State of the Art and New Trends from the 2022 Gism Annual Meeting

The 2022 Italian Mesenchymal Stem Cell Group (Gruppo Italiano Staminali Mesenchimali, GISM) Annual Meeting took place on 20–21 October 2022 in Turin (Italy), with the support of the University of Turin and the City of Health and Science of Turin. The novelty of this year’s meeting was its articulation, reflecting the new structure of GISM based on six sections: (1) Bringing advanced therapies to the clinic: trends and strategies, (2) GISM Next Generation, (3) New technologies for 3D culture systems, (4) Therapeutic applications of MSC-EVs in veterinary and human medicine, (5) Advancing MSC therapies in veterinary medicine: present challenges and future perspectives, (6) MSCs: a double-edged sword: friend or foe in oncology. National and international speakers presented their scientific works with the aim of promoting an interactive discussion and training for all attendees. The atmosphere was interactive, where ideas and questions between younger researchers and senior mentors were shared in all moments of the congress

Unusual skin toxicity associated with sustained disease response induced by nivolumab in a patient with non-small cell lung cancer

Introduction: Immunotherapy has shown efficacy in the treatment of different malignancies. Nivolumab, an immune checkpoint inhibitor directed against programmed death-1, has been approved for non-small cell lung cancer (NSCLC) in pretreated patients. Although it is generally well-tolerated, immunotherapy may be complicated by a wide range of immune-mediated adverse events. We describe the case of an uncommon skin toxicity arising as alopecia universalis induced by nivolumab in a patient with NSCLC. Case description: A 58-year-old man received nivolumab for metastatic NSCLC after progression to 3 lines of chemotherapy. The treatment was prescribed in June 2016, and induced a rapid and significant disease response. Nivolumab was well-tolerated until May 2017, when partial alopecia at hair and eyelashes appeared. In the next months, alopecia became complete and extended to the whole body surface. The dermatologic picture was compatible with alopecia areata. A topical steroid therapy was attempted, without benefit. The patient refused systemic treatments and is still undergoing nivolumab without new toxicities and with persistent disease response. Conclusions: This case suggests that alopecia areata may be a rare immune-related adverse event of immune checkpoint agents. Its late onset in our patient is uncommon and unexpected, underlining that the risk of nivolumab-induced toxicity is not limited to the beginning of treatment. Despite its rarity, alopecia areata should be considered in the range of adverse events potentially induced by immune checkpoint inhibitors even in the long term. Potential association between toxicity and efficacy of immunotherapy in NSCLC warrants further investigation

Efficacy and safety of immunotherapy in elderly patients with non-small cell lung cancer

OBJECTIVES: Most trials with Immune Checkpoint Inhibitors (ICIs) for Non-Small Cell Lung Cancer (NSCLC) included only small subgroups of patients aged 6565. As NSCLC is often diagnosed in patients aged 6570, real-world data about efficacy and safety of immunotherapy (IO) in elderly patients are essential. MATERIALS AND METHODS: We retrospectively collected data about all patients with advanced NSCLC treated with IO at our Institution between April 2013 and March 2019. The patients were stratified for age as follows: <70 year-old, 70-79 year-old, 6580 year-old. Chi-square test was used to compare qualitative variables. Survival was estimated with Kaplan-Meier method. Log-rank test was used to compare curves. Multivariate analyses were performed with Cox model. RESULTS: We reviewed 290 cases, with a median age of 67 (range: 29-89). Patients aged<70, 70-79 and 6580 year-old were 180, 94 and 16, respectively. Clinical/pathological variables were uniformly distributed across age classes, except for a higher rate of males (p 0.0228) and squamous histology (p 0.0071) in the intermediate class. Response Rate (RR) was similar across age groups (p 0.9470). Median Progression Free Survival (PFS) and Overall Survival (OS) did not differ according to age (p 0.2020 and 0.9144, respectively). Toxicity was comparable across subgroups (p 0.6493). The only variables influencing outcome were performance status (PS) (p\u2009<\u20090.0001 for PFS, p 0.0192 for OS), number of metastatic sites (p 0.0842 for PFS, p 0.0235 for OS) and IO line (p\u2009<\u20090.0001 for both PFS and OS). CONCLUSION: Advanced age was not associated to a reduced efficacy of IO in our case series. Furthermore, no toxicity concern emerged even among the eldest pts. To our opinion, ICIs should be considered irrespective of age, provided an optimal PS at baseline. Of note, IO is often the only therapeutic option applicable to these cases considering the toxicity of chemotherapy

Economic assessment of RFID coupled with open source technologies for wood traceability in Calabria

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Association between Antibiotic-Immunotherapy Exposure Ratio and outcome in metastatic Non Small Cell Lung Cancer

