ORCID Profile
0000-0003-1043-6169
Current Organisations
Dublin City University
,
Taipei Municipal Wan-Fang Hospital
,
Taipei Medical University
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479519
Abstract: Densitometry analysis for Figure 6B
Publisher: JMIR Publications Inc.
Date: 29-04-2021
DOI: 10.2196/21394
Abstract: The COVID-19 outbreak has spread rapidly and hospitals are overwhelmed with COVID-19 patients. While analysis of nasal and throat swabs from patients is the main way to detect COVID-19, analyzing chest images could offer an alternative method to hospitals, where health care personnel and testing kits are scarce. Deep learning (DL), in particular, has shown impressive levels of performance when analyzing medical images, including those related to COVID-19 pneumonia. The goal of this study was to perform a systematic review with a meta-analysis of relevant studies to quantify the performance of DL algorithms in the automatic stratification of COVID-19 patients using chest images. A search strategy for use in PubMed, Scopus, Google Scholar, and Web of Science was developed, where we searched for articles published between January 1 and April 25, 2020. We used the key terms “COVID-19,” or “coronavirus,” or “SARS-CoV-2,” or “novel corona,” or “2019-ncov,” and “deep learning,” or “artificial intelligence,” or “automatic detection.” Two authors independently extracted data on study characteristics, methods, risk of bias, and outcomes. Any disagreement between them was resolved by consensus. A total of 16 studies were included in the meta-analysis, which included 5896 chest images from COVID-19 patients. The pooled sensitivity and specificity of the DL models in detecting COVID-19 were 0.95 (95% CI 0.94-0.95) and 0.96 (95% CI 0.96-0.97), respectively, with an area under the receiver operating characteristic curve of 0.98. The positive likelihood, negative likelihood, and diagnostic odds ratio were 19.02 (95% CI 12.83-28.19), 0.06 (95% CI 0.04-0.10), and 368.07 (95% CI 162.30-834.75), respectively. The pooled sensitivity and specificity for distinguishing other types of pneumonia from COVID-19 were 0.93 (95% CI 0.92-0.94) and 0.95 (95% CI 0.94-0.95), respectively. The performance of radiologists in detecting COVID-19 was lower than that of the DL models however, the performance of junior radiologists was improved when they used DL-based prediction tools. Our study findings show that DL models have immense potential in accurately stratifying COVID-19 patients and in correctly differentiating them from patients with other types of pneumonia and normal patients. Implementation of DL-based tools can assist radiologists in correctly and quickly detecting COVID-19 and, consequently, in combating the COVID-19 pandemic.
Publisher: IEEE
Date: 11-2015
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479537.V1
Abstract: Flow cytometry control scatter plots for trastuzumab-488 and pertuzumab-550
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479516.V1
Abstract: Densitometry analysis for Figure 6D/E
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.C.6530235
Abstract: AbstractPurpose: Antibody-dependent cell-mediated cytotoxicity (ADCC) is one mechanism of action of the monoclonal antibody (mAb) therapies trastuzumab and pertuzumab. Tyrosine kinase inhibitors (TKIs), like lapatinib, may have added therapeutic value in combination with mAbs through enhanced ADCC activity. Using clinical data, we examined the impact of lapatinib on HER2/EGFR expression levels and natural killer (NK) cell gene signatures. We investigated the ability of three TKIs (lapatinib, afatinib, and neratinib) to alter HER2/immune-related protein levels in preclinical models of HER2-positive (HER2 sup + /sup ) and HER2-low breast cancer, and the subsequent effects on trastuzumab ertuzumab-mediated ADCC. Experimental Design: Preclinical studies (proliferation assays, Western blotting, high content analysis, and flow cytometry) employed HER2 sup + /sup (SKBR3 and HCC1954) and HER2-low (MCF-7, T47D, CAMA-1, and CAL-51) breast cancer cell lines. NCT00524303 provided reverse phase protein array–determined protein levels of HER2 HER2/EGFR EGFR. RNA-based NK cell gene signatures (CIBERSORT/MCP-counter) post-neoadjuvant anti-HER2 therapy were assessed (NCT00769470/NCT01485926). ADCC assays utilized flow