Benchmarking and improving the performance of variant-calling pipelines with RecallME.

MOTIVATION: The steady increment of Whole Genome/Exome sequencing and the development of novel Next Generation Sequencing-based gene panels requires continuous testing and validation of variant calling (VC) pipelines and the detection of sequencing-related issues to be maintained up-to-date and feasible for the clinical settings. State of the art tools are reliable when used to compute standard performance metrics. However, the need for an automated software to discriminate between bioinformatic and sequencing issues and to optimize VC parameters remains unmet. RESULTS: The aim of the current work is to present RecallME, a bioinformatic suite that tracks down difficult-to-detect variants as insertions and deletions in highly repetitive regions, thus providing the maximum reachable recall for both single nucleotide variants and small insertion and deletions and to precisely guide the user in the pipeline optimization process. AVAILABILITY AND IMPLEMENTATION: Source code is freely available under MIT license at https://github.com/mazzalab-ieo/recallme. RecallME web application is available at https://translational-oncology-lab.shinyapps.io/recallme/. To use RecallME, users must obtain a license for ANNOVAR by themselves.

Circulating extracellular vesicles are monitoring biomarkers of anti-PD1 response and enhancer of tumor progression and immunosuppression in metastatic melanoma.

BACKGROUND: Clinical drawback in checkpoint inhibitors immunotherapy (ICI) of metastatic melanoma (MM) is monitoring clinical benefit. Soluble forms of PD1(sPD1) and PD-L1(sPD-L1) and extracellular vesicles (EVs) expressing PD1 and PD-L1 have recently emerged as predictive biomarkers of response. As factors released in the blood, EVs and soluble forms could be relevant in monitoring treatment efficacy and adaptive resistance to ICI. METHODS: We used pre-therapy plasma samples of 110 MM patients and longitudinal samples of 46 patients. Elisa assay and flow cytometry (FCM) were used to measure sPD-L1 and sPD1 concentrations and the percentage of PD1+ EVs and PD-L1+ EVs, released from tumor and immune cells in patients subsets. Transwell assays were conducted to investigate the impact of EVs of each patient subset on MM cells invasion and interaction between tumor cells and macrophages or dendritic cells. Viability assays were performed to assess EVs effect on MM cells and organoids sensitivity to anti-PD1. FCM was used to investigate immunosuppressive markers in EVs and immune cells. RESULTS: The concentrations of sPD1 and sPD-L1 in pre-treatment and longitudinal samples did not correlate with anti-PD1 response, instead only tumor-derived PD1+ EVs decreased in long responders while increased during disease progression in responders. Notably, we observed reduction of T cell derived EVs expressing LAG3+ and PD1+ in long responders and their increase in responders experiencing progression. By investigating the impact of EVs on disease progression, we found that those isolated from non-responders and from patients with progression disease accelerated tumor cells invasiveness and migration towards macrophages, while EVs of long responders reduced the metastatic potential of MM cells and neo-angiogenesis. Additionally, the EVs of non-responders and of progression disease patients subset reduced the sensitivity of MM cells and organoids of responder to anti-PD1 and the recruitment of dendritic cells, while the EVs of progression disease subset skewed macrophages to express higher level of PDL-1. CONCLUSION: Collectively, we suggest that the detection of tumor-derived PD1 + EVs may represent a useful tool for monitoring the response to anti-PD1 and a role for EVs shed by tumor and immune cells in promoting tumor progression and immune dysfunction.

The role of unpaired image-to-image translation for stain color normalization in colorectal cancer histology classification.

