Abstract

Backgroud

   Pancreatic cancer (PC) is a highly invasive malignancy with extremely
   poor prognosis. STK31 has been identified as a cancer‐testis (CT) gene,
   but its function in PC has not been elucidated well.

Methods

   The effect of STK31 on cell proliferation, migration and invasion was
   investigated by in vitro and in vivo experiments and total RNA
   sequencing and targeted bisulfite sequencing was applied to explore the
   potential regulatory mechanisms of STK31 in PC.

Results

   By analysis of tissue samples and the clinicopathologic features, we
   found that STK31 was reactivated in PC and associated with poor
   prognosis. In addition, the vitro and vivo studies indicated that STK31
   could promote PC progression by facilitating cell proliferation,
   migration and invasion, and the indication. Targeted Bisulfite
   Sequencing showed that STK31 was regulated by methylation. Furthermore,
   the results of total RNA sequencing suggested that STK31 was closely
   related to signal transduction, metabolism, and the immune system.

Conclusions

   This study demonstrates that STK31, as a CT gene, can promote the
   development of PC and is regulated by methylation. STK31 could be
   considered as a potential therapeutic target for PC.

   Keywords: CT gene, immunotherapy, invasion, migration, proliferation,
   STK31
     __________________________________________________________________

   STK31 was reactivated in PC and associated with poor prognosis. STK31
   could promote PC progression by facilitating cell proliferation,
   migration and invasion in vitro and vivo studies. Targeted Bisulfite
   Sequencing showed that STK31 was regulated by methylation. And total
   RNA sequencing suggested that STK31 was closely related to signal
   transduction, metabolism and the immune system.

   graphic file with name CAM4-12-7273-g001.jpg

1. INTRODUCTION

   Pancreatic cancer (PC) is a highly invasive malignancy and the
   prognosis is extremely poor. In the United States, it is the fourth
   main cause of cancer‐related deaths both in male and female with a poor
   5‐year survival rate of 10%.[38] ^1 Radical resection combined with
   systematic chemotherapy could be the only chance for curing the
   condition.[39] ^2 And it seems promising that immunotherapy can benefit
   PC patients in clinical research.[40] ^3 According to Oliver's
   study,[41] ^4 radical resection combined with chemotherapy can provide
   a 5‐year survival rate to 30%–40%. However, only about 10%–15% of the
   patients have resectable lesions and half of PC patients present
   distant metastasis when diagnosed.[42] ^5 Due to the high lethality and
   slow progression in diagnosing and treatment, PC is predicted to become
   the second leading cancer‐related mortality by 2030.[43] ^6 Therefore,
   early diagnosis and new effective therapeutic targets would be the key
   to improving the outcomes of the condition in PC.

   Cancer‐testis (CT) genes are a class of genes whose expression is
   restricted to testis in normal tissues, but frequently aberrantly
   expressed in some cancers.[44] ^7 CT genes are considered as potential
   immunotherapy targets and diagnostic biomarkers of cancers owing to
   their fewer side effects because of the specific expression
   features.[45] ^8 , [46]^9 Serine/threonine kinase 31 (STK31, also known
   as TDRD8) has been identified as a CT gene in PC in our previous study
   and we have elucidated the potential clinical value of this gene.[47]
   ^10 In addition, STK31 has also been detected in gastric cancer,[48]
   ^11 colorectal cancer,[49] ^12 cervical cancer,[50] ^12 and lung
   cancer.[51] ^13 The biological functions of STK31 such as maintaining
   the undifferentiated state,[52] ^14 promoting cell proliferation, and
   cell cycle regulation, has been studied in regards to these
   conditions.[53] ^15 It's been found in our previous studies that the
   high expression of STK31 suggested a poor prognosis of PC.[54] ^16
   However, the function of STK31 in PC has not been demonstrated before.
   Thus, the aim of this present study was to elucidate the biological
   function and underlying mechanism of STK31 in PC by in vivo and in
   vitro experiments, which could give us a better understanding of the
   development of PC and also offer a new possibility for targeted
   therapy.

