The Open University’s first one day symposium on treatment-emergent neuroendocrine prostate cancer

The Open University's first one-day symposium on treatment-emergent neuroendocrine prostate cancer attracted world-leading figures, early career researchers and industry colleagues. The symposium proved insightful into the ‘real-world’ impact and current problems faced in the diagnosis and treatment of neuroendocrine prostate cancer. It was important for this meeting to take place as the incidence of neuroendocrine prostate cancer is increasing due to the widespread use of next-generation androgen deprivation drugs. The symposium discussions proposed new molecularly driven deadlines to accelerate research and improved the treatment of this deadly and poorly recognized malignancy

iNKT Cells Control Mouse Spontaneous Carcinoma Independently of Tumor-Specific Cytotoxic T Cells

CD1d-restricted invariant NKT (iNKT) cells are a subset of T lymphocytes endowed with innate effector functions that aid in the establishment of adaptive T and B cell immune responses. iNKT cells have been shown to play a spontaneous protective role against experimental tumors. Yet, the interplay between iNKT and tumor-specific T cells in cancer immune surveillance/editing has never been addressed. The transgenic adenocarcinoma of the mouse prostate (TRAMP) is a realistic model of spontaneous oncogenesis, in which the tumor-specific cytotoxic T cell (CTL) response undergoes full tolerance upon disease progression.We report here that lack of iNKT cells in TRAMP mice resulted in the appearance of more precocious and aggressive tumors that significantly reduced animal survival. TRAMP mice bearing or lacking iNKT cells responded similarly to a tumor-specific vaccination and developed tolerance to a tumor-associated antigen at comparable rate.Hence, our data argue for a critical role of iNKT cells in the immune surveillance of carcinoma that is independent of tumor-specific CTL

The evolutionarily conserved long non‐coding RNA <i>LINC00261</i> drives neuroendocrine prostate cancer proliferation and metastasis <i>via</i> distinct nuclear and cytoplasmic mechanisms

Metastatic neuroendocrine prostate cancer (NEPC) is a highly aggressive disease, whose incidence is rising. Long noncoding RNAs (lncRNAs) represent a large family of disease- and tissue-specific transcripts, most of which are still functionally uncharacterized. Thus, we set out to identify the highly conserved lncRNAs that play a central role in NEPC pathogenesis. To this end, we performed transcriptomic analyses of donor-matched patient-derived xenograft models (PDXs) with immunohistologic features of prostate adenocarcinoma (AR+/PSA+) or NEPC (AR-/SYN+/CHGA+ ) and through differential expression analyses identified lncRNAs that were upregulated upon neuroendocrine transdifferentiation. These genes were prioritized for functional assessment based on the level of conservation in vertebrates. Here, LINC00261 emerged as the top gene with over 3229-fold upregulation in NEPC. Consistently, LINC00261 expression was significantly upregulated in NEPC specimens in multiple patient cohorts. Knockdown of LINC00261 in PC-3 cells dramatically attenuated its proliferative and metastatic abilities, which are explained by parallel downregulation of CBX2 and FOXA2 through distinct molecular mechanisms. In the cell cytoplasm, LINC00261 binds to and sequesters miR-8485 from targeting the CBX2 mRNA, while inside the nucleus, LINC00261 functions as a transcriptional scaffold to induce SMAD-driven expression of the FOXA2 gene. For the first time, these results demonstrate hyperactivation of the LINC00261-CBX2-FOXA2 axes in NEPC to drive proliferation and metastasis, and that LINC00261 may be utilized as a therapeutic target and a biomarker for this incurable disease

Frenemies in the Microenvironment: Harnessing Mast Cells for Cancer Immunotherapy

