The tumor microenvironment (TME) creates a complex biochemical and physical barrier affecting the penetration of chemotherapeutic agents into the tumor. Nanotherapy, which allows targeted drug delivery, has generated considerable interest in recent times to overcome the limitations of conventional chemotherapeutics and target the TME. The therapeutic efficacy of nanoformulations is significantly influenced by the particle size. Paclitaxel (PTX) is one of the most effective chemotherapeutic drugs for solid tumors, but its major limitation is its low water solubility. Its organic solvent formulation (Taxol) is known to cause severe toxicity. Therefore, various PTX nanoformulations have been developed using carriers, such as albumin, liposomes, and polymeric micelles. Each carrier has specific characteristics that offer some advantages and also lead to some limitations. There is scarce literature on the comparative profiles of the various types of PTX nanoformulations. Polymeric micelles that are smaller than 100 nm have acquired considerable attention due to their unique structure and high-loading capacity. Currently, there is only one approved and marketed formulation of polymeric micellar PTX (Genexol-PM). Over the years since preclinical evaluation, 22 studies on Genexol-PM in various solid tumors have been published, making it the most widely studied polymeric micellar PTX, demonstrating its safety, efficacy, and higher maximum tolerated dose compared to the conventional formulations. However, many of these were phase 2 trials, and studies on the available liposomal PTX formulations are scarce. There is a need for more PTX nanoformulations with different carriers, and more phase 3 and phase 4 studies on the available PTX nanoformulations. Moreover, head-to-head studies comparing the outcomes of various PTX nanoformulations are necessary to help clinicians make an informed decision when choosing nano PTX for their patients.
BACKGROUND AND AIMS:Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) spans from simple steatosis to progressive forms like non-alcoholic steatohepatitis (NASH), fibrosis, and cirrhosis, making early diagnosis and grading crucial. This study aimed to develop and validate predictive models for diagnosing and assessing MASLD severity using routinely available biomarkers from both public and clinical datasets. APPROACH & RESULTS:We developed a novel MASLD Risk Score (MRS) using data from the CDC NHANES (2000-2020) and validated it in a clinically profiled Indian cohort. Unlike existing indices, the predictors were derived through data-driven feature selection from large dataset, ensuring statistical robustness. It integrates novel (Uric Acid, HOMA-IR) and established (liver enzymes, triglycerides, waist circumference, BMI) biomarkers to improve metabolic profiling and predictive accuracy. The MRS also uniquely enables grading of MASLD severity, addressing a key limitation of previous models. The MRS achieved AUROCs of 0.91 (public) and 0.85 (clinical) with accuracies of 94 % and 82 %, respectively. A Random Forest (RF) model built on the same features provided AUROCs of 0.87 (public) and 0.94 (clinical), with accuracies of 83 % and 82 %. MRS parameters were optimized using a diverse population, improving generalizability across demographics. Both models showed strong correlation with ultrasonography results and outperformed existing indices. CONCLUSIONS:The MRS offers a novel, interpretable, and cost-effective solution for MASLD screening. Its development from a large, demographically diverse population and incorporation of varied biomarkers supports generalizability. While results are promising, external validation in multi-center clinical settings is needed to confirm broad utility.
e14541 Background: EGFR is a commonly mutated gene in several cancer types, particularly lung cancer. The specific mutation can cause susceptibility or resistance to treatments such as tyrosine kinase inhibitors (TKIs), which is first-line treatment for non-small cell lung cancer (NSCLC) patients with sensitive EGFR mutations. Patients develop resistance post-treatment and some may thus continue TKI treatment. Skeletal metastasis (SM) significantly impacts the quality of life for patients, increasing risk of skeletal-related events (SREs) such as fracture and spinal cord compression. Bone metastases occur in a significant proportion of patientswith advanced NSCLC. EGFR-mutated NSCLC patients have a long post-metastasis bone disease survival, increasing the risk of developing SREs. We investigated, EGFR mutational types and their association with skeletal metastasis to determine its molecular significance as an early indicator. Methods: We retrospectively analyzed 112 lung cancer patients with diverse mutational and metastatic profiles. These patients were further categorized into different types of EGFR alterations with their corresponding metastatic regions at any time in their disease history. The association between EGFR mutational types with their mutational regions was analyzed. Patient metastatic history was obtained from PET scans and HPE reports were collated for NGS testing. NGS test was performed using OncoIndx CGP Assay. Results: Retrospectively we analyzed 112 patients, 6 patients had dual EGFR mutations. 14.3% (n = 16/112) of patients had EGFR deletion/insertion mutations and another 14.3% (n = 16/112) of patients were detected with EGFR missense mutations. A negligible 1.8% (n = 2/112) of patients were detected with EGFR amplification while 75% (n = 84/112) of cohort were identified with no EGFR mutations. 50% (n = 8/16), 75% (12/16) and 35.7% (n = 30/84) were detected with metastasis in cohorts with EGFR deletion/insertion mutations, missense mutations and no EGFR mutational cohorts respectively. Interestingly, 66.7% (n = 8/12) of patients in the EGFR missense mutational cohort showed SM while only 37.5% (n = 3/8) of patients in the EGFR deletion/insertion mutational cohort showed SM. Conversely, 43.3% (n = 13/84) of patients in the cohort without EGFR mutations showed skeletal mutations. Highest cooccurrence of SM was observed in cohort with EGFR missense mutations. The cohort with EGFR deletion/insertion mutations and no EGFR mutations almost had a similar % of skeletal metastasis 37.5% and 43.3% respectively. Conclusions: We conclude that patients with EGFR missense mutations could be more vulnerable to skeletal metastasis and could be early indicators of treating it. With painful consequences, compromised quality of life, and high mortality rates faced by patients with skeletal metastasis, this study could be a new avenue to look for molecular identifiers for specific metastatic regions.
