Impact of imperfect annotations on CNN training and performance for instance segmentation and classification in digital pathology.

Segmentation and classification of large numbers of instances, such as cell nuclei, are crucial tasks in digital pathology for accurate diagnosis. However, the availability of high-quality datasets for deep learning methods is often limited due to the complexity of the annotation process. In this work, we investigate the impact of noisy annotations on the training and performance of a state-of-the-art CNN model for the combined task of detecting, segmenting and classifying nuclei in histopathology images. In this context, we investigate the conditions for determining an appropriate number of training epochs to prevent overfitting to annotation noise during training. Our results indicate that the utilisation of a small, correctly annotated validation set is instrumental in avoiding overfitting and maintaining model performance to a large extent. Additionally, our findings underscore the beneficial role of pre-training.

Correction: VEGFR1 and VEGFR2 Involvement in Extracellular Galectin-1- and Galectin-3-Induced Angiogenesis.

[This corrects the article DOI: 10.1371/journal.pone.0067029.].

Usefulness of FAPα assessment in bronchoalveolar lavage as a marker of fibrogenesis: results of a preclinical study and first report in patients with idiopathic pulmonary fibrosis.

BACKGROUND: Fibroblast activation protein-α (FAPα) is a marker of activated fibroblasts that can be selectively targeted by an inhibitor (FAPI) and visualised by PET/CT imaging. We evaluated whether the measurement of FAPα in bronchoalveolar lavage fluids (BALF) and the uptake of FAPI by PET/CT could be used as biomarkers of fibrogenesis. METHODS: The dynamics of lung uptake of 18F-labeled FAPI ([18F]FAPI-74) was assessed in the bleomycin mouse model at various time points and using different concentrations of bleomycin by PET/CT. FAPα was measured in BALFs from these bleomycin-treated and control mice. FAPα levels were also assessed in BALFs from controls and patients with idiopathic pulmonary fibrosis (IPF). RESULTS: Bleomycin-treated mice presented a significantly higher uptake of [18F]FAPI-74 during lung fibrinogenesis (days 10 and 16 after instillation) compared to control mice. No significant difference was observed at initial inflammatory phase (3 days) and when fibrosis was already established (28 days). [18F]FAPI-74 tracer was unable to show a dose-response to bleomycin treatment. On the other hand, BALF FAPα levels were steeply higher in bleomycin-treated mice at day 10 and a significant dose-response effect was observed. Moreover, FAPα levels were strongly correlated with lung fibrosis as measured by the modified Aschroft histological analysis, hydroxyproline and the percentage of weight loss. Importantly, higher levels of FAPα were observed in IPF patients where the disease was progressing as compared to stable patients and controls. Moreover, patients with FAPα BALF levels higher than 192.5 pg/mL presented a higher risk of progression, transplantation or death compared to patients with lower levels. CONCLUSIONS: Our preclinical data highlight a specific increase of [18F]FAPI-74 lung uptake during the fibrotic phase of the bleomycin murine model. The measurement of FAPα in BALF appears to be a promising marker of the fibrotic activity in preclinical models of lung fibrosis and in IPF patients. Further studies are required to confirm the role of FAPα in BALF as biomarker of IPF activity and assess the relationship between FAPα levels in BALF and [18F]FAPI-74 uptake on PET/CT in patients with fibrotic lung disease.

Pharmacological targeting of netrin-1 inhibits EMT in cancer.

