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BACKGROUND: Cyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo-ovarian high-grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large-scale, histotype-specific validation has been performed. The hypothesis was that high-level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC. METHODS: Within the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated. RESULTS: High-level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high-level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08-1.47, p = .034, and HR, 1.18; 95% CI, 1.05-1.32, p = .015, respectively). This was also true for cases with combined high-level amplification/overexpression (HR, 1.26; 95% CI, 1.09-1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1-SD increase; 95% CI, 0.94-1.06; p = .58). CCNE1 high-level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss. CONCLUSION: This study provides large-scale validation that CCNE1 high-level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC. ispartof: CANCER vol:129 issue:5 pages:697-713 ispartof: location:United States status: published

How to identify follicular lymphoma (FL) patients with low disease burden but high risk for early progression is unclear. Building on a prior study demonstrating the early transformation of FLs with high variant allele frequency (VAF) BCL2 mutations at activation-induced cytidine deaminase (AICDA) sites, we examined 11 AICDA mutational targets, including BCL2, BCL6, PAX5, PIM1, RHOH, SOCS, and MYC, in 199 newly diagnosed grade 1 and 2 FLs. BCL2 mutations with VAF ≥20% occurred in 52% of cases. Among 97 FL patients who did not initially receive rituximab-containing therapy, nonsynonymous BCL2 mutations at VAF ≥20% were associated with increased transformation risk (HR 3.01, 95% CI 1.04–8.78, p = 0.043) and a trend toward shorter event-free survival (EFS, median 20 months with mutations versus 54 months without, p = 0.052). Other sequenced genes were less frequently mutated and did not increase the prognostic value of the panel. Across the entire population, nonsynonymous BCL2 mutations at VAF ≥20% were associated with decreased EFS (HR 1.55, 95% CI 1.02–2.35, p = 0.043 after correction for FLIPI and treatment) and decreased overall survival after median 14-year follow-up (HR 1.82, 95% CI 1.05–3.17, p = 0.034). Thus, high VAF nonsynonymous BCL2 mutations remain prognostic even in the chemoimmunotherapy era.

Supplementary Table 1 showing qRT-PCR primer sequences

PARP inhibitors (PARPi) have activity in homologous recombination (HR) repair-deficient, high-grade serous ovarian cancers (HGSOC). However, even responsive tumors develop PARPi resistance, highlighting the need to delay or prevent the appearance of PARPi resistance. Here, we showed that the ALK kinase inhibitor ceritinib synergizes with PARPis by inhibiting complex I of the mitochondrial electron transport chain, which increases production of reactive oxygen species (ROS) and subsequent induction of oxidative DNA damage that is repaired in a PARP-dependent manner. In addition, combined treatment with ceritinib and PARPi synergized in HGSOC cell lines irrespective of HR status, and a combination of ceritinib with the PARPi olaparib induced tumor regression more effectively than olaparib alone in HGSOC patient-derived xenograft (PDX) models. Notably, the ceritinib and olaparib combination was most effective in PDX models with preexisting PARPi sensitivity and was well tolerated. These findings unveil suppression of mitochondrial respiration, accumulation of ROS, and subsequent induction of DNA damage as novel effects of ceritinib. They also suggest that the ceritinib and PARPi combination warrants further investigation as a means to enhance PARPi activity in HGSOC, particularly in tumors with preexisting HR defects.Significance:The kinase inhibitor ceritinib synergizes with PARPi to induce tumor regression in ovarian cancer models, suggesting that ceritinib combined with PARPi may be an effective strategy for treating ovarian cancer.

