Abstract

   Ubiquitin Conjugating Enzyme 2C (UBE2C) is an emerging target gene for
   tumor progression. However, the tumorigenic effect and mechanism of
   UBE2C in adrenocortical carcinoma (ACC) remains unclear. Systematic
   investigation of the tumorigenic effect of UBE2C may help in
   understanding its prognostic value in adrenocortical carcinoma. First,
   we exploited the intersection on DFS-related genes, OS-related genes,
   highly expressed genes in adrenocortical carcinoma as well as
   differentially expressed genes (DEGs) between tumor and normal, and
   then obtained 20 candidate genes. UBE2C was identified to be the most
   significant DEG between tumor and normal. It is confirmed that high
   expression of UBE2C was strongly associated with poor prognosis in
   patients with ACC by analyzing RNA-seq data of ACC obtained from the
   Cancer Genome Atlas (TCGA) database implemented by ACLBI Web-based
   Tools. UBE2C expression could also promote m6A modification and
   stemness in ACC. We found that UBE2C expression is positively
   associated with the expression of CDC20, CDK1, and CCNA2 using ACLBI
   Web-based Tools, indicated the hyperactive cell cycle progression
   present in ACC with high UBE2C expression. In addition, UBE2C knockdown
   could significantly inhibit the proliferation, migration, invasion, EMT
   of adrenocortical carcinoma cells as well as the cell cycle progression
   in vitro. Notably, pan-cancer analysis also identified UBE2C as an
   oncogene in various tumors. Taken together, UBE2C was strongly
   associated with poor prognosis of patients with ACC by promoting cell
   cycle progression and EMT. This study provides a new theoretical basis
   for the development of UBE2C as a molecular target for the treatment of
   ACC.

Introduction

   Adrenocortical carcinoma (ACC) is an aggressive tumor originating in
   the adrenocortical cortex with a very low incidence about 0.5–1 per 1
   million people [[44]1] and poor prognosis with 5-year overall survival
   ranging from 16% to 47% [[45]1, [46]2]. The 5-year survival rate of ACC
   at stage I is about 81%, but when the disease progresses to stage Ⅳ,
   the 5-year survival rate can be reduced to about 13% [[47]3]. Disease
   progression is the main reason affecting the prognosis of ACC. Radical
   surgical excision is the only cure option for primary ACC [[48]4].
   However, the recurrence rate of ACC after surgical excision is highly
   [[49]5]. Although it is prone to metabolic and endocrine toxicity,
   mitotane remain as the only drug approved for the treatment of advanced
   adrenocortical carcinoma and postoperative [[50]6]. It follows that
   there is a lack of other effective drug for the treatment of ACC, so it
   is urgent to find new therapeutic targets. Hence, deciphering the
   complex molecular composition of ACC progression and developing
   targeted therapeutic agents, bioinformatics analysis as a convenient
   and effective strategy is a good choice to screen the available
   therapeutic targets.

   Ubiquitination of modified proteins is an important cellular mechanism
   that targets the degradation of abnormal or short-lived proteins and
   plays an important role in tumor progression [[51]7]. UBE2C is a key
   member of the E2 ubiquitin-binding enzyme family, encoding proteins
   necessary for the destruction of target proteins [[52]8]. Accumulating
   evidence suggested that overexpression of UBE2C can promote the
   proliferation of ACC by promoting the G2/M phase transition [[53]9] and
   the activation of the Spindle and Kinechore-Associated (SKA) Complex
   [[54]10]. Notably, the KRAS^G12D mutation can promote the expression of
   UBE2C to promote cell cycle progression and autophagy in lung cancer,
   which indicated that UBE2C is an attractive carcinogenic genetic target
   for lung cancer with KRAS mutations [[55]11]. A comprehensive
   bioinformatics analysis indicated the effect of UBE2C in promoting
   tumor progression [[56]12], but the carcinogenic effect of UBE2C in ACC
   still needs to be further investigated.