Epithelial-to-mesenchymal transition (EMT) regulates tumour initiation, progression, metastasis and resistance to anti-cancer therapy1-7. Although great progress has been made in understanding the role of EMT and its regulatory mechanisms in cancer, no therapeutic strategy to pharmacologically target EMT has been identified. Here we found that netrin-1 is upregulated in a primary mouse model of skin squamous cell carcinoma (SCC) exhibiting spontaneous EMT. Pharmacological inhibition of netrin-1 by administration of NP137, a netrin-1-blocking monoclonal antibody currently used in clinical trials in human cancer (ClinicalTrials.gov identifier NCT02977195 ), decreased the proportion of EMT tumour cells in skin SCC, decreased the number of metastases and increased the sensitivity of tumour cells to chemotherapy. Single-cell RNA sequencing revealed the presence of different EMT states, including epithelial, early and late hybrid EMT, and full EMT states, in control SCC. By contrast, administration of NP137 prevented the progression of cancer cells towards a late EMT state and sustained tumour epithelial states. Short hairpin RNA knockdown of netrin-1 and its receptor UNC5B in EPCAM+ tumour cells inhibited EMT in vitro in the absence of stromal cells and regulated a common gene signature that promotes tumour epithelial state and restricts EMT. To assess the relevance of these findings to human cancers, we treated mice transplanted with the A549 human cancer cell line-which undergoes EMT following TGFß1 administration8,9-with NP137. Netrin-1 inhibition decreased EMT in these transplanted A549 cells. Together, our results identify a pharmacological strategy for targeting EMT in cancer, opening up novel therapeutic interventions for anti-cancer therapy.

Netrin-1 blockade inhibits tumour growth and EMT features in endometrial cancer.

Netrin-1 is upregulated in cancers as a protumoural mechanism1. Here we describe netrin-1 upregulation in a majority of human endometrial carcinomas (ECs) and demonstrate that netrin-1 blockade, using an anti-netrin-1 antibody (NP137), is effective in reduction of tumour progression in an EC mouse model. We next examined the efficacy of NP137, as a first-in-class single agent, in a Phase I trial comprising 14 patients with advanced EC. As best response we observed 8 stable disease (8 out of 14, 57.1%) and 1 objective response as RECIST v.1.1 (partial response, 1 out of 14 (7.1%), 51.16% reduction in target lesions at 6 weeks and up to 54.65% reduction during the following 6 months). To evaluate the NP137 mechanism of action, mouse tumour gene profiling was performed, and we observed, in addition to cell death induction, that NP137 inhibited epithelial-to-mesenchymal transition (EMT). By performing bulk RNA sequencing (RNA-seq), spatial transcriptomics and single-cell RNA-seq on paired pre- and on-treatment biopsies from patients with EC from the NP137 trial, we noted a net reduction in tumour EMT. This was associated with changes in immune infiltrate and increased interactions between cancer cells and the tumour microenvironment. Given the importance of EMT in resistance to current standards of care2, we show in the EC mouse model that a combination of NP137 with carboplatin-paclitaxel outperformed carboplatin-paclitaxel alone. Our results identify netrin-1 blockade as a clinical strategy triggering both tumour debulking and EMT inhibition, thus potentially alleviating resistance to standard treatments.

SMAD4 Positive Pancreatic Ductal Adenocarcinomas Are Associated with Better Outcomes in Patients Receiving FOLFIRINOX-Based Neoadjuvant Therapy.

BACKGROUND: SMAD4 is inactivated in 50-55% of pancreatic ductal adenocarcinomas (PDACs). SMAD4 loss of expression has been described as a negative prognostic factor in PDAC associated with an increased rate of metastasis and resistance to therapy. However, the impact of SMAD4 inactivation in patients receiving neoadjuvant therapy (NAT) is not well characterized. The aim of our study was to investigate whether SMAD4 status is a prognostic and predictive factor in patients receiving NAT. METHODS: We retrospectively analyzed 59 patients from a single center who underwent surgical resection for primary PDAC after NAT. SMAD4 nuclear expression was assessed by immunohistochemistry, and its relationship to clinicopathologic variables and survival parameters was evaluated. Interaction testing was performed between SMAD4 status and the type of NAT. RESULTS: 49.15% of patients presented loss of SMAD4. SMAD4 loss was associated with a higher positive lymph node ratio (p = 0.03), shorter progression-free survival (PFS) (p = 0.02), and metastasis-free survival (MFS) (p = 0.02), but it was not an independent prognostic biomarker in multivariate analysis. Interaction tests demonstrated that patients with SMAD4-positive tumors receiving FOLFIRINOX-based NAT showed the best outcome. CONCLUSION: This study highlights the potential prognostic and predictive role of SMAD4 status in PDAC patients receiving FOLFIRINOX-based NAT.

