Drug Response In Patients Research Articles

Modeling Drug Responses and Evolutionary Dynamics using Patient-Derived Xenografts Reveals Precision Medicine Strategies for Triple Negative Breast Cancer

Abstract The inter- and intra-tumor heterogeneity of triple negative breast cancers (TNBC), which is reflected in diverse drug responses, interplays with tumor evolution. Here, we developed a preclinical experimental and analytical framework using treatment-naive TNBC patient-derived tumor xenografts (PDTX) to test their predictive value in personalized cancer treatment approaches. Patients and their matched PDTX exhibited concordant drug responses to neoadjuvant therapy using two trial designs and dosing schedules. This platform enabled analysis of non-genetic mechanisms involved in relapse dynamics. Treatment resulted in permanent phenotypic changes with functional and therapeutic consequences. High throughput drug screening methods in ex vivo patient derived tumor xenograft cells (PDTCs) revealed patient-specific drug response changes dependent on first-line therapy. This was validated in vivo, as exemplified by a change in olaparib sensitivity in tumors previously treated with clinically relevant cycles of standard-of-care chemotherapy. In summary, PDTXs provide a robust tool to test patient drug responses and therapeutic regimens and to model evolutionary trajectories. However, high inter-model variability and permanent non-genomic transcriptional changes constrain their use for personalized cancer therapy. This work highlights important considerations associated with preclinical drug response modeling and potential uses of the platform to identify efficacious and preferential sequential therapeutic regimens.

Organoids research progress in gynecological cancers: a bibliometric analysis

Background Gynecological cancers (GC) pose a severe threat to the health and safety of women’s lives, and organoids, as in-vitro research models, have demonstrated significant advantages in simulating tissue characteristics and drug screening. In recent years, there has been a rapid increase in research outcomes related to organoids in GC. However, there has been no bibliometric study concerning.Methods Publications related to GC and organoids from 2010-2023 were retrieved from the Web of Science Core Collection (WoSCC). We conducted a bibliometric analysis and visualization using CiteSpace, VOSviewer, and the Bibliometrix R Package. This analysis included the spatiotemporal distribution, author, sources, references, and keywords.Results A total of 333 publications were included. The number of annual publications indicated an explosive phase of development since 2019. The USA was the most important country in terms of cooperation, publication output, citation and centrality. University of California system ranked first in productivity among institutions, and HIPPO Y is the most relevant author in the research field. CANCERS published the most documents, and NATURE is the most cited sources. Analysis of Keywords and References, it is possible to establish the trend, and find the hotspots in the research field.Conclusion This bibliometric analysis delineated global landscapes and progress trends in GC organoids research. This study emphasized that organoids can effectively replicate the original tissue or tumors, providing a good in-vitro model for research on tumor-related mechanisms and showing significant advantages in drug screening and efficacy clinical prediction. Additionally, as preclinical models, they provide compelling evidence for personalized therapy and prediction of patient drug responses.

A structurally informed human protein-protein interactome reveals proteome-wide perturbations caused by disease mutations.

To assist the translation of genetic findings to disease pathobiology and therapeutics discovery, we present an ensemble deep learning framework, termed PIONEER (Protein-protein InteractiOn iNtErfacE pRediction), that predicts protein-binding partner-specific interfaces for all known protein interactions in humans and seven other common model organisms to generate comprehensive structurally informed protein interactomes. We demonstrate that PIONEER outperforms existing state-of-the-art methods and experimentally validate its predictions. We show that disease-associated mutations are enriched in PIONEER-predicted protein-protein interfaces and explore their impact on disease prognosis and drug responses. We identify 586 significant protein-protein interactions (PPIs) enriched with PIONEER-predicted interface somatic mutations (termed oncoPPIs) from analysis of approximately 11,000 whole exomes across 33 cancer types and show significant associations of oncoPPIs with patient survival and drug responses. PIONEER, implemented as both a web server platform and a software package, identifies functional consequences of disease-associated alleles and offers a deep learning tool for precision medicine at multiscale interactome network levels.