   In this study, we confirmed that UBE2C is a major response gene that
   affects the prognosis of ACC. In addition, we also explored the
   relationship between UBE2C expression and m6A methylation,
   proliferation-related and metastasis-related pathways in ACC. Moreover,
   in vitro experiments showed that UBE2C knockdown result in poor
   prognosis of ACC by inhibiting the proliferation, migration, invasion,
   epithelial–mesenchymal transition (EMT) of adrenocortical carcinoma
   cells as well as the cell cycle progression. And the pan-cancer
   analysis suggested that UBE2C is an oncogenic gene in various tumors.
   In conclusion, this study identified UBE2C as a novel oncogenic gene in
   promoting adrenocortical carcinoma progression and contributing to its
   poor prognosis.

Materials and methods

Research framework

   [57]Fig 1 showed the framework of this study.

Fig 1. Overview of the research design.

   [58]Fig 1
   [59]Open in a new tab

   (A) Data sources used in this research; (B) The main response genes
   related to poor prognosis in ACC were analyzed. (C) The expression of
   UBE2C is positively correlated with advanced clinicopathological
   characteristics and poor prognosis of ACC. (D) UBE2C expression can
   promote cell cycle progression and EMT. (E) Pan-cancer analysis
   identified UBE2C as an oncogene in various tumors.

Data retrieval, preprocessing, and analysis

   Obtained from TCGA database ([60]https://tcga-data.nci.nih.gov/tcga/),
   GEO database ([61]http://www.ncbi.nlm.nih.gov/geo), GTEx database
   ([62]https://www.gtexportal.org/), these significant data were used to
   detect target genes related to poor prognosis in patients with ACC.
   These data were analyzed using R packages implemented by R version
   4.0.3 (R foundation for statistical computing, 2020). Conveniently, all
   above data retrieval, preprocessing, and analysis were performed in
   STRING ([63]https://cn.string-db.org/), ACLBI Web-based Tools
   ([64]https://www.aclbi.com/) or Xiantao Academic web-based Tools
   ([65]https://www.xiantao.love/products).

Venn diagrams

   In order to screen out the likely response gene, Venn diagrams were
   created to analyze the difference between several dataset using a
   web-based tool
   ([66]http://www.bioinformatics.com.cn/static/others/jvenn/example.html)
   .

mRNA expression-based stemness index (mRNAsi)

   mRNA expression-based stemness index (mRNAsi) was identified as a
   measure of the tumor development according to the previously
   publication-n [[67]13]. Based on the OCLR algorithm [[68]13], the
   mRNAsi of ACC was calculated using ACC RNA-seq data obtained from TCGA
   database implemented by ACLBI Web-based Tools.

Cell culture

   The ACC cell line SW-13 was purchased from the American Type Culture
   Collection (ATCC, Maryland, USA) and cultured in Leibovitz’s L-15
   Medium (L-15, 11415064, Gibco, Grand Island, NY, USA) supplemented with
   1% penicillin and streptomycin and 10% fetal bovine serum (Gibco). The
   culture of SW-13 cells needed to maintain at 37°C.

RNA interference

   RNA interference (RNAi) was used to interfere with the expression of
   UBE2C in SW-13 cells. The siRNAs targeting UBE2C (TranSheepBio,
   Shanghai, China) and the scramble siRNAs were purchased. And then
   siRNAs targeting UBE2C were transfected into SW-13 cells using
   Lipofectamine™ 3000 (L3000015, ThermoFisher SCIENTIFIC) according to
   the manufacturer’s instructions.

Cells counting

   Cells proliferation was assessed using Neubauer counting chamber.
   First, RNAi technology was used to interfere with the UBE2C expression
   in SW-13 cells. Second, the treated SW-13 cells and non-treated SW-13
   cells were seeded into the 6-well plates. Then, the SW-13 cells were
   digested with trypsin and resuspended in PBS. Finally, the
   proliferation of SW-13 cells was assessed by cell counting using
   Neubauer counting chamber.