cytometry–based protocols. Results: Lapatinib significantly increased membrane HER2 levels, while afatinib and neratinib significantly decreased levels in all preclinical models. Single-agent lapatinib increased HER2 or EGFR levels in 10 of 11 (91%) tumor s les. NK cell signatures increased posttherapy ( i P /i = 0.03) and associated with trastuzumab response ( i P /i = 0.01). TKI treatment altered mAb-induced NK cell–mediated ADCC i in vitro /i , but it did not consistently correlate with HER2 expression in HER2 sup + /sup or HER2-low models. The ADCC response to trastuzumab and pertuzumab combined did not exceed either mAb alone. Conclusions: TKIs differentially alter tumor cell phenotype which can impact NK cell–mediated response to coadministered antibody therapies. mAb-induced ADCC response is relevant when rationalizing combinations for clinical investigation. /
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479510.V1
Abstract: Flow cytometry MFI and % positive cells data for fluorescently labelled trastuzumab and pertuzumab in SKBR3, HCC1954, T47D and MCF-7 treated with TKIs
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479540
Abstract: Rituximab ADCC negative control
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479522
Abstract: MFI comparison at T0 and T6 for T47D/MCF-7
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479522.V1
Abstract: MFI comparison at T0 and T6 for T47D/MCF-7
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.C.6530235.V1
Abstract: AbstractPurpose: Antibody-dependent cell-mediated cytotoxicity (ADCC) is one mechanism of action of the monoclonal antibody (mAb) therapies trastuzumab and pertuzumab. Tyrosine kinase inhibitors (TKIs), like lapatinib, may have added therapeutic value in combination with mAbs through enhanced ADCC activity. Using clinical data, we examined the impact of lapatinib on HER2/EGFR expression levels and natural killer (NK) cell gene signatures. We investigated the ability of three TKIs (lapatinib, afatinib, and neratinib) to alter HER2/immune-related protein levels in preclinical models of HER2-positive (HER2 sup + /sup ) and HER2-low breast cancer, and the subsequent effects on trastuzumab ertuzumab-mediated ADCC. Experimental Design: Preclinical studies (proliferation assays, Western blotting, high content analysis, and flow cytometry) employed HER2 sup + /sup (SKBR3 and HCC1954) and HER2-low (MCF-7, T47D, CAMA-1, and CAL-51) breast cancer cell lines. NCT00524303 provided reverse phase protein array–determined protein levels of HER2 HER2/EGFR EGFR. RNA-based NK cell gene signatures (CIBERSORT/MCP-counter) post-neoadjuvant anti-HER2 therapy were assessed (NCT00769470/NCT01485926). ADCC assays utilized flow cytometry–based protocols. Results: Lapatinib significantly increased membrane HER2 levels, while afatinib and neratinib significantly decreased levels in all preclinical models. Single-agent lapatinib increased HER2 or EGFR levels in 10 of 11 (91%) tumor s les. NK cell signatures increased posttherapy ( i P /i = 0.03) and associated with trastuzumab response ( i P /i = 0.01). TKI treatment altered mAb-induced NK cell–mediated ADCC i in vitro /i , but it did not consistently correlate with HER2 expression in HER2 sup + /sup or HER2-low models. The ADCC response to trastuzumab and pertuzumab combined did not exceed either mAb alone. Conclusions: TKIs differentially alter tumor cell phenotype which can impact NK cell–mediated response to coadministered antibody therapies. mAb-induced ADCC response is relevant when rationalizing combinations for clinical investigation. /
Publisher: American Association for Cancer Research (AACR)
Date: 02-2021
DOI: 10.1158/1078-0432.CCR-20-2007
