Author Correction: Aldo-keto reductase 1C2 (AKR1C2) as the second gene associated to non-syndromic primary lipedema: investigating activating mutation or overexpression as causative factors

Correction to: Eur Rev Med Pharmacol Sci 2023; 27 (6 Suppl): 127-136-DOI: 10.26355/eurrev_202312_34697 After publication and following some post-publication concerns, the authors have applied the following corrections to the galley proof. -       The conflict of interest section has been amended as follows: J. Kaftalli and G. Marceddu are employees at MAGI EUREGIO. K. Donato is employee at MAGI EUREGIO and MAGISNAT. M. Bertelli is president of MAGI EUREGIO, MAGISNAT, and MAGI's LAB. G. Bonetti, K. Dhuli, A. Macchia, and P.E. Maltese are employees at MAGI's LAB. M. Bertelli, P.E. Maltese, K. Louise Herbst, Sa. Michelini, Se. Michelini, and P. Chiurazzi are patent inventors (US20220362260A1). M. Bertelli, P.E. Maltese, G. Marceddu are patent inventors (US20230173003A1). M. Bertelli, K. Dhuli and P.E. Maltese are patent inventors (WO2022079498A1). M. Bertelli, P.E. Maltese, Sa. Michelini, Se. Michelini, P. Chiurazzi, K. Louise Herbst, J. Kaftalli, K. Donato, and A. Bernini are patent applicants (Application Number 18/516,241). M. Bertelli, K. Donato, P. Chiurazzi, G. Marceddu, K. Dhuli, G. Bonetti and J. Kaftalli are patent applicants (Application Number: 18/466.879). M. Bertelli, G. Bonetti, G. Marceddu, K. Donato, K. Dhuli, J. Kaftalli, Sa. Michelini, and K. Louise Herbst are patent applicants (Application Number 63/495,155). The remaining authors have no conflict of interest to disclose. -       Figure 5 has been modified as follows to better distinguish outliers: -       The legend of Figure 5 has to be modified as follows: Relative expression of AKR1C1 and AKR1C3 in different groups (CTR = non affected controls, L = lipedema patients without overexpression of AKR1C2, L-over = Lipedema patients with overexpression of AKR1C2), showing that lipedema patients expressed AKR1C1 and AKR1C3 levels similar to the control group. Outliers are reported as black triangles. There are amendments to this paper. The Publisher apologizes for any inconvenience this may cause. https://www.europeanreview.org/article/34697.

Author Correction: Genetic variants identified in novel candidate genes for anorexia nervosa and analysis of molecular pathways for diagnostic applications

Correction to: Eur Rev Med Pharmacol Sci 2023; 27 (6 Suppl): 77-88-DOI: 10.26355/eurrev_202312_34692 After publication and following some post-publication concerns, the authors have applied the following corrections to the galley proof. The conflict of interest section has been amended as follows: K. Donato is employee at MAGI EUREGIO and MAGISNAT. G. Marceddu is employee at MAGI EUREGIO. M. Bertelli is president of MAGI EUREGIO, MAGISNAT, and MAGI's LAB. M.C. Medori, A. Macchia, S. Cecchin, C. Micheletti, K. Dhuli, G. Madeo, G. Bonetti are employees at MAGI's LAB. M. Bertelli, M.R. Ceccarini, and P. Chiurazzi are patent inventors (US20220362260A11). M. Bertelli, P.E. Maltese, G. Marceddu, and S. Cecchin are patent inventors (US20230173003A1). M. Bertelli, K. Dhuli, and P.E. Maltese are patent inventors (WO2022079498A1). M. Bertelli, K. Donato, M.C. Medori, M.R. Ceccarini, T. Beccari, P. Chiurazzi, C. Micheletti, K. Dhuli, G. Bonetti, G. Marceddu are patent applicants (Application Number: 18/466.879). The remaining authors have no conflict of interest to disclose. Since the current study shares the same NGS panel for the genetic analysis as the study cited in Ref. 5 (Ceccarini MR, Precone V, Manara E, Paolacci S, Maltese PE, Benfatti V, Dhuli K, Donato K, Guerri G, Marceddu G, Chiurazzi P, Dalla Ragione L, Beccari T, Bertelli M. A next generation sequencing gene panel for use in the diagnosis of anorexia nervosa. Eat Weight Disord 2022; 27: 1869-1880), the authors amend the following sentence: "A subset comprising 163 genes from a dedicated Next-Generation Sequencing (NGS) panel was analyzed5" in "A subset comprising 163 genes from a dedicated Next-Generation Sequencing (NGS) panel, previously used in the study by Ceccarini et al5, was analyzed". The authors clarify that the analyzed patients of the two articles are completely independent. To clarify the data reported in Table II, the authors amend the following sentence: "Genetic variants identified in the AN population are reported in Table II." In "The genomic sequencing NGS was performed in all 135 patients recruited in the study. After obtaining the raw data, based on the ACMG guidelines (https://www.acmg.net/ACMG/Medical-Genetics-Practice-Resources/Practice-Guidelines.aspx), the results were filtered, and Table II reports the variants considered Pathogenic (P), likely pathogenic (LP), and Variable with Uncertain Significance (VUS), 61 patients in total". Consequently, to improve clarity, the legend of Table II has been amended as follows: Genetic variants identified in 61 patients out of the total 135 patients analyzed by NGS. There are amendments to this paper. The Publisher apologizes for any inconvenience this may cause. https://www.europeanreview.org/article/34692.

Aldo-keto reductase 1C2 (AKR1C2) as the second gene associated to non-syndromic primary lipedema: investigating activating mutation or overexpression as causative factors

OBJECTIVE

Lipedema is a debilitating chronic condition predominantly affecting women, characterized by the abnormal accumulation of fat in a symmetrical, bilateral pattern in the extremities, often coinciding with hormonal imbalances.

