Personalized Therapy Research Articles

Personalized therapy in oncology: melanoma as a paradigm for molecular-targeted treatment approaches.

In recent decades, the field of systemic cancer treatment has seen remarkable changes due to advancements in the understanding of cancer's biology, immunology, and genetic makeup. As a result, individuals with late-stage cancers are now achieving survival rates that were previously unattainable. The goal of personalized cancer therapy is to enhance clinical outcomes by customizing drug treatments to suit the unique genetic and/or epigenetic profiles of each patient's tumor. This approach aims to reduce the side effects commonly associated with ineffective treatments. Advances in genetic sequencing and molecular cytogenetics have been instrumental in identifying cancer-driving mutations and epigenetic irregularities, leading to the development of specific molecular therapies. This review article highlights the progress and success of targeted molecular therapies in treating malignant melanoma, illustrating the concept of personalized cancer treatment.

Enhancing chemotherapeutic efficacy: Niosome-encapsulated Dox-Cis with MUC-1 aptamer.

Cancer remains a formidable global health challenge, currently affecting nearly 20 million individuals worldwide. Due to the absence of universally effective treatments, ongoing research explores diverse strategies to combat this disease. Recent efforts have concentrated on developing combined drug regimens and targeted therapeutic approaches. This study aimed to investigate the anticancer efficacy of a conjugated drug system, consisting of doxorubicin and cisplatin (Dox-Cis), encapsulated within niosomes and modified with MUC-1 aptamers to enhance biocompatibility and target specific cancer cells. The chemical structure of the Dox-Cis conjugate was characterized using Fourier Transform Infrared Spectroscopy (FTIR) and Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry (LC-Q-TOF/MS). The zeta potential and morphological parameters of the niosomal vesicles were determined through Dynamic Light Scattering (DLS) and Transmission Electron Microscopy (TEM). In vitro assessments of cell viability and apoptosis were conducted on MUC-1 positive HeLa cells and MUC-1 negative U87 cells. The findings confirmed the successful conjugation of Dox and Cis within the niosomes. The Nio/Dox-Cis/MUC-1 formulation demonstrated enhanced efficacy compared to the individual drugs and their unencapsulated combination in both cell lines. Notably, the Nio/Dox-Cis/MUC-1 formulation exhibited greater effectiveness on HeLa cells (38.503 ± 1.407) than on U87 cells (46.653 ± 1.297). The study underscores the potential of the Dox-Cis conjugate as a promising strategy for cancer treatment, particularly through platforms that facilitate targeted drug delivery to cancer cells. This targeted approach could lead to more effective and personalized cancer therapies.

Identification of pyroptosis subtypes and prognosis model of hepatocellular carcinoma based on pyroptosis-related genes.

Hepatocellular carcinoma (HCC) is a common malignant tumor with poor prognosis. Pyroptosis, a type of programmed cell death, regulates tumor cell development. However, the role of pyroptosis-related genes (PRGs) in HCC and their association with prognosis are unclear. We conducted bioinformatics analysis to identify PRGs in The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) patients. Consensus clustering classified patients into different subtypes. We used LASSO regression to established a pyroptosis subtype-related score (PSRS) related to prognosis. OncoPredict identified potential pharmaceuticals based on PSRS. We found 20 HCC-related PRGs in 335 TCGA-LIHC patients. Consensus clustering classified patients into two subtypes. Subtype I had better overall survival and higher response to anti-PD1 treatment. The prognostic model involving 20 genes predicted poorer prognosis for high-PSRS group. The model was validated in two external cohorts. OncoPredict identified 65 potential pharmaceuticals based on PSRS. Our investigation revealed a correlation between pyroptosis and HCC. We established PSRS as independent risk factors for predicting prognosis. The study paves the way for using PRGs as prognostic biomarkers and exploring personalized therapy for HCC.

The Real-World Efficacy of Fixed Triple Inhalation Therapy in the Treatment of Moderate COPD Patients (RATIONALE Study).

