Imperial College London

Dr Alessio Cortellini MD PhD

Faculty of MedicineDepartment of Surgery & Cancer

Honorary Clinical Lecturer
 
 
 
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Contact

 

a.cortellini

 
 
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Location

 

138ICTEM buildingHammersmith Campus

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Summary

 

Publications

Publication Type
Year
to

337 results found

Hedayat S, Cascione L, Cunningham D, Schirripa M, Lampis A, Hahne JC, Tunariu N, Hong SP, Marchetti S, Khan K, Fontana E, Angerilli V, Delrieux M, Nava Rodrigues D, Procaccio L, Rao S, Watkins D, Starling N, Chau I, Braconi C, Fotiadis N, Begum R, Guppy N, Howell L, Valenti M, Cribbes S, Kolozsvari B, Kirkin V, Lonardi S, Ghidini M, Passalacqua R, Elghadi R, Magnani L, Pinato DJ, Di Maggio F, Ghelardi F, Sottotetti E, Vetere G, Ciraci P, Vlachogiannis G, Pietrantonio F, Cremolini C, Cortellini A, Loupakis F, Fassan M, Valeri Net al., 2024, Circulating microRNA analysis in a prospective co-clinical trial identifies MIR652-3p as a response biomarker and driver of regorafenib resistance mechanisms in colorectal cancer., Clin Cancer Res

BACKGROUND: The multi-kinase inhibitor regorafenib has demonstrated efficacy in chemo-refractory metastatic colorectal cancer (mCRC) patients. However, lack of predictive biomarkers and concerns over significant toxicities hamper the use of regorafenib in clinical practice. METHODS: Serial liquid biopsies were obtained at baseline and monthly until disease progression in chemo-refractory mCRC patients treated with regorafenib in a phase II clinical trial (PROSPECT-R n=40; NCT03010722) and in a multicentric validation cohort (n=241). Tissue biopsies collected at baseline, after 2 months and at progression in the PROSPECT-R trial were used to establish Patient-Derived Organoids (PDOs) and for molecular analyses. MicroRNA profiling was performed on baseline bloods using the NanoString nCounter platform and results were validated by digital droplet PCR and/or In Situ Hybridization in paired liquid and tissue biopsies. PDOs co-cultures and PDO-xenotransplants were generated for functional analyses. RESULTS: Large-scale microRNA expression analysis in longitudinal matched liquid and tissue biopsies from the PROSPECT-R trial identified MIR652-3p as a biomarker of clinical benefit to regorafenib. These findings were confirmed in an independent validation cohort and in a "control" group of 100 patients treated with lonsurf. Using ex vivo co-culture assays paired with single-cell RNA-sequencing of PDO established pre- and post-treatment, we modelled regorafenib response observed in vivo and in patients, and showed that MIR652-3p controls resistance to regorafenib by impairing regorafenib-induced lethal autophagy and by orchestrating the switch from neo-angiogenesis to vessel co-option. CONCLUSIONS: Our results identify MIR652-3p as potential biomarker and as a driver of cell and non-cell autonomous mechanisms of resistance to regorafenib.

Journal article

Mostaghim A, Minkove S, Aguilar-Company J, Ruiz-Camps I, Eremiev-Eremiev S, Dettorre GM, Fox L, Tondini C, Brunet J, Carmona-GarcĂ­a M, Lambertini M, Bower M, Newsom-Davis T, Sharkey R, Pria AD, Rossi M, Plaja A, Salazar R, Sureda A, Prat A, Michalarea V, Van Hemelrijck M, Sita-Lumsden A, Bertuzzi A, Rimassa L, Rossi S, Rizzo G, Pedrazzoli P, Lee AJ, Murphy C, Belessiotis K, Diamantis N, Mukherjee U, Pommeret F, Stoclin A, Martinez-Vila C, Bruna R, Gaidano G, D'Avanzo F, Gennari A, Athale J, Eichacker P, Pinato DJ, Torabi-Parizi P, Cortellini A, OnCovid study groupet al., 2024, Prior immune checkpoint inhibitor (ICI) therapy is associated with decreased COVID-19-related hospitalizations and complications in patients with cancer: Results of a propensity-matched analysis of the OnCovid registry, International Journal of Infectious Diseases, Vol: 139, Pages: 13-20, ISSN: 1201-9712

