Combining Multiplex SERS Nanovectors and Multivariate Analysis for In Situ Profiling of Circulating Tumor Cell Phenotype Using a Microfluidic Chip
Isolating and in situ profiling the heterogeneous molecular phenotype of circulating tumor cells are of great significance for clinical cancer diagnosis and personalized therapy. Herein, an on‐chip strategy is proposed that combines size‐based microfluidic cell isolation with multiple spectrally ort...
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description | Isolating and in situ profiling the heterogeneous molecular phenotype of circulating tumor cells are of great significance for clinical cancer diagnosis and personalized therapy. Herein, an on‐chip strategy is proposed that combines size‐based microfluidic cell isolation with multiple spectrally orthogonal surface‐enhanced Raman spectroscopy (SERS) analysis for in situ profiling of cell membrane proteins and identification of cancer subpopulations. With the developed microfluidic chip, tumor cells are sieved from blood on the basis of size discrepancy. To enable multiplex phenotypic analysis, three kinds of spectrally orthogonal SERS aptamer nanovectors are designed, providing individual cells with composite spectral signatures in accordance with surface protein expression. Next, to statistically demultiplex the complex SERS signature and profile the cellular proteomic phenotype, a revised classic least square algorithm is employed to obtain the 3D phenotypic information at single‐cell resolution. Combined with categorization algorithm partial least square discriminate analysis, cells from different human breast cancer subtypes can be reliably classified with high sensitivity and selectivity. The results demonstrate that this platform can identify cancer subtypes with the spectral information correlated to the clinically relevant surface receptors, which holds great potential for clinical cancer diagnosis and precision medicine.
For in situ profiling of cell membrane proteins and identification of cancer subpopulations, an on‐chip strategy that combines size‐based microfluidic cell isolation with multiple spectrally orthogonal surface‐enhanced Raman spectroscopy (SERS) analysis is proposed. Employing multivariate spectral analysis, the 3D phenotypic information and corresponding subtype of captured circulating tumor cells can be readily obtained according to their composite SERS signatures. |
doi_str_mv | 10.1002/smll.201704433 |
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For in situ profiling of cell membrane proteins and identification of cancer subpopulations, an on‐chip strategy that combines size‐based microfluidic cell isolation with multiple spectrally orthogonal surface‐enhanced Raman spectroscopy (SERS) analysis is proposed. Employing multivariate spectral analysis, the 3D phenotypic information and corresponding subtype of captured circulating tumor cells can be readily obtained according to their composite SERS signatures.</description><identifier>ISSN: 1613-6810</identifier><identifier>EISSN: 1613-6829</identifier><identifier>DOI: 10.1002/smll.201704433</identifier><identifier>PMID: 29665274</identifier><language>eng</language><publisher>Germany: Wiley Subscription Services, Inc</publisher><subject>Algorithms ; Cancer ; circulating tumor cells ; Diagnosis ; Genotype & phenotype ; Least squares ; Medical diagnosis ; microfluidics ; Molecular chains ; Multiplexing ; Multivariate analysis ; Nanotechnology ; phenotypes ; Proteins ; Receptors ; SERS ; Spectra ; Spectral signatures ; Tumors</subject><ispartof>Small (Weinheim an der Bergstrasse, Germany), 2018-05, Vol.14 (20), p.e1704433-n/a</ispartof><rights>2018 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim</rights><rights>2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3733-8faf7d8081786b1a62e13b0e31e5371a9cd2858149cd5cfa5e674456e0991f963</citedby><cites>FETCH-LOGICAL-c3733-8faf7d8081786b1a62e13b0e31e5371a9cd2858149cd5cfa5e674456e0991f963</cites><orcidid>0000-0002-4648-2506</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fsmll.201704433$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fsmll.201704433$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29665274$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhang, Yizhi</creatorcontrib><creatorcontrib>Wang, Zhuyuan</creatorcontrib><creatorcontrib>Wu, Lei</creatorcontrib><creatorcontrib>Zong, Shenfei</creatorcontrib><creatorcontrib>Yun, Binfeng</creatorcontrib><creatorcontrib>Cui, Yiping</creatorcontrib><title>Combining