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Glioblastoma, a grade 4 glioma as per the World Health Organization, poses a challenge in adult primary brain tumor management despite advanced surgical techniques and multimodal therapies. This review delves into the potential of targeting epidermal growth factor receptor (EGFR) with small-molecule inhibitors and antibodies as a treatment strategy. EGFR, a mutationally active receptor tyrosine kinase in over 50% of glioblastoma cases, features variants like EGFRvIII, EGFRvII and missense mutations, necessitating a deep understanding of their structures and signaling pathways. Although EGFR inhibitors have demonstrated efficacy in other cancers, their application in glioblastoma is hindered by blood-brain barrier penetration and intrinsic resistance. The evolving realm of nanodrugs and convection-enhanced delivery offers promise in ensuring precise drug delivery to the brain. Critical to success is the identification of glioblastoma patient populations that benefit from EGFR inhibitors. Tools like radiolabeled anti-EGFR antibody 806i facilitate the visualization of EGFR conformations, aiding in tailored treatment selection. Recognizing the synergistic potential of combination therapies with downstream targets like mTOR, PI3k, and HDACs is pivotal for enhancing EGFR inhibitor efficacy. In conclusion, the era of precision oncology holds promise for targeting EGFR in glioblastoma, contingent on tailored treatments, effective blood-brain barrier navigation, and the exploration of synergistic therapies.

This study focuses on understanding the transcriptional heterogeneity of activated platelets and its impact on diseases such as sepsis, COVID-19, and systemic lupus erythematosus (SLE). Recognizing the limited knowledge in this area, our research aims to dissect the complex transcriptional profiles of activated platelets to aid in developing targeted therapies for abnormal and pathogenic platelet subtypes. We analyzed single-cell transcriptional profiles from 47,977 platelets derived from 413 samples of patients with these diseases, utilizing Deep Neural Network (DNN) and eXtreme Gradient Boosting (XGB) to distinguish transcriptomic signatures predictive of fatal or survival outcomes. Our approach included source data annotations and platelet markers, along with SingleR and Seurat for comprehensive profiling. Additionally, we employed Uniform Manifold Approximation and Projection (UMAP) for effective dimensionality reduction and visualization, aiding in the identification of various platelet subtypes and their relation to disease severity and patient outcomes. Our results highlighted distinct platelet subpopulations that correlate with disease severity, revealing that changes in platelet transcription patterns can intensify endotheliopathy, increasing the risk of coagulation in fatal cases. Moreover, these changes may impact lymphocyte function, indicating a more extensive role for platelets in inflammatory and immune responses. This study identifies crucial biomarkers of platelet heterogeneity in serious health conditions, paving the way for innovative therapeutic approaches targeting platelet activation, which could improve patient outcomes in diseases characterized by altered platelet function.

Epigenetic dysregulation has long been recognized as a significant contributor to tumorigenesis and tumor maintenance, impacting all recognized cancer hallmarks. Although some epigenetic drugs have received regulatory approval for certain hematological malignancies, their efficacy in treating solid tumors has so far been largely disappointing. However, recent advancements in developing new compounds and a deeper understanding of cancer biology have led to success in specific solid tumor subtypes through precision medicine approaches. Moreover, epigenetic drugs may play a crucial role in synergizing with other anticancer treatments, enhancing the sensitivity of cancer cells to various anticancer therapies, including chemotherapy, radiation therapy, hormone therapy, targeted therapy, and immunotherapy. In this review, we critically evaluate the evolution of epigenetic drugs, tracing their development from initial use as monotherapies to their current application in combination therapies. We explore the preclinical rationale, completed clinical studies, and ongoing clinical trials. Finally, we discuss trial design strategies and drug scheduling to optimize the development of possible combination therapies. [ABSTRACT FROM AUTHOR]

Biochemical phenotyping has been the milestone for diagnosing and managing patients affected by inborn errors of intermediary metabolism (IEiM); however, identifying the genotype responsible for these monogenic disorders greatly contributes to achieving these goals. Herein, whole-exome sequencing (WES) was used to determine the genotypes of 95 unrelated Mexican pediatric patients suspected of having IEiM. They were classified into those bearing specific biochemical abnormalities (Group 1), and those presenting unspecific biochemical profiles (Group 2). The overall concordance between the initial biochemical diagnosis and final genotypic diagnoses was 72.6% (N = 69/95 patients), with the highest concordance achieved in Group 1 (91.3%, N = 63/69), whereas the concordance was limited in Group 2 (23.07%). This finding suggests that previous biochemical phenotyping correlated with the high WES diagnostic success. Concordance was high for urea cycle disorders (94.1%) and organic acid disorders (77.4%). The identified mutational spectrum comprised 83 IEiM-relevant variants (pathogenic, likely pathogenic, and variants of uncertain significance or VUS), including three novel ones, distributed among 29 different genes responsible for amino acid, organic acid, urea cycle, carbohydrate, and lipid disorders. Inconclusive WES results (7.3%, N = 7/95) relied on monoallelic pathogenic genotypes or those involving two VUS for autosomal-recessive IEiMs. A second monogenic disease was observed in 10.5% (N = 10/95) of the patients. According to the WES results, modifications in treatment had to be made in 33.6% (N = 32/95) of patients, mainly attributed to the presence of a second monogenic disease, or to an actionable trait. This study includes the largest cohort of Mexican patients to date with biochemically suspected IEiM who were genetically diagnosed through WES, underscoring its importance in medical management. [ABSTRACT FROM AUTHOR]

One of the most critical goals in healthcare is safe and effective drug therapy, which is directly related to an individual's response to treatment. Precision medicine can improve drug safety in many scenarios, including polypharmacy, and it requires the development of new genetic characterization methods. In this report, we use real-time PCR, microarray techniques, and mass spectrometry (MALDI-TOF), which allows us to compare them and identify the potential benefits of technological improvements, leading to better quality medical care. These comparative studies, as part of our pharmacogenetic Five-Step Precision Medicine (5SPM) approach, reveal the superiority of mass spectrometry over the other methods analyzed and highlight the importance of updating the laboratory's pharmacogenetic methodology to identify new variants with clinical impact. [ABSTRACT FROM AUTHOR]

Amelanotic melanoma (AM) is a subtype of hypomelanotic or completely amelanotic melanoma. AM is a rare subtype of melanoma that exhibits a higher recurrence rate and aggressiveness as well as worse surveillance than typical melanoma. AM shows a dysregulation of melanin production, cell cycle control, and apoptosis pathways. Knowing these pathways has an application in medicine due to targeted therapies based on the inhibiting elements of the abovementioned pathways. Therefore, we summarized and discussed AM biochemical and molecular induction pathways and personalized medicine approaches, clinical management, and future directions due to the fact that AM is relatively rare. AM is commonly misdiagnosed. Hence, the role of biomarkers is becoming significant. Nonetheless, there is a shortage of biomarkers specific to AM. BRAF, NRAS, and c-KIT genes are the main targets of therapy. However, the role of BRAF and KIT in AM varied among studies. BRAF inhibitors combined with MAK inhibitors demonstrate better results. Immune checkpoint inhibitors targeting CTLA-4 combined with a programmed death receptor 1 (PD-1) show better outcomes than separately. Fecal microbiota transplantation may overcome resistance to immune checkpoint therapy of AM. Immune-modulatory vaccines against indoleamine 2,3-dioxygenase (IDO) and PD ligand (PD-L1) combined with nivolumab may be efficient in melanoma treatment. [ABSTRACT FROM AUTHOR]

