Wen Foo

Positions:

Associate Professor of Pathology

Pathology
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

M.D. 2008

Duke University School of Medicine

Anatomic and Clinical Pathology, Pathology

Duke University School of Medicine

Cytopathology Fellowship, Pathology

Harvard Medical School

Grants:

Publications:

Characterization of a castrate-resistant prostate cancer xenograft derived from a patient of West African ancestry.

BACKGROUND: Prostate cancer is a clinically and molecularly heterogeneous disease, with highest incidence and mortality among men of African ancestry. To date, prostate cancer patient-derived xenograft (PCPDX) models to study this disease have been difficult to establish because of limited specimen availability and poor uptake rates in immunodeficient mice. Ancestrally diverse PCPDXs are even more rare, and only six PCPDXs from self-identified African American patients from one institution were recently made available. METHODS: In the present study, we established a PCPDX from prostate cancer tissue from a patient of estimated 90% West African ancestry with metastatic castration resistant disease, and characterized this model's pathology, karyotype, hotspot mutations, copy number, gene fusions, gene expression, growth rate in normal and castrated mice, therapeutic response, and experimental metastasis. RESULTS: This PCPDX has a mutation in TP53 and loss of PTEN and RB1. We have documented a 100% take rate in mice after thawing the PCPDX tumor from frozen stock. The PCPDX is castrate- and docetaxel-resistant and cisplatin-sensitive, and has gene expression patterns associated with such drug responses. After tail vein injection, the PCPDX tumor cells can colonize the lungs of mice. CONCLUSION: This PCPDX, along with others that are established and characterized, will be useful pre-clinically for studying the heterogeneity of prostate cancer biology and testing new therapeutics in models expected to be reflective of the clinical setting.
Authors
Patierno, BM; Foo, W-C; Allen, T; Somarelli, JA; Ware, KE; Gupta, S; Wise, S; Wise, JP; Qin, X; Zhang, D; Xu, L; Li, Y; Chen, X; Inman, BA; McCall, SJ; Huang, J; Kittles, RA; Owzar, K; Gregory, S; Armstrong, AJ; George, DJ; Patierno, SR; Hsu, DS; Freedman, JA
MLA Citation
Patierno, Brendon M., et al. “Characterization of a castrate-resistant prostate cancer xenograft derived from a patient of West African ancestry.Prostate Cancer Prostatic Dis, 2021. Pubmed, doi:10.1038/s41391-021-00460-y.
URI
https://scholars.duke.edu/individual/pub1466481
PMID
34645983
Source
pubmed
Published In
Prostate Cancer Prostatic Dis
Published Date
DOI
10.1038/s41391-021-00460-y

Prostate Cancer Detection Using 3-D Shear Wave Elasticity Imaging.

Transrectal ultrasound (TRUS) B-mode imaging provides insufficient sensitivity and specificity for prostate cancer (PCa) targeting when used for biopsy guidance. Shear wave elasticity imaging (SWEI) is an elasticity imaging technique that has been commercially implemented and is sensitive and specific for PCa. We have developed a SWEI system capable of 3-D data acquisition using a dense acoustic radiation force (ARF) push approach that leads to enhanced shear wave signal-to-noise ratio compared with that of the commercially available SWEI systems and facilitates screening of the entire gland before biopsy. Additionally, we imaged and assessed 36 patients undergoing radical prostatectomy using 3-D SWEI and determined a shear wave speed threshold separating PCa from healthy prostate tissue with sensitivities and specificities akin to those for multiparametric magnetic resonance imaging fusion biopsy. The approach measured the mean shear wave speed in each prostate region to be 4.8 m/s (Young's modulus E = 69.1 kPa) in the peripheral zone, 5.3 m/s (E = 84.3 kPa) in the central gland and 6.0 m/s (E = 108.0 kPa) for PCa with statistically significant (p < 0.0001) differences among all regions. Three-dimensional SWEI receiver operating characteristic analyses identified a threshold of 5.6 m/s (E = 94.1 kPa) to separate PCa from healthy tissue with a sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the curve (AUC) of 81%, 82%, 69%, 89% and 0.84, respectively. Additionally, a shear wave speed ratio was assessed to normalize for tissue compression and patient variability, which yielded a threshold of 1.11 to separate PCa from healthy prostate tissue and was accompanied by a substantial increase in specificity, PPV and AUC, where the sensitivity, specificity, PPV, NPV and AUC were 75%, 90%, 79%, 88% and 0.90, respectively. This work illustrates the feasibility of using 3-D SWEI data to detect and localize PCa and demonstrates the benefits of normalizing for applied compression during data acquisition for use in biopsy targeting studies.
Authors
Morris, DC; Chan, DY; Palmeri, ML; Polascik, TJ; Foo, W-C; Nightingale, KR
MLA Citation
Morris, D. Cody, et al. “Prostate Cancer Detection Using 3-D Shear Wave Elasticity Imaging.Ultrasound Med Biol, vol. 47, no. 7, July 2021, pp. 1670–80. Pubmed, doi:10.1016/j.ultrasmedbio.2021.02.006.
URI
https://scholars.duke.edu/individual/pub1478493
PMID
33832823
Source
pubmed
Published In
Ultrasound Med Biol
Volume
47
Published Date
Start Page
1670
End Page
1680
DOI
10.1016/j.ultrasmedbio.2021.02.006

Clinicopathological features to distinguish malignant solitary fibrous tumors of the prostate from prostatic stromal tumors.

