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Additional file 1 of Organelle resolved proteomics uncovers PLA2R1 as a novel cell surface marker required for chordoma growth

2024· article· en· W6977263482 on OpenAlexaff

Bibliographic record

VenueFigshare · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChromatin Remodeling and Cancer
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsProteomicsOrganelleProteomeTranscriptomeCellShotgun proteomics

Abstract

fetched live from OpenAlex

Additional file 1. Fig. S1: Protein detection and subtractive proteomics. a) Bar plot showing the number of proteins detected in each organelle fraction with the dots on the bar representing number of replicates. b) Principal component analysis (PCA) showing proteomic separation among the organelle fractions. c-f) Bar plot showing the number of proteins detected in the four clusters (through hierarchal clustering) corresponding to organelle selective proteins from different databases. Fig. S2: Differential expression analysis between organelle fractions. a) Venn diagram showing overlap between the plasma membrane fraction with all the other organelle fractions in the four chordoma cell lines. Proteins significantly enriched in plasma membrane fractions with a Geniescore of >20 and SPC score of 3 and the following cut-off values (FDR 1) are indicated in red. b) Upset plot showing the overlap of differentially expressed proteins with Genie score and SPC cut-off in the four chordoma cell lines. Fig. S3: Expression of PLA2R1 in HPA and publicly available proteomics and RNA-seq datasets. a) IHC staining of PLA2R1 in normal tissue as reported by HPA. 1 = Low expression; 2 = medium expression; 3 = high expression. b) Bar plot shows log2 iBAQ intensities of PLA2R1 in different normal tissues in the Wang et al. [44] proteomics dataset. c) Boxplots show log2 normalised protein abundance of PLA2R1 in the GTEx proteomics dataset, with bar plot showing number of samples the protein was detected in. D) Boxplots show log2 TPM+1 of PLA2R1 in GTEx transcriptomics dataset, with bar plot showing number of samples the protein was detected in different normal tissues. Fig. S4: Validation of PLA2R1. a) Immunoblots showing expression of PLA2R1 in an additional chordoma cell line, UM-Chor1 and in a negative control ovarian cancer cell line, Ovcar8. b) Representative IHC image showing expression of PLA2R1 localized to cell membrane. c) Expression of PLA2R1 in U-CH17M, U-CH17S and UM-Chor1 cell line after 24 and 48 hours of siRNA knockdown. d) Digital images of colony formation assay after siRNA KD of PLA2R1. Fig. S5: a) Boxplot with jitters showing almarBlue fluorometric intensity of the spheroids (p-values calculated with t-test, between sg1 and sg2 compared against LacZ). b) Immunoblots showing expression of total PARP and caspases in PLA2R1 KD cells and controls. c) Immunoblots showing that cleaved PARP, Caspase 3 and Caspase 7 expression are not observed after PLA2R1 KD. d) Immunoblots for total and phosphorylated AKT1 and its downstream substrate. The immunoblots show no change in phosphorylation of AKT and its downstream substrates. Fig. S6: Effect of PLA2R1 knockdown on cell proliferation. a) Plot showing cell proliferation by cell counting for a period of 16 days. The PLA2R1 KD cells show a slow down in growth compared to controls. b) Stacked barplot from EdU cell proliferation assay (n = 3) showing percentage (mean values from three experiments) of cells in different phases of cell cycle G0-G1 phase, S-phase and G2-M phase of PLA2R1 KD cells (sg1 and sg2) and controls (NT and LacZ). There is a higher percentage of cells in G0-G1 phase in PLA2R1 KD cells compared to control (LacZ) (p- values calculated with t-test comparison between sg1 and sg2 compared against LacZ). Lower percentage of cells in S-phase of cell cycle (p-values calculated with t-test comparison between sg1 and sg2 compared against LacZ). c–f) Representative images of EdU flow cytometry experiment of PLA2R1 KD cells (sg1 and sg2) and control cells (NT and LacZ).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.761
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.7610.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.236
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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