Fibroblast Growth Factor Receptors and Ligands in Context of Bevacizumab Response in Ovarian Carcinoma: An Exploratory Analysis of AGO-OVAR11/ICON-7

With more novel drugs being approved for the treatment of ovarian carcinoma, the question remains to what extent patients benefit from antiangiogenic treatment with bevacizumab, either in combination with poly-(ADP-ribose) polymerase inhibitors or as single-agent maintenance. As fibroblast growth factor receptors and their ligands (FGFRs/FGFs) are key players in angiogenic signaling and have been linked to resistance to several drugs, we investigated the prognostic or predictive potential of FGFs/FGFRs signaling in the context of bevacizumab treatment within the prospective phase III AGO-OVAR11/ICON-7 study. FGFR1, FGFR2, FGFR3, FGFR4, FGF1, and FGF19 gene expressions were determined in 380 ovarian carcinoma tumor samples collected from German centers in the multicenter phase III AGO-OVAR11 trial/ICON-7 trial. All patients received carboplatin and paclitaxel, administered every 3 weeks for 6 cycles, and were randomized to bevacizumab. Expressions of FGFR1, FGFR2, FGF1, and FGF19 were associated with progression-free survival in both uni- and multivariate (FGFR1: HR, 1.6, P < .001; FGFR2: HR, 1.6, P = .002; FGF1: HR, 2.3, P < .001; and FGF19: HR, 0.7; P = .007) analysis. A signature built by FGFR1, FGFR4, and FGF19 defined a subgroup (n = 62) of patients that derived the greatest bevacizumab-associated improvement of progression-free survival (HR, 0.3; P = .004). In this exploratory analysis of a prospective randomized phase III trial, we provide evidence that the expression of FGFRs/FGFs might have independent prognostic values. An FGFR/FGF-based gene signature identified in our study appears to predict long-term benefit from bevacizumab. This observation is hypothesis-generating and requires validation on independent cohorts.

The proteome of clear cell ovarian carcinoma

Clear cell ovarian carcinoma (CCOC) is the second most common subtype of epithelial ovarian carcinoma. Late-stage CCOC is not responsive to gold-standard chemotherapy and results in suboptimal outcomes for patients. In-depth molecular insight is urgently needed to stratify the disease and drive therapeutic development. We conducted global proteomics for 192 cases of CCOC and compared these with other epithelial ovarian carcinoma subtypes. Our results showed distinct proteomic differences in CCOC compared with other epithelial ovarian cancer subtypes including alterations in lipid and purine metabolism pathways. Furthermore, we report potential clinically significant proteomic subgroups within CCOC, suggesting the biologic plausibility of stratified treatment for this cancer. Taken together, our results provide a comprehensive understanding of the CCOC proteomic landscape to facilitate future understanding and research of this disease. © 2022 The Pathological Society of Great Britain and Ireland.

Multisite gynecologic endometrioid adenocarcinomas: Can mutation profiling be used to distinguish synchronous primary cancers from metastases?

It is well recognized that some patients with endometrioid gynecological cancers have tumors arising in multiple sites (ovary, endometrium, and endometriosis) at the time of diagnosis. Molecular analysis has helped discern whether these multisite cancers represent synchronous primary tumors or alternatively metastatic disease. We present a complex case of a patient with endometrioid carcinomas arising in multiple sites. We discuss the use of mutation profiling to discern clonality and highlight how this information may inform the clinical management of such cases.

Sphingosine-kinase-1 expression is associated with improved overall survival in high-grade serous ovarian cancer

Purpose

Sphingosine-kinase-1 (SPHK1) is a key enzyme of sphingolipid metabolism which is involved in ovarian cancer pathogenesis, progression and mechanisms of drug resistance. It is overexpressed in a variety of cancer subtypes. We investigated SPHK1 expression as a prognostic factor in epithelial ovarian cancer patients.