The gut microbiome emerges as an integral component of precision medicine because of its signature variability among individuals and its plasticity, which enables personalized therapeutic interventions, especially when integrated with other multiomics data. This promise is further fueled by advances in next-generation sequencing and metabolomics, which allow in-depth high-precision profiling of microbiome communities, their genetic contents, and secreted chemistry. This knowledge has advanced our understanding of our microbial partners, their interaction with cellular targets, and their implication in human conditions such as inflammatory bowel disease (IBD). This explosion of microbiome data inspired the development of next-generation therapeutics for treating IBD that depend on manipulating the gut microbiome by diet modulation or using live products as therapeutics. The current landscape of artificial microbiome therapeutics is not limited to probiotics and fecal transplants but has expanded to include community consortia, engineered probiotics, and defined metabolites, bypassing several limitations that hindered rapid progress in this field such as safety and regulatory issues. More integrated research will reveal new therapeutic targets such as enzymes or receptors mediating interactions between microbiota-secreted molecules that drive or modulate diseases. With the shift toward precision medicine and the enhanced integration of host genetics and polymorphism in treatment regimes, the following key questions emerge: How can we effectively implement microbiomics to further personalize the treatment of diseases like IBD, leveraging proven and validated microbiome links? Can we modulate the microbiome to manage IBD by altering the host immune response? In this review, we discuss recent advances in understanding the mechanism underpinning the role of gut microbes in driving or preventing IBD. We highlight developed targeted approaches to reverse dysbiosis through precision editing of the microbiome. We analyze limitations and opportunities while defining the specific clinical niche for this innovative therapeutic modality for the treatment, prevention, and diagnosis of IBD and its potential implication in precision medicine. [ABSTRACT FROM AUTHOR]

The paradigm "one drug fits all" or "one dose fits all" will soon be challenged by pharmacogenetics research and application. Drug response—efficacy or safety—depends on interindividual variability. The current clinical practice does not include genetic screening as a routine procedure and does not account for genetic variation. Patients with the same illness receive the same treatment, yielding different responses. Integrating pharmacogenomics in therapy would provide critical information about how a patient will respond to a certain drug. Worldwide, great efforts are being made to achieve a personalized therapy-based approach. Nevertheless, a global harmonized guideline is still needed. Plasma membrane proteins, like receptor tyrosine kinase (RTK) and G protein-coupled receptors (GPCRs), are ubiquitously expressed, being involved in a diverse array of physiopathological processes. Over 30% of drugs approved by the FDA target GPCRs, reflecting the importance of assessing the genetic variability among individuals who are treated with these drugs. Pharmacogenomics of transmembrane protein receptors is a dynamic field with profound implications for precision medicine. Understanding genetic variations in these receptors provides a framework for optimizing drug therapies, minimizing adverse reactions, and advancing the paradigm of personalized healthcare. [ABSTRACT FROM AUTHOR]

Lymphoid malignancies are complex diseases with distinct biological behaviors, clinical presentations, and treatment responses. Ongoing research and advancements in biotechnology enhance the understanding and management of these malignancies, moving towards more personalized approaches for diagnosis and treatment. Nanotechnology has emerged as a promising tool to improve some limitations of conventional diagnostics as well as treatment strategies for lymphoid malignancies. Nanoparticles (NPs) offer unique advantages such as enhanced multimodal detection, drug delivery, and targeted therapy capabilities, with the potential to improve precision medicine and patient outcomes. Here, we comprehensively examine the current landscape of nanoconstructs applied in the management of lymphoid disease. Through a comprehensive analysis of preclinical studies, we highlight the translational potential of NPs in revolutionizing the field of hematological malignancies, with a specific focus on lymphoid neoplasms. [ABSTRACT FROM AUTHOR]

Stargardt disease, one of the most common forms of inherited retinal diseases, affects individuals worldwide. The primary cause is mutations in the ABCA4 gene, leading to the accumulation of toxic byproducts in the retinal pigment epithelium (RPE) and subsequent photoreceptor cell degeneration. Over the past few years, research on Stargardt disease has advanced significantly, focusing on clinical and molecular genetics. Recent studies have explored various innovative therapeutic approaches, including gene therapy, stem cell therapy, and pharmacological interventions. Gene therapy has shown promise, particularly with adeno-associated viral (AAV) vectors capable of delivering the ABCA4 gene to retinal cells. However, challenges remain due to the gene's large size. Stem cell therapy aims to replace degenerated RPE and photoreceptor cells, with several clinical trials demonstrating safety and preliminary efficacy. Pharmacological approaches focus on reducing toxic byproduct accumulation and modulating the visual cycle. Precision medicine, targeting specific genetic mutations and pathways, is becoming increasingly important. Novel techniques such as clustered regularly interspaced palindromic repeats (CRISPR)/Cas9 offer potential for directly correcting genetic defects. This review aims to synthesize recent advancements in understanding and treating Stargardt disease. By highlighting breakthroughs in genetic therapies, stem cell treatments, and novel pharmacological strategies, it provides a comprehensive overview of emerging therapeutic options. [ABSTRACT FROM AUTHOR]

Cancer is the leading cause of disease-related death among children. Vincristine (VCR), a key component of childhood cancer treatment protocols, is associated with the risk of peripheral neuropathy (PN), a condition that may be reversible upon drug discontinuation but can also leave lasting sequelae. Single nucleotide polymorphism (SNP) in genes involved in VCR pharmacokinetics and pharmacodynamics have been investigated in relation to an increased risk of PN. However, the results of these studies have been inconsistent. A retrospective cohort study was conducted to investigate the potential association of drug transporter genes from the ATP-binding cassette (ABC) family and the centrosomal protein 72 (CEP72) gene with the development of PN in 88 Caucasian children diagnosed with cancer and treated with VCR. Genotyping was performed using real-time PCR techniques for the following SNPs: ABCB1 rs1128503, ABCC1 rs246240, ABCC2 rs717620, and CEP72 rs924607. The results indicated that age at diagnosis (OR = 1.33; 95% CI = 1.07–1.75) and the ABCC1 rs246240 G allele (OR = 12.48; 95% CI = 2.26–100.42) were associated with vincristine-induced peripheral neuropathy (VIPN). No association was found between this toxicity and CEP72 rs924607. Our study provides insights that may contribute to optimizing childhood cancer therapy in the future by predicting the risk of VIPN [ABSTRACT FROM AUTHOR]

Vitronectin is a glycoprotein present in plasma and the extracellular matrix that is implicated in cell migration. The high amount of vitronectin found in neuroblastoma biopsies has been associated with poor prognosis. Moreover, increased vitronectin levels have been described in the plasma of patients with different cancers. Our aim was to assess vitronectin as a potential circulating biomarker of neuroblastoma prognosis. Vitronectin concentration was quantified using ELISA in culture media of four neuroblastoma cell lines grown in a monolayer and in 3D models, and in the plasma of 114 neuroblastoma patients. Three of the neuroblastoma cell lines secreted vitronectin to culture media when cultured in a monolayer and 3D models. Vitronectin release was higher by neuroblastoma cells cultured in 3D models than in the monolayer and was still elevated when cells were grown in 3D scaffolds with cross-linked vitronectin. Vitronectin secretion occurred independently of cell numbers in cultures. Its concentration in the plasma of neuroblastoma patients ranged between 52.4 and 870 µg/mL (median, 218 µg/mL). A ROC curve was used to establish a cutoff of 361 µg/mL, above which patients over 18 months old had worse prognosis (p = 0.0018). Vitronectin could be considered a new plasma prognostic biomarker in neuroblastoma and warrants confirmation in collaborative studies. Drugs inhibiting vitronectin interactions with cells and/or the extracellular matrix could represent a significant improvement in survival for neuroblastoma patients. [ABSTRACT FROM AUTHOR]

RASopathies are a group of related genetic disorders caused by mutations in genes within the RAS/MAPK signaling pathway. This pathway is crucial for cell division, growth, and differentiation, and its disruption can lead to a variety of developmental and health issues. RASopathies present diverse clinical features and pose significant diagnostic and therapeutic challenges. Studying the landscape of biomarkers in RASopathies has the potential to improve both clinical practices and the understanding of these disorders. This review provides an overview of recent discoveries in RASopathy molecular profiling, which extend beyond traditional gene mutation analysis. mRNAs, non-coding RNAs, protein expression patterns, and post-translational modifications characteristic of RASopathy patients within pivotal signaling pathways such as the RAS/MAPK, PI3K/AKT/mTOR, and Rho/ROCK/LIMK2/cofilin pathways are summarized. Additionally, the field of metabolomics holds potential for uncovering metabolic signatures associated with specific RASopathies, which are crucial for developing precision medicine. Beyond molecular markers, we also examine the role of histological characteristics and non-invasive physiological assessments in identifying potential biomarkers, as they provide evidence of the disease's effects on various systems. Here, we synthesize key findings and illuminate promising avenues for future research in RASopathy biomarker discovery, underscoring rigorous validation and clinical translation. [ABSTRACT FROM AUTHOR]