Abstract: Antibody-dependent cell-mediated cytotoxicity (ADCC) is one mechanism of action of the monoclonal antibody (mAb) therapies trastuzumab and pertuzumab. Tyrosine kinase inhibitors (TKIs), like lapatinib, may have added therapeutic value in combination with mAbs through enhanced ADCC activity. Using clinical data, we examined the impact of lapatinib on HER2/EGFR expression levels and natural killer (NK) cell gene signatures. We investigated the ability of three TKIs (lapatinib, afatinib, and neratinib) to alter HER2/immune-related protein levels in preclinical models of HER2-positive (HER2+) and HER2-low breast cancer, and the subsequent effects on trastuzumab ertuzumab-mediated ADCC. Preclinical studies (proliferation assays, Western blotting, high content analysis, and flow cytometry) employed HER2+ (SKBR3 and HCC1954) and HER2-low (MCF-7, T47D, CAMA-1, and CAL-51) breast cancer cell lines. NCT00524303 provided reverse phase protein array–determined protein levels of HER2 HER2/EGFR EGFR. RNA-based NK cell gene signatures (CIBERSORT/MCP-counter) post-neoadjuvant anti-HER2 therapy were assessed (NCT00769470/NCT01485926). ADCC assays utilized flow cytometry–based protocols. Lapatinib significantly increased membrane HER2 levels, while afatinib and neratinib significantly decreased levels in all preclinical models. Single-agent lapatinib increased HER2 or EGFR levels in 10 of 11 (91%) tumor s les. NK cell signatures increased posttherapy (P = 0.03) and associated with trastuzumab response (P = 0.01). TKI treatment altered mAb-induced NK cell–mediated ADCC in vitro, but it did not consistently correlate with HER2 expression in HER2+ or HER2-low models. The ADCC response to trastuzumab and pertuzumab combined did not exceed either mAb alone. TKIs differentially alter tumor cell phenotype which can impact NK cell–mediated response to coadministered antibody therapies. mAb-induced ADCC response is relevant when rationalizing combinations for clinical investigation.
Publisher: JMIR Publications Inc.
Date: 16-06-2020
Abstract: he COVID-19 outbreak has spread rapidly and hospitals are overwhelmed with COVID-19 patients. While analysis of nasal and throat swabs from patients is the main way to detect COVID-19, analyzing chest images could offer an alternative method to hospitals, where health care personnel and testing kits are scarce. Deep learning (DL), in particular, has shown impressive levels of performance when analyzing medical images, including those related to COVID-19 pneumonia. he goal of this study was to perform a systematic review with a meta-analysis of relevant studies to quantify the performance of DL algorithms in the automatic stratification of COVID-19 patients using chest images. search strategy for use in PubMed, Scopus, Google Scholar, and Web of Science was developed, where we searched for articles published between January 1 and April 25, 2020. We used the key terms “COVID-19,” or “coronavirus,” or “SARS-CoV-2,” or “novel corona,” or “2019-ncov,” and “deep learning,” or “artificial intelligence,” or “automatic detection.” Two authors independently extracted data on study characteristics, methods, risk of bias, and outcomes. Any disagreement between them was resolved by consensus. total of 16 studies were included in the meta-analysis, which included 5896 chest images from COVID-19 patients. The pooled sensitivity and specificity of the DL models in detecting COVID-19 were 0.95 (95% CI 0.94-0.95) and 0.96 (95% CI 0.96-0.97), respectively, with an area under the receiver operating characteristic curve of 0.98. The positive likelihood, negative likelihood, and diagnostic odds ratio were 19.02 (95% CI 12.83-28.19), 0.06 (95% CI 0.04-0.10), and 368.07 (95% CI 162.30-834.75), respectively. The pooled sensitivity and specificity for distinguishing other types of pneumonia from COVID-19 were 0.93 (95% CI 0.92-0.94) and 0.95 (95% CI 0.94-0.95), respectively. The performance of radiologists in detecting COVID-19 was lower than that of the DL models however, the performance of junior radiologists was improved when they used DL-based prediction tools. ur study findings show that DL models have immense potential in accurately stratifying COVID-19 patients and in correctly differentiating them from patients with other types of pneumonia and normal patients. Implementation of DL-based tools can assist radiologists in correctly and quickly detecting COVID-19 and, consequently, in combating the COVID-19 pandemic.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479525
Abstract: All ADCC ratios from Figure 3 and trastuzumab ertuzumab ADCC comparison
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479519.V1
Abstract: Densitometry analysis for Figure 6B
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479531.V1
Abstract: Densitometry for Figure 2B
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479534.V1
Abstract: Densitometry for Figure 1D
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479513.V1
