Abstract

   Microgravity in space impacts human health. In particular, thyroid
   cancer, which has a high incidence rate, has been the subject of
   numerous studies with respect to microgravity. However, most studies
   have focused on Western follicular thyroid cancer cell lines, while
   data regarding the effects of microgravity on Asian cell lines are
   lacking. Therefore, we aimed to investigate the effect of simulated
   ground-based microgravity on two Korean thyroid cancer cell lines,
   namely SNU-790 and SNU-80. We found that both cell lines formed
   multicellular spheroids under simulated microgravity. Gene expression
   analysis revealed that in SNU-790 cells, histone-related genes were
   upregulated and microRNA-related genes were downregulated. Meanwhile,
   in SNU-80 cells, genes related to the cellular response to hypoxia were
   downregulated. These findings contribute to a better understanding of
   the effects of microgravity on thyroid cancer cells. Further validation
   studies and clinical significance analyses are needed to fully
   understand the implications of these findings.

   Subject terms: Cancer genetics, Thyroid cancer

Introduction

   Since the advent of space travel on April 12, 1961, extensive space
   exploration has been conducted^[32]1. The space environment is unique
   with microgravity and cosmic radiation, which cause damage and
   structural changes at the molecular and cellular levels, resulting in
   pathological conditions^[33]2. The effects of microgravity on various
   biological processes, including cell differentiation, proliferation,
   growth, apoptosis, adhesion, migration, invasion, and metastasis, have
   been studied^[34]2–[35]4. In particular, cells exposed to microgravity
   form three-dimensional aggregates known as multicellular spheroids
   (MCSs) because of alterations in the cytoskeleton and extracellular
   matrix^[36]1,[37]3.

   Despite advancements in medical science, definitive strategies for
   cancer prevention and treatment remain elusive^[38]5. Numerous studies
   have reported the inhibitory effects of microgravity on the growth and
   viability of cancer cells^[39]3–[40]5. As such, the microgravity
   environment holds potential as a novel therapeutic strategy for
   cancer^[41]5. In particular, owing to the steadily increasing incidence
   of thyroid cancer, research on its characteristics under microgravity
   environments has been actively conducted^[42]6. In fact, MCSs have been
   reported within normal thyroid cell and thyroid cancer cell cultures
   under microgravity^[43]3,[44]4,[45]7,[46]8. Moreover, in thyroid cancer
   cell cultures under microgravity, the expression of B cell lymphoma-1
   (BCL-2)—an antiapoptotic protein—and proinflammatory cytokines,
   including interleukin (IL)-6, IL-7, and IL-17, is
   upregulated^[47]5,[48]9. Under zero gravity conditions, the
   cytoskeleton of thyroid cancer cells also undergoes disintegration,
   accompanied by upregulated vimentin expression and increased production
   of extracellular matrix proteins^[49]10.

   However, thyroid cancer cells used in most zero gravity-related studies
   are follicular thyroid cancer (FTC) cells, whereas studies with
   papillary thyroid cancer (PTC) cells are rare^[50]3,[51]8,[52]10. Most
   microgravity studies using thyroid cells have been conducted using
   cells obtained from Westerns (Nthy-ori 3-1, HTU 5, FTC-133, UCLA
   RO82-W-1, and ONCO-DG1), while no such study exists using thyroid cells
   derived from Asians^[53]11–[54]15. In 2007, Koh et al. established
   SNU-790 and SNU-80 cells derived from Korean breast cancer and
   papillary thyroid cancer, respectively. They reported on the
   characteristics of these cells and demonstrated that these
   characteristics were maintained even after numerous passages^[55]16.
   This study aims to characterize the Korean-derived thyroid cancer
   cells, SNU-790 and SNU80, cultured under simulated microgravity
   conditions^[56]16.

Results

MCS formation

   Figures [57]1 and [58]2 show changes over time in the morphology and
   number of SNU-790 and SNU-80 cells cultured under simulated
   microgravity and normal gravity (1 G) conditions. Adherent SNU-790
   cells were identified as elongated spindle epithelial cells. Over time,
   adherent SNU-790 cells became densely cultured. SNU-790 cells began to
   form three-dimensional aggregates after 24 h of incubation under
   simulated microgravity. At 48 h and 72 h, slightly larger cellular
   aggregates were observed, and by 120 h, MCSs were discovered. In
   contrast, SNU-790 cells cultured under normal gravity conditions only
   displayed a two-dimensional structure with adherent cells. Meanwhile,
   adherent SNU-80 cells were observed as polygonal epithelial cells with
   large, round nuclei. These cells reached confluence over time. The
   formation of MCSs was observed in SNU-80 cells after 24-hour incubation
   under simulated microgravity, with the number of MCSs increasing over
   time. However, no MCSs were observed in SNU-80 cells cultured under
   1 G.

Fig. 1. Phase-contrast microscopy images of SNU-790 under normal gravity and
simulated microgravity conditions after 24 h, 48 h, 72 h, and 120 h of
treatment.

   [59]Fig. 1
   [60]Open in a new tab

   1 G, normal gravity, 0 G simulated microgravity.

Fig. 2. Phase-contrast microscopy images of SNU-80 under normal gravity and
simulated microgravity conditions after 24 h, 48 h, 72 h, and 120 h of
treatment.

   [61]Fig. 2
   [62]Open in a new tab

   1 G, normal gravity, 0 G simulated microgravity.

Altered gene expression in SNU-790 cells

   Differentially expressed gene (DEG) analysis in SNU-790 cells revealed
   1014 DEGs under simulated microgravity compared with those under 1 G
   conditions. Of these, 306 were upregulated and 708 were downregulated
   (Fig. [63]3). Moreover, heatmap and principal component analysis (PCA)
   results showed that SNU-790 cultured in simulated microgravity
   exhibited transcriptional profiles distinct from those of cells
   cultured under 1 G (Fig. [64]3).

Fig. 3. Analysis of differentially expressed genes in SNU-790 and SNU-80
cells under simulated microgravity conditions compared to those under normal
gravity.

   [65]Fig. 3
   [66]Open in a new tab

   (A) Number of differentially expressed genes; (B) volcano plot; (C)
   heatmap; (D) principal component analysis. In (b), (c), and (d), left
   panels represent SNU-790, right panels represent SNU-80.