Comparison Between Manual and Automated Assessment of Ki-67 in Breast Carcinoma: Test of a Simple Method in Daily Practice.

BACKGROUND: In the era of "precision medicine," the availability of high-quality tumor biomarker tests is critical and tumor proliferation evaluated by Ki-67 antibody is one of the most important prognostic factors in breast cancer. But the evaluation of Ki-67 index has been shown to suffer from some interobserver variability. The goal of the study is to develop an easy, automated, and reliable Ki-67 assessment approach for invasive breast carcinoma in routine practice. PATIENTS AND METHODS: A total of 151 biopsies of invasive breast carcinoma were analyzed. The Ki-67 index was evaluated by 2 pathologists with MIB-1 antibody as a global tumor index and also in a hotspot. These 2 areas were also analyzed by digital image analysis (DIA). RESULTS: For Ki-67 index assessment, in the global and hotspot tumor area, the concordances were very good between DIA and pathologists when DIA focused on the annotations made by pathologist (0.73 and 0.83, respectively). However, this was definitely not the case when DIA was not constrained within the pathologist's annotations and automatically established its global or hotspot area in the whole tissue sample (concordance correlation coefficients between 0.28 and 0.58). CONCLUSIONS: The DIA technique demonstrated a meaningful concordance with the indices evaluated by pathologists when the tumor area is previously identified by a pathologist. In contrast, basing Ki-67 assessment on automatic tissue detection was not satisfactory and provided bad concordance results. A representative tumoral zone must therefore be manually selected prior to the measurement made by the DIA.

Panoptic quality should be avoided as a metric for assessing cell nuclei segmentation and classification in digital pathology.

Panoptic Quality (PQ), designed for the task of "Panoptic Segmentation" (PS), has been used in several digital pathology challenges and publications on cell nucleus instance segmentation and classification (ISC) since its introduction in 2019. Its purpose is to encompass the detection and the segmentation aspects of the task in a single measure, so that algorithms can be ranked according to their overall performance. A careful analysis of the properties of the metric, its application to ISC and the characteristics of nucleus ISC datasets, shows that is not suitable for this purpose and should be avoided. Through a theoretical analysis we demonstrate that PS and ISC, despite their similarities, have some fundamental differences that make PQ unsuitable. We also show that the use of the Intersection over Union as a matching rule and as a segmentation quality measure within PQ is not adapted for such small objects as nuclei. We illustrate these findings with examples taken from the NuCLS and MoNuSAC datasets. The code for replicating our results is available on GitHub ( https://github.com/adfoucart/panoptic-quality-suppl ).

SARS-Cov-2 infection and neuropathological findings: a report of 18 cases and review of the literature.

INTRODUCTION: COVID-19-infected patients harbour neurological symptoms such as stroke and anosmia, leading to the hypothesis that there is direct invasion of the central nervous system (CNS) by SARS-CoV-2. Several studies have reported the neuropathological examination of brain samples from patients who died from COVID-19. However, there is still sparse evidence of virus replication in the human brain, suggesting that neurologic symptoms could be related to mechanisms other than CNS infection by the virus. Our objective was to provide an extensive review of the literature on the neuropathological findings of postmortem brain samples from patients who died from COVID-19 and to report our own experience with 18 postmortem brain samples. MATERIAL AND METHODS: We used microscopic examination, immunohistochemistry (using two different antibodies) and PCR-based techniques to describe the neuropathological findings and the presence of SARS-CoV-2 virus in postmortem brain samples. For comparison, similar techniques (IHC and PCR) were applied to the lung tissue samples for each patient from our cohort. The systematic literature review was conducted from the beginning of the pandemic in 2019 until June 1st, 2022. RESULTS: In our cohort, the most common neuropathological findings were perivascular haemosiderin-laden macrophages and hypoxic-ischaemic changes in neurons, which were found in all cases (n = 18). Only one brain tissue sample harboured SARS-CoV-2 viral spike and nucleocapsid protein expression, while all brain cases harboured SARS-CoV-2 RNA positivity by PCR. A colocalization immunohistochemistry study revealed that SARS-CoV-2 antigens could be located in brain perivascular macrophages. The literature review highlighted that the most frequent neuropathological findings were ischaemic and haemorrhagic lesions, including hypoxic/ischaemic alterations. However, few studies have confirmed the presence of SARS-CoV-2 antigens in brain tissue samples. CONCLUSION: This study highlighted the lack of specific neuropathological alterations in COVID-19-infected patients. There is still no evidence of neurotropism for SARS-CoV-2 in our cohort or in the literature.