PATIENTS AND METHODS

Despite the conjectured role of sex hormones in its etiology, a definitive link has remained elusive. This study explores the case of a patient possessing a mutation deletion within the C-terminal region of Aldo-keto reductases Member C2 (AKR1C2), Ser320PheTer2, that could lead to heightened enzyme activity. A cohort of 19 additional lipedema patients and 2 additional affected family members14 were enrolled in this study. The two additional affected family members are relatives of the patient with the AKR1C1 L213Q variant, which is included in the 19 cohorts and described in literature.

RESULTS

Our investigation revealed that AKR1C2 was overexpressed, as quantified by qPCR, in 5 out of 21 (24%) lipedema patients who did not possess mutations in the AKR1C2 gene. Collectively, these findings implicate AKR1C2 in the pathogenesis of lipedema, substantiating its causative role.

CONCLUSIONS

This study demonstrates that the activating mutation in the enzyme or its overexpression is a causative factor in the development of lipedema. Further exploration and replication in diverse populations will bolster our understanding of this significant connection.

Linking pathogenic and likely pathogenic gene variants to long-COVID symptoms

OBJECTIVE

Long-COVID is a clinical syndrome characterized by the presence of symptoms related to SARS-CoV-2 infection that persist for at least four weeks after recovery from COVID-19. Genetics have been proposed to play an important role in long-COVID syndrome onset. This study aimed to identify genetic pathogenetic and likely pathogenetic causative variants of Mendelian genetic diseases in patients with Long-COVID syndrome. Additionally, we aimed to establish an association between these genetic variants and the clinical symptoms manifested during long-COVID syndrome.

PATIENTS AND METHODS

95 patients affected by long-COVID syndrome were analyzed with a Next-Generation Sequencing (NGS) panel comprising 494 genes. The analyzed genes and the symptoms of the patients collected with an ad-hoc questionnaire were divided into four groups (cardiological, respiratory, immunological, and neurological). Finally, a statistical analysis comprising descriptive statistics, classification based on reported symptoms, and comparative analysis against a control group of healthy individuals was conducted.

RESULTS

12 patients resulted positive for genetic testing with an autosomal dominance (8) or autosomal recessive (4) inheritance, showing a higher prevalence of cardiovascular genetic diseases (9) in the analyzed cohort compared to the normal population. Moreover, the onset of the long-COVID syndrome and its cardiovascular manifestations was compliant with the onset reported in the literature for the identified genetic diseases, suggesting that COVID-19 could manifest late-onset genetic diseases associated with their appearance. Apart from the 12 positive patients, 57 were healthy carriers of genetic diseases. Analyzing the whole cohort, a statistical correlation between prevalent symptomatology and the gene class was established, suggesting an association between the genetic susceptibility of an individual and the possibility of developing specific long-COVID syndrome symptoms, especially cardiovascular symptoms. Furthermore, 17 genetic variants were identified in CFTR. Finally, we identified genetic variants in IFNAR2 and POLG, supporting their respective involvement in inflammation and mitochondria mechanisms, correlated with long-COVID syndrome according to literature data.

CONCLUSIONS

This study proposed COVID-19 to act as a manifest of underlying late-onset genetic diseases Mendelian associated with carrier status. Moreover, according to our results, mutations in cardiological genes are more present in patients who show cardiological symptoms during the syndrome. This underscores the necessity for cardiological investigation and genetic screening in long-COVID patients to address existing or potential clinical implications.

MAGI-Dock: a PyMOL companion to Autodock Vina

Molecular docking simulation of small molecule drugs to macromolecules is valuable in structural biology and medicinal chemistry research. Its spread is supported by freely available software and databases. Like many resources in the free domain, docking software is command-line based, which comes to a limitation when defining the volume encompassing an active site, the so-called docking box. The box center and size, usually specified as cartesian coordinates, can be adjusted to correctly cover the active site only with a third-party molecular graphics program compatible with the docking input/output files, which reduces the choice to a few options. Moreover, the additional staff training may hamper the adoption of such software, e.g., in an enterprise environment. We exposed the functionality of Autodock and Autodock Vina into a graphical user interface extending upon that of PyMOL. Both the functionality of PyMOL and Autodock are merged, synergizing the capabilities of each program. To overcome such limitations, here we present MAGI-Dock. This graphical user interface combines the power of two of the most used free software for docking and graphics, Autodock Vina and PyMOL. MAGI-Dock is a free open-source software available under the GPL and can be downloaded from https://github.com/gjonwick/MAGI-Dock. The coupling of Autodock Vina with PyMOL through a graphical interface removes the molecular modeling limitations that come with Autodock. Therefore, MAGI-Dock could be conducive to lowering the learning curve for molecular docking simulation, with benefits for trainees in both academia and enterprise environments.

Genetic variants identified in novel candidate genes for anorexia nervosa and analysis of molecular pathways for diagnostic applications

OBJECTIVE

Anorexia nervosa (AN) is a severe psychiatric disorder characterized by an intense fear of gaining weight, a relentless pursuit of thinness, and a distorted body image. Recent research highlights the substantial contribution of genetics to AN's etiology, with genes like BDNF, SLC6A4, and DRD2 implicated. However, a comprehensive genetic test for AN diagnosis is lacking. This study aims to elucidate the biological foundations of AN, examining variants in genes associated with syndromic forms, rare variants in AN patients, and candidate genes from GWAS studies, murine models, or established molecular pathways.

MATERIALS AND METHODS

The study involved 135 AN patients from Italy, diagnosed based on DSM-V criteria. A specialized Next-Generation Sequencing panel targeting 163 genes was designed. Sequencing was performed on an Illumina MiSeq System, and variants were analyzed using bioinformatics tools. Data on clinical parameters, exercise habits, and AN types were collected.