Methods

Expression analysis of SPHK1 was performed on formalin-fixed paraffin-embedded tissue from 1005 ovarian cancer patients with different histological subtypes using immunohistochemistry. Staining intensity of positive tumor cells was assessed semi-quantitatively, and results were correlated with clinicopathological characteristics and survival.

Results

In our ovarian cancer collective, high levels of SPHK1 expression correlated significantly with complete surgical tumor resection (p = 0.002) and lower FIGO stage (p = 0.04). Progression-free and overall survival were further significantly longer in patients with high-grade serous ovarian cancer and overexpression of SPHK1 (p = 0.002 and p = 0.006, respectively).

Conclusion

Our data identify high levels of SPHK1 expression as a potential favorable prognostic marker in ovarian cancer patients.

Supplementary Information

The online version of this article (10.1007/s00432-021-03558-x) contains supplementary material, which is available to authorized users.

Clinical and pathological associations of PTEN expression in ovarian cancer: a multicentre study from the Ovarian Tumour Tissue Analysis Consortium

BACKGROUND

PTEN loss is a putative driver in histotypes of ovarian cancer (high-grade serous (HGSOC), endometrioid (ENOC), clear cell (CCOC), mucinous (MOC), low-grade serous (LGSOC)). We aimed to characterise PTEN expression as a biomarker in epithelial ovarian cancer in a large population-based study.

METHODS

Tumours from 5400 patients from a multicentre observational, prospective cohort study of the Ovarian Tumour Tissue Analysis Consortium were used to evaluate associations between immunohistochemical PTEN patterns and overall survival time, age, stage, grade, residual tumour, CD8+ tumour-infiltrating lymphocytes (TIL) counts, expression of oestrogen receptor (ER), progesterone receptor (PR) and androgen receptor (AR) by means of Cox proportional hazard models and generalised Cochran-Mantel-Haenszel tests.

RESULTS

Downregulation of cytoplasmic PTEN expression was most frequent in ENOC (most frequently in younger patients; p value = 0.0001) and CCOC and was associated with longer overall survival in HGSOC (hazard ratio: 0.78, 95% CI: 0.65-0.94, p value = 0.022). PTEN expression was associated with ER, PR and AR expression (p values: 0.0008, 0.062 and 0.0002, respectively) in HGSOC and with lower CD8 counts in CCOC (p value < 0.0001). Heterogeneous expression of PTEN was more prevalent in advanced HGSOC (p value = 0.019) and associated with higher CD8 counts (p value = 0.0016).

CONCLUSIONS

PTEN loss is a frequent driver in ovarian carcinoma associating distinctly with expression of hormonal receptors and CD8+ TIL counts in HGSOC and CCOC histotypes.

Abstract B20: Endometrial cancer molecular risk stratification in endometrioid ovarian cancers: A novel application of precision medicine

Objective: Endometrioid ovarian carcinoma (ENOC) is associated with a generally more favorable prognosis compared to other ovarian carcinoma histotypes. Nonetheless, patients are still treated with a “one size fits all” approach. While tumor staging offers some stratification, the development of personalized treatment concepts remains elusive. Our group has recently validated the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE), to distinguish clinically relevant prognostic groups amongst endometrial carcinomas. ENOC shares risk factors, genomics, and histology with its endometrial counterpart. The aim of our study was to apply and test ProMisE on ENOC.

Methods: ProMisE was applied to 509 ENOC after biomarker-assisted review of ENOC histotype. Cases were aligned into low-risk POLE mutant (POLE), moderate-risk mismatch repair deficient (MMRd), high-risk p53 abnormal (p53abn), and a final moderate-risk category lacking these biomarkers (p53wt). Kaplan-Meier and multivariate survival analysis were performed.

Results: 4% of cases were POLE, 16% MMRd, 71% p53wt, and 10% p53abn. Groups showed distinct progression-free and overall survival (p &lt;0.001), near identical to profiles of endometrial cancers. 5-year PFS was 54% in p53abn, 82% in MMRd, 85% in p53wt, and 100% in POLEmut cases. Median overall survival was reached in p53 mutant cases only. ProMisE classes of ENOC were independent of stage and residual disease in multivariable analysis.

