The Instituto Português de Oncologia Francisco Gentil, also known as the Instituto Português de Oncologia (I.P.O.), Portuguese for Portuguese Oncology Institute, is a state-run cancer hospital and research organization in Portugal. The I.P.O. has autonomous regional branches in Lisbon, Porto and Coimbra..
Transarterial chemoembolization (TACE) is a promising locoregional therapy for unresectable colorectal liver metastases, but patient selection remains challenging. We aimed to develop and validate prognostic radiomics-based machine learning models in a multicenter, prospectively collected drug-eluting microsphere TACE cohort. We retrospectively analyzed 76 patients (176 lesions) from the prospective CIREL registry trial. Radiomic features were extracted from each lesion. We tested three types of imaging markers: general radiomics, intensity-based features, and lesion volume. For each, we derived baseline and delta features, reflecting the difference in feature vector values between baseline and first follow-up. Using a center-based split, we trained genetic/evolutionary machine learning models to predict survival and lesion-level response. The median age of the final study population with baseline imaging was 66 years (IQR, 59–71), with 67.1
Background:Complications following abdominal surgery have a very significant negative impact on the patient and the health care system. Despite the spread of minimally invasive surgery, there is no automated way to use intraoperative video to predict complications. New developments in data storage capacity and artificial intelligence (AI) algorithm creation now allow for this. Objective:This project aims to develop and validate deep learning models for accurately predicting postoperative complications, classified using the Clavien-Dindo scale. A key objective is to build and share an open-source dataset containing both intraoperative video data and postoperative outcomes. Methods:This prospective cohort study will collect data reflecting day-to-day surgical practice from 1200 patients, focusing on patient outcomes and intraoperative video. Data will be collected from patients undergoing minimally invasive appendectomy, cholecystectomy, and colorectal resection in the urgent and elective settings. Each video will be annotated at the temporal and semantic level by the study team. Comprehensive data collection will encompass three domains: (1) preoperative variables, including patient demographics, comorbidities, laboratory values, and imaging findings; (2) intraoperative data featuring complete surgical video recordings from laparoscopic or robotic monitors, procedure duration, surgical approach, intraoperative complications, and surgeon-defined technical factors; and (3) 30-day postoperative outcomes classified using the Clavien-Dindo scale (grades I-V). This dataset will be shared under a noncommercial CC BY-NC-SA use license to promote scientific collaboration and innovation, with complete anonymization including metadata removal and out-of-body image blurring. For analysis, the dataset will be split into training, validation, and testing sets. Deep learning algorithms will be developed through supervised learning methodology using 2 parallel approaches: data-derived predictors using fine-tuned surgical video foundational models based on vision transformer architectures and surgeon-defined predictors based on documented intraoperative strategies. Algorithms will be trained on the training set to predict the Clavien-Dindo postoperative complication grade and categorize postoperative outcomes in minimally invasive abdominal surgery. Model performance will be analyzed through sensitivity, specificity, positive and negative predictive values, and area under the receiver operating characteristic curve on the validation and testing sets. Results:Data collection started in 2024 and is expected to extend throughout 2025. The planned outputs include the publication of a research protocol, main results, and the open-source dataset. Through this initiative, the project seeks to significantly advance the field of AI-assisted surgery, contributing to safer and more effective practice. Conclusions:Through the creation of an open dataset and the development of state-of-the-art deep learning models, this project seeks to transform the current paradigm in minimally invasive surgery. By providing the surgical AI community with robust, real-world data, the project aspires to catalyze innovations that will enhance surgical safety; refine predictive capabilities; and, ultimately, lead to better clinical outcomes.
In an increasingly complex clinical setting, long peripheral catheters (LPC) are rapidly gaining popularity and represent an effective option for the administration of medications and fluids, especially for patients with difficult venous access. However, inconsistencies in the literature, particularly regarding terminology and insertion techniques, have contributed to significant variability in clinical outcomes. To standardize and promote a safer and more effective insertion of these catheters, the Italian Group of Long-Term Venous Access Devices (GAVeCeLT) and the Italian Vascular Access Society (IVAS) have developed a six-step protocol that provides evidence-based recommendations. This insertion bundle-named SILPeC (Safe Insertion of Long Peripheral Catheters-includes (1) pre-insertion assessment of the vein of the upper limbs, (2) insertion of the optimal site selection, (3) appropriate measures of asepsis, (4) ultrasound-guided puncture, (5) safe connection to infusion lines, and (6) proper device stabilization and appropriate protection of the exit site. Integrating the latest scientific evidence and clinical expertise, the SILPeC bundle provides a standardized and reproducible method for placement and maintenance of LPCs. This project complements the existing GAVeCeLT recommendations for other vascular access devices, contributing to safer and more consistent vascular access practices in both hospital and outpatient settings.
