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Metastatic recurrence in colorectal most cancers arises from residual EMP1+ cells

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  • Amin, M.B. et al. The Eighth Version AJCC Most cancers Staging Handbook: persevering with to construct a bridge from a population-based to a extra “customized” strategy to most cancers staging. CA 67, 93–99 (2017).

  • Shimokawa, M. et al. Visualization and focusing on of LGR5+ human colon most cancers stem cells. Nature 545, 187–192 (2017).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • de Sousa e Melo, F. et al. A definite position for Lgr5+ stem cells in main and metastatic colon most cancers. Nature 543, 676–680 (2017).

    ADS 
    PubMed 

    Google Scholar
     

  • Cortina, C. et al. A genome modifying strategy to check most cancers stem cells in human tumors. EMBO Mol. Med. 9, 869–879 (2017).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Calon, A. et al. Dependency of colorectal most cancers on a TGF-β-driven program in stromal cells for metastasis initiation. Most cancers Cell 22, 571–584 (2012).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Calon, A. et al. Stromal gene expression defines poor-prognosis subtypes in colorectal most cancers. Nat. Genet. 47, 320–329 (2015).

    CAS 
    PubMed 

    Google Scholar
     

  • Isella, C. et al. Stromal contribution to the colorectal most cancers transcriptome. Nat. Genet. 47, 312–319 (2015).

    CAS 
    PubMed 

    Google Scholar
     

  • Lee, H.-O. et al. Lineage-dependent gene expression applications affect the immune panorama of colorectal most cancers. Nat. Genet. 52, 594–603 (2020).

    CAS 
    PubMed 

    Google Scholar
     

  • Guinney, J. et al. The consensus molecular subtypes of colorectal most cancers. Nat. Med. 21, 1350–1356 (2015).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Raghavan, S. et al. Microenvironment drives cell state, plasticity, and drug response in pancreatic most cancers. Cell 184, 6119–6137 (2021).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Joanito, I. et al. Single-cell and bulk transcriptome sequencing identifies two epithelial tumor cell states and refines the consensus molecular classification of colorectal most cancers. Nat. Genet. 54, 963–975 (2022).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Tauriello, D. V. F. et al. TGFβ drives immune evasion in genetically reconstituted colon most cancers metastasis. Nature 554, 538–543 (2018).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Massagué, J. & Obenauf, A. C. Metastatic colonization by circulating tumour cells. Nature 529, 298–306 (2016).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Barriga, F. M. et al. Mex3a marks a slowly dividing subpopulation of Lgr5+ intestinal stem cells. Cell Stem Cell 20, 801–816 (2017).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lange, M. et al. CellRank for directed single-cell destiny mapping. Nat. Strategies 19, 159–170 (2022).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Álvarez-Varela, A. et al. Mex3a marks drug-tolerant persister colorectal most cancers cells that mediate relapse after chemotherapy. Nat. Most cancers 3, 1052–1070 (2022).

    PubMed 

    Google Scholar
     

  • Tyler, M. & Tirosh, I. Decoupling epithelial-mesenchymal transitions from stromal profiles by integrative expression evaluation. Nat. Commun. 12, 2592 (2021).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Grigore, A. D., Jolly, M. Okay., Jia, D., Farach-Carson, M. C. & Levine, H. Tumor budding: the title is EMT. Partial EMT. J. Clin. Med. 5, 51 (2016).

    PubMed Central 

    Google Scholar
     

  • Roa-Peña, L. et al. Keratin 17 identifies essentially the most deadly molecular subtype of pancreatic most cancers. Sci. Rep. 9, 11239 (2019).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Durgan, J. et al. SOS1 and Ras regulate epithelial tight junction formation within the human airway by way of EMP1. EMBO Rep. 16, 87–96 (2015).

    CAS 
    PubMed 

    Google Scholar
     

  • Bangsow, T. et al. The epithelial membrane protein 1 is a novel tight junction protein of the blood-brain barrier. J. Cereb. Blood Stream Metab. 28, 1249–1260 (2008).

