Identification of molecular biomarkers in esophageal adenocarcinoma

Esophageal adenocarcinoma (EAC) is a severe cancer that has been on the rise in Western nations over the past few decades. It has a high mortality rate and the 5-year survival rate is only 35%–45%. EAC has been included in a group of tumors with one of the highest rates of copy number alterations (CNAs), somatic structural rearrangements, high mutation frequency, with different mutational signatures, and with epigenetic mechanisms. The vast heterogeneity of EAC mutations makes it challenging to comprehend the biology that underlies tumor onset and development, identify prognostic biomarkers, and define a molecular classification to stratify patients. The only way to resolve the current disagreements is through an exhaustive molecular analysis of EAC. We examined the genetic profile of 164 patients' esophageal adenocarcinoma samples (without chemo-radiotherapy). The included patients did not receive neoadjuvant therapies, which can change the genetic and molecular composition of the tumor. Using next-generation sequencing technologies (NGS) at high coverage, we examined a custom panel of 26 cancer-related genes. Over the entire cohort, 337 variants were found, with the TP53 gene showing the most frequent alteration (67.27%). Poorer cancer-specific survival was associated with missense mutations in the TP53 gene (Log Rank P=0.0197). We discovered HNF1alpha gene disruptive mutations in 7 cases that were also affected by other gene changes. We started to investigate its role in EAC cell lines by silencing HNF1alpha to mimic our EAC cohort and we use Seahorse technique to analyze its role in the metabolism in esophageal cell. No significant changes were found in transfected cell lines. We conclude by finding that a particular class of TP53 mutations (missense changes) adversely impacted cancer-specific survival in EAC. HNF1alpha, a new EAC-mutated gene, was found, but more research is required to fully understand its function as a tumor suppressor gene.

Colic surgery in the equine patient: novel biomarkers, postoperative management, microbiotal influence and epidemiological analysis on the italian territory

The aim of this work was to investigate novel diagnostic and prognostic tools, postoperative treatments and epidemiologic factors impacting the outcome of surgical cases of colic. To make a more accurate diagnosis and establish a prognosis, several biomarkers have been investigated in colic patients. In this study we evaluated peritoneal PCT and blood ADMA and SDMA in SIRS positive and negative colic patients to be used as prognostic biomarkers. Our results highlighted the limits of these biomarkers in detection and the lack of specificity. In fact PCT was not detectable and even if ADMA and SDMA significantly increased in colic horses, they are not diagnostic nor prognostic markers for SIRS. Fluid therapy has been described to be crucial for the outcome of colic patients, nevertheless no guidelines have been established. Overhydration was the common practice in post surgical management. We compared cases with an extended fluid therapy protocol and cases with a restricted protocol. Results showed that survival rate and postoperative complications were similar between the groups, despite costs being significantly lower in the restricted group. The possible correlation between intestinal microbiota and colics has gained interest. In this study, cecal and colonic content from horses undergoing laparotomy were collected, and the microbiota analized. Results showed some differences in microbiota between discharged and non discharged patients, and between strangulating and non strangulating types of colic, that might suggest some influence of hind gut microbiota on the disease. A multicentric study involving three veterinary teaching hospitals on the italian territory was conducted investigating factors affecting postoperative survival and complications in colics. Results showed that the influence of age, PCV, TPP, blood lactate, reflux, type of disease, type of lesion, presence of anastomosis, duration of surgery and surgeons, were in line with literature. Amount of crystalloids used could affected the outcome.

[In search of] Digital biomarkers for objective pain assessment

Pain is a highly complex phenomenon involving intricate neural systems, whose interactions with other physiological mechanisms are not fully understood. Standard pain assessment methods, relying on verbal communication, often fail to provide reliable and accurate information, which poses a critical challenge in the clinical context. In the era of ubiquitous and inexpensive physiological monitoring, coupled with the advancement of artificial intelligence, these new tools appear as the natural candidates to be tested to address such a challenge. This thesis aims to conduct experimental research to develop digital biomarkers for pain assessment. After providing an overview of the state-of-the-art regarding pain neurophysiology and assessment tools, methods for appropriately conditioning physiological signals and controlling confounding factors are presented. The thesis focuses on three different pain conditions: cancer pain, chronic low back pain, and pain experienced by patients undergoing neurorehabilitation. The approach presented in this thesis has shown promise, but further studies are needed to confirm and strengthen these results. Prior to developing any models, a preliminary signal quality check is essential, along with the inclusion of personal and health information in the models to limit their confounding effects. A multimodal approach is preferred for better performance, although unimodal analysis has revealed interesting aspects of the pain experience. This approach can enrich the routine clinical pain assessment procedure by enabling pain to be monitored when and where it is actually experienced, and without the involvement of explicit communication,. This would improve the characterization of the pain experience, aid in antalgic therapy personalization, and bring timely relief, with the ultimate goal of improving the quality of life of patients suffering from pain.

