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 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.

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.

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.