Colony formation assay

   The effect of UBE2C on the colony formation capabilities of SW-13 cells
   was detected as previously described [[69]14]. Briefly, the expression
   of UBE2C in SW-13 cells were interfered using RNAi technology. The
   non-treated SW-13 cells and treated SW-13 cells (500 cells/well) were
   planted in a 6-well plate. The resultant colonies were fixed with 4%
   paraformaldehyde, and then coomassie blue solution were used to fix and
   stain the resultant colonies.

Wound-healing assay and transwell assay

   Wound-healing assay and transwell assay were performed as previously
   described [[70]14] to detect the change of migration and invasion
   capabilities of SW-13 cells, respectively. In wound-healing assay,
   SW-13 cells in a logarithmic growth phase were collected to seeded in a
   6-well plate. A wound was created mechanically using a 1 ml pipette
   tip. In transwell assay, the basement membrane was simulated using
   matrigel (354248, Corning, NY, USA).

Western blotting

   Western blotting was carried out as previously reported [[71]15]. The
   antibodies used for western blotting included C-myc (18583S, CST),
   Cyclin D1 (55506S, CST), UBE2C (14234S, CST), cleased-PARP-1 (5625S,
   CST), cleased-Caspase-7 (9491T, CST), E-cad (20874-1-AP, proteintech),
   N-cad (22018-1-AP, proteintech), Vimentin (10366-1-AP, proteintech),
   snail (ab216347, abcam), MMP2 (ab92536, abcam), GAPDH (ab8245, abcam).

Statistical analyses

   Statistical analyses in this study were carried out using the SPSS 24.0
   software (Abbott Laboratories, Chicago, USA). Data were shown as mean ±
   SD. P-values less than 0.05 was identified to be statistically
   significant.

Results

UBE2C expression strongly associated with advanced histopathological
characteristics and poor prognosis of adrenocortical carcinoma (ACC)

   In order to detect the main response gene strongly associated with poor
   prognosis in patients with ACC, we analyzed the intersection of four
   gene clusters including DFS-relates genes, OS-relates genes,
   differentially expressed genes (DEGs), and highly expressed genes. The
   volcano plot showed the DEGs of the patients with ACC ([72]Fig 2A and
   [73]S1 Table). After exploiting the intersection, we obtained 20
   candidate genes in ACC including CDC20, NUF2, BUB1, CCNA2, LMNB1,
   PTTG1, FSCN1, MELK, KIF11, CEP55, CDCA3, TROAP, CDKN3, CCNB2, CDT1,
   AURKB, CDT1, AURKB, BIRC5, UBE2C, CENPM, KIF4A ([74]Fig 2B and [75]S2
   Table). To identify the major response gene affecting prognosis in
   patients with ACC, GO and KEGG pathways enrichment analysis were used
   to analyze the activated signaling pathways accompanied by the highly
   expression of these candidate genes ([76]Fig 2C). Notably, UBE2C was
   the most significant DEG between ACC and normal ([77]Fig 2D and [78]S3
   Table). We also found that UBE2C was highly expressed in ACC especially
   in stage Ⅲ and stage Ⅳ using Xiantao Academic Web-based Tools ([79]Fig
   3A). To further study the correlation between UBE2C expression and
   histopathological characteristics of ACC, we tested UBE2C within the
   ACC dataset to better describe its functionality ([80]Fig 3B and [81]S4
   Table). These analyses confirmed that ACC patients with high UBE2C
   expression tended to have a poor prognosis compared to those with low
   UBE2C expression ([82]Fig 3C–3E). Taken together, UBE2C was highly
   expressed and strongly correlated with poor prognosis in patients with
   ACC.

Fig 2. Differentially expressed genes in ACC and functional enrichment
analysis.

   [83]Fig 2
   [84]Open in a new tab

   (A) Volcano plot: blue dots point different down-regulated genes and
   red dots point different up-regulated genes in ACC; (B) Venn diagrams:
   intersected with the DEGs, High-expression genes, OS-related genes, and
   DFS-related genes in ACC; (C) GO enrichment analysis and KEGG
   enrichment analysis of the 20 candidate genes; (D) the expression
   comparison of the 20 candidate genes between normal obtained for GTEx
   database and tumor obtained for TCGA database. *P < 0.05, **P < 0.01,
   ***P < 0.001, the asterisk represents the degree of statistical
   significance (*P).

