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Genina EA, Lazareva EN, Surkov YI, Serebryakova IA, Shushunova NA. Optical parameters of healthy and tumor breast tissues in mice. JOURNAL OF BIOPHOTONICS 2024:e202400123. [PMID: 38925916 DOI: 10.1002/jbio.202400123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 05/23/2024] [Accepted: 05/27/2024] [Indexed: 06/28/2024]
Abstract
Knowledge of the optical parameters of tumors is important for choosing the correct laser treatment parameters. In this paper, optical properties and refraction indices of breast tissue in healthy mice and a 4T1 model mimicking human breast cancer have been measured. A significant decrease in both the scattering and refractive index of tumor tissue has been observed. The change in tissue morphology has induced the change in the slope of the scattering spectrum. Thus, the light penetration depth into tumor has increased by almost 1.5-2 times in the near infrared "optical windows." Raman spectra have shown lower lipid content and higher protein content in tumor. The difference in the optical parameters of the tissues under study makes it possible to reliably differentiate them. The results may be useful for modeling the distribution of laser radiation in healthy tissues and cancers for deriving optimal irradiation conditions in photodynamic therapy.
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Affiliation(s)
- Elina A Genina
- Institute of Physics, Saratov State University, Saratov, Russia
- Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, Tomsk, Russia
| | - Ekaterina N Lazareva
- Institute of Physics, Saratov State University, Saratov, Russia
- Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, Tomsk, Russia
| | - Yuri I Surkov
- Institute of Physics, Saratov State University, Saratov, Russia
- Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, Tomsk, Russia
- Laboratory of Biomedical Photoacoustic, Saratov State University, Saratov, Russia
| | - Isabella A Serebryakova
- Institute of Physics, Saratov State University, Saratov, Russia
- Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, Tomsk, Russia
| | - Natalya A Shushunova
- Laboratory of Biomedical Photoacoustic, Saratov State University, Saratov, Russia
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2
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Orbach SM, DeVaull CY, Bealer EJ, Ross BC, Jeruss JS, Shea LD. An engineered niche delineates metastatic potential of breast cancer. Bioeng Transl Med 2024; 9:e10606. [PMID: 38193115 PMCID: PMC10771563 DOI: 10.1002/btm2.10606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 08/29/2023] [Accepted: 09/20/2023] [Indexed: 01/10/2024] Open
Abstract
Metastatic breast cancer is often not diagnosed until secondary tumors have become macroscopically visible and millions of tumor cells have invaded distant tissues. Yet, metastasis is initiated by a cascade of events leading to formation of the pre-metastatic niche, which can precede tumor formation by a matter of years. We aimed to distinguish the potential for metastatic disease from nonmetastatic disease at early times in triple-negative breast cancer using sister cell lines 4T1 (metastatic), 4T07 (invasive, nonmetastatic), and 67NR (nonmetastatic). We used a porous, polycaprolactone scaffold, that serves as an engineered metastatic niche, to identify metastatic disease through the characteristics of the microenvironment. Analysis of the immune cell composition at the scaffold was able to distinguish noninvasive 67NR tumor-bearing mice from 4T07 and 4T1 tumor-bearing mice but could not delineate metastatic potential between the two invasive cell lines. Gene expression in the scaffolds correlated with the up-regulation of cancer hallmarks (e.g., angiogenesis, hypoxia) in the 4T1 mice relative to 4T07 mice. We developed a 9-gene signature (Dhx9, Dusp12, Fth1, Ifitm1, Ndufs1, Pja2, Slc1a3, Soga1, Spon2) that successfully distinguished 4T1 disease from 67NR or 4T07 disease throughout metastatic progression. Furthermore, this signature proved highly effective at distinguishing diseased lungs in publicly available datasets of mouse models of metastatic breast cancer and in human models of lung cancer. The early and accurate detection of metastatic disease that could lead to early treatment has the potential to improve patient outcomes and quality of life.