   Figure [67]4 and Table [68]1 summarize the results of KEGG pathway and
   Gene Ontology (GO) enrichment analyses conducted on SNU-790 cells
   cultured under simulated microgravity conditions. The DEGs identified
   in SNU-790 cells were associated with 44 KEGG pathways. Among the top
   20 pathways analyzed, systemic lupus erythematosus (ID:05322),
   alcoholism (ID:05034), neutrophil extracellular trap formation
   (ID:04613), necroptosis (ID:04217), shigellosis (ID:05131), and viral
   carcinogenesis (ID:05203) were observed to express more
   histone-cluster-related genes than other genes. Moreover, a total of 32
   GO biological process (GO:BP) terms, 3 GO molecular function (GO:MF)
   terms, and 5 GO cellular component (GO:CC) terms were enriched.
   Protein-DNA complex subunit organization (GO:BP, GO:0071824), chromatin
   remodeling (GO:BP, GO:0006338), protein heterodimerization activity
   (GO:MF, GO:0046982), and nucleosome (GO:CC, GO:0000786), as well as
   similar terms were related to the overexpression of genes related to
   the histone cluster. Meanwhile, analysis of DEGs in SNU-790 cells
   cultured under simulated microgravity conditions revealed an
   overexpression of genes associated with histone clusters: HIST1H3G
   (fold change [FC] 3.286, adjusted P value [adj. P] < 0.001), HIST1H3B
   (FC 3.066, adj. P < 0.001), HISTH2AB (FC 2.555, adj. P < 0.001),
   HIST1H1B (FC 2.382, adj. P < 0.001), HIST1H2AI (FC 2.140, adj.
   P < 0.001), and HIST1H1E (FC 2.072, adj. P < 0.001; Table [69]2).

Fig. 4. Functional annotation analysis of differentiallyexpressed genes in
SNU-790 Cells under simulated microgravity conditions.

   [70]Fig. 4
   [71]Open in a new tab

   A Top 20 KEGG Pathways Enrichment Analysis, B GeneOntology enrichment
   analysis of Biological Processes, C GeneOntology enrichment analysis of
   Molecular Function, and D GeneOntology enrichment analysis of Cellular
   Component.

Table 1.

