PRIMARY RESEARCH
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Pan-cancer analysis of oncogenic role of Programmed Cell Death 2 Like (PDCD2L) and validation in colorectal cancer
Huabin Gaot, Cheng Xu1, Jiangtao Liang+, Songhan Ge, Fenfen Zhang, Ying Tuo, Huijuan Shi* and Anjia Han*(D *
Abstract
Background: Programmed Cell Death 2 Like (PDCD2L) correlates with cell proliferation, apoptosis and mouse embryonic development. However, the role of PDCD2L in human cancers is unclear.
Methods: Multiple bioinformatic methods, in vitro function experiments and validation were performed to clarify the oncogenic role of PDCD2L in human cancers.
Results: Our study found that PDCD2L was aberrantly expressed in multiple types of human cancers, and associated with clinical stage and molecular subtype. Furthermore, overexpression of PDCD2L predicted poor overall survival in adrenocortical carcinoma(ACC), kidney chromophobe(KICH), acute myeloid leukemia(LAML), brain lower grade glioma(LGG),liver hepatocellular carcinoma(LIHC), mesothelioma(MESO), uveal melanoma(UVM) and poor diseases free survival in ACC, bladder urothelial carcinoma(BLCA), cervical squamous cell carcinoma and endocervical adeno- carcinoma (CESC), kidney renal clear cell carcinoma(KIRC), kidney renal papillary cell carcinoma(KIRP), LGG, LIHC, and UVM. PDCD2L expression was negatively associated with cancer associated fibroblast in breast invasive carcinoma (BRCA), lung squamous cell carcinoma (LUSC), sarcoma (SARC), stomach adenocarcinoma (STAD) and testicular germ cell tumors (TGCT). Mechanically, we found that PDCD2L expression was associated with apoptosis, invasion and cell cycle by investigating single cell sequencing data. For further validation, PDCD2Lwas highly expressed in colorectal cancer (CRC) cell lines and tissue samples compared with the normal colon cell line and non-tumor adjacent colorec- tal mucosa tissues. PDCD2L knockdown induced the apoptosis and proliferation of CRC cells.
Conclusions: Our study shows that the oncogenic role of PDCD2L in various cancers and PDCD2L could be served as a biomarker of CRC.
Keywords: PDCD2L, Pan-cancer analysis, Oncogenic role, Colorectal cancer
Introduction
Cancer incidence is growing rapidly worldwide, female breast cancer has the highest incidence (11.7%), followed by lung cancer (11.4%) and colorectal cancer (10.0%). As a major cause of death, cancers kill almost 10.0 million
people in 2020.The top 3 tumor-related mortality rates are lung cancer(18%), colorectal cancer(9.4%), and liver cancer(8.3%) [1]. Accordingly, given the incidence and mortality of cancers, it is urgent to find perfect biomark- ers for making diagnosis and predicting the prognosis in various cancers.
Programmed Cell Death 2 Like (PDCD2L) is a cod- ing protein, which also has alias symbols MGC13096. PDCD2Lcontaining PDCD2(C) domain and the expres- sion of PDCD2L in HEK293T cells did not change sig- nificantly when apoptosis was induced by different
*Correspondence: shihj@mail.sysu.edu.cn; hananjia@mail.sysu.edu.cn
+Huabin Gao, Cheng Xu, and Jiangtao Liang contributed equally to this work
Department of Pathology, The First Affiliated Hospital, Sun Yat-Sen University, 58, Zhongshan Road II, Guangzhou 510080, China
☒ BMC
treatments [2]. Augmented levels of MGC13096 protein inhibit proliferation of HEK293T cells, while up-regula- tion of MGC13096 block cell cycle progression at S phase [3]. Intriguingly, Ye et al. showed that up-regulation of PDCD2L in pancreatic beta-cell enhanced palmitate- induced apoptotic rate, and down-regulation of PDCD2L partially diminished the apoptosis induced by palmitate. This study revealed that PDCD2L might play an impor- tant role in apoptosis of pancreatic beta-cell [4]. Moreo- ver, PDCD2L plays a key role during post-implantation embryonic development, which suggests that PDCD2L is evolutionarily conserved in development [5]. PDCD2L expression is related with cell proliferation, apoptosis, and mouse embryonic development. However, the role of PDCD2L is still unknown in various cancers.