COPD affects more than 300 million people worldwide, requiring inhalation treatment. Novel triple formulations of ICS, LABAs and LAMAs are becoming the mainstay of treatment, however there is still a lack of clinical evidence for personalized therapy. RATIONALE was a non-interventional, prospective, 52 week study, assessing the effectiveness of beclometasone/formoterol/glycopyrronium-bromide (BDP/FF/G), in symptomatic COPD patients, with moderate airflow obstruction. The study included 4 visits, where data on demographic parameters, exacerbations, symptoms, quality of life (based on the EQ-5D-3L questionnaire) and lung function were collected. Data on adherence to treatment, based on prescriptions filled was collected from the database of the National Health Insurance Fund, with the patients' consent. The primary objective was the change of adherence to treatment during the study, compared to baseline. Altogether 613 patients had been enrolled. Their average age was 64.56 years and 50.5% were female. The average CAT score was 20.86, and most patients had suffered minimum one exacerbation (82.2%). Average FEV1 was 59.6%. Most patients had some limitation in one or more dimensions of EQ-5D-3L, with an average visual analogue scale score (VAS) of 60.31. After 12 months of treatment, adherence improved significantly - proportion of patients in the highest adherence group increased from 29.8% to 69.7% (p<0.001). The average CAT score improved by 7.02 points (95% CI 5.82-8.21, p<0.001). There was a significant improvement in all dimensions of EQ-5D-3L, with an average increase of 17.91 (95% CI 16.51-19.31, p< 0.001) points in the VAS score. Exacerbation frequency also decreased significantly. Although limitations of observational studies are present, we observed that early introduction of fixed triple combination results in a marked improvement in adherence to treatment, symptom scores, exacerbation frequency and quality of life. The optimal choice of treatment is crucial for reaching the highest possible adherence.

Pembrolizumab in combination with trastuzumab for treatment of HER2-positive advanced gastric or gastro-esophageal junction cancer.

Gastric cancer remains a challenging malignancy with a high global mortality rate. Recent advances in targeted therapy and immunotherapy have shown promise in improving patient outcomes. This paper reviews the impact of incorporating targeted agents such as trastuzumab and immunotherapeutic agents like pembrolizumab into standard chemotherapy regimens for gastric cancer treatment. A comprehensive analysis was conducted on pivotal clinical trials, including KEYNOTE-590, KEYNOTE-811, and ToGA, focusing on their methodologies, patient populations, treatment regimens, and outcome measures. The review also explored emerging research avenues in precision medicine, particularly genomic sequencing and biomarker identification. To assess the efficacy and survival benefits of adding trastuzumab and pembrolizumab to standard chemotherapy in the treatment of gastric cancer and to outline future directions in gastric cancer research. Including trastuzumab and pembrolizumab in treatment regimens for human epidermal growth factor receptor 2 (HER2)-positive and PD-L1-expressing gastric cancers significantly improved progression-free and overall survival rates compared to chemotherapy alone. These findings highlight the potential of personalized therapy in enhancing treatment outcomes. Furthermore, ongoing research into the gastric cancer microenvironment and the role of the microbiome suggests novel targets for future therapeutic interventions. The integration of targeted and immunotherapeutic agents with traditional chemotherapy represents a pivotal shift in gastric cancer treatment, moving towards more personalized and effective regimens.

Molecular Characterization and Xenotransplantation of Pancreatic Cancer Using Endoscopic Ultrasound-Guided Fine Needle Aspiration (EUS-FNA).