Supplementary Materials and Methods

Supplementary Figures 1-8 with legends

Table S1 is an Excel sheet that provides a detailed listing of primary BRCA and TP53 mutations as well as BRCA reversion mutations detected in pretreatment and postprogression circulating cell-free DNA and tumor biopsy samples

A list of copy number alterations, rearrangements and short variants detected by Foundation Medicine NGS

Supplementary Tables, Figures and Video legends, Tables 2,3,5 and all Supplementary Figures. Supplementary Table 2. Confirmation of cis configuration of BRCA1 primary and secondary mutations in case 4 by colony PCR. Supplementary Table 3. IC50 (mircoM) values of the PARPi and platinum drugs in parental OVCAR8 cell line and OVCAR8 RAD51C KO clone, and the fold change in IC50 values. Supplementary Table 5. Sequences of primers used for site-directed mutagenesis. Supplementary Figure 1. Foundation Medicine NGS analysis of the 12 cases with archival tissue and/or pre-treatment and post-progression biopsies. Supplementary Figure 2. Sanger sequencing trace of the primary and secondary BRCA1 mutations in cis configuration in case 4 post-progression biopsy sample. Supplementary Figure 3. In vitro response to PARP inhibitor therapy and platinum agents in RAD51C deficient cell lines, with primary or secondary mutations in RAD51C. Supplementary Figure 4. RAD51 foci formation in geminin positive cells deficient for RAD51C, complemented with primary or secondary mutations in RAD51C. Supplementary Figure 5. Diagram of HR reporter assay. Supplementary Figure 6. RAD51C expression in MCF10A cells and in yeast. Supplementary Figure 7. Analysis of serial sections by direct PCR sequencing approach of a post-progression biopsy containing multiple secondary mutations in RAD51C. Supplementary Figure 8. Molecular Dynamics Modeling of WT RAD51D protein and RAD51D protein with secondary mutation c.770_776delinsA, p.S257_R259delinsK. Supplementary Figure 9. In vitro response to PARP inhibitor therapy and cisplatin in RAD51D deficient CHO cell line, with primary or secondary mutation in RAD51D. Supplementary Figure 10. Examination of the parental PEO4 cell line, PEO4 cells with the homozygous frameshift RAD51D mutation (c.762_763del, D254E*fs72) in the same exon as the primary mutation and PEO4 cells with the homozygous secondary RAD51D mutation (c.770_776delinsA, S257_R259delinsK). Supplementary Figure 11. Modeling of tumor clonal fractions in the post-progression biopsy sample with germline RAD51C mutation and multiple secondary mutations.

A key resistance mechanism to platinum-based chemotherapies and PARP inhibitors in BRCA-mutant cancers is the acquisition of BRCA reversion mutations that restore protein function. To estimate the prevalence of BRCA reversion mutations in high-grade ovarian carcinoma (HGOC), we performed targeted next-generation sequencing of circulating cell-free DNA (cfDNA) extracted from pretreatment and postprogression plasma in patients with deleterious germline or somatic BRCA mutations treated with the PARP inhibitor rucaparib. BRCA reversion mutations were identified in pretreatment cfDNA from 18% (2/11) of platinum-refractory and 13% (5/38) of platinum-resistant cancers, compared with 2% (1/48) of platinum-sensitive cancers (P = 0.049). Patients without BRCA reversion mutations detected in pretreatment cfDNA had significantly longer rucaparib progression-free survival than those with reversion mutations (median, 9.0 vs. 1.8 months; HR, 0.12; P < 0.0001). To study acquired resistance, we sequenced 78 postprogression cfDNA, identifying eight additional patients with BRCA reversion mutations not found in pretreatment cfDNA.Significance:BRCA reversion mutations are detected in cfDNA from platinum-resistant or platinum-refractory HGOC and are associated with decreased clinical benefit from rucaparib treatment. Sequencing of cfDNA can detect multiple BRCA reversion mutations, highlighting the ability to capture multiclonal heterogeneity.This article is highlighted in the In This Issue feature, p. 151

Molecular Dynamics Modeling of WT RAD51D monofilament interaction with dsDNA.