Objectives:To date, studies have not provided definitive answers regarding whether previous immune checkpoint inhibitor (ICI) treatment alters outcomes for cancer patients with COVID-19.Methods:The OnCovid registry (NCT04393974) was searched from February 27, 2020, to January 31, 2022, for patients who received systemic anti-cancer therapy in the 4 weeks before laboratory-confirmed COVID-19 diagnosis. Propensity-score matching using country, vaccination status, primary tumor type, sex, age, comorbidity burden, tumor stage, and remission status investigated differences in predefined clinical outcomes comparing those who had or had not received ICIs.Results:Of 3523 patients screened, 137 ICI-only and 1378 non-ICI met inclusion criteria. Before matching, ICI patients were older, male, enrolled at centers in Italy, and had histories of smoking, thoracic cancers, advanced cancer stages, and active malignancies (P ≤0.02). After matching, there were 120 ICI and 322 non-ICI patients. ICI patients had no differences (odds ratio: 95% CI) in presenting COVID-19 symptoms (0.69: 0.37-1.28), receipt of COVID-specific therapy (0.88: 0.54-1.41), 14-day (0.95: 0.56-1.61), or 28-day (0.79: 0.48-1.29) mortalities. However, ICI patients required less COVID-19-related hospitalization (0.37: 0.21-0.67) and oxygen therapy (0.51: 0.31-0.83) and developed fewer complications (0.57: 0.36-0.92).Conclusion:In this propensity-score matched analysis, previous ICI therapy did not worsen and potentially improved COVID-19 outcomes in patients with cancer.

Journal article

Balcar L, Scheiner B, Fulgenzi CAM, D'Alessio A, Pomej K, Roig MB, Meyer EL, Che J, Nishida N, Lee P-C, Wu L, Ang C, Krall A, Saeed A, Stefanini B, Cammarota A, Pressiani T, Abugabal YI, Chamseddine S, Wietharn B, Parisi A, Huang Y-H, Phen S, Vivaldi C, Salani F, Masi G, Bettinger D, Vogel A, von Felden J, Schulze K, Silletta M, Trauner M, Samson A, Wege H, Piscaglia F, Galle PR, Stauber R, Kudo M, Singal AG, Itani A, Ulahannan SV, Parikh ND, Cortellini A, Kaseb A, Rimassa L, Chon HJ, Pinato DJ, Pinter Met al., 2024, A meta-analysis and real-world cohort study on the sex-related differences in efficacy and safety of immunotherapy for hepatocellular carcinoma., JHEP Rep, Vol: 6

BACKGROUND & AIMS: Sex-related differences in the immune pathogenesis of hepatocellular carcinoma (HCC), particularly related to oestrogen-dependent secretion of pro-tumourigenic cytokines, are well-known. Whether sex influences the efficacy and safety of immunotherapy is not known. METHODS: We performed a restricted maximum likelihood random effects meta-analysis of five phase III trials that evaluated immune checkpoint inhibitors (ICIs) in advanced HCC and reported overall survival (OS) hazard ratios (HRs) stratified by sex to evaluate sex-related differences in OS. In a real-world cohort of 840 patients with HCC from 22 centres included between 2018 and 2023, we directly compared the efficacy and safety of atezolizumab + bevacizumab (A+B) between sexes. Radiological response was reported according to RECIST v1.1. Uni- and multivariable Cox regression analyses were performed for OS and progression-free survival (PFS). RESULTS: In the meta-analysis, immunotherapy was associated with a significant OS benefit only in male (pooled HR 0.79; 95% CI 0.73-0.86) but not in female (pooled HR 0.85; 95% CI 0.70-1.03) patients with HCC. When directly comparing model estimates, no differences in the treatment effect between sexes were observed. Among 840 patients, 677 (81%) were male (mean age 66 ± 11 years), and 163 (19%) were female (mean age 67 ± 12 years). Type and severity of adverse events were similar between the two groups. OS and PFS were comparable between males and females upon uni- and multivariable analyses (aHR for OS and PFS: 0.79, 95% CI 0.59-1.04; 1.02, 95% CI 0.80-1.30, respectively). Objective response rates (24%/22%) and disease control rates (59%/59%) were also similar between sexes. CONCLUSION: Female phase III trial participants experienced smaller OS benefit following ICI therapy for advanced HCC, while outcomes following A+B treatment were comparable between sexes in a large real-world database. Based on the ambiguous sex-related

