Regulatory agencies have progressively emphasized the importance of assessing broader aspects of patient well-being to better define therapeutic gain. As a result, clinical outcome assessments (COAs) are increasingly used to evaluate the impact, both positive and negative, of cancer treatments and in some instances have played a major factor in the regulatory approval of drugs. Challenges remain, however, in the routine incorporation of these measures in cancer clinical trials, particularly in brain tumor studies. Factors unique to brain tumor patients such as cognitive decline and language dysfunction may hamper their successful implementation. Study designs often relegated these outcome measures to exploratory endpoints, further compromising data completion. New strategies are needed to maximize the complementary information that COAs could add to clinical trials alongside more traditional measures such as progression-free and overall survival. The routine incorporation of COAs as either primary or secondary objectives with attention to minimizing missing data should define a novel clinical trial design. We provide a review of the approaches, challenges, and opportunities for incorporating COAs into brain tumor clinical research, providing a perspective for integrating these measures into clinical trials.
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http://dx.doi.org/10.1093/nop/npy032 | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
Department of Signaling and Gene Expression, La Jolla Institute for Allergy and Immunology, La Jolla, CA 92037.
is one of the three most frequently mutated genes in age-related clonal hematopoiesis (CH), alongside and (. CH can progress to myeloid malignancies including chronic monomyelocytic leukemia (CMML) and is also strongly associated with inflammatory cardiovascular disease and all-cause mortality in humans. DNMT3A and TET2 regulate DNA methylation and demethylation pathways, respectively, and loss-of-function mutations in these genes reduce DNA methylation in heterochromatin, allowing derepression of silenced elements in heterochromatin.
View Article and Find Full Text PDFPLoS One
January 2025
Departments of Global Pediatric Medicine and Oncology, St. Jude Children's Research Hospital, Memphis, TN, United States of America.
Background: The SEER Registry contains U.S. cancer statistics.
View Article and Find Full Text PDFCell Rep
January 2025
The Brain Tumor Translational Laboratory, Department of Cell Biology and Physiology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA; University of New Mexico Comprehensive Cancer Center, Albuquerque, NM 87131, USA. Electronic address:
The sub-ventricular zone (SVZ) is the most well-characterized neurogenic area in the mammalian brain. We previously showed that in 65% of patients with glioblastoma (GBM), the SVZ is a reservoir of cancer stem-like cells that contribute to treatment resistance and the emergence of recurrence. Here, we build a single-nucleus RNA-sequencing-based microenvironment landscape of the tumor mass and the SVZ of 15 patients and two histologically normal SVZ samples as controls.
View Article and Find Full Text PDFActa Neurochir (Wien)
January 2025
Department of Neurosurgery, University Hospital Eppendorf, Hamburg, Germany.
In recent years, it has been increasingly recognized that tumor growth relies not only on support from the surrounding microenvironment but also on the tumors capacity to adapt to - and actively manipulate - its niche. While targeting angiogenesis and modulating the local immune environment have been explored as therapeutic approaches, these strategies have yet to yield effective treatments for brain tumors and remain under refinement. More recently, the nervous system itself has been explored as a critical environmental support for cancer, with extensive neuro-tumoral interactions observed both intracranially and in extracranial sites containing neural components.
View Article and Find Full Text PDFNeurosurg Rev
January 2025
Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China.
Glioma is characterized by high heterogeneity and poor prognosis. Attempts have been made to understand its diversity in both genetic expressions and radiomic characteristics, while few integrated the two omics in predicting survival of glioma. This study was intended to investigate the connection between glioma imaging and genome, and examine its predictive value in glioma mortality risk and tumor immune microenvironment (TIME).
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