Shortcomings and areas for improvement in digital pathology image segmentation challenges.

Digital pathology image analysis challenges have been organised regularly since 2010, often with events hosted at major conferences and results published in high-impact journals. These challenges mobilise a lot of energy from organisers, participants, and expert annotators (especially for image segmentation challenges). This study reviews image segmentation challenges in digital pathology and the top-ranked methods, with a particular focus on how reference annotations are generated and how the methods' predictions are evaluated. We found important shortcomings in the handling of inter-expert disagreement and the relevance of the evaluation process chosen. We also noted key problems with the quality control of various challenge elements that can lead to uncertainties in the published results. Our findings show the importance of greatly increasing transparency in the reporting of challenge results, and the need to make publicly available the evaluation codes, test set annotations and participants' predictions. The aim is to properly ensure the reproducibility and interpretation of the results and to increase the potential for exploitation of the substantial work done in these challenges.

Chemerin plasma levels are increased in COVID-19 patients and are an independent risk factor of mortality.

Background: Chemerin is an extracellular protein with chemotactic activities and its expression is increased in various diseases such as metabolic syndrome and inflammatory conditions. Its role in lung pathology has not yet been extensively studied but both known pro- and anti-inflammatory properties have been observed. The aim of our study was to evaluate the involvement of the chemerin/ChemR23 system in the physiopathology of COVID-19 with a particular focus on its prognostic value. Methods: Blood samples from confirmed COVID-19 patients were collected at day 1, 5 and 14 from admission to Erasme Hospital (Brussels - Belgium). Chemerin concentrations and inflammatory biomarkers were analyzed in the plasma. Blood cells subtypes and their expression of ChemR23 were determined by flow cytometry. The expression of chemerin and ChemR23 was evaluated on lung tissue from autopsied COVID-19 patients by immunohistochemistry (IHC). Results: 21 healthy controls (HC) and 88 COVID-19 patients, including 40 in intensive care unit (ICU) were included. Plasma chemerin concentration were significantly higher in ICU patients than in HC at all time-points analyzed (p<0.0001). Moreover, they were higher in deceased patients compared to survivors (p<0.05). Logistic univariate regression and multivariate analysis demonstrated that chemerin level at day 14 of admission was an independent risk factor for death. Accordingly, chemerin levels correlated with inflammatory biomarkers such as C-reactive protein and tumor necrosis factor α. Finally, IHC analysis revealed a strong expression of ChemR23 on smooth muscle cells and chemerin on myofibroblasts in advanced acute respiratory distress syndrome (ARDS). Discussion: Increased plasma chemerin levels are a marker of severity and may predict death of COVID-19 patients. However, multicentric studies are needed, before chemerin can be considered as a biomarker of severity and death used in daily clinical practice. Further studies are also necessary to identify the precise mechanisms of the chemerin/ChemR23 system in ARDS secondary to viral pneumonia.

Deep Learning for Reaction-Diffusion Glioma Growth Modeling: Towards a Fully Personalized Model?