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Affiliation(s)
- Sophia M. Orbach
- Department of Biomedical EngineeringUniversity of MichiganAnn ArborMichiganUSA
| | | | - Elizabeth J. Bealer
- Department of Biomedical EngineeringUniversity of MichiganAnn ArborMichiganUSA
| | - Brian C. Ross
- Department of Biomedical EngineeringUniversity of MichiganAnn ArborMichiganUSA
| | - Jacqueline S. Jeruss
- Department of Biomedical EngineeringUniversity of MichiganAnn ArborMichiganUSA
- Department of PathologyUniversity of MichiganAnn ArborMichiganUSA
- Department of SurgeryUniversity of MichiganAnn ArborMichiganUSA
| | - Lonnie D. Shea
- Department of Biomedical EngineeringUniversity of MichiganAnn ArborMichiganUSA
- Department of Chemical EngineeringUniversity of MichiganAnn ArborMichiganUSA
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Sheikh E, Agrawal K, Roy S, Burk D, Donnarumma F, Ko YH, Guttula PK, Biswal NC, Shukla HD, Gartia MR. Multimodal Imaging of Pancreatic Cancer Microenvironment in Response to an Antiglycolytic Drug. Adv Healthc Mater 2023; 12:e2301815. [PMID: 37706285 PMCID: PMC10842640 DOI: 10.1002/adhm.202301815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Indexed: 09/15/2023]
Abstract
Lipid metabolism and glycolysis play crucial roles in the progression and metastasis of cancer, and the use of 3-bromopyruvate (3-BP) as an antiglycolytic agent has shown promise in killing pancreatic cancer cells. However, developing an effective strategy to avoid chemoresistance requires the ability to probe the interaction of cancer drugs with complex tumor-associated microenvironments (TAMs). Unfortunately, no robust and multiplexed molecular imaging technology is currently available to analyze TAMs. In this study, the simultaneous profiling of three protein biomarkers using SERS nanotags and antibody-functionalized nanoparticles in a syngeneic mouse model of pancreatic cancer (PC) is demonstrated. This allows for comprehensive information about biomarkers and TAM alterations before and after treatment. These multimodal imaging techniques include surface-enhanced Raman spectroscopy (SERS), immunohistochemistry (IHC), polarized light microscopy, second harmonic generation (SHG) microscopy, fluorescence lifetime imaging microscopy (FLIM), and untargeted liquid chromatography and mass spectrometry (LC-MS) analysis. The study reveals the efficacy of 3-BP in treating pancreatic cancer and identifies drug treatment-induced lipid species remodeling and associated pathways through bioinformatics analysis.
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Affiliation(s)
- Elnaz Sheikh
- Department of Mechanical and Industrial Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA
| | - Kirti Agrawal
- Department of Mechanical and Industrial Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA
| | - Sanjit Roy
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - David Burk
- Department of Cell Biology and Bioimaging, Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - Fabrizio Donnarumma
- Department of Chemistry, Louisiana State University, Baton Rouge, LA, 70803, USA
| | - Young H Ko
- NewG Lab Pharma, 701 East Pratt Street, Columbus Center, Baltimore, MD, 21202, USA
| | - Praveen Kumar Guttula
- Sprott Center for Stem Cell Research, Regenerative Medicine Program, Ottawa Hospital Research Institute, Ottawa, ON, K1H 8L6, Canada
- Department of Biochemistry, Microbiology, and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, ON, K1H 8M5, Canada
| | - Nrusingh C Biswal
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Hem D Shukla
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Manas Ranjan Gartia
- Department of Mechanical and Industrial Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA
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Wu Y, Wang Y, He C, Wang Y, Ma J, Lin Y, Zhou L, Xu S, Ye Y, Yin W, Ye J, Lu J. Precise diagnosis of breast phyllodes tumors using Raman spectroscopy: Biochemical fingerprint, tumor metabolism and possible mechanism. Anal Chim Acta 2023; 1283:341897. [PMID: 37977771 DOI: 10.1016/j.aca.2023.341897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 08/31/2023] [Accepted: 10/09/2023] [Indexed: 11/19/2023]
