Overexpression of <i>RECQL4</i> results in increased RAD51 foci and decreased tail moment.

(A) Overexpression of RECQL4 results in increased RAD51 foci, which is dependent on its helicase activity. U2OS cells were transfected with an empty plasmid or a plasmid expressing RECQL4 or RECQL4-K508A under a CMV promoter. The cells were either mock or cisplatin treated for one hour and after a two-hour recovery, imaged for RAD51 foci or DAPI by immunofluorescence. RAD51 foci was quantified from 200 cells per condition for each experiment. The experiment was performed three to five times and the median was graphed (Unprocessed foci count in S9 Data). Representative images are shown. (B) Overexpression of RECQL4 results decreased tail moment following cisplatin exposure, which is dependent on its helicase activity. U2OS cells were treated similarly to the immunofluorescence experiment, before being harvested for neutral comet assay. At least 40 comets were counted per condition for each experiment. The experiment was performed four times and the mean and standard deviation was graphed (Unprocessed tail moments in S10 Data).</p

Cross-cancer validation of CASCAM.

(A) Genome-wide preselection identifies 5 out of 24 liver cell lines as ILC. (B) Pathway-based heatmap reveals that these 5 preselected cell lines significantly diverge from the ILC tumor center in terms of differentially expressed genes and associated pathways. (TIF)</p

Densitometry for yeast cycloheximide chase experiments.

(XLSX)</p

Flowchart of CASCAM for congruence quantification and selection.

Tumor and cancer model gene expression data are first harmonized (Module 1). Transparent machine learning by sparse discriminant analysis (SDA) is applied by combining predication accuracy and SDA-based deviance score for pre-selecting candidate cancer models (Module 2). Pathway-specific mechanistic explorations are iteratively investigated to conclude the final representative cancer model (Module 3). Blue frames represent input data, orange frames for essential output results, parallelogram frames for intermediate results, rectangular frames for analysis process, bullet-shaped frames for visualization, and rhombus frames for decision making.</p

High RECQL4 expression correlates with increased recombination, mutations, and tumorigenesis.

(A) RECQL4 expression is elevated in tumors in comparison to adjacent normal tissue. RNAseq data from tumors and normal tissue matched samples was acquired from TCGA. The data was normalized by transcripts per million (TPM), then analyzed for RECQL4 expression. Box and whisker plots graph the median of the data alongside the 25th and 75th percentile. The number of samples alongside p-value are shown using Mann-Whitney U test. (B) RECQL4 expression is higher in ER- breast cancer. Transcriptome data from TCGA (RNA-seq) and METABRIC (microarray) was analyzed for RECQL4 expression in ER- (blue) and ER+ (red) cancers. Log2 (TPM+1) and normalized probe intensity were used respectively. Box and whisker plots alongside each data point was graphed. The number of samples alongside p-value are shown using Mann-Whitney U test. (C) Elevated levels of RECQL4 are associated with increased tumor mutation burden. The expression of RECQL4 in ER- breast tumors from TCGA was divided into quartiles based upon expression level. The mutation burden between the least expressing tumors (Quartile 1 –Q1, blue) and the highest expressing tumors (Quartile 4 –Q4, red) was analyzed. Box and whisker plots alongside each data point was graphed. The number of samples alongside p-value are shown. Annotated mutational data from ER- breast cancer was acquired from Firebrower. The mutational data was categorized using “maftools” in R. Tumor mutation burden was scored as described (Wang et al 2019). Significance was determined by Mann-Whitney U test. (D) High expression of RECQL4 correlates with enrichment of DNA repair, G2M checkpoint, MYC Targets V1, E2F Targets 1 and 2 in TNBC. Gene set variation analysis (GSVA) was performed on TNBC gene expression data from both TCGA and METABRIC using the 50 Hallmark gene sets from MSigDB. Correlation between TCGA and METABRIC datasets was plotted for enriched pathways. (E) Homologous recombination and RAD51 is enriched in TNBC tumors expressing high levels of RECQL4. GVSA results of “KEGG Homologous Recombination” gene set (MSigDB M11675) was parsed for the top 20 DNA repair genes enriched in TNBC tumors expressing high levels of RECQL4. HR pathway was enriched by GSVA analysis in RECQL4 high expressing TNBC compared to loss expressing TBNC. Box and whisker plots alongside each data point was graphed. The number of samples alongside p-value are shown using Mann-Whitney U test. (F,G) RECQL4 expression serves as a predictor for clinical outcomes. High expression of RECQL4 correlates with positive response to cisplatin and favorable clinical outcome (Good responder). Analysis from a study where cisplatin was given as a neoadjuvant therapy in 24 TNBC tumors [64]. Lower expressing RECQL4 tumors are shown as blue dots and high expressing RECQL4 tumors are shown as red dots. Clinical response to cisplatin was measured as progressive disease (PD), stable disease (SD), partial response (cPR), complete response (cCR). Good and poor responders were defined as patients with cPR/cCR status and PD/SD status respectively. Increased RECQL4 expression correlates with a good clinical response as determined by Mann-Whitney U test. Pathological response to cisplatin was monitored by Miller Payne metric score (grade 1 is no significant tumor reduction and grade 5 is compete tumor reduction) and graphed based on RECQL4 expression. Good and poor responders were defined as patients with a Miller Payne Score of 4–5 or 0–3 respectively. Increased RECQL4 expression correlates with a good pathological response as determined by Mann-Whitney U test.</p

High level of Hrq1-7KR results in cell lethality.

