Table S1: Description of the BCAC studies contributing to COGS. Table S2: Predicted effects of BRCA1 and BRCA2 variants included in the iCOGS array on protein function. Table S3: Frequency of BRCA1 and BRCA2 variants from iCOGS in breast cancer cases and controls. Table S4: Family studies of Y3035S showing scores for each family by constant relative risk and 75% penetrance. Supplementary References.

Table S1 shows the clinicopathological characteristics of the cases included in final analysis.

<p>Grade ≥ 3 adverse events (28 patients)</p>

Top-25 probesets differentially expressed between irradiated (2Gy) and control (0Gy) lymphocytes.

Figure S1: BCRA2 p.Y3035S Pedigrees. Figure S2: Western blot of ectopically expressed full-length wildtype and mutant hBRCA2 protein in VC8 DR-GFP cells subjected to HDR assay. Figure S3: Purification of wildtype and mutant BRCA2 from human cells. Figure S4: Position of BRCA2 DNA binding domain (DBD) variants on a ribbon diagram of the murine DBD crystal structure.

This case study explores the applicability of transcriptome data to characterize a common mechanism of action within groups of short-chain aliphatic α-, β-, and γ-diketones. Human reference in vivo data indicate that the α-diketone diacetyl induces bronchiolitis obliterans in workers involved in the preparation of microwave popcorn. The other three α-diketones induced inflammatory responses in preclinical in vivo animal studies, whereas beta and gamma diketones in addition caused neuronal effects. We investigated early transcriptional responses in primary human bronchiolar (PBEC) cell cultures after 24 h and 72 h of air-liquid exposure. Differentially expressed genes (DEGs) were assessed based on transcriptome data generated with the EUToxRisk gene panel of Temp-O-Seq®. For each individual substance, genes were identified displaying a consistent differential expression across dose and exposure duration. The log fold change values of the DEG profiles indicate that α- and β-diketones are more active compared to γ-diketones. α-diketones in particular showed a highly concordant expression pattern, which may serve as a first indication of the shared mode of action. In order to gain a better mechanistic understanding, the resultant DEGs were submitted to a pathway analysis using ConsensusPathDB. The four α-diketones showed very similar results with regard to the number of activated and shared pathways. Overall, the number of signaling pathways decreased from α-to β-to γ-diketones. Additionally, we reconstructed networks of genes that interact with one another and are associated with different adverse outcomes such as fibrosis, inflammation or apoptosis using the TRANSPATH-database. Transcription factor enrichment and upstream analyses with the geneXplain platform revealed highly interacting gene products (called master regulators, MRs) per case study compound. The mapping of the resultant MRs on the reconstructed networks, visualized similar gene regulation with regard to fibrosis, inflammation and apoptosis. This analysis showed that transcriptome data can strengthen the similarity assessment of compounds, which is of particular importance, e.g., in read-across approaches. It is one important step towards grouping of compounds based on biological profiles.

Figure S1: Schematic workflow of RAD51IRIF assay and accessory experimental timeline. Figure S2: Validation of RAD51 IRIF immunostaining: 2 hours post IR is optimal for RAD51 focus formation which are only formed in GEMININ positive cells Figure S3: ᵞ-H2AX and 53BP1 nuclear foci indicate the induction of DSBs in tissue slices Figure S4: Non-tumor cells display normal formation of RAD51 foci in tumor samples with impaired RAD51 IRIF formation Figure S5: Mutation and methylation analysis of impaired RAD51 IRIF tumors Figure S6: Tumor samples with BRCA1 promoter methylation displayed no in situ detection of BRCA1 mRNA Table S1: Complete overview of all tumor samples including Clinico-pathological characteristics Table S2: Clinico-pathological characteristics of Geminin positive vs Geminin negative tumor samples

Supplementary Tables S1-S4. Table S1. Description of primers used in this study. Table S2. Variants selected in BRCA2 exon 12 and its flanking intronic regions. Table S3. Overview of bioinformatics predictions and experimental data obtained for the 40 selected BRCA2 exon 12 variants. Table S4. Clinical and family data of patients carrying BRCA2 exon 12 spliceogenic variants.

Description of additional methods and procedures used in the study. Also includes Supplementary References.

