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Glioblastoma is a highly vascularised tumour and there are few treatment options after disease recurrence. Regorafenib is an oral multikinase inhibitor of angiogenic, stromal, and oncogenic receptor tyrosine kinases. We aimed to assess the efficacy and safety of regorafenib in the treatment of recurrent glioblastoma. REGOMA is a randomised, multicentre, open-label phase 2 trial done in ten centres in Italy. Eligible patients (aged ≥18 years) with histologically confirmed glioblastoma, Eastern Cooperative Oncology Group performance status 0 or 1, and documented disease progression after surgery followed by radiotherapy and temozolomide chemoradiotherapy were randomly assigned (1:1) by a web-based system, stratified by centre and surgery at recurrence (yes vs no), to receive regorafenib 160 mg once daily for the first 3 weeks of each 4-week cycle or lomustine 110 mg/m2 once every 6 weeks until disease progression, death, unacceptable toxicity, or consent withdrawal. The primary endpoint was overall survival in the intention-to-treat population. This trial is registered with ClinicalTrials.gov, NCT02926222, and is currently in follow-up. Between Nov 27, 2015, and Feb 23, 2017, 124 patients were screened and 119 eligible patients were randomly assigned to receive regorafenib (n=59) or lomustine (n=60). Median follow-up was 15·4 months (IQR 13·8–18·1). At the analysis cutoff date, 99 (83%) of 119 patients had died: 42 (71%) of 59 in the regorafenib group and 57 (95%) of 60 in the lomustine group. Overall survival was significantly improved in the regorafenib group compared with the lomustine group, with a median overall survival of 7·4 months (95% CI 5·8–12·0) in the regorafenib group and 5·6 months (4·7–7·3) in the lomustine group (hazard ratio 0·50, 95% CI 0·33–0·75; log-rank p=0·0009). Grade 3–4 treatment-related adverse events occurred in 33 (56%) of 59 patients treated with regorafenib and 24 (40%) of 60 with lomustine. The most frequent grade 3 or 4 adverse events related to regorafenib were hand–foot skin reaction, increased lipase, and blood bilirubin increased (in six [10%] of 59 patients each). In the lomustine group, the most common grade 3 or 4 adverse events were decreased platelet count (eight [13%] of 60 patients), decreased lymphocyte count (eight [13%]), and neutropenia (seven [12%]). No death was considered by the investigators to be drug related. REGOMA showed an encouraging overall survival benefit of regorafenib in recurrent glioblastoma. This drug might be a new potential treatment for these patients and should be investigated in an adequately powered phase 3 study. Veneto Institute of Oncology and Bayer Italy.

BackgroundMalignant gliomas (MG) are aggressive brain tumours in adults. The standard of care is concurrent radiation plus temozolomide (TMZ) [chemo-radiotherapy (CRT)] followed by TMZ maintenance up to 6 months. TMZ is considered to have a low toxicity profile, but several studies reported occurrence of severe myelosuppression, especially during the concomitant phase. Toxicity may be prolonged, thus treatment should be discontinued.PurposeTo evaluate the risk of recurrente myelotoxicity during adjuvant chemotherapy (CT) in patients who recovered from severe myelotoxicity during CRT.MethodsWe retrospectively collected data on patients with MG who developed and recovered from severe myelotoxicity during CRT from eight Italian neuro-oncology centers.ResultsWe included 87 patients. Histology was Glioblastoma (GBM) in 78 patients (89.7%); 60% of patients were female. After myelotoxicity recovery, 54 (62%) received treatment. The majority of them (82%, n = 44) received adjuvant TMZ and 18% (n = 10) others treatments. Out of 44 patients who received adjuvant TMZ, 34% experienced the re-occurrence of grade 3–4 myelotoxicity which required permanent CT discontinuation in 6 (13%) cases. Patients who received TMZ or other treatments had longer overall (OS) (adjusted HR 0.46, p = 0.008) and progression free survival (PFS) (adjusted HR 0.57, p = 0.034) than those who remained untreated.ConclusionOur study suggests that after severe myelotoxicity the majority of patients received treatment, particularly with TMZ. Only a fraction of patients experienced toxicity recurrence, suggesting that TMZ is well tolerated and had an impact on PFS and OS.

Liquid biopsy (LB) involves the analysis of circulating tumour-derived DNA (ctDNA), providing a minimally invasive method for gathering both quantitative and qualitative information. Genomic analysis of ctDNA through next-generation sequencing (NGS) enables comprehensive genetic profiling of tumours, including non-driver alterations that offer prognostic insights. LB can be applied in both early-stage disease settings, for the diagnosis and monitoring of minimal residual disease (MRD), and advanced disease settings, for monitoring treatment response and understanding the mechanisms behind disease progression and tumour heterogeneity. Currently, LB has limited use in clinical practice, primarily due to its significant costs, limited diagnostic yield, and uncertain prognostic role. The application of artificial intelligence (AI) in the medical field is a promising approach to processing extensive information and applying it to individual cases to enhance therapeutic decision-making and refine risk assessment.