Fig 3. UBE2C expression indicated advanced clinical characteristics in ACC.

   [85]Fig 3
   [86]Open in a new tab

   (A) the expression of UBE2C in different tumor status and different
   pathologic stages; (B) Sankey diagram: each column represents a
   characteristic variable, different colors represent different types or
   stages, and the lines represent the distribution of the same sample in
   different characteristic variables; (C) the relationship between UBE2C
   expression and survival time as well as survival status in ACC; (D) the
   KM survival curve of the UBE2C in ACC; (E) the ROC curve and AUC value
   of the UBE2C at different times in ACC. *P < 0.05, **P < 0.01, ***P <
   0.001, the asterisk represents the degree of statistical significance
   (*P).

UBE2C expression promoted m^6A methylation and stemness in ACC

   In order to understand the mode of UBE2C regulating downstream pathway,
   we explored the correlation between UBE2C expression and m6A
   methylation in ACC. Based on the identification and analysis of the m6A
   methylation regulators by Juan Xu’s research [[87]16], a circle was
   used to describe the interaction of expression on 20 m6A regulators in
   ACC using ACLBI Web-based Tools ([88]Fig 4A). And then the expression
   levels of UBE2C were categorized into two groups including G1 group
   (above 75th percentile of UBE2C expression) and G2 group (below 25th
   percentile of UBE2C expression). The result showed that G1 group
   contained 16 significantly overexpressed m6A regulators compared with
   G2 group ([89]Fig 4B and [90]S5 Table). We found that UBE2C expression
   was positively associated with the mRNAsi in ACC using ACLBI Web-based
   Tools, which suggested that UBE2C may lead to poor prognosis in
   patients with ACC via promoting self-renewal of ACC stem cells ([91]Fig
   4C and 4D).

Fig 4. UBE2C expression promoted m6A methylation and stemness in ACC.

   [92]Fig 4
   [93]Open in a new tab

   (A) The correlation of expression on 20 m6A regulators in ACC. The size
   of each circle represents the prognosis of each m6A regulator and
   scaled through P-value. The m6A regulating protein of three RNA
   modifies is represented by different colors of circles. The line
   connecting the m6A regulators represents the interaction between them.
   (B) Heatmap: A heatmap of m6A-related gene expression, in which
   different color represent expression trends in different groups. G1
   group was defined as above 75th percentile of UNE2C expression, and G2
   group was defined as below 25th percentile of UNE2C expression. (C) The
   correlation between UBE2C expression and mRNAsi of ACC. (D) As
   described above, comparison of mRNAsi between G1 group and G2 group. *P
   < 0.05, **P < 0.01, ***P < 0.001, the asterisk represents the degree of
   statistical significance (*P).

UBE2C expression activated the molecular pathways of cell cycle,
proliferation, and metastasis

   At first, a previously published geneset [[94]17] was analyzed for
   understanding the correlation between UBE2C expression and the
   activation of several signaling pathway in ACC implemented by ACLBI
   Web-based Tools, and the results showed that UBE2C expression was
   positively correlated with the activation of cell cycle, proliferation,
   and metastasis ([95]Fig 5). To further explore the downstream signaling
   pathways activated by UBE2C, we analyzed DEGs between G1 group and G2
   group as described above ([96]Fig 6A–6C and [97]S6 Table). Based on
   STRING protein-protein interaction network [[98]18], we found that
   there are 10 candidate proteins closely related to UBE2C protein
   expression ([99]Fig 6D). And based on LogFC and P-value (LogFC ≥ 2 or
   LogFC ≤ -2, P-value < 0.05), we identified 349 significantly DEGs
   ([100]Fig 6E). And then, we screened out a cluster containing 4 genes
   related to cell cycle by intersecting the two data sets ([101]Fig 6E
   and [102]S7 Table).

