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Some patients with advanced clear-cell ovarian cancer (CCOC) respond to immunotherapy; however, little is known about the tumor microenvironment (TME) of this relatively rare disease. Here, we describe a comprehensive quantitative and topographical analysis of biopsies from 45 patients, 9 with Federation Internationale des Gynaecologistes et Obstetristes (FIGO) stage I/II (early CCOC) and 36 with FIGO stage III/IV (advanced CCOC). We investigated 14 immune cell phenotype markers, PD-1 and ligands, and collagen structure and texture. We interrogated a microarray data set from a second cohort of 29 patients and compared the TMEs of ARID1A-wildtype (ARID1Awt) versus ARID1A-mutant (ARID1Amut) disease. We found significant variations in immune cell frequency and phenotype, checkpoint expression, and collagen matrix between the malignant cell area (MCA), leading edge (LE), and stroma. The MCA had the largest population of CD138+ plasma cells, the LE had more CD20+ B cells and T cells, whereas the stroma had more mast cells and αSMA+ fibroblasts. PD-L2 was expressed predominantly on malignant cells and was the dominant PD-1 ligand. Compared with early CCOC, advanced-stage disease had significantly more fibroblasts and a more complex collagen matrix, with microarray analysis indicating “TGFβ remodeling of the extracellular matrix” as the most significantly enriched pathway. Data showed significant differences in immune cell populations, collagen matrix, and cytokine expression between ARID1Awt and ARID1Amut CCOC, which may reflect different paths of tumorigenesis and the relationship to endometriosis. Increased infiltration of CD8+ T cells within the MCA and CD4+ T cells at the LE and stroma significantly associated with decreased overall survival.

Supplementary Data from The Tumor Microenvironment of Clear-Cell Ovarian Cancer

List of antibodies used for flow cytometry

IHC of TGFBI and POSTN

Legend of supplementary tables

Supplementary Table from The Genomic Landscape of Early-Stage Ovarian High-Grade Serous Carcinoma

Purpose:Ovarian high-grade serous carcinoma (HGSC) is usually diagnosed at late stage. We investigated whether late-stage HGSC has unique genomic characteristics consistent with acquisition of evolutionary advantage compared with early-stage tumors.Experimental Design:We performed targeted next-generation sequencing and shallow whole-genome sequencing (sWGS) on pretreatment samples from 43 patients with FIGO stage I–IIA HGSC to investigate somatic mutations and copy-number (CN) alterations (SCNA). We compared results to pretreatment samples from 52 patients with stage IIIC/IV HGSC from the BriTROC-1 study.Results:Age of diagnosis did not differ between early-stage and late-stage patients (median 61.3 years vs. 62.3 years, respectively). TP53 mutations were near-universal in both cohorts (89% early-stage, 100% late-stage), and there were no significant differences in the rates of other somatic mutations, including BRCA1 and BRCA2. We also did not observe cohort-specific focal SCNA that could explain biological behavior. However, ploidy was higher in late-stage (median, 3.0) than early-stage (median, 1.9) samples. CN signature exposures were significantly different between cohorts, with greater relative signature 3 exposure in early-stage and greater signature 4 in late-stage. Unsupervised clustering based on CN signatures identified three clusters that were prognostic.Conclusions:Early-stage and late-stage HGSCs have highly similar patterns of mutation and focal SCNA. However, CN signature analysis showed that late-stage disease has distinct signature exposures consistent with whole-genome duplication. Further analyses will be required to ascertain whether these differences reflect genuine biological differences between early-stage and late-stage or simply time-related markers of evolutionary fitness.See related commentary by Yang et al., p. 2730