Pancreatic cancer has one of the worst prognoses among all malignancies and few available treatment options. Patient-derived xenografts can be used to develop personalized therapy for pancreatic cancer. Endoscopic ultrasound fine-needle aspiration (EUS-FNA) may provide a powerful alternative to surgery for obtaining sufficient tissue for the establishment of patient-derived xenografts. In this study, EUS-FNA samples were obtained for 30 patients referred to the Ottawa Hospital, Ottawa, Ontario, Canada. These samples were used for xenotransplantation in NOD-SCID mice and for genetic analyses. The gene expression of pancreatic-cancer-relevant genes in xenograft tumors was examined by immunohistochemistry. Targeted sequencing of both the patient-derived tumors and xenograft tumors was performed. The xenografts' susceptibility to oncolytic virus infection was studied by infecting xenograft-derived cells with VSV∆51-GFP. The xenograft take rate was found to be 75.9% for passage 1 and 100% for passage 2. Eighty percent of patient tumor samples were successfully sequenced to a high depth for 42 cancer genes. Xenograft histological characteristics and marker expression were maintained between passages. All tested xenograft samples were susceptible to oncoviral infection. We found that EUS-FNA is an accessible, minimally invasive technique that can be used to acquire adequate pancreatic cancer tissue for the generation of patient-derived xenografts and for genetic sequencing.

Nordic inflammatory bowel disease treatment strategy trial: protocol for the NORDTREAT randomised controlled biomarker-strategy trial

IntroductionThe absence of reliable prognostic markers poses a challenge to the management of inflammatory bowel disease (IBD). Patients with aggressive disease may not receive sufficient treatment with conventional ‘step-up’ therapy,...

Physical therapy of persons after acute cerebrovascular accident in a long-term rehabilitation period

Purpose: to study the dynamics of recovery of walking, balance and quality of life of persons after acute cerebrovascular accident in a long-term rehabilitation period. Material and methods: patients were randomly divided into a main group (MG), which included 35 patients (n=35), and a comparison group (CG), which included 38 patients (n=38). The groups received rehabilitation intervention in accordance with the concept of the International Classification of Functioning, Disability, and Health (ICF). A categorical profile was created for each person and SMART goals were set. A physical therapy (PT) program was developed for MG after acute cerebrovascular accident (ACVA) in the long-term rehabilitation period. Short- and long-term goals were set in the SMART format, which included the use of therapeutic exercises. Functional capabilities and quality of life were assessed before and after the rehabilitation intervention using the ten-meter walk test, the Tinetty balance and fall risk scale, the modified Renkin functional independence scale and quality of life. Results: the dynamics of the ten-meter walking test during the PT program among patients in the MG is reflected in a decrease in the test completion time, which amounted to 23,6 s, and in the CG – 7 s. By the time of the final examination, the range of the obtained values was limited to 8 and 15 s in the MG, and among the CG, the extreme values were found at the levels of 12 and 160 s. By the time of the final examination, the "balance" item on the Tinetty balance and risk of falls scale in the MG was 13,8 ± 1,69 points out of a possible 16 points; the Me (25%; 75%) indicators were 14 (13; 15) points. In the CG, the indicator was slightly lower and was 12,3 ± 2,61 points; the Me (25%; 75%) indicators were 13 (10; 15) points. The difference between the groups by the end of the study for this indicator was significant (p&lt;0.05). As for the increase, it was 4.7 points in the MG and 3.1 points in the CG. The average statistical results of the assessment of the “Risk of Falls” section in the MG were 9.2±1.59 points out of a possible 12; the Me (25%; 75%) indicators were 9 (8; 11) points. In the CG patients, the indicator was slightly lower and was 5,2±1,99 points; the Me (25%; 75%) indicators were 6 (4; 6.3) points. The difference between the groups by the end of the study for this indicator was significant. (р&lt;0,01). As for the increase, it was 5 points in MG and 1,4 points in CG. The intermediate results on the Renkin scale were 1,83±0,62 and 2,13±0,74 points in MG and CG with Me (25%; 75%) – 2 (2; 2) and 2 (2; 3), respectively. At this stage, there was no statistical difference between the groups (p&gt;0,05), but both groups showed a reliable improvement compared to the initial result (p&lt;0,01). During the final examination, the results in MG patients improved and were 1,11±0,62 points, where the Me (25%; 75%) indicators were found at the level of 1 (1; 2) point. Among the CG patients, the final result was worse (p&lt;0.01) and was found at the level of 1,55±0,72 points with Me (25%; 75%) 1 (1; 2) point. Conclusions: Analysis of the dynamics of walking, balance and quality of life indicators after acute cerebrovascular accident in a long-term rehabilitation period confirmed the advantages of the developed physical therapy program for individuals from the MG.