Conclusion: ProMisE risk classification provides additional prognostic information in a large cohort of ENOC. Our findings support introduction of ProMisE-stratified treatment strategies to improve patient care across ENOC. Further, ENOC may benefit from parallel efforts under investigation in endometrial carcinoma.

Citation Format: Pauline Krämer, Aline Talhouk, Tjalling Bosse, Florian Heitz, Naveena Singh, Felix Kommoss, Sara Brucker, Jessica McAlpine, Stefan Kommoss, Martin Koebel, Michael Anglesio. Endometrial cancer molecular risk stratification in endometrioid ovarian cancers: A novel application of precision medicine [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr B20.

Abstract A03: PrOTYPE (Predictor of high-grade-serous Ovarian carcinoma molecular subTYPE): The development and validation of a clinical-grade consensus classifier for the molecular subtypes of high-grade serous tubo-ovarian cancer

Background: Gene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC) are distinguished by differential immune and stromal infiltration and may provide opportunities for targeted therapies. Integration of molecular subtypes into clinical trials has been hindered by inconsistent subtyping methodology.

Methods: Adopting two independent approaches, we derived and internally validated algorithms for molecular subtype prediction from gene-expression array data in 1,650 tumors. We applied resulting models to assign labels to 3829 HGSOCs from the Ovarian Tumor Tissue Analysis (OTTA) consortium evaluated on NanoString. Using the labeled NanoString data, we developed, confirmed, and validated a minimal gene set, clinical-grade test and prediction tool. We also used the OTTA dataset to evaluate associations between molecular subtype, biologic, and clinical features.

Findings: The locked-down test included a model with 55 genes that predicted HGSOC molecular subtype with &gt;95% accuracy. Subtype varied between primary and metastatic site taken at the time of primary surgery, and was significantly associated with age, stage, CD8+ lymphocyte infiltration, residual disease, and outcome. In multivariable models, molecular subtypes lose their prognostic significance in the presence of risk factors such as residual disease and BRCA1/2 germline mutations.

Interpretation: We validated the Predictor of high-grade-serous Ovarian carcinoma molecular subTYPE, or PrOTYPE, following the Institute of Medicine guidelines for the development of omics-based tests. This simple-to-use, cost-effective, fully defined, and locked-down clinical-grade assay will facilitate molecular subtype stratification into clinical trial design. PrOTYPE will allow for objective assessment of HGSOC molecular subtype predictive value in precision medicine applications.

Citation Format: Aline Talhouk, Joshy George, Chen Wang, Ellen Goode, Susan Ramus, Jennifer Doherty, David Bowtell, Michael Anglesio, OTTA Consortium. PrOTYPE (Predictor of high-grade-serous Ovarian carcinoma molecular subTYPE): The development and validation of a clinical-grade consensus classifier for the molecular subtypes of high-grade serous tubo-ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A03.

Histotype classification of ovarian carcinoma: A comparison of approaches

OBJECTIVE

Major changes in the classification of ovarian carcinoma histotypes occurred over the last two decades, resulting in the current 2014 World Health Organization (WHO) diagnostic criteria that recognize five principal histotypes: high-grade serous, low-grade serous, endometrioid, clear cell, and mucinous carcinoma. We assessed the impact of these guidelines and use of immunohistochemical (IHC) markers on classification of ovarian carcinomas in existing population-based studies.

METHODS

We evaluated histotype classification for 2361 ovarian carcinomas diagnosed between 1999 and 2009 from two case-control studies using three approaches: 1. pre-2014 WHO ("historic") histotype; 2. Standardized review of pathology slides using the 2014 WHO criteria alone; and 3. An integrated IHC assessment along with the 2014 WHO criteria. We used Kappa statistics to assess agreement between approaches, and Kaplan-Meier survival curves and Cox proportional hazards models to evaluate mortality.

