A5002133501- Prostate Cancer Treatment and Research
- Radiopharmaceutical Chemistry and Applications
- Bladder and Urothelial Cancer Treatments
- Peptidase Inhibition and Analysis
- Lung Cancer Research Studies
- Urinary and Genital Oncology Studies
- Neuroendocrine Tumor Research Advances
- Monoclonal and Polyclonal Antibodies Research
- Mass Spectrometry Techniques and Applications
- Neuroblastoma Research and Treatments
- Immunotherapy and Immune Responses
- Prostate Cancer Diagnosis and Treatment
- Cancer Research and Treatments
- Cancer-related gene regulation
- Advanced Breast Cancer Therapies
- Cancer Genomics and Diagnostics
- Medical Imaging Techniques and Applications
- Glycosylation and Glycoproteins Research
- Medical Imaging and Pathology Studies
- Eosinophilic Esophagitis
- Ubiquitin and proteasome pathways
- Inflammatory mediators and NSAID effects
- Ferroptosis and cancer prognosis
- Radiation Therapy and Dosimetry
- BRCA gene mutations in cancer
University of Minnesota
2023-2025
UCSF Helen Diller Family Comprehensive Cancer Center
2020-2024
University of California, San Francisco
2020-2024
Palmetto Hematology Oncology
2023
City College of San Francisco
2023
California State University, Chico
2018
Enfortumab vedotin (EV) is an antibody-drug conjugate (ADC) targeting NECTIN4 (encoded by the PVRL4/NECTIN4 gene) approved for treatment-refractory metastatic urothelial cancer. Factors that mediate sensitivity or resistance to EV are unknown. In this study, we sought (i) examine heterogeneity of gene expression across molecular subtypes bladder cancer and (ii) determine whether mediates resistance.Molecular subtyping data from seven muscle-invasive clinical cohorts (n = 1,915 total...
Radiopharmaceutical therapy is changing the standard of care in prostate cancer and other malignancies. We previously reported high CD46 expression developed an antibody-drug conjugate immunoPET agent based on YS5 antibody, which targets a tumor-selective epitope. Here, we present preparation, preclinical efficacy, toxicity evaluation [225Ac]DOTA-YS5, radioimmunotherapy antibody.
Abstract Effective treatments for de novo and treatment-emergent small-cell/neuroendocrine (t-SCNC) prostate cancer represent an unmet need this disease. Using metastatic biopsies from patients with advanced cancer, we demonstrate that delta-like ligand 3 (DLL3) is expressed in t-SCNC associated reduced survival. We develop a PET agent, [89Zr]-DFO-DLL3-scFv, detects DLL3 levels mouse SCNC models. In multiple patient-derived xenograft models, AMG 757 (tarlatamab), half-life–extended...
Abstract Genomic sequencing of thousands tumors has revealed many genes associated with specific types cancer. Similarly, large scale CRISPR functional genomics efforts have mapped required for cancer cell proliferation or survival in hundreds lines. Despite this, disease subtypes, such as metastatic prostate cancer, there are likely a number undiscovered tumor driver that may represent potential drug targets. To identify genetic dependencies, we performed genome-scale CRISPRi screens...
We recently identified CD46 as a novel therapeutic target in prostate cancer. In this study, we developed CD46-targeted PET radiopharmaceutical, [89Zr]DFO-YS5, and evaluated its performance for immunoPET imaging murine cancer models.[89Zr]DFO-YS5 was prepared vitro binding affinity measured. ImmunoPET conducted male athymic nu/nu mice bearing DU145 [AR-, CD46+, prostate-specific membrane antigen-negative (PSMA-)] or 22Rv1 (AR+, PSMA+) tumors, NOD/SCID gamma patient-derived adenocarcinoma...
Abstract Purpose: With the improvement in overall survival with 177Lu-PSMA 617, radioligand therapy (RLT) is now a viable option for patients metastatic castration-resistant prostate cancer (mCRPC). However, responses are variable, part due to low PSMA expression 30% of patients. Herein, we evaluated whether cell surface protein CUB domain-containing 1 (CDCP1) can be exploited treat mCRPC RLT, including PSMA-low subsets. Experimental Design: CDCP1 levels were using RNA sequencing from 119...
Abstract Neuroendocrine neoplasms (NENs) encompass a diverse set of malignancies with limited precision therapy options. Recently, therapies targeting DLL3 have shown clinical efficacy in aggressive NENs, including small cell lung cancers and neuroendocrine prostate cancers. Given the continued development expansion DLL3-targeted therapies, we sought to characterize expression identify its molecular correlates across non-neuroendocrine Here, interrogated paired DNA RNA-sequencing from 1,589...
