journal article·2024-10-22

GlycoSS: A DNA Glycosignal Sieve for Deciphering Spatially Resolved EpCAM-Specific Glycoforms

Ningke Fan, Ketong Yang, Xintong Bian, Yirong Chen, Lu Zhang, Zhujun Ai, Xinyu Li, Shijia Ding, Siqiao Li, Wei Cheng

ACS Nano· Volume 18· Issue 42
Publisher page

Abstract

Malignant transformation of cancer is often accompanied by aberrant glycopatterns. Epithelial–mesenchymal transition (EMT) is a crucial biological process in cancer migration and invasion, accelerating cancer deterioration. High-precision analysis of protein–glycan spatial profiling in the EMT process is essential for elucidating glycosylation functions and cancer progression. However, the diversity of glycans in composition and conformation complicates their spatial analysis. Here, we develop a DNA glycosignal sieve (GlycoSS) visualization platform for screening glycoform expression with a protein spatial dimension. GlycoSS utilizes protein-anchored DNA nanoscanners of distinct lengths to control glycosignal readout, enabling protein–glycan distance modulations, and simultaneously orthogonally amplify glycoform output through signal amplification by an exchange reaction. Using GlycoSS, we screened EpCAM-specific hypoglycosylated glycoform signals in different breast cancer cell subtypes, especially characterizing the spatial distribution of glycans on the MCF-7 cell surface. Considering that the EpCAM-specific N -glycan dysregulation in EMT is pivotal, GlycoSS revealed dynamic glycan fluctuations during IGF-1-induced EMT, revealing that the N -glycans were positively associated with tumor malignancy and metastasis. GlycoSS is anticipated to accelerate the identification of aberrant N -glycosylation in tumor progression, advancing systemic glycobiology insights. Notably, GlycoSS is capable of analyzing diverse glycoprotein profiles, offering additional dimensions into the role of glycoprotein nanoenvironments in regulating membrane protein function.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced biosensing and bioanalysis techniques · RNA and protein synthesis mechanisms · Genomics and Chromatin Dynamics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing 400016, China

Department of Laboratory Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China

School of Basic Medical Sciences, Chongqing Medical University, Chongqing 400016, China

The Center for Clinical Molecular Medical Detection, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China

Funding

Chongqing Municipal Education Commission · Natural Science Foundation of Chongqing Municipality · Chongqing Medical University · Science Fund for Distinguished Young Scholars of Chongqing Municipality · National Natural Science Foundation of China · Chongqing Talents-Innovation Leading Talents Project · Foundation for Innovative Research Groups of Chongqing Higher Education Institutions · Chongqing Postgraduate Research and Innovation Project

References (51)

Show source-provided references
1. 10.1021/acs.accounts.7b0061710.1021/acs.accounts.7b00617 ↗
2. 10.1038/nmat349210.1038/nmat3492 ↗
3. 10.1038/s41592-021-01209-010.1038/s41592-021-01209-0 ↗
4. 10.1021/acs.chemrev.7b0073210.1021/acs.chemrev.7b00732 ↗
5. 10.1038/s41592-020-0967-910.1038/s41592-020-0967-9 ↗
6. 10.1038/s41467-017-00535-210.1038/s41467-017-00535-2 ↗
7. 10.1038/nmeth.317910.1038/nmeth.3179 ↗
8. 10.1038/nbt.420110.1038/nbt.4201 ↗
9. 10.1038/s42003-020-0758-y10.1038/s42003-020-0758-y ↗
10. 10.1016/j.cell.2017.03.02810.1016/j.cell.2017.03.028 ↗
11. 10.1038/s41467-019-08288-w10.1038/s41467-019-08288-w ↗
12. 10.1016/j.molcel.2014.06.00310.1016/j.molcel.2014.06.003 ↗
13. 10.1021/ac501690v10.1021/ac501690v ↗
14. 10.1016/j.cell.2023.05.04410.1016/j.cell.2023.05.044 ↗
15. 10.1038/s41568-023-00596-010.1038/s41568-023-00596-0 ↗
16. 10.1038/s41592-023-01880-510.1038/s41592-023-01880-5 ↗
17. 10.1038/s41586-023-05914-y10.1038/s41586-023-05914-y ↗
18. 10.1073/pnas.200920611710.1073/pnas.2009206117 ↗
19. 10.1021/jacs.2c1115010.1021/jacs.2c11150 ↗
20. 10.1038/s41592-020-01010-510.1038/s41592-020-01010-5 ↗
21. 10.1007/978-1-4939-9537-0_110.1007/978-1-4939-9537-0_1 ↗
22. 10.1021/acs.analchem.1c0414810.1021/acs.analchem.1c04148 ↗
23. 10.1016/j.bios.2016.08.00310.1016/j.bios.2016.08.003 ↗
24. 10.1021/jacs.3c0262510.1021/jacs.3c02625 ↗
25. 10.1093/nar/gkab117810.1093/nar/gkab1178 ↗
26. 10.1002/INMD.2023004610.1002/INMD.20230046 ↗
27. 10.1016/j.bios.2017.05.02710.1016/j.bios.2017.05.027 ↗
28. 10.1016/j.bios.2017.04.00510.1016/j.bios.2017.04.005 ↗
29. 10.1038/s41587-019-0207-y10.1038/s41587-019-0207-y ↗
30. 10.1038/s41592-019-0404-010.1038/s41592-019-0404-0 ↗
31. 10.1002/adma.20190841010.1002/adma.201908410 ↗
32. 10.1021/acs.analchem.2c0176210.1021/acs.analchem.2c01762 ↗
33. 10.1038/nchem.287210.1038/nchem.2872 ↗
34. 10.1002/anie.20201064810.1002/anie.202010648 ↗
35. 10.1002/jev2.1236410.1002/jev2.12364 ↗
36. 10.1002/anie.20230702510.1002/anie.202307025 ↗
37. 10.1016/S0304-3835(03)00003-X10.1016/S0304-3835(03)00003-X ↗
38. 10.1002/jcp.2925210.1002/jcp.29252 ↗
39. 10.1002/jcp.2725610.1002/jcp.27256 ↗
40. 10.2741/307510.2741/3075 ↗
41. 10.1039/C5SC03560K10.1039/C5SC03560K ↗
42. 10.1002/hep.3217810.1002/hep.32178 ↗
43. 10.1002/path.437510.1002/path.4375 ↗
44. 10.1073/pnas.202283011810.1073/pnas.2022830118 ↗
45. 10.3390/cancers1006020710.3390/cancers10060207 ↗
46. 10.3390/toxins1311079210.3390/toxins13110792 ↗
47. 10.1371/journal.pone.020951510.1371/journal.pone.0209515 ↗
48. 10.1016/j.ccell.2023.01.00710.1016/j.ccell.2023.01.007 ↗
49. 10.1038/s41586-023-06372-210.1038/s41586-023-06372-2 ↗
50. 10.1016/S1470-2045(21)00343-010.1016/S1470-2045(21)00343-0 ↗
51. 10.1186/1478-811X-9-1010.1186/1478-811X-9-10 ↗