A5000693249- Ferroptosis and cancer prognosis
- RNA modifications and cancer
- Radiomics and Machine Learning in Medical Imaging
- Lung Cancer Diagnosis and Treatment
- Cancer Immunotherapy and Biomarkers
- Lung Cancer Treatments and Mutations
- Global Cancer Incidence and Screening
- Colorectal Cancer Screening and Detection
- Cancer, Lipids, and Metabolism
- Bioinformatics and Genomic Networks
- Cancer Genomics and Diagnostics
- Single-cell and spatial transcriptomics
- Cancer Cells and Metastasis
- Economic and Financial Impacts of Cancer
- HER2/EGFR in Cancer Research
- Mast cells and histamine
- melanin and skin pigmentation
- Peptidase Inhibition and Analysis
- Retinal Development and Disorders
- interferon and immune responses
- Advanced X-ray and CT Imaging
- Immune Cell Function and Interaction
- Proteoglycans and glycosaminoglycans research
- Gastric Cancer Management and Outcomes
- Immunotherapy and Immune Responses
Vanderbilt University Medical Center
2021-2023
Pulmonary and Allergy Associates
2021
Rationale: Patients with indeterminate pulmonary nodules (IPNs) at risk of cancer undergo high rates invasive, costly, and morbid procedures. Objectives: To train externally validate a prediction model that combined clinical, blood, imaging biomarkers to improve the noninvasive management IPNs. Methods: In this prospectively collected, retrospective blinded evaluation study, probability was calculated for 456 patient using Mayo Clinic model, patients were categorized into low-,...
HER2 is over-expressed in approximately 25% to 30% of human metastatic breast cancers, primarily due gene amplification. There are currently two HER2-targeted therapies approved for clinical use, the monoclonal antibody trastuzumab and EGFR/HER2 dual tyrosine kinase inhibitor lapatinib. Although both agents show benefit a subset patients with cancer, many HER2-over-expressing tumors do not respond these agents. Furthermore, those who an initial response generally demonstrate disease...
Abstract A deep learning model (LCP CNN) for the stratification of indeterminate pulmonary nodules (IPNs) demonstrated better discrimination than commonly used clinical prediction models. However, LCP CNN score is based on a single timepoint that ignores longitudinal information when prior imaging studies are available. Clinically, IPNs often followed over time and temporal trends in nodule size or morphology inform management. In this study we investigated whether change scores was...
Lung adenocarcinoma (ADC) is a heterogeneous group of tumors associated with different survival rates, even when detected at an early stage. Here, we aim to investigate whether CyTOF identifies cellular and molecular predictors tumor behavior. We developed validated panel 34 antibodies in four ADC cell lines PBMC. tested our set 10 ADCs, classified into long- (LPS) (n = 4) short-predicted (SPS) 6) based on radiomics features. identified subpopulations epithelial cancer cells (ECC) their...
Lung cancer is the deadliest in United States and worldwide, lung adenocarcinoma (LUAD) most prevalent histologic subtype States. LUAD exhibits a wide range of aggressiveness risk recurrence, but biological underpinnings this behavior are poorly understood. Past studies have focused on characteristics tumor itself, ability immune response to contain growth represents an alternative or complementary hypothesis. Emerging technologies enable us investigate spatial distribution specific cell...
Abstract Background A goal of developmental genetics is to identify functional interactions that underlie phenotypes caused by mutations. We sought interactors Vsx2 , which when mutated, disrupts early retinal development. utilized the loss‐of‐function mouse, ocular retardation J ( orJ ), assess based on principles positive and negative epistasis as applied bulk transcriptome data. This was first tested in vivo with Mitf a target repression, then cultures retina treated inhibitors Retinoid‐X...