FOXN3-AS1: A Candidate Prognostic Marker and Epigenetic Target with Immunotherapeutic Implications in Acute Myeloid Leukemia.

We focused on the FOXN3 gene and selected its antisense transcripts (FOXN3-AS1) to investigate its potential involvement in acute myeloid leukemia (AML). Several integrated multi-omics datasets have expanded the horizons of the cancer landscape. With the emergence of new high-throughput technologies, a large number of non-coding RNAs have been confirmed to be involved in the pathogenesis of different types of hematological malignancies. We conducted experimental validation using quantitative polymerase chain reaction (qPCR) with bone marrow specimens from AML patients. Then, Kaplan-Meier (KM) and Receiver Operating Characteristic (ROC) curves were used to substantiate the prognostic association between FOXN3-AS1 and AML patients within the TCGA database. Correlation between FOXN3-AS1 expression and gene mutation, immune, and immune function using Spearman correlation analysis. To explore the physical and functional interaction between FOXN3-AS1 and the DNMT1 protein, we utilized the RPISeq web tool from Iowa State University. Subsequently, we performed qPCR experiments to test the effect of 5AzaC (DNMT1 inhibitor) on FOXN3-AS1 expression AML cell lines (THP1 and OCI-AML3). We leveraged the "OncoPredict" R package in conjunction with the Genomics of Drug Sensitivity (GDSC) database to predict drug response in AML patients expressing FOXN3-AS1. We observed a significant upregulation of FOXN3-AS1 expression in AML patients compared to healthy controls using clinical samples. The TCGA database revealed an association between high FOXN3-AS1 expression and adverse prognosis. In our subsequent analysis, genes with poor prognostic implications in AML patients were exclusively identified in the FOXN3-AS1 high-expression group, further corroborating this relationship. AML patients with higher FOXN3-AS1 expression levels may respond less optimally to immunotherapy than patients with lower levels. Besides, we computationally predicted the interaction of FOXN3- AS1 and DNMT1 protein and experimentally confirmed that DNMT1i (GSK-3484862) affects the expression level of FOXN3-AS1. We also found that the chemotherapy drugs (5-Fluorouralic, Cisplatin, Dactolisib, Sapitinib, Temozolomide, Ulixertinib, Vinorelbine, Ruxolitinib, Osimertinib and Cisplatin) showed favorable responses in AML patients with high FOXN3-AS1 expression levels. Our candidate approach identifies FOXN3-AS1 as a prognostic indicator of survival in AML with a potential immune-related role. The preliminary observations we made on FOXN3-AS1/DNMT1 crosstalk warrant more in-depth invested immunotherapeutic approaches in AML.

Quantitative Systems Pharmacology Models: Potential Tools for Advancing Drug Development for Rare Diseases.

Rare diseases, affecting millions globally, present significant drug development challenges. This is due to the limited patient populations and the unique pathophysiology of these diseases, which can make traditional clinical trial designs unfeasible. Quantitative Systems Pharmacology (QSP) models offer a promising approach to expedite drug development, particularly in rare diseases. QSP models provide a mechanistic representation of the disease and drug response in virtual patients that can complement routinely applied empirical modeling and simulation approaches. QSP models can generate digital twins of actual patients and mechanistically simulate the disease progression of rare diseases, accounting for phenotypic heterogeneity. QSP models can also support drug development in various drug modalities, such as gene therapy. Impactful QSP models case studies are presented here to illustrate their value in supporting various aspects of drug development in rare indications. As these QSP model applications continue to mature, there is a growing possibility that they could be more widely integrated into routine drug development steps. This integration could provide a robust framework for addressing some of the inherent challenges in rare disease drug development.