Fig 5. UBE2C expression was correlated with the activation of several signal
pathway in ACC.

   [103]Fig 5
   [104]Open in a new tab

Fig 6. UBE2C expression with the activation of the molecular pathways of cell
cycle, proliferation, and metastasis.

   [105]Fig 6
   [106]Open in a new tab

   (A) Volcano plot: blue dots point different down-regulated genes and
   red dots point different up-regulated genes; (B) Heatmap: DEGs between
   G1 group and G2 group. G1 group was defined as above 75th percentile of
   UNE2C expression, and G2 group was defined as below 25th percentile of
   UNE2C expression as described above; (C) GO enrichment analysis of
   these genes; (D) 10 candidate proteins related to UBE2C protein were
   identified using STRING database; (E) Venn diagrams: the intersection
   between 11 candidate proteins obtained from STRING database and 349
   candidate genes obtained from significant DEGs between G1 group and G2
   group.

Pan-cancer analysis identified UBE2C as an oncogene in various tumor

   In this paper, pan-cancer analysis using TCGA dataset and GTEx dataset
   were all implemented by ACLBI web-based Tools. We found that UBE2C is
   almost overexpressed in all tumor including ACC, BLCA, BRCA, CESC,
   CHOL, COAD, DLBC, ESCA, GBM, HNSC, KICH, KIRC, KIRP, LGG, LIHC, LUAD,
   LUSC, OV, PAAD, PCPG, PRAD, READ, SARC, SKCM, STAD, TGCT, THCA, UCEC,
   and UCS by means of the comparison on UBE2C expression between the
   tumor and normal obtained from TCGA dataset and GTEx dataset,
   respectively ([107]Fig 7A). Moreover, UBE2C expression will leads to
   poor prognosis in various tumors ([108]Fig 7B and 7C). More
   importantly, we found that UBE2C expression is positively associated
   with hyperactive MSI as well as TMB, especially in ACC ([109]Fig 7D).
   This may imply that UBE2C can be used as a predictor of the efficacy of
   immunotherapy for patients with ACC. The relationship between UBE2C
   expression and immune infiltration in various tumors were also
   explored. And we found that UBE2C overexpression was positive
   correlation with the infiltration of Th1, Th2 as well as negative
   correlation with the infiltration of Treg, M2 macrophages ([110]Fig
   7E). But the relation between the Th1/Th2 immune balance and ACC
   progression need more studies. In conclusion, we found that UBE2C was
   highly expressed in various tumors and strongly associated with poor
   prognosis, but also predicted the hyperactivity of MSI and TMB,
   especially in ACC.

Fig 7. Pan-cancers analysis of UBE2C.

   [111]Fig 7
   [112]Open in a new tab

   (A) the different expression of UBE2C in 33 tumors. (B) the overall
   survival and disease-free survival defined by UBE2C in pan-cancer. (C)
   Forest plot: P-value, risk factor HR, and 95% confidence interval of
   the overall survival and disease-free survival defined by UBE2C in 33
   tumors. (D) Spearman correlation analysis of UBE2C expression with MSI
   and TMB. The abscissa and the size of the dots in the figure represent
   the correlation coefficient, and the ordinate represent different
   tumors. The different colors represent the P-value; (E) Heatmap plot:
   spearman correlation analysis between immune infiltration scores and
   UBE2C expression in 33 tumor tissues using XCELL method. *P < 0.05, **P
   < 0.01, ***P < 0.001, the asterisk represents the degree of statistical
   significance (*P).

