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Wang R, Ekem L, Gallagher J, Factor RE, Hall A, Ramanujam N. A color-based tumor segmentation method for clinical ex vivo breast tissue assessment utilizing a multi-contrast brightfield imaging strategy. JOURNAL OF BIOPHOTONICS 2024; 17:e202300241. [PMID: 38348582 PMCID: PMC11065618 DOI: 10.1002/jbio.202300241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 01/20/2024] [Accepted: 01/21/2024] [Indexed: 03/21/2024]
Abstract
We demonstrate an automated two-step tumor segmentation method leveraging color information from brightfield images of fresh core needle biopsies of breast tissue. Three different color spaces (HSV, CIELAB, YCbCr) were explored for the segmentation task. By leveraging white-light and green-light images, we identified two different types of color transformations that could separate adipose from benign and tumor or cancerous tissue. We leveraged these two distinct color transformation methods in a two-step process where adipose tissue segmentation was followed by benign tissue segmentation thereby isolating the malignant region of the biopsy. Our tumor segmentation algorithm and imaging probe could highlight suspicious regions on unprocessed biopsy tissue to guide selection of areas most similar to malignant tissues for tissue pathology whether it be formalin fixed or frozen sections, expedite tissue selection for molecular testing, detect positive tumor margins, or serve an alternative to tissue pathology, in countries where these services are lacking.
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Affiliation(s)
- Roujia Wang
- Department of Biomedical Engineering, Duke University, 27710 Durham, NC, USA
| | - Lillian Ekem
- Department of Biomedical Engineering, Duke University, 27710 Durham, NC, USA
| | - Jennifer Gallagher
- Department of Surgery, Duke University School of Medicine, 27710 Durham, NC, USA
| | | | - Allison Hall
- Department of Pathology, Duke University, 27710 Durham, NC, USA
| | - Nimmi Ramanujam
- Department of Biomedical Engineering, Duke University, 27710 Durham, NC, USA
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, 27710 Durham, NC, USA
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Xu Q, Li J, Zhang Z, Yang Q, Zhang W, Yao J, Zhang Y, Zhang Y, Guo Z, Li C, Li S, Zhang C, Wang C, Du L, Li C, Zhou L. Precise determination of reaction conditions for accurate quantification in digital PCR by real-time fluorescence monitoring within microwells. Biosens Bioelectron 2024; 244:115798. [PMID: 37924656 DOI: 10.1016/j.bios.2023.115798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Revised: 09/27/2023] [Accepted: 10/27/2023] [Indexed: 11/06/2023]
Abstract
Real-time digital polymerase chain reaction (qdPCR) provides enhanced precision in the field of molecular diagnostics by integrating absolute quantification with process information. However, the optimal reaction conditions are traditionally determined through multiple iterative of experiments. Therefore, we proposed a novel approach to precisely determine the optimal reaction conditions for qdPCR using a standard process, employing real-time fluorescence monitoring within microwells. The temperature-sensitive fluorophore intensity presented the real temperature of each microwell. This enabled us to determine the optimal denaturation and annealing time for qdPCR based on the corresponding critical temperatures derived from the melting curves and amplification efficiency, respectively. To confirm this method, we developed an ultrathin laminated chip (UTL chip) and chose a target that need to be absolutely quantitative. The UTL chip was designed using a fluid‒solid‒thermal coupling simulation model and exhibited a faster thermal response than a commercial dPCR chip. By leveraging our precise determination of reaction conditions and utilizing the UTL chip, 40 cycles of amplification were achieved within 18 min. This was accomplished by precisely controlling the denaturation temperature at 2 s and the annealing temperature at 10 s. Furthermore, the absolutely quantitative of DNA showed good correlation (R2 > 0.999) with the concentration gradient detection using the optimal reaction conditions with the UTL chip for qdPCR. Our proposed method can significantly improve the accuracy and efficiency of determining qdPCR conditions, which holds great promise for application in molecular diagnostics.