Journal article

Vincenzi B, Cortellini A, Mazzocca A, Orlando S, Romandini D, Aguilar-Company J, Ruiz-Camps I, Valverde Morales C, Eremiev-Eremiev S, Tondini C, Brunet J, Bertulli R, Provenzano S, Bower M, Generali D, Salazar R, Sureda A, Prat A, Vasiliki M, Van Hemelrijck M, Sita-Lumsden A, Bertuzzi A, Rossi S, Jackson A, Grosso F, Lee AJX, Murphy C, Belessiotis K, Mukherjee U, Pommeret F, Loizidou A, Gaidano G, Dettorre GM, Grisanti S, Tucci M, Fulgenzi CAM, Gennari A, Napolitano A, Pinato DJet al., 2024, Impact of SARS-CoV-2 vaccines and recent chemotherapy on COVID-19 morbidity and mortality in patients with soft tissue sarcoma: an analysis from the OnCovid registry, Therapeutic Advances in Medical Oncology, Vol: 16, Pages: 1-11, ISSN: 1758-8340

Background:To date, limited evidence exists on the impact of COVID-19 in patients with soft tissue sarcoma (STS), nor about the impact of SARS-CoV-2 vaccines and recent chemotherapy on COVID-19 morbidity and mortality in this specific population.Methods:We described COVID-19 morbidity and mortality among patients with STS across ‘Omicron’ (15 December 2021–31 January 2022), ‘Pre-vaccination’ (27 February 2020–30 November 2020), and ‘Alpha-Delta’ phase (01 December 2020–14 December 2021) using OnCovid registry participants (NCT04393974). Case fatality rate at 28 days (CFR28) and COVID-19 severity were also described according to the SARS-CoV-2 vaccination status, while the impact of the receipt of cytotoxic chemotherapy within 4 weeks prior to COVID-19 on clinical outcomes was assessed with Inverse Probability of Treatment Weighting (IPTW) models adjusted for possible confounders.Results:Out of 3820 patients, 97 patients with STS were included. The median age at COVID-19 diagnosis was 56 years (range: 18–92), with 65 patients (67%) aged < 65 years and most patients had a low comorbidity burden (65, 67.0%). The most frequent primary tumor sites were the abdomen (56.7%) and the gynecological tract (12.4%). In total, 36 (37.1%) patients were on cytotoxic chemotherapy within 4 weeks prior to COVID-19. The overall CFR28 was 25.8%, with 38% oxygen therapy requirement, 34% rate of complications, and 32.3% of hospitalizations due to COVID-19. CFR28 (29.5%, 21.4%, and 12.5%) and all indicators of COVID-19 severity demonstrated a trend toward a numerical improvement across the pandemic phases. Similarly, vaccinated patients demonstrated numerically improved CFR28 (16.7% versus 27.7%) and COVID-19 morbidity compared with unvaccinated patients. Patients who were on chemotherapy experienced comparable CFR28 (19.4% versus 26.0%, p = 0.4803), hospitalizations (50.0% versus 44.4%, p = 0.6883), complication rates (30.6% v

Journal article

Takada K, Takamori S, Brunetti L, Crucitti P, Cortellini Aet al., 2023, Impact of Neoadjuvant Immune Checkpoint Inhibitors on Surgery and Perioperative Complications in Patients With Non-small-cell Lung Cancer: A Systematic Review., Clin Lung Cancer, Vol: 24, Pages: 581-590.e5