Tumor development, progression, and resistance to therapies are influenced by the interactions between tumor cells and the surrounding microenvironment, comprising fibroblasts, immune cells, and extracellular matrix proteins. In this context, mast cells (MCs) have recently emerged as important players. Yet, their role is still controversial, as MCs can exert pro- or anti-tumor functions in different tumor types depending on their location within or around the tumor mass and their interaction with other components of the tumor microenvironment. In this review, we describe the main aspects of MC biology and the different contribution of MCs in promoting or inhibiting cancer growth. We then discuss possible therapeutic strategies aimed at targeting MCs for cancer immunotherapy, which include: (1) targeting c-Kit signaling; (2) stabilizing MC degranulation; (3) triggering activating/inhibiting receptors; (4) modulating MC recruitment; (5) harnessing MC mediators; (6) adoptive transferring of MCs. Such strategies should aim to either restrain or sustain MC activity according to specific contexts. Further investigation would allow us to better dissect the multifaceted roles of MCs in cancer and tailor novel approaches for an “MC-guided” personalized medicine to be used in combination with conventional anti-cancer therapies

Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments

Between January and October of 2020, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has infected more than 34 million persons in a worldwide pandemic leading to over one million deaths worldwide (data from the Johns Hopkins University). Since the virus begun to spread, emergency departments were busy with COVID-19 patients for whom a quick decision regarding in- or outpatient care was required. The virus can cause characteristic abnormalities in chest radiographs (CXR), but, due to the low sensitivity of CXR, additional variables and criteria are needed to accurately predict risk. Here, we describe a computerized system primarily aimed at extracting the most relevant radiological, clinical, and laboratory variables for improving patient risk prediction, and secondarily at presenting an explainable machine learning system, which may provide simple decision criteria to be used by clinicians as a support for assessing patient risk. To achieve robust and reliable variable selection, Boruta and Random Forest (RF) are combined in a 10-fold cross-validation scheme to produce a variable importance estimate not biased by the presence of surrogates. The most important variables are then selected to train a RF classifier, whose rules may be extracted, simplified, and pruned to finally build an associative tree, particularly appealing for its simplicity. Results show that the radiological score automatically computed through a neural network is highly correlated with the score computed by radiologists, and that laboratory variables, together with the number of comorbidities, aid risk prediction. The prediction performance of our approach was compared to that that of generalized linear models and shown to be effective and robust. The proposed machine learning-based computational system can be easily deployed and used in emergency departments for rapid and accurate risk prediction in COVID-19 patients

Macrophages Impair TLR9 Agonist Antitumor Activity through Interacting with the Anti-PD-1 Antibody Fc Domain

Background. A combination of TLR9 agonists and an anti-PD-1 antibody has been reported to be effective in immunocompetent mice but the role of innate immunity has not yet been completely elucidated. Therefore, we investigated the contribution of the innate immune system to this combinatorial immunotherapeutic regimens using an immunodeficient mouse model in which the effector functions of innate immunity can clearly emerge without any interference from T lymphocytes. Methods. Athymic mice xenografted with IGROV-1 human ovarian cells, reported to be sensitive to TLR9 agonist therapy, were treated with cytosine–guanine (CpG)-oligodeoxynucleotides (ODNs), an anti-PD-1 antibody or their combination. Results. We found that PD-1 blockade dampened CpG-ODN antitumor activity. In vitro studies indicated that the interaction between the anti-PD-1 antibody fragment crystallizable (Fc) domain and macrophage Fc receptors caused these immune cells to acquire an immunoregulatory phenotype, contributing to a decrease in the efficacy of CpG-ODNs. Accordingly, in vivo macrophage depletion abrogated the detrimental effect exerted by the anti-PD-1 antibody. Conclusion. Our data suggest that if TLR signaling is active in macrophages, coadministration of an anti-PD-1 antibody can reprogram these immune cells towards a polarization state able to negatively affect the immune response and eventually promote tumor growth

Survival of TRAMP mice lacking iNKT cells is reduced.

<p>Kaplan-Maier plot reporting the survival curves of groups of male TRAMP (black squares; n = 21) and TRAMPJα18^−/− mice (black circles; n = 21). Animals were examined twice a week and euthanized when signs of bulky prostate tumor and/or distress were manifest. At necropsy, the anatomy and histology of the UGA was analyzed as indicated in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0008646#s2" target="_blank">Material and Methods</a> section. Animals were attributed a disease score≥4. Statistical comparison (Log-Rank test) between the survival curves: p<0.0001.</p