Multiplex SERS Nanovectors and Multivariate Analysis for In Situ Profiling of Circulating Tumor Cell Phenotype Using a Microfluidic Chip</title><title>Small (Weinheim an der Bergstrasse, Germany)</title><addtitle>Small</addtitle><description>Isolating and in situ profiling the heterogeneous molecular phenotype of circulating tumor cells are of great significance for clinical cancer diagnosis and personalized therapy. Herein, an on‐chip strategy is proposed that combines size‐based microfluidic cell isolation with multiple spectrally orthogonal surface‐enhanced Raman spectroscopy (SERS) analysis for in situ profiling of cell membrane proteins and identification of cancer subpopulations. With the developed microfluidic chip, tumor cells are sieved from blood on the basis of size discrepancy. To enable multiplex phenotypic analysis, three kinds of spectrally orthogonal SERS aptamer nanovectors are designed, providing individual cells with composite spectral signatures in accordance with surface protein expression. Next, to statistically demultiplex the complex SERS signature and profile the cellular proteomic phenotype, a revised classic least square algorithm is employed to obtain the 3D phenotypic information at single‐cell resolution. Combined with categorization algorithm partial least square discriminate analysis, cells from different human breast cancer subtypes can be reliably classified with high sensitivity and selectivity. The results demonstrate that this platform can identify cancer subtypes with the spectral information correlated to the clinically relevant surface receptors, which holds great potential for clinical cancer diagnosis and precision medicine.
For in situ profiling of cell membrane proteins and identification of cancer subpopulations, an on‐chip strategy that combines size‐based microfluidic cell isolation with multiple spectrally orthogonal surface‐enhanced Raman spectroscopy (SERS) analysis is proposed. Employing multivariate spectral analysis, the 3D phenotypic information and corresponding subtype of captured circulating tumor cells can be readily obtained according to their composite SERS signatures.</description><subject>Algorithms</subject><subject>Cancer</subject><subject>circulating tumor cells</subject><subject>Diagnosis</subject><subject>Genotype & phenotype</subject><subject>Least squares</subject><subject>Medical diagnosis</subject><subject>microfluidics</subject><subject>Molecular chains</subject><subject>Multiplexing</subject><subject>Multivariate analysis</subject><subject>Nanotechnology</subject><subject>phenotypes</subject><subject>Proteins</subject><subject>Receptors</subject><subject>SERS</subject><subject>Spectra</subject><subject>Spectral signatures</subject><subject>Tumors</subject><issn>1613-6810</issn><issn>1613-6829</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqFkcFu1DAQhi0EoqVw5YgsceGyi8d27ORYRaVU2qUV254jb2JTV04c7LjtvkafGEdbFolLTx5rvvk09o_QRyBLIIR-jb1zS0pAEs4Ze4WOQQBbiJJWrw81kCP0LsY7QhhQLt-iI1oJUVDJj9FT7futHezwC6-Tm-zo9CPenP3c4B9q8Pe6nXyIWA3dvn2vglWTxqeDcrtoIzY-4IsBb-yU8FXwxrpZ5Q2ubWiTU9N8vU59xmrtHL661YOfdqPGN3FuKby2bZ5zyXa2xfWtHd-jN0a5qD88nyfo5tvZdf19sbo8v6hPV4uWScYWpVFGdiUpQZZiC0pQDWxLNANdMAmqajtaFiXwXBStUYUWkvNCaFJVYCrBTtCXvXcM_nfScWp6G9u8pBq0T7GhhEoiJAGa0c__oXc-hfwHM8WzFjhhmVruqfygGIM2zRhsr8KuAdLMaTVzWs0hrTzw6Vmbtr3uDvjfeDJQ7YEH6_TuBV2zWa9W_-R_AEPkod4</recordid><startdate>201805</startdate><enddate>201805</enddate><creator>Zhang, Yizhi</creator><creator>Wang, Zhuyuan</creator><creator>Wu, Lei</creator><creator>Zong, Shenfei</creator><creator>Yun, Binfeng</creator><creator>Cui, Yiping</creator><general>Wiley Subscription Services, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>L7M</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-4648-2506</orcidid></search><sort><creationdate>201805</creationdate><title>Combining Multiplex SERS Nanovectors and Multivariate Analysis for In Situ Profiling of Circulating Tumor Cell Phenotype Using a Microfluidic Chip</title><author>Zhang, Yizhi ; Wang, Zhuyuan ; Wu, Lei ; Zong, Shenfei ; Yun, Binfeng ; Cui, Yiping</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3733-8faf7d8081786b1a62e13b0e31e5371a9cd2858149cd5cfa5e674456e0991f963</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Algorithms</topic><topic>Cancer</topic><topic>circulating tumor cells</topic><topic>Diagnosis</topic><topic>Genotype & phenotype</topic><topic>Least squares</topic><topic>Medical diagnosis</topic><topic>microfluidics</topic><topic>Molecular chains</topic><topic>Multiplexing</topic><topic>Multivariate analysis</topic><topic>Nanotechnology</topic><topic>phenotypes</topic><topic>Proteins</topic><topic>Receptors</topic><topic>SERS</topic><topic>Spectra</topic><topic>Spectral signatures</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Yizhi</creatorcontrib><creatorcontrib>Wang, Zhuyuan</creatorcontrib><creatorcontrib>Wu, Lei</creatorcontrib><creatorcontrib>Zong, Shenfei</creatorcontrib><creatorcontrib>Yun, Binfeng</creatorcontrib><creatorcontrib>Cui, Yiping</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>MEDLINE - Academic</collection><jtitle>Small (Weinheim an der Bergstrasse, Germany)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Yizhi</au><au>Wang, Zhuyuan</au><au>Wu, Lei</au><au>Zong, Shenfei</au><au>Yun, Binfeng</au><au>Cui, Yiping</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Combining Multiplex SERS Nanovectors and Multivariate Analysis for In Situ Profiling of Circulating Tumor Cell Phenotype Using a Microfluidic Chip</atitle><jtitle>Small (Weinheim an der Bergstrasse, Germany)</jtitle><addtitle>Small</addtitle><date>2018-05</date><risdate>2018</risdate><volume>14</volume><issue>20</issue><spage>e1704433</spage><epage>n/a</epage><pages>e1704433-n/a</pages><issn>1613-6810</issn><eissn>1613-6829</eissn><abstract>Isolating and in situ profiling the heterogeneous molecular phenotype of circulating tumor cells are of great significance for clinical cancer diagnosis and personalized therapy. Herein, an on‐chip strategy is proposed that combines size‐based microfluidic cell isolation with multiple spectrally orthogonal surface‐enhanced Raman spectroscopy (SERS) analysis for in situ profiling of cell membrane proteins and identification of cancer subpopulations. With the developed microfluidic chip, tumor cells are sieved from blood on the basis of size discrepancy. To enable multiplex phenotypic analysis, three kinds of spectrally orthogonal SERS aptamer nanovectors are designed, providing individual cells with composite spectral signatures in accordance with surface protein expression. Next, to statistically demultiplex the complex SERS signature and profile the cellular proteomic phenotype, a revised classic least square algorithm is employed to obtain the 3D phenotypic information at single‐cell resolution. Combined with categorization algorithm partial least square discriminate analysis, cells from different human breast cancer subtypes can be reliably classified with high sensitivity and selectivity. The results demonstrate that this platform can identify cancer subtypes with the spectral information correlated to the clinically relevant surface receptors, which holds great potential for clinical cancer diagnosis and precision medicine.
For in situ profiling of cell membrane proteins and identification of cancer subpopulations, an on‐chip strategy that combines size‐based microfluidic cell isolation with multiple spectrally orthogonal surface‐enhanced Raman spectroscopy (SERS) analysis is proposed. Employing multivariate spectral analysis, the 3D phenotypic information and corresponding subtype of captured circulating tumor cells can be readily obtained according to their composite SERS signatures.</abstract><cop>Germany</cop><pub>Wiley Subscription Services, Inc</pub><pmid>29665274</pmid><doi>10.1002/smll.201704433</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-4648-2506</orcidid></addata></record> |
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subjects | Algorithms Cancer circulating tumor cells Diagnosis Genotype & phenotype Least squares Medical diagnosis microfluidics Molecular chains Multiplexing Multivariate analysis Nanotechnology phenotypes Proteins Receptors SERS Spectra Spectral signatures Tumors |
title | Combining Multiplex SERS Nanovectors and Multivariate Analysis for In Situ Profiling of Circulating Tumor Cell Phenotype Using a Microfluidic Chip |
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