RESULTS

Compared to the standardized pathologic review histotype, agreement across approaches was high (kappa = 0.892 for historic, and 0.849 for IHC integrated histotype), but the IHC integrated histotype identified more low-grade serous carcinomas and a subset of endometrioid carcinomas that were assigned as high-grade serous (n = 25). No substantial differences in histotype-specific mortality were observed across approaches.

CONCLUSIONS

Our findings suggest that histotype assignment is fairly consistent regardless of classification approach, but that progressive improvements in classification accuracy for some less common histotypes are achieved with pathologic review using the 2014 WHO criteria and with IHC integration. We additionally recommend a classification scheme to fit historic data into the 2014 WHO categories to answer histotype-specific research questions.

Abstract B22: Capturing L1 retrotransposon-mediated DNA transductions in endometriosis associated ovarian cancers as a way to track tumor development

Endometrioid ovarian cancer (ENOC) and clear cell ovarian cancer (CCOC) share a common precursor lesion, endometriosis (ectopic growth of uterine lining), hence the designation endometriosis-associated ovarian cancer (EAOC). Women with endometriosis have up to three-fold increased risk of developing ENOC and CCOC. Efforts have been made to look for biomarkers that can help identifying women at risk of developing cancer; however, there are currently no biomarkers that stratify risk of cancer development. We performed whole-genome sequencing (WGS) on 29 ENOC and 35 CCOC cases and observed a frequent transduction event originating from an active LINE-1 (L1) retrotransposable element in the TTC28 gene. Such event occurred in 34% (10/29) of ENOC, and 31% (11/35) of CCOC cases. L1 retrotransposons are repetitive, mobile genetic elements capable of taking downstream DNA fragments and inserting them into random genomic locations via a process called 3’ transduction. Approximately 70-100 different potentially active L1s are epigenetically silenced in normal tissues, but tend to be reactivated in cancers. We subsequently used PCR to validate these TTC28-L1 transductions, and compared their presence to single nucleotide variations (SNVs) and frameshift mutations in formalin-fixed, paraffin-embedded (FFPE) tumor tissues from different tumor sites for 4 ENOC and 3 CCOC cases. We found that these transduction events along with classical driver mutations were almost ubiquitous across the tumor sites, suggesting these L1 events likely occurred early in the malignant transformation of EAOCs.

We developed a low-input, probe-based capture assay to test the presence of TTC28-L1 transductions as an alternative method to performing WGS. Oligonucleotide probes tiling 1 kb downstream of active L1s are used to capture DNA fragments containing the transduced DNA, and the fragments are sequenced on the MiSeq next-generation sequencing platform. Analyses are performed using the Geneious software and the published bioinformatics tool Socrates, specific for detecting DNA fragments with split reads (fragments with ends aligning to different parts of the genome). We successfully validated the assay on 9 cases with WGS data: 7 EAOC cases with TTC28-L1 transductions and 2 EAOC cases without TTC28-L1 transductions. DNA extracted from frozen tumor and buffy coat (normal control) were used for each case, and FFPE tissues were used for selected cases. All reads containing the transduction events aligned to genomic coordinates corresponding to the WGS data.

While L1-mediated DNA transductions are often passenger events during tumorigenesis, our data suggest that they likely occur early in ovarian cancer tumorigenesis. Our data show that this probe-based capture assay provides an alternative method to WGS, and may be useful in detecting active 3’ transductions in novel cases to track the development of ovarian tumors.

Citation Format: Zhouchunyang Xia, Dawn Cochrane, Michael Anglesio, Winnie Yang, Miguel Alcaide, Tayyebeh Nazeran, Janine Senz, Amy Lum, Ali Bashashati, Yikan Wang, Ryan Morin, Sohrab Shah, David Huntsman. Capturing L1 retrotransposon-mediated DNA transductions in endometriosis associated ovarian cancers as a way to track tumor development. [abstract]. In: Proceedings of the AACR Conference: Addressing Critical Questions in Ovarian Cancer Research and Treatment; Oct 1-4, 2017; Pittsburgh, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(15_Suppl):Abstract nr B22.

