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  • 1.
    Berglund, Emelie
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Genteknologi.
    Maaskola, Jonas
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Genteknologi.
    Schultz, Niklas
    Friedrich, Stefanie
    Marklund, Maja
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Genteknologi.
    Bergenstrahle, Joseph
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Genteknologi.
    Tarish, Firas
    Tanoglidi, Anna
    Vickovic, Sanja
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Larsson, Ludvig
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Genteknologi.
    Salmén, Fredrik
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Ogris, Christoph
    Wallenborg, Karolina
    Lagergren, Jens
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Beräkningsvetenskap och beräkningsteknik (CST).
    Ståhl, Patrik
    Sonnhammer, Erik
    Helleday, Thomas
    Lundeberg, Joakim
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity2018Inngår i: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 9, artikkel-id 2419Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Intra-tumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.

  • 2.
    Borgström, Erik
    et al.
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Redin, David
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Lundin, Sverker
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Berglund, Emelie
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Andersson, Anders F.
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Ahmadian, Afshin
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Phasing of single DNA molecules by massively parallel barcoding2015Inngår i: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 6, artikkel-id 7173Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    High-throughput sequencing platforms mainly produce short-read data, resulting in a loss of phasing information for many of the genetic variants analysed. For certain applications, it is vital to know which variant alleles are connected to each individual DNA molecule. Here we demonstrate a method for massively parallel barcoding and phasing of single DNA molecules. First, a primer library with millions of uniquely barcoded beads is generated. When compartmentalized with single DNA molecules, the beads can be used to amplify and tag any target sequences of interest, enabling coupling of the biological information from multiple loci. We apply the assay to bacterial 16S sequencing and up to 94% of the hypothesized phasing events are shown to originate from single molecules. The method enables use of widely available short-read-sequencing platforms to study long single molecules within a complex sample, without losing phase information.

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