Background: Depatuxizumab Mafodotin (Depatux-M; ABT-414) is an antibody-drug conjugate consisting of a specific antibody against activated EGFR and a cytotoxic agent with antimicrotubule activity. The INTELLANCE 2/EORTC 1410 phase 2 trial produced interesting results for the combination regimen of Depatux-M and temozolomide in EGFR-amplified glioblastoma patients at first recurrence. For the first time worldwide, our work investigated the clinical outcome and safety of this combination in a real-life population. Materials and Methods: Patients were enrolled from seven AINO (Italian Association of Neuro-Oncology) Institutions. The major inclusion criteria were: histologically confirmed diagnosis of glioblastoma, EGFR-amplified, one or more prior systemic therapies and ECOG PS ≤ 2. According to the original schedule, patients received Depatux-M 1.25 mg/kg every 2 weeks combined with temozolomide. The primary endpoints of the study were overall survival and safety. Results: A total of 36 patients were enrolled. The median age was 57 years, ECOG PS was 0–1 in 28 patients (88%), MGMT methylated status was found in 22 (64%), 15 patients (42%) received the combined treatment as second-line therapy. The median OS was 8.04 months (95% CI, 5.3–10.7), the 12 month-OS was 37%. On univariate and multivariate analyses, the MGMT methylation status was the only factor resulting significantly associated with survival. Grade 3 ocular toxicity occurred in 11% of patients; no grade 4 ocular toxicity was reported. No death was considered to be drug-related. Conclusions: The study reported the first “real world” experience of Depatux-M plus temozolomide in recurrent glioblastoma patients. Encouraging clinical benefits were demonstrated, even though most patients were treated beyond second-line therapy. Overall, the results are close to those reported in the previous phase 2 trial. Toxicity was moderate and manageable.

Background The role of platinum-based chemotherapy (PBC) for the treatment of older patients with non-small cell lung cancer (NSCLC) is still a matter of debate, despite the advent of immunotherapy. Objective The aim of the study was to identify factors associated with first-line PBC prescription and, secondly, to evaluate the impact of first-line PBC on survival, treatment intensity, risk of hospitalization, and subsequent treatments. Patients and Methods We reviewed a consecutive series of 474 older patients (age ≥ 70 years) diagnosed with stage IIIB–IV NSCLC at the Department of Oncology, University Hospital of Udine, Italy from January 2009 to March 2017. Results Overall, 198 patients were deemed eligible, and 65.2% received a PBC. At multivariate analysis, older age was the only factor associated with PBC prescription. In the whole cohort, 46 patients (23.2%) were hospitalized for chemotherapy-related toxicity. Both PBC prescription (odds ratio [OR] 2.23, 95% confidence interval [CI] 1.02–4.87, p  = 0.04) and tumor burden (OR 2.39, 95% CI 1.07–5.32, p  = 0.03) emerged as independent risk factors for hospitalization. Moving to significant predictors of patterns of care, Eastern Cooperative Oncology Group (ECOG) performance status > 0 was associated with greater risk of first-line failure (OR 2.20, 95% CI 1.15–4.20, p  = 0.02), while bone metastases (OR 0.29, 95% CI 0.12–0.69, p  = 0.005) and a Charlson Comorbidity Index score ≥ 3 (OR 0.40, 95% CI 0.19–0.84, p  = 0.016) independently predicted lower probability of receiving second-line therapy. Remarkably, PBC did not significantly impact overall survival (hazard ratio [HR] 0.83, 95% CI 0.61–1.14, p  = 0.24) and progression-free survival (HR 0.95, 95% CI 0.70–1.28, p  = 0.73) compared to single-agent chemotherapy (SAC). However, according to an exploratory landmark analysis, patients who received four cycles of treatment or maintenance therapy experienced prolonged overall survival, regardless of PBC use. Conclusions This study evaluated the real-world use of PBC in older patients with NSCLC, offering an insight into the determinants of its prescription and the pattern of care of these patients. Of note, PBC use was associated with a higher likelihood of hospitalization for chemotherapy-related toxicity, with no benefit on survival compared to SAC.

PurposeEpigenetic variations in the O6-methylguanine-methyltransferase gene had been widely associated with a favorable impact on survival in patients affected by glioblastoma multiforme (GBM). Aim of this study is to explore a scoring system based on the gene promoter methylation in order to predict patients’ prognosis.MethodsA series of 128 patients with GBM was retrospectively analyzed. A training set and a validations set were then generated. The methylation level of CpGi from 74 to 83 was determined by pyrosequencing. In accordance to previous literature, each island was assigned with 1 point if the corresponding methylation level was higher than 9%. The sum consisted in a score that went from 0 (all CpGi < 9%) to 10 (all CpGi ≥ 9%). A threshold capable to detect a favorable outcome (overall survival, OS > 24 months) was identified by ROC analysis.ResultsMedian OS and follow-up were 14 and 32.6 months respectively. Among the total population, 35% of the pts had a score of 0, while 29% had a score of 10. A score ≥ 6 was associated with a favorable prognosis also when corrected for age (> 70 vs. ≤ 70 years) and ECOG performance status (0–1 vs. 2–3). Similar results were observed also in terms of PFS. Results were consistent in the training and in the validation set.ConclusionsThe present manuscript explored a novel scoring system capable to take into consideration the methylation status of each single CpGi, capable to better predict prognosis in GBM patients.