BACKGROUND: Histological assessment of colorectal cancer (CRC) tissue is a crucial and demanding task for pathologists. Unfortunately, manual annotation by trained specialists is a burdensome operation, which suffers from problems like intra- and inter-pathologist variability. Computational models are revolutionizing the Digital Pathology field, offering reliable and fast approaches for challenges like tissue segmentation and classification. With this respect, an important obstacle to overcome consists in stain color variations among different laboratories, which can decrease the performance of classifiers. In this work, we investigated the role of Unpaired Image-to-Image Translation (UI2IT) models for stain color normalization in CRC histology and compared to classical normalization techniques for Hematoxylin-Eosin (H&E) images. METHODS: Five Deep Learning normalization models based on Generative Adversarial Networks (GANs) belonging to the UI2IT paradigm have been thoroughly compared to realize a robust stain color normalization pipeline. To avoid the need for training a style transfer GAN between each pair of data domains, in this paper we introduce the concept of training by exploiting a meta-domain, which contains data coming from a wide variety of laboratories. The proposed framework enables a huge saving in terms of training time, by allowing to train a single image normalization model for a target laboratory. To prove the applicability of the proposed workflow in the clinical practice, we conceived a novel perceptive quality measure, which we defined as Pathologist Perceptive Quality (PPQ). The second stage involved the classification of tissue types in CRC histology, where deep features extracted from Convolutional Neural Networks have been exploited to realize a Computer-Aided Diagnosis system based on a Support Vector Machine (SVM). To prove the reliability of the system on new data, an external validation set composed of N = 15,857 tiles has been collected at IRCCS Istituto Tumori "Giovanni Paolo II". RESULTS: The exploitation of a meta-domain consented to train normalization models that allowed achieving better classification results than normalization models explicitly trained on the source domain. PPQ metric has been found correlated to quality of distributions (Fréchet Inception Distance - FID) and to similarity of the transformed image to the original one (Learned Perceptual Image Patch Similarity - LPIPS), thus showing that GAN quality measures introduced in natural image processing tasks can be linked to pathologist evaluation of H&E images. Furthermore, FID has been found correlated to accuracies of the downstream classifiers. The SVM trained on DenseNet201 features allowed to obtain the highest classification results in all configurations. The normalization method based on the fast variant of CUT (Contrastive Unpaired Translation), FastCUT, trained with the meta-domain paradigm, allowed to achieve the best classification result for the downstream task and, correspondingly, showed the highest FID on the classification dataset. CONCLUSIONS: Stain color normalization is a difficult but fundamental problem in the histopathological setting. Several measures should be considered for properly assessing normalization methods, so that they can be introduced in the clinical practice. UI2IT frameworks offer a powerful and effective way to perform the normalization process, providing realistic images with proper colorization, unlike traditional normalization methods that introduce color artifacts. By adopting the proposed meta-domain framework, the training time can be reduced, and the accuracy of downstream classifiers can be increased.

Tumor Cellularity Assessment of Breast Histopathological Slides via Instance Segmentation and Pathomic Features Explainability.

The segmentation and classification of cell nuclei are pivotal steps in the pipelines for the analysis of bioimages. Deep learning (DL) approaches are leading the digital pathology field in the context of nuclei detection and classification. Nevertheless, the features that are exploited by DL models to make their predictions are difficult to interpret, hindering the deployment of such methods in clinical practice. On the other hand, pathomic features can be linked to an easier description of the characteristics exploited by the classifiers for making the final predictions. Thus, in this work, we developed an explainable computer-aided diagnosis (CAD) system that can be used to support pathologists in the evaluation of tumor cellularity in breast histopathological slides. In particular, we compared an end-to-end DL approach that exploits the Mask R-CNN instance segmentation architecture with a two steps pipeline, where the features are extracted while considering the morphological and textural characteristics of the cell nuclei. Classifiers that are based on support vector machines and artificial neural networks are trained on top of these features in order to discriminate between tumor and non-tumor nuclei. Afterwards, the SHAP (Shapley additive explanations) explainable artificial intelligence technique was employed to perform a feature importance analysis, which led to an understanding of the features processed by the machine learning models for making their decisions. An expert pathologist validated the employed feature set, corroborating the clinical usability of the model. Even though the models resulting from the two-stage pipeline are slightly less accurate than those of the end-to-end approach, the interpretability of their features is clearer and may help build trust for pathologists to adopt artificial intelligence-based CAD systems in their clinical workflow. To further show the validity of the proposed approach, it has been tested on an external validation dataset, which was collected from IRCCS Istituto Tumori "Giovanni Paolo II" and made publicly available to ease research concerning the quantification of tumor cellularity.

miRNA deregulation and relationship with metabolic parameters after Mediterranean dietary intervention in BRCA-mutated women.