2. MATERIAL AND METHODS

2.1. Patients and samples

   Forty‐eight patients, who were confirmed as PC by two pathologists,
   were enrolled from the Pancreas Center, the First Affiliated Hospital
   with Nanjing Medical University. All these patients were underwent
   initial surgical resection between December 2016 and April 2017. In
   regards to public databases, the expression pattern can be confirmed by
   GEPIA2, which is a web service for analyzing the RNA sequencing
   expression data from the TCGA or GTEx projects by a standard processing
   pipeline.[55] ^17 This study was approved by the Institutional Review
   Board of the First Affiliated Hospital with Nanjing Medical University
   (2021‐SR‐483) and a waiver of written informed consent was granted by
   the Institutional Review Board Committee.

2.2. Cell lines

   Human PC cell lines BXPC‐3, Capan‐2, CFPAC‐1, COLO‐357, MIA PaCa‐2, and
   PANC‐1 were purchased from the Shanghai Cell Bank. The cell line
   hTERT‐HPNE was obtained from the American Type Culture Collection
   (ATCC, CRL‐4037). All these cell lines were cultured according to their
   manufacturer's instructions.

2.3. Transfection of siRNAs and plasmids

   The small interfering RNAs (siRNAs) and plasmid to STK31 were purchased
   from GenePharma (Shanghai, China) and GeneChem (Shanghai, China),
   respectively. The sequences of siRNAs were as follows: siRNA#1:
   5’‐GGACCAG AAACUGAUUGAATT‐3′(sense) and 5’‐UUCAAUCAGU UUCUGGUCCTT‐3′
   (antisense); siRNA#2: 5’‐GAGGAG UUCACCAGUGUUATT‐3′ (sense) and
   5’‐UAACACUGG UGAACUCCUCTT‐3′ (antisense); siRNA#3: 5’‐GGAGA
   UAGCUCUGGUUGAUTT‐3′ (sense) and 5’‐AUCAACCA GAGCUAUCUCCTT‐3′
   (antisense). The plasmid vector is GV144 (CMV‐EGFP‐MCS‐SV40‐Neomycin)
   and carrying the sequences of STK31 ([56]NM_032944). The transfection
   of siRNAs and plasmids were performed with Lipofectamine3000 according
   to the manufacturer's instructions. Cells were collected for subsequent
   experiments after transfection for 48–72 hours.

2.4. Preparation of STK31‐overexpressing cells

   STK31‐overpressing lentivirus were constructed by OBiO Technology Corp.
   The full‐length coding region of human STK31 was subcloned into the
   pLenti‐EF1a‐P2A‐Puro‐CMV‐STK31. Stable cell lines were selected by
   culturing in complete medium containing 5 μg/mL puromycin. STK31
   expression was confirmed by qRT‐PCR and western blotting.

2.5. Quantitative RT‐PCR and western blotting

   Total RNAs were extracted from cells and tumor tissues by Total RNA Kit
   I (Omega Bio‐tek Inc) and then reverse‐transcribed into cDNA with
   HiScript II qRT SuperMix (Vazyme Inc). The qRT‐PCR was performed by the
   StepOnePlus Real‐Time PCR System (Applied Biosystems) and the primers
   were the same as in the previous study.[57] ^10 The total protein from
   cells was extracted using a RIPA lysis buffer. The extracted protein
   was mixed with a 5× SDS‐PAGE sample loading buffer and boiled.