RESULTS

The AN cohort, predominantly female, exhibited diverse clinical characteristics. Our analysis identified gene variants associated with syndromic forms of AN, such as STRA6, NF1, MAT1A, and ABCC6. Variants were also found in known AN-related genes (CD36, DRD4, GCKR, GHRL, GRIN3B, GPR55, LEPR) and in other 16 candidate genes (A2M, AEBP1, ABHD4, ACBD7, CNTNAP, GFRAL, GRIN2D, LIPE, LMNA, NMU, PDE3B, POMC, RYR1, TNXB, TYK2, VPS13B), highlighting the complexity of AN's genetic landscape. The endocannabinoid and dopamine pathways play crucial roles. Skeletal muscle-related genes and appetite-regulating hormones also revealed potential connections. Adipogenesis-related genes suggest AN's association with subcutaneous adipose tissue deficiency.

CONCLUSIONS

This study provides comprehensive insights into the genetic underpinnings of AN, emphasizing the importance of multiple pathways. The identified variants contribute.

Correlation between COVID-19 and air pollution: the effects of PM2.5 and PM10 on COVID-19 outcomes

OBJECTIVE

Given its effects on long-term illnesses, like heart problems and diabetes, air pollution may be among the reasons that led COVID-19 to get worse and kill a larger number of people. Experiments have shown that breathing in polluted air weakens the immune system, making it easier for viruses to enter the body and grow. Viruses may be able to survive in the air by interacting in complex ways with particles and gases. These interactions depend on the air's chemical makeup, the particles' electric charges, and environmental conditions like humidity, UV light, and temperature. Moreover, exposure to UV rays and air pollution may reduce the organism's production of antimicrobial molecules, thus supporting viral infections. More epidemiological studies are needed to determine what effects air pollution has on COVID-19. In this review, we will discuss how air pollutants such as PM2.5 and PM10 contribute to the transmission of COVID-19.

MATERIALS AND METHODS

We have used nine target cities in the Tuscany region to verify this certainty, and in all these cases, the air pollution factors were found to be strongly correlated with COVID-19 cases. For each city, we applied a multivariate analysis and found an appropriate model that better fits the data.

RESULTS

This review underlines that both short-term and long-term exposure to air pollution may be crucial exasperating factors for SARS-CoV-2 transmission and COVID-19 severity and lethality. The statistical analysis concludes that air pollution should be accounted for as a possible risk factor in future COVID-19 investigations, and it should be avoided as much as possible by the general population.

CONCLUSIONS

Our research highlighted the correlation between COVID-19 and air pollution. Reducing air pollution exposure should be one of the first measures against COVID-19 spread.

AKR1C1 and hormone metabolism in lipedema pathogenesis: a computational biology approach

OBJECTIVE

Lipedema is an autosomal dominant genetic disease that mainly affects women. It is characterized by excess deposition of subcutaneous adipose tissue, pain, and anxiety. The genetic and environmental etiology of lipedema is still largely unknown. Although considered a rare disease, this pathology has been suggested to be underdiagnosed or misdiagnosed as obesity or lymphedema. Steroid hormones seem to be involved in the pathogenesis of lipedema. Indeed, aldo-keto reductase family 1 member C1 (AKR1C1), a gene coding for a protein involved in steroid hormones metabolism, was the first proposed to be correlated with lipedema.

PATIENTS AND METHODS

In this study, we employed a molecular dynamics approach to assess the pathogenicity of AKR1C1 genetic variants found in patients with lipedema. Moreover, we combined information theory and structural bioinformatics to identify AKR1C1 polymorphisms from the gnomAD database that could predispose to the development of lipedema.

RESULTS

Three genetic variants in AKR1C1 found in patients with lipedema were disruptive to the protein's function. Furthermore, eight AKR1C1  variants found in the general population could predispose to the development of lipedema.

CONCLUSIONS

The results of this study provide evidence that AKR1C1 may be a key gene in lipedema pathogenesis, and that common polymorphisms could predispose to lipedema development.

Omics sciences and precision medicine in pancreas cancer

Abstract

Pancreatic cancer is a leading cause of death worldwide, associated with poor prognosis outcomes and late treatment interventions. The pathological nature and extreme tissue heterogeneity of this disease has hampered all efforts to correctly diagnose and treat it. Omics sciences and precision medicine have revolutionized our understanding of pan-creatic cancer, providing a new hope for patients suffering from this devastating disease. By analyzing large-scale biological data sets and developing personalized treatment strategies, researchers and clinicians are working together to improve patient outcomes and ultimately find a cure for pancreatic cancer.

X-linked genodermatoses from diagnosis to tailored therapy

Background

Genodermatoses are rare heterogeneous genetic skin diseases with multiorgan involvement. They severely impair an individual's well-being and can also lead to early death.

Methods

During the progress of this review, we have implemented a targeted research approach, diligently choosing the most relevant and exemplary articles within the subject matter. Our method entailed a systematic exploration of the scientific literature to ensure a compre-hensive and accurate compilation of the available sources.

Results

Among genodermatoses, X-linked ones are of particular importance and should always be considered when pediatric males are affected. Regardless of other syndromic forms without prevalence of skin symptoms, X-linked genodermatoses can be classified in three main groups: keratinization defects, pigmentation defects, and inflammatory skin diseases. Typical examples are dyskeratosis congenita, keratosis follicularis spinulosa decalvans, hypohidrotic ectodermal dysplasia, chondrodysplasia punctata, hypohidrotic ectodermal dysplasia, incontinentia pigmenti, chronic granulomatous disease, CHILD syndrome and ichthyosis. In this field, genetic diagnosis of the specific disease is important, also considering that numerous clinical trials of orphan drugs and genetic therapies are being proposed for these rare genetic diseases.