MicroRNA-506 as a tumor suppressor in prostate cancer by regulation of Hippo signaling pathway

IntroductionProstate cancer (PCa) is considered as one of the leading causes of cancer related deaths among males globally. There is a high rate of tumor relapse and metastasis in PCa patients that is associated with chemo-resistance. Beside the elimination of tumor cells, chemotherapy has an adverse effect in normal cells. Therefore, it is required to clarify the molecular tumor biology to introduce novel markers to predict the drug response in PCa patients. Hippo signaling pathway is an important regulator of cell proliferation, migration, and drug response that can be modulated by microRNAs (miRNAs). Since, miR-506 deregulation has been reported in PCs, in the present study we assessed a probable role of miR-506 in regulation of Hippo signaling pathway during prostate tumor cell migration and drug resistance. Materials and methodsThe mRNA expression levels of Hippo signaling components were assessed in miR-506 ectopic expressed in comparison with control PC3 cells. Apoptosis assay, drug response, and cell migration were also assessed to find the role of miR-506 in prostate tumor cell aggressiveness. ResultsMiR-506 promoted the Hippo signaling pathway via TAZ and CTGF up regulations, while BIRC5, FAT, and C-MYC down regulations in PC3 cells. MiR-506 significantly reduced prostate tumor cell migration (p = 0.019) and Paclitaxel (TXL) resistance (p = 0.0006), while promoted apoptosis (p < 0.0001). ConclusionmiR-506 exerted a tumor suppressor role during PCa progression by activation of Hippo pathway. MiR-506 targeted the FAT to activate the YAP/TAZ and nuclear translocation where it can bind with TEAD to up regulate the CTGF that resulted in reduced PCa cell migration. The WNT inhibition and C-MYC down regulation by the CTGF resulted in BIRC5 down regulation that induced apoptosis in PCa cells. Therefore, miR-506 can be introduced as a therapeutic marker in PCa following the confirmation by the animal studies and further clinical trials.

Pharmacogenomic Analysis in Determining Optimal Drug Dosage in Chronic Disease Patients in Indonesia

. Pharmacogenomics, the science that combines genetics with pharmacology, plays a vital role in determining the optimal dosage of drugs for patients, especially those with chronic diseases. In Indonesia, the use of pharmacogenomic approaches is still limited even though the genetically diverse population requires more personalized dosage adjustments. This study aims to analyze the effect of genetic variation on drug response in patients with chronic diseases, such as diabetes, hypertension, and cardiovascular disease, in Indonesia. By collecting and analyzing genetic data and patient clinical data, this study will identify genetic biomarkers associated with drug metabolism and therapeutic effectiveness. The results of this study are expected to provide guidance for more accurate and personalized drug dosage determination, which will ultimately improve therapeutic outcomes and reduce the risk of side effects. This study is also expected to encourage wider adoption of pharmacogenomic approaches in clinical practice in Indonesia, as part of the effort towards more personalized and effective medicine.

Change in prostate tissue gene expression following finasteride or doxazosin administration in the medical therapy for prostatic symptoms (MTOPS) study

Benign prostatic hyperplasia (BPH) may decrease patient quality of life and often leads to acute urinary retention and surgical intervention. While effective treatments are available, many BPH patients do not respond or develop resistance to treatment. To understand molecular determinants of clinical symptom persistence after initiating BPH treatment, we investigated gene expression profiles before and after treatments in the prostate transitional zone of 108 participants in the Medical Therapy of Prostatic Symptoms (MTOPS) Trial. Unsupervised clustering revealed molecular subgroups characterized by expression changes in a large set of genes associated with resistance to finasteride, a 5α-reductase inhibitor. Pathway analyses within this gene cluster found finasteride administration induced changes in fatty acid metabolism, amino acid metabolism, immune response, steroid hormone metabolism, and kinase activity within the transitional zone. We found that patients without this transcriptional response were highly likely to develop clinical progression, which is expected in 13.2% of finasteride-treated patients. Importantly, a patient’s transcriptional response to finasteride was associated with their pre-treatment kinase expression. Further, we identified novel expression signatures of finasteride resistance among the transcriptionally responded patients. These patients showed different gene expression profiles at baseline and increased prostate transitional zone volume compared to the patients who responded to the treatment. Our work suggests molecular mechanisms of clinical resistance to finasteride treatment that could be potentially helpful for personalized BPH treatment as well as new drug development to increase patient drug response.

Drug Response of Iranian Alzheimer's Patients to Rivastigmine Concerning Their Genotype for VDR rs11568820 and MTHFR C677T Variants: A Pharmacogenetic and Association Study.