2.6. Targeted bisulfite sequencing and methylation detection

   Genomic DNA from 27 tumor tissue samples of 48 patients was extracted
   by AllPrep DNA/RNA Mini Kit (Qiagen). Methylation analysis was
   performed with a working concentration of 20 ng/μL and 500 ng genomic
   DNA was subjected to bisulfite conversion using the EpiTect Fast DNA
   Bisulfite Kit (Qiagen). CpG sites located in the promoter of the STK31
   gene were selected from the 2 k upstream of a transcriptional start
   site (TSS) to the 1 k downstream of the first exon, and two CpG regions
   of the STK31 gene were included. The methylation levels of the STK31
   gene promoter were analyzed by MethylTarget™ (Genesky Biotechnologies
   Inc.), an NGS‐based multiple methylation specific PCR analysis method.
   According to the manufacturer's protocol, the detection of STK31
   methylation was performed on Illumina Hiseq 2000 with a 2 × 150 bp
   sequencing mode. The methylation levels of the 33 CpG sites were
   measured.

2.7. Cell count kit‐8 assay and EdU assay

   Cells transfected with siRNA and plasmids were seeded in 96‐well plates
   at a density of 30% and 70% area of per well. For cell count kit‐8
   assay (CCK‐8), the CCK‐8 assay kit (Dojindo) was utilized to detect the
   ability of cell proliferation. The premixed 100 μl medium which
   consisted of 10:1 complete medium and CCK8 reagent was added to each
   well every 24 hours. After incubation in the dark at 37 °C for 2 hours,
   then the mixture was measured at 450 nm by a spectrometer. For EdU
   assay, a Cell Light EdU DNA imaging Kit (Ribo Bio) was used. Cell
   proliferation was evaluated by the proportion of positive stained
   cells. Three duplicated wells were detected.

2.8. Clone formation assay

   The 1000 transfected cells were seeded in each well of 6‐well plate.
   The complete medium was changed every 5 days. After 10 days, the clones
   were stained with crystal violet solution. The number of clones was
   quantified to assess cell proliferation.

2.9. Cellular transwell assay

   Twenty‐four well Millicell Hanging Cell Culture Inserts (Merck
   Millipore) and Biocoat Matrigel (BD Bioscience) were used to access the
   cell migration and invasion ability. 5 × 10^4 transfected cells
   included in the 200 μl serum‐free medium were seeded in the upper
   chamber with an uncoated or Matrigel‐coated membrane, and 600 μl
   complete medium was added into the lower room as a chemoattractant.
   After 24 h of culturing for CFPAC‐1 and PANC‐1 and 48 h for MIA PaCa‐2,
   non‐migrating cells in the upper chamber were wiped. These cells
   migrating to the lower surface of the membrane were stained with
   crystal violet for 30 minutes and then photographed.

2.10. Animal study

   Four‐week‐old male BALB/c nude mice were obtained from the Animal
   Center of the Nanjing Medical University. A total of 12 mice were
   randomly divided into stable STK31‐overexpressing and control MIA
   PaCa‐2 cells groups. 2 × 10^7 tumor cells were injected into the axilla
   of mice for subcutaneous tumor formation. Once visible, the tumor size
   of these subcutaneous tumors were measured every 4 days. Four weeks
   later, after euthanizing all nude mice, the tumors were resected and
   photographed. And the size and weight of these subcutaneous tumor were
   measured. The animal use protocol has been reviewed and approved by the
   Animal Ethical and Welfare Committee (AEWC) of Nanjing Medical
   University (IACUC‐1904050).

2.11. RNA sequencing, differentially expressed genes (DGEs) identifying and
function annotation and pathway enrichment analysis

   RNA sequencing was performed by BGISEQ Genetic Sequencer (BGI, China).
   Stable MIA PaCa‐2 cells with overexpression of STK31 was analyzed in
   comparison of vector control. Each group had three duplications. Genes
   with fold change (FC) ≥ 2 and adjusted p value≤0.001 were considered as
   DGEs. The gene ontology (GO) analysis and Kyoto Encyclopedia of Genes
   and Genomes (KEGG) analysis was performed for function annotation and
   pathway enrichment.