Reaction-diffusion models have been proposed for decades to capture the growth of gliomas, the most common primary brain tumors. However, ill-posedness of the initialization at diagnosis time and parameter estimation of such models have restrained their clinical use as a personalized predictive tool. In this work, we investigate the ability of deep convolutional neural networks (DCNNs) to address commonly encountered pitfalls in the field. Based on 1200 synthetic tumors grown over real brain geometries derived from magnetic resonance (MR) data of six healthy subjects, we demonstrate the ability of DCNNs to reconstruct a whole tumor cell-density distribution from only two imaging contours at a single time point. With an additional imaging contour extracted at a prior time point, we also demonstrate the ability of DCNNs to accurately estimate the individual diffusivity and proliferation parameters of the model. From this knowledge, the spatio-temporal evolution of the tumor cell-density distribution at later time points can ultimately be precisely captured using the model. We finally show the applicability of our approach to MR data of a real glioblastoma patient. This approach may open the perspective of a clinical application of reaction-diffusion growth models for tumor prognosis and treatment planning.

The Role of SMAD4 Inactivation in Epithelial-Mesenchymal Plasticity of Pancreatic Ductal Adenocarcinoma: The Missing Link?

Pancreatic ductal adenocarcinoma (PDAC) presents a five-year survival rate of 10% and its incidence increases over the years. It is, therefore, essential to improve our understanding of the molecular mechanisms that promote metastasis and chemoresistance in PDAC, which are the main causes of death in these patients. SMAD4 is inactivated in 50% of PDACs and its loss has been associated with worse overall survival and metastasis, although some controversy still exists. SMAD4 is the central signal transducer of the transforming growth factor-beta (TGF-beta) pathway, which is notably known to play a role in epithelial-mesenchymal transition (EMT). EMT is a biological process where epithelial cells lose their characteristics to acquire a spindle-cell phenotype and increased motility. EMT has been increasingly studied due to its potential implication in metastasis and therapy resistance. Recently, it has been suggested that cells undergo EMT transition through intermediary states, which is referred to as epithelial-mesenchymal plasticity (EMP). The intermediary states are characterized by enhanced aggressiveness and more efficient metastasis. Therefore, this review aims to summarize and analyze the current knowledge on SMAD4 loss in patients with PDAC and to investigate its potential role in EMP in order to better understand its function in PDAC carcinogenesis.

Immunohistochemistry as an accurate tool for the assessment of BRAF V600E and TP53 mutations in primary and metastatic melanoma.

Metastatic melanoma is a fatal disease with poor prognosis. Ever since targeted therapy against oncogenic BRAF was approved, molecular profiling has become an integral part of the management of such patients. While molecular testing is not available in all pathology laboratories, immunohistochemistry (IHC) is a reliable screening option. The major objective of the present study was to evaluate whether IHC detection of BRAF and the tumor (suppressor) protein 53 gene (TP53) are reliable surrogates for mutation detection. Formalin-fixed paraffin-embedded samples of melanomas for which molecular data were previously obtained by targeted next-generation sequencing (NGS) between January 2014 and February 2019 were immunostained with BRAF V600E and p53 antibodies. A blinded evaluation of the IHC slides was performed by two pathologists in order to evaluate inter-observer concordance (discordant cases were reviewed by a third observer). The associations between the results of IHC and molecular profiling were evaluated. The study included a series of 37 cases of which 15 harbored a BRAF mutation and five a TP53 mutation. IHC had an overall diagnostic accuracy of 93.9% for BRAF V600E and 68.8% for TP53 compared to NGS. A statistically significant association between the two diagnostic methods was obtained for BRAF V600E (P=0.0004) but not for p53 (P=0.3098) IHC. The κ coefficient for IHC assessment of p53 was 0.55 and that for BRAF V600E was 0.72. In conclusion, the present results evidenced that IHC staining is a reliable surrogate for NGS in identifying the BRAF V600E mutation, which may become an efficient screening tool. Aberrant expression of p53 on IHC is at times associated with TP53 mutations but it was not possible to establish a direct link.

Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study.