MGMT promoter methylation has been associated with improved survival in glioblastoma multiforme treated with temozolomide. However, there is no consensus on specific cut-off levels of methylation. The aims of the study were to explore the prognostic impact of MGMT methylation status and to analyze the role of specific cut-off values. We analyzed 108 glioblastoma multiforme patients treated between 2008 and 2013 stratified according to three pyrosequencing-based quantitative methylation in: unmethylated (methylation <9%), intermediate (9-29%) and highly methylated (>29%). The three-class stratification has a prognostic impact (median progression-free survival: 7.97, 11.6 and 15 months respectively; p = 0.004; median OS: 13.2, 15.8 and 19.5 months, respectively; p = 0.0002), especially in patients exposed to temozolomide. Our study confirmed that the independent prognostic role of MGMT methylation status. An average level of methylation between all investigated CpGs of 9% may help discriminating between methylated and unmethylated tumors.

Background. O6-methylguanine (O6-MeG)-DNA methyltransferase (MGMT) methylation status is a predictive factor for alkylating treatment efficacy in glioblastoma patients, but its prognostic role is still unclear. We performed a large, multicenter study to evaluate the association between MGMT methylation value and survival. Methods. We evaluated glioblastoma patients with an assessment of MGMT methylation status by pyrosequencing from nine Italian centers. The inclusion criteria were histological diagnosis of IDH wild-type glioblastoma, Eastern Cooperative Oncology Group Performance Status (ECOG-PS) ≤2, and radio-chemotherapy treatment with temozolomide. The relationship between OS and MGMT was investigated with a time-dependent Receiver Operating Characteristics (ROC) curve and Cox regression models. Results. In total, 591 newly diagnosed glioblastoma patients were analyzed. The median OS was 16.2 months. The ROC analysis suggested a cut-off of 15% for MGMT methylation. The 2-year Overall Survival (OS) was 18.3% and 51.8% for MGMT methylation <15% and ≥15% (p < 0.0001). In the multivariable analysis, MGMT methylation <15% was associated with impaired survival (p < 0.00001). However, we also found a non-linear association between MGMT methylation and OS (p = 0.002): median OS was 14.8 months for MGMT in 0–4%, 18.9 months for MGMT in 4–40%, and 29.9 months for MGMT in 40–100%. Conclusions. Our findings suggested a non-linear relationship between OS and MGMT promoter methylation, which implies a varying magnitude of prognostic effect across values of MGMT promoter methylation by pyrosequencing in newly diagnosed IDH wild-type glioblastoma patients treated with chemoradiotherapy.

The efficacy of temozolomide (TMZ) plus radiation therapy (RT) in elderly patients with glioblastoma is unclear. We performed a large multicenter retrospective study to analyze prognostic factors and clinical outcome in these patients. Inclusion criteria were age ≥65 years, newly histologically confirmed glioblastoma, ECOG PS 0-2, adjuvant treatment with RT plus TMZ. We enrolled 237 patients; the average age was 71 and ECOG PS was 0-1 in 196 patients; gross total resection was performed in 174 cases. MGMT was analyzed in 151 persons and was methylated in 56 %. IDH1 was assessed in 100 patients and was mutated in 6 %. Seventy-one patients were treated with RT 40 Gy and 166 with RT 60 Gy. Progression-free survival and overall survival (OS) were 11.3 and 17.3 months, respectively. Overall survival was 19.4 vs 13.8 months for patients treated with RT 60 Gy and 40 Gy (p = 0.02); OS was 17.7 versus 16.1 months for patients treated with gross total resection vs partial surgery (p = 0.02); OS was 21.2 versus 13.6 months for methylated and unmethylated MGMT (p < 0.001). On multivariate analysis, gross total resection, RT 60 Gy, methylated MGMT and ECOG PS 0-1 were independent predictors of longer survival. Twenty-five patients (10 %) had grade 3-4 haematological toxicity during the concomitant treatment. We showed that, in elderly patients in good clinical condition treated with concomitant treatment, standard-course irradiation might be more effective than short-course irradiation. Methylated MGMT remains the most important prognostic factor.

Predicting the effects of mutations on protein function is an important issue in evolutionary biology and biomedical applications. Computational approaches, ranging from graphical models to deep-learning architectures, can capture the statistical properties of sequence data and predict the outcome of high-throughput mutagenesis experiments probing the fitness landscape around some wild-type protein. However, how the complexity of the models and the characteristics of the data combine to determine the predictive performance remains unclear. Here, based on a theoretical analysis of the prediction error, we propose descriptors of the sequence data, characterizing their quantity and relevance relative to the model. Our theoretical framework identifies a trade-off between these two quantities, and determines the optimal subset of data for the prediction task, showing that simple models can outperform complex ones when inferred from adequately-selected sequences. We also show how repeated subsampling of the sequence data is informative about how much epistasis in the fitness landscape is not captured by the computational model. Our approach is illustrated on several protein families, as well as on in silico solvable protein models.