Conclusions

Thus, this chapter starts from clinical to molecular testing and ends with a review of all clinical trials on orphan drugs and gene therapy for genodermatoses.

Omics sciences and precision medicine in glioblastoma

Abstract

Glioblastoma is a highly aggressive and malignant type of brain cancer with a poor prognosis, despite current treatment options of surgery, radiation therapy, and chemotherapy. These treatments have limitations due to the aggressive nature of the cancer and the difficulty in completely removing the tumor without damaging healthy brain tissue. Personalized medicine, using genomic profiling to tailor treatment to the patient's specific tumor, and immunotherapy have shown promise in clinical trials. The blood-brain barrier also poses a challenge in delivering treatments to the brain, and researchers are exploring various approaches to bypass it. More effective, personalized treatment approaches are needed to improve outcomes for glioblastoma patients. This tumor is studied using genomics, transcriptomics, and proteomics techniques, to better understand its underlying molecular mechanisms. Recent studies have used these techniques to identify potential therapeutic targets, molecular subtypes, and heterogeneity of tumor cells. Advancements in omics sciences have improved our understanding of glioblastoma biology, and precision medicine approaches have impli-cations for more accurate diagnoses, improved treatment outcomes, and personalized preventive care. Precision medicine can match patients with drugs that target specific genetic mutations, improve clinical trials, and identify individuals at higher risk for certain diseases. Precision medicine, which involves customizing medical treatment based on an individual's genetic makeup, lifestyle, and environmental factors, has shown promise in improving treatment outcomes for glioblastoma patients. Identifying biomarkers is essential for patient stratification and treatment selection in precision medicine approaches for glioblastoma, and several biomarkers have shown promise in predicting patient response to treatment. Targeted therapies are a key component of precision medicine approaches in glioblastoma, but there is still a need to improve their effectiveness. Technical challenges, such as sample quality and availability, and challenges in analyzing and interpreting large amounts of data remain significant obstacles in omics sciences and precision medicine for glioblastoma. The clinical implementation of precision medicine in glioblastoma treatment faces challenges related to patient selection, drug development, and clinical trial design, as well as ethical and legal considerations related to patient privacy, informed consent, and access to expensive treatments.

Omics sciences and precision medicine in prostate cancer

Abstract

In the last decade, Prostate Cancer (PCa) has emerged as the second most prevalent and serious medical condition, and is considered one of the leading factors contributing to global mortality rates. Several factors (genetic as well as environmental) contribute to its development and seriousness. Since the disease is usually asymptomatic at early stages, it is typically misdiagnosed or over-diagnosed by the diagnostic procedures currently in use, leading to improper treatment. Effective biomarkers and diagnostic techniques are desperately needed in clinical settings for better management of PCa patients. Studies integrating omics sciences have shown that the accuracy and dependability of diagnostic and prognostic evaluations have increased because of the use of omics data; also, the treatment plans using omics can be facilitated by personalized medicine. The present review emphasizes innovative multi-omics methodologies, encompassing proteomics, genomics, microbiomics, metabolomics, and transcriptomics, with the aim of comprehending the molecular alterations that trigger and contribute to PCa. The review shows how early genomic and transcriptomic research has made it possible to identify PCa-related genes that are controlled by tumor-relevant signaling pathways. Proteomic and metabolomic analyses have recently been integrated, advancing our understanding of the complex mechanisms at play, the multiple levels of regulation, and how they interact. By applying the omics approach, new vulnerabilities may be discovered, and customized treatments with improved efficacy will soon be accessible.

The Role of Olive Tree Polyphenols in the Prevention of COVID-19: A Scoping Review, part 1

Abstract

The global COVID-19 outbreak, started in December 2019, resulted in severe financial losses and extraordinary health crises. Finding a potent and secure medication candidate to treat SARS-CoV-2 infection and its symptoms is still an urgent global need. After reviewing previous studies, olive leaves, being rich in polyphenolic compounds (a large class of bioactive substances naturally found in plants), were proposed as a viable co-therapy supplement to treat and improve clinical symptoms in COVID-19 patients. It has long been known that olive tree polyphenols-such as oleuropein, hydroxytyrosol, verbascoside, as well as triterpenoids like maslinic, ursolic, and oleanolic acids-have anti-inflammatory and multitarget antiviral effects on several virus families, and they could be one of the reasons of the beneficial effects of the Mediterranean diet against COVID-19. Thus, olive tree poly-phenols were tested in silico and in vitro for preventing SARS-CoV-2 infection, claiming that they have beneficial effects. Nevertheless, there is still a small number of research studies on this topic. The aim of this scoping review is to provide more information and offer an opinion on the feasibility of using olive tree polyphenols as a springboard for the creation of innovative natural remedies against this viral illness, ultimately planning future relevant studies.

Omics sciences and precision medicine in breast and ovarian cancer

Background

Human breast carcinoma is a complex disease, affecting 1 in 8 women worldwide. The seriousness of the disease increases when the definite cause of the disease remains obscure, thus making prognosis challenging. Researchers are emphasizing on adapting more advanced and targeted therapeutic approaches to address the multifaceted impacts of the disease. Hence, modern multi-omics systems have gained popularity among clinicians, as they offer insights into the genomic, pharmacogenomic, metabolomic, and microbiomic factors, thus allowing researchers to develop targeted and personalized approaches for breast cancer prevention and early detection, and eventually improving patient outcomes.

Aim

The primary focus of this study is to elucidate, through the integration of multi-omics research findings, the inherent molecular origins of diverse subtypes of breast cancer and to evaluate the effectiveness of these findings in reducing breast cancer-related mortalities.

Methods

Thorough investigation was conducted by reviewing reputable and authoritative medical journals, e-books, and online databases dedicated to cancer research. The Mendelian inheritance in man database (OMIM) was used to scrutinize specific genes and their respective loci associated with the development of different types of breast cancer.