   KEGG pathway analysis and Gene Ontology enrichment analysis of
   differentially expressed genes in SNU-790 cells cultured under
   simulated microgravity conditions.
   No. Gene symbol Fold change Adjusted P value Gene description
   (A) Top five KEGG pathways associated with histone-related genes
   (A-a) Systemic lupus erythematosus (ID 05322, FDR <0.001)
   1 HIST1H3G 3.286 <0.001 Histone cluster 1, h3g
   2 HIST1H3B 3.066 <0.001 Histone cluster 1, h3b
   3 HIST2H2AB 2.555 <0.001 Histone cluster 2, h2ab
   4 HIST1H2AI 2.140 <0.001 Histone cluster 1, h2ai
   5 HIST1H2AM 3.286 <0.001 Histone cluster 1, h2am
   6 HIST1H2BG −1.513 <0.001 Histone cluster 1, h2bg
   7 HIST1H2AK −1.615 <0.001 Histone cluster 1, h2ak
   8 HIST2H2BF −1.679 0.005 Histone cluster 2, h2bf
   9 C4A −2.095 <0.001 Complement component 4A (Rodgers blood group)
   10 C4B −2.130 <0.001 Complement component 4B (Chido blood group)
   (A-b) Alcoholism (ID 05034, FDR <0.001)
   1 HIST1H3G 3.286 <0.001 Histone cluster 1, h3g
   2 HIST1H3B 3.066 <0.001 Histone cluster 1, h3b
   3 HIST2H2AB 2.555 <0.001 Histone cluster 2, h2ab
   4 HIST1H2AI 2.140 <0.001 Histone cluster 1, h2ai
   5 HIST1H2AM 1.981 0.003 Histone cluster 1, h2am
   6 HIST1H2BG −1.513 <0.001 Histone cluster 1, h2bg
   7 HIST1H2AK −1.615 <0.001 Histone cluster 1, h2ak
   8 HIST2H2BF −1.679 0.005 Histone cluster 2, h2bf
   9 GNAI3 −2.572 <0.001 Guanine nucleotide-binding protein (G protein),
   alpha inhibiting activity polypeptide 3
   (A-c) Neutrophil extracellular trap formation (ID 04613, FDR <0.001)
   1 HIST1H3G 3.286 <0.001 Histone cluster 1, h3g
   2 HIST1H3B 3.066 <0.001 Histone cluster 1, h3b
   3 HIST2H2AB 2.555 <0.001 Histone cluster 2, h2ab
   4 HIST1H2AI 2.140 <0.001 Histone cluster 1, h2ai
   5 HIST1H2AM 1.981 0.003 Histone cluster 1, h2am
   6 HIST1H2BG −1.513 <0.001 Histone cluster 1, h2bg
   7 HIST1H2AK −1.615 <0.001 Histone cluster 1, h2ak
   8 HIST2H2BF −1.679 0.005 Histone cluster 2, h2bf
   9 SELP −1.888 0.004 Selectin P (granule membrane protein 140 kda,
   antigen CD62)
   (A-d) Necroptosis (ID:04217, FDR < 0.001)
   1 HIST2H2AB 2.555 0.000 Histone cluster 2, h2ab
   2 HIST1H2AI 2.140 0.000 Histone cluster 1, h2ai
   3 HIST1H2AM 1.981 0.003 Histone cluster 1, h2am
   4 FADD 1.864 0.000 Fas (TNFRSF6)-associated via death domain
   5 IL33 1.802 0.000 Interleukin 33
   6 TRAF5 −1.524 0.002 TNF receptor-associated factor 5
   7 HIST1H2AK −1.615 0.000 Histone cluster 1, h2ak
   (A-e) Shigellosis (ID:05131, FDR <0.001)
   1 HIST1H3G 3.286 0.000 Histone cluster 1, h3g
   2 HIST1H3B 3.066 0.000 Histone cluster 1, h3b
   3 CXCL8 2.417 0.000 Chemokine (C-X-C motif) ligand 8
   4 HIST2H3A 1.809 0.000 Histone cluster 2, h3a
   5 HIST2H3A 1.809 0.000 Histone cluster 2, h3a
   6 ACTR3B −1.516 0.009 ARP3 actin-related protein 3 homolog B (yeast)
   7 TRAF5 −1.524 0.002 TNF receptor-associated factor 5
   8 NAIP −1.561 0.000 NLR family, apoptosis inhibitory protein
   9 SEPT11 −1.705 0.000 Septin 11
   10 NAIP −1.766 0.000 NLR family, apoptosis inhibitory protein
   (A-f) Viral carcinogenesis (ID:05203)
   1 HIST1H4C 1.819 0.000 Histone cluster 1, h4c
   2 HIST1H2BB 1.787 0.011 Histone cluster 1, h2bb
   3 HIST1H4D 1.729 0.000 Histone cluster 1, h4d
   4 CDK1 1.638 0.000 Cyclin-dependent kinase 1
   5 HIST1H4K 1.539 0.000 Histone cluster 1, h4k
   6 HIST1H2BG −1.513 0.000 Histone cluster 1, h2bg
   7 TRAF5 −1.524 0.002 TNF receptor-associated factor 5
   8 HIST2H2BF −1.679 0.005 Histone cluster 2, h2bf
   9 GTF2H2 −1.882 0.000 General transcription factor IIH subunit 2
   (B) Top five KEGG pathways associated with microRNA-related genes
   (B-a) MicroRNAs in cancer (ID 05206, FDR< 0.001)
   1 MIR520E 2.017 0.001 MicroRNA 520e
   2 MIR146A 1.610 <0.001 MicroRNA 146a
   3 MIRLET7C −2.101 <0.001 MicroRNA let-7c
   4 MIRLET7F1 −2.151 0.001 MicroRNA let-7f-1
   5 ZEB2 −2.281 <0.001 Zinc finger E-box binding homeobox 2
   6 MIR222 −2.549 <0.001 MicroRNA 222
   7 MIRLET7A2 −2.835 <0.001 MicroRNA let-7a-2
   (C) Top five Gene Ontology enrichment terms associated with
   histone-related genes
   (C-a) Protein-DNA complex subunit organization (GO:BP, GO:0071824, adj.
   P <0.001)
   1 HIST1H3G 3.286 <0.001 Histone cluster 1, h3g
   2 HIST1H3B 3.066 <0.001 Histone cluster 1, h3b
   3 HIST1H1B 2.382 <0.001 Histone cluster 1, h1b
   4 HIST1H1E 2.072 <0.001 Histone cluster 1, h1e
   5 HIST1H4C 1.819 <0.001 Histone cluster 1, h4c
   6 HIST1H2BG −1.513 <0.001 Histone cluster 1, h2bg
   7 CHAF1B −1.633 0.005 Chromatin assembly factor 1, subunit B (p60)
   8 HIST2H2BF −1.679 0.005 Histone cluster 2, h2bf
   9 CHAF1B −1.749 0.040 Chromatin assembly factor 1, subunit B (p60)
   (C-b) Protein-DNA complex assembly (GO:BP, GO:0065004, adj. P < 0.001)
   1 HIST1H3G 3.286 <0.001 Histone cluster 1, h3g
   2 HIST1H3B 3.066 <0.001 Histone cluster 1, h3b
   3 HIST1H1B 2.382 <0.001 Histone cluster 1, h1b
   4 HIST1H1E 2.072 <0.001 Histone cluster 1, h1e
   5 HIST1H4C 1.819 <0.001 Histone cluster 1, h4c
   6 HIST1H2BG −1.513 <0.001 Histone cluster 1, h2bg
   7 CHAF1B −1.633 0.005 Chromatin assembly factor 1, subunit B (p60)
   8 HIST2H2BF −1.679 0.005 Histone cluster 2, h2bf
   9 CHAF1B −1.749 0.040 Chromatin assembly factor 1, subunit B (p60)
   (C-c) Chromatin remodeling (GO:BP, GO:0006338, adj. P = 0.002)
   1 HIST1H3G 3.286 <0.001 Histone cluster 1, h3g
   2 HIST1H3B 3.066 <0.001 Histone cluster 1, h3b
   3 HIST1H1B 2.382 <0.001 Histone cluster 1, h1b
   4 HIST1H1E 2.072 <0.001 Histone cluster 1, h1e
   5 HIST1H4C 1.819 <0.001 Histone cluster 1, h4c
   6 PABPC1L −1.627 0.001 Poly(A) binding protein, cytoplasmic 1-like
   7 CHAF1B −1.633 0.005 Chromatin assembly factor 1, subunit B (p60)
   8 HIST2H2BF −1.679 0.005 Histone cluster 2, h2bf
   9 CHAF1B −1.749 0.040 Chromatin assembly factor 1, subunit B (p60)
   10 KDM4C −1.889 0.001 Lysine (K)-specific demethylase 4C
   (C-d) Protein heterodimerization activity (GO:MF, GO:0046982, adj. P =
   0.001)
   1 HIST1H3G 3.286 0.000 Histone cluster 1, h3g
   2 HIST1H3B 3.066 0.000 Histone cluster 1, h3b
   3 HIST2H2AB 2.555 0.000 Histone cluster 2, h2ab
   4 HIST1H2AI 2.140 0.000 Histone cluster 1, h2ai
   5 HIST1H2AM 1.981 0.003 Histone cluster 1, h2am
   6 HIST1H2BG −1.513 0.000 Histone cluster 1, h2bg
   7 HIST1H2AK −1.615 0.000 Histone cluster 1, h2ak
   8 TPM1 −1.623 0.000 Tropomyosin 1 (alpha)
   9 HIST2H2BF −1.679 0.005 Histone cluster 2, h2bf
   10 TENM4 −2.150 0.000 Teneurin transmembrane protein 4
   (C-e) Nucleosome (GO:CC, GO:0000786, adj. P < 0.001)
   1 HIST1H3G 3.286 0.000 Histone cluster 1, h3g
   2 HIST1H3B 3.066 0.000 Histone cluster 1, h3b
   3 HIST2H2AB 2.555 0.000 Histone cluster 2, h2ab
   4 HIST1H1B 2.382 0.000 Histone cluster 1, h1b
   5 HIST1H2AI 2.140 0.000 Histone cluster 1, h2ai
   6 HIST1H2BG −1.513 0.000 Histone cluster 1, h2bg
   7 HIST1H2AK −1.615 0.000 Histone cluster 1, h2ak
   8 HIST2H2BF −1.679 0.005 Histone cluster 2, h2bf
   (D) Top five Gene Ontology enrichment terms associated with
   microRNA-related genes
   (D-a) Gene silencing by miRNA (GO:BP, GO:0035195, adj. P < 0.001)
   1 MIR520E 2.017 0.001 MicroRNA 520e
   2 MIR519A2 1.905 0.022 MicroRNA 519a-2
   3 MIR196A1 1.868 0.023 MicroRNA 196a-1
   4 MIR328 1.616 0.003 MicroRNA 328
   5 MIR146A 1.610 0.000 MicroRNA 146a
   6 NEAT1 −2.311 0.000 Nuclear paraspeckle assembly transcript 1
   (non-protein coding)
   7 MIR573 −2.359 0.000 MicroRNA 573
   8 MIR604 −2.396 0.000 MicroRNA 604
   9 MIR222 −2.549 0.000 MicroRNA 222
   10 MIRLET7A2 −2.835 0.000 MicroRNA let-7a-2
   (D-b) Posttranscriptional gene silencing (GO:BP, GO:0035194, adj. P <
   0.001)
   1 MIR520E 2.017 0.001 MicroRNA 520e
   2 MIR519A2 1.905 0.022 MicroRNA 519a-2
   3 MIR196A1 1.868 0.023 MicroRNA 196a-1
   4 MIR328 1.616 0.003 MicroRNA 328
   5 MIR146A 1.610 0.000 MicroRNA 146a
   6 NEAT1 −2.311 0.000 Nuclear paraspeckle assembly transcript 1
   (non-protein coding)
   7 MIR573 −2.359 0.000 MicroRNA 573
   8 MIR604 −2.396 0.000 MicroRNA 604
   9 MIR222 −2.549 0.000 MicroRNA 222
   10 MIRLET7A2 −2.835 0.000 MicroRNA let-7a-2
   [72]Open in a new tab

   KEGG Kyoto Encyclopedia of Genes and Genomes, FDR false discovery rate,
   No number, GO gene ontology, BP biological process, adj.P adjusted P
   value, MF molecular function, CC cellular component.