Genetic polymorphisms to identify patients with an optimal response to tildrakizumab in psoriasis patients from real-life clinical practice.

Detecting the association of genetic variants to the response of biological therapy represents an important advance in developing a personalized therapy. The aim of this work was to study the association of polymorphisms with an optimal response to tildrakizumab in patients with psoriasis in a real-life clinical practice. Ninety patients with plaque psoriasis recruited from-Spanish hospitals receiving tildrakizumab for at least 24 weeks were genotyped for 180 polymorphisms. Optimal response to tildrakizumab was evaluated by absolute PASI ≤1 at 6 and 12 months. Polymorphisms corrected for weight and disease duration with an FDR <0.15 were included in a multiple regression model. Sixty three percent of patients achieved an absolute PASI ≤1 at 6 months, while 71% did so after 12 months. Disease duration (>27 years) and weight (>76 kg) were associated with treatment response; after correcting by these factors, no association (FDR >0.15) was found for any polymorphism and response to tildrakizumab at 6 months. The analysis at 12 months identified the genotype GG for rs610604 (TNFAIP3), CT for rs9373839 (ATG5), and delCTGT/delCTGT for rs72167053 (PDE4D) as risk factors to not achieve an optimal response (PASI ≤1), while CT for rs708567 (IL17RC) was protective, independently of weight and disease duration (FDR <0.15). The final multivariable model at 12 months showed an AUC of 0.90 (95% CI 0.82 to -0.98). We identified a set of polymorphisms that could be helpful to identify psoriatic patients with an optimal response to tildrakizumab at 12 months in real-world practice conditions.

Diseases Caused by Faulty Gene Expression. There are Several Hereditary Diseases that may be Entirely Cured if Detected and Treated Early Enough

Many genes and environmental factors often work together to cause a disease. The identification of significant genetic factors is useful for both medical (by aiding drug development and personalised therapy) and scientific (by shedding light on mechanistic and evolutionary aspects of illness) purposes. Linkage analysis (which joins loci that have a propensity to be inherited together) and association studies are two of the many genetic methods that have shown correlations between illnesses and particular sections of the genome (mapping correlation between alleles at different loci). Several hundreds of genes are examined in these types of studies, much too numerous to be tested experimentally as potential disease genes. The use of computer methods to assess the possibility of individual genes within a certain chromosomal area being disease genes is thus quite useful. Many diseases' susceptibilities have been demonstrated to a fair degree. changes in the rate at which genes are expressed in various cell types. In instance, if a gene or gene cluster is more common in sick individuals than in healthy people, it's likely that the gene plays a role in illness. Microarray studies were the major method for detecting the differences in expression levels.

Histone acetylation risk model predicts prognosis and guides therapy selection in glioblastoma: implications for chemotherapy and anti-CTLA-4 immunotherapy

BackgroundGlioblastoma is characterized by high aggressiveness, frequent recurrence, and poor prognosis. Histone acetylation-associated genes have been implicated in its occurrence and development, yet their predictive ability in glioblastoma prognosis remains unclear.ResultsThis study constructs a histone acetylation risk model using Cox and LASSO regression analyses to evaluate glioblastoma prognosis. We assessed the model’s prognostic ability with univariate and multivariate Cox regression analyses. Additionally, immune infiltration was evaluated using ESTIMATE and TIMER algorithms, and the SubMAP algorithm was utilized to predict responses to CTLA4 inhibitor. Multiple drug databases were applied to assess drug sensitivity in high- and low-risk groups. Our results indicate that the histone acetylation risk model is independent and reliable in predicting prognosis.ConclusionsLow-risk patients showed higher immune activity and longer overall survival, suggesting anti-CTLA4 immunotherapy suitability, while high-risk patients might benefit more from chemotherapy. This model could guide personalized therapy selection for glioblastoma patients.

