. Y., Srivastava, S., Kinnunen, P. C., Garikipati, K., Luker, G. D., & Luker, K. E. (2023) · Bioengineering · doi:10.3390/bioengineering10020269 · Cited by 8 · see citing works
Self-citationHo, K. K. Y., Buschhaus, J. M., Zhang, A., Cutter, A. C., Humphries, B. A., & Luker, G. D. (2025) · Scientific Reports · doi:10.1038/s41598-025-14495-x · Cited by 7 · see citing works
Self-citationSrivastava, S., Kinnunen, P. C., Wang, Z., Ho, K. K. Y., Humphries, B. A., Chen, S., Linderman, J. J., Luker, G. D., Luker, K. E., & Garikipati, K. (2025) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1013607 · Cited by 5 · see citing works
“We engineered the MDA-MB-231 breast cancer cells used in this work to express a stable histone-2B (H2B) nuclear marker (mCherry), along with kinase translocation reporters [32] for the Akt and ERK kinases, as described previously [33,34].”
Self-citationInertial effect of cell state velocity on the quiescence-proliferation fate decision
Venkatachalapathy, H., Brzakala, C., Batchelor, E., Azarin, S. M., & Sarkar, C. A. (2024) · npj Systems Biology and Applications · doi:10.1038/s41540-024-00428-3 · Cited by 4 · see citing works
Computational modeling implicates protein scaffolding in p38 regulation of Akt
Kinnunen, P. C., Luker, G. D., Luker, K. E., & Linderman, J. J. (2022) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2022.111294 · Cited by 4 · see citing works
Self-citationKinnunen, P. C., Ho, K. K. Y., Srivastava, S., Huang, C., Shen, W., Garikipati, K., Luker, G. D., Banović, N., Huan, X., Linderman, J. J., et al. (2024) · Frontiers in Systems Biology · doi:10.3389/fsysb.2024.1333760 · Cited by 3 · see citing works
Self-citationCell-to-cell variability of dynamic CXCL12-CXCR4 signaling and morphological processes in chemotaxisPreprint
Ho, K. K. Y., Srivastava, S., Kinnunen, P. C., Garikipati, K., Luker, G. D., & Luker, K. E. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.19.492090
Self-citationJiao, L., Yang, Q., Miao, G., Wang, Y., Yang, Z., & Liu, X. (2022) · Journal of Biomaterials and Tissue Engineering · doi:10.1166/jbt.2022.3136
Li, W., Zhang, B., Zhao, W., Wang, H., Zhou, M., Li, Y., Ma, J., Chu, L., Ruan, X., Xiao, P., et al. (2026) · Cells · doi:10.3390/cells15151340
- Authors
- Spinosa, P. C., Kinnunen, P. C., Humphries, B. A., Luker, G. D., Luker, K. E., & Linderman, J. J.
- Affiliations
- University of Michigan (US)
- Corresponding author
- Luker, Kathryn E.
- Linderman, Jennifer J.
- Venue
- Cellular and Molecular Bioengineering
- Published
- 2020-07-27
- Volume
- 14
- Issue
- 1
- Pages
- 49-64
- ISSN
- 1865-5025 (ISSN-L)
- 1865-5033
- PMC
- PMC7878609
- OpenAlex
- W3045883177
- Cited by
- 10
- References
- 69
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 3 · 2023: 1 · 2022: 4
- FWCI
- 0.41
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Cellular and Molecular Bioengineering (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (R01CA196018, R01CA238042, R01CA238023, R33CA225549, R37CA222563, R50CA221807, U01CA210152)
- National Institute of Biomedical Imaging and Bioengineering (T32 EB005582)
- American Cancer Society (PF-18-236-01-CCG)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Kinase Regulation and GTPase Signaling
- Physical Sciences › Mathematics › Modeling and Simulation › Mathematical Biology Tumor Growth
- Keywords
- EGFR signaling, CXCR4 signaling, ERK activation, Akt activation, phosphatidylinositol 3-kinase, MEK inhibition, breast cancer, G protein-coupled receptors, receptor tyrosine kinase, cancer therapy optimization
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