   (Gene names are to be presented in italics).

Table 2.

   Comparative analysis of differentially expressed genes in SNU-790 cells
   cultured under simulated microgravity and normal gravity conditions.
   No. Gene symbol Fold change Adjusted P value Gene description
   (A) Top 20 upregulated genes in SNU-790 cells in simulated microgravity
   1 SNORA14A 6.173 <0.001 Small nucleolar RNA, H/ACA box 14A
   2 HIST1H3G 3.286 <0.001 Histone cluster 1, h3g
   3 TNFAIP6 3.223 <0.001 Tumor necrosis factor, alpha-induced protein 6
   4 HIST1H3B 3.066 <0.001 Histone cluster 1, h3b
   5 SNORA11 2.734 <0.001 Small nucleolar RNA, H/ACA box 11
   6 HIST2H2AB 2.555 <0.001 Histone cluster 2, h2ab
   7 CXCL8 2.417 <0.001 Chemokine (C-X-C motif) ligand 8
   8 HIST1H1B 2.382 <0.001 Histone cluster 1, h1b
   9 METRN 2.230 <0.001 Meteorin, glial cell differentiation regulator
   10 DNLZ 2.217 <0.001 DNL-type zinc finger
   11 SNORA38B 2.211 <0.001 Small nucleolar RNA, H/ACA box 38B
   12 C1QTNF1 2.201 <0.001 C1q and tumor necrosis factor related protein 1
   13 RNU5F-1 2.175 <0.001 RNA, U5F small nuclear 1
   14 MYDGF 2.152 <0.001 Myeloid-derived growth factor
   15 HIST1H2AI 2.140 <0.001 Histone cluster 1, h2ai
   16 SERPINB2 2.091 <0.001 Serpin peptidase inhibitor, clade B
   (ovalbumin), member 2
   17 TRAJ44 2.078 0.002 T cell receptor alpha joining 44
   18 HIST1H1E 2.072 <0.001 Histone cluster 1, h1e
   19 TUBA3C 2.037 <0.001 Tubulin, alpha 3c
   20 MT1JP 2.025 0.010 Metallothionein 1J, pseudogene
   (B) Top 20 downregulated genes in SNU-790 cells in simulated
   microgravity
   21 MIR4798 −3.437 <0.001 MicroRNA 4798
   22 MIR548K −3.234 <0.001 MicroRNA 548k
   23 MIR4762 −3.217 <0.001 MicroRNA 4762
   24 MIR548O2 −3.111 <0.001 MicroRNA 548o-2
   25 PCDHB13 −3.098 <0.001 Protocadherin beta 13
   26 MIR1284 −3.066 <0.001 MicroRNA 1284
   27 MIR4524A −2.925 <0.001 MicroRNA 4524a
   28 MIRLET7A2 −2.835 <0.001 MicroRNA let-7a-2
   29 SNORA31 −2.790 <0.001 Small nucleolar RNA, H/ACA box 31
   30 IFNE −2.779 <0.001 Interferon, epsilon
   31 PWAR6 −2.759 <0.001 Prader Willi/Angelman region RNA 6
   32 MIR4668 −2.672 <0.001 MicroRNA 4668
   33 SNORA16B −2.656 <0.001 Small nucleolar RNA, H/ACA box 16B
   34 TBC1D3E −2.650 <0.001 TBC1 domain family, member 3E
   35 RPS15AP10 −2.620 <0.001 Ribosomal protein S15a pseudogene 10
   36 MIR4742 −2.613 <0.001 MicroRNA 4742
   37 MIR4441 −2.607 <0.001 MicroRNA 4441
   38 MIR4500 −2.597 <0.001 MicroRNA 4500
   39 GLIS3 −2.589 <0.001 GLIS family zinc finger 3
   40 GNAI3 −2.572 <0.001 Guanine nucleotide binding protein (G protein),
   alpha inhibiting activity polypeptide 3
   [73]Open in a new tab

   (Gene names are to be presented in italics).

   KEGG pathway enrichment analysis of SNU-790 cells under simulated
   microgravity revealed that most genes related to cancer-associated
   microRNAs (ID:05206) were downregulated. Additionally, terms related to
   gene silencing, such as gene silencing by miRNA (GO:BP, GO:0035195) and
   posttranscriptional gene silencing (GO:BP, GO:0035194), were associated
   with low expression of microRNA-related genes. The top genes
   downregulated in the simulated microgravity culture of SNU-790 were
   MIR4798 (FC − 3.437, adj. P < 0.001), MIR548K (FC − 3.234, adj.
   P < 0.001), MIR4762 (FC − 3.217, adj. P < 0.001), MIR548O2 (FC − 3.111,
   adj. P < 0.001), MIR1284 (FC − 3.066, adj. P < 0.001), MIR4524A
   (FC − 2.925, adj. P < 0.001), MIRLET7A2 (FC − 2.835, adj. P < 0.001),
   MIR4668 (FC − 2.672, adj. P < 0.001), MIR4742 (FC -2.613, adj.
   P < 0.001), MIR4441 (FC -2.607, adj. P < 0.001), and MIR4500 (FC
   -2.597, adj. P < 0.001).

Altered gene expression in SNU-80 cells

   SNU-80 cell analysis revealed 96 DEGs under simulated microgravity
   compared with those under 1 G. Of these, 41 were upregulated and 55
   were downregulated (Fig. [74]3). The heatmap and PCA showed that SNU-80
   cultured in simulated microgravity had transcriptional profiles
   distinct from those of cells cultured in 1 G (Fig. [75]3).

   Figure [76]5 and Table [77]3 summarize the results of the KEGG pathway
   enrichment and GO enrichment analyses of SNU-80 cells under simulated
   microgravity. A total of 15 KEGG pathways showed remarkable results in
   the enrichment analysis using the SNU-80 DEG set. The HIF-1 signaling
   pathway (ID 04066, P = 0.001, FDR = 0.159) was analyzed, and genes
   related to response to hypoxic conditions, including EDN1 (FC − 1.979,
   adj. P < 0.001), PDK1 (FC − 1.844, adj. P < 0.001), ENO2 (FC − 1.628,
   adj. P < 0.001), and HK2 (FC − 1.552, adj. P < 0.001), were
   downregulated. Moreover, DEGs related to the response to hypoxia were
   observed in pathways such as central carbon metabolism in cancer (ID
   05230, P = 0.008, adj. P = 0.217), lipid and atherosclerosis (ID 05417,
   P = 0.008, adj. P = 0.217), and metabolic pathways (ID 01100,
   P = 0.008, adj. P = 0.217). A total of 164 GO:BP terms, 3 GO molecular
   function (GO:MF) terms, and 5 GO cellular component (GO:CC) terms were
   analyzed. A total of six GO:BP terms were associated with the response
   to hypoxic conditions, including response to hypoxia (GO:BP,
   GO:0001666, adj. P < 0.001), response to decreased oxygen levels
   (GO:BP, GO:0036293, adj. P < 0.001), and response to oxygen levels
   (GO:BP, GO:0070482, adj. P < 0.001).