Background: Breast cancer onset is determined by a genetics-environment interaction. BRCA1/2 gene alterations are often genetically shared in familial context, but also food intake and hormonal assessment seem to influence the lifetime risk of developing this neoplasia. We previously showed the relationship between a six-months Mediterranean dietary intervention and insulin, glucose and estradiol levels in BRCA1/2 carrier subjects. The aim of the present study was to evidence the eventual influence of this dietary intervention on the relationship between circulating miRNA expression and metabolic parameters in presence of BRCA1/2 loss of function variants. Methods: Plasma samples of BRCA-women have been collected at the baseline and at the end of the dietary intervention. Moreover, subjects have been randomized in two groups: dietary intervention and placebo. miRNA profiling and subsequent ddPCR validation have been performed in all the subjects at both time points. Results: ddPCR analysis confirmed that five (miR-185-5p, miR-498, miR-3910, miR-4423 and miR-4445) of seven miRNAs, deregulated in the training cohort, were significantly up-regulated in subjects after dietary intervention compared with the baseline measurement. Interestingly, when we focused on variation of miRNA levels in the two timepoints, it could be observed that miR-4423, miR-4445 and miR-3910 expressions are positively correlated with variation in vitaminD level; whilst miR-185-5p difference in expression is related to HDL cholesterol variation. Conclusions: We highlighted the synergistic effect of a healthy lifestyle and epigenetic regulation in BC through the modulation of specific miRNAs. Different miRNAs have been reported involved in the tumor onset acting as tumor suppressors by targeting tumor-associated genes that are often downregulated.

Remote vs in-person BRCA1/2 non-carriers test disclosure: patients' choice during Covid-19 pandemic restriction.

During Covid-19 pandemic most hospitals have restricted in-person delivery of non-essential healthcare services, including genetic testing delivery, to slow the spread of the virus. Our Onco-Genetic Service also faced this challenging period and had to re-organize its clinical practice with the use of tele-health. Aim of the present paper is to understand whether and how Covid-19-related changes in medical practice influenced patients' satisfaction about the health service provided. 125 BRCA1/2 non carriers (109/125, 87.2% female and 16/125, 12.8% male) in Istituto Tumori "Giovanni Paolo II" of Bari were enrolled. All participants were asked to choose whether they prefer in-person or remote post-test counselling session. Basing on patients' choice, two groups of subjects were composed. One week after the post-test counselling session, participants were phone called and asked to complete: a socio-demographic form, a brief structured interview about their Covid-19 related worries and their satisfaction with the health service provided, Hospital Anxiety and Depression Scale and Fear of Covid-19 scale. Qualitative information about patients' choice were also collected. No significant difference about patients' satisfaction with the health service provided emerged between groups. Patients who preferred remote post-test counselling had higher anxiety, worries and fear-of Covid-19 than the others. All remote-counselling subjects preferred tele-genetics because of Covid-19 security, would choose it again and would recommend it to others. Cancer tele-genetics offers good guarantees of comfort and efficacy, but patients' choices are related to personal and psychological variables. The use of tele-genetics has to be a patient's choice.

Consolidative thoracic radiation therapy for extensive-stage small cell lung cancer in the era of first-line chemoimmunotherapy: preclinical data and a retrospective study in Southern Italy.

