Connect with us

Health

Spatial genomics maps the structure, nature and evolution of cancer clones

Spatial genomics maps the structure, nature and evolution of cancer clones

 


  • Gerstung, M. et al. The evolutionary history of 2,658 cancers. Nature 578, 122–128 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Andor, N. et al. Pan-cancer analysis of the extent and consequences of intratumor heterogeneity. Nat. Med. 22, 105–113 (2016).

    CAS 
    PubMed 

    Google Scholar
     

  • Yates, L. R. et al. Subclonal diversification of primary breast cancer revealed by multiregion sequencing. Nat. Med. 21, 751–759 (2015).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Greaves, M. & Maley, C. C. Clonal evolution in cancer. Nature 481, 306–313 (2012).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • McGranahan, N. & Swanton, C. Clonal heterogeneity and tumor evolution: past, present, and the future. Cell 168, 613–628 (2017).

    CAS 
    PubMed 

    Google Scholar
     

  • Nowell, P. C. The clonal evolution of tumor cell populations. Science 194, 23–28 (1976).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Dentro, S. C. et al. Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes. Cell 184, 2239–2254.e39 (2021).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Nik-Zainal, S. et al. The life history of 21 breast cancers. Cell 149, 994–1007 (2012).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Gaglia, G. et al. Temporal and spatial topography of cell proliferation in cancer. Nat. Cell Biol. 24, 316–326 (2022).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Risom, T. et al. Transition to invasive breast cancer is associated with progressive changes in the structure and composition of tumor stroma. Cell 185, 299–310.e18 (2022).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Dhainaut, M. et al. Spatial CRISPR genomics identifies regulators of the tumor microenvironment. Cell 185, 1223–1239.e20 (2022).

    CAS 
    PubMed 

    Google Scholar
     

  • Yates, L. R. et al. Genomic evolution of breast cancer metastasis and relapse. Cancer Cell 32, 169–184.e7 (2017).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Maley, C. C. et al. Genetic clonal diversity predicts progression to esophageal adenocarcinoma. Nat. Genet. 38, 468–473 (2006).

    CAS 
    PubMed 

    Google Scholar
     

  • Jamal-Hanjani, M. et al. Tracking the evolution of non–small-cell lung cancer. N. Engl. J. Med. 376, 2109–2121 (2017).

    CAS 
    PubMed 

    Google Scholar
     

  • Janiszewska, M. et al. Subclonal cooperation drives metastasis by modulating local and systemic immune microenvironments. Nat. Cell Biol. 21, 879–888 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Juric, D. et al. Convergent loss of PTEN leads to clinical resistance to a PI(3)Kα inhibitor. Nature 518, 240–244 (2015).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Jones, S. et al. Comparative lesion sequencing provides insights into tumor evolution. Proc. Natl Acad. Sci. USA 105, 4283–4288 (2008).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Shah, S. P. et al. Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature 461, 809–813 (2009).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Casasent, A. K. et al. Multiclonal invasion in breast tumors identified by topographic single cell sequencing. Cell 172, 205–217.e12 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Tarabichi, M. et al. A practical guide to cancer subclonal reconstruction from DNA sequencing. Nat. Methods 18, 144–155 (2021).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Shen, C. Y. et al. Genome-wide search for loss of heterozygosity using laser capture microdissected tissue of breast carcinoma: an implication for mutator phenotype and breast cancer pathogenesis. Cancer Res. 60, 3884–3892 (2000).

    CAS 
    PubMed 

    Google Scholar
     

  • Zhao, T. et al. Spatial genomics enables multi-modal study of clonal heterogeneity in tissues. Nature 601, 85–91 (2022).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Erickson, A. et al. Spatially resolved clonal copy number alterations in benign and malignant tissue. Nature 608, 360–367 (2022).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Janiszewska, M. et al. In situ single-cell analysis identifies heterogeneity for PIK3CA mutation and HER2 amplification in HER2-positive breast cancer. Nat. Genet. 47, 1212–1219 (2015).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Larsson, C., Grundberg, I., Söderberg, O. & Nilsson, M. In situ detection and genotyping of individual mRNA molecules. Nat. Methods 7, 395–397 (2010).