Alzheimer's disease is a neurodegenerative disorder with polygenic etiology. Genetic risk variants for Alzheimer's disease differ among populations. Thus, discovering them in each population is clinically important. A total of 118 patients and 97 controls for VDR rs11568820 and 88 patients and 100 healthy controls for MTHFR C677T polymorphism were genotyped to evaluate the association of these polymorphisms with late-onset Alzheimer's disease in the Iranian population, along with their impacts on the response to Rivastigmine treatment. The VDR C allele was significantly associated with Alzheimer's disease and provided protection against it (P = 0.003, RR = 1.14, 95% CI 1.04-1.24), while the T allele increased susceptibility (P = 0.003, RR = 1.93, 95% CI 1.23-3.02). These results were also considerable upon excluding the effect of APOE ε4 allele. The Prevalence-corrected Positive Predictive Value was 1.71% for the VDR CC genotype and 4% for the VDR CT genotype, indicating lower and almost twofold higher chances of developing Alzheimer's disease, respectively. No significant correlation was observed between MTHFR C677T and Alzheimer's disease. Based on our pharmacogenetic study, MTHFR T allele carriers lacking APOE ε4 allele showed a better response to Rivastigmine treatment after a 2-year follow-up. Moreover, patients with VDR CC genotype displayed milder Alzheimer's disease, particularly when coincided with the APOE ε4 allele. The VDR rs11568820 polymorphism affects both Alzheimer's disease risk and the response to Rivastigmine in Iranian patients. Also, MTHFR C677T polymorphism may play a role in the response to Rivastigmine, through a pathway that needs to be elucidated in future studies.

Characterization of Chemoresistance in Pancreatic Cancer: A Look at MDR-1 Polymorphisms and Expression in Cancer Cells and Patients.

Pancreatic malignancy is the fourth cause of cancer-related death in Western countries and is predicted to become the second leading cause of cancer-related mortality by 2030. The standard therapies (FOLFIRINOX and gemcitabine with nab-paclitaxel) are not resolutive because this type of cancer is also characterized by a high chemoresistance, due in part to the activity of the ATP Binding Cassette (ABC) pumps accounting for the reduction in the intracellular concentration of the drugs. In this work, we analyze the occurrence of single-nucleotide polymorphisms (SNPs) in the MDR-1 gene, in different pancreatic cancer cell lines, and in tissues from pancreatic cancer patients by DNA sequencing, as well as the expression levels of MDR-1 mRNA and protein, by qRT-PCR and Western Blot analysis. We found that gemcitabine-resistant cells, in conjunction with homozygosis of analyzed SNPs, showed high MDR-1 basal levels with further increases after gemcitabine treatment. Nevertheless, we did not observe in the human PDAC samples a correlation between the level of MDR-1 mRNA and protein expression and SNPs. Preliminary, we conclude that in our small cohort, these SNPs cannot be used as molecular markers for predicting the levels of MDR-1 mRNA/protein levels and drug responses in patients with PDAC.

Analysis of the current situation of pharmacogenomics in terms of educational and healthcare needs in Egypt and Lebanon.

Pharmacogenomics (PGx) is a practice that investigates the link between genetic differences and drug response in patients. This can improve treatment effectiveness and reduce harmful side effects. However, has yet to be adequately realized in developing nations. Three surveys were conducted between November 2022 to March 2023 in Egypt and Lebanon. The first survey assessed availability of PGx testing in different healthcare facilities; the second one assessed knowledge, interest and attitude toward learning about PGx among pharmacists and physicians; and the third one assessed interest in providing PGx education at academic levels. In Egypt, a few of the surveyed healthcare facilities are conducting some form of pharmacogenetic testing. In Lebanon, very few germline pharmacogenomic tests are offered in Greater Beirut's leading hospitals, and no other testing was recorded. PGx education attracts considerable interest, with 34.3% of pharmacists very interested and 48.8% interested. Similarly, 24.8% of total physicians were very interested while 44.8% were interested. Academic professionals in the surveyed institutions in both countries agreed on the need for educational programs in PGx and 78.2% agreed that there were good opportunities for implementing PGx testing. These findings clearly indicate the need to develop and implement educational programs in PGx in the Middle-East.

