0000000000020308
AUTHOR
Ella L. Kim
showing 7 related works from this author
Oncobox, gene expression-based second opinion system for predicting response to treatment in advanced solid tumors.
2019
e13143 Background: Anticancer Targeted Drugs (ATDs) specifically target one or a few types of tumor-related molecules in a cell. More than two hundred of ATDs were approved worldwide. They have different mechanisms of action and are effective for different cohorts of patients. However, many individual cases remain poorly responsive and it is of great importance to identify predictive markers of ATD efficacy. Our aim was to develop a platform enabling smart selection of the most efficient ATD therapies. Methods: We generated a second-opinion platform for clinical oncologists termed Oncobox. It is based on the analysis of gene expression profile of a cancer sample in comparison with the corr…
Diversity of Clinically Relevant Outcomes Resulting from Hypofractionated Radiation in Human Glioma Stem Cells Mirrors Distinct Patterns of Transcrip…
2020
Hypofractionated radiotherapy is the mainstay of the current treatment for glioblastoma. However, the efficacy of radiotherapy is hindered by the high degree of radioresistance associated with glioma stem cells comprising a heterogeneous compartment of cell lineages differing in their phenotypic characteristics, molecular signatures, and biological responses to external signals. Reconstruction of radiation responses in glioma stem cells is necessary for understanding the biological and molecular determinants of glioblastoma radioresistance. To date, there is a paucity of information on the longitudinal outcomes of hypofractionated radiation in glioma stem cells. This study addresses long-te…
CD133 Expression Is Not Synonymous to Immunoreactivity for AC133 and Fluctuates throughout the Cell Cycle in Glioma Stem-Like Cells.
2015
A transmembrane protein CD133 has been implicated as a marker of stem-like glioma cells and predictor for therapeutic response in malignant brain tumours. CD133 expression is commonly evaluated by using antibodies specific for the AC133 epitope located in one of the extracellular domains of membrane-bound CD133. There is conflicting evidence regarding the significance of the AC133 epitope as a marker for identifying stem-like glioma cells and predicting the degree of malignancy in glioma cells. The reasons for discrepant results between different studies addressing the role of CD133/AC133 in gliomas are unclear. A possible source for controversies about CD133/AC133 is the widespread assumpt…
Clinical use of RNA sequencing and oncobox analytics to predict personalized targeted therapeutic efficacy.
2020
e13676 Background: Analysis of mutation profiles in cancer patients does not provide clinical benefits in 80-90% of cases in the US (Marquart et al., 2018). Gene expression analysis potentially complements standard detection of clinically relevant mutations. Methods: 239 adult late-stage cancer patients. RNA gene expression sequencing completed on solid tumor samples using FFPE blocks. Patient mRNA profiles were analyzed using Oncobox bioinformatics, prioritizing target drugs according to their personalized predicted efficacy. Summary reports were provided to oncologists and resulting treatment selection and outcomes were assessed. Results: As of February 2020, feedback was received from p…
Intratumoral Heterogeneity, Its Contribution to Therapy Resistance and Methodological Caveats to Assessment
2014
Cancer is one of the most urgent health issues of today. According to WHO, the number of cancer cases is expected to increase by 75% in the next two decades (1). Despite some remarkable achievements in the fields of cancer prevention and early detection, the goal of developing effective anti-cancer therapies still remains unmet. Tumor recurrence due to treatment resistance is the most common cause of death from cancer. Delineating cellular and molecular mechanisms underlying tumor recurrence is of prime importance for the ability to improve the efficacy of existing therapies and develop new strategies to cancer treatment.
RNA-sequencing and bioinformatic analysis to pre-assess sensitivity to targeted therapeutics in recurrent glioblastoma.
2019
e13533 Background: This study developed molecular guided tools for individualized selection of chemotherapeutics for recurrent glioblastoma (rGB). A consortium involving clinical neurooncologists, molecular biologists and bioinformaticians identified gene expression patterns in rGB and quantitatively analyzed pathways involved in response to FDA approved oncodrugs. Methods: From2016 to 2018 biopsies from GB were collected using a multisampling approach. Biopsy material was used to isolate glioma stem-like cells and examined by RNA-sequencing. RNA-seq results were subjected to differential expression (DE) analysis and Oncobox analysis – a bioinformatic tool for quantitative pathway activati…
Intratumoral Heterogeneity and Longitudinal Changes in Gene Expression Predict Differential Drug Sensitivity in Newly Diagnosed and Recurrent Gliobla…
2020
Background: Inevitable recurrence after radiochemotherapy is the major problem in the treatment of glioblastoma, the most prevalent type of adult brain malignancy. Glioblastomas are notorious for a high degree of intratumor heterogeneity manifest through a diversity of cell types and molecular patterns. The current paradigm of understanding glioblastoma recurrence is that cytotoxic therapy fails to target effectively glioma stem cells. Recent advances indicate that therapy-driven molecular evolution is a fundamental trait associated with glioblastoma recurrence. There is a growing body of evidence indicating that intratumor heterogeneity, longitudinal changes in molecular biomarkers and spe…