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Affiliation(s)
- Qi Xu
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China; CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Jinze Li
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Zhiqi Zhang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China; CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China; Suzhou CASENS Co., Ltd, Suzhou, 215163, China
| | - Qi Yang
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Wei Zhang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China; CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China; Suzhou CASENS Co., Ltd, Suzhou, 215163, China; Ji Hua Laboratory, Foshan, 528000, China
| | - Jia Yao
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Yaxin Zhang
- Department of Mechanical and Electric Engineering, Changchun University of Science and Technology, Changchun, 130022, China
| | - Yueye Zhang
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Zhen Guo
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China; CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Chao Li
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China; CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Shuli Li
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Changsong Zhang
- Suzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, Suzhou, 215153, China
| | - Chuanxin Wang
- Department of Clinical Laboratory, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Lutao Du
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, Shandong Provincial Key Laboratory of Innovation Technology in Laboratory Medicine, Jinan, 250012, China.
| | - Chuanyu Li
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China; CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.
| | - Lianqun Zhou
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China; CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China; Suzhou CASENS Co., Ltd, Suzhou, 215163, China.
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Hu X, Zhu C, Sun F, Chen Z, Zou J, Chen X, Yang Z. J-Aggregation Strategy toward Potentiated NIR-II Fluorescence Bioimaging of Molecular Fluorophores. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2304848. [PMID: 37526997 DOI: 10.1002/adma.202304848] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 07/28/2023] [Indexed: 08/03/2023]
Abstract
Molecular fluorophores emitting in the second near-infrared (NIR-II, 1000-1700 nm) window with strong optical harvesting and high quantum yields hold great potential for in vivo deep-tissue bioimaging and high-resolution biosensing. Recently, J-aggregates are harnessed to engineer long-wavelength NIR-II emitters and show unique superiority in tumor detection, vessel mapping, surgical navigation, and phototheranostics due to their bathochromic-shifted optical bands in the required slip-stacked arrangement aggregation state. However, despite the preliminary progress of NIR-II J-aggregates and theoretical study of structure-property relationships, further paradigms of NIR-II J-aggregates remain scarce due to the lack of study on aggregated fluorophores with slip-stacked fashion. In this effort, how to utilize the specific molecular structure to form slip-stacked packing motifs with J-type aggregated exciton coupling is emphatically elucidated. First, several molecular regulating strategies to achieve NIR-II J-aggregates containing intermolecular interactions and external conditions are positively summarized and deeply analyzed. Then, the recent reports on J-aggregates for NIR-II bioimaging and theranostics are systematically summarized to provide a clear reference and direction for promoting the development of NIR-II organic fluorophores. Eventually, the prospective efforts on ameliorating and promoting NIR-II J-aggregates to further clinical practices are outlined.
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Affiliation(s)
- Xiaoming Hu
- Jiangxi Key Laboratory of Nanobiomaterials, School of Materials Science and Engineering, East China Jiaotong University, Nanchang, 330013, China
- Strait Laboratory of Flexible Electronics (SLoFE), Strait Institute of Flexible Electronics (SIFE, Future Technologies), Fujian Normal University, Fuzhou, Fujian, 350117, China
| | - Caijun Zhu
- Jiangxi Key Laboratory of Nanobiomaterials, School of Materials Science and Engineering, East China Jiaotong University, Nanchang, 330013, China
| | - Fengwei Sun
- Strait Laboratory of Flexible Electronics (SLoFE), Strait Institute of Flexible Electronics (SIFE, Future Technologies), Fujian Normal University, Fuzhou, Fujian, 350117, China
| | - Zejing Chen
- Jiangxi Key Laboratory of Nanobiomaterials, School of Materials Science and Engineering, East China Jiaotong University, Nanchang, 330013, China
| | - Jianhua Zou
- Departments of Diagnostic Radiology, Surgery, Chemical and Biomolecular Engineering and Biomedical Engineering, Yong Loo Lin School of Medicine and Faculty of Engineering, National University of Singapore, Singapore, 119074, Singapore
| | - Xiaoyuan Chen
- Departments of Diagnostic Radiology, Surgery, Chemical and Biomolecular Engineering and Biomedical Engineering, Yong Loo Lin School of Medicine and Faculty of Engineering, National University of Singapore, Singapore, 119074, Singapore
- Institute of Molecular and Cell Biology, Agency for Science, Technology, and Research (A*STAR) 61 Biopolis Drive, Proteos, Singapore, 138673, Singapore
| | - Zhen Yang
- Strait Laboratory of Flexible Electronics (SLoFE), Strait Institute of Flexible Electronics (SIFE, Future Technologies), Fujian Normal University, Fuzhou, Fujian, 350117, China