Here, we explored the expression and prognostic value of PDCD2L in multiple cancers. Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG)pathways were performed to explore the under- lying molecular mechanisms of PDCD2L and its bind- ing proteins. Then we explored the correlation between PDCD2L expression and immune infiltration. Moreover, single cell sequencing data was applied to investigate rel- evant cancer cell status of PDCD2L. We further verify PDCD2L expression in CRC cell lines and tissues by real- time quantitative PCR (RT-qPCR), western blot (WB), and immunohistochemistry (IHC) staining. We also ana- lyzed the role of PDCD2L in CRC progression in vitro.
Material and methods
PDCD2L gene expression analysis based on pan-cancer database
PDCD2L expression data in pan-cancer tissues and cor- responding adjacent tissues were downloaded from ONCOMINE website (https://www.oncomine.org/resou rce/login.html) [6, 7]and TIMER2.0 website (http:// timer.cistrome.org/) [8-10].The threshold settings of ONCOMINE were followed: p-value of 0.001, fold change of 2.0,gene ranking of top 10%, and data type of all. Expression data of PDCD2L in different clinical stages of cancers were obtained from GEPIA2.0 website (http:// gepia2.cancer-pku.cn/#index) [11].We also downloaded the expression data of PDCD2L in different molecular subtypes of tumor from TISDB website (http://cis.hku. hk/TISIDB/index.php) [12].TISDB is a website for the cross-linking analysis of tumor and immunity, which includes a variety of data, such as the results reported in PubMed database, high-throughput sequencing data, exon and RNA sequencing data of immunotherapy patients, genome, transcription group and clinical char- acteristics of patients downloaded from TCGA, and pub- lic databases.
Survival and prognosis analysis
Overall survival data and diseases free survival data were downloaded from GEPIA2. The median expression of PDCD2L was divided into high PDCD2L expression group and low PDCD2L expression group. Log-rank test was used to analyze the relationship between PDCD2L expression and the survival rate of patients with different tumors.
PDCD2L-related functional enrichment analysis
We analyzed the proteins binding to PDCD2L from STRING website (https://string-db.org/) and the version was 11.0 (archived version) [13].Then we set the follow- ing threshold to obtain the binding proteins: network type of full network, active interaction sources of experi- ments, minium required interaction score of low confi- dence (0.150).The meaning of network edges was set as evidence, also Max number of interactors to show was set as no more than 20 interactors. We found 18 proteins that bind to PDCD2L, which were validated by experi- ment. Furthermore, we analyzed the genes which have similar expression pattern with PDCD2L in pan-cancer by GEPIA2, and the top 100 genes were selected as can- didate genes. GO enrichment analysis and KEGG path- way analysis of PDCD2L, 18 PDCD2L-binding proteins and 100 candidate genes (including the common gene LSM14A) were performed on DAVID website (https:// david.ncifcrf.gov/) [14, 15].
Immune infiltration analysis
TIMER2.0 provides a variety of immune deconvolution methods including TIMER, CIBERSORT, EPIC, MCP- COUNTER, XCELL, TIDE, etc., which provide approach for analyzing the immune, clinical and genetic character- istics of different tumors, comprehensively. The relation- ship between PDCD2L expression and immune infiltration of various cancers was analyzed by TIMER2.0 website, and the correlation between PDCD2L expression and can- cer associated fibroblast (CAF) of various cancers was explored. Moreover, the association between PDCD2L expression and different tumor immune subtypes was ana- lyzed by TISDB website. Different immune types are sum- marized as followed:C1 (wound healing), C2(IFN-gamma dominant), C3(inflammatory), C4(lymphocyte depleted), C5(immunologically), C6(TGF-b dominant).