Inflammatory bowel disease (IBD) represents heterogeneous and relapsing intestinal conditions with a severe impact on the quality of life of individuals and a continuously increasing prevalence. In recent years, the development of sequencing technology has provided new means of exploring the complex pathogenesis of IBD. An ideal solution is represented by the approach of precision medicine that investigates multiple cellular and molecular interactions, which are tools that perform a holistic, systematic, and impartial analysis of the genomic, transcriptomic, proteomic, metabolomic, and microbiomics sets. Hence, it has led to the orientation of current research towards the identification of new biomarkers that could be successfully used in the management of IBD patients. Multi-omics explores the dimension of variation in the characteristics of these diseases, offering the advantage of understanding the cellular and molecular mechanisms that affect intestinal homeostasis for a much better prediction of disease development and choice of treatment. This review focuses on the progress made in the field of prognostic and predictive biomarkers, highlighting the limitations, challenges, and also the opportunities associated with the application of genomics and epigenomics technologies in clinical practice. [ABSTRACT FROM AUTHOR]

Accurate detection and analysis of somatic variants in cancer involve multiple third-party tools with complex dependencies and configurations, leading to laborious, error-prone, and time-consuming data conversions. This approach lacks accuracy, reproducibility, and portability, limiting clinical application. Musta was developed to address these issues as an end-to-end pipeline for detecting, classifying, and interpreting cancer mutations. Musta is based on a Python command-line tool designed to manage tumor-normal samples for precise somatic mutation analysis. The core is a Snakemake-based workflow that covers all key cancer genomics steps, including variant calling, mutational signature deconvolution, variant annotation, driver gene detection, pathway analysis, and tumor heterogeneity estimation. Musta is easy to install on any system via Docker, with a Makefile handling installation, configuration, and execution, allowing for full or partial pipeline runs. Musta has been validated at the CRS4-NGS Core facility and tested on large datasets from The Cancer Genome Atlas and the Beijing Institute of Genomics. Musta has proven robust and flexible for somatic variant analysis in cancer. It is user-friendly, requiring no specialized programming skills, and enables data processing with a single command line. Its reproducibility ensures consistent results across users following the same protocol. [ABSTRACT FROM AUTHOR]

Skin is the forestage for a series of many-sided functions of tumor necrosis factor-alpha (TNF-α), a proinflammatory cytokine with staggering versatility and sizable implications for tissue homeostasis, immune responses, angiogenesis, apoptosis, local and systemic inflammation. An aberrant TNF-α-mediated crosstalk has been linked to the pathogenesis of acute and chronic skin inflammatory diseases, and indeed, TNF-α dysregulation can contribute to the development and progression of psoriasis, vitiligo, local damage following exposition to ultraviolet light radiations, cutaneous lupus erythematosus, and acne vulgaris. Therapies that target TNF-α are conspicuously used in the treatment of different skin disorders, aiming to modulate the in vivo immune functions triggered by many cutaneous cells, including keratinocytes, mast cells, or Langerhans cells, and reduce inflammation taking place within the skin. Herein, we focus on the key relationships between TNF-α and distinct skin non-neoplastic inflammatory or physiologic conditions, showing that a natural induction of TNF-α may have a protective significance but that TNF-α overproduction may be harmful or even lethal. Many questions remain unraveled in the therapeutic practice, and caution should be exercised due to eventual backlashes exerted by TNF-α in maintaining skin health or in provoking skin disease. [ABSTRACT FROM AUTHOR]

Endometrial cancer (EC) is a heterogeneous disease with a rising incidence worldwide. The understanding of its molecular pathways has evolved substantially since The Cancer Genome Atlas (TCGA) stratified endometrial cancer into four subgroups regarding molecular features: POLE ultra-mutated, microsatellite instability (MSI) hypermutated, copy-number high with TP53 mutations, and copy-number low with microsatellite stability, also known as nonspecific molecular subtype (NSMP). More recently, the International Federation of Gynecology and Obstetrics (FIGO) updated their staging classification to include information about POLE mutation and p53 status, as the prognosis differs according to these characteristics. Other biomarkers are being identified and their prognostic and predictive role in response to therapies are being evaluated. However, the incorporation of molecular aspects into treatment decision-making is challenging. This review explores the available data and future directions on tailoring treatment based on molecular subtypes, alongside the challenges associated with their testing. [ABSTRACT FROM AUTHOR]

Pancreatic cancer (PC) is an increasing cause of cancer-related death, with a dismal prognosis caused by its aggressive biology, the lack of clinical symptoms in the early phases of the disease, and the inefficacy of treatments. PC is characterized by a complex tumor microenvironment. The interaction of its cellular components plays a crucial role in tumor development and progression, contributing to the alteration of metabolism and cellular hyperproliferation, as well as to metastatic evolution and abnormal tumor-associated immunity. Furthermore, in response to intrinsic oncogenic alterations and the influence of the tumor microenvironment, cancer cells undergo a complex oncogene-directed metabolic reprogramming that includes changes in glucose utilization, lipid and amino acid metabolism, redox balance, and activation of recycling and scavenging pathways. The advent of omics sciences is revolutionizing the comprehension of the pathogenetic conundrum of pancreatic carcinogenesis. In particular, metabolomics and genomics has led to a more precise classification of PC into subtypes that show different biological behaviors and responses to treatments. The identification of molecular targets through the pharmacogenomic approach may help to personalize treatments. Novel specific biomarkers have been discovered using proteomics and metabolomics analyses. Radiomics allows for an earlier diagnosis through the computational analysis of imaging. However, the complexity, high expertise required, and costs of the omics approach are the main limitations for its use in clinical practice at present. In addition, the studies of extracellular vesicles (EVs), the use of organoids, the understanding of host–microbiota interactions, and more recently the advent of artificial intelligence are helping to make further steps towards precision and personalized medicine. This present review summarizes the main evidence for the application of omics sciences to the study of PC and the identification of future perspectives. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD) plays a significant role in global morbidity and mortality rates, typified by progressive airflow restriction and lingering respiratory symptoms. Recent explorations in molecular biology have illuminated the complex mechanisms underpinning COPD pathogenesis, providing critical insights into disease progression, exacerbations, and potential therapeutic interventions. This review delivers a thorough examination of the latest progress in molecular research related to COPD, involving fundamental molecular pathways, biomarkers, therapeutic targets, and cutting-edge technologies. Key areas of focus include the roles of inflammation, oxidative stress, and protease–antiprotease imbalances, alongside genetic and epigenetic factors contributing to COPD susceptibility and heterogeneity. Additionally, advancements in omics technologies—such as genomics, transcriptomics, proteomics, and metabolomics—offer new avenues for comprehensive molecular profiling, aiding in the discovery of novel biomarkers and therapeutic targets. Comprehending the molecular foundation of COPD carries substantial potential for the creation of tailored treatment strategies and the enhancement of patient outcomes. By integrating molecular insights into clinical practice, there is a promising pathway towards personalized medicine approaches that can improve the diagnosis, treatment, and overall management of COPD, ultimately reducing its global burden. [ABSTRACT FROM AUTHOR]

