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  • 501.
    Älgenäs, Cajsa
    et al.
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Agaton, Charlotta
    Fagerberg, Linn
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Asplund, Anna
    Björling, Lisa
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Björling, Erik
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Kampf, Caroline
    Lundberg, Emma
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Nilsson, Peter
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Persson, Anja
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Wester, Kenneth
    Pontén, Fredrik
    Wernerus, Henrik
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Ottosson Takanen, Jenny
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Hober, Sophia
    KTH, Skolan för bioteknologi (BIO), Proteinteknologi.
    Antibody performance in western blot applications is context- dependent2014Inngår i: Biotechnology Journal, ISSN 1860-6768, E-ISSN 1860-7314, Vol. 9, nr 3, s. 435-445Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    An important concern for the use of antibodies in various applications, such as western blot (WB) or immunohistochemistry (IHC), is specificity. This calls for systematic validations using well-designed conditions. Here, we have analyzed 13000 antibodies using western blot with lysates from human cell lines, tissues, and plasma. Standardized stratification showed that 45% of the antibodies yielded supportive staining, and the rest either no staining (12%) or protein bands of wrong size (43%). A comparative study of WB and IHC showed that the performance of antibodies is application-specific, although a correlation between no WB staining and weak IHC staining could be seen. To investigate the influence of protein abundance on the apparent specificity of the antibody, new WB analyses were performed for 1369 genes that gave unsupportive WBs in the initial screening using cell lysates with overexpressed full-length proteins. Then, more than 82% of the antibodies yielded a specific band corresponding to the full-length protein. Hence, the vast majority of the antibodies (90%) used in this study specifically recognize the target protein when present at sufficiently high levels. This demonstrates the context- and application-dependence of antibody validation and emphasizes that caution is needed when annotating binding reagents as specific or cross-reactive. WB is one of the most commonly used methods for validation of antibodies. Our data implicate that solely using one platform for antibody validation might give misleading information and therefore at least one additional method should be used to verify the achieved data.

  • 502. Ågren, Rasmus
    et al.
    Mardinoglu, Adil
    Asplund, Anna
    Kampf, Caroline
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Identification of anticancer drugs for hepatocellular carcinoma through personalized genome-scale metabolic modeling2014Inngår i: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 10, nr 3, s. A721-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Synopsis image Personalized GEMs for six hepatocellular carcinoma patients are reconstructed using proteomics data and a task-driven model reconstruction algorithm. These GEMs are used to predict antimetabolites preventing tumor growth in all patients or in individual patients. The presence of proteins encoded by 15,841 genes in tumors from 27 HCC patients is evaluated by immunohistochemistry. Personalized GEMs for six HCC patients and GEMs for 83 healthy cell types are reconstructed based on HMR 2.0 and the tINIT algorithm for task-driven model reconstruction. 101 antimetabolites are predicted to inhibit tumor growth in all patients. Antimetabolite toxicity is tested using the 83 cell type-specific GEMs. An l-carnitine analog inhibits the proliferation of HepG2 cells. Abstract Genome-scale metabolic models (GEMs) have proven useful as scaffolds for the integration of omics data for understanding the genotype-phenotype relationship in a mechanistic manner. Here, we evaluated the presence/absence of proteins encoded by 15,841 genes in 27 hepatocellular carcinoma (HCC) patients using immunohistochemistry. We used this information to reconstruct personalized GEMs for six HCC patients based on the proteomics data, HMR 2.0, and a task-driven model reconstruction algorithm (tINIT). The personalized GEMs were employed to identify anticancer drugs using the concept of antimetabolites; i.e., drugs that are structural analogs to metabolites. The toxicity of each antimetabolite was predicted by assessing the in silico functionality of 83 healthy cell type-specific GEMs, which were also reconstructed with the tINIT algorithm. We predicted 101 antimetabolites that could be effective in preventing tumor growth in all HCC patients, and 46 antimetabolites which were specific to individual patients. Twenty-two of the 101 predicted antimetabolites have already been used in different cancer treatment strategies, while the remaining antimetabolites represent new potential drugs. Finally, one of the identified targets was validated experimentally, and it was confirmed to attenuate growth of the HepG2 cell line.

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