Investigating the impact of SMAD2 and SMAD4 downregulation in colorectal cancer and their correlation with immune markers, prognosis, and drug resistance and sensitivity.

While many genes linked to colorectal cancer (CRC) contribute to cancer development, a thorough investigation is needed to explore crucial hub genes yet to be fully studied. A pivotal pathway in CRC is transforming growth factor-beta (TGF-β). This study aimed to assess SMAD2 and SMAD4 gene expression from this pathway. Counted data from the Cancer Genome Atlas (TCGA) were examined, comparing 483 tumor and 41 normal samples. Using clinical data, genes impacting overall survival (OS) were evaluated. GSE39582 was employed to confirmed the levels of genes in CRC compared to the normal samples. Additionally, employing unhealthy samples and the RT-qPCR means our outcomes was validated. Finally, PharmacoGx information were utilized to connect the levels of potential genes to drug tolerance and susceptibility. Our findings showed SMAD2 and SMAD4 levels in TGF-β signaling were more significant than other pathway genes. Our findings indicated that the protein levels of these genes were lower in malignant tissues than in healthy tissues. Results revealed a significant correlation between low levels of SMAD2 and unfavorable OS in CRC individuals. RT-qPCR results demonstrated decreased expressions of both SMAD2 and SMAD4 in cancer tissues compared to elevated levels in adjacent normal samples. Our results showed significant association between selected genes and immune cell infiltration markers such as CD8+, and B-cells. Our results indicated a potential association among the levels of SMAD2 and SMAD4 genes and tolerance and susceptibility to Nilotinib and Panobinostat drugs. Reduced expression of SMAD2 and SMAD4 may be pivotal in CRC progression, impacting downstream genes unrelated to patient OS. These findings suggest a potential role for SMAD2 and SMAD4 as predictive markers for drug response in CRC patients.

Prediction of drug targets related to HCC metastasis from the perspective of programmed cell death based on transformer

Hepatocellular carcinoma (HCC) ranks as the sixth most prevalent cancer globally and the third leading cause of cancer-related deaths. The early diagnosis of HCC is challenging, and its propensity for metastasis results in generally poor prognosis. Existing studies have demonstrated a close association between HCC metastasis and programmed cell death (PCD). However, due to the high-dimensional, high-order nonlinear interactions and complex regulatory mechanisms of genes, establishing the biological process from genes to PCD to HCC metastasis through biological experiments is difficult. These genes represent crucial drug targets for blocking HCC progression. Deep learning technologies, particularly Transformer models, have shown great potential in analyzing clinical and genetic data in oncology. In this study, we identified 147 key genes related to PCD that are closely associated with HCC metastasis and developed a Transformer-based predictive model for HCC metastasis. To elucidate the potential of these genes as drug targets, we first investigated the impact of various types of PCD on the pathophysiology of HCC. Subsequently, we validated the drug responses of different patients through immunoassays and drug sensitivity tests. Finally, survival analysis indicated that these genes significantly affect patient survival rates. In summary, we have identified numerous drug targets influencing HCC metastasis through PCD.

Identification of a Macrophage marker gene signature to evaluate immune infiltration and therapeutic response in hepatocellular carcinoma