Psoriasis is an autoimmune cutaneous condition that significantly impacts quality of life and represents a burden on society due to its prevalence. Genome-wide association studies (GWASs) have pinpointed several psoriasis-related risk loci, underlining the disease's complexity. Functional genomics is paramount to unveiling the role of such loci in psoriasis and disentangling its complex nature. In this review, we aim to elucidate the main findings in this field and integrate our discussion with gold-standard techniques in molecular biology—i.e., Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)—and high-throughput technologies. These tools are vital to understanding how disease risk loci affect gene expression in psoriasis, which is crucial in identifying new targets for personalized treatments in advanced precision medicine. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is the second leading cause of cancer deaths globally. While ethnic differences in driver gene mutations have been documented, the South American population remains understudied at the genomic level, despite facing a rising burden of CRC. We analyzed tumors of 40 Chilean CRC patients (Chp) using next-generation sequencing and compared them to data from mainly Caucasian cohorts (TCGA and MSK-IMPACT). We identified 388 mutations in 96 out of 135 genes, with TP53 (45%), KRAS (30%), PIK3CA (22.5%), ATM (20%), and POLE (20%) being the most frequently mutated. TSC2 mutations were associated with right colon cancer (44.44% in RCRC vs. 6.45% in LCRC, p-value = 0.016), and overall frequency was higher compared to TCGA (p-value = 1.847 × 10−5) and MSK-IMPACT cohorts (p-value = 3.062 × 10−2). Limited sample size restricts definitive conclusions, but our data suggest potential differences in driver mutations for Chilean patients, being that the RTK-RAS oncogenic pathway is less affected and the PI3K pathway is more altered in Chp compared to TCGA (45% vs. 25.56%, respectively). The prevalence of actionable pathways and driver mutations can guide therapeutic choices, but can also impact treatment effectiveness. Thus, these findings warrant further investigation in larger Chilean cohorts to confirm these initial observations. Understanding population-specific driver mutations can guide the development of precision medicine programs for CRC patients. [ABSTRACT FROM AUTHOR]

Exosomes are extracellular vesicles of endosomal origin, ranging from 30 to 150 nm in diameter, that mediate intercellular transfer of various biomolecules, such as proteins, lipids, nucleic acids, and metabolites. They modulate the functions of recipient cells and participate in diverse physiological and pathological processes, such as immune responses, cell–cell communication, carcinogenesis, and viral infection. Stem cells (SCs) are pluripotent or multipotent cells that can differentiate into various cell types. SCs can also secrete exosomes, which exhibit remarkable therapeutic potential for various diseases, especially in the field of regenerative medicine. For example, exosomes derived from mesenchymal stem cells (MSCs) contain proteins, lipids, and miRNAs that can ameliorate endocrine disorders, such as diabetes and cancer. Exosomes from SCs (sc-exos) may offer similar advantages as SCs, but with reduced risks and challenges. Sc-exos have lower tumorigenicity, immunogenicity, and infectivity. They can also deliver drugs more efficiently and penetrate deeper into tissues. In this review, we provide an overview of the recent advances in sc-exos and their therapeutic applications in various diseases, such as diabetes and cancer. We also elucidate how the biological effects of sc-exos depend on their molecular composition. We also address the current challenges and future directions of using sc-exos. [ABSTRACT FROM AUTHOR]

Retinitis pigmentosa 11 is an untreatable, dominantly inherited retinal disease caused by heterozygous mutations in pre-mRNA processing factor 31 PRPF31. The expression level of PRPF31 is linked to incomplete penetrance in affected families; mutation carriers with higher PRPF31 expression can remain asymptomatic. The current study explores an antisense oligonucleotide exon skipping strategy to treat RP11 caused by truncating mutations within PRPF31 exon 12 since it does not appear to encode any domains essential for PRPF31 protein function. Cells derived from a patient carrying a PRPF31 1205C>A nonsense mutation were investigated; PRPF31 transcripts encoded by the 1205C>A allele were undetectable due to nonsense-mediated mRNA decay, resulting in a 46% reduction in PRPF31 mRNA, relative to healthy donor cells. Antisense oligonucleotide-induced skipping of exon 12 rescued the open reading frame with consequent 1.7-fold PRPF31 mRNA upregulation in the RP11 patient fibroblasts. The level of PRPF31 upregulation met the predicted therapeutic threshold of expression inferred in a non-penetrant carrier family member harbouring the same mutation. This study demonstrated increased PRPF31 expression and retention of the nuclear translocation capability for the induced PRPF31 isoform. Future studies should evaluate the function of the induced PRPF31 protein on pre-mRNA splicing in retinal cells to validate the therapeutic approach for amenable RP11-causing mutations. [ABSTRACT FROM AUTHOR]

Familial dilated cardiomyopathy (DCM) is among the leading indications for heart transplantation. DCM alters the transcriptomic profile. The alteration or activation/silencing of physiologically operating transcripts may explain the onset and progression of this pathological state. The mediator complex (MED) plays a fundamental role in the transcription process. The aim of this study is to investigate the MED subunits, which are altered in DCM, to identify target crossroads genes. RNA sequencing allowed us to identify specific MED subunits that are altered during familial DCM, transforming into human myocardial samples. N = 13 MED subunits were upregulated and n = 7 downregulated. MED9 alone was significantly reduced in patients compared to healthy subjects (HS) (FC = −1.257; p < 0.05). Interestingly, we found a short MED9 isoform (MED9s) (ENSG00000141026.6), which was upregulated when compared to the full-transcript isoform (MED9f). Motif identification analysis yielded several significant matches (p < 0.05), such as GATA4, which is downregulated in CHD. Moreover, although the protein–protein interaction network showed FOG2/ZFPM2, FOS and ID2 proteins to be the key interacting partners of GATA4, only FOG2/ZFPM2 overexpression showed an interaction score of "high confidence" ≥ 0.84. A significant change in the MED was observed during HF. For the first time, the MED9 subunit was significantly reduced between familial DCM and HS (p < 0.05), showing an increased MED9s isoform in DCM patients with respect to its full-length transcript. MED9 and GATA4 shared the same sequence motif and were involved in a network with FOG2/ZFPM2, FOS, and ID2, proteins already implicated in cardiac development. [ABSTRACT FROM AUTHOR]

Advances in molecular tumor diagnostics have transformed cancer care. However, it remains unclear whether precision oncology has the same impact and transformative nature across all malignancies. We conducted a retrospective analysis of patients with human papillomavirus (HPV)-related gynecologic malignancies who underwent comprehensive molecular profiling and subsequent discussion at the interdisciplinary Molecular Tumor Board (MTB) of the University Hospital, LMU Munich, between 11/2017 and 06/2022. We identified a total cohort of 31 patients diagnosed with cervical (CC), vaginal or vulvar cancer. Twenty-two patients (fraction: 0.71) harbored at least one mutation. Fifteen patients (0.48) had an actionable mutation and fourteen (0.45) received a recommendation for a targeted treatment within the MTB. One CC patient received a biomarker-guided treatment recommended by the MTB and achieved stable disease on the mTOR inhibitor temsirolimus for eight months. Factors leading to non-adherence to MTB recommendations in other patient cases included informed patient refusal, rapid deterioration, stable disease, or use of alternative targeted but biomarker-agnostic treatments such as antibody–drug conjugates or checkpoint inhibitors. Despite a remarkable rate of actionable mutations in HPV-related gynecologic malignancies at our institution, immediate implementation of biomarker-guided targeted treatment recommendations remained low, and access to targeted treatment options after MTB discussion remained a major challenge. [ABSTRACT FROM AUTHOR]

Several genetic investigations were conducted to identify germline and somatic mutations in somatotropinomas, a subtype of pituitary tumors. To our knowledge, we report the first acromegaly patient carrying a RET pathogenic variant: c.2410G>A (rs79658334), p.Val804Met. Alongside the fact that the patient's father and daughter carried the same variant, we investigated the clinical significance of this variant in the context of somatotropinomas and other endocrine tumors, reviewing the RET mutations' oncogenic mechanisms. The aim was to search for new targets to precisely manage and treat acromegaly. Our case describes a new phenotype associated with the RET pathogenic variant, represented by aggressive acromegaly, and suggests consideration for RET mutation screening if NGS for well-established PitNET-associated gene mutations renders negative. [ABSTRACT FROM AUTHOR]