Single cell sequencing data analysis
CancerSEA (http://biocc.hrbmu.edu.cn/CancerSEA/home. jsp) is a specialized database for single cell sequencing, which can provide different functional status of cancer cells at the single cell level [16].We downloaded the correlation data between PDCD2L expression and different tumor functional
status based on single cell sequencing data from CancerSEA and drew a heatmap. The t-SNE diagrams of all individual cells were obtained directly from the CancerSEA website.
Clinical CRC tissue samples
Totally, 157 cases of paraffin embedding CRC specimens and 140 cases of non-tumor adjacent colorectal mucosa tissues (which included 126 paired CRC specimens) were obtained from our Department of Pathology, the first Affiliated Hospital, Sun Yat-Sen University, Guang- zhou, China, between January 2013 and December 2013. Among them, 97 cases contain available follow-up infor- mation. The histopathology of CRC was determined by two experienced pathologists based on the criteria of the World Health Organization. We also obtained Prior patient consent and approval from the Institutional Research Ethics Committee.
Cell lines and siRNA transfection
Colorectal cancer cell lines including HT29, HCT116, LOVO, RKO, SW480, SW620, and T84 were purchased from Cell Bank of Chinese Scientific Academy in 2017 and 2018 (Shanghai, China), colon mucosal epithelial cell line-NCM460 was purchased from INCELL Com- pany (San Antonio, USA). The above cell lines were cul- tured in Dulbecco’smodified Eagle’s medium (DMEM) (Invitrogen, Carlsbad, CA) with 10% fetal bovine serum (Gibco, LifeTechnologies, CA) and 100 µg/ml penicil- lin-streptomycin. Cells were cultured at 37 ℃ with5% CO2 in a humidified incubator. siRNAs were pur- chased from RIBOBIO (Gunagzhou, China), then trans- fected with Lipofectamine3000reagent. The target sequence of PDCD2L siRNA were as followed: negative control:siN0000001-1-5, si-PDCD2L-1:GCTCAAGAG TGCTAATTTA, si-PDCD2L-2:GGACTATCAGCAGAG AGAA, and si-PDCD2L-3:GGAACAATTCTAGTTTAC A.
RNA extraction and quantitative RT-PCR
CRC cells or fresh tissues were collected and added with Trizol reagent according to the manufacturer’s guide- lines. RNA concentration was measured by nanodrop one, and then reverse transcribed into cDNA. Then we performed quantitative RT-PCR by SYBR Premix ExTaq II (Takara, Osaka,Japan). GAPDH was used as normaliza- tion. The primers of quantitative RT-PCR are purchased from SANGON BIOTECH (Shanghai, China) and the sequences were as followed: PDCD2L-forward: GCG AATTGCTGCTTGTCAGG, PDCD2L-reverse: GAG CTCGGTGACTTCTGATGTAGG,
GAPDH-forward: CAGGAGGCATTGCTGATGAT, GAPDH-reverse:
GAAGGCTGGGGCTCATTT. All experiments were performed three times in triplicate.
Western blot
Cells were collected from tissues using lysis buffer. Then we added 40 µg of protein per sample for SDS- PAGE separation and blot onto PVDF membranes. After blocking by 5% milk for 1 h at room temperature, membranes were incubated with primary antibodies PDCD2L(#A7394, Abclonal), P53(#10,442-1-AP, pro- teintech), c-Myc(#9402, Cell Signaling Technology), and GAPDH(#5174, Cell Signaling Technology) overnight at 4 ℃. Then the membranes were incubated with HRP- linked secondary antibody (#7074, Cell Signaling Tech- nology) at room temperature for 1 h. Finally, we obtained the signal from chemiluminescence detection reagent (Millipore).