Several clinical trials are currently underway to evaluate immune checkpoint inhibitors (ICIs) as neoadjuvant treatment for patients with early-stage non-small-cell lung cancer (NSCLC), and their use in clinical practice is expected to increase in the future. Therefore, a proper assessment of surgical outcomes and perioperative complications after neoadjuvant ICIs is essential to establish recommendations and guidelines. We performed a systematic literature review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines (PRISMA), searching the PubMed and Scopus databases from the January 1, 2017, to the July 27, 2023, to identify potentially relevant published trials of neoadjuvant ICIs in patients with reseactable NSCLC with available information on surgical outcomes and perioperative complications. A total of 18 studies were included in the review. The rates of surgery cancellation ranged from 0% to 45.8%. Importantly, adverse events (AEs) were the least reported underlying cause, while disease progression caused from 0% to 75% of cancellations. Surgery delays ranged from 0% to 31.3% with AEs as the most frequently reported underlying cause. However, 6 out of 13 trials (46.2%) reported no surgery delays. Conversion rates from minimally invasive to open chest surgery were available for 7 trials and ranged from 0% to 53.8%. Thirty-day mortality rates ranged from 0% to 5.4%, with 11 out of 16 trials reporting 0%. A few reports described perioperative complications in detail. Considering the limited evidence available, we can preliminarily confirm that preoperative ICIs are safe and well tolerated even from the surgical perspective. Additional details on intraoperative findings from prospective controlled trials are needed to establish and disseminate guidelines and recommendations for thoracic surgeons.

Journal article

Choucair K, Nebhan C, Cortellini A, Hentzen S, Wang Y, Liu C, Giusti R, Filetti M, Ascierto PA, Vanella V, Galetta D, Catino A, Al-Bzour N, Saeed A, Cavalcante L, Pizzutilo P, Genova C, Bersanelli M, Buti S, Johnson DB, Fulgenzi CAM, Pinato DJ, Radford M, Kim C, Naqash AR, Saeed Aet al., 2023, Characterization of Age-Associated, Neutrophil-to-Lymphocyte Ratio (NLR) and Systemic Immune-Inflammatory Index (SII) as Biomarkers of Inflammation in Geriatric Patients with Cancer Treated with Immune Checkpoint Inhibitors: Impact on Efficacy and Survival., Cancers (Basel), Vol: 15, ISSN: 2072-6694

BACKGROUND: Geriatric patients (≥80 years) are underrepresented in immune checkpoint inhibitor (ICIs) clinical trials. However, their unique biology may affect their response to ICIs. There are currently no established biomarkers of the response to ICIs in adult patients with cancer that can help with patient selection. METHODS: We built a multicenter, international retrospective study of 885 patients (<80 years: n = 417, 47.12%; ≥80 years: n = 468, 52.88%) with different tumor types treated with ICIs between 2011 and 2021 from 11 academic centers in the U.S. and Europe. The main outcome measures were objective response rates (ORR), progression-free survival (PFS) and overall survival (OS) stratified by age and circulating inflammatory levels (neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammatory index (SII)). RESULTS: Patients ≥80 years with low NLR (NLR-L) and SII (SII-L) had significantly higher ORR (vs. high NLR [NLR-H], p < 0.01 and SII-H, p < 0.05, respectively). At median follow-ups (13.03 months), and compared to SII-H, patients with SII-L had significantly longer median PFS and OS in patients <80 (p < 0.001), and ≥80 years (p < 0.001). SII-L was independently associated with longer PFS and OS (HR: 0.61 and 0.62, respectively, p < 0.01). CONCLUSION: Lower inflammation pre-ICI initiation may predict an improved response and survival in geriatric patients with cancer.

Journal article

Pecci F, Cantini L, Cognigni V, Perrone F, Mazzaschi G, Agostinelli V, Mentrasti G, Favari E, Maffezzoli M, Cortellini A, Rossi F, Chiariotti R, Venanzi FM, Lo Russo G, Galli G, Proto C, Ganzinelli M, Tronconi F, Morgese F, Campolucci C, Moretti M, Vignini A, Tiseo M, Minari R, Rocchi MLB, Buti S, Berardi Ret al., 2023, Prognostic Impact of Blood Lipid Profile in Patients With Advanced Solid Tumors Treated With Immune Checkpoint Inhibitors: A Multicenter Cohort Study, ONCOLOGIST, ISSN: 1083-7159

Journal article

Cortellini A, D'Alessio A, Pinato DJ, 2023, Diabetes and Immune Checkpoint Inhibitors-Response, CLINICAL CANCER RESEARCH, Vol: 29, Pages: 4017-4018, ISSN: 1078-0432