    CAS 
    PubMed 

    Google Scholar
     

  • Aceto, N. et al. Circulating tumor cell clusters are oligoclonal precursors of breast most cancers metastasis. Cell 158, 1110–1122 (2014).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Barry, E. R. et al. Restriction of intestinal stem cell growth and the regenerative response by YAP. Nature 493, 106–110 (2013).

    ADS 
    PubMed 

    Google Scholar
     

  • Cheung, P. et al. Regenerative reprogramming of the intestinal stem cell state through hippo signaling suppresses metastatic colorectal most cancers. Cell Stem Cell 27, 590–604 (2020).

    CAS 
    PubMed 

    Google Scholar
     

  • Vasquez, E. G. et al. Dynamic and adaptive most cancers stem cell inhabitants admixture in colorectal neoplasia. Cell Stem Cell 29, 1213–1228 (2022).

    CAS 
    PubMed 

    Google Scholar
     

  • Han, T. et al. Lineage reversion drives WNT independence in intestinal most cancers. Most cancers Discov. 10, 1590–1609 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lupo, B. et al. Colorectal most cancers residual illness at maximal response to EGFR blockade shows a druggable Paneth cell-like phenotype. Sci. Transl. Med. 12, eaax8313 (2020).

    CAS 
    PubMed 

    Google Scholar
     

  • Heinz, M. C. et al. Liver colonization by colorectal most cancers metastases requires YAP-controlled plasticity on the micrometastatic stage. Most cancers Res. 82, 1953–1968 (2022).

    CAS 
    PubMed 

    Google Scholar
     

  • Solé, L. et al. p53 wild-type colorectal most cancers cells that specific a fetal gene signature are related to metastasis and poor prognosis. Nat. Commun. 13, 2866 (2022).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ohta, Y. et al. Cell-matrix interface regulates dormancy in human colon most cancers stem cells. Nature 680, 784–794 (2022).

    ADS 

    Google Scholar
     

  • Mustata, R. C. et al. Identification of Lgr5-independent spheroid-generating progenitors of the mouse fetal intestinal epithelium. Cell Rep. 5, 421–432 (2013).

    CAS 
    PubMed 

    Google Scholar
     

  • Wang, Y. et al. Complete molecular characterization of the hippo signaling pathway in most cancers. Cell Rep. 25, 1304–1317 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Yuan, Y. et al. YAP1/TAZ-TEAD transcriptional networks keep pores and skin homeostasis by regulating cell proliferation and limiting KLF4 exercise. Nat. Commun. 11, 1472 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Morral, C. et al. Zonation of ribosomal DNA transcription defines a stem cell hierarchy in colorectal most cancers. Cell Stem Cell 26, 845–861 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Le, D. T. et al. PD-1 blockade in tumors with mismatch-repair deficiency. N. Engl. J. Med. 372, 2509–2520 (2015).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Fumagalli, A. et al. Plasticity of Lgr5-negative most cancers cells drives metastasis in colorectal most cancers. Cell Stem Cell 26, 569–578 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ganesh, Okay. et al. L1CAM defines the regenerative origin of metastasis-initiating cells in colorectal most cancers. Nat. Most cancers 1, 28–45 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Padmanaban, V. et al. E-cadherin is required for metastasis in a number of fashions of breast most cancers. Nature 573, 439–444 (2019).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Chalabi, M. et al. Neoadjuvant immunotherapy results in pathological responses in MMR-proficient and MMR-deficient early-stage colon cancers. Nat. Med. 26, 566–576 (2020).

    CAS 
    PubMed 

    Google Scholar
     

  • Matano, M. et al. Modeling colorectal most cancers utilizing CRISPR-Cas9–mediated engineering of human intestinal organoids. Nat. Med. 21, 256–262 (2015).

    CAS 
    PubMed 

    Google Scholar
     

  • Drost, J. et al. Sequential most cancers mutations in cultured human intestinal stem cells. Nature 521, 43–47 (2015).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Céspedes, M. V. et al. Orthotopic microinjection of human colon most cancers cells in nude mice induces tumor foci in all clinically related metastatic websites. Am. J. Pathol. 170, 1077–1085 (2007).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Chen, Y.-C. et al. Intestine fecal microbiota transplant in a mouse mannequin of orthotopic rectal most cancers. Entrance. Oncol. 10, 568012 (2020).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Conti, S. et al. CAFs and most cancers cells co-migration in 3D spheroid invasion assay. Strategies Mol. Biol. 2179, 243–256 (2020).


