Optimized p53 immunohistochemistry is an accurate predictor of TP53 mutation in ovarian carcinoma.

TP53 mutations are ubiquitous in high-grade serous ovarian carcinomas (HGSOC), and the presence of TP53 mutation discriminates between high and low-grade serous carcinomas and is now an important biomarker for clinical trials targeting mutant p53. p53 immunohistochemistry (IHC) is widely used as a surrogate for TP53 mutation but its accuracy has not been established. The objective of this study was to test whether improved methods for p53 IHC could reliably predict TP53 mutations independently identified by next generation sequencing (NGS). Four clinical p53 IHC assays and tagged-amplicon NGS for TP53 were performed on 171 HGSOC and 80 endometrioid carcinomas (EC). p53 expression was scored as overexpression (OE), complete absence (CA), cytoplasmic (CY) or wild type (WT). p53 IHC was evaluated as a binary classifier where any abnormal staining predicted deleterious TP53 mutation and as a ternary classifier where OE, CA or WT staining predicted gain-of-function (GOF or nonsynonymous), loss-of-function (LOF including stopgain, indel, splicing) or no detectable TP53 mutations (NDM), respectively. Deleterious TP53 mutations were detected in 169/171 (99%) HGSOC and 7/80 (8.8%) EC. The overall accuracy for the best performing IHC assay for binary and ternary prediction was 0.94 and 0.91 respectively, which improved to 0.97 (sensitivity 0.96, specificity 1.00) and 0.95 after secondary analysis of discordant cases. The sensitivity for predicting LOF mutations was lower at 0.76 because p53 IHC detected mutant p53 protein in 13 HGSOC with LOF mutations. CY staining associated with LOF was seen in 4 (2.3%) of HGSOC. Optimized p53 IHC can approach 100% specificity for the presence of TP53 mutation and its high negative predictive value is clinically useful as it can exclude the possibility of a low-grade serous tumour. 4.1% of HGSOC cases have detectable WT staining while harboring a TP53 LOF mutation, which limits sensitivity for binary prediction of mutation to 96%.Terry Fox Research Institute (COEUR) Cancer Research UK . Grant Number: A15601 University of Cambridg

Combining measures of immune infiltration shows additive effect on survival prediction in high-grade serous ovarian carcinoma

Abstract: Background: In colorectal and breast cancer, the density and localisation of immune infiltrates provides strong prognostic information. We asked whether similar automated quantitation and combined analysis of immune infiltrates could refine prognostic information in high-grade serous ovarian carcinoma (HGSOC) and tested associations between patterns of immune response and genomic driver alterations. Methods: Epithelium and stroma were semi-automatically segmented and the infiltration of CD45RO+, CD8+ and CD68+ cells was automatically quantified from images of 332 HGSOC patient tissue microarray cores. Results: Epithelial CD8 [p = 0.027, hazard ratio (HR) = 0.83], stromal CD68 (p = 3 × 10−4, HR = 0.44) and stromal CD45RO (p = 7 × 10−4, HR = 0.76) were positively associated with survival and remained so when averaged across the tumour and stromal compartments. Using principal component analysis, we identified optimised multiparameter survival models combining information from all immune markers (p = 0.016, HR = 0.88). There was no significant association between PTEN expression, type of TP53 mutation or presence of BRCA1/BRCA2 mutations and immune infiltrate densities or principal components. Conclusions: Combining measures of immune infiltration provided improved survival modelling and evidence for the multiple effects of different immune factors on survival. The presence of stromal CD68+ and CD45RO+ populations was associated with survival, underscoring the benefits evaluating stromal immune populations may bring for prognostic immunoscores in HGSOC

Ovarian cancer cell line panel (OCCP): Clinical importance of in vitro morphological subtypes

Epithelial ovarian cancer is a highly heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Therapeutic approaches need to account for inter-patient and intra-tumoural heterogeneity and detailed characterization of in vitro models representing the different histological a

DNA Methylation Profiles of Ovarian Clear Cell Carcinoma

BACKGROUND: Ovarian clear cell carcinoma (OCCC) is a rare ovarian cancer histotype that tends to be resistant to standard platinum-based chemotherapeutics. We sought to better understand the role of DNA methylation in clinical and biological subclassification of OCCC. METHODS: We interrogated genome-wide methylation using DNA from fresh frozen tumors from 271 cases, applied non-smooth non-negative matrix factorization (nsNMF) clustering, and evaluated clinical associations and biological pathways. RESULTS: Two approximately equally sized clusters that associated with several clinical features were identified. Compared to Cluster 2 (N=137), Cluster 1 cases (N=134) presented at a more advanced stage, were less likely to be of Asian ancestry, and tended to have poorer outcomes including macroscopic residual disease following primary debulking surgery (p-values <0.10). Subset analyses of targeted tumor sequencing and immunohistochemical data revealed that Cluster 1 tumors showed TP53 mutation and abnormal p53 expression, and Cluster 2 tumors showed aneuploidy and ARID1A/PIK3CA mutation (p-values <0.05). Cluster-defining CpGs included 1,388 CpGs residing within 200 bp of the transcription start sites of 977 genes; 38% of these genes (N=369 genes) were differentially expressed across cluster in transcriptomic subset analysis (p-values <10(−4)). Differentially expressed genes were enriched for six immune-related pathways, including interferon alpha and gamma responses (p-values < 10(−6)). CONCLUSIONS: DNA methylation clusters in OCCC correlate with disease features and gene expression patterns among immune pathways. IMPACT: This work serves as a foundation for integrative analyses that better understand the complex biology of OCCC in an effort to improve potential for development of targeted therapeutics

Kinome capture sequencing of high-grade serous ovarian carcinoma reveals novel mutations in the JAK3 gene.