Copy number estimation by SNP array in the archival tumor tissue of the patient identified to have a germline RAD51C mutation (c.577C

Purpose: Previous studies have shown that the replication checkpoint, which involves the kinases ataxia telangiectasia mutated and Rad3 related (ATR) and Chk1, contributes to cytarabine resistance in cell lines. In the present study, we examined whether this checkpoint is activated in clinical acute myelogenous leukemia (AML) during cytarabine infusion in vivo and then assessed the impact of combining cytarabine with the recently described Chk1 inhibitor SCH 900776 in vitro.Experimental design: AML marrow aspirates harvested before and during cytarabine infusion were examined by immunoblotting. Human AML lines treated with cytarabine in the absence or presence of SCH 900776 were assayed for checkpoint activation by immunoblotting, nucleotide incorporation into DNA, and flow cytometry. Long-term effects in AML lines, clinical AML isolates, and normal myeloid progenitors were assayed using clonogenic assays.Results: Immunoblotting revealed increased Chk1 phosphorylation, a marker of checkpoint activation, in more than half of Chk1-containing AMLs after 48 hours of cytarabine infusion. In human AML lines, SCH 900776 not only disrupted cytarabine-induced Chk1 activation and S-phase arrest but also markedly increased cytarabine-induced apoptosis. Clonogenic assays demonstrated that SCH 900776 enhanced the antiproliferative effects of cytarabine in AML cell lines and clinical AML samples at concentrations that had negligible impact on normal myeloid progenitors.Conclusions: These results not only provide evidence for cytarabine-induced S-phase checkpoint activation in AML in the clinical setting, but also show that a selective Chk1 inhibitor can overcome the S-phase checkpoint and enhance the cytotoxicity of cytarabine. Accordingly, further investigation of the cytarabine/SCH 900776 combination in AML appears warranted. Clin Cancer Res; 18(19); 5364–73. ©2012 AACR.

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Preclinical investigations have identified insulin-like growth factor (IGF) signaling as a key mechanism for cancer growth and resistance to clinically useful therapies in multiple tumor types including breast cancer. Thus, agents targeting and blocking IGF signaling have promise in the treatment of solid tumors. To identify possible mechanisms of resistance to blocking the IGF pathway, we generated a cell line that was resistant to the IGF-1R/InsR benzimidazole inhibitors, BMS-554417 and BMS-536924, and compared expression profiles of the parental and resistant cells lines using Affymetrix GeneChip Human Genome U133 arrays. Compared with MCF-7 cells, breast cancer resistance protein (BCRP) expression was increased 9-fold in MCF-7R4, which was confirmed by immunoblotting and was highly statistically significant (P = 7.13E-09). BCRP was also upregulated in an independently derived resistant cell line, MCF-7 924R. MCF-7R4 cells had significantly lower intracellular accumulation of BMS-536924 compared with MCF-7 cells. Expression of BCRP in MCF-7 cells was sufficient to reduce sensitivity to BMS-536924. Furthermore, knockdown of BCRP in MCF-7R4 cells resensitized cells to BMS-536924. Four cell lines selected for resistance to the pyrrolotriazine IGF-1R/InsR inhibitor, BMS-754807, did not have upregulation of BCRP. These data suggest that benzimidazole IGF-1R/InsR inhibitors may select for upregulation and be effluxed by the ATP-binding cassette transporter, BCRP, contributing to resistance. However, pyrrolotriazine IGF-1R/InsR inhibitors do not appear to be affected by this resistance mechanism. Mol Cancer Ther; 10(1); 117–25. ©2011 AACR.

Supplementary Table 1. Key clinical characteristics of public cohort with respect to individual 14 studies Supplementary Table 2. Key clinical characteristics of Mayo Clinic HGSOC cohort Supplementary Table 3. Expression centroids of five de novo subtypes Supplementary Table 4. Expression centroids of four Tothill's HGSOC subtypes (C1/C2/C4/C5) Supplementary Table 5. Cross-tab between de novo subtypes and two other subtyping systems in public cohort Supplementary Table 6. The differential expression analysis results between s1.MES and rest de novo subtypes in public cohort Supplementary Table 7. The differential expression analysis results between s2.IMM and rest de novo subtypes in public cohort Supplementary Table 8. The differential expression analysis results between s3.RPO and rest de novo subtypes in public cohort Supplementary Table 9. The differential expression analysis results between s4.DIF and rest de novo subtypes in public cohort Supplementary Table 10. The differential expression analysis results between s5.ANM and rest de novo subtypes in public cohort Supplementary Table 11. Distribution tables of HGSOC molecular subtypes vs. surgical outcomes (optimal- and sub-optimal debulking) in Public and Mayo Clinic cohorts Supplementary Table 12. Previously reported debulking-predictive genes and their differential expressions related to s1.MES subtype in HGSOC public cases Supplementary Table 13. Enriched pathways (q-value

PDF file - 298K, 1) Ki67 IHC staining of patient & Avatars; 2) pan-CK, CD45, vimentin staining of Avatars; 3) graph of gains/losses by aCGH in Avatars; 4) Ca125 levels in serum of patients/Avatars.