2.12. Statistical analysis

   Statistical analysis was performed by Graphpad Prism (Version 8.0) and
   R (Version 4.1.1). Quantitative data were expressed as mean ± SD from
   three duplicate experiments. The difference of the mean between two
   groups was analyzed by Student's t‐test. All the data was
   representative of three independent repeated experiments. In both TCGA
   and our PC cohort, we considered those lower quartile expression levels
   as low expression and the rest as high expression. The correlation
   between STK31 expression and methylation levels was examined by Pearson
   test. p < 0.05 was considered statistically significant.

3. RESULTS

3.1. Expression characterizations and roles of STK31 in PC

   As we have found in previous studies, the STK31 expression was
   restricted to the testis. We analyzed the expression of STK31 in PC and
   examples of normal pancreas in GEPIA2, and it showed that the
   expression of STK31 was higher in 179 PC than 171 normal pancreas
   (p < 0.05, Figure [58]1A). Furthermore, survival analysis revealed that
   patients with relatively high STK31 expression had poorer overall
   survival (Figure [59]1B). The results from our biobank showed similar
   results (Figure [60]1C). This data suggested STK31 was abnormally
   upregulated in PC and was associated with poor prognosis. The brief
   information of these PC patients from our cohort was described in
   Supplement Table [61]1.

FIGURE 1.

   FIGURE 1
   [62]Open in a new tab

   The expression pattern of STK31 gene. (A) STK31 was overexpressed in
   pancreatic cancer. Patients with relatively high expressions of STK31
   had poorer overall survival rates in TCGA dataset (B) and samples from
   our biobank (C).

3.2. Inhibition of STK31 in CFPAC‐1 and PANC‐1 and overexpression in MIA
PaCa‐2

   The expression of STK31 was detected in hTERT‐HPNE cell line and six
   pancreatic cancer cell lines (Capan‐2, BXPC‐3, CFPAC‐1, MIA PaCa‐2,
   COLO‐357, and PANC‐1) by qRT‐PCR and western blot (Figure [63]2A, B).
   Compared to hTERT‐HPNE cell line, the STK31 expression level of mRNA
   and protein was elevated in CFPAC‐1 and PANC‐1 while lower STK31
   expression was detected in MIA PaCa‐2. Hence, CFPAC‐1, PANC‐1, and MIA
   PaCa‐2 cell lines were selected for subsequent study. The interference
   efficiency for three siRNAs and plasmid of STK31 were examined by both
   qRT‐PCR and western blot (Figure [64]1C–E). After evaluating the
   efficiency, siRNA #1 and the plasmid of STK31 were applied for further
   functional experiments.

FIGURE 2.

   FIGURE 2
   [65]Open in a new tab

   Knockdown and overexpression of STK31. The expression of STK31 was
   detected by qRT‐PCR (A) and western blot (B) in HPNE and PC cell lines.
   The interference efficiency for three siRNAs and plasmid of STK31 were
   examined by both qRT‐PCR and western blot in three PC cells—CFPAC‐1
   (C), PANC‐1 (D), and MIA PaCa‐2 (E). The representative data of all
   experiments are presented as the mean ± SEM.