BackgroundOnly a minority of hepatocellular carcinoma (HCC) patients can benefit from systemic regimens. Macrophages, which abundantly infiltrate in HCC, could mediate tumour microenvironment remodelling and immune escape, proving to be powerful weapons in combating HCC. Thus, a deeper understanding of macrophages is necessary for improving existing antitumour treatments. MethodsWith a series of bioinformatic approaches, we comprehensively explored the role of macrophage-related genes in human HCCs from multiple single-cell and bulk RNA sequencing datasets. Unsupervised clustering was performed to cluster the macrophage marker genes (MMGs). GSVA and functional enrichment analysis were used to elucidate the functional differences among the MMG-associated clusters. Subsequently, a component analysis algorithm was used to construct a Macrosig score, and the prognosis, biological characteristics, mutation profile, TME cell infiltration status and drug response of patients with different Macrosig scores were further analysed. ResultsWe identified 13 MMGs in 574 HCC samples, based on which three MMG-associated clusters were defined. Overall survival time, clinicopathological features and immune infiltration scores differed among the different clusters. On this basis, 12 hub genes were identified among these clusters; subsequently, a scoring system was constructed to determine the Macrosig score. Importantly, patients with low-Macrosig scores, characterized by increased immune infiltration, increased mutation frequency and increased immune checkpoint expression, including CTLA-4, LAG3, PDCD1 and TIGIT, exhibited enhanced efficacy of immunotherapy when validated in an external database. Moreover, a low-Macrosig score indicates increased sensitivity to AZD.2281, A.443654, ABT.263, ABT.888, AG.014699 and ATRA, while a high Macrosig score indicates increased sensitivity to AZD6482, AKT inhibitor VIII, AS601245, AZ628, AZD.0530 and AZD6244. ConclusionsA novel scoring system was constructed to guide more effective prognostic evaluation and tailoring therapeutic regimens for HCC patients.

Accurate and comprehensive evaluation of O6-methylguanine-DNA methyltransferase promoter methylation by nanopore sequencing.

The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter region is essential in evaluating the prognosis and predicting the drug response in patients with glioblastoma. In this study, we evaluated the utility of using nanopore long-read sequencing as a method for assessing methylation levels throughout the MGMT CpG-island, compared its performance to established techniques and demonstrated its clinical applicability. We analysed 165 samples from CNS tumours, focusing on the MGMT CpG-island using nanopore sequencing. Oxford Nanopore Technologies (ONT) MinION and PromethION flow cells were employed for single sample or barcoded assays, guided by a CRISPR/Cas9 protocol, adaptive sampling or as part of a whole genome sequencing assay. Methylation data obtained through nanopore sequencing were compared to results obtained via pyrosequencing and methylation bead arrays. Hierarchical clustering was applied to nanopore sequencing data for patient stratification. Nanopore sequencing displayed a strong correlation (R2 = 0.91) with pyrosequencing results for the four CpGs of MGMT analysed by both methods. The MGMT-STP27 algorithm's classification was effectively reproduced using nanopore data. Unsupervised hierarchical clustering revealed distinct patterns in methylated and unmethylated samples, providing comparable survival prediction capabilities. Nanopore sequencing yielded high-confidence results in a rapid timeframe, typically within hours of sequencing, and extended the analysis to all 98 CpGs of the MGMT CpG-island. This study presents nanopore sequencing as a valid and efficient method for determining MGMT promotor methylation status. It offers a comprehensive view of the MGMT promoter methylation landscape, which enables the identification of potentially clinically relevant subgroups of patients. Further exploration of the clinical implications of patient stratification using nanopore sequencing of MGMT is warranted.

Pro-resolving lipid mediator reduces amyloid-β42-induced gene expression in human monocyte-derived microglia.

JOURNAL/nrgr/04.03/01300535-202503000-00031/figure1/v/2024-06-17T092413Z/r/image-tiff Specialized pro-resolving lipid mediators including maresin 1 mediate resolution but the levels of these are reduced in Alzheimer's disease brain, suggesting that they constitute a novel target for the treatment of Alzheimer's disease to prevent/stop inflammation and combat disease pathology. Therefore, it is important to clarify whether they counteract the expression of genes and proteins induced by amyloid-β. With this objective, we analyzed the relevance of human monocyte-derived microglia for in vitro modeling of neuroinflammation and its resolution in the context of Alzheimer's disease and investigated the pro-resolving bioactivity of maresin 1 on amyloid-β42-induced Alzheimer's disease-like inflammation. Analysis of RNA-sequencing data and secreted proteins in supernatants from the monocyte-derived microglia showed that the monocyte-derived microglia resembled Alzheimer's disease-like neuroinflammation in human brain microglia after incubation with amyloid-β42. Maresin 1 restored homeostasis by down-regulating inflammatory pathway related gene expression induced by amyloid-β42 in monocyte-derived microglia, protection of maresin 1 against the effects of amyloid-β42 is mediated by a re-balancing of inflammatory transcriptional networks in which modulation of gene transcription in the nuclear factor-kappa B pathway plays a major part. We pinpointed molecular targets that are associated with both neuroinflammation in Alzheimer's disease and therapeutic targets by maresin 1. In conclusion, monocyte-derived microglia represent a relevant in vitro microglial model for studies on Alzheimer's disease-like inflammation and drug response for individual patients. Maresin 1 ameliorates amyloid-β42-induced changes in several genes of importance in Alzheimer's disease, highlighting its potential as a therapeutic target for Alzheimer's disease.