Endometriosis and endometriosis-associated cancers: new insights into the molecular mechanisms of ovarian cancer development

Endometriosis is a fascinating disease that we strive to better understand. Molecular techniques are shedding new light on many important aspects of this disease: from pathogenesis to the recognition of distinct disease variants like deep infiltrating endometriosis. The observation that endometriosis is a cancer precursor has now been strengthened with the knowledge that mutations that are present in endometriosis-associated cancers can be found in adjacent endometriosis lesions. Recent genomic studies, placed in context, suggest that deep infiltrating endometriosis may represent a benign neoplasm that invades locally but rarely metastasises. Further research will help elucidate distinct aberrations which result in this phenotype. With respect to identifying those patients who may be at risk of developing endometriosis-associated cancers, a combination of molecular, pathological, and inheritance markers may define a high-risk group that might benefit from risk-reducing strategies.

Abstract LB-312: The somatic mutational landscape of ovarian clear cell carcinoma and its precursor lesions

Clear Cell ovarian carcinomas (CCC) represent ∼10% of ovarian carcinomas, with outcomes for high-stage cases significantly worse than the more common high-grade serous form. Response to standard chemotherapies are poor and efforts to improve treatment strategies are confounded by studies grouping ovarian histologies together, as well as a general lack of molecular background data on CCC. CCC frequently occurs in a background of endometriosis. The complete mutational landscape, the molecular basis of the transformation of endometriosis and patterns of clonal evolution in CCC are not understood.

We performed whole genome sequencing and gene expression profiling on 19 CCC to uncover candidate somatic alterations (mutations and, copy number aberrations) and measure their effect on transcriptional networks as candidates for driver mutations. We then performed targeted deep sequencing on the primary tumor samples, metastases and, from a subset of cases, adjacent or distant typical and atypical endometriosis. We used statistical modeling approaches to validate mutations, quantify the degree of clonal diversity and trace patterns of selection through oncogenic transformation.

Mutations in ARID1A and PIK3CA were by far the most frequent aberrations seen in the cohort (ARID1A: 10/19 cases; PIK3CA: 8/19 cases). The majority of ARID1A mutant cases exhibited bi-allelic loss of function. Two non-ARID1A mutant cases showed alterations in other SWI/SNF complex components. Amongst the 24 most significant candidate drivers impacting expression, five genes (PIK3CA, CTNNB1, TP53, PPP2R1A and KRAS) were known drivers. No association between PIK3CA or ARID1A status with disease stage, genomic instability, or mutation load was observed. Analysis of deep sequencing data suggested the presence of multiple clones in every case. For each case with matching precursor lesions, we observed multiple mutations in at least one such lesion. Cases with ARID1A and PIK3CA mutations always showed evidence of these mutations in their precursor lesions. The proportion of mutations from the primary tumor that were also present in precursor lesions varied widely across the cohort from approximately 10% to nearly 100%.

Our data support both ARID1A and PIK3CA mutations as early events in CCC. The pattern of endometriosis transformation could be associated with somatic mutations in all cases. This suggests that candidate tumor-initiating mutations and global- or individually- targetable features should be a focus to improve management of this disease. Finally, we suggest that patterns of mutational conservation across the series of precursor lesions presents an opportunity for early screening of endometriosis tissues as an indicator of transformation potential.

