|
| Status |
Public on Jan 01, 2024 |
| Title |
HCC tumor from patient MDA_014 |
| Sample type |
protein |
| |
|
| Source name |
primary HCC tumor
|
| Organism |
Homo sapiens |
| Characteristics |
organ: liver
age (years): 45
Sex: M
death: dead
follow-up (month): 9.37
|
| Treatment protocol |
Not treated
|
| Growth protocol |
Collected primary tumors
|
| Extracted molecule |
protein |
| Extraction protocol |
protein was extracted from tumors using an RPPA lysis buffer (1% Triton X-100, 50 nmol/L HEPES, pH 7.4, 150 nmol/L NaCl, 1.5 nmol/L MgCl2, 1 mmol/L EGTA, 100 nmol/L NaF, 10 nmol/L sodium pyrophosphate, 10% glycerol, 1 nmol/L phenylmethylsulfonyl fluoride, 1 nmol/L Na3VO4, 10 µg/mL aprotinin). Lysis buffer was used to lyse frozen tumors with a Precellys homogenizer (Bertin Instruments). Tumor lysates were adjusted to a concentration of 1 g/L as determined using a bicinchoninic acid assay and boiled with 1% sodium dodecyl sulfate.
|
| Label |
n/a
|
| Label protocol |
Protein lysate from each sample was spotted to nitrocellulose-coated slides and probed with over 200 antibodies. Printed proteins in slides were probed with 201 validated primary antibodies followed by corresponding secondary antibodies (goat anti-rabbit IgG, goat anti-mouse IgG, or rabbit anti-goat IgG)
|
| |
|
| Hybridization protocol |
Protein lysate from each sample was spotted to nitrocellulose-coated slides and probed with over 200 antibodies. Printed proteins in slides were probed with 201 validated primary antibodies followed by corresponding secondary antibodies (goat anti-rabbit IgG, goat anti-mouse IgG, or rabbit anti-goat IgG)
|
| Scan protocol |
Slides were scanned on a flatbed scanner to produce 16-bit tiff images. Spots from tiff images were identified and their densities were quantified by MicroVigene. Relative protein levels for each sample were determined by interpolation of each dilution curve from the standard curve (supercurve) of the slide (antibody). Supercurve is constructed from a script in R written by the informatics department. These values are given as Normalized values.
|
| Description |
Protein lysate from each sample was spotted to nitrocellulose-coated slides and probed with over 200 antibodies.
|
| Data processing |
Expression data was normalized for possible unequal protein loading, taking into account the signal intensity for each sample for all antibodies tested. Log2 values were media-centered by protein to account for variability in signal intensity by time and were calculated using the formula log2 signal to log2 median. Principal component analysis was used to check for a batch effect and feature-by-feature two-sample t-tests were used to assess differences between treatment and control groups. We also used feature-by-feature one-way analysis of variance (ANOVA) followed by the Tukey test to perform pair comparisons for all groups. Beta-uniform mixture models were used to fit the resulting p value distributions to adjust for multiple comparisons. The cutoff p values and number of significant proteins were computed for several different false discovery rates (FDRs).
|
| |
|
| Submission date |
Mar 22, 2022 |
| Last update date |
Jan 01, 2024 |
| Contact name |
Ju-Seog Lee |
| E-mail(s) |
jlee@mdanderson.org
|
| Phone |
713-834-6154
|
| Organization name |
UT MD Anderson Cancer Ctr.
|
| Street address |
6565 MD Anderson Blvd
|
| City |
Houston |
| State/province |
Texas |
| ZIP/Postal code |
77030 |
| Country |
USA |
| |
|
| Platform ID |
GPL32072 |
| Series (1) |
| GSE199141 |
Proteomic characteristics of mesenchymal subtypes of hepatocellular carcinoma |
|