Abstract
BACKGROUND Breast fibroadenomas and phyllodes tumors are both fibroepithelial tumors with comparable histological characteristics. However, rapid and precise differential diagnosis is a tough point in clinical pathology. Given the tendency of phyllodes tumors to recur, the difficulty in differential diagnosis with fibroadenomas leads to the difficulty in optimal management for these patients. METHOD In this study, we used Raman spectroscopy to differentiate phyllodes tumors from breast fibroadenomas based on the biochemical and metabolic composition and develop a classification model. The model was validated by 5-fold cross-validation in the training set and tested in an independent test set. The potential metabolic differences between the two types of tumors observed in Raman spectroscopy were confirmed by targeted metabolomic analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS). RESULTS A total of 204 patients with formalin-fixed paraffin-embedded (FFPE) tissue samples, including 100 fibroadenomas and 104 phyllodes tumors were recruited from April 2014 to August 2021. All patients were randomly divided into the training cohort (n = 153) and the test cohort (n = 51). The Raman classification model could differentiate phyllodes tumor versus fibroadenoma with cross-validation accuracy, sensitivity, precision, and area under curve (AUC) of 85.58 % ± 1.77 %, 83.82 % ± 1.01 %, 87.65 % ± 4.22 %, and 93.18 % ± 1.98 %, respectively. When tested in the independent test set, it performed well with the test accuracy, sensitivity, specificity, and AUC of 83.50 %, 86.54 %, 80.39 %, and 90.71 %. Furthermore, the AUC was significantly higher for the Raman model than that for ultrasound (P = 0.0017) and frozen section diagnosis (P < 0.0001). When it came to much more difficult diagnosis between fibroadenoma and benign or small-size phyllodes tumor for pathological examination, the Raman model was capable of differentiating with AUC up to 97.45 % and 95.61 %, respectively. On the other hand, targeted metabolomic analysis, based on fresh-frozen tissue samples, confirmed the differential metabolites (including thymine, dihydrothymine, trans-4-hydroxy-l-proline, etc.) identified from Raman spectra between phyllodes tumor and fibroadenoma. SIGNIFICANCE AND NOVELTY In this study, we obtained the molecular information map of breast phyllodes tumors provided by Raman spectroscopy for the first time. We identified a novel Raman fingerprint signature with the potential to precisely characterize and distinguish phyllodes tumors from fibroadenoma as a quick and accurate diagnostic tool. Raman spectroscopy is expected to further guide the precise diagnosis and optimal treatment of breast fibroepithelial tumors in the future.
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Affiliation(s)
- Yifan Wu
- Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, PR China
| | - Yaohui Wang
- Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, PR China.
| | - Chang He
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PR China
| | - Yan Wang
- Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, PR China
| | - Jiayi Ma
- Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, PR China
| | - Yanping Lin
- Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, PR China
| | - Liheng Zhou
- Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, PR China
| | - Shuguang Xu
- Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, PR China
| | - Yumei Ye
- Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, PR China
| | - Wenjin Yin
- Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, PR China.
| | - Jian Ye
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PR China; Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, PR China; Shanghai Key Laboratory of Gynecologic Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, PR China.
| | - Jingsong Lu
- Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, PR China.