Excel data file of NNMT and CDK12 protein levels in HGSOC tumors from patients.

ClinVar variant interpretations from May 2019 for variants identified in discovery cohorts

Supplementary Data from A Phase I Clinical Trial of the Poly(ADP-ribose) Polymerase Inhibitor Veliparib and Weekly Topotecan in Patients with Solid Tumors

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In high-grade serous ovarian carcinoma (HGSC), deleterious mutations in DNA repair gene RAD51C are established drivers of defective homologous recombination and are emerging biomarkers of PARP inhibitor (PARPi) sensitivity. RAD51C promoter methylation (meRAD51C) is detected at similar frequencies to mutations, yet its effects on PARPi responses remain unresolved.In this study, three HGSC patient-derived xenograft (PDX) models with methylation at most or all examined CpG sites in the RAD51C promoter show responses to PARPi. Both complete and heterogeneous methylation patterns were associated with RAD51C gene silencing and homologous recombination deficiency (HRD). PDX models lost meRAD51C following treatment with PARPi rucaparib or niraparib, where a single unmethylated copy of RAD51C was sufficient to drive PARPi resistance. Genomic copy number profiling of one of the PDX models using SNP arrays revealed that this resistance was acquired independently in two genetically distinct lineages.In a cohort of 12 patients with RAD51C-methylated HGSC, various patterns of meRAD51C were associated with genomic “scarring,” indicative of HRD history, but exhibited no clear correlations with clinical outcome. Differences in methylation stability under treatment pressure were also observed between patients, where one HGSC was found to maintain meRAD51C after six lines of therapy (four platinum-based), whereas another HGSC sample was found to have heterozygous meRAD51C and elevated RAD51C gene expression (relative to homozygous meRAD51C controls) after only neoadjuvant chemotherapy.As meRAD51C loss in a single gene copy was sufficient to cause PARPi resistance in PDX, methylation zygosity should be carefully assessed in previously treated patients when considering PARPi therapy.Significance:Homozygous RAD51C methylation is a positive predictive biomarker for sensitivity to PARP inhibitors, whereas a single unmethylated gene copy is sufficient to confer resistance.

Supplementary Figure 1 from Drug Efflux by Breast Cancer Resistance Protein Is a Mechanism of Resistance to the Benzimidazole Insulin-Like Growth Factor Receptor/Insulin Receptor Inhibitor, BMS-536924