Evaluation of OCT biomarker changes in treatment-naive neovascular AMD using a deep semantic segmentation algorithm

ObjectivesTo determine real-life quantitative changes in OCT biomarkers in a large set of treatment naive patients in a real-life setting undergoing anti-VEGF therapy. For this purpose, we devised a novel deep learning based semantic segmentation algorithm providing the first benchmark results for automatic segmentation of 11 OCT features including biomarkers for neovascular age-related macular degeneration (nAMD).MethodsTraining of a Deep U-net based semantic segmentation ensemble algorithm for state-of-the-art semantic segmentation performance which was used to analyze OCT features prior to, after 3 and 12 months of anti-VEGF therapy.ResultsHigh F1 scores of almost 1.0 for neurosensory retina and subretinal fluid on a separate hold-out test set with unseen patients. The algorithm performed worse for subretinal hyperreflective material and fibrovascular PED, on par with drusenoid PED, and better in segmenting fibrosis. In the evaluation of treatment naive OCT scans, significant changes occurred for intraretinal fluid (mean: 0.03 µm3 to 0.01 µm3, p < 0.001), subretinal fluid (0.08 µm3 to 0.01 µm3, p < 0.001), subretinal hyperreflective material (0.02 µm3 to 0.01 µm3, p < 0.001), fibrovascular PED (0.12 µm3 to 0.09 µm3, p = 0.02) and central retinal thickness C0 (225.78 µm3 to 169.40 µm3). The amounts of intraretinal fluid, fibrovascular PED, and ERM were predictive of poor outcome.ConclusionsThe segmentation algorithm allows efficient volumetric analysis of OCT scans. Anti-VEGF provokes most potent changes in the first 3 months while a gradual loss of RPE hints at a progressing decline of visual acuity. Additional research is required to understand how these accurate OCT predictions can be leveraged for a personalized therapy regimen.

Assessment of cellular signaling pathways in cancer: Targeting aberrant kinases and phosphatases for personalized therapy

Assessment of cellular signaling pathways in cancer: Targeting aberrant kinases and phosphatases for personalized therapy

Cytotoxic potential of Curcuma caesia rhizome extract and derived gold nanoparticles in targeting breast cancer cell lines

Among all types of cancer, breast cancer is the most aggressive, as it is responsible for most of the cancer related death of women. Though several medical therapies are available, the scenario of curing such disease is not favorable. Therefore, there is an urgent need to find alternatives to deal with it. The knowledge of ethnopharmacy might give some better solution to mitigate such deadly diseases. Here, we are using the rhizome of Curcuma caesia Roxb. (Black turmeric), as well as gold nanoparticles (GNPs) synthesized with it to check their specific cytotoxic potentiality against breast cancer cell lines. In our study, ethanolic extract was used to evaluate the cytotoxic effect of the rhizome. GNPs were synthesized by using the same extract and characterized by UV–Vis spectroscopy (UV–Vis), Transmission electron microscopy (TEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and Thermo gravimetric analysis (TGA). The TEM, XRD, FTIR and TGA results revealed the successful synthesis and capping of GNPs. The UV–Vis Spectrum showed a sharp and narrow absorption peak at 550 nm and HRTEM confirmed both the stability and successful synthesis of the nanoparticles. The MTT assay of the crude extract revealed strong cytotoxicity against breast cancer cell lines viz. MCF-7 (ER+) and MDA MB-231 (Triple Negative Breast Cancer, TNBC) by showing IC50 values as 15.70 ± 0.029 and 21.57 ± 0.031 μg/mL respectively. For extract mediated GNPs, the IC50 values were found to be 6.44 ± 0.045 and 5.87 ± 0.031μg/mL respectively in both breast cancer cell lines. As the IC50 value for GNPs was found to be much lower than that of crude extract, it indicates a higher efficiency of the GNP. However, both the rhizome extract and its mediated GNPs showed more toxicity towards MDA MB-231 (TNBC) cell lines. It was also observed that the GNPs showed more toxicity towards TNBC cell lines compared to the rhizome extract. No toxicity was found in case of other cell lines such as L 929 and HeLa for both crude extract as well as for GNPs. These observations suggests that both the crude rhizome extract and its derived GNPs exhibit selective cytotoxic potential against breast cancer cell lines, which might be exploited for target specific treatment. Moreover, with an understanding of the mechanism behind the GNPs therapeutic efficiency, it can be developed as a personalized therapy to treat such type of cancers.