Fig. 5. Functional annotation analysis of differentially expressed genes in
SNU-80 Cells under simulated microgravity conditions.

   [78]Fig. 5
   [79]Open in a new tab

   A Top 20 KEGG Pathways Enrichment Analysis, B Gene Ontology enrichment
   analysis of Biological Processes, C Gene Ontology enrichment analysis
   of Molecular Function, and D Gene Ontology enrichment analysis of
   Cellular Component.

Table 3.

   KEGG pathway analysis and Gene Ontology enrichment analysis of
   differentially expressed genes in SNU-80 cells cultured under simulated
   microgravity conditions.
   No Gene symbol Fold change Adjusted P value Gene description
   (A) Top five downregulated KEGG pathways associated with genes related
   to response to hypoxia
   (A-a) HIF-1 signaling pathway (ID 04066, P = 0.001, adj. P = 0.159)
   1 HK2 −1.552 <0.001 Hexokinase 2
   2 ENO2 −1.628 <0.001 Enolase 2 (gamma, neuronal)
   3 PDK1 −1.844 <0.001 Pyruvate dehydrogenase kinase, isozyme 1
   4 EDN1 −1.979 <0.001 Endothelin 1
   (A-b) Central carbon metabolism in cancer (ID 05230, P = 0.008, adj. P
   = 0.217)
   1 HK2 −1.552 <0.001 Hexokinase 2
   2 PDK1 −1.844 <0.001 Pyruvate dehydrogenase kinase, isozyme 1
   (A-c) Lipid and atherosclerosis (ID 05417, P = 0.008, adj. P = 0.217)
   1 VLDLR −1.792 <0.001 Very low density lipoprotein receptor
   (A-d) Metabolic pathways (ID 01100, P = 0.008, adj. P = 0.217)
   1 CPOX 2.114 0.009 Coproporphyrinogen oxidase
   2 GBE1 −1.536 <0.001 Glucan (1,4-alpha-), branching enzyme 1
   3 HK2 −1.552 <0.001 Hexokinase 2
   4 ENO2 −1.628 <0.001 Enolase 2 (gamma, neuronal)
   5 P4HA1 −1.653 <0.001 Prolyl 4-hydroxylase, alpha polypeptide I
   6 CA9 −2.211 <0.001 Carbonic anhydrase IX
   (B) Top five Gene Ontology terms associated with genes related to the
   response to hypoxia
   (B-a) Response to hypoxia (GO:BP, GO:0001666, adj. P < 0.001)
   1 NDRG1 −1.677 <0.001 N-myc downstream regulated 1
   2 PDK1 −1.844 <0.001 Pyruvate dehydrogenase kinase, isozyme 1
   3 EDN1 −1.979 <0.001 Endothelin 1
   4 BNIP3 −2.130 <0.001 BCL2/adenovirus E1B 19 kDa interacting protein 3
   5 CA9 −2.211 <0.001 Carbonic anhydrase IX
   (B-b) Response to decreased oxygen levels (GO:BP, GO:0036293, adj. P <
   0.001)
   1 NDRG1 −1.677 <0.001 N-myc downstream regulated 1
   2 PDK1 −1.844 <0.001 Pyruvate dehydrogenase kinase, isozyme 1
   3 EDN1 −1.979 <0.001 Endothelin 1
   4 BNIP3 −2.130 <0.001 BCL2/adenovirus E1B 19 kDa interacting protein 3
   5 CA9 −2.211 <0.001 Carbonic anhydrase IX
   (B-c) Response to oxygen levels (GO:BP, GO:0070482, adj. P < 0.001)
   1 NDRG1 −1.677 <0.001 N-myc downstream regulated 1
   2 PDK1 −1.844 <0.001 Pyruvate dehydrogenase kinase, isozyme 1
   3 EDN1 −1.979 <0.001 Endothelin 1
   4 BNIP3 −2.130 <0.001 BCL2/adenovirus E1B 19 kDa interacting protein 3
   5 CA9 −2.211 <0.001 Carbonic anhydrase IX
   (B-d) Cellular response to hypoxia (GO:BP, GO:0071456, adj. P = 0.002)
   1 STC1 −1.524 <0.001 Stanniocalcin 1
   2 NDRG1 −1.677 <0.001 N-myc downstream regulated 1
   3 PDK1 −1.844 <0.001 Pyruvate dehydrogenase kinase, isozyme 1
   4 EDN1 −1.979 <0.001 Endothelin 1
   5 BNIP3 −2.130 <0.001 BCL2/adenovirus E1B 19 kDa interacting protein 3
   (B-e) Cellular response to decreased oxygen levels (GO:BP, GO:0036294,
   adj. P = 0.002)
   1 STC1 −1.524 <0.001 Stanniocalcin 1
   2 NDRG1 −1.677 <0.001 N-myc downstream regulated 1
   3 PDK1 −1.844 <0.001 Pyruvate dehydrogenase kinase, isozyme 1
   4 EDN1 −1.979 <0.001 Endothelin 1
   5 BNIP3 −2.130 <0.001 BCL2/adenovirus E1B 19 kDa interacting protein 3
   [80]Open in a new tab

   (Gene names are to be presented in italics).

   Table [81]4 summarizes the top 17 up- and 20 downregulated mRNAs from
   microarray analysis of SNU-80 cells in simulated microgravity culture.
   CA9 (FC − 2.211, adj. P < 0.001), BNIP3 (FC − 2.130, adj. P < 0.001),
   NPPB (FC − 2.017, adj. P < 0.001), EDN1 (FC − 1.979, adj. P < 0.001),
   PDK1 (FC − 1.844, adj. P < 0.001), VLDLR (FC − 1.792, adj. P < 0.001),
   and NDRG1 (FC − 1.677, adj. P < 0.001) were downregulated under
   simulated microgravity in SNU-80 cells, and were related to the
   cellular response to hypoxia.

Table 4.