OBJECTIVES: Immunotherapy (IO) is effective in metastatic Non Small Cell Lung Cancer (NSCLC). Gut microbiota has an impact on immunity and its imbalance due to antibiotics may impair the efficacy of IO. We investigated this topic in a case series of NSCLC patients treated with IO. MATERIALS AND METHODS: Data about all metastatic NSCLC patients treated with IO between 04/2013 and 01/2018 were collected. Patients were stratified according to antibiotic use during the Early IO Period (EIOP), and according to the Antibiotic-ImmunotherapyExposure Ratio (AIER) defined as "days of antibiotic/days of IO" during the Whole IO Period (WIOP). Survival was estimated using the Kaplan-Meier method. Log-rank test was used to compare the curves. Multivariate analyses were performed with the Cox model. RESULTS: We analyzed 157 patients. Forty-six patients received antibiotics during the WIOP, 27 patients during the EIOP. No differences in either Progression-Free Survival (PFS) or Overall Survival (OS) were observed according to antibiotic use during the EIOP (p\u2009=\u20090.1772 and p\u2009=\u20090.2492, respectively). Considering the WIOP, median AIER was 4.2%. The patients with a higher AIER had worse PFS (p\u2009<\u20090.0001) and OS (p\u2009=\u20090.0004) than the others. Results were significant also after correction for the IO line (p\u2009=\u20090.0018 for PFS) and performance status (p\u2009<\u20090.0001 for PFS, p\u2009=\u20090.0052 for OS). CONCLUSION: Although no difference in outcome were observed with antibiotic use in the EIOP, a detrimental effect became evident for patients with a higher AIER in the WIOP. If its relevance is confirmed, AIER may become an innovative variable for estimating the impact of antibiotics on IO efficacy

SMO mutations confer poor prognosis in malignant pleural mesothelioma

Background: Malignant pleural mesothelioma (MPM) is an aggressive tumor but approximately 12% of patients survive more than 3 years. The biological differences underlying better outcomes are not known. Several targeted agents and immunotherapy have been ineffective. Hedgehog (Hh) is one emerging pathway. We compared the biological profiles of patients with different survival, investigating the most frequently altered genes, including the Hh pathway. Methods: We analyzed 56 MPM. A 36-month overall survival (OS) cut-off divided patients into 32 normo (NS) and 24 long (LS) survivors. We used next generation sequencing to test 21 genes, immunohistochemistry to evaluate SMO expression. Mutation differences between NS and LS and their associations with clinical features were analysed by Fisher's test, OS with the Kaplan-Meier method and its association with mutations by univariate and multivariate Cox proportional hazard models. Results: Clinical features were similar in both groups. Eighteen out of 56 patients (32%) were wild-type for the genes analysed. At least five had mutations in BAP1, NF2, TP53, SMO and PTCH1 with no significant differences between the groups except for SMO. SMO, a member of the Hh pathway, was mutated only in NS (15.6%) and only SMO mutations were significantly associated with poor prognosis at univariate (HR =4.36, 95% CI: 2.32-8.18, P<0.0001) and multivariate (HR =9.2, 95% CI: 3.0-28.4, P=0.0001) analysis. All SMO mutated patients expressed high protein levels. Conclusions: SMO mutations were clearly associated with worse prognosis. SMO may be a therapeutic target but this needs to be confirmed in a prospective trial

Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review

Background: The widespread use of immune checkpoint inhibitors (ICIs) has revolutionised treatment of multiple cancer types. However, selecting patients who may benefit from ICI remains challenging. Artificial intelligence (AI) approaches allow exploitation of high-dimension oncological data in research and development of precision immuno-oncology. Materials and methods: We conducted a systematic literature review of peer-reviewed original articles studying the ICI efficacy prediction in cancer patients across five data modalities: genomics (including genomics, transcriptomics, and epigenomics), radiomics, digital pathology (pathomics), and real-world and multimodality data. Results: A total of 90 studies were included in this systematic review, with 80% published in 2021-2022. Among them, 37 studies included genomic, 20 radiomic, 8 pathomic, 20 real-world, and 5 multimodal data. Standard machine learning (ML) methods were used in 72% of studies, deep learning (DL) methods in 22%, and both in 6%. The most frequently studied cancer type was non-small-cell lung cancer (36%), followed by melanoma (16%), while 25% included pan-cancer studies. No prospective study design incorporated AI-based methodologies from the outset; rather, all implemented AI as a post hoc analysis. Novel biomarkers for ICI in radiomics and pathomics were identified using AI approaches, and molecular biomarkers have expanded past genomics into transcriptomics and epigenomics. Finally, complex algorithms and new types of AI-based markers, such as meta-biomarkers, are emerging by integrating multimodal/multi-omics data. Conclusion: AI-based methods have expanded the horizon for biomarker discovery, demonstrating the power of integrating multimodal data from existing datasets to discover new meta-biomarkers. While most of the included studies showed promise for AI-based prediction of benefit from immunotherapy, none provided high-level evidence for immediate practice change. A priori planned prospective trial designs are needed to cover all lifecycle steps of these software biomarkers, from development and validation to integration into clinical practice

Supporting Clinical Decision-Making during the SARS-CoV-2 Pandemic through a Global Research Commitment: The TERAVOLT Experience.

To understand the real impact of COVID-19 on cancer patients, an entirely new data collection effort was initiated within the Thoracic Cancers International COVID-19 Collaboration (TERAVOLT). TERAVOLT reported high mortality related to COVID-19 infection in thoracic cancer patients and identified several negative prognostic factors. In this commentary, we discuss the importance and limits of patient registries to support decision-making in thoracic cancer during the SARS-CoV-2 pandemic