Fig 1: Discovery of Synthetic Lethal Interactions with Genomic Loss of Established Tumor Suppressors(A) Synthetic lethality analysis workflow. Copy number of 51 tumor suppressor genes across cancer cell lines was correlated with gene-dependency scores from CRISPR-SpCas9 or RNAi interference screens.(B) q-q plot showing significant, positive Pearson’s correlations between gene dependency scores and tumor suppressor gene deletion. For each pair, the dependency gene is listed first, followed by the associated tumor suppressor gene. Highly significant correlations (FDR 10%, q < 0.1) are highlighted (beige) with emphasis on the VPS4A-SMAD4 and VPS4B-CDH1 synthetic lethal interactions (pink).(C) Number of significant synthetic lethal interactions for each tumor suppressor gene that shows significant dependency-copy number Pearson’s correlation coefficient in both RNAi and CRISPR datasets (q < 0.1).(D) Log-normalized q-values for all significant and positive correlating gene dependencies (q < 0.1) for the 10 most-correlated tumor suppressor genes.See also Figures S1 and S10, Table S1, and Data S1.
Fig 2: VPS4A Suppression Leads to ESCRT-III Filament Accumulation, Deformed Nuclei, and Abscission Defects in VPS4Bloss Cancer Cells(A) Known functions of the ESCRT machinery in membrane biology.(B) Digitized immunoblot showing VPS4A and Vinculin protein levels in VPS4Bneutral and VPS4Bloss cancer cell lines with the dox-inducible shVPS4A-2 RNAi system after 5 days of treatment with control or 1 µM dox.(C) Confocal immunofluorescence of CHMP4B in four cancer cell lines with the dox-inducible shVPS4A-2 RNAi system, from (B) imaged after 6 days of treatment. (grayscale, scale bars: 50 µm).(D) Quantification of CHMP4B speckle formation in untreated (orange) and dox-treated (blue) cells from (C) on multiple random images (n = 3–9). ns, not significant; **q < 0.01, ****q < 0.0001.(E) Confocal fluorescence imaging of DNA (DAPI, blue) of parental RD-SpCas9 cancer cells euploid for VPS4B copy and clone B2 RD-SpCas9 cancer cells with knockout of VPS4B (Figures 4F, 4G, and S6D). Scale bars: 50 mm. Nuclear surface size by CellProfiler. ****p < 0.0001.(F) Confocal (immuno)fluorescence of the inner nuclear membrane protein Emerin (Alexa Fluor 561, red) and DNA (DAPI, blue) in four different cancer cell lines, from (B) after 6 days of treatment. Arrows: micronuclei. Scale bars: 50 µm.(G) (Immuno)fluorescence of cytokinetic bridges and midbodies using tubulin (Alexa Fluor 488, green) and DNA (DAPI) in 3 different cancer cell lines after 4 days of induction of CRISPR-SpCas9-mediated disruption of an intergenic region (sgChr2–2) or VPS4A (sgVPS4A-1). Arrows: cytokinetic bridges.(H) Quantification of cancer cells connected to neighboring cells by cytokinetic bridges. ns, not significant; **p < 0.01, ****p < 0.0001.See also Figure S7.
Fig 3: Interferon Signaling and CHMP4B Expression Modulate VPS4A Dependency(A) Pearson’s correlation coefficients between gene mRNA expression and CRISPR-SpCas9 VPS4A dependency scores (x axis) and the log-normalized statistical significance (q value) of these interactions (y axis) across 619 CCLE cancer cell lines. Top negatively correlated genes are shown in orange, whereas genes localizing to chromosome 18q are shown in blue. Grey area, values outside 5% FDR q < 0.05.(B) Gene set-enrichment plot showing statistical significance (x axis) of Metascape (https://metascape.org) summary gene sets mapped to the top 250 genes whose mRNA expression significantly anticorrelated with VPS4A CRISPR dependency scores, orange genes in (A). Gene sets associated with interferon signaling are highlighted (blue).(C) Six-day cell viability of KP4 and SNU213 pancreatic cancer cell lines stably expressing the dox-inducible shVPS4A-2 RNAi system (see STAR Methods).(D) Digitized immunoblot and quantification of VPS4A, VPS4B and total protein from SNU213-shVPS4A-2 cancer cells treated for 4 days with interferon-ß (blue) or interferon-? (orange-brown).(E) Linear regression with 95% confidence interval (blue line) and Pearson’s correlation between prediction values from a 10-fold cross-validated multiple linear regression model (y axis) and observed VPS4A CRISPR dependency scores (x axis). The linear model uses normalized VPS4B, CHMP4B, ISG15, and ITCH mRNA expression values across 621 cancer cell lines to predict VPS4A dependency.(F) As in (E) but for VPS4B CRISPR dependency scores (x axis).See also Figure S9 and Table S1.