   Comparative analysis of differentially expressed genes in SNU-80 cells
   cultured under simulated microgravity and normal gravity conditions.
   No. Gene symbol Fold change Adjusted P-value Gene description
   (A) Top 17 upregulated genes in SNU-80 cells in simulated microgravity
   1 MIR29A 2.418 0.018 MicroRNA 29a
   2 CPOX 2.114 0.009 Coproporphyrinogen oxidase
   3 GBP4 1.902 <0.001 Guanylate binding protein 4
   4 TLR3 1.797 0.039 Toll-like receptor 3
   5 IFI44L 1.785 <0.001 Interferon-induced protein 44-like
   6 SERPINB4 1.707 0.024 Serpin peptidase inhibitor, clade B (ovalbumin),
   member 4
   7 IFIT1 1.645 <0.001 Interferon-induced protein with tetratricopeptide
   repeats 1
   8 GBP1 1.629 0.024 Guanylate binding protein 1, interferon-inducible
   9 MIR4668 1.600 <0.001 MicroRNA 4668
   10 IFIH1 1.577 0.009 Interferon induced, with helicase C domain 1
   11 MIR4295 1.573 0.011 MicroRNA 4295
   12 EVI2A 1.570 0.039 Ecotropic viral integration site 2A
   13 IL24 1.549 <0.001 Interleukin 24
   14 HERC6 1.532 0.002 HECT and RLD domain containing E3 ubiquitin
   protein ligase family member 6
   15 XAF1 1.516 0.001 XIAP associated factor 1
   16 RAB27B 1.507 0.013 RAB27B, member RAS oncogene family
   17 STEAP1 1.503 0.021 Six transmembrane epithelial antigen of the
   prostate 1
   (B) Top 17 downregulated genes in SNU-80 cells in simulated
   microgravity
   21 CA9 −2.211 <0.001 Carbonic anhydrase IX
   22 NRN1 −2.137 <0.001 Neuritin 1
   23 BNIP3 −2.130 <0.001 BCL2/adenovirus E1B 19 kDa interacting protein 3
   24 OR10V2P −2.083 <0.001 Olfactory receptor, family 10, subfamily V,
   member 2 pseudogene
   25 FGF11 −2.039 <0.001 Fibroblast growth factor 11
   26 NPPB −2.017 <0.001 Natriuretic peptide B
   27 EDN1 −1.979 <0.001 Endothelin 1
   28 TMEM45A −1.944 <0.001 Transmembrane protein 45A
   29 LOX −1.910 <0.001 Lysyl oxidase
   30 LIMCH1 −1.875 <0.001 LIM and calponin homology domains 1
   31 PDK1 −1.844 <0.001 Pyruvate dehydrogenase kinase, isozyme 1
   32 MAMDC2 −1.842 0.001 MAM domain containing 2
   33 VLDLR −1.792 <0.001 Very low density lipoprotein receptor
   34 UPK1A −1.756 0.004 Uroplakin 1A
   35 LOC154761 −1.735 0.001 Family with sequence similarity 115, member C
   pseudogene
   36 NDRG1 −1.677 <0.001 N-myc downstream regulated 1
   37 COL11A1 −1.655 <0.001 Collagen, type XI, alpha 1
   38 P4HA1 −1.653 <0.001 Prolyl 4-hydroxylase, alpha polypeptide I
   39 ENO2 −1.628 <0.001 Enolase 2 (gamma, neuronal)
   40 SPAG4 −1.571 <0.001 Sperm-associated antigen 4
   [82]Open in a new tab

   (Gene names are to be presented in italics).

Discussion

   In this study, we investigated the morphological and gene expression
   differences between Korean-derived thyroid cancer cell lines, SNU-790
   and SNU-80, cultured under normal gravity and simulated ground-based
   microgravity conditions. Our findings confirmed that SNU-790 and SNU-80
   cells formed three-dimensional MCSs when cultured under simulated
   microgravity. Specifically, SNU-790 cells exhibited an upregulation of
   histone-related genes and downregulation of microRNA-related genes.
   Meanwhile, in SNU-80 cells genes associated with hypoxia response were
   downregulated. Collectively, this study provides valuable insights into
   the molecular and transcriptional changes of Korean thyroid cancer
   cells under simulated microgravity conditions, representing the first
   research using a Korean-derived cell line.

   Research on cancer cells in a microgravity environment represents a
   highly promising field with the potential to enhance cancer prevention
   and treatment strategies^[83]5. The global incidence of thyroid cancer
   has been steadily increasing, particularly in Asian nations^[84]17.
   However, most studies investigating thyroid cancer cells under
   microgravity have predominantly focused on Western populations and
   utilized FTC cells^[85]3,[86]8,[87]10. This approach may not adequately
   capture the diverse characteristics of thyroid cancer. Hence, there is
   a need for research that specifically assesses thyroid cancer cells
   across different racial backgrounds to facilitate the development of
   more effective methods for preventing and treating thyroid cancer,
   while advancing our understanding of thyroid cancer treatment on a
   global scale.

   In our study, we observed the formation of MCSs when SNU-790 and SNU-80
   cells were cultured under simulated microgravity conditions. Unlike
   their adherent growth in normal gravity, these cells exhibited
   three-dimensional growth patterns under simulated microgravity, which
   has been observed previously^[88]18. MCS formation is not influenced by
   the cellular phenotype (normal or malignant) and is formed under
   microgravity regardless of cell type^[89]9,[90]18,[91]19. As such,
   culturing human FTC cells (UCLA RO82-W-1 cell line) under microgravity
   induces distinct characteristics, including the development of stress
   fibers and cellular extensions (lamellipodia, filopodia, and
   microvilli), compared to cells cultured under normal gravity
   conditions^[92]20. MCSs not only exhibit distinct structural
   characteristics but also mimic the behaviors of physiological processes
   in the human body^[93]3. Consequently, MCSs have emerged as valuable
   models for studying cancer metastasis and exploring drug-targeting
   strategies^[94]3,[95]18. The confirmation of MCS formation in SNU-790
   and SNU-80 cell lines represents a significant finding, offering a
   potential foundation for future investigations into the underlying
   mechanisms and the development of innovative treatment approaches
   utilizing non-Western thyroid cancer cell lines. However, the DEG, KEGG
   pathway enrichment, and GO analyses in the current study did not
   provide sufficient data to infer the mechanisms underlying MCS
   formation. Therefore, further systematic research in this regard is
   warranted.

   Through this study, we found that the characteristics of SNU-790 and
   SNU-80 under simulated microgravity conditions were comparable to those
   of FTC cell lines derived from Western populations. In particular, we
   observed DEGs related to histone and microRNAs in SNU-790 cells. The
   involvement of histone and microRNAs in gene transcription suggests
   their potential impact on various cellular biological processes,
   including proliferation, growth, or differentiation, aligning with
   findings from previous research^[96]2–[97]4. Additionally, a separate
   study reported the differential expression of over 100 microRNAs when
   thyroid cancer cells (FTC-133) were cultured at the International Space
   Station, indicating the potential for further investigations in this
   area^[98]21. However, it is important to note that our study focused on
   analyzing DEGs between simulated microgravity and normal gravity
   conditions, which limits our interpretation to correlation rather than
   establishing causal relationships.

   SNU-790 cells cultured under simulated microgravity showed that
   histone-related genes were upregulated. Histones form nucleosomes with
   DNA, compose DNA-histone complexes called chromatin, and regulate RNA
   expression. Histones play a role in development and cancer growth
   through epigenetic changes, such as methylation, acetylation, and
   phosphorylation^[99]22. These findings align with the results of Singh
   et al., who observed that microgravity triggers epigenetic changes in
   human lymphocytes, including alterations in the expression of DNMT1 and
   HDAC, which subsequently impacts gene expression^[100]23. Histone
   acetylation activates transcription by making DNA more accessible, and
   histone methylation regulates transcription by recruiting other
   transcription-related proteins^[101]24. The diversity of cellular
   functions related to histone modification emphasizes the need for
   additional research to provide more precise interpretation of our
   findings.