Background: Consolidative thoracic radiotherapy (TRT) has been commonly used in the management of extensive-stage small cell lung cancer (ES-SCLC). Nevertheless, phase III trials exploring first-line chemoimmunotherapy have excluded this treatment approach. However, there is a strong biological rationale to support the use of radiotherapy (RT) as a boost to sustain anti-tumor immune responses. Currently, the benefit of TRT after chemoimmunotherapy remains unclear. The present report describes the real-world experiences of 120 patients with ES-SCLC treated with different chemoimmunotherapy combinations. Preclinical data supporting the hypothesis of anti-tumor immune responses induced by RT are also presented. Methods: A total of 120 ES-SCLC patients treated with chemoimmunotherapy since 2019 in the South of Italy were retrospectively analyzed. None of the patients included in the analysis experienced disease progression after undergoing first-line chemoimmunotherapy. Of these, 59 patients underwent TRT after a multidisciplinary decision by the treatment team. Patient characteristics, chemoimmunotherapy schedule, and timing of TRT onset were assessed. Safety served as the primary endpoint, while efficacy measured in terms of overall survival (OS) and progression-free survival (PFS) was used as the secondary endpoint. Immune pathway activation induced by RT in SCLC cells was explored to investigate the biological rationale for combining RT and immunotherapy. Results: Preclinical data supported the activation of innate immune pathways, including the STimulator of INterferon pathway (STING), gamma-interferon-inducible protein (IFI-16), and mitochondrial antiviral-signaling protein (MAVS) related to DNA and RNA release. Clinical data showed that TRT was associated with a good safety profile. Of the 59 patients treated with TRT, only 10% experienced radiation toxicity, while no ≥ G3 radiation-induced adverse events occurred. The median time for TRT onset after cycles of chemoimmunotherapy was 62 days. Total radiation dose and fraction dose of TRT include from 30 Gy in 10 fractions, up to definitive dose in selected patients. Consolidative TRT was associated with a significantly longer PFS than systemic therapy alone (one-year PFS of 61% vs. 31%, p<0.001), with a trend toward improved OS (one-year OS of 80% vs. 61%, p=0.027). Conclusion: Multi-center data from establishments in the South of Italy provide a general confidence in using TRT as a consolidative strategy after chemoimmunotherapy. Considering the limits of a restrospective analysis, these preliminary results support the feasibility of the approach and encourage a prospective evaluation.

NDG-CAM: Nuclei Detection in Histopathology Images with Semantic Segmentation Networks and Grad-CAM.

Nuclei identification is a fundamental task in many areas of biomedical image analysis related to computational pathology applications. Nowadays, deep learning is the primary approach by which to segment the nuclei, but accuracy is closely linked to the amount of histological ground truth data for training. In addition, it is known that most of the hematoxylin and eosin (H&E)-stained microscopy nuclei images contain complex and irregular visual characteristics. Moreover, conventional semantic segmentation architectures grounded on convolutional neural networks (CNNs) are unable to recognize distinct overlapping and clustered nuclei. To overcome these problems, we present an innovative method based on gradient-weighted class activation mapping (Grad-CAM) saliency maps for image segmentation. The proposed solution is comprised of two steps. The first is the semantic segmentation obtained by the use of a CNN; then, the detection step is based on the calculation of local maxima of the Grad-CAM analysis evaluated on the nucleus class, allowing us to determine the positions of the nuclei centroids. This approach, which we denote as NDG-CAM, has performance in line with state-of-the-art methods, especially in isolating the different nuclei instances, and can be generalized for different organs and tissues. Experimental results demonstrated a precision of 0.833, recall of 0.815 and a Dice coefficient of 0.824 on the publicly available validation set. When used in combined mode with instance segmentation architectures such as Mask R-CNN, the method manages to surpass state-of-the-art approaches, with precision of 0.838, recall of 0.934 and a Dice coefficient of 0.884. Furthermore, performance on the external, locally collected validation set, with a Dice coefficient of 0.914 for the combined model, shows the generalization capability of the implemented pipeline, which has the ability to detect nuclei not only related to tumor or normal epithelium but also to other cytotypes.

Communications Is Time for Care: An Italian Monocentric Survey on Human Papillomavirus (HPV) Risk Information as Part of Cervical Cancer Screening.

Human papilloma virus (HPV) infection could be considered a social disease, both for its high incidence, especially in younger subjects, and for the risk of neoplastic evolution linked to viral infection. Therefore, the National Health System, in collaboration with the state, must help women to understand the oncological risk of HPV and suitable methods of prevention. We conducted an Italian monocentric survey on HPV risk information as part of cervical cancer screening. An anonymous questionnaire was administered to 200 women with high-risk positive HPV and low-grade cervical lesions during second-level cervical cancer screening at the Gynecology and Obstetrics Unit of the "San Paolo" Hospital. From this survey, the need to improve communication for patients has emerged, as currently it is not exhaustive. In response to this need, organizational changes have been implemented to centralize the moment of counseling in the second levels of screening and to improve the training of health workers in level I as well as family doctors. In addition, psychological support was also proposed to patients who requested it, as was the dissemination of material such as that produced by GISCI (Italian Cervico-Carcinoma Screening Group) and updated in May 2018, which provides 100 answers to questions on HPV in order to achieve effective and comprehensive communication. This investigation requires further development, and the expansion of this investigation to the multicenter level is already underway. Therefore, this survey will represent a cornerstone for further discussion on the topic considering the necessity of appropriate communication in the oncological context.

