Phase Ib study of poly-epitope peptide vaccination to thymidylate synthase (TSPP) and GOLFIG chemo-immunotherapy for treatment of metastatic colorectal cancer patients

ABSTRACT: Thymidylate synthase (TS) is a tumor-associated enzyme critical for DNA replication and main 5′-fluorouracil (5′-FU) target. TSPP/VAC1 is a multi-arm trial phase-Ib trial program aimed to investigate the toxicity and biomodulatory activity of a poly-epitope-peptide vaccine to TS (TSPP) in cancer patients (pts). Here, we present the results of the TSPP/VAC1/arm C trial aimed to evaluate TSPP in combination with chemo-immunotherapy in pretreated metastatic colo-rectal cancer (mCRC) pts. Twenty-nine pts, 14 males and 15 females, received poly-chemotherapy with gemcitabine [GEM; 1,000 mg/sqm, day-1], oxaliplatin [OX; 80 mg/sqm, day-2], levofolinate [100 mg/sqm, days 1–2], bolus/infusional 5′-FU [400 mg/800 mg/sqm, days 1–2], sargramostim [50 μg, days 3–7/q30], and interleukin-2 [sc. 0.5 MIU twice a day, days 8–14/18–30] [GOLFIG-regimen]. Seventeen pts received sc. TSPP injections at escalating dosage [3 pts, 100 µg (DL-1); 3 pts, 200 µg (DL-2) and 11pts, 300 µg (DL-3)] one week after each chemotherapy cycle (concomitant module), while 10 out 12 pts received TSPP (300 µg) after 12 GOLFIG courses [dose level (DL)-0] (sequential module). TSPP MTD was not achieved. Adverse events consisted in swelling/erythema at injection sites (17 cases), G1–2 haematological (16 cases) and gastro-enteric events (12), fever, rhinitis, conjunctivitis, and poly-arthralgia and rise in auto-antibodies [ANA, ENA, c-ANCA, p-ANCA in the DL1–3 pts]. Both treatment-modules showed immunomodulating and antitumor activity (disease-control-rate, DL1–3 and DL0 were 70.6% and 83.3%, respectively) with a better survival recorded in the second group [median OS DL1–3 vs. DL0 = 8 vs. 16 mo, p = 0.049]. The promising long-term survival produced by the sequential treatment module deserves further phase II evaluation

Erratum to: One-year follow-up of mud-bath therapy in patients with bilateral knee osteoarthritis: a randomized, single-blind controlled trial

The online version of the original article can be found at http://dx.doi.org/ 10.1007/s00484-14-0943-0

Clinical and molecular characterization of COVID-19 hospitalized patients

Clinical and molecular characterization by Whole Exome Sequencing (WES) is reported in 35 COVID-19 patients attending the University Hospital in Siena, Italy, from April 7 to May 7, 2020. Eighty percent of patients required respiratory assistance, half of them being on mechanical ventilation. Fiftyone percent had hepatic involvement and hyposmia was ascertained in 3 patients. Searching for common genes by collapsing methods against 150 WES of controls of the Italian population failed to give straightforward statistically significant results with the exception of two genes. This result is not unexpected since we are facing the most challenging common disorder triggered by environmental factors with a strong underlying heritability (50%). The lesson learned from Autism-Spectrum-Disorders prompted us to re-analyse the cohort treating each patient as an independent case, following a Mendelian-like model. We identified for each patient an average of 2.5 pathogenic mutations involved in virus infection susceptibility and pinpointing to one or more rare disorder(s). To our knowledge, this is the first report on WES and COVID-19. Our results suggest a combined model for COVID-19 susceptibility with a number of common susceptibility genes which represent the favorite background in which additional host private mutations may determine disease progression

Association of Toll-like receptor 7 variants with life-threatening COVID-19 disease in males: findings from a nested case-control study

Background: Recently, loss-of-function variants in TLR7 were identified in two families in which COVID-19 segregates like an X-linked recessive disorder environmentally conditioned by SARS-CoV-2. We investigated whether the two families represent the tip of the iceberg of a subset of COVID-19 male patients.Methods: This is a nested case-control study in which we compared male participants with extreme phenotype selected from the Italian GEN-COVID cohort of SARS-CoV-2-infected participants (<60y, 79 severe cases versus 77 control cases). We applied the LASSO Logistic Regression analysis, considering only rare variants on young male subsets with extreme phenotype, picking up TLR7 as the most important susceptibility gene.Results: Overall, we found TLR7 deleterious variants in 2.1% of severely affected males and in none of the asymptomatic participants. The functional gene expression profile analysis demonstrated a reduction in TLR7-related gene expression in patients compared with controls demonstrating an impairment in type I and II IFN responses.Conclusion: Young males with TLR7 loss-of-function variants and severe COVID-19 represent a subset of male patients contributing to disease susceptibility in up to 2% of severe COVID-19

Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features

The impact of common and rare variants in COVID-19 host genetics has been widely studied. In particular, in Fallerini et al. (Human genetics, 2022, 141, 147–173), common and rare variants were used to define an interpretable machine learning model for predicting COVID-19 severity. First, variants were converted into sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. After that, the Boolean features, selected by these logistic models, were combined into an Integrated PolyGenic Score (IPGS), which offers a very simple description of the contribution of host genetics in COVID-19 severity. IPGS leads to an accuracy of 55%–60% on different cohorts, and, after a logistic regression with both IPGS and age as inputs, it leads to an accuracy of 75%. The goal of this paper is to improve the previous results, using not only the most informative Boolean features with respect to the genetic bases of severity but also the information on host organs involved in the disease. In this study, we generalize the IPGS adding a statistical weight for each organ, through the transformation of Boolean features into “Boolean quantum features,” inspired by quantum mechanics. The organ coefficients were set via the application of the genetic algorithm PyGAD, and, after that, we defined two new integrated polygenic scores ((Formula presented.) and (Formula presented.)). By applying a logistic regression with both IPGS, ((Formula presented.) (or indifferently (Formula presented.)) and age as inputs, we reached an accuracy of 84%–86%, thus improving the results previously shown in Fallerini et al. (Human genetics, 2022, 141, 147–173) by a factor of 10%