G protein-coupled receptors (GPCRs) are the largest class of receptors in the human genome and constitute about 30% of all drug targets. In this article, intended for a non-mathematical audience, both experimental observations and new theoretical results are compared in the context of information transmission across the cell membrane. The amount of information actually currently used or projected to be used in clinical settings is a small fraction of the information transmission capacity of the GPCR. This indicates that the number of yet undiscovered drug targets within GPCRs is much larger than what is currently known. Theoretical studies with some experimental validation indicate that localized heat deposition and dissipation are key to the identification of sites and mechanisms for drug action. [ABSTRACT FROM AUTHOR]

Prostate cancer (PCa) has been known as the most prevalent cancer disease and the second leading cause of cancer mortality in men almost all over the globe. There is an urgent need for establishment of PCa models that can recapitulate the progress of genomic landscapes and molecular alterations during development and progression of this disease. Notably, several organoid models have been developed for assessing the complex interaction between PCa and its surrounding microenvironment. In recent years, PCa organoids have been emerged as powerful in vitro 3D model systems that recapitulate the molecular features (such as genomic/epigenomic changes and tumor microenvironment) of PCa metastatic tumors. In addition, application of organoid technology in mechanistic studies (i.e., for understanding cellular/subcellular and molecular alterations) and translational medicine has been recognized as a promising approach for facilitating the development of potential biomarkers and novel therapeutic strategies. In this review, we summarize the application of PCa organoids in the high-throughput screening and establishment of relevant xenografts for developing novel therapeutics for metastatic, castration resistant, and neuroendocrine PCa. These organoid-based studies are expected to expand our knowledge from basic research to clinical applications for PCa diseases. Furthermore, we also highlight the optimization of PCa cultures and establishment of promising 3D organoid models for in vitro and in vivo investigations, ultimately facilitating mechanistic studies and development of novel clinical diagnosis/prognosis and therapies for PCa. [ABSTRACT FROM AUTHOR]

Ovarian cancer (OC) is a type of malignant tumor with a consistently high mortality rate. The diagnosis of early-stage OC and identification of functional subsets in the tumor microenvironment are essential to the development of patient management strategies. However, the development of robust models remains unsatisfactory. We aimed to utilize artificial intelligence and single-cell analysis to address this issue. Two independent datasets were screened from the Gene Expression Omnibus (GEO) database and processed to obtain overlapping differentially expressed genes (DEGs) in stage II–IV vs. stage I diseases. Three explainable machine learning algorithms were integrated to construct models that could determine the tumor stage and extract important characteristic genes as diagnostic biomarkers. Correlations between cancer-associated fibroblast (CAF) infiltration and characteristic gene expression were analyzed using TIMER2.0 and their relationship with survival rates was comprehensively explored via the Kaplan–Meier plotter (KM-plotter) online database. The specific expression of characteristic genes in fibroblast subsets was investigated through single-cell analysis. A novel fibroblast subset signature was explored to predict immune checkpoint inhibitor (ICI) response and oncogene mutation through Tumor Immune Dysfunction and Exclusion (TIDE) and artificial neural network algorithms, respectively. We found that Support Vector Machine–Shapley Additive Explanations (SVM-SHAP), Extreme Gradient Boosting (XGBoost), and Random Forest (RF) successfully diagnosed early-stage OC (stage I). The area under the receiver operating characteristic curves (AUCs) of these models exceeded 0.990. Their overlapping characteristic gene, secreted frizzled-related protein 2 (SFRP2), was a risk factor that affected the overall survival of OC patients with stage II–IV disease (log-rank test: p < 0.01) and was specifically expressed in a fibroblast subset. Finally, the SFRP2+ fibroblast signature served as a novel predictor in evaluating ICI response and exploring pan-cancer tumor protein P53 (TP53) mutation (AUC = 0.853, 95% confidence interval [CI]: 0.829–0.877). In conclusion, the models based on SVM-SHAP, XGBoost, and RF enabled the early detection of OC for clinical decision making, and SFRP2+ fibroblast signature used in diagnostic models can inform OC treatment selection and offer pan-cancer TP53 mutation detection. [ABSTRACT FROM AUTHOR]

Recently, advances in molecular biology and bioinformatics have allowed a more thorough understanding of tumorigenesis in aggressive PitNETs (pituitary neuroendocrine tumors) through the identification of specific essential genes, crucial molecular pathways, regulators, and effects of the tumoral microenvironment. Target therapies have been developed to cure oncology patients refractory to traditional treatments, introducing the concept of precision medicine. Preliminary data on PitNETs are derived from preclinical studies conducted on cell cultures, animal models, and a few case reports or small case series. This study comprehensively reviews the principal pathways involved in aggressive PitNETs, describing the potential target therapies. A search was conducted on Pubmed, Scopus, and Web of Science for English papers published between 1 January 2004, and 15 June 2023. 254 were selected, and the topics related to aggressive PitNETs were recorded and discussed in detail: epigenetic aspects, membrane proteins and receptors, metalloprotease, molecular pathways, PPRK, and the immune microenvironment. A comprehensive comprehension of the molecular mechanisms linked to PitNETs' aggressiveness and invasiveness is crucial. Despite promising preliminary findings, additional research and clinical trials are necessary to confirm the indications and effectiveness of target therapies for PitNETs. [ABSTRACT FROM AUTHOR]

Nonsense mutations cause several genetic diseases such as cystic fibrosis, Duchenne muscular dystrophy, β-thalassemia, and Shwachman–Diamond syndrome. These mutations induce the formation of a premature termination codon (PTC) inside the mRNA sequence, resulting in the synthesis of truncated polypeptides. Nonsense suppression therapy mediated by translational readthrough-inducing drugs (TRIDs) is a promising approach to correct these genetic defects. TRIDs generate a ribosome miscoding of the PTC named "translational readthrough" and restore the synthesis of full-length and potentially functional proteins. The new oxadiazole-core TRIDs NV848, NV914, and NV930 (NV) showed translational readthrough activity in nonsense-related in vitro systems. In this work, the possible off-target effect of NV molecules on natural termination codons (NTCs) was investigated. Two different in vitro approaches were used to assess if the NV molecule treatment induces NTC readthrough: (1) a study of the translational-induced p53 molecular weight and functionality; (2) the evaluation of two housekeeping proteins' (Cys-C and β2M) molecular weights. Our results showed that the treatment with NV848, NV914, or NV930 did not induce any translation alterations in both experimental systems. The data suggested that NV molecules have a specific action for the PTCs and an undetectable effect on the NTCs. [ABSTRACT FROM AUTHOR]

Revamping the current biomarker landscape of hepatocellular carcinoma (HCC) with cell-free DNA (cfDNA) could improve overall outcomes. The use of commercially available cfDNA testing (also known as liquid biopsy) is limited by the low prevalence of targetable mutations and does not have any prognostic or predictive value. Thus, current cfDNA testing cannot be relied upon for perioperative risk stratification (POR), including early detection of recurrence, long-term surveillance, predicting outcomes, and treatment response. Prior evidence on cfDNA mutation profiling (non-specific detection or gene panel testing) suggests that it can be a reliable tool for POR and prognostication, but it still requires significant improvements. cfDNA methylation changes or epigenetic markers have not been explored extensively, but early studies have shown potential for it to be a prognostic biomarker tool. The predictive value of cfDNA (mutations and EM) to assist treatment selection (systemic therapy, immune-checkpoint inhibitor vs. tyrosine kinase inhibitor) and to monitor response to systemic and locoregional therapies should be a future area of focus. We highlighted the unmet needs in the HCC management and the current role of cfDNA testing in HCC in addressing them. [ABSTRACT FROM AUTHOR]