3.3. The effect of STK31 on cell proliferation, migration, and invasion in PC

   CCK‐8, EDU, and clone formation assays were conducted to investigate
   the effect of STK31 on pancreatic cancer cell lines. As shown in
   Figure [66]3A, the results of CCK‐8 demonstrated that the knockdown of
   STK31 by siRNAs significantly impaired cell proliferation (P < 0.05).
   Similar results were obtained by EDU (Figure [67]3B) and clone
   formation assays (Figure [68]3C). On the contrary, overexpression of
   STK31 in MIA PaCa‐2 promoted cell proliferation. To further determine
   the influence of STK31 on PC cell proliferation, an in vivo study using
   stable STK31‐overexpressing MIA PaCa‐2 cell line prepared by
   STK31‐overexpressing lentivirus was performed. The results indicated
   that tumors in mice injected with overexpressing‐STK31 MIA PaCa‐2 cells
   grew faster, as they had larger tumor volume and tumor mass (p < 0.05
   in both comparisons) (Figure [69]3D–F). These results suggested that
   STK31 could facilitate PC cell proliferation. The transwell assay was
   applied to investigate whether STK31 has an effect on cell migration
   and invasion. As shown in Figure [70]3G, cell migration and invasion
   were inhibited after the downregulation of STK31, whereas enhanced
   results were observed following the overexpression of STK31 (p < 0.05
   in both comparisons). In conclusion, STK31 could promote the ability of
   proliferation, migration, and invasion in PC cells.

FIGURE 3.

   FIGURE 3
   [71]Open in a new tab

   STK31 promoted cell proliferation, migration, and invasion in
   pancreatic cancer. CCK‐8 (A), EDU (B), and clone formation (C) were
   performed to investigate cell proliferation after STK31 was
   downregulated and overexpressed. Magnification for B: 100× and scale
   bar = 200 μm. Stable MIA PaCa‐2 cells with overexpressed STK31 and
   vectors were injected subcutaneously in nude mice. Tumors in mice
   injected with MIA PaCa‐2 cells overexpressing STK31 grew faster, as
   they had larger tumor volumes (D) and tumor mass (E & F). Cell
   migration and invasion were conducted, and the magnification is
   100 × and scale bar = 100 μm (G). The representative data of all
   experiments are presented as the mean ± SEM. *p < 0.05, **p < 0.01 or
   ***p < 0.001.

3.4. The association between methylation and expression levels of STK31

   It is widely known that methylation could affect multiple physiological
   activities by regulating gene expression. To evaluate the effect of
   methylation on STK31 expression, we applied MethylTarget to detect the
   methylation level in 27 pancreatic cancer tissue samples. Finally, two
   significant CpG sites (STK31_29: −277 to −123 of transcriptional start
   site and STK31_38: −105 to 77 of transcriptional start site) located at
   STK31 were selected. Interestingly, the results showed that the
   methylation level of STK31_29 was negatively correlated with the
   expression of STK31, while STK31_38 was not (for STK31_29 CpG site:
   Pearson r = −0.44, p = 0.03; for STK31_38 CpG site: Pearson r = −0.32,
   p = 0.12; for total of two STK31 CpG sites: Pearson r = −0.47,
   p = 0.02; Figure [72]4).

FIGURE 4.

   FIGURE 4
   [73]Open in a new tab

   STK31 expression was regulated by methylation. Schematic diagrams
   showed the location of CpG sites STK31_29 (A) and STK31_38 (B). The
   visualizations of top three haplotype with the highest depth
   sequencing. The hollow circle represents unmethylated while the red
   circle represents methylated. There was an overall negative correlation
   between STK31 expression and methylation (C). The methylation level of
   STK31_29 (D) was negatively correlated with STK31 expression but
   STK31_38 (E) was not.

3.5. Identification of DGEs after overexpressing STK31 and GO and KEGG
pathway analysis of DGEs

   After overexpressing STK31 in MIA PaCa‐2 cells, RNA sequencing was
   performed for further analysis. Twenty nine DGEs were identified
   including 18 upregulated and 11 downregulated genes (Figure [74]5A, B).
   To get further insight into the functions of the DGEs, GO and KEGG
   analyses were performed for these 29 genes. The KEGG analysis indicated
   that these DGEs were mainly associated with transport and catabolism,
   signal transduction, metabolism, immune system, and other biological
   pathways (Figure [75]5C). In GO biological process analysis, 29 DGEs
   were enriched in the cellular process, metabolic process as well as
   other biological processes (Figure [76]5D).

FIGURE 5.

