Clinical applications of personalized medicine: a new paradigm and challenge

The personalized medicine is an emergent and rapidly developing method of clinical practice that uses new technologies to provide decisions in regard to the prediction, prevention, diagnosis and treatment of disease. The continue evolution of technology and the developments in molecular diagnostics and genomic analysis increased the possibility of an even more understanding and interpretation of the human genome and exome, allowing a "personalized" approach to clinical care, so that the concepts of "Systems Medicine" and "System Biology" are increasingly actual. The purpose of this study is to evaluate the personalized medicine about its indications and benefits, actual clinical applications and future perspectives as well as its issues and health care implications. It was made a careful review of the scientific literature on this field that highlighted the applicability and usefulness of this new medical approach as well as the fact that personalized medicine strategy is even more increasing in numerous fields of applications

Gene variants with suicidal risk in a sample of subjects with chronic migraine and affective temperamental dysregulation

BACKGROUND: Risk factors for suicide are at least partially heritable and functional polymorphisms of targeted genes have been suggested to be implicated in the pathogenesis of this phenomenon. However, other studies examining the association between specific gene variants and suicide revealed inconsistent findings. We aims to evaluate the possible association between MAO-A3, CYP1A2*1F and GNB3 gene variants, hopelessness and suicidal risk in a sample of subjects with chronic migraine and affective temperamental dysregulation. METHODS: 56 women were genotyped for MAO-A3, CYP1A2*1F and GNB3 gene variants. Participants were also assessed using Beck Hopelessness Scale (BHS), the Temperament Evaluation of the Memphis, Pisa, Paris and San Diego-Autoquestionnaire (TEMPS-A), and the Suicidal History Self-Rating Screening Scale (SHSS). RESULTS: Patients with higher total scores on affective dysregulated temperaments are more likely to have higher BHS (11.27 +/- 5.54 vs. 5.73 +/- 3.81; t19.20 = -3.57; p = 9 indicating high levels of hopelessness. No association was found between MAO-A3, CYP1A2*1F and GNB3 gene variants and suicidal risk as assessed by BHS and SHSS. CONCLUSIONS: This study did not sustain the association between MAO-A3, CYP1A2*1F and GNB3 gene variants and increased suicidal risk in patients with chronic migraine and affective temperamental dysregulation. Further studies investigating the gene-environment interaction or focusing on other genetic risk factors involved in suicidal behaviour are needed

Short-term one-lung ventilation does not influence local inflammatory cytokine response after lung resection

Background: One-lung ventilation (OLV) is a ventilation procedure used for pulmonary resection which may results in lung injury. The aim of this study was to evaluate the local inflammatory cytokine response from the dependent lung after OLV and its correlation to VT. The secondary aim was to evaluate the clinical outcome of each patient. Methods: Twenty-eight consecutive patients were enrolled. Ventilation was delivered in volume-controlled mode with a VT based on predicted body weight (PBW). 5 cmH2O positive end-expiratory pressure (PEEP) and FiO20.5 were applied. Bronchoalveolar lavage (BAL) was performed in the dependent lung before and after OLV. The levels of pro-inflammatory interleukins (IL-1α, IL-1β, IL-6, IL-8), tumor necrosis factor alpha (TNFα), vascular endothelial growth factor (VEGF), endothelial growth factor (EGF), monocyte chemoattractant protein-1 (MCP-1) and anti-inflammatory cytokines, such as interleukins (IL-2, IL-4, IL-10) and interferon (IFN-γ), were evaluated. Subgroup analysis: to analyze the VT setting during OLV, all patients were ventilated within a range of 5-10 mL/kg. Thirteen patients, classified as a conventional ventilation (CV) subgroup, received 8-10 mL/kg, while 15 patients, classified as a protective ventilation (PV) subgroup, received 5-7 mL/kg. Results: Cytokine BAL levels after surgery showed no significant increase after OLV, and no significant differences were recorded between the two subgroups. The mean duration of OLV was 64.44±21.68 minutes. No postoperative respiratory complications were recorded. The mean length of stay was for 4.00±1.41 days in the PV subgroup and 4.45±2.07 days in the CV group; no statistically significant differences were recorded between the two subgroups (P=0.511). Conclusions: Localized inflammatory cytokine response after OLV was not influenced by the use of different VT. Potentially, the application of PEEP in both ventilation strategies and the short duration of OLV could prevent postoperative complications