Important advances in diabetic retinopathy (DR) research and management have occurred in the last few years. Neurodegenerative changes before the onset of microvascular alterations have been well established. So, new strategies are required for earlier and more effective treatment of DR, which still is the first cause of blindness in working age. We describe herein gene regulation through Lnc-RNAs as an interesting subject related to DR. Long non-coding RNAs (Lnc-RNAs) are non-protein-coding transcripts larger than 200 nucleotides. Lnc-RNAs regulate gene expression and protein formation at the epigenetic, transcriptional, and translational levels and can impact cell proliferation, apoptosis, immune response, and oxidative stress. These changes are known to take part in the mechanism of DR. Recent investigations pointed out that Lnc-RNAs might play a role in retinopathy development as Metastasis-Associated Lung Adenocarcinoma Transcript (Lnc-MALAT1), Maternally expressed gene 3 (Lnc-MEG3), myocardial-infarction-associated transcript (Lnc-MIAT), Lnc-RNA H19, Lnc-RNA HOTAIR, Lnc-RNA ANRIL B-Raf proto-oncogene (Lnc-RNA BANCR), small nucleolar RNA host gene 16 (Lnc-RNA SNHG16) and others. Several molecular pathways are impacted. Some of them play a role in DR pathophysiology, including the PI3K-Akt signaling axis, NAD-dependent deacetylase sirtuin-1 (Sirti1), p38 mitogen-activated protein kinase (P38/mapk), transforming growth factor beta signaling (TGF-β) and nuclear factor erythroid 2-related factor 2 (Nrf2). The way Lnc-RNAs affect diabetic retinopathy is a question of great relevance. Performing a more in-depth analysis seems to be crucial for researchers if they want to target Lnc-RNAs. New knowledge on gene regulation and biomarkers will enable investigators to develop more specialized therapies for diabetic retinopathy, particularly in the current growing context of precision medicine. [ABSTRACT FROM AUTHOR]

IgA Nephropathy (IgAN) and Membranous Nephropathy (MN) are primary immune-mediated glomerular diseases with highly variable prognosis. Current guidelines recommend that greater immunologic activity and worse prognosis should guide towards the best treatment in an individualized approach. Nevertheless, proteinuria and glomerular filtration rate, the current gold standards for prognosis assessment and treatment guidance in primary glomerular diseases, may be altered with chronic damage and nephron scarring, conditions that are not related to immune activity. In recent years, thanks to the development of new molecular technologies, among them genome-wide genotyping, RNA sequencing techniques, and mass spectrometry, we have witnessed an outstanding improvement in understanding the pathogenesis of IgAN and MN. In addition, recent genome-wide association studies have suggested potential targets for immunomodulating agents, stressing the need for the identification of specific biomarkers of immune activity. In this work, we aim to review current evidence and recent progress, including the more recent use of omics techniques, in the identification of potential biomarkers for immune monitoring in IgAN and MN. [ABSTRACT FROM AUTHOR]

Molecular profiling may enable earlier detection of pancreatic cancer (PC) in high-risk individuals undergoing surveillance and allow for personalization of treatment. We hypothesized that the detection rate of DNA mutations is higher in pancreatic juice (PJ) than in plasma due to its closer contact with the pancreatic ductal system, from which pancreatic cancer cells originate, and higher overall cell-free DNA (cfDNA) concentrations. In this study, we included patients with pathology-proven PC or intraductal papillary mucinous neoplasm (IPMN) with high-grade dysplasia (HGD) from two prospective clinical trials (KRASPanc and PACYFIC) for whom both PJ and plasma were available. We performed next-generation sequencing on PJ, plasma, and tissue samples and described the presence (and concordance) of mutations in these biomaterials. This study included 26 patients (25 PC and 1 IPMN with HGD), of which 7 were women (27%), with a median age of 71 years (IQR 12) and a median BMI of 23 kg/m2 (IQR 4). Ten patients with PC (40%) were (borderline) resectable at baseline. Tissue was available from six patients (resection n = 5, biopsy n = 1). A median volume of 2.9 mL plasma (IQR 1.0 mL) and 0.7 mL PJ (IQR 0.1 mL, p < 0.001) was used for DNA isolation. PJ had a higher median cfDNA concentration (2.6 ng/μL (IQR 4.2)) than plasma (0.29 ng/μL (IQR 0.40)). A total of 41 unique somatic mutations were detected: 24 mutations in plasma (2 KRAS, 15 TP53, 2 SMAD4, 3 CDKN2A 1 CTNNB1, and 1 PIK3CA), 19 in PJ (3 KRAS, 15 TP53, and 1 SMAD4), and 8 in tissue (2 KRAS, 2 CDKN2A, and 4 TP53). The mutation detection rate (and the concordance with tissue) did not differ between plasma and PJ. In conclusion, while the concentration of cfDNA was indeed higher in PJ than in plasma, the mutation detection rate was not different. A few cancer-associated genetic variants were detected in both biomaterials. Further research is needed to increase the detection rate and assess the performance and suitability of plasma and PJ for PC (early) detection. [ABSTRACT FROM AUTHOR]

One of the major challenges in the treatment of cancer are differential responses of patients to existing standard of care anti-cancer drugs. These differential responses may, in part, be due to a diverse range of genomic, epigenomic, proteomic, and metabolic alterations among individuals suffering from the same type of cancer. Precision medicine is an emerging approach in cancer therapeutics that takes into account specific molecular alterations, environmental factors as well as lifestyle of individual patients. This approach allows clinicians and researchers to select or predict treatments that would most likely benefit the patient based on their individual tumor characteristics. One class of precision medicine tools are predictive, in vitro drug-response assays designed to test the sensitivity of patient tumor cells to existing or novel therapies. These assays have the potential to rapidly identify the most effective treatments for cancer patients and thus hold great promise in the field of precision medicine. In this review, we have highlighted several drug-response assays developed in ovarian cancer and discussed the current challenges and future prospects of these assays in the clinical management of this disease.

Neurodegenerative diseases affect millions of people worldwide and are characterized by the chronic and progressive deterioration of neural function. Neurodegenerative diseases, such as Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and Huntington's disease (HD), represent a huge social and economic burden due to increasing prevalence in our aging society, severity of symptoms, and lack of effective disease-modifying therapies. This lack of effective treatments is partly due to a lack of reliable models. Modeling neurodegenerative diseases is difficult because of poor access to human samples (restricted in general to postmortem tissue) and limited knowledge of disease mechanisms in a human context. Animal models play an instrumental role in understanding these diseases but fail to comprehensively represent the full extent of disease due to critical differences between humans and other mammals. The advent of human-induced pluripotent stem cell (hiPSC) technology presents an advantageous system that complements animal models of neurodegenerative diseases. Coupled with advances in gene-editing technologies, hiPSC-derived neural cells from patients and healthy donors now allow disease modeling using human samples that can be used for drug discovery.

The aetiology of Kawasaki disease (KD), an acute inflammatory disorder of childhood, remains unknown despite various triggers of KD having been proposed. Host 'omic profiles offer insights into the host response to infection and inflammation, with the interrogation of multiple 'omic levels in parallel providing a more comprehensive picture. We used differential abundance analysis, pathway analysis, clustering, and classification techniques to explore whether the host response in KD is more similar to the response to bacterial or viral infections at the transcriptomic and proteomic levels through comparison of 'omic profiles from children with KD to those with bacterial and viral infections. Pathways activated in patients with KD included those involved in anti-viral and anti-bacterial responses. Unsupervised clustering showed that the majority of KD patients clustered with bacterial patients on both 'omic levels, whilst application of diagnostic signatures specific for bacterial and viral infections revealed that many transcriptomic KD samples had low probabilities of having bacterial or viral infections, suggesting that KD may be triggered by a different process not typical of either common bacterial or viral infections. Clustering based on the transcriptomic and proteomic responses during KD revealed three clusters of KD patients on both 'omic levels, suggesting heterogeneity within the inflammatory response during KD. The observed heterogeneity may reflect differences in the host response to a common trigger, or variation dependent on different triggers of the condition.