Development of machine learning methods for multi-modal biomarkers detection and integration

In medicine, innovation depends on a better knowledge of the human body mechanism, which represents a complex system of multi-scale constituents. Unraveling the complexity underneath diseases proves to be challenging. A deep understanding of the inner workings comes with dealing with many heterogeneous information. Exploring the molecular status and the organization of genes, proteins, metabolites provides insights on what is driving a disease, from aggressiveness to curability. Molecular constituents, however, are only the building blocks of the human body and cannot currently tell the whole story of diseases. This is why nowadays attention is growing towards the contemporary exploitation of multi-scale information. Holistic methods are then drawing interest to address the problem of integrating heterogeneous data. The heterogeneity may derive from the diversity across data types and from the diversity within diseases. Here, four studies conducted data integration using customly designed workflows that implement novel methods and views to tackle the heterogeneous characterization of diseases. The first study devoted to determine shared gene regulatory signatures for onco-hematology and it showed partial co-regulation across blood-related diseases. The second study focused on Acute Myeloid Leukemia and refined the unsupervised integration of genomic alterations, which turned out to better resemble clinical practice. In the third study, network integration for artherosclerosis demonstrated, as a proof of concept, the impact of network intelligibility when it comes to model heterogeneous data, which showed to accelerate the identification of new potential pharmaceutical targets. Lastly, the fourth study introduced a new method to integrate multiple data types in a unique latent heterogeneous-representation that facilitated the selection of important data types to predict the tumour stage of invasive ductal carcinoma. The results of these four studies laid the groundwork to ease the detection of new biomarkers ultimately beneficial to medical practice and to the ever-growing field of Personalized Medicine.

Anatomical biomarkers of body composition in oncological population: application and development of artificial intelligences

In the Era of precision medicine and big medical data sharing, it is necessary to solve the work-flow of digital radiological big data in a productive and effective way. In particular, nowadays, it is possible to extract information “hidden” in digital images, in order to create diagnostic algorithms helping clinicians to set up more personalized therapies, which are in particular targets of modern oncological medicine. Digital images generated by the patient have a “texture” structure that is not visible but encrypted; it is “hidden” because it cannot be recognized by sight alone. Thanks to artificial intelligence, pre- and post-processing software and generation of mathematical calculation algorithms, we could perform a classification based on non-visible data contained in radiological images. Being able to calculate the volume of tissue body composition could lead to creating clasterized classes of patients inserted in standard morphological reference tables, based on human anatomy distinguished by gender and age, and maybe in future also by race. Furthermore, the branch of “morpho-radiology" is a useful modality to solve problems regarding personalized therapies, which is particularly needed in the oncological field. Actually oncological therapies are no longer based on generic drugs but on target personalized therapy. The lack of gender and age therapies table could be filled thanks to morpho-radiology data analysis application.

Study of the urinary biomarkers of synthetic cannabinoid receptor agonists (SCRAs) for the forensic unequivocal proof of consumption: medico-legal implications for drug abuse prevention

Introduction. Synthetic cannabinoid receptor agonists (SCRAs) represent the widest group of New Psychoactive Substances (NPS) and, around 2021-2022, new compounds emerged on the market. The aims of the present research were to identify suitable urinary markers of Cumyl-CB-MEGACLONE, Cumyl-NB-MEGACLONE, Cumyl-NB-MINACA, 5F-EDMB-PICA, EDMB-PINACA and ADB-HEXINACA, to present data on their prevalence and to adapt the methodology from the University of Freiburg to the University of Bologna. Materials and methods. Human phase-I metabolites detected in 46 authentic urine samples were confirmed in vitro with pooled human liver microsomes (pHLM) assays, analyzed by liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-qToF-MS). Prevalence data were obtained from urines collected for abstinence control programs. The method to study SCRAs metabolism in use at the University of Freiburg was adapted to the local facilities, tested in vitro with 5F-EDMB-PICA and applied to the study of ADB-HEXINACA metabolism. Results. Metabolites built by mono, di- and tri-hydroxylation were recommended as specific urinary biomarkers to monitor the consumption of SCRAs bearing a cumyl moiety. Monohydroxylated and defluorinated metabolites were suitable proof of 5F-EDMB-PICA consumption. Products of monohydroxylation and amide or ester hydrolysis, coupled to monohydroxylation or ketone formation, were recognized as specific markers for EDMB-PINACA and ADB-HEXINACA. The LC-qToF-MS method was successfully adapted to the University of Bologna, as tested with 5F-EDMB-PICA in vitro metabolites. Prevalence data showed that 5F-EDMB-PINACA and EDMB-PINACA were more prevalent than ADB-HEXINACA, but for a limited period. Conclusion. Due to undetectability of parent compounds in urines and to shared metabolites among structurally related compounds, the identification of specific urinary biomarkers as unequivocal proofs of SCRAs consumption remains challenging for forensic laboratories. Urinary biomarkers are necessary to monitor SCRAs abuse and prevalence data could help in establishing tailored strategies to prevent their spreading, highlighting the role for legal medicine as a service to public health.