Evaluating the Role of Neddylation Modifications in Kidney Renal Clear Cell Carcinoma: An Integrated Approach Using Bioinformatics, MLN4924 Dosing Experiments, and RNA Sequencing.

Neddylation, a post-translational modification process, plays a crucial role in various human neoplasms. However, its connection with kidney renal clear cell carcinoma (KIRC) remains under-researched. We validated the Gene Set Cancer Analysis Lite (GSCALite) platform against The Cancer Genome Atlas (TCGA) database, analyzing 33 cancer types and their link with 17 neddylation-related genes. This included examining copy number variations (CNVs), single nucleotide variations (SNVs), mRNA expression, cellular pathway involvement, and methylation. Using Gene Set Variation Analysis (GSVA), we categorized these genes into three clusters and examined their impact on KIRC patient prognosis, drug responses, immune infiltration, and oncogenic pathways. Afterward, our objective is to identify genes that exhibit overexpression in KIRC and are associated with an adverse prognosis. After pinpointing the specific target gene, we used the specific inhibitor MLN4924 to inhibit the neddylation pathway to conduct RNA sequencing and related in vitro experiments to verify and study the specificity and potential mechanisms related to the target. This approach is geared towards enhancing our understanding of the prognostic importance of neddylation modification in KIRC. We identified significant CNV, SNV, and methylation events in neddylation-related genes across various cancers, with notably higher expression levels observed in KIRC. Cluster analysis revealed a potential trade-off in the interactions among neddylation-related genes, where both high and low levels of gene expression are linked to adverse prognoses. This association is particularly pronounced concerning lymph node involvement, T stage classification, and Fustat score. Simultaneously, our research discovered that PSMB10 exhibits overexpression in KIRC when compared to normal tissues, negatively impacting patient prognosis. Through RNA sequencing and in vitro assays, we confirmed that the inhibition of neddylation modification could play a role in the regulation of various signaling pathways, thereby influencing the prognosis of KIRC. Moreover, our results underscore PSMB10 as a viable target for therapeutic intervention in KIRC, opening up novel pathways for the development of targeted treatment strategies. This study underscores the regulatory function and potential mechanism of neddylation modification on the phenotype of KIRC, identifying PSMB10 as a key regulatory target with a significant role in influencing the prognosis of KIRC.

Serum levels of tumour necrosis factor (TNF-α) and interleukin-17 (IL-17) in patients with nail psoriasis: A cross-sectional study.

