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.

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.

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.

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.

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.

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 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 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 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.

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.

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.

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 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 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 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.

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.