Reaction-diffusion models have been proposed for decades to capture the growth of gliomas. Nevertheless, these models require an initial condition: the tumor cell density distribution over the whole brain at diagnosis time. Several works have proposed to relate this distribution to abnormalities visible on magnetic resonance imaging (MRI). In this work, we verify these hypotheses by stereotactic histological analysis of a non-operated brain with glioblastoma using a 3D-printed slicer. Cell density maps are computed from histological slides using a deep learning approach. The density maps are then registered to a postmortem MR image and related to an MR-derived geodesic distance map to the tumor core. The relation between the edema outlines visible on T2-FLAIR MRI and the distance to the core is also investigated. Our results suggest that (i) the previously proposed exponential decrease of the tumor cell density with the distance to the core is reasonable but (ii) the edema outlines would not correspond to a cell density iso-contour and (iii) the suggested tumor cell density at these outlines is likely overestimated. These findings highlight the limitations of conventional MRI to derive glioma cell density maps and the need for other initialization methods for reaction-diffusion models to be used in clinical practice.

Analyses of DNA Methylation Profiling in the Diagnosis of Intramedullary Astrocytomas.

Intramedullary astrocytomas (IMAs) consist of a heterogeneous group of rare central nervous system (CNS) tumors associated with variable outcomes. A DNA methylation-based classification approach has recently emerged as a powerful tool to further classify CNS tumors. However, no DNA methylation-related studies specifically addressing to IMAs have been performed yet. In the present study, we analyzed 16 IMA samples subjected to morphological and molecular analyses, including DNA methylation profiling. Among the 16 samples, only 3 cases were classified in a reference methylation class (MC) with the recommended calibrated score (≥0.9). The remaining cases were either considered "no-match" cases (calibrated score <0.3, n = 7) or were classified with low calibrated scores (ranging from 0.32 to 0.53, n = 6), including inconsistent classification. To obtain a more comprehensive tool for pathologists, we used different unsupervised analyses of DNA methylation profiles, including our data and those from the Heidelberg reference cohort. Even though our cohort included only 16 cases, hypotheses regarding IMA-specific classification were underlined; a potential specific MC of PA_SPINE was identified and high-grade IMAs, probably consisting of H3K27M wild-type IMAs, were mainly associated with ANA_PA MC. These hypotheses strongly suggest that a specific classification for IMAs has to be investigated.

Voxelwise Principal Component Analysis of Dynamic [S-Methyl-11C]Methionine PET Data in Glioma Patients.

Recent works have demonstrated the added value of dynamic amino acid positron emission tomography (PET) for glioma grading and genotyping, biopsy targeting, and recurrence diagnosis. However, most of these studies are based on hand-crafted qualitative or semi-quantitative features extracted from the mean time activity curve within predefined volumes. Voxelwise dynamic PET data analysis could instead provide a better insight into intra-tumor heterogeneity of gliomas. In this work, we investigate the ability of principal component analysis (PCA) to extract relevant quantitative features from a large number of motion-corrected [S-methyl-11C]methionine ([11C]MET) PET frames. We first demonstrate the robustness of our methodology to noise by means of numerical simulations. We then build a PCA model from dynamic [11C]MET acquisitions of 20 glioma patients. In a distinct cohort of 13 glioma patients, we compare the parametric maps derived from our PCA model to these provided by the classical one-compartment pharmacokinetic model (1TCM). We show that our PCA model outperforms the 1TCM to distinguish characteristic dynamic uptake behaviors within the tumor while being less computationally expensive and not requiring arterial sampling. Such methodology could be valuable to assess the tumor aggressiveness locally with applications for treatment planning and response evaluation. This work further supports the added value of dynamic over static [11C]MET PET in gliomas.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Genome Sequencing from Post-Mortem Formalin-Fixed, Paraffin-Embedded Lung Tissues.

