Publications by authors named "Kim A Do"
Purpose: To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts.
Experimental Design: Metabolomic profiling was performed on an initial set of sera from 101 serous and nonserous ovarian cancer cases and 134 individuals with benign pelvic masses (BPM). Using a deep learning model, a panel consisting of seven cancer-related metabolites [diacetylspermine, diacetylspermidine, N-(3-acetamidopropyl)pyrrolidin-2-one, N-acetylneuraminate, N-acetyl-mannosamine, N-acetyl-lactosamine, and hydroxyisobutyric acid] was developed for distinguishing early-stage ovarian cancer from BPM.
Article Synopsis
- - The study aims to find biomarkers that can predict how triple-negative breast cancer (TNBC) patients will respond to neoadjuvant chemotherapy (NACT), focusing on blood polyamine levels.
- - Researchers discovered that high levels of acetylated polyamines in pre-treatment plasma were linked to TNBC patients with a worse response to NACT, indicating a moderate to extensive tumor burden.
- - By using artificial intelligence, a deep learning model was created to identify a panel of metabolites, including polyamines, which can help predict which TNBC patients are less likely to benefit from NACT and may require alternative treatments.
Background: T cells expressing antigen-specific chimeric antigen receptors (CARs) improve outcomes for CD19-expressing B cell malignancies. We evaluated a human application of T cells that were genetically modified using the Sleeping Beauty (SB) transposon/transposase system to express a CD19-specific CAR.
Methods: T cells were genetically modified using DNA plasmids from the SB platform to stably express a second-generation CD19-specific CAR and selectively propagated ex vivo with activating and propagating cells (AaPCs) and cytokines.
Purpose: p27 localization and expression has prognostic and predictive value in cancer. Little is known regarding expression patterns of p27 in renal cell carcinoma (RCC) or how p27 participates in disease progression or response to therapy.
Experimental Design: RCC-derived cell lines, primary tumors, and normal renal epithelial cells were analyzed for p27 expression, phosphorylation (T157 of the NLS), and subcellular localization.
Motivation: Individual microarray studies searching for prognostic biomarkers often have few samples and low statistical power; however, publicly accessible data sets make it possible to combine data across studies.
Method: We present a novel approach for combining microarray data across institutions and platforms. We introduce a new algorithm, robust greedy feature selection (RGFS), to select predictive genes.
Background: This study compared the accuracy of transrectal ultrasound (TRUS) versus magnetic resonance imaging (MRI) in the detection of rectal wall involvement by prostate cancer in patients undergoing salvage total pelvic exenteration (TPE) or cystoprostatectomy.
Methods: We identified 16 patients who underwent TPE and 24 patients who underwent cystoprostatectomy for locally advanced prostate cancer as salvage procedures with palliative intent. Patients were examined by TRUS, MRI, or both within the month preceding surgery.