   SNU-790 cells tended to under-express microRNA-related genes under
   simulated microgravity. MicroRNAs play a crucial role in regulating
   gene expression at the post-transcriptional level through RNA
   silencing^[102]25. They are involved in regulating various biological
   processes, such as cell differentiation, proliferation, apoptosis,
   energy metabolism, and cytokinesis^[103]26. Our findings align with
   previous studies that have reported the impact of weightlessness on the
   regulation of microRNA expression in colorectal cancer cells and
   leukocytes, leading to alterations in various biological processes
   associated with cancer^[104]27,[105]28. However, in cancer cells,
   microRNAs can either induce or suppress tumor growth depending on the
   specific tissue and microRNA involved^[106]25,[107]26. The precise
   implications of our findings on cancer characteristics remain unclear,
   and further analysis is needed to determine whether the observed
   under-expression of microRNAs affects oncogene or tumor suppressor gene
   expression.

   In the case of SNU-80, the HIF-1 signaling pathway or GO terms related
   to hypoxia and under-expression of related genes were analyzed. HIF-1
   plays a role in regulating oxygen homeostasis in the body. However,
   even when intratumoral hypoxia occurs because of the growth of cancer
   cells, it impacts vascularization and metabolic reprogramming for
   oxygen homeostasis, affecting cancer progression, invasion, and
   metastasis^[108]29. We conducted technical replicate experiments at
   least 10 times to eliminate confounding variables other than
   gravitational conditions and reduce experimental errors. After
   confirming the consistency of the results, we proceeded with the cDNA
   array analysis. Subsequently, we performed microarray analysis,
   confirming outcomes consistent across repetitions. As a result, our
   research team concluded that the effects observed were unlikely to be
   attributed to hypoxic conditions. Moreover, when comparing our findings
   to Xiao’s study, where FTC-133 cells were cultivated in a microgravity
   simulator, we noted similar enrichments of Gene Ontology (GO) terms
   related to the response to oxygen levels. This strengthens our
   inference that the observed effects in our study are likely associated
   with cancer-related pathways^[109]30. CA9 was under-expressed in our
   study and reportedly causes angiogenesis and metabolic remodeling under
   conditions of hypoxia and acidosis while promoting invasiveness and
   metastatic propensity^[110]31. HK2 is an enzyme that plays an important
   role in glycolysis. HK2 overexpression has been reported in several
   carcinomas, whereas its deletion reportedly reduces cancer cell
   proliferation^[111]32. In addition, PDK1 was also under-expressed in
   the present study. PDK1 overexpression, which has been reported in
   melanoma, leukemia, and gastric carcinoma, results in poor overall
   survival or recurrence rates^[112]33. We observed differences in DEGs
   related to hypoxia in SNU-80 under microgravity, suggesting, in line
   with previous studies, that cancer cells in microgravity exhibit a less
   aggressive phenotype^[113]3.

   The present study has a limitation in that it can only establish an
   association between gravitational conditions and DEGs. Additional
   research is needed to establish a causal relationship and to
   investigate the relations between DEG differences and specific clinical
   characteristics. Furthermore, the results obtained in this study
   necessitate well-designed research for validation.

   In conclusion, this is the first study in which Korean thyroid cancer
   cell lines were used to study the effect of simulated microgravity on
   morphology and gene expression. SNU-790 and SNU-80 cultured under
   simulated microgravity formed MCSs. SNU-790 cells under microgravity
   revealed upregulation of histone-related genes and down-regulation of
   microRNA-related genes, whereas SNU-80 showed down-regulation of genes
   related to hypoxia responses. Our research demonstrated the potential
   of conducting microgravity studies using Korean thyroid cells.
   Additional research is needed to elucidate the mechanism and causal
   relationship in SNU-790 and SNU-80 cells exposed to simulated
   microgravity.

Methods

Cells and culture conditions

   Human Korean PTC cells (SNU-790) and human anaplastic thyroid cancer
   cells (SNU-80) were purchased from the Korean cell line bank
   ([114]https://www.cellosaurus.org; Seoul, Korea). Additional
   information regarding the acquisition of the cells used in this study
   can be obtained from the Seoul National University Cancer Research
   Institute. ([115]https://cri.snu.ac.kr). The SNU-790 cell line used in
   this research was at passage number 10, while the SNU-80 cell line was
   at passage 8. The SNU-790 cell line (CVCL_5093) is a thyroid gland
   papillary carcinoma cell line obtained from the thyroid gland of a
   72-year-old Korean male (NCBI Taxonomy: 9606). This cell line harbors
   BRAF (c.1799T>A) mutation, and its doubling time is 33 h. The SNU-80
   cell line (CVCL_5097) is a thyroid gland anaplastic carcinoma cell line
   obtained from the thyroid gland of a 59-year-old Korean woman (NCBI
   Taxonomy: 9606) and harbors BRAF (c.1405 G > C) and TP53 (c.832 C > G)
   mutations; its doubling time is 37 h.

   Both cell lines were cultured in RPMI-1640 (Cytiva, Marlborough, MA,
   USA), supplemented with 10% fetal bovine serum (FBS; Cytiva), 1%
   penicillin-streptomycin (Thermo Fisher scientific, Waltham, MA, USA) in
   a humidified atmosphere of 5% CO[2] at 37 °C. To proceed with cell
   culture experiments in simulated microgravity, 10^6 cells were seeded
   in T-25 culture flasks (Corning, Corning, NY, USA).

Simulated ground-based microgravity platform and cell culture

   Gravite (Space Bio-Laboratories Co., Ltd., Hiroshima, Japan) is a
   simulated microgravity generator (Fig. [116]6) that uses simultaneous
   rotation of the chamber on two axes at a constant angular velocity to
   uniformly distribute, and cancels the cumulative gravity vector to
   simulate microgravity^[117]34. Initially, 1 × 10^6 SNU-790 and SNU-80
   cells were sub-cultured under 1 G conditions for 24 h. After the
   subculture period, the same number of cells (1 × 10^6 cells) for each
   cell line was re-seeded into T-25 cell culture flasks (Corning) with
   RPMI-1640 media (Cytiva), supplemented with 10% FBS (Cytiva), and 1%
   penicillin-streptomycin (Thermo Fisher Scientific) in a humidified
   atmosphere of 5% CO[2] at 37 °C. Cells were cultured until day 7
   without changing the medium. Cell morphology and cell number via
   counting were confirmed after 24, 48, 72, and 120 h following
   re-seeding and culturing cells. Cell morphology imaging and cell
   counting were confirmed based on the adherent cells at the bottom of
   the T25 flask. Phase-contrast microscopy using Nikon eclipse TS100
   (Marshall Scientific, Hampton, NH, USA) with 4×, 10×, 20×, and 40×
   objective lenses was used for observation of the cell morphology (Fig.
   [118]1 and Fig. [119]2). The cultured cells were enumerated using Life
   technology countess II (Thermo Fisher Scientific).