Understanding complex disease mechanisms requires a comprehensive understanding of the gene regulatory networks, as complex diseases are often characterized by the dysregulation and dysfunction of molecular networks, rather than abnormalities in single genes. Specifically, the exploration of cell line-specific gene networks can provide essential clues for precision medicine, as this methodology can uncover molecular interplays specific to particular cell line statuses, such as drug sensitivity, cancer progression, etc. In this article, we provide a comprehensive review of computational strategies for cell line-specific gene network analysis: (1) cell line-specific gene regulatory network estimation and analysis of gene networks under varying epithelial–mesenchymal transition (EMT) statuses of cell lines; and (2) an explainable artificial intelligence approach for interpreting the estimated massive multiple EMT-status-specific gene networks. The objective of this review is to help readers grasp the concept of computational network biology, which holds significant implications for precision medicine by offering crucial clues. [ABSTRACT FROM AUTHOR]

Despite being standard tools in research, the application of cellular and animal models in drug development is hindered by several limitations, such as limited translational significance, animal ethics, and inter-species physiological differences. In this regard, 3D cellular models can be presented as a step forward in biomedical research, allowing for mimicking tissue complexity more accurately than traditional 2D models, while also contributing to reducing the use of animal models. In cancer research, 3D models have the potential to replicate the tumor microenvironment, which is a key modulator of cancer cell behavior and drug response. These features make cancer 3D models prime tools for the preclinical study of anti-tumoral drugs, especially considering that there is still a need to develop effective anti-cancer drugs with high selectivity, minimal toxicity, and reduced side effects. Metallodrugs, especially transition-metal-based complexes, have been extensively studied for their therapeutic potential in cancer therapy due to their distinctive properties; however, despite the benefits of 3D models, their application in metallodrug testing is currently limited. Thus, this article reviews some of the most common types of 3D models in cancer research, as well as the application of 3D models in metallodrug preclinical studies. [ABSTRACT FROM AUTHOR]

Endocrine-resistant, hormone receptor-positive, and HER2-negative (HR+/HER2-) metastatic breast cancer (mBC) is largely governed by acquired mutations in the estrogen receptor, which promote ligand-independent activation, and by truncal alterations in the PI3K signaling pathway, with a broader range of gene alterations occurring with less prevalence. Circulating tumor DNA (ctDNA)-based technologies are progressively permeating the clinical setting. However, their utility for serial monitoring has been hindered by their significant costs, inter-technique variability, and real-world patient heterogeneity. We interrogated a longitudinal collection of 180 plasma samples from 75 HR+/HER2- mBC patients who progressed or relapsed after exposure to aromatase inhibitors and were subsequently treated with endocrine therapy (ET) by means of highly sensitive and affordable digital PCR and SafeSEQ sequencing. Baseline PIK3CA and TP53 mutations were prognostic of a shorter progression-free survival in our population. Mutant PIK3CA was prognostic in the subset of patients receiving fulvestrant monotherapy after progression to a CDK4/6 inhibitor (CDK4/6i)-containing regimen, and its suppression was predictive in a case of long-term benefit with alpelisib. Mutant ESR1 was prognostic in patients who did not receive concurrent CDK4/6i, an impact influenced by the variant allele frequency, and its early suppression was strongly predictive of efficacy and associated with long-term benefit in the whole cohort. Mutations in ESR1, TP53, and KRAS emerged as putative drivers of acquired resistance. These findings collectively contribute to the characterization of longitudinal ctDNA in real-world cases of HR+/HER2- mBC previously exposed to aromatase inhibitors and support ongoing studies either targeting actionable alterations or leveraging the ultra-sensitive tracking of ctDNA. [ABSTRACT FROM AUTHOR]

Prostate cancer is one of the most common malignant diseases in men, and it contributes significantly to the increased mortality rate in men worldwide. This study aimed to review the roles of p300 and TMPRSS2 (transmembrane protease, serine 2) in the AR (androgen receptor) pathway as they are closely related to the development and progression of prostate cancer. This paper represents a library-based study conducted by selecting the most suitable, up-to-date scientific published articles from online journals. We focused on articles that use similar techniques, particularly those that use prostate cancer cell lines and immunohistochemical staining to study the molecular impact of p300 and TMPRSS2 in prostate cancer specimens. The TMPRSS2:ERG fusion is considered relevant to prostate cancer, but its association with the development and progression as well as its clinical significance have not been fully elucidated. On the other hand, high p300 levels in prostate cancer biopsies predict larger tumor volumes, extraprostatic extension of disease, and seminal vesicle involvement at prostatectomy, and may be associated with prostate cancer progression after surgery. The inhibition of p300 has been shown to reduce the proliferation of prostate cancer cells with TMPRSS2:ETS (E26 transformation-specific) fusions, and combining p300 inhibitors with other targeted therapies may increase their efficacy. Overall, the interplay between the p300 and TMPRSS2 pathways is an active area of research. [ABSTRACT FROM AUTHOR]

Tissue biopsy is essential for NSCLC diagnosis and treatment management. Over the past decades, liquid biopsy has proven to be a powerful tool in clinical oncology, isolating tumor-derived entities from the blood. Liquid biopsy permits several advantages over tissue biopsy: it is non-invasive, and it should provide a better view of tumor heterogeneity, gene alterations, and clonal evolution. Consequentially, liquid biopsy has gained attention as a cancer biomarker tool, with growing clinical applications in NSCLC. In the era of precision medicine based on molecular typing, non-invasive genotyping methods became increasingly important due to the great number of oncogene drivers and the small tissue specimen often available. In our work, we comprehensively reviewed established and emerging applications of liquid biopsy in NSCLC. We made an excursus on laboratory analysis methods and the applications of liquid biopsy either in early or metastatic NSCLC disease settings. We deeply reviewed current data and future perspectives regarding screening, minimal residual disease, micrometastasis detection, and their implication in adjuvant and neoadjuvant therapy management. Moreover, we reviewed liquid biopsy diagnostic utility in the absence of tissue biopsy and its role in monitoring treatment response and emerging resistance in metastatic NSCLC treated with target therapy and immuno-therapy. [ABSTRACT FROM AUTHOR]

There is early evidence of extraocular systemic signals effecting function and morphology in neovascular age-related macular degeneration (nAMD). The prospective, cross-sectional BIOMAC study is an explorative investigation of peripheral blood proteome profiles and matched clinical features to uncover systemic determinacy in nAMD under anti-vascular endothelial growth factor intravitreal therapy (anti-VEGF IVT). It includes 46 nAMD patients stratified by the level of disease control under ongoing anti-VEGF treatment. Proteomic profiles in peripheral blood samples of every patient were detected with LC-MS/MS mass spectrometry. The patients underwent extensive clinical examination with a focus on macular function and morphology. In silico analysis includes unbiased dimensionality reduction and clustering, a subsequent annotation of clinical features, and non-linear models for recognition of underlying patterns. The model assessment was performed using leave-one-out cross validation. The findings provide an exploratory demonstration of the link between systemic proteomic signals and macular disease pattern using and validating non-linear classification models. Three main results were obtained: (1) Proteome-based clustering identifies two distinct patient subclusters with the smaller one (n = 10) exhibiting a strong signature for oxidative stress response. Matching the relevant meta-features on the individual patient's level identifies pulmonary dysfunction as an underlying health condition in these patients. (2) We identify biomarkers for nAMD disease features with Aldolase C as a putative factor associated with superior disease control under ongoing anti-VEGF treatment. (3) Apart from this, isolated protein markers are only weakly correlated with nAMD disease expression. In contrast, applying a non-linear classification model identifies complex molecular patterns hidden in a high number of proteomic dimensions determining macular disease expression. In conclusion, so far unconsidered systemic signals in the peripheral blood proteome contribute to the clinically observed phenotype of nAMD, which should be examined in future translational research on AMD. [ABSTRACT FROM AUTHOR]