Identification of outcome-oriented cut-offs for copy number alterations in multiple myeloma: predictive biomarkers with improved prognostic accuracy

Aim of the present study was to develop a statistical approach to define the best cut-off Copy number alterations (CNAs) calling from genomic data provided by high throughput experiments, able to predict a specific clinical end-point (early relapse, 18 months) in the context of Multiple Myeloma (MM). 743 newly diagnosed MM patients with SNPs array-derived genomic and clinical data were included in the study. CNAs were called both by a conventional (classic, CL) and an outcome-oriented (OO) method, and Progression Free Survival (PFS) hazard ratios of CNAs called by the two approaches were compared. The OO approach successfully identified patients at higher risk of relapse and the univariate survival analysis showed stronger prognostic effects for OO-defined high-risk alterations, as compared to that defined by CL approach, statistically significant for 12 CNAs. Overall, 155/743 patients relapsed within 18 months from the therapy start. A small number of OO-defined CNAs were significantly recurrent in early-relapsed patients (ER-CNAs) - amp1q, amp2p, del2p, del12p, del17p, del19p -. Two groups of patients were identified either carrying or not ≥1 ER-CNAs (249 vs. 494, respectively), the first one with significantly shorter PFS and overall survivals (OS) (PFS HR 2.15, p<0001; OS HR 2.37, p<0.0001). The risk of relapse defined by the presence of ≥1 ER-CNAs was independent from those conferred both by R-IIS 3 (HR=1.51; p=0.01) and by low quality (< stable disease) clinical response (HR=2.59 p=0.004). Notably, the type of induction therapy was not descriptive, suggesting that ER is strongly related to patients’ baseline genomic architecture. In conclusion, the OO- approach employed allowed to define CNAs-specific dynamic clonality cut-offs, improving the CNAs calls’ accuracy to identify MM patients with the highest probability to ER. As being outcome-dependent, the OO-approach is dynamic and might be adjusted according to the selected outcome variable of interest.

Progetto e implementazione di software di segmentazione assistita di immagini mediche e predizione di biomarkers

La segmentazione prevede la partizione di un'immagine in aree strutturalmente o semanticamente coerenti. Nell'imaging medico, è utilizzata per identificare, contornandole, Regioni di Interesse (ROI) clinico, quali lesioni tumorali, oggetto di approfondimento tramite analisi semiautomatiche e automatiche, o bersaglio di trattamenti localizzati. La segmentazione di lesioni tumorali, assistita o automatica, consiste nell’individuazione di pixel o voxel, in immagini o volumi, appartenenti al tumore. La tecnica assistita prevede che il medico disegni la ROI, mentre quella automatica è svolta da software addestrati, tra cui i sistemi Computer Aided Detection (CAD). Mediante tecniche di visione artificiale, dalle ROI si estraggono caratteristiche numeriche, feature, con valore diagnostico, predittivo, o prognostico. L’obiettivo di questa Tesi è progettare e sviluppare un software di segmentazione assistita che permetta al medico di disegnare in modo semplice ed efficace una o più ROI in maniera organizzata e strutturata per futura elaborazione ed analisi, nonché visualizzazione. Partendo da Aliza, applicativo open-source, visualizzatore di esami radiologici in formato DICOM, è stata estesa l’interfaccia grafica per gestire disegno, organizzazione e memorizzazione automatica delle ROI. Inoltre, è stata implementata una procedura automatica di elaborazione ed analisi di ROI disegnate su lesioni tumorali prostatiche, per predire, di ognuna, la probabilità di cancro clinicamente non-significativo e significativo (con prognosi peggiore). Per tale scopo, è stato addestrato un classificatore lineare basato su Support Vector Machine, su una popolazione di 89 pazienti con 117 lesioni (56 clinicamente significative), ottenendo, in test, accuratezza = 77%, sensibilità = 86% e specificità = 69%. Il sistema sviluppato assiste il radiologo, fornendo una seconda opinione, non vincolante, adiuvante nella definizione del quadro clinico e della prognosi, nonché delle scelte terapeutiche.