High-grade serous ovarian carcinoma (HGSOC) remains the deadliest form of epithelial ovarian cancer and despite major efforts little improvement in overall survival has been achieved. Identification of recurring "driver" genetic lesions has the potential to enable design of novel therapies for cancer. Here, we report on a study to find such new therapeutic targets for HGSOC using exome-capture sequencing approach targeting all kinase genes in 127 patient samples. Consistent with previous reports, the most frequently mutated gene was TP53 (97% mutation frequency) followed by BRCA1 (10% mutation frequency). The average mutation frequency of the kinase genes mutated from our panel was 1.5%. Intriguingly, after BRCA1, JAK3 was the most frequently mutated gene (4% mutation frequency). We tested the transforming properties of JAK3 mutants using the Ba/F3 cell-based in vitro functional assay and identified a novel gain-of-function mutation in the kinase domain of JAK3 (p.T1022I). Importantly, p.T1022I JAK3 mutants displayed higher sensitivity to the JAK3-selective inhibitor Tofacitinib compared to controls. For independent validation, we re-sequenced the entire JAK3 coding sequence using tagged amplicon sequencing (TAm-Seq) in 463 HGSOCs resulting in an overall somatic mutation frequency of 1%. TAm-Seq screening of CDK12 in the same population revealed a 7% mutation frequency. Our data confirms that the frequency of mutations in kinase genes in HGSOC is low and provides accurate estimates for the frequency of JAK3 and CDK12 mutations in a large well characterized cohort. Although p.T1022I JAK3 mutations are rare, our functional validation shows that if detected they should be considered as potentially actionable for therapy. The observation of CDK12 mutations in 7% of HGSOC cases provides a strong rationale for routine somatic testing, although more functional and clinical characterization is required to understand which nonsynonymous mutations alterations are associated with homologous recombination deficiency

Kinome capture sequencing of high-grade serous ovarian carcinoma reveals novel mutations in theJAK3gene

High-grade serous ovarian carcinoma (HGSOC) remains the deadliest form of epithelial ovarian cancer and despite major efforts little improvement in overall survival has been achieved. Identification of recurring "driver" genetic lesions has the potential to enable design of novel therapies for cancer. Here, we report on a study to find such new therapeutic targets for HGSOC using exome-capture sequencing approach targeting all kinase genes in 127 patient samples. Consistent with previous reports, the most frequently mutated gene wasTP53(97% mutation frequency) followed byBRCA1(10% mutation frequency). The average mutation frequency of the kinase genes mutated from our panel was 1.5%. Intriguingly, afterBRCA1,JAK3was the most frequently mutated gene (4% mutation frequency). We tested the transforming properties of JAK3 mutants using the Ba/F3 cell-basedin vitrofunctional assay and identified a novel gain-of-function mutation in the kinase domain ofJAK3(p.T1022I). Importantly, p.T1022IJAK3mutants displayed higher sensitivity to the JAK3-selective inhibitor Tofacitinib compared to controls. For independent validation, we re-sequenced the entireJAK3coding sequence using tagged amplicon sequencing (TAm-Seq) in 463 HGSOCs resulting in an overall somatic mutation frequency of 1%. TAm-Seq screening ofCDK12in the same population revealed a 7% mutation frequency. Our data confirms that the frequency of mutations in kinase genes in HGSOC is low and provides accurate estimates for the frequency ofJAK3andCDK12mutations in a large well characterized cohort. Although p.T1022IJAK3mutations are rare, our functional validation shows that if detected they should be considered as potentially actionable for therapy. The observation ofCDK12mutations in 7% of HGSOC cases provides a strong rationale for routine somatic testing, although more functional and clinical characterization is required to understand which nonsynonymous mutations alterations are associated with homologous recombination deficiency.ISSN:1932-620

FrenchFISH: Poisson Models for Quantifying DNA Copy Number From Fluorescence In Situ Hybridization of Tissue Sections