NR1H3 (LXRα) is associated with pro-inflammatory macrophages, predicts survival and suggests potential therapeutic rationales in diffuse large b-cell lymphoma.

The role of macrophages (Mo) and their prognostic impact in diffuse large B-cell lymphomas (DLBCL) remain controversial. By regulating the lipid metabolism, Liver-X-Receptors (LXRs) control Mo polarization/inflammatory response, and their pharmacological modulation is under clinical investigation to treat human cancers, including lymphomas. Herein, we surveyed the role of LXRs in DLBCL for prognostic purposes. Comparing bulk tumors with purified malignant and normal B-cells, we found an intriguing association of NR1H3, encoding for the LXR-α isoform, with the tumor microenvironment (TME). CIBERSORTx-based purification on large DLBCL datasets revealed a high expression of the receptor transcript in M1-like pro-inflammatory Mo. By determining an expression cut-off of NR1H3, we used digital measurement to validate its prognostic capacity on two large independent on-trial and real-world cohorts. Independently of classical prognosticators, NR1H3high patients displayed longer survival compared with NR1H3low cases and a high-resolution Mo GEP dissection suggested a remarkable transcriptional divergence between subgroups. Overall, our findings indicate NR1H3 as a Mo-related biomarker identifying patients at higher risk and prompt future preclinical studies investigating its mouldability for therapeutic purposes.

Multiple Genetic Alterations as Resistance Mechanism during Second-Line Lorlatinib for Advanced ALK-Rearranged Lung Adenocarcinoma: A Case Report.

Second and third-generation ALK-TKI inhibitors have showed better activity and have replaced crizotinib in most of cases of advanced ALK-rearranged lung adenocarcinoma. The emergence of resistance adversely affects also the activity of these newer drugs; in particular, lorlatinib often shows multiple and complex resistance mechanisms. The case reported here highlights the importance of reassessing the biomolecular profile during the disease course, both by tissutal and liquid biopsy, with the aim of improving the knowledge of these resistance mechanisms, and so identifying new drugs or sequences able to optimize the management of these patients.

Circulating extracellular vesicles expressing PD1 and PD-L1 predict response and mediate resistance to checkpoint inhibitors immunotherapy in metastatic melanoma.

BACKGROUND: The immunotherapy with immune checkpoints inhibitors (ICI) has changed the life expectancy in metastatic melanoma (MM) patients. Nevertheless, several patients do not respond hence, the identification and validation of novel biomarkers of response to ICI is of crucial importance. Circulating extracellular vesicles (EVs) such as PD-L1+ EV mediate resistance to anti-PD1, instead the role of PD1+ EV is not fully understood. METHODS: We isolated the circulating EVs from the plasma of an observational cohort study of 71 metastatic melanoma patients and correlated the amount of PD-L1+ EVs and PD1+ EVs with the response to ICI. The analysis was performed according to the origin of EVs from the tumor and the immune cells. Subsequently, we analysed the data in a validation cohort of 22 MM patients to assess the reliability of identified EV-based biomarkers. Additionally we assessed the involvement of PD1+ EVs in the seizure of nivolumab and in the perturbation of immune cells-mediated killing of melanoma spheroids. RESULTS: The level of PD-L1+ EVs released from melanoma and CD8+ T cells and that of PD1+ EVs irrespective of the cellular origin were higher in non-responders. The Kaplan-Meier curves indicated that higher levels of PD1+ EVs were significantly correlated with poorer progression-free survival (PFS) and overall survival (OS). Significant correlations were found for PD-L1+ EVs only when released from melanoma and T cells. The multivariate analysis showed that high level of PD1+ EVs, from T cells and B cells, and high level of PD-L1+ EVs from melanoma cells, are independent biomarkers of response. The reliability of PD-L1+ EVs from melanoma and PD1+ EVs from T cells in predicting PFS was confirmed in the validation cohort through the univariate Cox-hazard regression analysis. Moreover we discovered that the circulating EVs captured nivolumab and reduced the T cells trafficking and tumor spheroids killing. CONCLUSION: Our study identified circulating PD1+ EVs as driver of resistance to anti-PD1, and highlighted that the analysis of single EV population by liquid biopsy is a promising tool to stratify MM patients for immunotherapy.