   FIGURE 5
   [77]Open in a new tab

   Exploration of biological functions of DEGs. (A) The volcano plot for
   DGEs comparing stable STK31‐ overexpressed MIA PaCa‐2 cells with
   corresponding control cells. Eighteen upregulated genes (red dots) and
   11 downregulated genes (blue dots) were identified. (B) Heatmap of
   DGEs. (C) KEGG pathways analysis of these DGEs. (D) GO analysis of
   these DGEs

4. DISCUSSION

   PC is a highly invasive and lethal malignancy with a poor prognosis.
   The complicated mechanism of tumorigenesis and its extremely malignant
   biological behaviour have made progression in early diagnosis and
   effective treatment stagnant.[78] ^2 , [79]^4 In this study, the
   results indicated that STK31 was abnormally reactivated in PC tissues.
   The high expression of STK31 was associated with poor prognosis of PC.
   STK31 could promote cancer progression by facilitating cell
   proliferation, migration, and invasion. As a result, STK31 is a
   oncogene and can be considered as a potential therapeutic target for
   the condition.

   STK31 was first identified in the spermatogonia in mice, and the human
   ortholog STK31 was also only detected in human testis among these
   samples from different parts of the body.[80] ^18 , [81]^19 Then Wu et
   al.[82] ^20 demonstrated STK31 was detected in germ cells of human
   testis and located in the cytoplasm. Studies investigating STK31 in
   cancers mostly focus on colorectal cancers before. In 2008, STK31 was
   detected by laser microdissection and cDNA microarray in colorectal
   cancer cells.[83] ^12 Furthermore, a STK31 peptide was able to induce
   immune responses by eliciting specific cytotoxic T lymphocytes.[84] ^12
   STK31 was also reported to play a critical role to maintain the
   undifferentiated state of colon cancer cells, and a downregulation of
   STK31 could significantly suppress cell proliferation both in vitro and
   vivo studies.[85] ^14 Kuo et al. also indicated that the expression
   level of STK31 in colorectal cancer cells was cell cycle‐dependent and
   that the abnormal overexpression of STK31 enhanced the cell abilities
   of migration and invasion without altering cell proliferation.[86] ^15
   Furthermore, STK31 was reported to be a potential biomarker in
   predicting the metastasis of colorectal cancer[87] ^21 and to
   differentiate colorectal cancer from benign polyps.[88] ^22 Except for
   colorectal cancer, STK31 is also abnormally expressed in lung cancer.
   STK31 was reported to promote cell proliferation in lung cancer cells
   by the Wnt/β‐catenin signaling pathway and positive feedback regulation
   of c‐myc.[89] ^13 In general, the oncogenic role of STK31 indicated by
   the present study was consistent with previous reports. However, some
   results in this study should be taken carefully. The ability of the MIA
   PaCa‐2 cell line to pass through well is relatively weak so we have to
   double the duration of cellular transwell assay of MIA PaCa‐2 cells.
   Moreover, we actually employed PANC‐1 and MIA PaCa‐2 cell lines in vivo
   to explore the effect of STK31 on cell proliferation. However,
   subcutaneous tumorigenesis was barely observed in mice injected with
   PANC‐1 cells, and as a result the corresponding outcome was absent.

   Previous studies have identified that KRAS, CDKN2A, TP53, and SMAD4 was
   the major four mutation driver genes for PC.[90] ^2 However, mutation
   driver genes can only explain part of the carcinogenesis. Epigenetic
   drivers are also identified as a significant characteristic of
   tumorigenesis.[91] ^23 CT genes characterizing distinct expression in
   testis and some certain tumors are crucial members of epigenetic
   drivers.[92] ^24 In addition to contributing to spermatogenesis,[93]
   ^25 , [94]^26 STK31 is frequently expressed in various cancers,[95] ^12
   thus serving as a CT gene. In our previous study, methylation is
   considered to be one of the mechanisms that regulates STK31 expression
   through TCGA database analysis.[96] ^10 In this study, we confirmed
   this result in the tumor tissues from our center. However, it is
   interesting that not all methylation levels of SKT31 CpG sites were
   associated with the STK31 expression. We found that only the SKT31_29
   CpG site was associated with gene expression but not STK31_38.