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Rodriguez Troncoso J, Marium Mim U, Ivers JD, Paidi SK, Harper MG, Nguyen KG, Ravindranathan S, Rebello L, Lee DE, Zaharoff DA, Barman I, Rajaram N. Evaluating differences in optical properties of indolent and aggressive murine breast tumors using quantitative diffuse reflectance spectroscopy. BIOMEDICAL OPTICS EXPRESS 2023; 14:6114-6126. [PMID: 38420330 PMCID: PMC10898562 DOI: 10.1364/boe.505153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 10/06/2023] [Accepted: 10/26/2023] [Indexed: 03/02/2024]
Abstract
We used diffuse reflectance spectroscopy to quantify tissue absorption and scattering-based parameters in similarly sized tumors derived from a panel of four isogenic murine breast cancer cell lines (4T1, 4T07, 168FARN, 67NR) that are each capable of accomplishing different steps of the invasion-metastasis cascade. We found lower tissue scattering, increased hemoglobin concentration, and lower vascular oxygenation in indolent 67NR tumors incapable of metastasis compared with aggressive 4T1 tumors capable of metastasis. Supervised learning statistical approaches were able to accurately differentiate between tumor groups and classify tumors according to their ability to accomplish each step of the invasion-metastasis cascade. We investigated whether the inhibition of metastasis-promoting genes in the highly metastatic 4T1 tumors resulted in measurable optical changes that made these tumors similar to the indolent 67NR tumors. These results demonstrate the potential of diffuse reflectance spectroscopy to noninvasively evaluate tumor biology and discriminate between indolent and aggressive tumors.
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Affiliation(s)
| | - Umme Marium Mim
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
| | - Jesse D. Ivers
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
| | - Santosh K. Paidi
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Mason G. Harper
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
| | - Khue G. Nguyen
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
| | - Sruthi Ravindranathan
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
| | - Lisa Rebello
- Cell and Molecular Biology Program, University of Arkansas, Fayetteville, AR 72701, USA
| | - David E. Lee
- Cell and Molecular Biology Program, University of Arkansas, Fayetteville, AR 72701, USA
- Department of Exercise Science, University of Arkansas, Fayetteville, AR 72703, USA
| | - David A. Zaharoff
- Joint Department of Biomedical Engineering, University of North Carolina and North Carolina State University, Raleigh, NC 27695, USA
| | - Ishan Barman
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Narasimhan Rajaram
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
- Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
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6
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Yang E, Kim JH, Tressler CM, Shen XE, Brown DR, Johnson CC, Hahm TH, Barman I, Glunde K. RaMALDI: Enabling simultaneous Raman and MALDI imaging of the same tissue section. Biosens Bioelectron 2023; 239:115597. [PMID: 37597501 PMCID: PMC10544780 DOI: 10.1016/j.bios.2023.115597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 08/02/2023] [Accepted: 08/11/2023] [Indexed: 08/21/2023]
Abstract
Multimodal tissue imaging techniques that integrate two complementary modalities are powerful discovery tools for unraveling biological processes and identifying biomarkers of disease. Combining Raman spectroscopic imaging (RSI) and matrix-assisted laser-desorption/ionization (MALDI) mass spectrometry imaging (MSI) to obtain fused images with the advantages of both modalities has the potential of providing spatially resolved, sensitive, specific biomolecular information, but has so far involved two separate sample preparations, or even consecutive tissue sections for RSI and MALDI MSI, resulting in images with inherent disparities. We have developed RaMALDI, a streamlined, integrated, multimodal imaging workflow of RSI and MALDI MSI, performed on a single tissue section with one sample preparation protocol. We show that RaMALDI imaging of various tissues effectively integrates molecular information acquired from both RSI and MALDI MSI of the same sample, which will drive discoveries in cell biology, biomedicine, and pathology, and advance tissue diagnostics.
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Affiliation(s)
- Ethan Yang
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Jeong Hee Kim
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Caitlin M Tressler
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Xinyi Elaine Shen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Dalton R Brown
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Cole C Johnson
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Tae-Hun Hahm
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Ishan Barman
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA; Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
| | - Kristine Glunde
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA; Departments of Oncology and Biological Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA.