Results

Our present research revealed the holistic picture of sundry molecular, genomic, pharmacogenomic, metabolomic, and microbiomic features of breast cancer. Such findings, like genetic alterations in highly penetrant genes, plus metabolomic and microbiomic signatures of breast cancer, unveil valuable insights and show great potential for multi-omics research in breast oncology.

Conclusion

Further research in omics sciences pertaining to breast cancer are at the forefront of shaping precise treatment and bolstering patient survival.

Omics sciences and precision medicine in colon cancer

Abstract

Colon cancer presents a complex pathophysiological landscape, which poses a significant challenge to the precise prediction of patient prognosis and treatment response. However, the emergence of omics sciences such as genomics, transcriptomics, proteomics, and metabolomics has provided powerful tools to identify molecular alterations and pathways involved in colon cancer development and progression. To address the lack of literature exploring the intersection of omics sciences, precision medicine, and colon cancer, we conducted a comprehensive search in ScienceDirect and PubMed databases. We included systematic reviews, reviews, case studies, clinical studies, and randomized controlled trials that were published between 2015-2023. To refine our search, we excluded abstracts and non-English studies. This review provides a comprehensive summary of the current understanding of the latest developments in precision medicine and omics sciences in the context of colon cancer. Studies have identified molecular subtypes of colon cancer based on genomic and transcrip-tomic profiles, which have implications for prognosis and treatment selection. Furthermore, precision medicine (which involves tailoring treatments, based on the unique molecular characteristics of each patient's tumor) has shown promise in improving outcomes for colon cancer patients. Omics sciences and precision medicine hold great promise for identifying new therapeutic targets and developing more effective treatments for colon cancer. Although not strictly designed as a systematic review, this review provides a readily accessible and up-to-date summary of the latest developments in the field, highlighting the challenges and opportunities for future research.

Omics sciences and precision medicine in lung cancer

Abstract

Lung cancer is a complex disease, with a wide range of genetic alterations and clinical presentations. Understanding the natural and clinical history of the disease is crucial for developing effective diagnostic and treatment strategies. Omics approaches, such as genomics, transcriptomics, proteomics, and metabolomics, have emerged as powerful tools for understanding the molecular mechanisms underlying lung cancer and for identifying novel biomarkers and therapeutic targets. These approaches enable researchers to examine the entire genome, transcriptome, proteome, or metabolome of a cell or tissue, providing a comprehensive view of the biological processes involved in lung cancer development and progression. Targeted therapies that address specific genetic mutations and pathways hold promise for improving the diagnosis and treatment of this disease.

Omics sciences and precision medicine in kidney cancer

Abstract

In the last decade, renal carcinoma has become more prevalent in European and North American regions. Kidney tumors are usually categorized based on histological features, with renal cell carcinoma being the most common subtype in adults. Despite conventional diagnostic and therapeutic strategies, a rise in cancer incidence and recurrence necessitates a fresh approach to diagnosing and treating kidney cancer. This review focuses on novel multi-omics approaches, such as genomics, transcriptomics, proteomics, metabolomics, and microbiomics, to better understand the molecular and clinical features of renal cell carcinoma. Studies integrating omics sciences have shown early promise in enhancing prognostic and therapeutic outcomes for various kidney cancer subtypes and providing insight into fundamental pathophysiological mechanisms occurring at different molecular levels. This review highlights the importance of utilizing omics sciences as a revolutionary concept in diagnostics and therapeutics and the clinical implications of renal cell carcinoma. Finally, the review presents the most recent findings from large-scale multi-omics studies on renal cell carcinoma and its associations with patient subtyping and drug development.

Omics sciences and precision medicine in sarcoma

Background

Sarcomas are a relatively rare but diverse group of cancers that typically develop in the mesenchymal cells of bones and soft tissues. Occurring in more than 70 subtypes, sarcomas have broad histological presentations, posing significant challenges of prognosis and treatment. Modern multi-omics studies, which include genomics, proteomics, metabolomics, and micro-biomics, are vital to understand the underlying mechanisms of sarcoma development and progression, identify molecular biomarkers for early detection, develop personalized treatment plans, and discover drug resistance mechanisms in sarcomas to upsurge the survival rate.

Aim

This study aims to highlight the genetic risk factors responsible for sarcoma-genesis, and to present a comprehensive review of multi-omics studies about sarcoma.

Methods

Extensive literature research was undertaken using reliable and authentic medical journals, e-books, and online cancer research databases. Mendelian inheritance in man database (OMIM) was explored to study particular genes and their loci that are responsible to cause various sarcomas.

Result

This in-depth research led to the finding out that omics studies provide a more comprehensive understanding of underlying molecular mechanisms of sarcomas. Through genomics, we can reveal genetic alterations that predispose to sarcoma, like mutation in TP53, NF1, and so on. Pharmacogenomics enable us to find molecular targets for specific drugs. Whereas, proteomic and metabolomic studies provide insights into the biological pathways involved in sarcoma development and progression.

Conclusion

Future advancements in omics sciences for sarcoma are on the cutting-edge of defining precision treatment plans and improved resilience of sarcoma patients.

Characterization of somatic mutations in the pathogenesis of lipedema

Background

Lipedema, a complex and enigmatic adipose tissue disorder, remains poorly understood despite its significant impact on the patients' quality of life. Genetic investigations have uncovered potential contributors to its pathogenesis, including somatic mutations, which are nonheritable genetic alterations that can play a pivotal role in the development of this disease.

Aim

This review aims to elucidate the role of somatic mutations in the etiology of lipedema by examining their implications in adipose tissue biology, inflammation, and metabolic dysfunction.