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Sunassee ED, Jardim-Perassi BV, Madonna MC, Ordway B, Ramanujam N. Metabolic Imaging as a Tool to Characterize Chemoresistance and Guide Therapy in Triple-Negative Breast Cancer (TNBC). Mol Cancer Res 2023; 21:995-1009. [PMID: 37343066 PMCID: PMC10592445 DOI: 10.1158/1541-7786.mcr-22-1004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 04/07/2023] [Accepted: 06/15/2023] [Indexed: 06/23/2023]
Abstract
After an initial response to chemotherapy, tumor relapse is frequent. This event is reflective of both the spatiotemporal heterogeneities of the tumor microenvironment as well as the evolutionary propensity of cancer cell populations to adapt to variable conditions. Because the cause of this adaptation could be genetic or epigenetic, studying phenotypic properties such as tumor metabolism is useful as it reflects molecular, cellular, and tissue-level dynamics. In triple-negative breast cancer (TNBC), the characteristic metabolic phenotype is a highly fermentative state. However, during treatment, the spatial and temporal dynamics of the metabolic landscape are highly unstable, with surviving populations taking on a variety of metabolic states. Thus, longitudinally imaging tumor metabolism provides a promising approach to inform therapeutic strategies, and to monitor treatment responses to understand and mitigate recurrence. Here we summarize some examples of the metabolic plasticity reported in TNBC following chemotherapy and review the current metabolic imaging techniques available in monitoring chemotherapy responses clinically and preclinically. The ensemble of imaging technologies we describe has distinct attributes that make them uniquely suited for a particular length scale, biological model, and/or features that can be captured. We focus on TNBC to highlight the potential of each of these technological advances in understanding evolution-based therapeutic resistance.
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Affiliation(s)
- Enakshi D. Sunassee
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | | | - Megan C. Madonna
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Bryce Ordway
- Department of Cancer Physiology, Moffitt Cancer Center, Tampa, FL 33612, USA
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Nirmala Ramanujam
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC 27708, USA
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Du Y, Cao L, Li X, Zhu T, Yan R, Dong WF, Li L. Preparation and application of high-brightness red carbon quantum dots for pH and oxidized L-glutathione dual response. Analyst 2023; 148:2375-2386. [PMID: 37129055 DOI: 10.1039/d3an00383c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Carbon dots (CDs) with red fluorescence emission are highly desirable for use in bioimaging and trace- substance detection, with potential applications in biotherapy, photothermal therapy, and tumor visualization. Most CDs emit green or blue fluorescence, thus limiting their applicability. We report a novel fluorescent detection platform based on high-brightness red fluorescence emission carbon dots (R-CDs) co-doped with nitrogen and bromine, which exhibit pH and oxidized L-glutathione (GSSG) dual-responsive characteristics. The absolute quantum yield of the R-CDs was as high as 11.93%. We discovered that the R-CDs were able to detect acidic pH in live cells and zebrafish owing to protonation and deprotonation. In addition, GSSG was detected in vitro over a broad linear range (8-200 μM) using the R-CDs with excitation-independent emission. Furthermore, cell imaging and bioimaging experiments demonstrated that the R-CDs were highly cytocompatible and could be used as fluorescent probes to target lysosomes and nucleolus. These studies highlight the promising prospects of R-CDs as biosensing tools for bioimaging and trace-substance detection applications.
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Affiliation(s)
- Yuwei Du
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- CAS Key Laboratory of Biomedical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science (CAS), Suzhou, 215163, China.
| | - Lei Cao
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- CAS Key Laboratory of Biomedical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science (CAS), Suzhou, 215163, China.
| | - Xinlu Li
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- CAS Key Laboratory of Biomedical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science (CAS), Suzhou, 215163, China.
| | - Tongtong Zhu
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- CAS Key Laboratory of Biomedical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science (CAS), Suzhou, 215163, China.
| | - Ruhong Yan
- Department of Clinical Laboratory, Suzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, Suzhou, 215153, China.
- CAS Key Laboratory of Biomedical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science (CAS), Suzhou, 215163, China.
| | - Wen-Fei Dong
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- CAS Key Laboratory of Biomedical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science (CAS), Suzhou, 215163, China.
| | - Li Li
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- CAS Key Laboratory of Biomedical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science (CAS), Suzhou, 215163, China.
- Jinan Guokeyigong Science and Technology Development Co., Ltd, Jinan, 250104, China.
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