Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning Strategy
Ovarian cancer survival depends strongly on the time of diagnosis. Detection at stage 1 must be the goal of liquid biopsies for ovarian cancer detection. We report the development and validation of graphene-based optical nanobiosensors (G-NBSs) that quantify the activities of a panel of proteases, w...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Cells |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4409/14/5/375 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850225630090625024 |
|---|---|
| author | Obdulia Covarrubias-Zambrano Deepesh Agarwal Joan Lewis-Wambi Raul Neri Andrea Jewell Balasubramaniam Natarajan Stefan H. Bossmann |
| author_facet | Obdulia Covarrubias-Zambrano Deepesh Agarwal Joan Lewis-Wambi Raul Neri Andrea Jewell Balasubramaniam Natarajan Stefan H. Bossmann |
| author_sort | Obdulia Covarrubias-Zambrano |
| collection | DOAJ |
| description | Ovarian cancer survival depends strongly on the time of diagnosis. Detection at stage 1 must be the goal of liquid biopsies for ovarian cancer detection. We report the development and validation of graphene-based optical nanobiosensors (G-NBSs) that quantify the activities of a panel of proteases, which were selected to provide a crowd response that is specific for ovarian cancer. These G-NBSs consist of few-layer explosion graphene featuring a hydrophilic coating, which is linked to fluorescently labeled highly selective consensus sequences for the proteases of interest, as well as a fluorescent dye. The panel of G-NBSs showed statistically significant differences in protease activities when comparing localized (early-stage) ovarian cancer with both metastatic (late-stage) and healthy control groups. A hierarchical framework integrated with active learning (AL) as a prediction and analysis tool for early-stage detection of ovarian cancer was implemented, which obtained an overall accuracy score of 94.5%, with both a sensitivity and specificity of 0.94. |
| format | Article |
| id | doaj-art-c3307e1a1e904a8bba59fc2dcfbb0e99 |
| institution | OA Journals |
| issn | 2073-4409 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cells |
| spelling | doaj-art-c3307e1a1e904a8bba59fc2dcfbb0e992025-08-20T02:05:17ZengMDPI AGCells2073-44092025-03-0114537510.3390/cells14050375Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning StrategyObdulia Covarrubias-Zambrano0Deepesh Agarwal1Joan Lewis-Wambi2Raul Neri3Andrea Jewell4Balasubramaniam Natarajan5Stefan H. Bossmann6Department of Cancer Biology, University of Kansas Medical Center, Kansas City, KS 66160, USADepartment of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506, USADepartment of Cancer Biology, University of Kansas Medical Center, Kansas City, KS 66160, USADepartment of Cancer Biology, University of Kansas Medical Center, Kansas City, KS 66160, USADepartment of Obstetrics and Gynecology, University of Kansas Medical Center, Kansas City, KS 66160, USADepartment of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506, USADepartment of Cancer Biology, University of Kansas Medical Center, Kansas City, KS 66160, USAOvarian cancer survival depends strongly on the time of diagnosis. Detection at stage 1 must be the goal of liquid biopsies for ovarian cancer detection. We report the development and validation of graphene-based optical nanobiosensors (G-NBSs) that quantify the activities of a panel of proteases, which were selected to provide a crowd response that is specific for ovarian cancer. These G-NBSs consist of few-layer explosion graphene featuring a hydrophilic coating, which is linked to fluorescently labeled highly selective consensus sequences for the proteases of interest, as well as a fluorescent dye. The panel of G-NBSs showed statistically significant differences in protease activities when comparing localized (early-stage) ovarian cancer with both metastatic (late-stage) and healthy control groups. A hierarchical framework integrated with active learning (AL) as a prediction and analysis tool for early-stage detection of ovarian cancer was implemented, which obtained an overall accuracy score of 94.5%, with both a sensitivity and specificity of 0.94.https://www.mdpi.com/2073-4409/14/5/375graphene-based nanobiosensorsbiomarkersliquid biopsyovarian cancer detectionprotease activitybiophotonics |
| spellingShingle | Obdulia Covarrubias-Zambrano Deepesh Agarwal Joan Lewis-Wambi Raul Neri Andrea Jewell Balasubramaniam Natarajan Stefan H. Bossmann Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning Strategy Cells graphene-based nanobiosensors biomarkers liquid biopsy ovarian cancer detection protease activity biophotonics |
| title | Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning Strategy |
| title_full | Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning Strategy |
| title_fullStr | Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning Strategy |
| title_full_unstemmed | Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning Strategy |
| title_short | Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning Strategy |
| title_sort | few layer graphene based optical nanobiosensors for the early stage detection of ovarian cancer using liquid biopsy and an active learning strategy |
| topic | graphene-based nanobiosensors biomarkers liquid biopsy ovarian cancer detection protease activity biophotonics |
| url | https://www.mdpi.com/2073-4409/14/5/375 |
| work_keys_str_mv | AT obduliacovarrubiaszambrano fewlayergraphenebasedopticalnanobiosensorsfortheearlystagedetectionofovariancancerusingliquidbiopsyandanactivelearningstrategy AT deepeshagarwal fewlayergraphenebasedopticalnanobiosensorsfortheearlystagedetectionofovariancancerusingliquidbiopsyandanactivelearningstrategy AT joanlewiswambi fewlayergraphenebasedopticalnanobiosensorsfortheearlystagedetectionofovariancancerusingliquidbiopsyandanactivelearningstrategy AT raulneri fewlayergraphenebasedopticalnanobiosensorsfortheearlystagedetectionofovariancancerusingliquidbiopsyandanactivelearningstrategy AT andreajewell fewlayergraphenebasedopticalnanobiosensorsfortheearlystagedetectionofovariancancerusingliquidbiopsyandanactivelearningstrategy AT balasubramaniamnatarajan fewlayergraphenebasedopticalnanobiosensorsfortheearlystagedetectionofovariancancerusingliquidbiopsyandanactivelearningstrategy AT stefanhbossmann fewlayergraphenebasedopticalnanobiosensorsfortheearlystagedetectionofovariancancerusingliquidbiopsyandanactivelearningstrategy |