The tumor microenvironment evolves during malignant progression, with major changes in nonmalignant cells, cytokine networks, and the extracellular matrix (ECM). In this study, we aimed to understand how the ECM changes during neoplastic transformation of serous tubal intraepithelial carcinoma lesions (STIC) into high-grade serous ovarian cancers (HGSOC). Analysis of the mechanical properties of human fallopian tubes (FT) and ovaries revealed that normal FT and fimbria had a lower tissue modulus, a measure of stiffness, than normal or diseased ovaries. Proteomic analysis of the matrisome fraction between FT, fimbria, and ovaries showed significant differences in the ECM protein TGF beta induced (TGFBI, also known as βig-h3). STIC lesions in the fimbria expressed high levels of TGFBI, which was predominantly produced by CD163-positive macrophages proximal to STIC epithelial cells. In vitro stimulation of macrophages with TGFβ and IL4 induced secretion of TGFBI, whereas IFNγ/LPS downregulated macrophage TGFBI expression. Immortalized FT secretory epithelial cells carrying clinically relevant TP53 mutations stimulated macrophages to secrete TGFBI and upregulated integrin αvβ3, a putative TGFBI receptor. Transcriptomic HGSOC datasets showed a significant correlation between TGFBI expression and alternatively activated macrophage signatures. Fibroblasts in HGSOC metastases expressed TGFBI and stimulated macrophage TGFBI production in vitro. Treatment of orthotopic mouse HGSOC tumors with an anti-TGFBI antibody reduced peritoneal tumor size, increased tumor monocytes, and activated β3-expressing unconventional T cells. In conclusion, TGFBI may favor an immunosuppressive microenvironment in STICs that persists in advanced HGSOC. Furthermore, TGFBI may be an effector of the tumor-promoting actions of TGFβ and a potential therapeutic target. Significance: Analysis of ECM changes during neoplastic transformation reveals a role for TGFBI secreted by macrophages in immunosuppression in early ovarian cancer.

Some patients with advanced clear-cell ovarian cancer (CCOC) respond to immunotherapy; however, little is known about the tumor microenvironment (TME) of this relatively rare disease. Here, we describe a comprehensive quantitative and topographical analysis of biopsies from 45 patients, 9 with Federation Internationale des Gynaecologistes et Obstetristes (FIGO) stage I/II (early CCOC) and 36 with FIGO stage III/IV (advanced CCOC). We investigated 14 immune cell phenotype markers, PD-1 and ligands, and collagen structure and texture. We interrogated a microarray data set from a second cohort of 29 patients and compared the TMEs of ARID1A-wildtype (ARID1Awt) versus ARID1A-mutant (ARID1Amut) disease. We found significant variations in immune cell frequency and phenotype, checkpoint expression, and collagen matrix between the malignant cell area (MCA), leading edge (LE), and stroma. The MCA had the largest population of CD138+ plasma cells, the LE had more CD20+ B cells and T cells, whereas the stroma had more mast cells and αSMA+ fibroblasts. PD-L2 was expressed predominantly on malignant cells and was the dominant PD-1 ligand. Compared with early CCOC, advanced-stage disease had significantly more fibroblasts and a more complex collagen matrix, with microarray analysis indicating “TGFβ remodeling of the extracellular matrix” as the most significantly enriched pathway. Data showed significant differences in immune cell populations, collagen matrix, and cytokine expression between ARID1Awt and ARID1Amut CCOC, which may reflect different paths of tumorigenesis and the relationship to endometriosis. Increased infiltration of CD8+ T cells within the MCA and CD4+ T cells at the LE and stroma significantly associated with decreased overall survival.

High-quality histopathology is essential for the success of clinical trials. Histopathologists have a detailed understanding of tumour biology and mechanisms of disease, as well as practical knowledge of optimal tissue handling and logistical service requirements for study delivery, such as biomarker evaluation, tissue acquisition and turnaround times. As such, histopathologist input is essential throughout every stage of research and clinical trials, from concept development and study design to trial delivery, analysis and dissemination of results. Patient recruitment to trials takes place among all healthcare settings, meaning that histopathologists make an invaluable contribution to clinical trials as part of their routine day-to-day work that often goes unrecognised. More complex evaluation of surgical specimens in the neoadjuvant setting and ever-expanding minimum data sets add to the workload of every histopathologist, not just academic pathologists in tertiary centres. This is occurring against a backdrop of increasing workload pressures and a worldwide shortage of histopathologists and biomedical scientists. Providing essential histopathology support for trials at grassroots level requires funding for adequate resources including histopathologist time, education and training, biomedical scientist and administrative support and greater recognition of the contribution made by histopathology. This paper will discuss the many ways in which histopathologists are involved in clinical trials and the challenges faced in meeting the additional demands posed by trial participation and potential ways to address this, with a special emphasis on the UK model and the Cellular-Molecular Pathology Initiative (CM-Path).