Validation of a small-size pooling approach targeting hospital surveillance of SARS-CoV-2 infection

Recent studies describing the detection of SARS-CoV-2 RNA in pools of 5 to 32 samples reported false negative rates up to 10% for large groups, suggesting that smaller sample pools are a good compromise to increase sample processing capacity while maintaining test reliability. Since 5-sample pools were shown to efficiently detect SARS-CoV-2 RNA in RT-PCR assays, we chose to test and validate this approach using a highthroughput RNA extraction and amplification platform

Degradation rate of 5-fluorouracil in metastatic colorectal cancer. A new predictive outcome biomarker?

BACKGROUND: 5-FU based chemotherapy is the most common first line regimen used for metastatic colorectal cancer (mCRC). Identification of predictive markers of response to chemotherapy is a challenging approach for drug selection. The present study analyzes the predictive role of 5-FU degradation rate (5-FUDR) and genetic polymorphisms (MTHFR, TSER, DPYD) on survival. MATERIALS AND METHODS: Genetic polymorphisms of MTHFR, TSER and DPYD, and the 5-FUDR of homogenous patients with mCRC were retrospectively studied. Genetic markers and the 5-FUDR were correlated with clinical outcome. RESULTS: 133 patients affected by mCRC, treated with fluoropyrimidine-based chemotherapy from 2009 to 2014, were evaluated. Patients were classified into three metabolic classes, according to normal distribution of 5-FUDR in more than 1000 patients, as previously published: poor-metabolizer (PM) with 5-FU-DR ≤ 0,85 ng/ml/106 cells/min (8 pts); normal metabolizer with 0,85 < 5-FU-DR < 2,2 ng/ml/106 cells/min (119 pts); ultra-rapid metabolizer (UM) with 5-FU-DR ≥ 2,2 ng/ml/106 cells/min (6 pts). PM and UM groups showed a longer PFS respect to normal metabolizer group (14.5 and 11 months respectively vs 8 months; p = 0.029). A higher G3-4 toxicity rate was observed in PM and UM, respect to normal metabolizer (50% in both PM and UM vs 18%; p = 0.019). No significant associations between genes polymorphisms and outcomes or toxicities were observed. CONCLUSION: 5-FUDR seems to be significantly involved in predicting survival of patients who underwent 5-FU based CHT for mCRC. Although our findings require confirmation in large prospective studies, they reinforce the concept that individual genetic variation may allow personalized selection of chemotherapy to optimize clinical outcomes

Predicting Dihydropyrimidine Dehydrogenase Deficiency and Related 5-Fluorouracil Toxicity. Opportunities and Challenges of DPYD Exon Sequencing and the Role of Phenotyping Assays

Deficiency of dihydropyrimidine dehydrogenase (DPD), encoded by the DPYD gene, is associated with severe toxicity induced by the anti-cancer drug 5-Fluorouracil (5-FU). DPYD genotyping of four recommended polymorphisms is widely used to predict toxicity, yet their prediction power is limited. Increasing availability of next generation sequencing (NGS) will allow us to screen rare variants, predicting a larger fraction of DPD deficiencies. Genotype−phenotype correlations were investigated by performing DPYD exon sequencing in 94 patients assessed for DPD deficiency by the 5-FU degradation rate (5-FUDR) assay. Association of common variants with 5-FUDR was analyzed with the SNPStats software. Functional interpretation of rare variants was performed by in-silico analysis (using the HSF system and PredictSNP) and literature review. A total of 23 rare variants and 8 common variants were detected. Among common variants, a significant association was found between homozygosity for the rs72728438 (c.1974+75A&gt;G) and decreased 5-FUDR. Haplotype analysis did not detect significant associations with 5-FUDR. Overall, in our sample cohort, NGS exon sequencing allowed us to explain 42.5% of the total DPD deficiencies. NGS sharply improves prediction of DPD deficiencies, yet a broader collection of genotype−phenotype association data is needed to enable the clinical use of sequencing data

A 17-Gene Expression Signature for Early Identification of Poor Prognosis in Clear Cell Renal Cell Carcinoma