Immunohistochemistry staining and evaluation
Immunohistochemistry staining was performed as we previously described [17].The working concentration of PDCD2L(#A7394, Abclonal) was 1:200. The immunohis- tochemical score was obtained by the percentage score of positive tumor cells x intensity score. Among them, the percentage of positive tumor cells was scored from 0-1. The positive intensity was identified as 0 as negative, weak positive as 1, moderate positive as 2, and strong positive as 3. The immunohistochemical score was com- pleted by two experienced pathologists.
Apoptosis assay
The cells were digested by trypsin without EDTA, washed twice by phosphate buffered saline (PBS). Then we per- formed apoptosis assay using Annexin V-APC/PI Apop- tosis Detection Kit (#KGA1030-50, KeyGen, Nanjing, China) according to the manufacturer’s guidelines, and detected on the flow cytometry. The experiments were performed three times in triplicate.
Proliferation assays
CRC cell viability were performed by using Cell Count- ing Kit-8 (CCK-8) (#B34304, bimake). 1 x 103/well of cells were collected and seeded into a 96 well plate. Then absorbance values were measured every day for 5 days according to manufacturer’s protocol. DNA syn- thesized rate of CRC cells (1 x 104/well) was analyzed by 5-ethynyl-20-deoxyuridine (EdU) assay kit (#C10310, Ribobio, Guangzhou, China) following the manufactur- er’s guidelines. Cell proliferation activity were assessed by the ratio of EDU positive cells (red fluorescence) to
Hoechest-stained cells (blue fluorescence). The experi- ments were performed three times in triplicate.
Statistical analysis
Unpaired t-tests were applied to compare the differ- ence between two groups and data were presented as the mean ±standard deviation. Spearman’s rank corre- lation coefficient was applied to evaluate the correlation between two groups. The association between prognosis of patients and PDCD2Lexpression levels was assessed using Kaplan-Meier method. p <0.05 was considered as a statistically significant difference.
Results
Aberrant expression of PDCD2L in pan-cancer
Firstly, we analyzed PDCD2L expression in pan-cancer through ONCOMINE website. The database provided gene expression of various cancers and correspond- ing normal samples. Results revealed thatPDCD2Lwas up-regulated in CRC, gastric cancer, kidney cancer and ovarian cancer while down-regulated in other cancers (Fig. 1A). Furthermore, we validated PDCD2L expres- sion in pan-cancer by TIMER2.0. Consistent with our above finding, PDCD2L expression was increased in BLCA, BRCA, Cholangio carcinoma (CHOL), Colon adenocarcinoma(COAD), Esophageal carcinoma (ESCA), Head and Neck squamous cell carcinoma (HNSC), HNSC-HPVpos, KICH, KIRC, KIRP, LIHC, Lung adenocarcinoma (LUAD), LUSC, Prostate adeno- carcinoma (PRAD), Rectum adenocarcinoma (READ), STAD, Thyroid carcinoma (THCA) and Uterine Corpus Endometrial Carcinoma (UCEC) (Fig. 1B).To explore the relationship between PDCD2L expression and clini- cal stage of pan-cancer, we performed further analysis by GEPIA2. The result suggested that PDCD2L expression was significantly associated with clinical stages of ACC, KIRC, KIRP and LUSC (Fig. 1C).While PDCD2L expres- sion was not significantly associated with clinical stages of other cancers including BLCA, BRCA, CESC, CHOL, COAD, Lymphoid Neoplasm Diffuse Large B-cell Lym- phoma (DLBC), ESCA, HNSC, KICH, LIHC, LUAD, Ovarian serous cystadenocarcinoma (OV),Pancreatic adenocarcinoma (PAAD), READ, Skin Cutaneous Mela- noma (SKCM), STAD, TGCT, THCA, UCEC and Uterine Carcinosarcoma (UCS) (data not shown).We also per- formed another analysis through TISDB, which revealed that PDCD2L expression was significantly associated with the molecular subtype of ACC, BRCA, ESCA, Glio- blastoma multiforme (GBM), HNSC, KIRP, LGG, LUSC, OV, PRAD, STAD and UCEC (Fig. 1D).While the expres- sion of PDCD2L was not associated with the molecu- lar subtype of COAD, LIHC, pheochromocytoma and
paraganglioma(PCPG), READ and SKCM (Additional file 1: Figure S1).Taken together, compared with adjacent normal tissues, PDCD2L expression was up-regulated in various cancers and PDCD2Lmight be serve as an onco- gene in these cancers.