PurposeHigh grade serous carcinoma (HGSC) is the commonest type of ovarian cancer. Nearly all HGSC cases are diagnosed at late stage and it is not clear whether early stage HGSC has unique characteristics compared to late stage tumours.Experimental DesignWe analysed samples from 45 patients with FIGO stage I - IIA HGSC - 40 from the pathology archives of three large UK cancer centres and 5 from the BriTROC-1 study. We performed shallow whole genome sequencing (sWGS) and targeted next generation sequencing to investigate somatic mutations and copy number alterations. We compared results to 51 stage IIIC/IV HGSC patients from the BriTROC-1 study.ResultsThere was no difference in median age between the early stage (median 61.3 years, range 40-84) and late stage (median 62.3 years, range 34-76) patients at diagnosis. TP53 mutations were near-universal (92% early stage, 100% late stage samples) and there were no significant differences in the rates of other somatic mutations, including BRCA1 and BRCA2, or focal copy number alterations between early- and late-stage cohorts. There were also no unique amplifications or deletions in either cohort. However, median ploidy was greater in late stage (median 3.1) than early stage (median 2.0) samples. In addition, there were higher numbers of breakpoints per 10MB and per chromosome arm and higher absolute copy number in late stage than early stage cohorts; early stage samples had longer segment length. Overall copy number signature exposures were significantly different between early and late stage samples with greater signature 3 exposure in early stage and greater signature 4 in late stage. Both simplex plot and unsupervised hierarchical clustering suggested that a subset of late stage samples retain early stage appearances with high signature 3 and co-clustering with the early stage samplesConclusionsThese data suggest that there are no unique mutations or focal copy number alterations in early stage HGSC. However, whole genome duplication is significantly more common in late-stage disease, suggesting evolution during disease progression. However, a subset of late stage HGSC retains early-stage features, which are associated with improved overall survival.

Human papillomavirus (HPV)-associated cervical cancer represents one of the leading causes of cancer death worldwide. Although low-middle income countries are disproportionately affected, our knowledge of the disease predominantly originates from populations in high-income countries. Using the largest multi-omic analysis of cervical squamous cell carcinoma (CSCC) to date, totalling 643 tumours and representing patient populations from the USA, Europe and Sub-Saharan Africa, we identify two CSCC subtypes (C1 and C2) with differing prognosis. C1 tumours are largely HPV16-driven, display increased cytotoxic T-lymphocyte infiltration and frequently harbour PIK3CA and EP300 mutations. C2 tumours are associated with shorter overall survival, are frequently driven by HPVs from the HPV18-containing alpha-7 clade, harbour alterations in the Hippo signalling pathway and increased expression of immune checkpoint genes, B7-H3 (also known as CD276) and NT5E (also known as CD73) and PD-L2 (also known as PDCD1LG2). In conclusion, we identify two novel, therapy-relevant CSCC subtypes that share the same defining characteristics across three geographically diverse cohorts.

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.

The aim of this study is to characterize and validate similarities between the human tumor microenvironment (TME) and the TME of new HGSOC murine models and to use the models to analyze the role of tumor associated macrophages (TAMs) after chemotherapy. HGSOC has seen in the past decades only a modest reduction of mortality. This is in part due to the lack of suitable models, as the origin and mutation patterns of HGSOC were not previously understood. Despite recent advances with organoid models, murine models that represent the TME and in particular the complex interactions with the immune system are needed. We characterized the TME of six orthotopic, transplantable syngeneic murine HGSOC lines established from tumors in genetic models and compared these to patient biopsies. This analysis identified significant correlations between the transcriptome, host cell infiltrates, immune response, matrisome, vasculature and tissue modulus of mouse and human TMEs, with several stromal and malignant cell targets in common. However, each model also showed distinct differences and potential vulnerabilities that will enable us to study potential therapies. These models allowed us to extend our understanding of the role of TAMs following chemotherapy. Chemotherapy reduced the number and changed the phenotype of TAMs both in patient biopsies and in mouse models. Following chemotherapy, inflammasome activation in TAMs was also observed. Depletion of TAMs with CSFR1 inhibitors after carboplatin treatment reduced survival in a mouse model, suggesting that chemotherapy can activate sub-populations of macrophages to an anti-tumor phenotype that can sustain adaptive immunity. In conclusion, we have characterized murine transplantable models that share similarities with human HGSOC and have helped us elucidate the anti-tumor role of TAMs once activated by chemotherapy. Citation Format: Chiara Berlato, Owen Heath, Eleni Maniati, Ganga Gopinathan, Panoraia Kotantaki, Samar Elorbany, Jacqueline McDermott, Colin Pegrum, Ludmila Szabova, Ruth Perets, Ronny Drapkin, Peter Bailey, Alessandro Annibaldi, Desmond P. Barton, Frances R. Balkwill. Murine high grade serous ovarian cancer (HGSOC) models replicate the human tumor microenvironment and suggest anti-tumor activities of macrophages after chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2745.