Fig 4: Altered VPS4B Expression Modulates VPS4A Dependency in Cancer Cells(A) Linear regression with 95% confidence interval (blue line) and Pearson’s correlation between VPS4B RNA-seq expression (y axis) and VPS4B relative copy number (x axis) from 1,196 cancer cell lines in the CCLE.(B) Histogram of Pearson’s correlation coefficients of correlating each gene’s mRNA expression level with its copy number for all 18,749 genes from the CCLE (orange histogram), with VPS4A and VPS4B indicated. The blue histogram shows a null distribution generated by correlating 18,749 random copy number-mRNA expression gene pairs.(C) Linear regression correlation with 95% confidence interval (blue line) and Pearson’s correlation between VPS4B quantitative mass-spectrometry protein expression (y axis) and VPS4B relative copy number (x axis) from 374 cancer cell lines in the CCLE. y axis represents log2 protein expression of a cell line normalized to expression of the protein in a set of 10 reference cancer cell lines (zero as mean reference value).(D) Digitized VPS4B and total protein immunoblot from 29 cancer cell lines (n = 14 VPS4Bneutral and 15 VPS4Bloss). Relative VPS4B copy number values from the CCLE are shown.(E) Linear regression with 95% confidence interval (blue line) and Pearson’s correlation between quantified, normalized VPS4B protein levels from (D) and VPS4B relative copy number across cancer cell lines with neutral (gray) or reduced (black) VPS4B copy number. Violin plot with the average and standard deviation marked for normalized VPS4B protein level in VPS4Bneutral and VPS4Bloss cancer cells. ****p < 0.0001.(F) VPS4B immunoblot from the parental RD-SpCas9 cancer cell line (VPS4Bneutral) and a mixture of two pools of four monoclonal RD-SpCas9 VPS4B-/- CRISPR-SpCas9 knockout cell lines.(G) Cell viability of VPS4Bneutral RD-SpCas9 cells (left panel) and two pools of four monoclonal RD-SpCas9 VPS4B-/- cell lines, from (F) and Figure S6D. Each dot represents normalized cell viability from an individual assay well with the indicated sgRNAs (legend), and black bars indicate the mean of each group.(H) VPS4B immunoblot from the VPS4Bloss JR-SpCas9 cancer cell line and a JR-SpCas9 cancer cell line overexpressing VPS4BWT fused to a V5 protein tag.(I and J) Cell viability of VPS4Bloss JR-SpCas9 cancer cells (left) and JR-SpCas9 cells overexpressing the indicated controls or VPS4B (I) or VPS4A (J) cDNAs. ORF, open reading frame. Black bars indicate the mean of each group.See also Figure S6.
Fig 5: Validation of VPS4A as a Dependency in Cancer Cells with Copy Loss of VPS4B(A) Seven-day viability assays from eight VPS4Bneutral and 10 VPS4Bloss cell lines stably transduced with CRISPR-SpCas9. Each dot represents the mean viability effect (y axis) of cells infected with the indicated sgRNA (n = 3). Black bars indicate the mean cell viability effect of all three VPS4A sgRNAs. See Method Details. ****p < 0.0001.(B) Seven-day viability assays from 2 VPS4Bneutral and 5 VPS4Bloss cell lines stably transduced with the shSeed2 control (orange) and shVPS4A-2 (blue) tetracycline-inducible RNAi reagents after treatment with 0.5 µM of doxycycline (dox; 0.222 µg/mL). Each dot represents a technical replicate and shows relative cell viability (y axis) compared with untreated cells. ns, not significant; ****p < 0.0001.(C) Ten-day proliferation curve of VPS4Bloss SNU213 pancreatic cancer cells stably transduced with the tetracycline-inducible RNAi system for shSeed2 control (orange and brown) or shVPS4A-2 (blue). Cells were either grown in control or 1 mM dox (0.444 µg/mL) medium.(D) In vivo subcutaneous tumor growth in immune-compromised NOG mice of VPS4Bloss SMSCTR rhabdomyosarcoma (top) and SNU213 pancreatic cancer cells (bottom) stably transduced with the SpCas9 endonuclease and either the shSeed2 control (orange) or the shVPS4A-2 (blue) tetracycline-inducible RNAi systems. ****p < 0.0001.(E) Kaplan-Meier survival plot of NOG mice bearing subcutaneous SMSCTR (top) or SNU213 (bottom) xenografts described in (D). Crosses indicate censored mice. ****p < 0.0001.(F) Digitized immunoblot for VPS4A, VPS4B, and Vinculin from SMSCTR (top) and SNU213 (bottom) xenograft tumors in NOG mice described in (D). SMSCTR, 7 days after randomization; SNU213, days 20~25 after treatment start for shSeed2 untreated or day 73 after treatment start for shVPS4A-2, +dox.(G) Caspase 3/7 apoptosis activity (y axis) over time (x axis) in four cancer cell lines. Cells stably expressing SpCas9 were lentivirally transduced with a control sgRNA (orange) or an sgRNA targeting VPS4A (blue). Caspase 3/7 signal was normalized relative to time-matched uninfected cells. ****p < 0.0001.(H) Stacked bar plots showing cell cycle distribution of ES2, KP4 (VPS4Bneutral, gray) and SMSCTR, 59M and JR (VPS4Bloss, black) cells using DAPI staining and EdU incorporation analyzed by flow cytometry 4 days after VPS4A ablation by CRISPR-SpCas9. *q < 0.05, **q < 0.01, ***q < 0.001, ****q < 0.0001.See also Figure S5 and Table S1.
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