Mesenchymal tumors of the prostate are rare but encompass a wide differential diagnosis. In our study, we aimed to investigate the clinicopathological features that can be used to differentiate malignant solitary fibrous tumors (mSFTs) occurring in the prostate from prostatic stromal tumors. A total of 15 patients with mesenchymal tumors of the prostate were identified in Nanjing Drum Tower Hospital from 2009 to 2019, including 3 mSFTs, 9 stromal tumors of uncertain malignant potential (STUMPs), and 3 prostatic stromal sarcomas (PSSs). Immunohistochemical stains for signal transducer and activator of transcription 6 (STAT6), aldehyde dehydrogenase 1 (ALDH1), CD34, desmin, smooth muscle actin (SMA), progesterone receptor (PR), CD117, and cytokeratin (CK) were performed on representative sections from each tumor, and the clinical features, histology, and immunophenotype of these three groups were analyzed. There was no significant difference in mean patient age of patients diagnosed with mSFTs, STUMPs, and PSSs. mSFTs and PSSs showed significantly increased tumor size (p < 0.05), Ki-67 proliferation index (p < 0.0001), and mitotic activity (p < 0.05) when compared with STUMPs. mSFTs showed significantly higher expression of STAT6 compared with both PSSs and STUMPs (p < 0.0001, p < 0.0001). PR showed significantly more expression in STUMPs than in mSFTs or PSSs (p < 0.0001, p < 0.0001). Desmin and SMA showed significantly more expression in STUMPs than in mSFTs (p < 0.05). ALDH1, CD117, CK, and CD34 showed no significant difference in staining between mSFTs, STUMPs, and PSSs. Therefore, a limited panel of STAT6, PR, and Ki-67 may be useful in distinguishing between mSFTs, STUMPs, and PSSs.
Authors
Xu, Y; Li, Z; Shi, J; Fu, Y; Zhu, L; Fan, X; Foo, W-C
MLA Citation
Xu, Yuemei, et al. “Clinicopathological features to distinguish malignant solitary fibrous tumors of the prostate from prostatic stromal tumors.Virchows Arch, vol. 478, no. 4, Apr. 2021, pp. 619–26. Pubmed, doi:10.1007/s00428-020-02909-2.
URI
https://scholars.duke.edu/individual/pub1456763
PMID
32820389
Source
pubmed
Published In
Virchows Arch
Volume
478
Published Date
Start Page
619
End Page
626
DOI
10.1007/s00428-020-02909-2

Multiparametric Ultrasound for Targeting Prostate Cancer: Combining ARFI, SWEI, QUS and B-Mode.

Diagnosing prostate cancer through standard transrectal ultrasound (TRUS)-guided biopsy is challenging because of the sensitivity and specificity limitations of B-mode imaging. We used a linear support vector machine (SVM) to combine standard TRUS imaging data with acoustic radiation force impulse (ARFI) imaging data, shear wave elasticity imaging (SWEI) data and quantitative ultrasound (QUS) midband fit data to enhance lesion contrast into a synthesized multiparametric ultrasound volume. This SVM was trained and validated using a subset of 20 patients and tested on a second subset of 10 patients. Multiparametric US led to a statistically significant improvements in contrast, contrast-to-noise ratio (CNR) and generalized CNR (gCNR) when compared with standard TRUS B-mode and SWEI; in contrast and CNR when compared with MF; and in CNR when compared with ARFI. ARFI, MF and SWEI also outperformed TRUS B-mode in contrast, with MF outperforming B-mode in CNR and gCNR as well. ARFI, although only yielding statistically significant differences in contrast compared with TRUS B-mode, captured critical qualitative features for lesion identification. Multiparametric US enhanced lesion visibility metrics and is a promising technique for targeted TRUS-guided prostate biopsy in the future.
Authors
Morris, DC; Chan, DY; Lye, TH; Chen, H; Palmeri, ML; Polascik, TJ; Foo, W-C; Huang, J; Mamou, J; Nightingale, KR
MLA Citation
Morris, D. Cody, et al. “Multiparametric Ultrasound for Targeting Prostate Cancer: Combining ARFI, SWEI, QUS and B-Mode.Ultrasound Med Biol, vol. 46, no. 12, Dec. 2020, pp. 3426–39. Pubmed, doi:10.1016/j.ultrasmedbio.2020.08.022.
URI
https://scholars.duke.edu/individual/pub1461735
PMID
32988673
Source
pubmed
Published In
Ultrasound Med Biol
Volume
46
Published Date
Start Page
3426
End Page
3439
DOI
10.1016/j.ultrasmedbio.2020.08.022

Multiparametric Ultrasound for the Targeting of Prostate Cancer using ARFI, SWEI, B-mode, and QUS

Prostate cancer diagnosis using standard transrectal ultrasound (TRUS) and systematic biopsy is challenging. To improve the performance of TRUS imaging, we combined it with acoustic radiation force impulse (ARFI) imaging and shear wave elasticity imaging (SWEI) to enhance lesion contrast into a multiparametric ultrasound (mpUS) synthesized image using a linear support vector machine (SVM). The SVM was trained on one subset of patients (N=15) and applied to a second subset (N=15) imaged with a different transducer. mpUS imaging identified 79% of clinically significant PCa in the second cohort with a PPV of 95%.
Authors
Morris, DC; Chan, DY; Chen, H; Palmeri, ML; Polascik, TJ; Foo, WC; Huang, J; Mamou, J; Nightingale, KR
MLA Citation
Morris, D. C., et al. “Multiparametric Ultrasound for the Targeting of Prostate Cancer using ARFI, SWEI, B-mode, and QUS.” Ieee International Ultrasonics Symposium, Ius, vol. 2019-October, 2019, pp. 880–83. Scopus, doi:10.1109/ULTSYM.2019.8926035.
URI
https://scholars.duke.edu/individual/pub1427968
Source
scopus
Published In
Ieee International Ultrasonics Symposium, Ius
Volume
2019-October
Published Date
Start Page
880
End Page
883
DOI
10.1109/ULTSYM.2019.8926035