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Sökning: WFRF:(Masucci GV)

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  • Andtback, HB, et al. (författare)
  • Sex Differences in Overall Survival and the Effect of Radiotherapy in Merkel Cell Carcinoma-A Retrospective Analysis of a Swedish Cohort
  • 2021
  • Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 13:2
  • Tidskriftsartikel (refereegranskat)abstract
    • Merkel cell carcinoma (MCC) is a rare and aggressive skin cancer where Merkel cell Polyomavirus (MCPyV) contributes to the pathogenesis. In an adjuvant setting, radiotherapy (RT) is believed to give a survival benefit. The prognostic impact of sex related to MCPyV-status and adjuvant RT were analyzed in patients referred to Karolinska University Hospital. Data were collected from 113 patients’ hospital records and MCPyV analyses were made in 54 patients (48%). We found a significantly better overall survival (OS) for women compared to men and a significant difference in OS in patients receiving adjuvant RT. Furthermore, we found that men with virus negative MCC have an increased risk for earlier death (HR 3.6). This indicates that MCPyV positive and negative MCC act as two different diseases, and it might be due to different mechanism in the immune response between male and female patients. This could have significance in tailoring treatment and follow-up in MCC patients in the future.
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  • Cesano, A, et al. (författare)
  • Society for Immunotherapy of Cancer clinical and biomarkers data sharing resource document: Volume II-practical challenges
  • 2020
  • Ingår i: Journal for immunotherapy of cancer. - : BMJ. - 2051-1426. ; 8:2
  • Tidskriftsartikel (refereegranskat)abstract
    • The development of strongly predictive validated biomarkers is essential for the field of immuno-oncology (IO) to advance. The highly complex, multifactorial data sets required to develop these biomarkers necessitate effective, responsible data-sharing efforts in order to maximize the scientific knowledge and utility gained from their collection. While the sharing of clinical- and safety-related trial data has already been streamlined to a large extent, the sharing of biomarker-aimed clinical trial derived data and data sets has been met with a number of hurdles that have impaired the progression of biomarkers from hypothesis to clinical use. These hurdles include technical challenges associated with the infrastructure, technology, workforce, and sustainability required for clinical biomarker data sharing. To provide guidance and assist in the navigation of these challenges, the Society for Immunotherapy of Cancer (SITC) Biomarkers Committee convened to outline the challenges that researchers currently face, both at the conceptual level (Volume I) and at the technical level (Volume II). The committee also suggests possible solutions to these problems in the form of professional standards and harmonized requirements for data sharing, assisting in continued progress toward effective, clinically relevant biomarkers in the IO setting.
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  • Isgro, MA, et al. (författare)
  • Immunotherapy may protect cancer patients from SARS-CoV-2 infection: a single-center retrospective analysis
  • 2021
  • Ingår i: Journal of translational medicine. - : Springer Science and Business Media LLC. - 1479-5876. ; 19:1, s. 132-
  • Tidskriftsartikel (refereegranskat)abstract
    • Coronavirus disease 2019 (COVID-19) global pandemic has created unique challenges to healthcare systems throughout the world. Ensuring subjects’ safety is mandatory especially in oncology, in consideration of cancer patients’ particular frailty. We examined the proportion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) IgM and/or IgG positive subjects in three different groups from Istituto Nazionale Tumori – IRCCS “Fondazione G. Pascale” in Naples (Campania region, Italy): cancer patients treated with Innovative Immunotherapy (Immune Checkpoint Inhibitors, ICIs), cancer patients undergoing standard Chemotherapies (CHTs) and healthcare providers. 9 out of 287 (3.1%) ICIs patients resulted positive, with a significant lower percentage in respect to CHTs patients (39 positive subjects out of 598, 6.5%) (p = 0.04). There was no statistically significant difference between ICIs cohort and healthcare providers, 48 out of 1050 resulting positive (4.6%). Performing a Propensity Score Matching based on gender and tumor stage, the effect of treatment on seropositivity was analyzed through a regression logistic model and the ICIs treatment resulted to be the only protective factor significantly (p = 0.03) associated with positivity (odds ratio—OR: 0.41; 95% confidence interval—CI 0.18–0.91). According to these preliminary data, ICIs would appear to be a protective factor against the onset of COVID-19 infection.