Treatment of advanced Clear Cell Ovarian Cancer (CCOC) with immune checkpoint inhibition (ICI) is currently undergoing evaluation in a Phase II clinical trial. ARID1A mutations, which occur in up to 57% of CCOC, influence immune cell infiltration in pre-clinical models, but more information is needed on how it alters the tumor microenvironment (TME) of human CCOC. Methods: FFPE samples from 36 cases of FIGO III-IV CCOC were analyzed. Of the 36 cases; 21 were ARID1A wildtype (ARID1Awt), 14 ARID1A mutant (ARID1Amut) and 1 mixed. Immunohistochemistry was performed for immune markers (CD3, CD8, CD4, CD45RO, FOXP3, CD20, CD68, CD1a, Mast Cell Tryptase, Eosinophil Derived Neurotoxin, alpha-SMA) alongside PD1, PDL1, PDL2 and quantified using QuPath. The malignant cell area (MCA), leading edge (LE) and stroma were measured separately to provide information on immune marker location within the TME. Collagen was identified by Masson's Trichrome with structural analysis using the FIJI plugin TWOMBLI. Statistical analysis was performed on PRISM. Results: In this study we found significant differences between the TME of ARID1Awt and ARID1Amut tumors in terms of both immune infiltrate, collagen density and structure. ARID1Awt tumors had more collagen, with longer fibers and more branchpoints across the MCA, LE and Stroma ( Conclusion: There are significant differences in the collagen matrix, immune cell populations and the PD1-PDL1-PDL2 axis between ARID1Awt and ARID1Amut advanced CCOC tumors. This may influence response to ICI and other therapies. Citation Format: Michael-John Devlin, Rebecca S. Kristeleit, Jacqueline McDermott, Eleni Maniati, Florian Laforêts, Panoraia Kotantaki, Rowan Miller, Frances Balkwill. Impact of ARID1A mutation on the tumor microenvironment of advanced clear cell ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2748.

B cells are salient features of pancreatic ductal adenocarcinoma (PDAC) tumors, yet their role in this disease remains controversial. Murine studies have indicated a protumoral role for B cells, whereas clinical data show tumor-infiltrating B cells are a positive prognostic factor, both in PDAC and other cancers. This disparity needs to be clarified in order to develop effective immunotherapies. In this study, we provide new evidence that reconcile human and mouse data and highlight the importance of using relevant preclinical tumor models when assessing B cell function. We compared B cell infiltration and activation in both a genetic model of murine PDAC (KPC mouse) and an injectable orthotopic model. A pronounced B cell infiltrate was only observed in KPC tumors and correlated with T cell infiltration, mirroring human disease. In contrast, orthotopic tumors exhibited a relative paucity of B cells. Accordingly, KPC-derived B cells displayed markers of B cell activation (germinal center entry, B cell memory, and plasma cell differentiation) accompanied by significant intratumoral immunoglobulin deposition, a feature markedly weaker in orthotopic tumors. Tumor immunoglobulins, however, did not appear to form immune complexes. Furthermore, in contrast to the current paradigm that tumor B cells are immunosuppressive, when assessed as a bulk population, intratumoral B cells upregulated several proinflammatory and immunostimulatory genes, a distinctly different phenotype to that of splenic-derived B cells; further highlighting the importance of studying tumor-infiltrating B cells over B cells from secondary lymphoid organs. In agreement with the current literature, genetic deletion of B cells (μMT mice) resulted in reduced orthotopic tumor growth, however, this was not recapitulated by treatment with B-cell-depleting anti-CD20 antibody and, more importantly, was not observed in anti-CD20-treated KPC mice. This suggests the result from B cell deficient mice might be caused by their altered immune system, rather than lack of B cells. Therefore, our data indicate B cells do not favor tumor progression. In conclusion, our analysis of relevant preclinical models shows B cells to be active members of the tumor microenvironment, producing immunostimulatory factors that might support the adaptive antitumor immune response, as suggested by human PDAC studies.