Fig. 6. Simulator of microgravity, Gravity controller: “Gravite”.

   [120]Fig. 6
   [121]Open in a new tab

   Main unit size (width × depth × height), 425 × 420 × 445 (mm); weight,
   13.5 kg; main body sample holder, T25 flask insertion, maximum six
   flasks, Atmosphere inside the chamber: 37 °C, 5% CO2.

   The culture conditions of the experimental and control groups in the
   Gravite are depicted in Fig. [122]6. The SNU-790 and SNU-80 cells,
   which had been sub-cultured for 24 h, were divided into T25 flasks at a
   density of 1 × 10^6 cells. In the experimental group, the T25 flask was
   positioned in the Gravite sample holder, whereas in the control group,
   the T25 flask was placed at the bottom of the Gravite chamber. Both the
   experimental and control groups were subsequently cultured for a
   duration of 120 h. Placing the T25 flask in the control group at the
   bottom of the Gravite chamber established equivalent conditions that
   could potentially impact cell culture, aside from the effects of
   gravity. This experimental setup was employed to ensure a consistent
   and controlled environment for both groups, facilitating accurate
   comparisons and observations.

RNA extraction, quality control, and cDNA microarray

   After culturing the cells for 5 d, the supernatant was removed from the
   T25 flask, and adherent cells were washed twice with phosphate buffered
   saline (Cytiva). Subsequently, 1 mL of 0.25% Trypsin-EDTA buffer was
   added, and incubated for 1 − 2 min; the growth medium was added, and
   the cultured cells were transferred to a 15 mL tube and centrifuged at
   4 °C and 3000 rpm (1952 × g) for 3 min using Hanil combi R515 (Hanil
   Scientific Inc., Gimpo, Korea). After centrifugation, the supernatant
   was aspirated, leaving only the pellet.

   The pellets were sent to Macrogen (Macrogen, Inc., Seoul, Korea) for
   RNA extraction, which was performed as follows. For homogenization
   prior to RNA extraction, the cultured cells were uniformly immersed in
   lysis buffer using TransZol (TransGen Biotech Co., Ltd., Beijing,
   China) and disrupted. The lysate was transferred to a microcentrifuge
   tube and incubated for 5 min at room temperature (18–23 °C) after the
   visible precipitate had dispersed. Chloroform (Merck KGaA, Darmstadt,
   Germany) was added to the microcentrifuge tube at a rate of 0.2 mL per
   1 mL of TransZol. The tube was shaken vigorously for 15 s, incubated at
   room temperature (18–23 °C) for 3 min, and then centrifuged at 13,000 ×
   g for 15 min at 4 °C. Next, the colorless upper aqueous phase
   containing RNA was transferred to a new RNase-free tube. Isopropanol
   (Merck KGaA) was added to the RNase-free tubes at a ratio of 1 mL of
   isopropanol per 1 mL of TransZol. The tube was incubated at room
   temperature (18–23°C) for 10 min and centrifuged at 13,000 × g for
   10 min at 4 °C. Following centrifugation, the supernatant was
   discarded. After adding 1 mL of 80% ethanol (Thermo Fisher Scientific),
   the tube was mixed vigorously and centrifuged at 13,000 × g for 5 min
   at 4 °C. Following centrifugation, the supernatant was discarded and
   the step was repeated by adding 1 mL of 80% ethanol to the tube. The
   tube was mixed by inverting and centrifuged at 13,000× g for 10 min at
   4 °C. Again, following centrifugation, the supernatant was discarded.
   After air-drying the RNA pellet for approximately 5 min, it was
   dissolved in distilled water (Thermo Fisher Scientific) and incubated
   at 55 − 60 °C for 10 min.

   Comprehensive RNA quality control measures were conducted, including
   purity and quantity assessment using a NanoDrop (Thermo Fisher
   Scientific). Absorbance measurements at 260 nm were employed to
   quantify RNA. Purity values of 1.7–2.0 were considered indicative of
   relatively pure RNA. An RNA integrity evaluation was performed using an
   Agilent Technologies 2100 Bioanalyzer (Agilent Technologies, Santa
   Clara, CA, USA) with an RNA Integrity Number value ≥8. Additionally,
   RNA quantity was assessed using a Quantus Fluorometer with Quant-iT
   microRNA Assay Kit (Thermo Fisher Scientific). RNA integrity was
   evaluated using an Agilent Technologies 2100 Bioanalyzer with Small RNA
   Chip (Agilent Technologies).

   GeneChip Human Gene 2.0 ST Array (Thermo Fisher Scientific) was used in
   this study. cDNA was synthesized using the GeneChip WT (Whole
   Transcript) Amplification kit (Thermo Fisher Scientific), as described
   by the manufacturer. The sense cDNA was then fragmented and
   biotin-labeled with terminal deoxynucleotidyl transferase (TdT) using
   the GeneChip WT Terminal labeling kit (Thermo Fisher Scientific).
   Approximately 5.5 μg of labeled DNA target was hybridized to the
   Affymetrix GeneChip Array (Affymetrix Inc., Santa Clara, CA, USA) at
   45 °C for 16 h. Hybridized arrays were washed and stained on a GeneChip
   Fluidics Station 450 (Thermo Fisher Scientific) and scanned on a
   GCS3000 Scanner (Affymetrix Inc.). The probe cell intensity data
   computation and a CEL file generation were performed using Affymetrix
   GeneChip Command Console Software (Affymetrix Inc.).

Statistical analysis

   In the DEG analysis, raw CEL files were processed using the Affymetrix
   Power Tools program (Affymetrix Inc.) with the Robust Multichip
   Analysis (RMA) algorithm to extract normalized signal
   intensity^[123]35. Filtering was then applied to retain probe sets that
   were not related to genes or transcripts, but rather contained main or
   consensus probes only. Subsequently, the fold change of the filtered
   probes was calculated, and the Local-pooled-error (LPE) test was
   performed to obtain LPE P-values^[124]36. However, the LPE P-value was
   not considered for selecting significant probes for Functional
   Analysis. Instead, only the fold change was considered (absolute value
   of fold change ≥ 1.5) to ensure a sufficient number of significant
   probes for further analysis. For a DEG set, hierarchical cluster
   analysis was performed using complete linkage and Euclidean distance as
   a measure of similarity. Gene-Enrichment and Functional Annotation
   analysis for a significant probe list was performed using Gene Ontology
   ([125]http://geneontology.org) and KEGG ([126]http://kegg.jp).
   Enrichment results were analyzed for GO terms with an adjusted
   P-value < 0.05 for each GO category. Considering that the statistical
   significance of GO terms with very small or large term sizes may be
   exaggerated, size filtering was performed on the top 20 GO terms that
   satisfy a term size of ≥ 10 and ≤ 500. All data analysis and
   visualization of DEGs were conducted using R 3.3.2
   ([127]www.r-project.org; The R Foundation, Indianapolis, IN, United
   States).

Acknowledgements