The ERRα-VDR axis promotes calcitriol degradation and estrogen signaling in breast cancer cells, while VDR-CYP24A1-ERRα overexpression correlates with poor prognosis in patients with basal-like breast cancer.

Vitamin D is used to reduce cancer risk and improve the outcome of cancer patients, but the vitamin D receptor (VDR; also known as the calcitriol receptor) pathway needs to be functionally intact to ensure the biological effects of circulating calcitriol, the active form of vitamin D. Besides estrogen receptor alpha (ERα), estrogen-related receptor alpha (ERRα) has also been shown to interfere with the VDR pathway, but its role in the antitumor and transactivation activity of calcitriol is completely unknown in breast cancer (BC). We observed that ERRα functionally supported the proliferation of BC cell lines and acted as a calcitriol-induced regulator of VDR. As such, ERRα deregulated the calcitriol-VDR transcription by enhancing the expression of CYP24A1 as well as of both ERα and aromatase (CYP19A1) in calcitriol-treated cells. ERRα knockdown limited the effect of calcitriol by reducing calcitriol-induced G0/G1 phase cell cycle arrest and by affecting the expression of cyclin D1 and p21/Waf. The interactome analysis suggested that Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-α (PGC-1α) and Proline-, glutamic acid-, and leucine-rich protein 1 (PELP1) are key players in the genomic actions of the calcitriol-VDR-ERRα axis. Evaluation of patient outcomes in The Cancer Genome Atlas (TCGA) dataset showed the translational significance of the biological effects of the VDR-ERRα axis, highlighting that VDR, CYP24A1, and ERRα overexpression correlates with poor prognosis in basal-like BC.

A Promising Role of TGF-ß Pathway in Response to Regorafenib in Metastatic Colorectal Cancer: A Case Report.

Colorectal cancer (CRC) is one of the most common cancer types around the world. The prognosis of patients with advanced diseases is still poor in spite of currently available therapeutic options. Regorafenib is an oral tyrosine kinase inhibitor (TKI) approved to treat refractory metastatic colorectal cancer (mCRC). We investigated Somatic mutations in several genes involved in immunological response and cancer progression in both long/short responder mCRC patients who underwent third-line therapy with regorafenib to identify predictive biomarkers of response using Ion Torrent PGM sequencing and bioinformatic tools. We found Somatic mutations in TGFBR1, TGFBR2, and TGFBR3 genes in primary tumor and metastases samples of long-responder patients. Furthermore, our bioinformatic results show that they were mainly enriched in immune response, cell junction, and cell adhesion in long responder patients, particularly in primary tumor and metastatic sites. These data suggest that the TGF-b pattern could be the leading actor of a prolonged response to this drug.

A New Score to Assess the Perioperative Period of the Cancer Patient Undergoing Non-Palliative Elective Surgery: A Retrospective Evaluation of a Case Report by PERIDIA Score.

The complexity of cancer patients and the use of advanced and demolitive surgical techniques frequently need post-operatory ICU hospitalization. To increase safety and to select the best medical strategies for the patient, a multidisciplinary team has performed a new peri-operatory assessment, arising from evidence-based literature data. Verifying that most of the cancer patients, admitted to the intensive care unit, undergo major surgery with localizations in the supramesocolic thoraco-abdominal area, the team focused the attention on supramesocolic peridiaphragmatic cancer surgery. Some scores already in use in clinical practice were selected for the peri-operatory evaluation process. None of them evaluate parameters relating to the entire peri-operative period. In detail, only a few study models were found that concern the assessment of the intra-operative period. Therefore, we wanted to see if using a mix of validated scores, it was possible to build a single evaluation score (named PERIDIAphragmatic surgery score or PERIDIA-score) for the entire peri-operative period that could be obtained at the end of the patient's hospitalization period in post-operative ICU. The main property sought with the creation of the PERIDIA-score is the proportionality between the score and the incidence of injuries, deaths, and the length of stay in the ward. This property could organize a tailor-made therapeutic path for the patient based on pre-rehabilitation, physiotherapy, activation of social assistance services, targeted counseling, collaborations with the continuity of care network. Furthermore, if the pre-operative score is particularly high, it could suggest different or less invasive therapeutic options, and if the intra-operative score is particularly high, it could suggest a prolongation of hospitalization in ICU. The retrospective prospective study conducted on 83 patients is still ongoing. The first data would seem to prove an increase of clinical complications in patients who were assigned a one-third score with respect to the maximum (16/48) of PERIDIA-score. Moreover, patients with a 10/16 score within each phase of the evaluation (pre, peri, and post) more frequently develop injuries. In the light of these evidence, the 29-point score assigned to our patient can be considered as predictive for the subsequent critical and fatal complications the patient faced up.