Journal article

Naqash AR, McCallen JD, Mi E, Iivanainen S, Marie MA, Gramenitskaya D, Clark J, Koivunen JP, Macherla S, Jonnalagadda S, Polsani S, Jiwani RA, Hafiz M, Muzaffar M, Brunetti L, Stroud CRG, Walker PR, Wang K, Chung Y, Ruppin E, Lee S-H, Yang LV, Pinato DJ, Lee JS, Cortellini Aet al., 2023, Increased interleukin-6/C-reactive protein levels are associated with the upregulation of the adenosine pathway and serve as potential markers of therapeutic resistance to immune checkpoint inhibitor-based therapies in non-small cell lung cancer., J Immunother Cancer, Vol: 11

BACKGROUND: Systemic immune activation, hallmarked by C-reactive protein (CRP) and interleukin-6 (IL-6), can modulate antitumor immune responses. In this study, we evaluated the role of IL-6 and CRP in the stratification of patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs). We also interrogated the underlying immunosuppressive mechanisms driven by the IL-6/CRP axis. METHODS: In cohort A (n=308), we estimated the association of baseline CRP with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) in patients with NSCLC treated with ICIs alone or with chemo-immunotherapy (Chemo-ICI). Baseline tumor bulk RNA sequencing (RNA-seq) of lung adenocarcinomas (LUADs) treated with pembrolizumab (cohort B, n=59) was used to evaluate differential expression of purine metabolism, as well as correlate IL-6 expression with PFS. CODEFACS approach was applied to deconvolve cohort B to characterize the tumor microenvironment by reconstructing the cell-type-specific transcriptome from bulk expression. Using the LUAD cohort from The Cancer Genome Atlas (TCGA) we explored the correlation between IL-6 expression and adenosine gene signatures. In a third cohort (cohort C, n=18), plasma concentrations of CRP, adenosine 2a receptor (A2aR), and IL-6 were measured using ELISA. RESULTS: In cohort A, 67.2% of patients had a baseline CRP≥10 mg/L (CRP-H). Patients with CRP-H achieved shorter OS (8.6 vs 14.8 months; p=0.006), shorter PFS (3.3 vs 6.6 months; p=0.013), and lower ORR (24.7% vs 46.3%; p=0.015). After adjusting for relevant clinical variables, CRP-H was confirmed as an independent predictor of increased risk of death (HR 1.51, 95% CI: 1.09 to 2.11) and lower probability of achieving disease response (OR 0.34, 95% CI: 0.13 to 0.89). In cohort B, RNA-seq analysis demonstrated higher IL-6 expression on tumor cells of non-responders, along with a shorter PFS (p<0.05) and enrichment of the puri

Journal article

El Zarif T, Nassar AH, Pond GR, Zhuang TZ, Master V, Nazha B, Niglio S, Simon N, Hahn AW, Pettaway CA, Tu S-M, Abdel-Wahab N, Velev M, Flippot R, Buti S, Maruzzo M, Mittra A, Gheeya J, Yang Y, Rodriguez PA, Castellano D, de Velasco G, Roviello G, Antonuzzo L, Mckay RR, Vincenzi B, Cortellini A, Hui G, Drakaki A, Glover M, Khaki AR, El-Am E, Adra N, Mouhieddine TH, Patel V, Piedra A, Gernone A, Davis NB, Matthews H, Harrison MR, Kanesvaran R, Giudice GC, Barata P, Farolfi A, Lee JL, Milowsky M, Stahlfeld C, Appleman L, Kim JW, Freeman D, Choueiri TK, Spiess PE, Necchi A, Apolo AB, Sonpavde GPet al., 2023, Safety and efficacy of immune checkpoint inhibitors in advanced penile cancer: report from the Global Society of Rare Genitourinary Tumors, JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, ISSN: 0027-8874

Journal article

Di Nardo L, Del Regno L, Di Stefani A, Mannino M, Fossati B, Catapano S, Quattrini L, Pellegrini C, Cortellini A, Parisi A, Capoluongo E, Autilio C, Fargnoli MC, Peris Ket al., 2023, The dynamics of circulating tumour DNA (ctDNA) during treatment reflects tumour response in advanced melanoma patients, EXPERIMENTAL DERMATOLOGY, ISSN: 0906-6705

