journal article·2024-04-08

Formation Pattern Analysis of Spheroids Formed by a Droplet-Based Microfluidic System for Predicting the Aggressiveness of Tumor Cells

Sunghan Lee, Chang Jae Woo, Hyo-Il Jung, Ki Chang Nam, Ji Seok Lim, Bong Seop Kwak

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Abstract

Examining tumor heterogeneity is essential for selecting an appropriate anticancer treatment for an individual. This study aimed to distinguish low- and high-aggressive tumor cells by analyzing the formation patterns of spheroids. The droplet-based microfluidic system was employed for the formation of each spheroid from four different subtypes of breast tumor cells. Additionally, heterotypic spheroids with T lymphocytes and cancer-associated fibroblasts (CAFs) were produced, and distinctions between low- and high-aggressive tumor cells were explored through the analysis of formation patterns using circularity, convexity, and cell distributions. In both homotypic spheroids and heterotypic spheroids with T lymphocytes, spheroids formed from low-aggressive tumor cells exhibited high circularity and convexity. On the other hand, spheroids formed from high-aggressive tumor cells had relatively low circularity and convexity. In the case of heterotypic spheroids with CAFs, circularity and convexity did not exhibit clear differences between low- and high-aggressive tumor cells, but distinct variations were observed in cell distributions. CAFs and low-aggressive tumor cells were evenly distributed, whereas the CAFs were predominantly located in the inner layer, and high-aggressive tumor cells were primarily located in the outer layer. This finding can offer valuable insights into predicting the aggressiveness of unknown tumor cells.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Cancer Cells and Metastasis · 3D Printing in Biomedical Research · Cancer Genomics and Diagnostics

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

Affiliations

School of Mechanical Engineering, Yonsei University, 50 Yonsei-ro, Seadaemun-gu, Seoul 03722, Republic of Korea

College of Medicine, Dongguk University, 32 Dongguk-ro, Ilsandong-gu, Goyangsi 10326, Gyeonggi-do, Republic of Korea

National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang-si 10408, Gyeonggi-do, Republic of Korea

The DABOM Inc., Seodaemun-gu, Seoul 03722, Republic of Korea

School of Mechanical Engineering, Yeungnam University, 280 Daehak-ro, Gyeongsan-si 38541, Gyeongsanbuk-do, Republic of Korea

MediSphere Inc., Gyeongsan-si 38541, Gyeongsanbuk-do, Republic of Korea

Funding

Dongguk University · Ministry of Science, ICT and Future Planning

References (45)

Show source-provided references
1. 10.21037/atm-21-194810.21037/atm-21-1948 ↗
2. 10.1038/s41598-017-18965-910.1038/s41598-017-18965-9 ↗
3. 10.3892/mmr.2017.760810.3892/mmr.2017.7608 ↗
4. 10.1007/s13206-022-00067-y10.1007/s13206-022-00067-y ↗
5. 10.1007/s13577-021-00642-910.1007/s13577-021-00642-9 ↗
6. 10.1007/s13206-022-00086-910.1007/s13206-022-00086-9 ↗
7. 10.1016/j.jconrel.2012.04.04510.1016/j.jconrel.2012.04.045 ↗
8. 10.1016/j.tibtech.2004.02.00210.1016/j.tibtech.2004.02.002 ↗
9. 10.1007/s12079-018-0498-710.1007/s12079-018-0498-7 ↗
10. 10.1517/14712598.2012.70718110.1517/14712598.2012.707181 ↗
11. 10.1038/am.2016.13010.1038/am.2016.130 ↗
12. 10.1186/s12935-021-01853-810.1186/s12935-021-01853-8 ↗
13. 10.1016/j.bios.2023.11578710.1016/j.bios.2023.115787 ↗
14. 10.1016/j.jconrel.2018.02.02910.1016/j.jconrel.2018.02.029 ↗
15. 10.1007/s13206-020-4201-810.1007/s13206-020-4201-8 ↗
16. 10.1242/jcs.11639210.1242/jcs.116392 ↗
17. Ikeda H. · Nihon Rinsho · 2012 · 70 · 2043
18. 10.1016/j.addr.2015.07.00710.1016/j.addr.2015.07.007 ↗
19. 10.1038/s41417-021-00318-410.1038/s41417-021-00318-4 ↗
20. 10.18632/oncotarget.765910.18632/oncotarget.7659 ↗
21. 10.1038/srep1910310.1038/srep19103 ↗
22. 10.1177/11782234100040000410.1177/117822341000400004 ↗
23. Hajra K. M. · Cancer Res. · 2002 · 62 · 1613
24. 10.1371/journal.pone.007728110.1371/journal.pone.0077281 ↗
25. 10.3121/cmr.2009.82510.3121/cmr.2009.825 ↗
26. 10.1038/s41586-019-1526-310.1038/s41586-019-1526-3 ↗
27. 10.4297/najms.2011.322710.4297/najms.2011.3227 ↗
28. 10.1016/j.bios.2020.11256410.1016/j.bios.2020.112564 ↗
29. 10.7150/jca.1845710.7150/jca.18457 ↗
30. 10.3892/ijo.2017.412810.3892/ijo.2017.4128 ↗
31. 10.3390/jcm1204137510.3390/jcm12041375 ↗
32. 10.1002/smll.20170285810.1002/smll.201702858 ↗
33. 10.1016/S0012-1606(02)00016-710.1016/S0012-1606(02)00016-7 ↗
34. 10.1038/srep4116010.1038/srep41160 ↗
35. 10.1038/s41598-017-10078-710.1038/s41598-017-10078-7 ↗
36. 10.1073/pnas.160844811410.1073/pnas.1608448114 ↗
37. 10.3389/fcell.2020.0001710.3389/fcell.2020.00017 ↗
38. 10.1186/bcr314810.1186/bcr3148 ↗
39. 10.1007/s00262-008-0594-210.1007/s00262-008-0594-2 ↗
40. 10.1016/j.coi.2021.09.00510.1016/j.coi.2021.09.005 ↗
41. 10.3892/ol.2019.997310.3892/ol.2019.9973 ↗
42. 10.1038/s41571-023-00781-y10.1038/s41571-023-00781-y ↗
43. 10.1093/bioinformatics/btab58110.1093/bioinformatics/btab581 ↗
44. 10.1093/gigascience/giad08210.1093/gigascience/giad082 ↗
45. 10.1038/s41598-018-25337-410.1038/s41598-018-25337-4 ↗