Spectrum of Germline Pathogenic Variants in BRCA1/2 Genes in the Apulian Southern Italy Population: Geographic Distribution and Evidence for Targeted Genetic Testing.

BRCA1/2-associated hereditary breast and ovarian cancer is the most common form of hereditary breast and ovarian cancer and occurs in all ethnicities and racial populations. Different BRCA1/BRCA2 pathogenic variants (PVs) have been reported with a wide variety among populations. In this study, we retrospectively analyzed prevalence and geographic distribution of pathogenic germline BRCA1/2 variants in families from Apulia in southern Italy and evaluated the genotype-phenotype correlations. Data were collected from Oncogenetic Services present in Apulian hospitals and a shared database was built containing Apulian native probands (n = 2026) that had undergone genetic testing from 2004 to 2019. PVs were detected in 499 of 2026 (24.6%) probands and 68.5% of them (342 of 499) were in the BRCA1 gene. We found 65 different PVs in BRCA1 and 46 in BRCA2. There were 10 most recurrent PVs and their geographical distribution appears to be significantly specific for each province. We have assumed that these PVs are related to the historical and geopolitical changes that occurred in Apulia over time and/or to a "founder effect". Broader knowledge of BRCA1/2 prevalence and recurring PVs in specific geographic areas could help establish more flexible genetic testing strategies that may enhance our ability to detect high-risk subjects.

Weighted Gene Co-Expression Network Analysis Combined with Machine Learning Validation to Identify Key Modules and Hub Genes Associated with SARS-CoV-2 Infection.

The coronavirus disease-2019 (COVID-19) pandemic has caused an enormous loss of lives. Various clinical trials of vaccines and drugs are being conducted worldwide; nevertheless, as of today, no effective drug exists for COVID-19. The identification of key genes and pathways in this disease may lead to finding potential drug targets and biomarkers. Here, we applied weighted gene co-expression network analysis and LIME as an explainable artificial intelligence algorithm to comprehensively characterize transcriptional changes in bronchial epithelium cells (primary human lung epithelium (NHBE) and transformed lung alveolar (A549) cells) during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Our study detected a network that significantly correlated to the pathogenicity of COVID-19 infection based on identified hub genes in each cell line separately. The novel hub gene signature that was detected in our study, including PGLYRP4 and HEPHL1, may shed light on the pathogenesis of COVID-19, holding promise for future prognostic and therapeutic approaches. The enrichment analysis of hub genes showed that the most relevant biological process and KEGG pathways were the type I interferon signaling pathway, IL-17 signaling pathway, cytokine-mediated signaling pathway, and defense response to virus categories, all of which play significant roles in restricting viral infection. Moreover, according to the drug-target network, we identified 17 novel FDA-approved candidate drugs, which could potentially be used to treat COVID-19 patients through the regulation of four hub genes of the co-expression network. In conclusion, the aforementioned hub genes might play potential roles in translational medicine and might become promising therapeutic targets. Further in vitro and in vivo experimental studies are needed to evaluate the role of these hub genes in COVID-19.

Prospective Observational COVID-19 Screening and Monitoring of Asymptomatic Cancer Center Health-Care Workers with a Rapid Serological Test.