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  • Madonna, G, et al. (författare)
  • Clinical Categorization Algorithm (CLICAL) and Machine Learning Approach (SRF-CLICAL) to Predict Clinical Benefit to Immunotherapy in Metastatic Melanoma Patients: Real-World Evidence from the Istituto Nazionale Tumori IRCCS Fondazione Pascale, Napoli, Italy
  • 2021
  • Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 13:16
  • Tidskriftsartikel (refereegranskat)abstract
    • The real-life application of immune checkpoint inhibitors (ICIs) may yield different outcomes compared to the benefit presented in clinical trials. For this reason, there is a need to define the group of patients that may benefit from treatment. We retrospectively investigated 578 metastatic melanoma patients treated with ICIs at the Istituto Nazionale Tumori IRCCS Fondazione “G. Pascale” of Napoli, Italy (INT-NA). To compare patients’ clinical variables (i.e., age, lactate dehydrogenase (LDH), neutrophil–lymphocyte ratio (NLR), eosinophil, BRAF status, previous treatment) and their predictive and prognostic power in a comprehensive, non-hierarchical manner, a clinical categorization algorithm (CLICAL) was defined and validated by the application of a machine learning algorithm—survival random forest (SRF-CLICAL). The comprehensive analysis of the clinical parameters by log risk-based algorithms resulted in predictive signatures that could identify groups of patients with great benefit or not, regardless of the ICI received. From a real-life retrospective analysis of metastatic melanoma patients, we generated and validated an algorithm based on machine learning that could assist with the clinical decision of whether or not to apply ICI therapy by defining five signatures of predictability with 95% accuracy.
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  • Mlecnik, B, et al. (författare)
  • Clinical Performance of the Consensus Immunoscore in Colon Cancer in the Asian Population from the Multicenter International SITC Study
  • 2022
  • Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 14:18
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: In this study, we evaluated the prognostic value of Immunoscore in patients with stage I–III colon cancer (CC) in the Asian population. These patients were originally included in an international study led by the Society for Immunotherapy of Cancer (SITC) on 2681 patients with AJCC/UICC-TNM stages I–III CC. METHODS: CD3+ and cytotoxic CD8+ T-lymphocyte densities were quantified in the tumor and invasive margin by digital pathology. The association of Immunoscore with prognosis was evaluated for time to recurrence (TTR), disease-free survival (DFS), and overall survival (OS). RESULTS: Immunoscore stratified Asian patients (n = 423) into different risk categories and was not impacted by age. Recurrence-free rates at 3 years were 78.5%, 85.2%, and 98.3% for a Low, Intermediate, and High Immunoscore, respectively (HR[Low-vs-High] = 7.26 (95% CI 1.75−30.19); p = 0.0064). A High Immunoscore showed a significant association with prolonged TTR, OS, and DFS (p < 0.05). In Cox multivariable analysis stratified by center, Immunoscore association with TTR was independent (HR[Low-vs-Int+High] = 2.22 (95% CI 1.10–4.55) p = 0.0269) of the patient’s gender, T-stage, N-stage, sidedness, and MSI status. A significant association of a High Immunoscore with prolonged TTR was also found among MSS (HR[Low-vs-Int+High] = 4.58 (95% CI 2.27−9.23); p ≤ 0.0001), stage II (HR[Low-vs-Int+High] = 2.72 (95% CI 1.35−5.51); p = 0.0052), low-risk stage-II (HR[Low-vs-Int+High] = 2.62 (95% CI 1.21−5.68); p = 0.0146), and high-risk stage II patients (HR[Low-vs-Int+High] = 3.11 (95% CI 1.39−6.91); p = 0.0055). CONCLUSION: A High Immunoscore is significantly associated with the prolonged survival of CC patients within the Asian population.
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