Citation Format: Ali Bashashati, Michael Anglesio, Yikan Wang, Gavin Ha, Janine Senz, Winnie Yang, Steve Kalloger, Leah Prentice, Satoshi Yanagida, Clara Salamanca, Galina Soukhatcheva, Anthony Karnezis, Hector Chang, Martin Hirst, Anne-Marie Mes-Mason, Aikou Okamoto, Marco Marra, Blake Gilks, Sohrab Shah, David Huntsman. The somatic mutational landscape of ovarian clear cell carcinoma and its precursor lesions. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-312. doi:10.1158/1538-7445.AM2014-LB-312

Abstract 544: Recurrent DICER1 hotspot mutations in endometrial cancer and their impact on microRNA biogenesis

Alternation in genes associated with microRNA (miRNA) biogenesis pathway may lead to miRNA dysregulation, and is implicated in a variety of human malignancies. Previously our group identified recurrent somatic “hotspot” mutations (E1705, D1709, D1810, E1813) in a critical miRNA-processing gene, DICER1, in rare sex cord-stromal tumors. During miRNA biogenesis, the two RNase III domains of DICER1 form an intramolecular dimer, which leads to the cleavage of the precursor miRNA (pre-miRNA) hairpin and generate mature 5p and 3p miRNAs from 5’ and 3’ arms of the precursor hairpin respectively. Studies have shown that the hotspot mutations in the RNase IIIb metal binding domain could impair DICER1's ability to generate mature 5p miRNAs, leading to global loss of 5p miRNAs.

Recently, in collaboration with The Cancer Genome Atlas (TCGA), we identified DICER1 hotspot mutations in a small subset of endometrial cancer from TCGA cohort (6/248) as well as our own tumor bank (6/307), suggesting disruption of DICER1 is implicated in a common malignancy. We also found an additional recurrent mutation G1809R and demonstrated that it has similar detrimental effects on miRNA biogenesis as hotspot mutations through deep sequencing and realtime PCR. Using Illumina Miseq targeted resequencing and Sanger sequencing, we observed biallelic DICER1 mutations in RNase IIIb domain in some but not all cases. miRNA deep sequencing confirmed that 5p miRNAs are decreased in both cell line models and endometrial tumors with hotspot mutations. Bioinformatic analysis of RNA sequencing profiles from TCGA dataset predicted hotspot DICER1 mutations to have greater functional impact than non-hotspot DICER1 mutations on gene expression. The oncogenic properties of DICER1 hotspot mutations are currently under investigation.

Citation Format: Jiamin Chen, Yemin Wang, Melissa McConechy, Michael Anglesio, Janine Senz, Winnie Yang, Jamie Rosner, Andy Chu, Grace Cheng, Gregg Morin, David Huntsman. Recurrent DICER1 hotspot mutations in endometrial cancer and their impact on microRNA biogenesis. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 544. doi:10.1158/1538-7445.AM2014-544

Markers of T cell infiltration and function associate with favorable outcome in vascularized high-grade serous ovarian carcinoma

Background

When T cells infiltrate the tumor environment they encounter a myriad of metabolic stressors including hypoxia. Overcoming the limitations imposed by an inadequate tumor vasculature that contributes to these stressors may be a crucial step to immune cells mounting an effective anti-tumor response. We sought to determine whether the functional capacity of tumor infiltrating lymphocytes (TIL) could be influenced by the tumor vasculature and correlated this with survival in patients with ovarian cancer.

Methodology and Principal Findings

In 196 high-grade serous ovarian tumors, we confirmed that the tumor vascularity as measured by the marker CD31 was associated with improved patient disease-specific survival. We also found that tumors positive for markers of TIL (CD8, CD4 and forkhead box P3 (FoxP3)) and T cell function (granzyme B and T-cell restricted intracellular antigen-1 (TIA-1)) correlated significantly with elevated vascularity. In vitro, hypoxic CD8 T cells showed reduced cytolytic activity, secreted less effector cytokines and upregulated autophagy. Survival analysis revealed that patients had a significant improvement in disease-specific survival when FoxP3 expressing cells were present in CD31-high tumors compared to patients with FoxP3 expressing cells in CD31-low tumors [HR: 2.314 (95% CI 1.049–5.106); p = 0.0377]. Patients with high vascular endothelial growth factor (VEGF) expressing tumors containing granzyme B positive cells had improved survival compared to patients with granzyme B positive cells in VEGF-low tumors [HR: 2.522 (95% CI 1.097–5.799); p = 0.0294].