Supplementary Figure 1. Analytical workflow of the present study. Supplementary Figure 2. Principal component analysis plots of public expression datasets before (A) and after (B) batch-correction Supplementary Figure 3. Consensus clustering results of non-negative matrix factorization from K= 2 to K = 9. The stable clustering relationships can be observed from K=2 to K=5. Supplementary Figure 4. Overall survival plots according to late-stage HGSOC cases in public cohort, n=1946. Supplementary Figure 5. Overall survival plots according to late-stage HGSOC cases with optimal debulking surgeries, in (A) public cohort, n=936; (B) Mayo Clinic cohort, n=250. Supplementary Figure 6. Overall survival plots according to late-stage HGSOC cases with sub-optimal debulking surgeries, in (A) public cohort, n=660; (B) Mayo Clinic cohort, n=88. Supplementary Figure 7. Overall survival plots according to surgical outcomes in Mayo clinic cohorts, for (A) all the late-stage HGSOC patients, (B-F) for late-stage patients belonging to each subtype. Supplementary Figure 8. Volcano plot of S1.MES subtype vs. other molecular subtypes. X-axis is the log-scaled expression fold-change (FC) and Y-axis is the significance level of differential expression analysis, defined as -log10(q-value). Two identical volcano plots were presented, where the larger one plotting according to gene symbols, and the smaller one plotting using dots. Red-color and green-color are used to indicate significantly up-regulated (FC{greater than or equal to}0.5 & q-value{less than or equal to}0.01) and down-regulated genes (FC{less than or equal to} -0.5 & q-value{less than or equal to}0.01), respectively. Supplementary Figure 9. Volcano plot of S2.IMM subtype vs. other molecular subtypes. X-axis is the log-scaled expression fold-change (FC) and Y-axis is the significance level of differential expression analysis, defined as -log10(q-value). Two identical volcano plots were presented, where the larger one plotting according to gene symbols, and the smaller one plotting using dots. Red-color and green-color are used to indicate significantly up-regulated (FC{greater than or equal to}0.5 & q-value{less than or equal to}0.01) and down-regulated genes (FC{less than or equal to} -0.5 & q-value{less than or equal to}0.01), respectively. Supplementary Figure 10. Volcano plot of S3.PRO subtype vs. other molecular subtypes. X-axis is the log-scaled expression fold-change (FC) and Y-axis is the significance level of differential expression analysis, defined as -log10(q-value). Two identical volcano plots were presented, where the larger one plotting according to gene symbols, and the smaller one plotting using dots. Red-color and green-color are used to indicate significantly up-regulated (FC{greater than or equal to}0.5 & q-value{less than or equal to}0.01) and down-regulated genes (FC{less than or equal to} -0.5 & q-value{less than or equal to}0.01), respectively. Supplementary Figure 11. Volcano plot of S4.DIF subtype vs. other molecular subtypes. X-axis is the log-scaled expression fold-change (FC) and Y-axis is the significance level of differential expression analysis, defined as -log10(q-value). Two identical volcano plots were presented, where the larger one plotting according to gene symbols, and the smaller one plotting using dots. Red-color and green-color are used to indicate significantly up-regulated (FC{greater than or equal to}0.5 & q-value{less than or equal to}0.01) and down-regulated genes (FC{less than or equal to} -0.5 & q-value{less than or equal to}0.01), respectively. Supplementary Figure 12. Volcano plot of S5.ANM subtype vs. other molecular subtypes. X-axis is the log-scaled expression fold-change (FC) and Y-axis is the significance level of differential expression analysis, defined as -log10(q-value). Two identical volcano plots were presented, where the larger one plotting according to gene symbols, and the smaller one plotting using dots. Red-color and green-color are used to indicate significantly up-regulated (FC{greater than or equal to}0.5 & q-value{less than or equal to}0.01) and down-regulated genes (FC{less than or equal to} -0.5 & q-value{less than or equal to}0.01), respectively. Supplementary Figure 13. Enriched pathways (q-value {less than or equal to}0.1) for S1.MES subtype vs. other molecular subtypes. Green and red colors are used to represent significantly down- and up-regulated pathways, respectively. Supplementary Figure 14. Enriched pathways (q-value {less than or equal to}0.1) for S2.IMM subtype vs. other molecular subtypes. Green and red colors are used to represent significantly down- and up-regulated pathways, respectively. Supplementary Figure 15. Enriched pathways (q-value {less than or equal to}0.1) for S3.PRO subtype vs. other molecular subtypes. Green and red colors are used to represent significantly down- and up-regulated pathways, respectively. Supplementary Figure 16. Enriched pathways (q-value {less than or equal to}0.1) for S4.DIF subtype vs. other molecular subtypes. Green and red colors are used to represent significantly down- and up-regulated pathways, respectively. Supplementary Figure 17. Enriched pathways (q-value {less than or equal to}0.1) for S5.ANM subtype vs. other molecular subtypes. Green and red colors are used to represent significantly down- and up-regulated pathways, respectively. Supplementary Figure 18. Expression scatterplot between PD-L1 and TAP1 genes; the figure was generated using cBioPortal (http://www.cbioportal.org/) according to TCGA HGSOC data. Supplementary Figure 19. Distribution boxplots of four genomics scores with respect to five de novo subtypes for TCGA HGSOC cases.