Results

Studies focusing on leukocyte clones, genetic alterations like TET2 and DNMT3A, and the intricate interplay between adipose tissue and other organs have shed light on the underlying mechanisms driving lipedema. From the study of the scientific literature, mutations to genes correlated to three main pathways could be involved in the somatic development of lipedema: genes related to mitochondrial activity, genes related to localized disorders of subcutaneous adipose tissue, and genes of leukocyte clones.

Conclusions

The insights gained from these diverse studies converge to highlight the complex genetic underpinnings of lipedema and offer potential avenues for therapeutic interventions targeting somatic mutations to alleviate the burden of this condition on affected individuals.

Omics sciences and precision medicine in thyroid cancer

Background

Thyroid cancer, a heterogeneous disease originating from the thyroid gland, stands as the predominant endocrine malignan-cy worldwide. Despite advances in diagnosis and treatment, some patients still experience recurrence and mortality, which highlights the need for more personalized approaches to treatment. Omics sciences, encompassing genomics, transcriptomics, proteomics, and metabolomics, offer a high-throughput and impartial methodology for investigating the molecular signatures of thyroid cancer.

Methods

In the course of this review, we have adopted a focu-sed research strategy, meticulously selecting the most pertinent and emblematic articles related to the topic. Our methodology included a systematic examination of the scientific literature to guarantee a thorough and precise synthesis of the existing sources.

Results

These techniques enable the identification of molecular markers that can aid in diagnosis, prognosis, and treatment selection. As an illustration, through genomics studies, numerous genetic alterations commonly discovered in thyroid cancer have been identified, such as mutations in the BRAF and RAS genes. Through transcriptomics studies, distinctively expressed genes in thyroid cancer have been uncovered, playing roles in diverse biological processes, including cell proliferation, invasion, and metastasis. These genes can serve as potential targets for novel therapies. Proteomics studies have unveiled differentially expressed proteins intricately involved in thyroid cancer pathogenesis, presenting promising biomarkers for early detection and disease progression monitoring. Metabolomics studies have identified alterations in metabolic pathways linked to thyroid cancer, offering promising avenues for potential therapeutic targets.

Conclusions

Precision medicine in thyroid cancer involves the integration of omics sciences with clinical data to develop personalized treatment plans for patients. Employing targeted therapies guided by molecular markers has exhibited promising outcomes in enhancing the prognosis of thyroid cancer patients. Notably, those with advanced hyroid cancer carrying BRAF mutations have displayed substantial responses to specific targeted therapies, such as vemurafenib and dabrafenib.

Omics sciences and precision medicine in Urothelial Carcinoma

Abstract

This comprehensive review explores the potential of omics sciences - such as genomics, transcriptomics, proteomics, and metabolomics - in advancing the diagnosis and therapy of urothelial carcinoma (UC), a prevalent and heterogeneous cancer affecting the urinary tract. The article emphasizes the significant advancements in understanding the molecular mechanisms underlying UC development and progression, obtained through the application of omics approa-ches. Genomic studies have identified recurrent genetic alterations in UC, while transcriptomic analyses have revealed distinct gene expression profiles associated with different UC subtypes. Proteomic investigations have recognized protein biomarkers with diagnostic and prognostic potential, and metabolomic profiling has found metabolic alterations that are specific to UC. The integration of multi-omics data holds promises in refining UC subtyping, identifying therapeutic targets, and predicting treatment response. However, challenges like the standardization of omics technologies, validation of biomarkers, and ethical considerations need to be addressed to successfully translate these findings into clinical practice. Omics sciences offer tremendous potential in revolutionizing the diagnosis and therapy of UC, enabling more precise diagnostic methods, prognostic evaluations, and personalized treatment selection for UC patients. Future research efforts should focus on overcoming these challenges and translating omics discoveries into meaningful clinical applications to improve outcomes for UC patients.

Omics sciences and precision medicine in testicular cancer

Background

Cancer, a potentially fatal condition, is one of the leading causes of death worldwide. Among males aged 20 to 35, the most common cancer in healthy individuals is testicular cancer, accounting for 1% to 2% of all cancers in men.

Methods

Throughout this review, we have employed a targeted research approach, carefully handpicking the most representative and relevant articles on the subject. Our methodology involved a systematic review of the scientific literature to ensure a comprehensive and accurate overview of the available sources.

Results

The onset and spread of testicular cancer are significantly influenced by genetic changes, including mutations in oncogenes, tu-mor suppressor genes, and DNA repair genes. As a result of identifying these specific genetic mutations in cancers, targeted medications have been developed to disrupt the signaling pathways affected by these genetic changes. To improve the diagnosis and treatment of this disease, it is crucial to understand its natural and clinical histories.

Conclusions

In order to comprehend cancer better and to discover new biomarkers and therapeutic targets, oncologists are increasingly employing omics methods, such as genomics, transcriptomics, proteomics, and metabolomics. Targeted medications that focus on specific genetic pathways and mutations hold promise for advancing the diagnosis and management of this disease.

Omics sciences and precision medicine in melanoma

Background

This article provides an overview of the application of omics sciences in melanoma research. The name omics sciences refers to the large-scale analysis of biological molecules like DNA, RNA, proteins, and metabolites.

Methods

In the course of this review, we have adopted a focu-sed research strategy, meticulously selecting the most pertinent and emblematic articles related to the topic. Our methodology included a systematic examination of the scientific literature to guarantee a thorough and precise synthesis of the existing sources.

Results

With the advent of high-throughput technologies, omics have become an essential tool for understanding the complexity of melanoma. In this article, we discuss the different omics approaches used in melanoma research, including genomics, transcriptomics, proteomics, and metabolomics. We also highlight the major findings and insights gained from these studies, including the identification of new therapeutic targets and the development of biomarkers for diagnosis and prognosis. Finally, we discuss the challenges and future directions in omics-based melanoma research, including the integration of multiple omics data and the development of personalized medicine approaches.