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Anantha P, Liu Z, Raj P, Barman I. Optical diffraction tomography and Raman spectroscopy reveal distinct cellular phenotypes during white and brown adipocyte differentiation. Biosens Bioelectron 2023; 235:115388. [PMID: 37207582 PMCID: PMC10626559 DOI: 10.1016/j.bios.2023.115388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Revised: 05/06/2023] [Accepted: 05/10/2023] [Indexed: 05/21/2023]
Abstract
White adipose tissue (WAT) and brown adipose tissue (BAT) are the primary types of fats in humans, and they play prominent roles in energy storage and thermogenesis, respectively. While the mechanisms of terminal adipogenesis are well understood, much remains unknown about the early stages of adipogenic differentiation. Label-free approaches, such as optical diffraction tomography (ODT) and Raman spectroscopy, offer the ability to retrieve morphological and molecular information at the single cell level without the negative effects of photobleaching and system perturbation due to introduction of fluorophores. In this study, we employed 3D ODT and Raman spectroscopy to gain deeper insights into the early stages of differentiation of human white preadipocytes (HWPs) and human brown preadipocytes (HBPs). We utilized ODT to retrieve morphological information, including cell dry mass and lipid mass, and Raman spectroscopy to obtain molecular information about lipids. Our findings reveal that HWPs and HBPs undergo dynamic and differential changes during the differentiation process. Notably, we found that HBPs accumulated lipids more rapidly and had a higher lipid mass than HWPs. Additionally, both cell types experienced an increase and subsequent decrease in cell dry mass during the first seven days, followed by an increase after day 7, which we attribute to the transformation of adipogenic precursors in the early stages. Finally, HBPs had higher lipid unsaturation levels than HWPs for the same differentiation timepoints. The insights gained from our study provide crucial contributions towards the advancement of new therapies for obesity and related diseases.
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Affiliation(s)
- Pooja Anantha
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Zhenhui Liu
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Piyush Raj
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Ishan Barman
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA; Department of Oncology, Johns Hopkins University, Baltimore, MD, 21287, USA; The Russell H. Morgan Department of Radiology and Radiological Science, Division of Cancer Imaging Research, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
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8
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Becker L, Lu CE, Montes-Mojarro IA, Layland SL, Khalil S, Nsair A, Duffy GP, Fend F, Marzi J, Schenke-Layland K. Raman microspectroscopy identifies fibrotic tissues in collagen-related disorders via deconvoluted collagen type I spectra. Acta Biomater 2023; 162:278-291. [PMID: 36931422 DOI: 10.1016/j.actbio.2023.03.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 02/28/2023] [Accepted: 03/09/2023] [Indexed: 03/18/2023]
Abstract
Fibrosis is a consequence of the pathological remodeling of extracellular matrix (ECM) structures in the connective tissue of an organ. It is often caused by chronic inflammation, which over time, progressively leads to an excess deposition of collagen type I (COL I) that replaces healthy tissue structures, in many cases leaving a stiff scar. Increasing fibrosis can lead to organ failure and death; therefore, developing methods that potentially allow real-time monitoring of early onset or progression of fibrosis are highly valuable. In this study, the ECM structures of diseased and healthy human tissue from multiple organs were investigated for the presence of fibrosis using routine histology and marker-independent Raman microspectroscopy and Raman imaging. Spectral deconvolution of COL I Raman spectra allowed the discrimination of fibrotic and non-fibrotic COL I fibers. Statistically significant differences were identified in the amide I region of the spectral subpeak at 1608 cm-1, which was deemed to be representative for structural changes in COL I fibers in all examined fibrotic tissues. Raman spectroscopy-based methods in combination with this newly discovered spectroscopic biomarker potentially offer a diagnostic approach to non-invasively track and monitor the progression of fibrosis. STATEMENT OF SIGNIFICANCE: Current diagnosis of fibrosis still relies on histopathological examination with invasive biopsy procedures. Although, several non-invasive imaging techniques such as positron emission tomography, single-photon emission computed tomography and second harmonic generation are gradually employed in preclinical or clinical studies, these techniques are limited in spatial resolution and the morphological interpretation highly relies on individual experience and knowledge. In this study, we propose a non-destructive technique, Raman microspectroscopy, to discriminate fibrotic changes of collagen type I based on a molecular biomarker. The changes of the secondary structure of collagen type I can be identified by spectral deconvolution, which potentially can provide an automatic diagnosis for fibrotic tissues in the clinical applicaion.