    Google Scholar
     

  • Gonzalez-Roca, E. et al. Correct expression profiling of very small cell populations. PLoS ONE 5, e14418 (2010).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Dobin, A. et al. STAR: ultrafast common RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    CAS 
    PubMed 

    Google Scholar
     

  • Tarasov, A., Vilella, A. J., Cuppen, E., Nijman, I. J. & Prins, P. Sambamba: quick processing of NGS alignment codecs. Bioinformatics 31, 2032–2034 (2015).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Liao, Y., Smyth, G. Okay. & Shi, W. The R package deal Rsubread is simpler, quicker, cheaper and higher for alignment and quantification of RNA sequencing reads. Nucleic Acids Res. 47, e47 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq information with DESeq2. Genome Biol. 15, 550 (2014).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Carvalho, B. S. & Irizarry, R. A. A framework for oligonucleotide microarray preprocessing. Bioinformatics 26, 2363–2367 (2010).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bolstad, B. M. et al. in Bioinformatics and Computational Biology Options Utilizing R and Bioconductor (eds Gentleman, R. et al.) (Springer, 2005).

  • Fridlyand, J. Microarray Knowledge Evaluation. in Chosen Works in Chance and Statistics (ed Dudoit, S.) https://doi.org/10.1007/978-1-4614-1347-9_15 (Springer, 2012).

  • Ritchie, M. E. et al. Limma powers differential expression analyses for RNA-sequencing and microarray research. Nucleic Acids Res. 43, e47 (2015).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Eklund, A. C. & Szallasi, Z. Correction of technical bias in scientific microarray information improves concordance with recognized organic data. Genome Biol. 9, R26 (2008).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Wu, D. et al. ROAST: rotation gene set assessments for complicated microarray experiments. Bioinformatics 26, 2176–2182 (2010).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Efron, B. & Tibshirani, R. On testing the importance of units of genes. Ann. Appl. Stat. 1, 107–129 (2007).

    MathSciNet 
    MATH 

    Google Scholar
     

  • Lee, E., Chuang, H. Y., Kim, J. W., Ideker, T. & Lee, D. Inferring pathway exercise towards exact illness classification. PLoS Comput. Biol. 4, e1000217 (2008).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zheng, G. X. Y. et al. Massively parallel digital transcriptional profiling of single cells. Nat. Commun. 8, 14049 (2017).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Hao, Y. et al. Built-in evaluation of multimodal single-cell information. Cell 184, 3573–3587 (2021).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Satija, R., Farrell, J. A., Gennert, D., Schier, A. F. & Regev, A. Spatial reconstruction of single-cell gene expression information. Nat. Biotechnol. 33, 495–502 (2015).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic information throughout totally different situations, applied sciences, and species. Nat. Biotechnol. 36, 411–420 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Stuart, T. et al. Complete integration of single-cell information. Cell 177, 1888–1902 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Hafemeister, C. & Satija, R. Normalization and variance stabilization of single-cell RNA-seq information utilizing regularized damaging binomial regression. Genome Biol. 20, 296 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • van Dijk, D. et al. Recovering gene interactions from single-cell information utilizing information diffusion. Cell 174, 716–729 (2018).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Subramanian, A. et al. Gene set enrichment evaluation: a knowledge-based strategy for deciphering genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Parekh, S., Ziegenhain, C., Vieth, B., Enard, W. & Hellmann, I. zUMIs—a quick and versatile pipeline to course of RNA sequencing information with UMIs. Gigascience 7, giy059 (2018).

  • La Manno, G. et al. RNA velocity of single cells. Nature 560, 494–498 (2018).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bergen, V., Lange, M., Peidli, S., Wolf, F. A. & Theis, F. J. Generalizing RNA velocity to transient cell states by way of dynamical modeling. Nat. Biotechnol. 38, 1408–1414 (2020).