UBE2C knockdown weakened proliferation, migration, and invasion via
inhibiting ACC cycle progression and EMT in vitro

   At first, we assessed the effects of UBE2C on adrenocortical carcinoma
   cell growth. Morphological changes of SW-13 cells showed that
   transfected with control or UBE2C siRNAs strongly inhibited
   proliferation of adrenocortical carcinoma cell ([113]Fig 8A). The clone
   formation assays further verified the promoting effect of UBE2C on the
   proliferation of SW-13 cells ([114]Fig 8B). To test our hypothesis that
   UBE2C is involved in tumor invasion, siRNAs were used to transiently
   silence UBE2C expression. And then the effect of UBE2C on migration and
   invasion in adrenocortical carcinoma cell were further investigated.
   Transwell assay results demonstrated that UBE2C siRNAs stimulation
   remarkably suppressed the invasion of adrenocortical carcinoma cell
   compared to treated with a scramble siRNA ([115]Fig 8C). We assessed
   migration capacity through wound-healing assays in vitro with taking a
   picture and calculating the distance travelled at a 0-hour, 24-hour and
   48-hour time point. Compared to SW-13 cells treated with a scramble
   siRNA, those receiving UBE2C siRNAs stimulation travelled a shorter
   distance ([116]Fig 8D). For tumor invasion requiring both degradation
   of ECM components and cell migration, we performed western blotting and
   found that UBE2C knockdown indeed inhibited EMT of adrenocortical
   carcinoma cells, manifested as the decreased expression of N-cad,
   Vimentin, snail, MMP2 and increased expression of E-cadherin ([117]Fig
   8E). Moreover, western blotting indicated that UBE2C siRNAs can inhibit
   proliferation, inhibit damage repair of DNA, and induced apoptosis in
   ACC cells, characterized by the increased expression of
   cleased-Caspase-7 as well as the decreased expression of
   cleased-PARP-1, C-myc, cyclin D1 ([118]Fig 8F). In conclusion, these
   results demonstrated that UBE2C knockdown can weaken proliferation,
   migration, and invasion of adrenocortical carcinoma cell via inhibiting
   cycle progression and EMT.

Fig 8. UBE2C knockdown weakened proliferation, migration, and invasion.

   Fig 8
   [119]Open in a new tab

   (A) Morphological changes of SW-13 cells transfected with control or
   UBE2C siRNA. (B) SW-13 cells were transfected with control or UBE2C
   siRNA, and colonies were counted after 14 days. (C) SW-13 cells were
   transfected with control or UBE2C siRNA, and cell invasion was
   determined by transwell assay. (D) SW-13 cells were transfected with
   control or UBE2C siRNA, and cell migration was detected by wound
   healing assay. (E-F) Western blotting assay of the indicated proteins
   in SW-13 cells were transfected with UBE2C or control siRNA for 48 h.
   *P < 0.05, **P < 0.01, ***P < 0.001, the asterisk represents the degree
   of statistical significance (*P) (n = 3).

Discussion

   Adrenocortical carcinoma is a rare tumor with a very low incidence.
   However, patients with adrenocortical carcinoma usually have poor
   prognosis. When patients with adrenocortical carcinoma progressed from
   the stage I to the stage Ⅳ, the 5-year survival rate would be reduced
   by more than 60%. Unfortunately, only mitotane with limited
   therapeutical effects can be used for patients with advanced
   adrenocortical carcinoma or postoperative recurrence. Hence, it is a
   major challenge for the scientific community to develop more safe and
   more effective anti-ACC drugs. A new understanding of pathogenesis and
   an in-depth exploration of novel drug targets are urgently needed in
   ACC to find anti-cancer drugs.

   It is helpful to excavate potential oncogene and to better integrate
   biological evidence for understanding the mechanism of tumor
   progression using web-based tools or database. We screened out 20
   oncogenes including CDC20, NUF2, BUB1, CCNA2, LMNB1, PTTG1, FSCN1,
   MELK, KIF11, CEP55, CDCA3, TROAP, CDKN3, CCNB2, CDT1, AURKB, CDT1,
   AURKB, BIRC5, UBE2C, CENPM, KIF4A by analyzing TCGA data sets and GTEx
   data sets implemented by ACLBI Web-based Tools. We not only found these
   20 oncogenes were highly expressed in tumor tissues, but also study the
   differential expression levels of these genes between tumor and normal.
   These results identified UBE2C as the significant DEG between tumor and
   normal.