PURPOSE:BRCA-deficient breast cancers (BC) are highly sensitive to platinum-based chemotherapy and PARP inhibitors due to their deficiency in the homologous recombination (HR) pathway. However, HR deficiency (HRD) extends beyond BRCA-associated BC, highlighting the need for a sensitive method to enrich for HRD tumors in an alternative way. A promising approach is the use of functional HRD tests which evaluate the HR capability of tumor cells by measuring RAD51 protein accumulation at DNA damage sites. This study aims to evaluate the performance of a functional RAD51-based HRD test for the identification of HRD BC.METHODS:The functional HR status of 63 diagnostic formalin-fixed paraffin-embedded (FFPE) BC samples was determined by applying the RAD51-FFPE test. Samples were screened for the presence of (epi)genetic defects in HR and matching tumor samples were analyzed with the RECAP test, which requires ex vivo irradiated fresh tumor tissue on the premise that the HRD status as determined by the RECAP test faithfully represented the functional HR status.RESULTS:The RAD51-FFPE test identified 23 (37%) of the tumors as HRD, including three tumors with pathogenic variants in BRCA1/2. The RAD51-FFPE test showed a sensitivity of 88% and a specificity of 76% in determining the HR-class as defined by the RECAP test.CONCLUSION:Given its high sensitivity and compatibility with FFPE samples, the RAD51-FFPE test holds great potential to enrich for HRD tumors, including those associated with BRCA-deficiency. This potential extends to situations where DNA-based testing may be challenging or not easily accessible in routine clinical practice. This is particularly important considering the potential implications for treatment decisions and patient stratification.

<p>A CAMERA geneset test was performed to identify sets consisting of genes that are highly ranked in terms of differential expression upon irradiation relative to genes not in the set.</p>

Table S2 shows the clinicopathological characteristics of the homologous recombination intermediate cases.

Table S3 gives an overview of the detected class 3, 4 and 5 variants in the final cohort.

<p>Differential response to irradiation between Grade 3 and Grade 0 patients for the probesets part of the HR geneset.</p>

Receiver operating characteristic (ROC) curve and foci decay ratios from our retrospective study ; Induction of gene expression upon irradiation calculated within each individual patient (indicated by the index on the x-axis) for three selected radiation-sensitive genes ; Enrichment of the set of 439 probesets included in the HALLMARK P53 PATHWAY geneset that was strongly induced upon irradiation ; Volcano plots for the comparison of response to irradiation between Grade 3, 2, 1 and Grade 0 patients ; Receiver operating characteristic curve for the mean log2 fold inductions of the HR geneset .

Differential response to irradiation between Grade 3 and Grade 0 patients for the probesets part of the NHEJ/BEJ geneset.

Supplementary Material and Methods

<p>Differential response to irradiation between Grade 3 and Grade 0 patients for the probesets part of the HR geneset.</p>

<p>Top-10 probesets with a different response to irradiation between the four patient groups.</p>

Fig. S1 to S10. Figure S1. Variant selection from human variation databases; Figure S2. Capillary electrophoresis analyses of BRCA2 exon 12 splicing patterns in minigene assays of presumed LoF variants; Figure S3. Bioinformatics predictions of 3'/5' ss alterations for variants located at position IVS{plus minus}1/2 of BRCA2 exon 12; Figure S4. Bioinformatics analysis of variants predicted to alter 3'/5' ss of BRCA2 exon 12 (â^†MES {less than or equal to} -15%); Figure S5. Capillary electrophoresis analyses of BRCA2 exon 12 splicing patterns in minigene assays of variants predicted to alter 3'/5' ss (A) or ESR (B); Figure S6. Capillary electrophoresis analyses of BRCA2 exon 12 splicing patterns in control and patient lymphoblastoid cell lines; Figure S7. RT-PCR analysis of BRCA2 exon 12 splicing patterns in puromycin- or mock-treated lymphoblastoid cell lines of control individuals and patients carrying the c.6844G>T or c.6901G>T nonsense variants; Figure S8. Capillary electrophoresis analyses of BRCA2 exon 12 splicing patterns in variant-expressing mESC; Figure S9. Quantitation of BRCA2 protein expression in mESC; Figure S10. Sensitivity of BRCA2 variants to cisplatin and PARP inhibitors.