Lung adenocarcinoma (LUAD) is a heterogeneous group of tumors associated with different survival rates, even when detected at an early stage. Here, we aim to investigate the biological determinants LUAD indolence or aggressiveness using radiomics as surrogate behavior. We present set 92 patients data collected across methodologies. Patients were risk-stratified CT-based Score Indicative cancer Aggression (SILA) tool (0 = least aggressive, 1 most aggressive). grouped indolent (
Abstract Background: Diagnostic prediction models are useful guides when considering lesions suspicious for cancer, as they provide a quantitative estimate of the probability that lesion is malignant. However, decision to intervene ultimately rests on patient and physician preferences. The appropriate intervention in many clinical situations typically defined by clinically relevant, actionable subgroups based upon malignancy. “all-or-nothing” approach threshold-based decisions practice...
<div><p>Lung adenocarcinoma (LUAD) is a heterogeneous group of tumors associated with different survival rates, even when detected at an early stage. Here, we aim to investigate the biological determinants LUAD indolence or aggressiveness using radiomics as surrogate behavior. We present set 92 patients data collected across methodologies. Patients were risk-stratified CT-based Score Indicative Lung cancer Aggression (SILA) tool (0 = least aggressive, 1 most aggressive). grouped...
<div>Abstract<p>Lung adenocarcinoma (LUAD) is a heterogeneous group of tumors associated with different survival rates, even when detected at an early stage. Here, we aim to investigate the biological determinants LUAD indolence or aggressiveness using radiomics as surrogate behavior. We present set 92 patients data collected across methodologies. Patients were risk-stratified Computed Tomography–based Score Indicative Lung cancer Aggression (SILA) tool (0=least aggressive, 1=...
<p>Supplementary Figures S1-S21</p>
<p>Supplementary Figures S1-S21</p>
<p>Supplementary figures</p>
<p>Profiling of LUAD TME by single-cell RNA-seq analysis. <b>A,</b> Uniform Manifold Approximation and Projection (UMAP) representation colored cell type using all cells (left) density grouped risk group (right). <b>B,</b> UMAP gene expression top lineage markers for each main type. Reclustering analysis T (<b>C</b>), myeloid (<b>D</b>), B (<b>E</b>). cluster, followed some subset representative markers. On the far right, we...
<p>Profiling of LUAD TME by single-cell RNA-seq analysis. <b>A,</b> Uniform Manifold Approximation and Projection (UMAP) representation colored cell type using all cells (left) density grouped risk group (right). <b>B,</b> UMAP gene expression top lineage markers for each main type. Reclustering analysis T (<b>C</b>), myeloid (<b>D</b>), B (<b>E</b>). cluster, followed some subset representative markers. On the far right, we...
<p>Data integration reveals an association between radiomics features and tumor biology. <b>A,</b> Heat map showing the z-score per patient (columns) feature (rows) split by clusters. Top annotation shows some clinical characteristics bottom mutated genes. <b>B,</b> PCA of patients (top) (bottom) colored cluster. <b>C,</b> RFS (left) PFS from cluster 4 versus 1, 2, 3 1 (bottom).</p>
<p>Data integration reveals an association between radiomics features and tumor biology. <b>A,</b> Heat map showing the z-score per patient (columns) feature (rows) split by clusters. Top annotation shows some clinical characteristics bottom mutated genes. <b>B,</b> PCA of patients (top) (bottom) colored cluster. <b>C,</b> RFS (left) PFS from cluster 4 versus 1, 2, 3 1 (bottom).</p>
<p>CyTOF analysis of LUAD samples reveal subsets associated with HLA-DR protein expression. <b>A,</b> Uniform Manifold Approximation and Projection (UMAP) representation colored by cell type [epithelial cancer cells (blue), endothelial (red), fibroblasts/mesenchymal (green), CD8<sup>+</sup> T (orange), CD4<sup>+</sup> (pink), double-negative (yellow), myeloid (purple), other immune (gray)], density, patient ID, expression lineage markers (bottom)....
<p>CyTOF analysis of LUAD samples reveal subsets associated with HLA-DR protein expression. <b>A,</b> Uniform Manifold Approximation and Projection (UMAP) representation colored by cell type [epithelial cancer cells (blue), endothelial (red), fibroblasts/mesenchymal (green), CD8<sup>+</sup> T (orange), CD4<sup>+</sup> (pink), double-negative (yellow), myeloid (purple), other immune (gray)], density, patient ID, expression lineage markers (bottom)....