Colorectal cancer (CRC) progression is fuelled by immune evasion, yet the underlying molecular mechanisms remain to be fully characterized. CD276 (B7-H3), an immune checkpoint glycoprotein frequently overexpressed in aggressive tumors, is extensively modified by glycosylation, a process known to regulate protein stability, localization, and immune interactions. However, its glycosylation-dependent functions in CRC remain unclear. TCGA Transcriptomic data were analysed to identify glycogene alterations linked to patient prognosis. The O-glycome of advanced CRC and normal mucosa was profiled by mass spectrometry. CD276 expression and glycosylation were examined in primary tumors, lymph nodes, and metastases by immunohistochemistry, proximity ligation assays, and dual immunofluorescence. CRC proteomic datasets from PRIDE (≥ 90 cases) were reanalyzed to map CD276 immature glycosylation across differentiation states. C1GALT1 knockout CRC cell lines were generated with CRISPR-Cas9 to mimic immature glycosylation in tumors, and CD276 was silenced with siRNAs. Immunoprecipitation, lectin blotting, protein stability assays, proliferation, invasion, phosphoproteomics, and T cell co-culture experiments were used to assess functional consequences. Downregulation of B3GNT6 and C1GALT1 or C1GALT1C1 defined an immature O-glycosylation phenotype associated with poor prognosis. Glycomic profiling revealed Tn- and sialyl-Tn(sTn)-enriched glycophenotypes in both epithelial- and mesenchymal-like tumors, with subtype-specific patterns. CD276 colocalized with Tn and sTn, carried immature O-glycans absent from healthy tissues, and was enriched in right-sided and metastatic CRC, correlating with worse survival. PRIDE reanalysis suggested widespread CD276 expression and revealed differentiation-linked glycosylation, which was denser in the IgV and IgC domains of epithelial-like tumors and sparser, membrane-proximal in mesenchymal-like tumors. C1GALT1 knockout in CRC cells enhanced invasion while increasing CD276 stability and transcription, driving its overexpression. Aberrantly glycosylated CD276 promoted proliferation, invasion, kinase-driven signalling, and T cell suppression while driving cytokines toward immunosuppression. TCGA confirmed that high CD276 and low C1GALT1 expression correlated with transcriptional signatures of heightened immune checkpoint activity and T cell exhaustion. Immature CD276 glycosylation promotes CRC aggressiveness and immune escape, representing a candidate prognostic biomarker and therapeutic target. Colorectal cancer (CRC) progression is closely linked to immune evasion, yet the molecular mechanisms underlying this process remain poorly understood. This study identifies CD276 (B7-H3) as a glycosylation-driven regulator of CRC aggressiveness and demonstrates how O-glycosylation remodelling promotes tumor immune escape. These findings establish CD276 as a potential therapeutic target and highlight the role of glycoproteoform-specific immune modulation in cancer progression.
Background: Uterine sarcomas represent a small and heterogeneous subgroup of uterine malignancies (accounting for less than 5%), characterized by high biological aggressiveness, high recurrence rates, and diagnostic complexity; surgical management remains the cornerstone of treatment and, consequently, the primary determinant of patient prognosis. Objective: This review synthesizes current evidence regarding the accurate diagnosis and appropriate surgical management of the main histological subtypes of uterine sarcoma across different stages, within a multidisciplinary therapeutic framework. Methods: A comprehensive narrative review was conducted using recent publications from major biomedical databases, with an emphasis on studies exploring surgical outcomes, molecular profiling, therapeutic strategies, and survival patterns. Results: Leiomyosarcoma and endometrial stromal sarcoma represent more than 80% of histological subtypes, with histological grade being the factor of greatest prognostic significance. Complete disease resection, without tumor fragmentation and with negative surgical margins, is the undisputed standard objective. Variations from the standard treatment—en bloc total hysterectomy with bilateral salpingo-oophorectomy—exist depending on histology and tumor staging. Conclusions: Individualized surgical treatment tailored to the specific histological subtype, combined with multimodal treatment strategies based on accurate tumor staging, molecular characterization, and recurrence patterns, is essential to improve survival. Such management should be conducted in referral centers with expertise in treating these rare and fearsome malignancies.