(A) Hrq1-7KR protein levels are similar to WT in basal conditions. The indicative strains were grown overnight in 2% galactose, subsequently TCA was performed and western was run to determined protein level. (B) Stabilization or overexpression of Hrq1 does not lead to increased cisplatin sensitivity. The indicated yeast strains were five-fold serial diluted onto SC medium containing DMSO and/or SC medium containing the indicated amount of cisplatin. The plates were photographed after 2 days of incubation at 30°C in the dark. Plates that were used with Hrq1-OE (GAL-HRQ1, galactose inducible/dextrose repressible promoter) strains were made with galactose instead of glucose medium. (C) Overexpression of the Hrq1-7KR mutant results in cell lethality. The indicated yeast strains were grown overnight in SC medium containing raffinose. Subsequently they were five-fold serial diluted onto galactose SC plates. The plates were photographed after 2 days of incubation at 30°C in the dark. (D) pCMV-RECQL4-KA promotes similar overexpression compared to pCMV-RECQL4. Protein extracts from cells 3 days post-transfection. Endogenous RECQL4 was detected using α-RECQL4, GAPDH served as a control. (TIF)</p

Confusion matrix of genome-wide predication for HER2+, ER+/PR+, and TNBC prediction.

Confusion matrix of genome-wide predication for HER2+, ER+/PR+, and TNBC prediction.</p

Although Hrq1 is needed for cisplatin resistance, it is degraded by the proteasome upon cisplatin exposure.

(A) HRQ1-null cells are sensitive to cisplatin. Wild-type (WT) or hrq1Δ disrupted cells were five-fold serially diluted on medium containing 30 μg/ml cisplatin and/or 0.1% DMSO, grown for 48 hours at 30°C, and photographed. (B) Hrq1 level is stable following treatment with other DNA damaging agents: cisplatin (100 ug/ml), MMS (0.03%), IR (100 Gy), HU (100 mM). Exponentially growing cells with Hrq1-9xMYC were treated with the indicated drugs for 2 hours before being harvested for western. (C) Hrq1 protein levels are decreased upon cisplatin treatment. Exponentially growing cells with Hrq1-9xMYC were incubated with cycloheximide in the presence or absence of 100 μg/ml cisplatin and/or 0.1% DMSO. Quantification of the proportion of Hrq1 remaining relative to time 0 (before CHX addition) and the loading control, Kar2. The experiment was performed five times with mean and standard error plotted (Raw densitometry data in Sheets A-E in S1 Data). It is important to note that Hrq1 and the loading control, Kar2, were analyzed from the same gels to account for pipetting errors. Since Hrq1 is not as abundant as the loading control, there is a limitation for the densitometry analysis. (D) The proteasome degrades Hrq1 following cisplatin exposure. PDR5 disrupted cells were untreated (0.1% DMSO), cisplatin treated, or pretreated for one hour with 50 μM MG-132 before cisplatin addition with 0.1% DMSO. Cycloheximide chases were performed the similarly as (B) but further timepoints were taken.</p

Model of Hrq1/RECQL4 function during replication-associated intrastrand crosslink repair.

When the replication fork stalls, PCNA (yellow trimer) is monoubiquitylated (Ub, purple circle) by Rad6-Rad18 on lysine 164 (K164). Monoubiquitylation of PCNA recruits the error-prone translesion synthesis polymerases, i.e. Rev1 to bypass the lesion. Alternatively, PCNA is further poly-ubiquitylated by Rad5-Ubc13-Mms2. Polyubiquitylation of PCNA mediates error-free repair through template switching, which is a homology directed process. Hrq1/RECQL4 (blue oval) facilitates a template switch to bypass the lesion and then is subsequently ubiquitylated by Rad16 and degraded. Degradation of Hrq1 by the proteasome prevents aberrant recombination and subsequent mutation. Once the lesion is bypass, the NER machinery facilitates repair. Created using biorender.com.</p

UMAP of Celligner alignment between tumors and PDX/PDO models.

(A) Three distinct clusters were observed. The small cluster on the left consists of a seemingly rare breast cancer subtype, the upper-right cluster includes mostly non-basal samples, and the lower-right cluster includes mostly basal samples. (B) UMAP is redrawn when the small cluster in (A) is removed. (TIF)</p