Discovery and validation of a 10-gene predictive signature for response to adjuvant chemotherapy in stage II and III colon cancer

Identifying patients with stage II and III colon cancer who will benefit from 5-fluorouracil (5-FU)-based adjuvant chemotherapy is crucial for the advancement of personalized cancer therapy. We employ a semi-supervised machine learning approach to analyze a large dataset with 933 stage II and III colon cancer samples. Our analysis leverages gene regulatory networks to discover an 18-gene prognostic signature and to explore a 10-gene signature that potentially predicts chemotherapy benefits. The 10-gene signature demonstrates strong prognostic power and shows promising potential to predict chemotherapy benefits. We establish a robust clinical assay on the NanoString nCounter platform, validated in a retrospective formalin-fixed paraffin-embedded (FFPE) cohort, which represents an important step toward clinical application. Our study lays the groundwork for improving adjuvant chemotherapy and potentially expanding into immunotherapy decision-making in colon cancer. Future prospective studies are needed to validate and establish the clinical utility of the 10-gene signature in clinical settings.

TP53 mutations in urothelial carcinoma: not all one and the same†.

Systemic therapy options for urothelial carcinoma have expanded in recent years, with both immunotherapy and cytotoxic chemotherapy being widely available. However, we lack biomarkers to select which drug is likely to work best in individual patients. A new article in this journal by Jin, Xu, Su, et al reports that disruptive versus non-disruptive TP53 mutations may guide these personalised therapy choices. Intriguingly, patients with disruptive TP53 tumour mutations had poor overall survival versus those with non-disruptive TP53 mutations or wild type TP53 but responded particularly well to immunotherapy. Of relevance, an increased tumour mutational burden and increased effector CD8+ T-cell infiltration was seen in tumours with disruptive mutations. The impact of different TP53 mutations on prognosis and therapy choices appears to be tumour- and therapy-type specific, with no clear consensus on overall tumour phenotype according to type of mutation. Nonetheless, profiling of specific types of TP53 mutation is increasingly clinically feasible with targeted sequencing or immunohistochemistry. There is an urgent need for additional studies in urothelial cancer clarifying how the type of TP53 mutation present within a tumour can best be used as a predictive biomarker. Further important remaining questions include the impact of TP53 mutations on other clinically important aspects of the tumour microenvironment, including cancer-associated fibroblasts. Furthermore, the impact of gain-of-function mutations in TP53 and other related genes signalling upstream or downstream of TP53 is of wide interest. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Advancing bladder cancer management: development of a prognostic model and personalized therapy.

Bladder cancer (BLCA) was recognized as a significant public health challenge due to its high incidence and mortality rates. The influence of molecular subtypes on treatment outcomes was well-acknowledged, necessitating further exploration of their characterization and application. This study was aimed at enhancing the understanding of BLCA by mapping its molecular heterogeneity and developing a robust prognostic model using single-cell and bulk RNA sequencing data. Additionally, immunological characteristics and personalized treatment strategies were investigated through the risk score. Single-cell RNA sequencing (scRNA-seq) data from GSE135337 and bulk RNA-seq data from several sources, including GSE13507, GSE31684, GSE32894, GSE69795, and TCGA-BLCA, were utilized. Molecular subtypes, particularly the basal-squamous (Ba/Sq) subtype associated with poor prognosis, were identified. A prognostic model was constructed using LASSO and Cox regression analyses focused on genes linked with the Ba/Sq subtype. this model was validated across internal and external datasets to ensure predictive accuracy. High- and low-risk groups based on the risk score derived from TCGA-BLCA data were analyzed to examine their immune-related molecular profiles and treatment responses. Six molecular subtypes were identified, with the Ba/Sq subtype being consistently associated with poor prognosis. The prognostic model, based on basal-squamous subtype-related genes (BSSRGs), was shown to have strong predictive performance across diverse clinical settings with AUC values at 1, 3, and 5 years indicating robust predictability in training, testing, and entire datasets. Analysis of the different risk groups revealed distinct immune infiltration and microenvironments. Generally higher tumor mutation burden (TMB) scores and lower tumor immune dysfunction and exclusion (TIDE) scores were exhibited by the low-risk group, suggesting varied potentials for systemic drug response between the groups. Finally, significant differences in potential systemic drug response rates were also observed between risk groups. The study introduced and validated a new prognostic model for BLCA based on BSSRGs, which was proven effective in prognosis prediction. The potential for personalized therapy, optimized by patient stratification and immune profiling, was highlighted by our risk score, aiming to improve treatment efficacy. This approach was promised to offer significant advancements in managing BLCA, tailoring treatments based on detailed molecular and immunological insights.