   Ubiquitin-proteasome system (UPS) is one of the major pathways for
   protein degradation through a series of steps such as substrate
   recognition, ubiquitin coupling and proteasome-ubiquitinated substrate
   degradation [[120]19, [121]20]. Unlike autophagy, UPS primarily
   degrades single unfolded peptides with capacity of entering narrow
   channels of the proteasome [[122]21]. Human UBE2C (also known as
   UBCH10) is located on chromosome 20q13.12 [[123]22]. UBE2C can promote
   anaphase-promoting complex (APC/C) specifically combine with protein
   degradation pathway, and plays a key role in regulating the cell cycle,
   apoptosis, and transcriptional processes by catalyzing degradation of
   proteins [[124]8, [125]23, [126]24]. APC/C, a multi-subunit complexes,
   can accelerate the mitotic progression from metaphase to anaphase by
   catalyzing the multi-ubiquitination of key regulatory factors in the
   cell cycle [[127]25]. Hence, the abnormal expression of UBE2C will
   cause the hyperactivity of the APC/C-dependent ubiquitination in tumor
   cells, which accelerates the cell cycle and eventually leads to
   malignant transformation. It is well known that the KRAS^G12D target
   have ushered in a new era in the treatment of KRAS-mutant oncology
   drugs [[128]26]. Remarkably, a study discovered that Kras^G12D mutation
   regulates the cell cycle by promoting the expression of UBE2C, which
   ultimately promotes tumor cell growth [[129]11]. That validates UBE2C
   as a potential therapeutic target for lung cancer with KRAS^G12D
   mutations. Accumulating evidence also suggested that the high
   expression of UBE2C is strongly related to poor prognosis in patients
   with breast cancer [[130]24, [131]27], lung adenocarcinoma [[132]28] or
   gastric cancer [[133]29]. On the one hand, based on the description of
   hallmarks of cancer proposed by Professor Douglas Hanahan [[134]30], it
   has been confirmed that UBE2C can promote tumor growth [[135]31],
   angiogenesis [[136]32], tumor metastasis [[137]33, [138]34],
   anchorage-independent growth [[139]35], stemness [[140]36], resist
   apoptosis [[141]37, [142]38], induce immunosuppressive microenvironment
   [[143]39], and enhance glycolytic activity [[144]40, [145]41]. On the
   other hand, high expression of UBE2C will lead to treatment failure
   attributed to overactive anchorage-independent growth and reduced
   oxidative stress-induced cell apoptosis resulting in chemotherapy
   resistance [[146]35], and reduce radiosensitivity [[147]38],
   respectively. In short, a series of studies shown that UBE2C is highly
   expressed in tumors tissues and able to promote tumor progression.

   In this study, we identified UBE2C as a potential oncogene after
   analyzing the TCGA dataset implemented by ACLBI Web-based Tools.
   Interestingly, we found that UBE2C only significantly expressed in
   patients with ACC stage Ⅲ and stage Ⅳ using Xiantao Academic Web-based
   Tools. Hence, patients with Advanced ACC or postoperative recurrence
   ACC are lack of effective treatment strategies. UBE2C is mainly
   expressed in advanced ACC, which may be a theoretical basis for solving
   these contradictions in ACC. Moreover, we evaluated the correlation
   between the expression levels of UBE2C and the function of m6A in ACC.
   At first, we identified the m6A methylation modification patterns in
   ACC mediated by 20 regulators using ACLBI Web-based Tools ([148]Fig
   4A). Accumulating evidence showed that more than 60% RNA modifications
   in mammalian cells are methylation modification, and m6A methylation is
   the most common, abundant, and conservative internal RNA modification
   [[149]42]. M6A methylation can speed up transcription and participate
   in proteins translation and mRNA degradation [[150]43–[151]45]. m6A
   methylation modification can directly or indirectly regulate target
   genes, which can affect biological behaviors such as the proliferation,
   metastasis, and immune escape of tumor cells [[152]46]. Hence,
   explaining the relationship between UBE2C and m6A regulators in ACC can
   enhance our understanding of the mechanism of UBE2C promoting the tumor
   development. In vitro experiments data showed that suppressing UBE2C
   expression can inhibit metastasis and proliferation, weaken DNA damage
   repair, and induce the apoptosis. Our preliminary results suggested
   that UBE2C can activate the C-myc signaling pathway to promote cell
   cycle progression as well as activate the snail signaling pathway to
   induce EMT in ACC. A study uncovered that PARP-1 can activate the snail
   signaling pathway to induce EMT in melanoma cells [[153]47]. These
   results cued that the mechanism of UBE2C promoting proliferation and
   metastasis of ACC will be more complicated, and further investigations
   are still needed to clarify this important issue.