    CAS 
    PubMed 

    Google Scholar
     

  • Grundberg, I. et al. In situ mutation detection and visualization of intratumor heterogeneity for cancer research and diagnostics. Oncotarget 4, 2407–2418 (2013).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ke, R. et al. In situ sequencing for RNA analysis in preserved tissue and cells. Nat. Methods 10, 857–860 (2013).

    CAS 
    PubMed 

    Google Scholar
     

  • Baker, A.-M. et al. Robust RNA-based in situ mutation detection delineates colorectal cancer subclonal evolution. Nat. Commun. 8, 1998 (2017).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Cowell, C. F. et al. Progression from ductal carcinoma in situ to invasive breast cancer: revisited. Mol. Oncol. 7, 859–869 (2013).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Svedlund, J. et al. Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer. EBioMedicine 48, 212–223 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Wu, S. Z. et al. A single-cell and spatially resolved atlas of human breast cancers. Nat. Genet. 53, 1334–1347 (2021).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ellis, P. et al. Reliable detection of somatic mutations in solid tissues by laser-capture microdissection and low-input DNA sequencing. Nat. Protoc. 16, 841–871 (2021).

    CAS 
    PubMed 

    Google Scholar
     

  • Gataric, M. et al. PoSTcode: probabilistic image-based spatial transcriptomics decoder. Preprint at https://doi.org/10.1101/2021.10.12.464086 (2021).

  • Nirmal, A. J. et al. The spatial landscape of progression and immunoediting in primary melanoma at single-cell resolution. Cancer Discov. 12, 1518–1541 (2022).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Kole, A. J. et al. Overall survival is improved when DCIS accompanies invasive breast cancer. Sci. Rep. 9, 9934 (2019).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Going, J. J. & Moffat, D. F. Escaping from flatland: clinical and biological aspects of human mammary duct anatomy in three dimensions. J. Pathol. 203, 538–544 (2004).

    PubMed 

    Google Scholar
     

  • Schnitt, S. J. & Collins, L. C. Biopsy Interpretation of the Breast (Lippincott Williams & Wilkins, 2009).

  • Pinder, S. E. Ductal carcinoma in situ (DCIS): pathological features, differential diagnosis, prognostic factors and specimen evaluation. Mod. Pathol. 23, S8–S13 (2010).

    PubMed 

    Google Scholar
     

  • Thomson, J. Z. et al. Growth pattern of ductal carcinoma in situ (DCIS): a retrospective analysis based on mammographic findings. Br. J. Cancer 85, 225–227 (2001).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Solin, L. J. et al. A multigene expression assay to predict local recurrence risk for ductal carcinoma in situ of the breast. J. Natl Cancer Inst. 105, 701–710 (2013).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Jatoi, I., Hilsenbeck, S. G., Clark, G. M. & Osborne, C. K. Significance of axillary lymph node metastasis in primary breast cancer. J. Clin. Oncol. 17, 2334–2340 (1999)

  • Sereesongsaeng, N., McDowell, S. H., Burrows, J. F., Scott, C. J. & Burden, R. E. Cathepsin V suppresses GATA3 protein expression in luminal A breast cancer. Breast Cancer Res. 22, 139 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Kwon, M. J. et al. CD24 overexpression is associated with poor prognosis in luminal A and triple-negative breast cancer. PLoS ONE 10, e0139112 (2015).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Li, X.-P. et al. Co-expression of CXCL8 and HIF-1α is associated with metastasis and poor prognosis in hepatocellular carcinoma. Oncotarget 6, 22880–22889 (2015).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Cairns, R. A. & Hill, R. P. Acute hypoxia enhances spontaneous lymph node metastasis in an orthotopic murine model of human cervical carcinoma. Cancer Res. 64, 2054–2061 (2004).

