Project description:Dermatofibrosarcoma protuberans (DFSP) is a soft-tissue sarcoma characterized by a high risk of local infiltration. The identification of the COL1A1-PDGFB t(17;22) translocation activating the PDGF pathway led to the use of imatinib in unresectable DFSP, with a response rate of 36-80%. Pazopanib is a multitarget tyrosine kinase inhibitor approved for soft tissue sarcomas. We conducted a phase II study of patients with unresectable DFSP to evaluate the efficacy and safety of pazopanib. Patients received 800 mg pazopanib daily. The primary endpoint was the objective response rate defined as the reduction of the largest diameter of the tumor ≥30% at 6 months or at surgery assessed by physical examination. Twenty-three patients, including one pre-treated with imatinib, were enrolled. With a median follow-up of 6.2 months (interquartile range 5.6-7.8 months), 5 patients (22%, 95% CI: 7-22%) had a partial response to pazopanib. The best objective response rate was 30% (95% CI 13-53%) using RECIST. One patient with metastatic DFSP previously treated with imatinib died after 2.4 months. Nine (39%) patients discontinued the treatment due to adverse events. Pharmacodynamics analyses of tumor samples were conducted: the enrichment of EGF and the EGFR-associated gene panel was associated with resistance, suggesting that EGFR-targeted therapies could be a therapeutic option to explore in DFSP.

2020-05-19 | GSE150787 | GEO

Efficacy of continued cetuximab for unresectable metastatic colorectal cancer after disease progression during first-line cetuximab-based chemotherapy: a retrospective cohort study.

Project description: Not available

| S-EPMC4905480 | biostudies-literature

Mortality-associated Plasma Proteome Dynamics in a Prospective Multicenter Sepsis Cohort

Project description:Understanding the plasma proteome dynamics in sepsis patients is crucial for improving prognostic and therapeutic strategies, as sepsis remains a leading cause of mortality in intensive care units. In this study, 363 patients with newly diagnosed sepsis were enrolled and plasma was collected on the first and fourth day after diagnosis. Proteome analysis was performed using liquid chromatography–tandem mass spectrometry. The plasma proteome was analyzed via classical statistical analysis and machine learning to identify associations with 30-day survival. Out of 363 sepsis patients, 224 survived and 139 did not survive the 30-day period. Significant differences in the abundance of 87 proteins on day 1 and 95 proteins on day 4 were found between survivors and non-survivors. Additionally, between days 1 and 4, 63 proteins were differentially regulated between both groups. We found that protein regulations within the first days of sepsis were generally associated with a worse outcome. Statistical analysis revealed the underlying proteins to be foremost related to blood coagulation, immune response and complement activation. Complementarily, the machine learning classifier achieved an area under the receiver operating characteristic curve of 0.75 for predicting 30-day survival. The feature importance analysis highlighted additional proteins and substantiated the findings of univariate statistics. This study describes the temporal alterations of the plasma proteome and the underlying protein networks that are associated with survival. These findings enhance the understanding of sepsis pathophysiology and the identified proteins might serve as starting points for further investigations and guide the development of targeted therapeutic strategies.

2024-12-16 | PXD055932 | Pride

Real-World Data of Triplet Combination of Trastuzumab, Lapatinib, and Chemotherapy in HER2-Positive Metastatic Breast Cancer: A Multicenter Retrospective Study.

Project description: Not available

| S-EPMC7062863 | biostudies-literature