A Putative Otu Domain-containing Protein 1 Deubiquitinating Enzyme Is Differentially Expressed In Thyroid Cancer And Identifies Less-aggressive Tumours.

This study aimed to identify novel biomarkers for thyroid carcinoma diagnosis and prognosis. We have constructed a human single-chain variable fragment (scFv) antibody library that was selected against tumour thyroid cells using the BRASIL method (biopanning and rapid analysis of selective interactive ligands) and phage display technology. One highly reactive clone, scFv-C1, with specific binding to papillary thyroid tumour proteins was confirmed by ELISA, which was further tested against a tissue microarray that comprised of 229 thyroid tissues, including: 110 carcinomas (38 papillary thyroid carcinomas (PTCs), 42 follicular carcinomas, 30 follicular variants of PTC), 18 normal thyroid tissues, 49 nodular goitres (NG) and 52 follicular adenomas. The scFv-C1 was able to distinguish carcinomas from benign lesions (P=0.0001) and reacted preferentially against T1 and T2 tumour stages (P=0.0108). We have further identified an OTU domain-containing protein 1, DUBA-7 deubiquitinating enzyme as the scFv-binding antigen using two-dimensional polyacrylamide gel electrophoresis and mass spectrometry. The strategy of screening and identifying a cell-surface-binding antibody against thyroid tissues was highly effective and resulted in a useful biomarker that recognises malignancy among thyroid nodules and may help identify lower-risk cases that can benefit from less-aggressive management.

Avoiding Pitfalls Of Intraoperative Peripheral Endovascular Surgery With The Aid Of Osirix: Expanding The Use Of Virtual Fluoroscopy.

We have shown how the analysis of the angiotomography reconstruction through OsiriX program has assisted in endovascular perioperative programming. We presented its application in situations when an unexpected existence of metallic overlapping artifact (orthopedic osteosynthesis) compromised the adequate visualization of the arterial lesion during the procedure. Through manipulation upon OsiriX software, with assistance of preview under virtual fluoroscopy, it was possible to obtain the angles that would avoid this juxtaposition. These angles were reproduced in the C-arm, allowing visualization of the occluded segment, reducing the need for repeated image acquisitions and contrast overload, allowing the continuation of the procedure.

Applications Of Visual Evoked Potentials And Fourier-domain Optical Coherence Tomography In Parkinson's Disease: A Controlled Study.

The goal of this cross-sectional observational study was to quantify the pattern-shift visual evoked potentials (VEP) and the thickness as well as the volume of retinal layers using optical coherence tomography (OCT) across a cohort of Parkinson's disease (PD) patients and age-matched controls. Forty-three PD patients and 38 controls were enrolled. All participants underwent a detailed neurological and ophthalmologic evaluation. Idiopathic PD cases were included. Cases with glaucoma or increased intra-ocular pressure were excluded. Patients were assessed by VEP and high-resolution Fourier-domain OCT, which quantified the inner and outer thicknesses of the retinal layers. VEP latencies and the thicknesses of the retinal layers were the main outcome measures. The mean age, with standard deviation (SD), of the PD patients and controls were 63.1 (7.5) and 62.4 (7.2) years, respectively. The patients were predominantly in the initial Hoehn-Yahr (HY) disease stages (34.8% in stage 1 or 1.5, and 55.8 % in stage 2). The VEP latencies and the thicknesses as well as the volumes of the retinal inner and outer layers of the groups were similar. A negative correlation between the retinal thickness and the age was noted in both groups. The thickness of the retinal nerve fibre layer (RNFL) was 102.7 μm in PD patients vs. 104.2 μm in controls. The thicknesses of retinal layers, VEP, and RNFL of PD patients were similar to those of the controls. Despite the use of a representative cohort of PD patients and high-resolution OCT in this study, further studies are required to establish the validity of using OCT and VEP measurements as the anatomic and functional biomarkers for the evaluation of retinal and visual pathways in PD patients.

Ten Years Of Proteomics In Multiple Sclerosis.