Health-care workers (HCW) are at high risk for SARS-CoV-2 infection and, if asymptomatic, for transmitting the virus to fragile cancer patients. We monitored all asymptomatic HCWs of a cancer institute (94% of all employees agreed to enter the study) with the rapid serological test, VivaDiagTM, identifying SARS-CoV-2 associated-IgM/IgG. The tests were performed at time 0 (n = 606) and after 14 days (n = 393). Overall, the VivaDiagTM results of nine HCWs (1.5%) were positive, with one confirmed to be SARS-CoV-2-positive after oropharyngeal swab testing by RT-PCR. At time 0, all nine cases showed IgM expression while IgG was detected in only one. After 14 days, IgM persisted in all the cases, while IgG became evident in four. A chemiluminescence immunoassay (CLIA) confirmed IgM positivity in 5/13 VivaDiagTM positive cases and IgG positivity in 4/5 VivaDiagTM positive cases. Our study suggests that the VivaDiagTM test can be of help in identifying SARS-CoV-2 infected people in cohorts of subjects with a high prevalence.

Molecular alterations in basal cell carcinoma subtypes.

A number of genes have been implicated in the pathogenesis of BCC in addition to the Hedgehog pathway, which is known to drive the initiation of this tumour. We performed in-depth analysis of 13 BCC-related genes (CSMD1, CSMD2, DPH3 promoter, PTCH1, SMO, GLI1, NOTCH1, NOTCH2, TP53, ITIH2, DPP10, STEAP4, TERT promoter) in 57 BCC lesions (26 superficial and 31 nodular) from 55 patients and their corresponding blood samples. PTCH1 and TP53 mutations were found in 71.9% and 45.6% of BCCs, respectively. A high mutation rate was also detected in CSMD1 (63.2%), NOTCH1 (43.8%) and DPP10 (35.1%), and frequent non-coding mutations were identified in TERT (57.9%) and DPH3 promoter (49.1%). CSMD1 mutations significantly co-occurred with TP53 changes (p = 0.002). A significant association was observed between the superficial type of BCC and PTCH1 (p = 0.018) and NOTCH1 (p = 0.020) mutations. In addition, PTCH1 mutations were significantly associated with intermittent sun exposure (p = 0.046) and the occurrence of single lesions (p = 0.021), while NOTCH1 mutations were more frequent in BCCs located on the trunk compared to the head/neck and extremities (p = 0.001). In conclusion, we provide further insights into the molecular alterations underlying the tumorigenic mechanism of superficial and nodular BCCs with a view towards novel rationale-based therapeutic strategies.

uPAR+ extracellular vesicles: a robust biomarker of resistance to checkpoint inhibitor immunotherapy in metastatic melanoma patients.

BACKGROUND: Emerging evidence has highlighted the importance of extracellular vesicle (EV)-based biomarkers of resistance to immunotherapy with checkpoint inhibitors in metastatic melanoma. Considering the tumor-promoting implications of urokinase-type plasminogen activator receptor (uPAR) signaling, this study aimed to assess uPAR expression in the plasma-derived EVs of patients with metastatic melanoma to determine its potential correlation with clinical outcomes. METHODS: Blood samples from 71 patients with metastatic melanoma were collected before initiating immunotherapy. Tumor-derived and immune cell-derived EVs were isolated and analyzed to assess the relative percentage of uPAR+ EVs. The associations between uPAR and clinical outcomes, sex, BRAF status, baseline lactate dehydrogenase levels and number of metastatic sites were assessed. RESULTS: Responders had a significantly lower percentage of tumor-derived, dendritic cell (DC)-derived and CD8+ T cell-derived uPAR +EVs at baseline than non-responders. The Kaplan-Meier survival curves for the uPAR+EV quartiles indicated that higher levels of melanoma-derived uPAR+ EVs were strongly correlated with poorer progression-free survival (p<0.0001) and overall survival (p<0.0001). We also found a statistically significant correlation between lower levels of uPAR+ EVs from both CD8+ T cells and DCs and better survival. CONCLUSIONS: Our results indicate that higher levels of tumor-derived, DC-derived and CD8+ T cell-derived uPAR+ EVs in non-responders may represent a new biomarker of innate resistance to immunotherapy with checkpoint inhibitors. Moreover, uPAR+ EVs represent a new potential target for future therapeutic approaches.