: The Identification of reliable Biomarkers able to predict the outcome after nephrectomy of patients with clear cell renal cell carcinoma (ccRCC) is an unmet need. The gene expression analysis in tumor tissues represents a promising tool for better stratification of ccRCC subtypes and patients' evaluation. Methods: In our study we retrospectively analyzed using Next-Generation expression analysis (NanoString), the expression of a gene panel in tumor tissue from 46 consecutive patients treated with nephrectomy for non-metastatic ccRCC at two Italian Oncological Centres. Significant differences in expression levels of selected genes was sought. Additionally, we performed a univariate and a multivariate analysis on overall survival according to Cox regression model. Results: A 17-gene expression signature of patients with a recurrence-free survival (RFS) &lt; 1 year (unfavorable genomic signature (UGS)) and of patients with a RFS &gt; 5 years (favorable genomic signature (FGS)) was identified and resulted in being significantly correlated with overall survival of the patients included in this analysis (HR 51.37, p &lt; 0.0001). Conclusions: The identified Genomic Signatures may serve as potential biomarkers for prognosis prediction of non-metastatic RCC and could drive both follow-up and treatment personalization in RCC management

The Exponential Phase of the Covid-19 Pandemic in Central Italy: An Integrated Care Pathway

The Coronavirus Disease (Covid-19) pandemic is rapidly spreading across the world, representing an unparalleled challenge for health care systems. There are differences in the estimated fatality rates, which cannot be explained easily. In Italy, the estimated case fatality rate was 12.7% in mid-April, while Germany remained at 1.8%. Moreover, it is to be noted that different areas of Italy have very different lethality rates. Due to the complexity of Covid-19 patient management, it is of paramount importance to develop a well-defined clinical workflow in order to avoid the inconsistent management of patients. The Integrated Care Pathway (ICP) represents a multidisciplinary outline of anticipated care to support patient management in the Sant’Andrea Hospital, Rome. The main objective of this pilot study was to develop a new ICP evaluated by care indicators, in order to improve the COVID-19 patient management. The suggested ICP was developed by a multi-professional team composed of different specialists and administrators already involved in clinical and management processes. After a review of current internal practices and published evidences, we identified (1) the activities performed during care delivery, (2) the responsibilities for these activities, (3) hospital structural adaptation needs and potential improvements, and (4) ICP indicators. The process map formed the basis of the final ICP document; 160 COVID-19 inpatients were considered, and the effect of the ICP implementation was evaluated over time during the exponential phase of the COVID-19 pandemic. In conclusion, a rapid adoption of ICP and regular audits of quality indicators for the management of COVID-19 patients might be important tools to improve the quality of care and outcomes

DRD2, DRD3, and HTR2A Single-Nucleotide Polymorphisms Involvement in High Treatment Resistance to Atypical Antipsychotic Drugs

Background: The objective of this study was to investigate the DRD2 rs1800497, rs1799732, rs1801028, DRD3 rs6280, and HTR2A rs6314, rs7997012, and rs6311 single-nucleotide polymorphism (SNP) correlations with resistance to second-generation antipsychotics (SGAs) in a real-world sample of patients with treatment-resistant mental disorders. Methods: We divided 129 participants into a high treatment resistance (HTR) group (current treatment with two SGAs, or clozapine, or classic neuroleptics for a failure of previous SGAs trials) and a low treatment resistance (LTR) group (current treatment with one atypical antipsychotic). We used Next-Generation Sequencing on DNA isolated from peripheral blood samples to analyze the polymorphisms. We performed logistic regression to search for predictors of HTR membership. Results: A diagnosis of schizophrenia significantly predicted the HTR membership compared to other diagnoses. Other predictors were the DRD3 rs6280 C|T (OR = 22.195) and T|T (OR = 18.47) vs. C|C, HTR2A rs7997012 A|G vs. A|A (OR = 6.859) and vs. G|G (OR = 2.879), and DRD2 rs1799732 I|I vs. D|I (OR = 12.079) genotypes. Conclusions: A diagnosis of schizophrenia and the DRD2 rs1799732, DRD3 rs6280, and HTR2A rs7997012 genotypes can predict high treatment resistance to SGAs