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Quantative data in PhosphoSitePlus® (PSP)

We have begun curating quantitative MS2 datasets into PSP: these will be accessible from the “QUANT” column in the Browsing interfaces as shown below. The CST-LINCS datasets described below are new datasets not yet published elsewhere. They are made available to the community so that novel analytical tools might be applied to the multidimensional data that will lead to new insights in network biology and the cell biology of cancer.



CST-LINCS MS TMT Data.

PTM-specific antibodies were used to enrich modified peptides followed by 6-plex TMT mass-spec analyses to quantitatively measure over 12,000 differentially phosphorylated, acetylated, and methylated sites on over 4,000 proteins. Two sets of experiments were performed:

  • The “Lung Cancer Cell Line” (LCCL) study includes 45 lung cancer cell lines, 12 SCLC and 33 NSCLC cell lines, including those with known oncogenic kinases and fusion-proteins. Comparison of NSCLC with SCLC reveals different kinase signatures between the two types.

  • The “Drug Treament” (TKI) study includes 6 cancer cell lines with known disease drivers, 5 NSCLC and one gastric carcinoma with an amplification of the Met oncogene. Cell lines were treated with three different TKIs and the kinetics of protein modifications were followed from 1 to 24 hours. These datasets are available in the accompanying Excel file.

Antibodies and Signaling Spaces. Seven signaling spaces were analyzed for each sample using the following CST motif antibodies. The signaling space is in Italic followed by the specificity of the antibody and its CST Catalog #: Tyrosine kinase signaling (phospho-Tyr, #5636); Growth/cell cycle (phospho-MAPK/CDK substrates, #5501); Metabolism/energy sensing (phospho-AMPK substrates, #5759); Growth/anti-apoptosis (phospho-Akt/AGC substrates, #9614); DNA Damage Response (phospho-ATM/ATR substrate, #9607); RNA Processing/Epigenetics (methyl-1 Arginine, (not yet in catalog)); and Metabolism/Epigenetics (acetyl-Lysine, #13416).


General goals:

  • Identify phospho (p), acetyl (ac) and methyl (me) PTMs that cocluster and may be functionally linked in lung cancer cell lines

  • Identify and analyze differences between SCLC and NSCLC PTM signatures

  • Identify p[ST], acK, meK, and meR sites that may be regulated downstream from pY signaling in CCLs with known driver mutations

These experiments are described in greater detail in the accompanying Power Point Show presentation.


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