Implementation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing in the daily practice of pathology laboratories requires procedure adaptation to formalin-fixed, paraffin-embedded (FFPE) samples. So far, one study reported the feasibility of SARS-CoV-2 genome sequencing on FFPE tissues with only one contributory case of two. This study optimized SARS-CoV-2 genome sequencing using the Ion AmpliSeq SARS-CoV-2 Panel on 22 FFPE lung tissues from 16 deceased coronavirus disease 2019 (COVID-19) patients. SARS-CoV-2 was detected in all FFPE blocks using a real-time RT-qPCR targeting the E gene with crossing point (Cp) values ranging from 16.02 to 34.16. Sequencing was considered as contributory (i.e. with a uniformity >55%) for 17 FFPE blocks. Adapting the number of target amplification PCR cycles according to the RT-qPCR Cp values allowed optimization of the sequencing quality for the contributory blocks (i.e. 20 PCR cycles for blocks with a Cp value <28 and 25 PCR cycles for blocks with a Cp value between 28 and 30). Most blocks with a Cp value >30 were non-contributory. Comparison of matched frozen and FFPE tissues revealed discordance for only three FFPE blocks, all with a Cp value >28. Variant identification and clade classification was possible for 13 patients. This study validates SARS-CoV-2 genome sequencing on FFPE blocks and opens the possibility to explore correlation between virus genotype and histopathologic lesions.

Fat1 deletion promotes hybrid EMT state, tumour stemness and metastasis.

FAT1, which encodes a protocadherin, is one of the most frequently mutated genes in human cancers1-5. However, the role and the molecular mechanisms by which FAT1 mutations control tumour initiation and progression are poorly understood. Here, using mouse models of skin squamous cell carcinoma and lung tumours, we found that deletion of Fat1 accelerates tumour initiation and malignant progression and promotes a hybrid epithelial-to-mesenchymal transition (EMT) phenotype. We also found this hybrid EMT state in FAT1-mutated human squamous cell carcinomas. Skin squamous cell carcinomas in which Fat1 was deleted presented increased tumour stemness and spontaneous metastasis. We performed transcriptional and chromatin profiling combined with proteomic analyses and mechanistic studies, which revealed that loss of function of FAT1 activates a CAMK2-CD44-SRC axis that promotes YAP1 nuclear translocation and ZEB1 expression that stimulates the mesenchymal state. This loss of function also inactivates EZH2, promoting SOX2 expression, which sustains the epithelial state. Our comprehensive analysis identified drug resistance and vulnerabilities in FAT1-deficient tumours, which have important implications for cancer therapy. Our studies reveal that, in mouse and human squamous cell carcinoma, loss of function of FAT1 promotes tumour initiation, progression, invasiveness, stemness and metastasis through the induction of a hybrid EMT state.

The potential of tumour microenvironment markers to stratify the risk of recurrence in prostate cancer patients.

The tumour micro-environment (TME) plays a crucial role in the onset and progression of prostate cancer (PCa). Here we studied the potential of a selected panel of TME-markers to predict clinical recurrence (CLR) in PCa. Patient cohorts were matched for the presence or absence of CLR 5 years post-prostatectomy. Tissue micro-arrays (TMA) were composed with both prostate non-tumour (PNT) and PCa tissue and subsequently processed for immunohistochemistry (IHC). The IHC panel included markers for cancer activated fibroblasts (CAFs), blood vessels and steroid hormone receptors ((SHR): androgen receptor (AR), progesterone receptor (PR) and estrogen receptor (ER)). Stained slides were digitalised, selectively annotated and analysed for percentage of marker expression with standardized and validated image analysis algorithms. A univariable analysis identified several TME markers with significant impact on CR: expression of CD31 (vascular marker) in PNT stroma, expression of alpha smooth muscle actin (αSMA) in PCa stroma, and PR expression ratio between PCa stroma and PNT stroma. A multivariable model, which included CD31 expression (vascular marker) in PNT stroma and PR expression ratio between PCa stroma and PNT stroma, could significantly stratify patients for CLR, with the identification of a low risk and high-risk subgroup. If validated and confirmed in an independent prospective series, this subgroup might have clinical potential for PCa patient stratification.