<p>DLL3-high versus -low hazard ratios across cancer.</p>
<p>Demographics of NEN samples by anatomic site</p>
<p>Supplementary Figure S1: UMAP view of NEN samples across diverse anatomic sites. Samples were unbiasedly clustered based off the top 1,000 variably expressed genes and annotated using (A) DLL3 expression level (B) site origin.</p>
<div>Abstract<p>Neuroendocrine neoplasms (NEN) encompass a diverse set of malignancies with limited precision therapy options. Recently, therapies targeting DLL3 have shown clinical efficacy in aggressive NENs, including small cell lung cancers and neuroendocrine prostate cancers. Given the continued development expansion DLL3-targeted therapies, we sought to characterize expression identify its molecular correlates across non-neuroendocrine Here, interrogated paired DNA...
<p>Correlates of <i>DLL3</i> expression with immune repertoire, alternative targets, and non-neuroendocrine cancers. <b>A,</b> Radar plots displaying differences in infiltrates between <i>DLL3</i>-high -low NENs. <b>B,</b> Ridgeline comparing the density precision targets NENs site-matched ADCs. <b>C,</b> Violin plots, bar heatmap <i>DLL3</i>, percent <i>DLL3</i>-high, hazard ratio, respectively, across...
<p>Supplementary Figure S4: Genetic dependencies in neuroendocrine cancer cell lines. Scatterplot displaying gene depletion effects NEN lines represented DepMap. Data points represent the mean effect of each target. Highlighted genes potential (gene < -0.5).</p>
<p>Supplementary Figure S3: Immune repertoire of DLL3-high versus –low NENs across anatomic sites. Stacked radar plots comparing the imputed cell fractions immune cells between and -low samples in (A) lung NECs, (B) NETs, (C) prostate NENs, (D) bladder NENs. *q < 0.05, **q 0.01</p>
<p>Supplementary Figure S2: Correlations between expression of DLL3, ASCL1, and NEUROD1 across select NEN sites. Scatterplots displaying the DLL3 vs ASCL1 (top) (bottom) Expression is depicted as log(TPM + 0.001). Spearman correlations corresponding p-values are shown for each site.</p>
<p>Expression patterns of <i>DLL3</i> across NENs. <b>A,</b> Violin plots displaying expression in NENs and ADCs originating from the lung or prostate. <b>B,</b> by histologic grade. Bar above show proportion grade that was defined as <i>DLL3</i>-high. LNEC, large cell neuroendocrine carcinoma; SNEC, small carcinoma. <b>C,</b> Differences genetic alterations between <i>DLL3</i>-high -low NENs, well breakdown...
<p>DLL3-high versus -low hazard ratios across NEN anatomic sites</p>
<p>Supplementary Figure S4: Genetic dependencies in neuroendocrine cancer cell lines. Scatterplot displaying gene depletion effects NEN lines represented DepMap. Data points represent the mean effect of each target. Highlighted genes potential (gene < -0.5).</p>
<p>Supplementary Figure S1: UMAP view of NEN samples across diverse anatomic sites. Samples were unbiasedly clustered based off the top 1,000 variably expressed genes and annotated using (A) DLL3 expression level (B) site origin.</p>
<p>Supplementary Figure S3: Immune repertoire of DLL3-high versus –low NENs across anatomic sites. Stacked radar plots comparing the imputed cell fractions immune cells between and -low samples in (A) lung NECs, (B) NETs, (C) prostate NENs, (D) bladder NENs. *q < 0.05, **q 0.01</p>
<p>DLL3-high versus -low hazard ratios across NEN anatomic sites</p>
<p>Supplementary Figure S2: Correlations between expression of DLL3, ASCL1, and NEUROD1 across select NEN sites. Scatterplots displaying the DLL3 vs ASCL1 (top) (bottom) Expression is depicted as log(TPM + 0.001). Spearman correlations corresponding p-values are shown for each site.</p>
<p>DLL3-high versus -low hazard ratios across cancer.</p>
<p>Supplementary Figure S2: Correlations between expression of DLL3, ASCL1, and NEUROD1 across select NEN sites. Scatterplots displaying the DLL3 vs ASCL1 (top) (bottom) Expression is depicted as log(TPM + 0.001). Spearman correlations corresponding p-values are shown for each site.</p>