Abstract: Additional supporting information for methods outlined in main manuscript
Publisher: Elsevier BV
Date: 09-2017
DOI: 10.1016/J.CELLIMM.2017.07.005
Abstract: Trastuzumab is an anti-HER2 monoclonal antibody (mAb) therapy capable of antibody-dependent cell-mediated cytotoxicity (ADCC) and used in the treatment of HER2+ breast cancer. Through interactions with FcƴR+ immune cell subsets, trastuzumab functions as a passive immunotherapy. The EGFR/HER2-targeting tyrosine kinase inhibitor (TKI) lapatinib and the next generation TKIs afatinib and neratinib, can alter HER2 levels, potentially modulating the ADCC response to trastuzumab. Using LDH-release assays, we investigated the impact of antigen modulation, assay duration and peripheral blood mononuclear cell (PBMC) activity on trastuzumab-mediated ADCC in breast cancer models of maximal (SKBR3) and minimal (MCF-7) target antigen expression to determine if modulating the ADCC response to trastuzumab using TKIs may be a viable approach for enhancing tumor immune reactivity. HER2 levels were determined in lapatinib, afatinib and neratinib-treated SKBR3 and MCF-7 using high content analysis (HCA). Trastuzumab-mediated ADCC was assessed following treatment with TKIs utilising a colorimetric LDH release-based protocol at 4 and 12h timepoints. PBMC activity was assessed against non-MHC-restricted K562 cells. A flow cytometry-based method (CFSE/7-AAD) was also used to measure trastuzumab-mediated ADCC in medium-treated SKBR3 and MCF-7. HER2 antigen levels were significantly altered by the three TKIs in both cell line models. The TKIs significantly reduced LDH levels directly in SKBR3 cells but not MCF-7. Lapatinib and neratinib augment trastuzumab-related ADCC in SKBR3 but the effect was not consistent with antigen expression levels and was dependent on volunteer PBMC activity (vs. K562). A 12h assay timepoint produced more consistent results. Trastuzumab-mediated ADCC (PBMC:target cell ratio of 10:1) was measured at 7.6±4.7% (T12) by LDH assay and 19±3.2 % (T12) using the flow cytometry-based method in the antigen-low model MCF-7. In the presence of effector cells with high cytotoxic capacity, TKIs have the ability to augment the passive immunotherapeutic potential of trastuzumab in SKBR3, a model of HER2+ breast cancer. ADCC levels detected by LDH release assays are extremely low in MCF-7 the flow cytometry-based CFSE/7-AAD method is more sensitive and consistent for the determination of ADCC in HER2-low models.
Publisher: MDPI AG
Date: 02-05-2021
DOI: 10.3390/JCM10091961
Abstract: Artificial intelligence (AI) has shown immense potential to fight COVID-19 in many ways. This paper focuses primarily on AI’s role in managing COVID-19 using digital images, clinical and laboratory data analysis, and a summary of the most recent articles published last year. We surveyed the use of AI for COVID-19 detection, screening, diagnosis, the progression of severity, mortality, drug repurposing, and other tasks. We started with the technical overview of all models used to fight the COVID-19 pandemic and ended with a brief statement of the current state-of-the-art, limitations, and challenges.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479534
Abstract: Densitometry for Figure 1D
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479531
Abstract: Densitometry for Figure 2B
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479510
Abstract: Flow cytometry MFI and % positive cells data for fluorescently labelled trastuzumab and pertuzumab in SKBR3, HCC1954, T47D and MCF-7 treated with TKIs
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479537
Abstract: Flow cytometry control scatter plots for trastuzumab-488 and pertuzumab-550
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479516
Abstract: Densitometry analysis for Figure 6D/E
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479525.V1
Abstract: All ADCC ratios from Figure 3 and trastuzumab ertuzumab ADCC comparison
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479513
Abstract: Additional supporting information for methods outlined in main manuscript
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22479540.V1
Abstract: Rituximab ADCC negative control
Location: Taiwan, Province of China
No related grants have been discovered for Denis Collins.