Bipolar disorder (BD) is a severe chronic disorder that represents one of the main causes of disability among young people. To date, no reliable biomarkers are available to inform the diagnosis of BD or clinical response to pharmacological treatment. Studies focused on coding and noncoding transcripts may provide information complementary to genome-wide association studies, allowing to correlate the dynamic evolution of different types of RNAs based on specific cell types and developmental stage with disease development or clinical course. In this narrative review, we summarize findings from human studies that evaluated the potential utility of messenger RNAs and noncoding transcripts, such as microRNAs, circular RNAs and long noncoding RNAs, as peripheral markers of BD and/or response to lithium and other mood stabilizers. The majority of available studies investigated specific targets or pathways, with large heterogeneity in the included type of cells or biofluids. However, a growing number of studies are using hypothesis-free designs, with some studies also integrating data on coding and noncoding RNAs measured in the same participants. Finally, studies conducted in neurons derived from induced-pluripotent stem cells or in brain organoids provide promising preliminary findings supporting the power and utility of these cellular models to investigate the molecular determinants of BD and clinical response. [ABSTRACT FROM AUTHOR]

Pediatric brain tumors remain a significant source of morbidity and mortality. Though developments have been made in treating these malignancies, the blood–brain barrier, intra- and inter-tumoral heterogeneity, and therapeutic toxicity pose challenges to improving outcomes. Varying types of nanoparticles, including metallic, organic, and micellar molecules of varying structures and compositions, have been investigated as a potential therapy to circumvent some of these inherent challenges. Carbon dots (CDs) have recently gained popularity as a novel nanoparticle with theranostic properties. This carbon-based modality is highly modifiable, allowing for conjugation to drugs, as well as tumor-specific ligands in an effort to more effectively target cancerous cells and reduce peripheral toxicity. CDs are being studied pre-clinically. The ClinicalTrials.gov site was queried using the search terms: brain tumor and nanoparticle, liposome, micelle, dendrimer, quantum dot, or carbon dot. At the time of this review, 36 studies were found, 6 of which included pediatric patients. Two of the six studies investigated nanoparticle drug formulations, whereas the other four studies were on varying liposomal nanoparticle formulations for the treatment of pediatric brain tumors. Here, we reviewed the context of CDs within the broader realm of nanoparticles, their development, promising pre-clinical potential, and proposed future translational utility. [ABSTRACT FROM AUTHOR]

Kidney renal clear cell carcinoma (KIRC) accounts for approximately 75% of all renal cancers. The prognosis for patients with metastatic KIRC is poor, with less than 10% surviving five years after diagnosis. Inner membrane mitochondrial protein (IMMT) plays a crucial role in shaping the inner mitochondrial membrane (IMM), regulation of metabolism and innate immunity. However, the clinical relevance of IMMT in KIRC is not yet fully understood, and its role in shaping the tumor immune microenvironment (TIME) remains unclear. This study aimed to investigate the clinical significance of IMMT in KIRC using a combination of supervised learning and multi-omics integration. The supervised learning principle was applied to analyze a TCGA dataset, which was downloaded and split into training and test datasets. The training dataset was used to train the prediction model, while the test and the entire TCGA dataset were used to evaluate its performance. Based on the risk score, the cutoff between the low and high IMMT group was set at median value. A Kaplan-Meier curve, receiver operating characteristic (ROC) curve, principal component analysis (PCA) and Spearman's correlation were conducted to evaluate the prediction ability of the model. Gene Set Enrichment Analysis (GSEA) was used to investigate the critical biological pathways. Immunogenicity, immunological landscape and single-cell analysis were performed to examine the TIME. Databases including Gene Expression Omnibus (GEO), Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) were employed for inter-database verification. Pharmacogenetic prediction was analyzed via single-guide RNA (sgRNA)-based drug sensitivity screening using Q-omics v.1.30. Low expressions of IMMT in tumor predicted dismal prognosis in KIRC patients and correlated with KIRC progression. GSEA revealed that low expressions of IMMT were implicated in mitochondrial inhibition and angiogenetic activation. In addition, low IMMT expressions had associations with reduced immunogenicity and an immunosuppressive TIME. Inter-database verification corroborated the correlation between low IMMT expressions, KIRC tumors and the immunosuppressive TIME. Pharmacogenetic prediction identified lestaurtinib as a potent drug for KIRC in the context of low IMMT expressions. This study highlights the potential of IMMT as a novel biomarker, prognostic predictor and pharmacogenetic predictor to inform the development of more personalized and effective cancer treatments. Additionally, it provides important insights into the role of IMMT in the mechanism underlying mitochondrial activity and angiogenesis development in KIRC, which suggests IMMT as a promising target for the development of new therapies. [ABSTRACT FROM AUTHOR]

The complexity of the cellular and non-cellular milieu surrounding human tumors plays a decisive role in the course and outcome of disease. The high variability in the distribution of the immune and non-immune compartments within the tumor microenvironments (TME) among different patients governs the mode of their response or resistance to current immunotherapeutic approaches. Through deciphering this diversity, one can tailor patients' management to meet an individual's needs. Single-cell (sc) omics technologies have given a great boost towards this direction. This review gathers recent data about how multi-omics profiling, including the utilization of single-cell RNA sequencing (scRNA-seq), assay for transposase-accessible chromatin with sequencing (scATAC-seq), T-cell receptor sequencing (scTCR-seq), mass, tissue-based, or microfluidics cytometry, and related bioinformatics tools, contributes to the high-throughput assessment of a large number of analytes at single-cell resolution. Unravelling the exact TCR clonotype of the infiltrating T cells or pinpointing the classical or novel immune checkpoints across various cell subsets of the TME provide a boost to our comprehension of adaptive immune responses, their antigen specificity and dynamics, and grant suggestions for possible therapeutic targets. Future steps are expected to merge high-dimensional data with tissue localization data, which can serve the investigation of novel multi-modal biomarkers for the selection and/or monitoring of the optimal treatment from the current anti-cancer immunotherapeutic armamentarium. [ABSTRACT FROM AUTHOR]

The emergence of high-throughput approaches has had a profound impact on personalized medicine, evolving the identification of inheritable variation to trajectory analyses of transient states and paving the way for the unveiling of response biomarkers. The utilization of the multi-layered pharmaco-omics data, including genomics, transcriptomics, proteomics, and relevant biological information, has facilitated the identification of key molecular biomarkers that can predict the response to therapy, thereby optimizing treatment regiments and providing the framework for a tailored treatment plan. Despite the availability of multiple therapeutic options for chronic diseases, the highly heterogeneous clinical response hinders the alleviation of disease signals and exacerbates the annual burden and cost of hospitalization and drug regimens. This review aimed to examine the current state of the pharmaco-omic approaches performed in psoriasis, a common inflammatory disease of the skin. We sought to identify central studies that investigate the inter-individual variability and explore the underlying molecular mechanisms of drug response progression via biological profiling in psoriatic patients administered with the extended therapeutic armamentarium of psoriasis, incorporating conventional therapies, small molecules, as well as biological drugs that inhibit central pathogenic cytokines involved in the disease pathogenesis. [ABSTRACT FROM AUTHOR]

In the past decade, immense progress has been made in advancing personalized medicine to effectively address patient-specific disease complexities in order to develop individualized treatment strategies. In particular, the emergence of 3D bioprinting for in vitro models of tissue and organ engineering presents novel opportunities to improve personalized medicine. However, the existing bioprinted constructs are not yet able to fulfill the ultimate goal: an anatomically realistic organ with mature biological functions. Current bioprinting approaches have technical challenges in terms of precise cell deposition, effective differentiation, proper vascularization, and innervation. This review introduces the principles and realizations of bioprinting with a strong focus on the predominant techniques, including extrusion printing and digital light processing (DLP). We further discussed the applications of bioprinted constructs, including the engraftment of stem cells as personalized implants for regenerative medicine and in vitro high-throughput drug development models for drug discovery. While no one-size-fits-all approach to bioprinting has emerged, the rapid progress and promising results of preliminary studies have demonstrated that bioprinting could serve as an empowering technology to resolve critical challenges in personalized medicine. [ABSTRACT FROM AUTHOR]