Background Psoriasis is a common chronic inflammatory disorder affecting all aspects of a patient's life. Nail involvement is frequent, but little is known about its associated inflammatory biomarker profile, including similarities or differences from cutaneous disease. Aims We conducted this cross-sectional study to evaluate serum levels of inflammatory cytokines [tumour necrosis factor-alpha (TNF-α) and interleukin -17 (IL-17)] in patients with nail psoriasis and compared these to psoriasis patients without nail involvement, as well as in non-psoriatic healthy controls. Methods Adult psoriasis patients with (Group I, n = 30) and without nail involvement (Group-II, n = 30) were sequentially recruited. In addition, non-psoriatic healthy controls (Group-III, n = 20) were recruited. The nail disease severity by NAPSI score was determined for patients in Group I. Cutaneous disease severity (by PASI score) and presence of psoriatic arthritis (through CASPAR criteria) were evaluated for patients in Groups I and II. Serum levels of TNF-α, IL-17, erythrocyte sedimentation rate (ESR), rheumatoid factor (RA factor), and anti-cyclic citrullinated peptide antibody (Anti-CCP) were evaluated for all three groups. Results The median age was significantly higher for Group I as compared to Group II patients (41 ± 12.6 years vs 30 ± 12.4 years, p = 0.017). Group I patients also had higher median PASI score than Group II patients, although the difference was not statistically significant (10 ± 11.41 vs 6.50 ± 5.46, p = 0.275). The mean serum IL-17 levels were significantly higher for Group-I (113.39 ± 251.30 pg/mL) than Group II (27.91 ± 18.22 pg/mL, p = 0.002) and Group III (25.67 ± 12.08 pg/mL, p = 0.005). A weak positive correlation was found between NAPSI and serum IL-17 levels (Spearman's Rho = 0.355) though not statistically significant (p = 0.054). Correlation between serum IL-17 and PASI was poor for Group-I patients (Spearman's Rho = 0.13, p = 0.944) and strongly negative for Group-II patients (Spearman's Rho = -0.368, statistically significant with p = 0.045). The mean serum levels of TNF-α were below the detection threshold of the assay kit, hence no meaningful comparison could be made. Limitations A small sample size and low sensitivity of TNF-α assay kit. Conclusion Our study showed that nail psoriasis could be independently associated with an elevation of IL-17. This can help choose appropriate drugs and estimate drug response in patients with nail psoriasis.

Integration of Computational Pipeline to Streamline Efficacious Drug Nomination and Biomarker Discovery in Glioblastoma.

Glioblastoma multiforme (GBM) is the deadliest, most heterogeneous, and most common brain cancer in adults. Not only is there an urgent need to identify efficacious therapeutics, but there is also a great need to pair these therapeutics with biomarkers that can help tailor treatment to the right patient populations. We built patient drug response models by integrating patient tumor transcriptome data with high-throughput cell line drug screening data as well as Bayesian networks to infer relationships between patient gene expression and drug response. Through these discovery pipelines, we identified agents of interest for GBM to be effective across five independent patient cohorts and in a mouse avatar model: among them are a number of MEK inhibitors (MEKis). We also predicted phosphoglycerate dehydrogenase enzyme (PHGDH) gene expression levels to be causally associated with MEKi efficacy, where knockdown of this gene increased tumor sensitivity to MEKi and overexpression led to MEKi resistance. Overall, our work demonstrated the power of integrating computational approaches. In doing so, we quickly nominated several drugs with varying known mechanisms of action that can efficaciously target GBM. By simultaneously identifying biomarkers with these drugs, we also provide tools to select the right patient populations for subsequent evaluation.

Aberrant functional connectivity associated with drug response in patients with newly diagnosed epilepsy.

To analyze the local functional activity and connectivity features of the brain associated with drug response inpatients newly diagnosed with epilepsy (NDE) who are naïve to anti-seizure medication (ASM). Recruited patients, underwent functional magnetic resonance imaging at baseline, and were assigned to the well-controlled (WC, n = 28) or uncontrolled (UC, n = 11) groups based on their response to ASM. Healthy participants were included in the control group (HC, n = 29). The amplitudes of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) were used to measure local functional activity, and voxel-wise degree centrality (DC) and seed-based functional connectivity (FC) were used to evaluate the connecting intensity of the brain areas. Compared to the HC and WC groups, the UC group had higher ALFF values in the left posterior central gyrus (PoCG.L) and left inferior temporal gyrus (ITG.L) and higher DC in the bilateral PoCG (Gaussian random field correction, voxel-level P < 0.001, and cluster-level P < 0.05). Both PoCG and ITG.L in the UC group showed stronger FC with multiple brain regions, mainly located in the occipital and temporal lobes, compared to the HC or WC group, while the WC group showed decreased or similar FC compared to the HC group. Excessive enhancement of brain functional activity or connecting intensity in ASM-naïve patients with NDE may be associated with a higher risk of poor drug response.