Multiple sclerosis, which is the most common cause of chronic neurological disability in young adults, is an inflammatory, demyelinating, and neurodegenerative disease of the CNS, which leads to the formation of multiple foci of demyelinated lesions in the white matter. The diagnosis is based currently on magnetic resonance image and evidence of dissemination in time and space. However, this could be facilitated if biomarkers were available to rule out other disorders with similar symptoms as well as to avoid cerebrospinal fluid analysis, which requires an invasive collection. Additionally, the molecular mechanisms of the disease are not completely elucidated, especially those related to the neurodegenerative aspects of the disease. The identification of biomarker candidates and molecular mechanisms of multiple sclerosis may be approached by proteomics. In the last 10 years, proteomic techniques have been applied in different biological samples (CNS tissue, cerebrospinal fluid, and blood) from multiple sclerosis patients and in its experimental model. In this review, we summarize these data, presenting their value to the current knowledge of the disease mechanisms, as well as their importance in identifying biomarkers or treatment targets.

Improvement Of The Physical Performance Is Associated With Activation Of No/pgc-1α/mttfa Signaling Pathway And Increased Protein Expressions Of Electron Transport Chain In Gastrocnemius Muscle From Rats Supplemented With L-arginine.

To examine the influence of l-arginine supplementation in combination with physical training on mitochondrial biomarkers from gastrocnemius muscle and its relationship with physical performance. Male Wistar rats were divided into four groups: control sedentary (SD), sedentary supplemented with l-arginine (SDLA), trained (TR) and trained supplemented with l-arginine (TRLA). Supplementation of l-arginine was administered by gavage (62.5mg/ml/day/rat). Physical training consisted of 60min/day, 5days/week, 0% grade, speed of 1.2km/h. The study lasted 8weeks. Skeletal muscle mitochondrial enriched fraction as well as cytoplasmic fractions were obtained for Western blotting and biochemical analyses. Protein expressions of transcriptor coactivator (PGC-1α), transcriptor factors (mtTFA), ATP synthase subunit c, cytochrome oxidase (COXIV), constitutive nitric oxide synthases (eNOS and nNOS), Cu/Zn-superoxide dismutase (SOD) and manganese-SOD (Mn-SOD) were evaluated. We also assessed in plasma: lipid profile, glycemia and malondialdehyde (MDA) levels. The nitrite/nitrate (NOx(-)) levels were measured in both plasma and cytosol fraction of the gastrocnemius muscle. 8-week l-arginine supplementation associated with physical training was effective in promoting greater tolerance to exercise that was accompanied by up-regulation of the protein expressions of mtTFA, PGC-1α, ATP synthase subunit c, COXIV, Cu/Zn-SOD and Mn-SOD. The upstream pathway was associated with improvement of NO bioavailability, but not in NO production since no changes in nNOS or eNOS protein expressions were observed. This combination would be an alternative approach for preventing cardiometabolic diseases given that in overt diseases a profound impairment in the physical performance of the patients is observed.

Circulating Levels Of Chemokines In Psoriasis.

Chemokines may contribute to local and systemic inflammation in patients with psoriasis. Previous studies have demonstrated the importance of chemokine ligands and receptors in the recruitment of T cells into psoriatic lesional skin and synovial fluid. The aim of this study was to evaluate the levels of Th1-related chemokines in psoriasis and to investigate any association with disease severity. We quantified serum levels of CXCL9, CXCL10 and CXCL16 and the frequencies of CD4+CXCR3+ T lymphocytes through ELISA and flow cytometry, respectively. A total of 38 patients with psoriasis and 33 controls were included. There were no significant differences in chemokine levels between psoriasis and control groups. Patients with psoriatic arthritis had lower median level of CXCL10 when compared with controls (p=0.03). There were no significant correlations between serum chemokines analyzed and disease severity. Frequencies of CD4+CXCR3+ T cells were lower in patients with psoriasis than in controls (p<0.01). A sensitivity analysis excluding patients on systemic therapy yielded similar results. Serum concentrations of CXCL9, CXCL10 and CXCL16 were not increased in the psoriasis group or correlated with disease severity. Systemic levels of chemokine ligands do not seem to be sensitive biomarkers of disease activity or accurate parameters to predict response to therapy. Frequencies of CD4+CXCR3+ T cells were decreased in the peripheral blood of psoriasis patients, possibly due to recruitment to inflammatory lesions.

Serum Bdnf Levels Are Not Reliable Correlates Of Neurodegeneration In Ms Patients.

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