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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).

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.

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.

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.