Journal article

Vithayathil M, D'Alessio A, Fulgenzi CAM, Nishida N, Schoenlein M, von Felden J, Schulze K, Wege H, Saeed A, Wietharn B, Hildebrand H, Wu L, Ang C, Marron TU, Weinmann A, Galle PR, Bettinger D, Bengsch B, Vogel A, Balcar L, Scheiner B, Lee P-C, Huang Y-H, Amara S, Muzaffar M, Naqash AR, Cammarota A, Zanuso V, Pressiani T, Pinter M, Cortellini A, Kudo M, Rimassa L, Pinato DJ, Sharma Ret al., 2023, Impact of body mass index in patients receiving atezolizumab plus bevacizumab for hepatocellular carcinoma, HEPATOLOGY INTERNATIONAL, Vol: 17, Pages: 904-914, ISSN: 1936-0533

Journal article

El Zarif T, Nassar AH, Adib E, Fitzgerald BG, Huang J, Mouhieddine TH, Rubinstein PG, Nonato T, McKay RR, Li M, Mittra A, Owen DH, Baiocchi RA, Lorentsen M, Dittus C, Dizman N, Falohun A, Abdel-Wahab N, Diab A, Bankapur A, Reed A, Kim C, Arora A, Shah NJ, El-Am E, Kozaily E, Abdallah W, Al-Hader A, Abu Ghazal B, Saeed A, Drolen C, Lechner MG, Drakaki A, Baena J, Nebhan CA, Haykal T, Morse MA, Cortellini A, Pinato DJ, Dalla Pria A, Hall E, Bakalov V, Bahary N, Rajkumar A, Mangla A, Shah V, Singh P, Nana FA, Lopetegui-Lia N, Dima D, Dobbs RW, Funchain P, Saleem R, Woodford R, Long GV, Menzies AM, Genova C, Barletta G, Puri S, Florou V, Idossa D, Saponara M, Queirolo P, Lamberti G, Addeo A, Bersanelli M, Freeman D, Xie W, Reid EG, Chiao EY, Sharon E, Johnson DB, Ramaswami R, Bower M, Emu B, Marron TU, Choueiri TK, Baden LR, Lurain K, Sonpavde GP, Naqash ARet al., 2023, Safety and Activity of Immune Checkpoint Inhibitors in People Living With HIV and Cancer: A Real-World Report From the Cancer Therapy Using Checkpoint Inhibitors in People Living With HIV-International (CATCH-IT) Consortium, JOURNAL OF CLINICAL ONCOLOGY, Vol: 41, Pages: 3712-+, ISSN: 0732-183X

Journal article

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Methods S1 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Tumour micron-environment transcriptome analysis.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S10 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Detailed random blood sugar test results used to compute the median baseline glycaemia (MBG). 133 patients included (30 from the Pascale Cancer Institute and 103 from Imperial College London Cohort.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S2 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Details of diabetes medications.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S7 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on metformin only and patients who were not receiving diabetes medications (ratio 1:3, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S10 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Detailed random blood sugar test results used to compute the median baseline glycaemia (MBG). 133 patients included (30 from the Pascale Cancer Institute and 103 from Imperial College London Cohort.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S6 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution between patients on metformin only and those who were not on diabetes medications.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S5 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Melanoma cohort - summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on diabetes medications and those who were not receiving diabetes medications (ratio 1:3, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S1 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Participating centres’ list.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S2 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Details of diabetes medications.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S3 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on diabetes medications and those who were not receiving diabetes medications (ratio 1:2, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S11 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics of patients included in the targeted transcriptome analysis.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S1 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Participating centres’ list.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S9 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on other antidiabetic drugs/insulin only and those who were not on diabetes medications (ratio 1:3, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S9 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on other antidiabetic drugs/insulin only and those who were not on diabetes medications (ratio 1:3, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S3 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on diabetes medications and those who were not receiving diabetes medications (ratio 1:2, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S4 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;NSCLC cohort - summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on diabetes medications and those who were not receiving diabetes medications (ratio 1:1, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S7 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on metformin only and patients who were not receiving diabetes medications (ratio 1:3, caliper 0.1).&lt;/p&gt;</jats:p>

Other

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