Conclusions

Overall, this article emphasizes the importance of omics science in advancing our understanding of melanoma and its potential for improving patient outcomes.

Targeting Mast Cells: Sodium Cromoglycate as a Possible Treatment of Lipedema

Background

Mast cells are immune cells that mediate hypersensi-tivity and allergic reactions in the body, secreting histamine and other inflammatory molecules. They have been associated with different inflammatory conditions such as obesity and other adipose tissue di-sorders. Lipedema is a chronic disease characterized by an abnormal accumulation of adipose tissue on the legs and arms, pain, and other symptoms. Mast cells may play a role in the pathology of lipedema.

Objective

Pilot study to determine levels of histamine and its metabolites in lipedema subcutaneous adipose tissue (SAT) biopsy samples, and to test sodium cromoglycate for the treatment of mast cells in women with lipedema.

Methods

Biopsies from lipedema and control SAT were collected and analyzed histologically for the presence of mast cells. Mass spec-trometry was used to measure the levels of histamine, a key marker of mast cells, and its metabolites in SAT in women with lipedema and controls, and after a group of women with lipedema were administered oral and topical doses of sodium cromoglycate for two weeks.

Results

Histological examination of biopsies from lipedema patients confirmed the presence of mast cells. Metabolomic analysis revealed high levels of histamine and its metabolites in samples from women with lipedema compared to controls. Following a two-week treatment period, lipedema tissue samples exhibited reduced levels of histamine, suggesting a reduction of mast cell activity.

Conclusion

Sodium cromoglycate has the ability to stabilize mast cells and reduce histamine levels in lipedema patients, which could be useful in lowering the symptoms of lipedema.

CNV analysis in a diagnostic setting using target panel

OBJECTIVE

Copy-number variation (CNV) is an important source of genetic diversity in humans. It can cause Mendelian or sporadic traits or be associated with complex diseases by various molecular mechanisms, including gene dosage, gene disruption, gene fusion and position effects. In clinical diagnostics, it is therefore fundamental to be able to identify such variations. The preferred techniques for CNV detection are MLPA, aCGH and qPCR, which have proven to be valuable, and they are complex, costly and require prior knowledge of the region to analyze. CNV calling from NGS data still suffers from data variability. Coverage can vary greatly from one region of the genome to another, depending on many factors like complexity, GC content, repeated regions and many others. In this paper, we describe how we developed a method for CNV detection.

MATERIALS AND METHODS

Our method exploits CoNVaDING to detect single- and multiple-exon CNVs in targeted NGS data.

RESULTS

We demonstrated that our CNV analysis has 100% specificity and 99.998% sensitivity. We also show how we evaluated the performance of this method based on internal analysis.

CONCLUSIONS

The results indicate that the method can be used to screen prior to standard labs technologies, thus reducing the number of analyses, as well as costs, and increasing test conclusiveness.

Improvement of quality of life by intake of hydroxytyrosol in patients with lymphedema and association of lymphedema genes with obesity

OBJECTIVE

Lymphedema is a debilitating disease and may be a comorbidity of obesity. New molecules have been investigated for the treatment of lymphedema; one of the most promising molecules is hydroxytyrosol. The aim of this study was to evaluate the association between mutations in genes mutated in lymphedema and the presence of obesity and making an estimate of the quality of life in lymphedema patients.

MATERIALS AND METHODS

We recruited 71 Caucasian individuals with the diagnosis of primary lymphedema, and they undertook a questionnaire to assess their quality life. For this purpose, we developed a NGS custom-made panel comprising genes associated with lymphedema.

RESULTS

An obesity rate of 20% was detected. The average Lymph-ICF-LL value for patients who consume olive oil daily was 20 with a better quality of life. Twenty-three patients resulted positive to the genetic test. Genetic variants with a likely association with obesity have been identified in PROX1, FOXC2 and FLT4.

CONCLUSIONS

A obesity rate, higher than that reported by ISTAT, was detected. The use of olive oil enhances the quality of life of lymphedema patients. Moreover, a diagnostic approach by a NGS panel shows an association of lymphedema with obesity.

Integration of VarSome API in an existing bioinformatic pipeline for automated ACMG interpretation of clinical variants

OBJECTIVE

While the bioinformatic workflow, from quality control to annotation, is quite standardized, the interpretation of variants is still a challenge. The decreasing cost of massively parallel NGS has produced hundreds of variants per patient to analyze and interpret. The ACMG "Standards and guidelines for the interpretation of sequence variants", widely adopted in clinical settings, assume that the clinician has a comprehensive knowledge of the literature and the disease.

MATERIALS AND METHODS

To semi-automatize the application of the guidelines, we decided to develop an algorithm that exploits VarSome, a widely used platform that interprets variants on the basis of information from more than 70 genome databases.

RESULTS

Here we explain how we integrated VarSome API into our existing clinical diagnostic pipeline for NGS data to obtain validated reproducible results as indicated by accuracy, sensitivity and specificity.

CONCLUSIONS

We validated the automated pipeline to be sure that it was doing what we expected. We obtained 100% sensitivity, specificity and accuracy, confirming that it was suitable for use in a diagnostic setting.

PipeMAGI: an integrated and validated workflow for analysis of NGS data for clinical diagnostics

OBJECTIVE

We describe how to set up a custom workflow for the analysis of next generation sequencing (NGS) data suitable for the diagnosis of genetic disorders and that meets the strictest standards of quality and accuracy. Our method goes from DNA extraction to data analysis with a computational in-house pipeline. The system was extensively validated using three publicly available Coriell samples, estimating accuracy, sensitivity and specificity. Multiple runs were also made to assess repeatability and reproducibility.