Summary Although there are many prospective targets in the tumor microenvironment (TME) of high-grade serous ovarian cancer (HGSOC), pre-clinical testing is challenging, especially as there is limited information on the murine TME. Here, we characterize the TME of six orthotopic, transplantable syngeneic murine HGSOC lines established from genetic models and compare these to patient biopsies. We identify significant correlations between the transcriptome, host cell infiltrates, matrisome, vasculature, and tissue modulus of mouse and human TMEs, with several stromal and malignant targets in common. However, each model shows distinct differences and potential vulnerabilities that enabled us to test predictions about response to chemotherapy and an anti-IL-6 antibody. Using machine learning, the transcriptional profiles of the mouse tumors that differed in chemotherapy response are able to classify chemotherapy-sensitive and -refractory patient tumors. These models provide useful pre-clinical tools and may help identify subgroups of HGSOC patients who are most likely to respond to specific therapies., Graphical Abstract, Highlights • Mouse ovarian cancers replicate the human ovarian tumor microenvironment • Stromal, immune, and malignant cell targets in common • Evidence for distinct therapeutic vulnerabilities in individual models • Models may help identify patient subgroups likely to respond to specific therapies, Maniati et al. show how orthotopic transplantable mouse ovarian cancers with appropriate genotypes develop microenvironments that replicate many features of human primary ovarian tumors and metastases. Molecular features of the mouse tumors combined with machine learning may allow the identification of patients who are most likely to respond to specific therapies.

Background: In colorectal and breast cancer, the density and localization 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 and Findings: 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. Epithelial CD8 (p=0.027, 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 tumor and stromal compartments.Using principal component analysis (PCA), we identified optimized multiparameter survival models that combined 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 modeling and evidence for the multiple effects of different immune factors on survival. The presence of stromal CD68+ and CD45RO+ populations was strongly associated with survival, underscoring the benefits that evaluating stromal immune populations may bring for prognostic immunoscores in HGSOC. Citation Format: Anne Montfort, Steph J. Owen, Anna M. Piskorz, Anna Supernat, Luiza Moore, Sarwah Al-Khalidi, Steffen Boehm, Paul Pharoah, Jacqueline McDermott, Frances R. Balkwill, James D. Brenton. Combining measures of immune infiltration uncovers predictors of survival in high-grade serous ovarian cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4976.

Epithelial ovarian cancer consists of 5 major histotypes: high-grade serous carcinoma (HGSC), endometrioid carcinoma (EC), clear cell carcinoma (CCC), mucinous carcinoma (MC) and low-grade serous (LGSC). Each can have a broad spectrum of morphological appearances, and one histotype can closely mimic histopathological features more typical of another. Historically, there has been a relatively high frequency of mixed, defined by 2 or more distinct histotypes present based on routine histopathological assessment, histotype carcinoma diagnoses (3–11%), however recent immunohistochemical studies identifying histotype specific markers and allowing more refined histotype diagnoses suggests a much lower incidence. We reviewed hematoxylin and eosin stained slides from 871 cases of epithelial ovarian cancer and found the frequency of mixed carcinomas to be 1.7% when modern diagnostic criteria are applied. Through international collaboration, we established a cohort totaling 22 mixed epithelial ovarian cancers, consisting of 9 EC/CCC, 4 EC/LGSC, 3 HGSC/CCC, 2 CCC/MC and 4 other combinations. We interrogated the molecular differences between the different components of each case using immunohistochemistry, gene expression and hotspot sequencing analyses. Immunohistochemical data alone suggested 9 of the 22 cases were not mixed tumors as they presented a uniform immuno-phenotype throughout, and these cases most probably represent morphological mimicry and variation within tumors of a single histotype. Synthesis of molecular data further reduces the incidence of mixed carcinomas. Based on these results, true mixed carcinomas with both morphological and molecular support for the presence of more than one histotype within a given tumor represent less than 1% of epithelial ovarian cancers.