   Currently the biological functions of CT genes are mostly unclear.
   Emerging evidence suggested that they could contribute to tumorigenesis
   by regulating transcriptional activity, mitotic fidelity, and protein
   degradation.[97] ^9 Due to the immune‐privileged status of the testis,
   ectopic expression of CT genes in cancers can induce immune responses
   with fewer side effects. As a result, CT genes products are also named
   CT antigens. The immunogenicity of CT antigens enables them to become
   potential targets for immunotherapy.[98] ^7 MAGEA‐3 is a founding
   member of CT antigens and vaccines targeting MAGEA‐3 have been tested
   in patients.[99] ^27 The safety and immunogenicity have been
   demonstrated in MAGEA‐3 positive patients with non‐small cell lung
   cancer.[100] ^28 Another famous CT antigen, NY‐ESO‐1, has also
   initiated clinical trials. Preliminary results have shown clinically
   meaningful benefits, but the true effect needs further
   investigation.[101] ^29 , [102]^30 JQ‐1, an inhibitor of the CT antigen
   BRDT, was reported to inhibit the growth of xenograft models in
   PC.[103] ^31 Given that STK31 was one of the CT genes and the RNA
   sequencing results in this study suggest that STK31 was closely related
   to signal transduction and immune systems, it might be a potential
   target for immunotherapy of PC. In summary, although the safety and
   feasibility have been demonstrated, the true benefit of CT
   antigen‐based immunotherapy still needs further investigation. CT
   antigen specific immunotherapy in combination with chemotherapy or
   other immunotherapeutic treatments, such as checkpoint blockades, may
   be a promising direction.

   Several limitations still existed in this study. First, although we
   have observed that STK31 was an important effect on the development of
   PC, no in‐depth mechanism has been studied. We will investigate the
   mechanism of STK31 affecting on PC in future studies. Second, we do not
   have a good way to affect the expression of STK31 in vivo to improve
   the prognosis of PC. Methylation, as well as miRNAs which were
   described in our previous studies,[104] ^16 would be a potential way of
   treatment. Third, because of the limited sample size, we have not been
   able to definite a value of STK31 expression level to distinguish the
   prognosis of PC, which is helpful for clinical decision making.

   In conclusion, STK31 was aberrantly upregulated and suggested a poor
   prognosis in patients with PC. STK31 promotes development of PC by
   accelerating cell proliferation, migration, and invasion. However, the
   expression level of STK31 is regulated by methylation. Due to the
   special CT gene expression pattern, STK31 could be considered as a
   promising biomarker for early diagnosis and a hopeful therapeutic
   target for PC.

AUTHOR CONTRIBUTIONS

   Hao Gao: Data curation (equal); formal analysis (equal); writing –
   original draft (equal). Baobao Cai: Data curation (equal); formal
   analysis (equal); writing – original draft (equal). Zipeng Lu:
   Resources (supporting). Guangfu Wang: Data curation (supporting). Yong
   Gao: Data curation (supporting). Yi Miao: Project administration
   (supporting); supervision (equal). Kuirong Jiang: Conceptualization
   (supporting); project administration (equal); supervision (lead). Kai
   Zhang: Conceptualization (lead); resources (equal); validation (lead);
   writing – review and editing (lead).

CONFLICTS OF INTEREST

   The authors have no conflict of interest to declare .

ETHICAL APPROVAL

   This study was approved by the Institutional Review Board of the First
   Affiliated Hospital of Nanjing Medical University (2021‐SR‐483).

Supporting information

   Table S1
   [105]Click here for additional data file.^ (11.8KB, docx)

ACKNOWLEDGMENTS