Conclusions

   In summary, the present study demonstrates that UBE2C is strongly
   correlation with poor prognosis in patients with ACC via promoting cell
   cycle progression and EMT. This study not only uncovers the mechanism
   of UBE2C in promoting ACC proliferation and metastasis but also
   provides a novel rationale for developing UBE2C as a potential
   molecular target for the treatment of advanced ACC.

Supporting information

   S1 Table. The DEGs of the patients with ACC.

   The differentially expressed genes between patients with ACC and normal
   were analyzed. RNA-sequencing expression profiles of 79 patients with
   ACC were downloaded from the TCGA database. And RNA-sequencing
   expression profiles of 258 normal were downloaded from GTEx database.
   These data were analyzed using R packages implemented by R version
   4.0.3 in ACLBI Web-based Tools ([154]https://www.aclbi.com/). “LogFC ≥
   2 or LogFC ≤ -2, P-value < 0.05” was defined as a screening criterion
   for identifying differentially expressed genes.

   (XLSX)
   [155]Click here for additional data file.^ (117.2KB, xlsx)
   S2 Table. 20 candidate genes in ACC were identified.

   The intersection of four gene clusters was analyzed including
   DFS-relates genes, OS-relates genes, differentially expressed genes
   (DEGs), and highly expressed genes.

   (XLSX)
   [156]Click here for additional data file.^ (57.2KB, xlsx)
   S3 Table. UBE2C was the most significant DEG between ACC and normal.

   RNA-sequencing expression profiles of 79 patients with ACC were
   downloaded from the TCGA database. And RNA-sequencing expression
   profiles of 258 normal were downloaded from GTEx database. These data
   were analyzed using R packages implemented by R version 4.0.3 in ACLBI
   Web-based Tools ([157]https://www.aclbi.com/).

   (XLSX)
   [158]Click here for additional data file.^ (237.6KB, xlsx)
   S4 Table. UBE2C expression within the ACC dataset.

   UBE2C expression and corresponding clinical information of 79 patients
   with ACC were described in detail.

   (XLSX)
   [159]Click here for additional data file.^ (22.4KB, xlsx)
   S5 Table. G1 group contained 16 significantly overexpressed m6A
   regulators compared with G2 group.

   The result showed that G1 group (above 75th percentile of UBE2C
   expression) contained 16 significantly overexpressed m6A regulators
   compared with G2 group (below 25th percentile of UBE2C expression).

   (XLSX)
   [160]Click here for additional data file.^ (21.3KB, xlsx)
   S6 Table. DEGs between G1 group and G2 group.

   The result showed the differentially expressed genes between G1 group
   (above 75th percentile of UBE2C expression) and G2 group (below 25th
   percentile of UBE2C expression).

   (XLSX)
   [161]Click here for additional data file.^ (1.4MB, xlsx)
   S7 Table. A cluster containing 4 genes related to cell cycle by
   intersecting the two data sets.

   The candidate proteins obtained from STRING database; and the
   significant DEGs between G1 group (above 75th percentile of UBE2C
   expression) and G2 group (below 25th percentile of UBE2C expression)
   were analyzed from the TCGA dataset. “LogFC ≥ 2 or LogFC ≤ -2, P-value
   < 0.05” was defined as a screening criterion.

   (XLSX)
   [162]Click here for additional data file.^ (15.8KB, xlsx)
   S1 Raw images

   (PDF)
   [163]Click here for additional data file.^ (669.7KB, pdf)

Acknowledgments