Many tumours have abundant macrophage populations. Tumour-associated macrophages (TAMs) frequently have tumour promoting roles and are associated with poor clinical outcome. We hypothesise that targeting TAMs in high-grade serous ovarian cancer (HGSOC) may improve response to chemotherapy. We have assessed the effects of chemotherapy on TAM populations in human HGSOC obtained pre- and post-chemotherapy as well as in murine HGSOC models harbouring a relevant mutational profile. We find that chemotherapy treatment decreases TAM density within tumour areas. Furthermore, TAMs expressing markers known to associate with disease progression were decreased following chemotherapy. In vivo and in vitro we have demonstrated an up-regulation of inflammasome activation and TLR signalling in live myeloid cells following chemotherapy and have shown that macrophages are killed by chemotherapy at clinically relevant drug concentrations. These observations suggest a mechanism for TAM depletion and highlight chemotherapy induced activation of innate immunity in HGSOC. The majority of HGSOC patients respond well to first line chemotherapy but will relapse and succumb to treatment resistant disease. We have developed a murine model of HGSOC relapse after first-line chemotherapy, which has the potential to extend translational studies into this clinically important area. We have found that TAMs are re-established in tumours at relapse, suggesting a clinically defined window of opportunity to target TAMs in HGSOC following first-line chemotherapy. Overall, our results provide a rationale for targeted re-programming of TAMs in HGSOC after chemotherapy. Citation Format: Owen M. Heath, Eleni Maniati, Chiara Belato, Ganga Gopinathan, Laura Lecker, Anissa Lakhani, Colin Pegrum, Jacqueline McDermott, Michelle Lockley, Desmond P. Barton, Frances Balkwill. The effects of neo-adjuvant chemotherapy on myeloid cells in high-grade serous ovarian cancer metastases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1103.

A 3-tier histopathologic scoring system, the chemotherapy response score (CRS), was previously devised for reporting the histologic response to neoadjuvant chemotherapy in interval debulking surgery specimens of stage IIIc/IV tuboovarian high-grade serous carcinoma. This has been shown to predict the outcome and offer additional information to other methods of assessing the treatment response. In the present study, the reproducibility of this scoring system was assessed by determining the interobserver agreement among reporting pathologists. A total of 5 groups each comprising 3 pathologists with different levels of expertise were selected. The participants underwent an online tutorial on how to apply the CRS system. 40 cases (38 cases in 2 appraiser groups) were scored individually by each of the 15 pathologists. The interobserver reproducibility was calculated using Fleiss' κ, Kendall's coefficient of concordance, and the absolute agreement between (a) individual pathologists within 1 group, (b) with the majority score agreement between all groups, and (c) with all individual scores. The CRS system was found to be highly reproducible among all the pathologists' groups (κ=0.761). The agreement in identifying the group of patients with the best response to chemotherapy was exceptionally high (κ=0.926). We conclude that CRS has a high interobserver reproducibility, especially in identifying the subgroup of patients with the best chemotherapy response, justifying its inclusion in clinical trials and reporting practice.

The WHO Poliovirus Eradication Programme has renewed interest in the identification of wild and vaccine strains of poliovirus circulating in the community. One method of monitoring these strains is to study poliovirus isolates detected in sewage. To facilitate the isolation of poliovirus from sewage and eliminate the possibility of detecting the other enteroviruses, sewage was inoculated onto a transfected Mouse L cell line. This cell line contains the gene for the poliovirus receptor which allows poliovirus infection to take place but not that of other enteroviruses. This cell line is, however, too sensitive to the toxic elements of concentrated sewage to be of practical use. Polioviruses have also been isolated from river and seawater as part of three year surveys of sewage discharges into a river system and a coastal harbour. These isolates have been characterised using PCR amplification of a region of the VP1 gene followed by restriction fragment length polymorphism (RFLP) analysis. All isolates were vaccine-like although many poliovirus type 2 isolates had distinct PCR-RFLP profiles. The RFLP typing method is an efficient system for rapidly monitoring poliovirus isolates from the environment.