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Affiliation(s)
- Lucas Becker
- Institute of Biomedical Engineering, Department for Medical Technologies and Regenerative Medicine, Silcherstr. 7/1, Eberhard Karls University, 72076 Tübingen, Germany; Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", Eberhard Karls University, Tübingen, Germany
| | - Chuan-En Lu
- Institute of Biomedical Engineering, Department for Medical Technologies and Regenerative Medicine, Silcherstr. 7/1, Eberhard Karls University, 72076 Tübingen, Germany
| | | | - Shannon L Layland
- Institute of Biomedical Engineering, Department for Medical Technologies and Regenerative Medicine, Silcherstr. 7/1, Eberhard Karls University, 72076 Tübingen, Germany
| | - Suzan Khalil
- Department of Medicine/Cardiology, Cardiovascular Research Laboratories, David Geffen School of Medicine at UCLA, 675 Charles E. Young Drive South, MRL 3645 Los Angeles, CA, USA
| | - Ali Nsair
- Department of Medicine/Cardiology, Cardiovascular Research Laboratories, David Geffen School of Medicine at UCLA, 675 Charles E. Young Drive South, MRL 3645 Los Angeles, CA, USA
| | - Garry P Duffy
- Anatomy & Regenerative Medicine Institute, School of Medicine, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, H91 TK33, Galway, Ireland
| | - Falko Fend
- Institute of Pathology and Neuropathology, University Hospital Tübingen, Tübingen, Germany
| | - Julia Marzi
- Institute of Biomedical Engineering, Department for Medical Technologies and Regenerative Medicine, Silcherstr. 7/1, Eberhard Karls University, 72076 Tübingen, Germany; Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", Eberhard Karls University, Tübingen, Germany; NMI Natural and Medical Sciences Institute at the University of Tübingen, Markwiesenstr. 55, 72770 Reutlingen, Germany
| | - Katja Schenke-Layland
- Institute of Biomedical Engineering, Department for Medical Technologies and Regenerative Medicine, Silcherstr. 7/1, Eberhard Karls University, 72076 Tübingen, Germany; Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", Eberhard Karls University, Tübingen, Germany; NMI Natural and Medical Sciences Institute at the University of Tübingen, Markwiesenstr. 55, 72770 Reutlingen, Germany.
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9
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Goffin N, Buache E, Charpentier C, Lehrter V, Morjani H, Gobinet C, Piot O. Trajectory Inference for Unraveling Dynamic Biological Processes from Raman Spectral Data. Anal Chem 2023; 95:4395-4403. [PMID: 36788139 DOI: 10.1021/acs.analchem.2c04901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Cell heterogeneity is a crucial parameter for understanding the complexity of numerous biomedical issues. Trajectory inference-based approaches are recent tools developed for single-cell transcriptomics (scRNA-seq) data analysis. They aim to reconstruct evolving pathways from the variety of cell states that coexist simultaneously in a cell population. We propose to expand this concept to Raman spectroscopy, a label-free modality that probes the global molecular nature of a sample, by investigating the dynamics of adipocyte differentiation.
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Affiliation(s)
- Nicolas Goffin
- University of Reims Champagne Ardenne, BioSpecT EA 7506, SFR Santé, France
| | - Emilie Buache
- University of Reims Champagne Ardenne, BioSpecT EA 7506, SFR Santé, France
| | - Celine Charpentier
- University of Reims Champagne Ardenne, BioSpecT EA 7506, SFR Santé, France
| | - Véronique Lehrter
- University of Reims Champagne Ardenne, BioSpecT EA 7506, SFR Santé, France
| | - Hamid Morjani
- University of Reims Champagne Ardenne, BioSpecT EA 7506, SFR Santé, France
| | - Cyril Gobinet
- University of Reims Champagne Ardenne, BioSpecT EA 7506, SFR Santé, France
| | - Olivier Piot
- University of Reims Champagne Ardenne, BioSpecT EA 7506, SFR Santé, France.,University of Reims Champagne Ardenne, Platform of Cellular and Tissular Imaging (PICT) EA 7506, SFR Santé, France
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