MATERIALS AND METHODS

Three different Coriell samples were analyzed in a single run to perform coverage, sensitivity, specificity, accuracy, reproducibility and repeatability analysis. The three samples were analyzed with a custom-made oligonucleotide probe library using Nextera Rapid Capture enrichment technique and subsequently quantified using the Qubit method. Sample quality was verified using a 4200 TapeStation and sequenced on a MiSeq personal sequencer. Analysis of NGS data was then performed with a custom pipeline.

RESULTS

The workflow enabled an accurate and precise analysis of NGS data that meets all the requirements of quality and accuracy required by international standards such as ISO15189 and the Association of Molecular Pathology.

CONCLUSIONS

The proposed analysis/validation workflow has high assay accuracy, precision and robustness and can, therefore, be used for clinical diagnostic applications.

Putative role of Brugada syndrome genes in familial atrial fibrillation

OBJECTIVE

Familial atrial fibrillation (FAF), a not uncommon arrhythmia of the atrium, is characterized by heritability, early onset and absence of other heart defects. The molecular and genetic basis is still not completely clear and genetic diagnosis cannot be achieved in about 90% of patients. In this study, we present the results of genetic screening by next generation sequencing in affected Russian families.

PATIENTS AND METHODS

Sixty subjects (18 probands and 42 relatives) with a clinical diagnosis of FAF were enrolled in the study. Since AF frequently associates with other cardiomyopathies, we included all genes that were known to be associated with these disorders at the time of our study. All probands were therefore systematically screened for 47 genes selected from the literature.

RESULTS

Our study revealed that seven variants co-segregated with the clinical phenotype in seven families. Interestingly, four out of six genes and three out of seven variants have already been associated with Brugada syndrome in the literature.

CONCLUSIONS

To our knowledge, this is the first report of association of the CACNA1C, CTNNA3, PKP2, ANK2 and SCN10A genes with FAF; it is also the first study in Russian families.

Analysis of machine learning algorithms as integrative tools for validation of next generation sequencing data

OBJECTIVE

While next generation sequencing (NGS) has become the technology of choice for clinical diagnostics, most genetic laboratories still use Sanger sequencing for orthogonal confirmation of NGS results. Previous studies have shown that when the quality of NGS data is high, most calls are indicated by Sanger sequencing, making confirmation redundant. We aimed at establishing a set of criteria that make it possible to distinguish NGS calls that need orthogonal confirmation from those that do not would significantly decrease the amount of work necessary to reach a diagnosis.

MATERIALS AND METHODS

A data set of 7976 NGS calls confirmed as true or false positive by Sanger sequencing was used to train and test different machine learning (ML) approaches. By varying the size and class balance of the training dataset, we measured the performance of the different algorithms to determine the conditions under which ML is a valid approach for confirming NGS calls in a diagnostic environment.

RESULTS

Our results indicate that machine learning is a valid approach to find variant calls that need more investigation, but in order to reach the high accuracy required in a clinical environment, the training data set must include enough observations and these observations must be well-balanced between true/false positive NGS calls.

CONCLUSIONS

Our results show that it is possible to integrate the diagnostic NGS validation workflow with a machine learning approach to reduce the number of Sanger confirmations of high- quality NGS calls, reducing the time and costs of diagnosis.

Bioinformatic analysis indicates that SARS-CoV-2 is unrelated to known artificial coronaviruses

OBJECTIVE

SARS-CoV-2 is responsible for the present coronavirus pandemic and some suggestions were made about its possible artificial origin. We, therefore, compared SARS-CoV-2 with such known viruses that were prepared in the laboratory and other relevant natural strains to estimate their genetic relatedness.

MATERIALS AND METHODS

BLAST and clustalW were used to identify and align viral sequences of SARS-CoV-2 to other animal coronaviruses (human, bat, mouse, pangolin) and related artificial constructs. Phylogenetics trees were then prepared using iTOL.

RESULTS

Our study supports the notion that known artificial coronaviruses, including the chimeric SL-SHC014-MA15 synthesized in 2015, differ too much from SARS-CoV-2 to hypothesize an artificial origin of the latter. On the contrary, our data support the natural origin of the COVID-19 virus, likely derived from bats, possibly transferred to pangolins, before spreading to man.

CONCLUSIONS

Speculations about the artificial origin of SARS-CoV-2 are most likely unfounded. On the contrary, when carefully handled, engineered organisms provide a unique opportunity to study biological systems in a controlled fashion. Biotechnology is a powerful tool to advance medical research and should not be abandoned because of irrational fears.

Genetic Screening in a Large Cohort of Italian Patients Affected by Primary Lymphedema Using a Next Generation Sequencing (NGS) Approach

Primary lymphedema is a rare inherited condition characterized by swelling of body tissues caused by accumulation of fluid, especially in the lower limbs. In many patients, primary lymphedema has been associated with variations in a number of genes involved in the development and maintenance of the lymphatic system. In this study, we performed a genetic screening in patients affected by primary lymphedema using a next generation sequencing (NGS) approach. With this technology, based on a custom-made oligonucleotide probe library, we were able to analyze simultaneously in each patient all the coding exons of 10 genes (FLT4, FOXC2, CCBE1, GJC2, MET, HGF, GATA2, SOX18, VEGFC, KIF11) associated with primary lymphedema. In the study population, composed of 45 familial and 71 sporadic cases, we identified the presence of rare variants with a potential pathogenic effect in 33% of subjects. Overall, we found a total of 36 different rare nucleotidic alterations, 30 of which had not been previously described. Among these, we identified 23 mutations that we considered most likely to be disease causing. Patients with an FLT4 or FOXC2 alteration accounted for the largest percentage of the sample, followed by MET, HGF, KIK11, GJC2 and GATA2. No alterations were identified in SOX18, VEGFC, and CCBE1 genes. In conclusion, we showed that NGS technology can be successfully applied to perform molecular screening of lymphedema-associated genes in large cohort of patients with a reasonable effort in terms of cost, work, and time.