    CAS 
    PubMed 

    Google Scholar
     

  • Sottoriva, A. et al. A Big Bang model of human colorectal tumor growth. Nat. Genet. 47, 209–216 (2015).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Vickovic, S. et al. High-definition spatial transcriptomics for in situ tissue profiling. Nat. Methods 16, 987–990 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Gyllborg, D. et al. Hybridization-based in situ sequencing (HybISS) for spatially resolved transcriptomics in human and mouse brain tissue. Nucleic Acids Res. 48, e112 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lee, H., Marco Salas, S., Gyllborg, D. & Nilsson, M. Direct RNA targeted in situ sequencing for transcriptomic profiling in tissue. Sci. Rep. 12, 7976 (2022).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Dobzhansky, T. Nothing in biology makes sense except in the light of evolution. Am. Biol. Teach. 35, 125–129 (1973).


    Google Scholar
     

  • Sources

    1/ https://Google.com/

    2/ https://www.nature.com/articles/s41586-022-05425-2

    The mention sources can contact us to remove/changing this article

    What Are The Main Benefits Of Comparing Car Insurance Quotes Online

    LOS ANGELES, CA / ACCESSWIRE / June 24, 2020, / Compare-autoinsurance.Org has launched a new blog post that presents the main benefits of comparing multiple car insurance quotes. For more info and free online quotes, please visit https://compare-autoinsurance.Org/the-advantages-of-comparing-prices-with-car-insurance-quotes-online/ The modern society has numerous technological advantages. One important advantage is the speed at which information is sent and received. With the help of the internet, the shopping habits of many persons have drastically changed. The car insurance industry hasn't remained untouched by these changes. On the internet, drivers can compare insurance prices and find out which sellers have the best offers. View photos The advantages of comparing online car insurance quotes are the following: Online quotes can be obtained from anywhere and at any time. Unlike physical insurance agencies, websites don't have a specific schedule and they are available at any time. Drivers that have busy working schedules, can compare quotes from anywhere and at any time, even at midnight. Multiple choices. Almost all insurance providers, no matter if they are well-known brands or just local insurers, have an online presence. Online quotes will allow policyholders the chance to discover multiple insurance companies and check their prices. Drivers are no longer required to get quotes from just a few known insurance companies. Also, local and regional insurers can provide lower insurance rates for the same services. Accurate insurance estimates. Online quotes can only be accurate if the customers provide accurate and real info about their car models and driving history. Lying about past driving incidents can make the price estimates to be lower, but when dealing with an insurance company lying to them is useless. Usually, insurance companies will do research about a potential customer before granting him coverage. Online quotes can be sorted easily. Although drivers are recommended to not choose a policy just based on its price, drivers can easily sort quotes by insurance price. Using brokerage websites will allow drivers to get quotes from multiple insurers, thus making the comparison faster and easier. For additional info, money-saving tips, and free car insurance quotes, visit https://compare-autoinsurance.Org/ Compare-autoinsurance.Org is an online provider of life, home, health, and auto insurance quotes. This website is unique because it does not simply stick to one kind of insurance provider, but brings the clients the best deals from many different online insurance carriers. In this way, clients have access to offers from multiple carriers all in one place: this website. On this site, customers have access to quotes for insurance plans from various agencies, such as local or nationwide agencies, brand names insurance companies, etc. "Online quotes can easily help drivers obtain better car insurance deals. All they have to do is to complete an online form with accurate and real info, then compare prices", said Russell Rabichev, Marketing Director of Internet Marketing Company. CONTACT: Company Name: Internet Marketing CompanyPerson for contact Name: Gurgu CPhone Number: (818) 359-3898Email: [email protected]: https://compare-autoinsurance.Org/ SOURCE: Compare-autoinsurance.Org View source version on accesswire.Com:https://www.Accesswire.Com/595055/What-Are-The-Main-Benefits-Of-Comparing-Car-Insurance-Quotes-Online View photos

    ExBUlletin

    to request, modification Contact us at Here or [email protected]