Significance

Overall, this data provides a rationale for developing strategies aimed at improving the adaptability and function of TIL to hypoxic tumor conditions.

Distinct evolutionary trajectories of primary high-grade serous ovarian cancers revealed through spatial mutational profiling

High-grade serous ovarian cancer (HGSC) is characterized by poor outcome, often attributed to the emergence of treatment-resistant subclones. We sought to measure the degree of genomic diversity within primary, untreated HGSCs to examine the natural state of tumour evolution prior to therapy. We performed exome sequencing, copy number analysis, targeted amplicon deep sequencing and gene expression profiling on 31 spatially and temporally separated HGSC tumour specimens (six patients), including ovarian masses, distant metastases and fallopian tube lesions. We found widespread intratumoural variation in mutation, copy number and gene expression profiles, with key driver alterations in genes present in only a subset of samples (eg PIK3CA, CTNNB1, NF1). On average, only 51.5% of mutations were present in every sample of a given case (range 10.2-91.4%), with TP53 as the only somatic mutation consistently present in all samples. Complex segmental aneuploidies, such as whole-genome doubling, were present in a subset of samples from the same individual, with divergent copy number changes segregating independently of point mutation acquisition. Reconstruction of evolutionary histories showed one patient with mixed HGSC and endometrioid histology, with common aetiologic origin in the fallopian tube and subsequent selection of different driver mutations in the histologically distinct samples. In this patient, we observed mixed cell populations in the early fallopian tube lesion, indicating that diversity arises at early stages of tumourigenesis. Our results revealed that HGSCs exhibit highly individual evolutionary trajectories and diverse genomic tapestries prior to therapy, exposing an essential biological characteristic to inform future design of personalized therapeutic solutions and investigation of drug-resistance mechanisms.

Accelerating type-specific ovarian carcinoma research: Calculator for Ovarian Subtype Prediction (COSP) is a reliable high-throughput tool for case review

AIMS

The recent recognition that ovarian carcinoma is composed of five distinct disease entities has served to increase the value of accurate histotyping. Reliable identification of histotypes is essential for the success of studies testing novel therapies, as well as for biomarker discovery research. The aim of this study was to examine the utility of a nine-marker immunohistochemical (IHC) panel, designated the Calculator for Ovarian Subtype Prediction (COSP), to reliably reproduce the consensus diagnosis of two expert gynaecological pathologists.

METHODS AND RESULTS

A total of 423 cases from the AGO-OVAR11 trial were evaluated using the COSP IHC panel, and compared to original diagnoses from >100 local contributing pathologists and independent expert gynaecopathology review. The overall concordance between COSP and expert review was 89%; in cases where a local pathologist's diagnosis was confirmed by COSP, the expert gynaecopathologist also agreed in 97.5% of cases.

CONCLUSIONS

The incorporation of COSP into a high-throughput diagnostic review algorithm will decrease the need for expert review by identifying a small number of difficult cases that truly require expert review. This modification will serve to increase the efficiency of the diagnostic review process, which will probably serve to reduce operational costs and expedite translational studies on ovarian carcinoma.

Profiling the cancer genome

Cancer profiling studies have had a profound impact on our understanding of the biology of cancers in a number of ways, including providing insights into the biological heterogeneity of specific cancer types, identification of novel oncogenes and tumor suppressors, and defining pathways that interact to drive the growth of individual cancers. Several large-scale genomic studies are underway that aim to catalog all biologically significant mutational events in each cancer type, and these findings will allow researchers to understand how mutational networks function within individual tumors. The identification of molecular predictive and prognostic tools to facilitate treatment decisions is an important step for individualized patient therapy and, ultimately, in improving patient outcomes. Whereas there are still significant challenges to implementing genomic testing and targeted therapy into routine clinical practice, rapid technological advancements provide hope for overcoming these obstacles.