Profiling of Tumour-Infiltrating Lymphocytes and Tumour-Associated Macrophages in Ovarian Epithelial Cancer-Relation to Tumour Characteristics and Impact on Prognosis.

Early evidence suggests a strong impact of tumour-infiltrating lymphocytes (TILs) on both the prognosis and clinical behaviour of ovarian cancer. Proven associations, however, have not yet translated to successful immunotherapies and further work in the field is urgently needed. We aimed to analyse the tumour microenvironment of a well-characterised cohort of ovarian cancer samples. Tumour markers were selected owing to their comparative underrepresentation in the current literature. Paraffin-embedded, formalin-fixed tumour tissue blocks of 138 patients representative of the population and including early stage disease were identified, stained for CD3, CD20, CD68 and CD163 and analysed for both the stromal and intertumoral components. Data were statistically analysed in relation to clinical details, histological subtype, borderline vs. malignant status, survival and management received. Mean stromal CD3, total CD3 count, mean stromal CD20 and total CD20 count all correlated negatively with survival. Malignant ovarian tumours consistently demonstrated significantly higher infiltration of all analysed immune cells than borderline tumours. Assessment of the stromal compartment produced a considerably higher proportion of significant results when compared to the intra-tumoural infiltrates. Customary assessment of solely intra-tumoural cells in advanced stage disease patients undergoing primary debulking surgery should be challenged, with recommendations for future scoring systems provided.

Protocol for transcutaneous tumor photolabeling to track immune cells in vivo using Kaede mice.

Preclinical tumor models have advanced our understanding of the tumor microenvironment. However, the temporal dynamics of cellular recruitment and retention within these models is poorly understood. Here, we present a protocol using transcutaneous labeling of the tumor compartment using subcutaneous and orthotopic tumors. We describe the process of cell line implantation and photoconversion of tumors to differentiate newly recruited cells from those retained within tumors. Photoconversion enables tracking of both immune cell recruitment to tumors and egress to the lymphatics. For complete details on the use and execution of this protocol, please refer to Li et al.1 and Molostvov et al.2.

Deciphering the molecular biology of inflammatory breast cancer through molecular characterization of patient samples and preclinical models.

Inflammatory breast cancer is an aggressive subtype of breast cancer with dismal patient prognosis and a unique clinical presentation. In the past two decades, molecular profiling technologies have been used in order to gain insight into the molecular biology of IBC and to search for possible targets for treatment. Although a gene signature that accurately discriminates between IBC and nIBC patient samples and preclinical models was identified, the overall genomic and transcriptomic differences are small and ambiguous, mainly due to the limited sample sizes of the evaluated patient series and the failure to correct for confounding effects of the molecular subtypes. Nevertheless, data collected over the past 20 years by independent research groups increasingly support the existence of several IBC-specific biological characteristics. In this review, these features are classified as established, emerging and conceptual hallmarks based on the level of evidence reported in the literature. In addition, a synoptic model is proposed that integrates all hallmarks and that can explain how cancer cell intrinsic mechanisms (i.e. NF-κB activation, genomic instability, MYC-addiction, TGF-ß resistance, adaptive stress response, chromatin remodeling, epithelial-to-mesenchymal transition) can contribute to the establishment of the dynamic immune microenvironment associated with IBC. It stands to reason that future research projects are needed to further refine (parts of) this model and to investigate its clinical translatability.