Challenges for emergency departments: Anti-amyloid therapy and amyloid-related imaging abnormalities in persons with dementia.

Challenges for emergency departments: Anti-amyloid therapy and amyloid-related imaging abnormalities in persons with dementia.

Supramolecular Modulator Assisted Cryo-Engineered Porous Cu-DNA Nano-Vehicles for Versatile Theranostic Agent Delivery.

DNA nanotechnology combines structural design with therapeutic functions via programmable DNA motifs, but faces challenges in drug loading capacity. Herein a pore-engineering strategy is reported to develop a highly porous, universal DNA nano-vehicle through coordination self-assembly, cryo-engineering, and supramolecular chemistry, adapting to diverse cargo loading with desired theranostic agents. Thus, the complex synthesis and compatibility challenges typically associated with switching between different drug carriers are avoided. To this end, Cu2+ and nucleic acid therapeutic G3139 self-assemble into a prefabricated solid nanostructure, which subsequently undergoes ultrafast freezing and sublimation to introduce porosity, forming highly porous Cu-G3139 nanoparticles (CG NPs). The porous CG NPs efficiently accommodate diverse therapeutic molecules, from chemotherapeutics to non-chemotherapeutic agents, facilitated by positively-charged cyclodextrin. As a proof-of-concept, the photosensitizer indocyanine green (ICG) is loaded and coated with tannic acid (TA) to form CICG@TA, enabling remarkable photothermal and fluorescence imaging-guided synergistic tumor ablation. This work represents the first demonstration of sublimation-induced pore formation in metal-DNA hybrid nanoparticles without chemical etching, offering a scalable "plug-and-play" platform for personalized cancer therapy without redesign. This versatile pore-engineering strategy, merging supramolecular chemistry with cryo-engineered porosity, opens up new avenues for efficient, customized multidrug delivery for diverse tumor theranostic applications.

Cystic Fibrosis: Understanding Cystic Fibrosis Transmembrane Regulator Mutation Classification and Modulator Therapies.

A common life-threatening hereditary disease, Cystic Fibrosis (CF), affects primarily Caucasian infants. High sweat-salt levels are observed as a result of a single autosomal mutation in chromosome 7 that affects the critical function of the cystic fibrosis transmembrane regulator (CFTR). For establishing tailored treatment strategies, it is important to understand the broad range of CFTR mutations and their impacts on disease pathophysiology. This study thoroughly investigates the six main classes of classification of CFTR mutations based on their functional effects. Each class is distinguished by distinct molecular flaws, such as poor protein synthesis, misfolding, gating defects, conduction defects, and decreased CFTR expression at the apical membrane. Furthermore, this paper focuses on the emerging field of CFTR modulators, which intend to restore CFTR function or mitigate its consequences. These modulators, which are characterized by the mode of action and targeted mutation class, have the potential to provide personalized therapy regimens in CF patients. This review provides valuable insights into the genetic basis of CF pathology, and highlights the potential for precision medicine methods in CF therapy by thoroughly investigating CFTR mutation classification and related modulators.