    CAS 
    PubMed 

    Google Scholar
     

  • R Core Group. R: A Language and Surroundings for Statistical Computing (R Basis for Statistical Computing, 2020).

  • Barrett, T. & Edgar, R. [19] Gene Expression Omnibus: microarray information storage, submission, retrieval, and evaluation. Strategies Enzymol. 411, 352–369 (2006).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Grossman, R. L. et al. Towards a shared imaginative and prescient for most cancers genomic information. N. Engl. J. Med. 375, 1109–1112 (2016).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Muzny, D. M. et al. Complete molecular characterization of human colon and rectal most cancers. Nature 487, 330–337 (2012).

    ADS 
    CAS 

    Google Scholar
     

  • Tripathi, M. Okay. et al. Nuclear issue of activated T-cell exercise is related to metastatic capability in colon most cancers. Most cancers Res. 74, 6947–6957 (2014).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Sanz-Pamplona, R. et al. Aberrant gene expression in mucosa adjoining to tumor reveals a molecular crosstalk in colon most cancers. Mol. Most cancers 13, 46 (2014).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Kemper, Okay. et al. Mutations within the Ras-Raf axis underlie the prognostic worth of CD133 in colorectal most cancers. Clin. Most cancers Res. 18, 3132–3141 (2012).

    CAS 
    PubMed 

    Google Scholar
     

  • Jorissen, R. N. et al. Metastasis-associated gene expression modifications predict poor outcomes in sufferers with dukes stage B and C colorectal most cancers. Clin. Most cancers Res. 15, 7642–7651 (2009).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Marisa, L. et al. Gene expression classification of colon most cancers into molecular subtypes: characterization, validation, and prognostic worth. PLoS Med. 10, e1001453 (2013).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Laibe, S. et al. A seven-gene signature aggregates a subgroup of stage II colon cancers with stage III. OMICS 16, 560–565 (2012).

    CAS 
    PubMed 

    Google Scholar
     

  • Jorissen, R. N. et al. DNA copy-number alterations underlie gene expression variations between microsatellite secure and unstable colorectal cancers. Clin. Most cancers Res. 14, 8061–8069 (2008).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Azzalini, A. & Menardi, G. Clustering through nonparametric density estimation: the R package deal pdfcluster. J. Stat. Softw. 57, 1–26 (2014).

    MATH 

    Google Scholar
     

  • Azzalini, A. & Torelli, N. Clustering through nonparametric density estimation. Stat. Comput. 17, 71–80 (2007).

    MathSciNet 

    Google Scholar
     

  • Smedley, D. et al. The BioMart neighborhood portal: an progressive different to giant, centralized information repositories. Nucleic Acids Res. 43, W589–W598 (2015).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Drost, H. G. & Paszkowski, J. Biomartr: genomic information retrieval with R. Bioinformatics 33, 1216–1217 (2017).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Li, B. & Dewey, C. N. RSEM: correct transcript quantification from RNA-seq information with or with no reference genome. BMC Bioinform. 12, 323 (2011).

    CAS 

    Google Scholar
     

  • Bates, D., Mächler, M., Bolker, B. M. & Walker, S. C. Becoming linear mixed-effects fashions utilizing lme4. J. Stat. Softw. 67, 1–48 (2015).


    Google Scholar
     

  • Therneau, T. M., Grambsch, P. M. & Pankratz, V. S. Penalized survival fashions and frailty. J. Comput. Graph. Stat. 12, 156–175 (2003).

    MathSciNet 

    Google Scholar
     

  • Therneau, T. coxme: blended results Cox fashions. R package deal model 2.2-3 www.cran.R-project.org/package deal=coxme.Oikos (2012).

  • Sanchez-Vega, F. et al. Oncogenic signaling pathways within the Most cancers Genome Atlas. Cell 173, 321–337 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Mootha, V. Okay. et al. PGC-1α-responsive genes concerned in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat. Genet. 34, 267–273 (2003).

    CAS 
    PubMed 

    Google Scholar
     

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