Purpose: Chromosomal aberration and DNA copy number change are robust hallmarks of cancer. The gold standard for detecting copy number changes in tumor cells is fluorescence in situ hybridization (FISH) using locus-specific probes that are imaged as fluorescent spots. However, spot counting often does not perform well on solid tumor tissue sections due to partially represented or overlapping nuclei. Materials and Methods: To overcome these challenges, we have developed a computational approach called FrenchFISH, which comprises a nuclear volume correction method coupled with two types of Poisson models: either a Poisson model for improved manual spot counting without the need for control probes or a homogeneous Poisson point process model for automated spot counting. Results: We benchmarked the performance of FrenchFISH against previous approaches using a controlled simulation scenario and tested it experimentally in 12 ovarian carcinoma FFPE-tissue sections for copy number alterations at three loci (c-Myc, hTERC, and SE7). FrenchFISH outperformed standard spot counting with 74% of the automated counts having &lt; 1 copy number difference from the manual counts and 17% having &lt; 2 copy number differences, while taking less than one third of the time of manual counting. Conclusion: FrenchFISH is a general approach that can be used to enhance clinical diagnosis on sections of any tissue by both speeding up and improving the accuracy of spot count estimates

Enhanced detection of circulating tumor DNA by fragment size analysis.

Existing methods to improve detection of circulating tumor DNA (ctDNA) have focused on genomic alterations but have rarely considered the biological properties of plasma cell-free DNA (cfDNA). We hypothesized that differences in fragment lengths of circulating DNA could be exploited to enhance sensitivity for detecting the presence of ctDNA and for noninvasive genomic analysis of cancer. We surveyed ctDNA fragment sizes in 344 plasma samples from 200 patients with cancer using low-pass whole-genome sequencing (0.4×). To establish the size distribution of mutant ctDNA, tumor-guided personalized deep sequencing was performed in 19 patients. We detected enrichment of ctDNA in fragment sizes between 90 and 150 bp and developed methods for in vitro and in silico size selection of these fragments. Selecting fragments between 90 and 150 bp improved detection of tumor DNA, with more than twofold median enrichment in >95% of cases and more than fourfold enrichment in >10% of cases. Analysis of size-selected cfDNA identified clinically actionable mutations and copy number alterations that were otherwise not detected. Identification of plasma samples from patients with advanced cancer was improved by predictive models integrating fragment length and copy number analysis of cfDNA, with area under the curve (AUC) >0.99 compared to AUC 0.91 compared to AUC < 0.5 without fragmentation features. Fragment size analysis and selective sequencing of specific fragment sizes can boost ctDNA detection and could complement or provide an alternative to deeper sequencing of cfDNA.We would like to acknowledge the support of The University of Cambridge, Cancer Research UK and the EPSRC (CRUK grant numbers A11906 (NR), A20240 (NR), A22905 (JDB), A15601 (JDB), A25177 (CRUK Cancer Centre Cambridge), A17242 (KMB), A16465 (CRUK-EPSRC Imaging Centre in Cambridge and Manchester)). The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 337905. The research was supported by the National Institute for Health Research Cambridge, National Cancer Research Network, Cambridge Experimental Cancer Medicine Centre and Hutchison Whampoa Limited. This research is also supported by Target Ovarian Cancer and the Medical Research Council through their Joint Clinical Research Training Fellowship for Dr Moore. The CALIBRATE study was supported by funding from AstraZeneca

Population-based targeted sequencing of 54 candidate genes identifies PALB2 as a susceptibility gene for high-grade serous ovarian cancer

Purpose: The known epithelial ovarian cancer (EOC) susceptibility genes account for less than 50% of the heritable risk of ovarian cancer suggesting that other susceptibility genes exist. The aim of this study was to evaluate the contribution to ovarian cancer susceptibility of rare deleterious germline variants in a set of candidate genes. Methods: We sequenced the coding region of 54 candidate genes in 6385 invasive EOC cases and 6115 controls of broad European ancestry. Genes with an increased frequency of putative deleterious variants in cases versus controls were further examined in an independent set of 14 135 EOC cases and 28 655 controls from the Ovarian Cancer Association Consortium and the UK Biobank. For each gene, we estimated the EOC risks and evaluated associations between germline variant status and clinical characteristics. Results: The ORs associated for high-grade serous ovarian cancer were 3.01 for PALB2 (95% CI 1.59 to 5.68; p=0.00068), 1.99 for POLK (95% CI 1.15 to 3.43; p=0.014) and 4.07 for SLX4 (95% CI 1.34 to 12.4; p=0.013). Deleterious mutations in FBXO10 were associated with a reduced risk of disease (OR 0.27, 95% CI 0.07 to 1.00, p=0.049). However, based on the Bayes false discovery probability, only the association for PALB2 in high-grade serous ovarian cancer is likely to represent a true positive. Conclusions: We have found strong evidence that carriers of PALB2 deleterious mutations are at increased risk of high-grade serous ovarian cancer. Whether the magnitude of risk is sufficiently high to warrant the inclusion of PALB2 in cancer gene panels for ovarian cancer risk testing is unclear; much larger sample sizes will be needed to provide sufficiently precise estimates for clinical counselling

Copy number signatures and mutational processes in ovarian carcinoma.

The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.NIHR, Ovarian Cancer Action, Cancer Research UK Cambridge Centre, Cambridge Experimental Cancer Medicine Centr