Prognostic analysis of PDCD2L expression in pan-cancer
To explore the relationship between PDCD2L expression and prognosis of patients in pan-cancer, we performed survival analysis by GEPIA2.The results suggested that high PDCD2L expression indicated poor overall sur- vival rate in ACC (P=0.04), KICH (P=0.0075), LAML (P=0.0032), LGG (P=0.013), LIHC (P=0.044), MESO (P=0.0077), and UVM(P=0.016),while highPDCD2L expression revealed favorable overall survival rate in UCEC(P=0.039) (Fig. 2A and B). Moreover, high PDCD2L expression also indicated unfavorable diseases free survival in ACC (P=0.039), BLCA (P=0.048), CESC (P=0.014), KIRC (P=0.031), KIRP (P=0.041), LGG (P=0.043), LIHC (P=0.021), and UVM (P=0.016). While high PDCD2L expression suggested favorable dis- eases free survival in PAAD (P=0.043) (Fig. 2C and D). We also noticed that PDCD2L expression was not asso- ciated with the overall survival of BLCA, BRCA, CESC, CHOL, COAD, DLBC, ESCA, GBM, HNSC, KIRC, KIRP, LUAD, LUSC, OV, PAAD, PCPG, PRAD, READ, SARC, SKCM, STAD, TGCT, THCA, Thymoma (THYM) and UCS (data not shown). Furthermore, PDCD2L expres- sion was not associated with the diseases free survival of BRCA, CHOL. COAD, DLBC, ESCA, GBM, HNSC, KICH, LAML, LUAD, LUSC, MESO, OV, PCPG, PRAD, READ, SARC, SKCM, STAD, TGCT, THCA, THYM, UCEC, and UCS (data not shown).
Co-expression network of PDCD2L and enrichment pathway analysis
Our above results suggested that PDCD2L might play an oncogene role in pan-cancer and could be used as a prognostic marker. However, the molecular mecha- nism of PDCD2L in tumorigenesis remains unknown. To explore the co-expression network and enrichment pathways of PDCD2L in pan-cancer, firstly, we predicted the binding proteins of PDCD2L by STRING website, which were validated by experiment. The result revealed that there were 18 proteins includingFXR2, LSM14B, LSM14A, FXR1, NUFIP1, SRP14, PRMT3, SLC35B4, SLX4IP, RPS2, BMX, FMR1, ITGB1BP2, MAEL, MRPS5, NAP1L5, PCBP3, and PDCD1binding to PDCD2L (Fig. 3A).Then we obtained the top 100 genes that closely related to PDCD2L from GEPIA2.By crossing two sets of data, we found that LSM14A was the only common gene in both groups. Further, GO and KEGG enrich- ment analysis were performed for the 117 gene. GO
A
B
Cancer
Normal
**
**
Analysis Type by Cancer
PDCD2L Expression Level (log2 TPM)
6.
Bladder Cancer
Brain and CNS Cancer
Breast Cancer
Cervical Cancer
Colorectal Cancer
15
4
Esophageal Cancer
Gastric Cancer
1
Head and Neck Cancer
Kidney Cancer
1
Leukemia
2
Liver Cancer
Lung Cancer
2
Lymphoma
Melanoma
Myeloma
Other Cancer
1
ACC. Tumor
BLCA. Tumor
BLCA.Normal
BRCA. Tumor
BRCA.Normal
BRCA-Basal. Tumor
BRCA-Her2. Tumor
BRCA-Luminal. Tumor
CESC. Tumor
CHOL. Tumor
CHOL.Normal
COAD. Tumor
COAD.Normal
DLBC. Tumor
ESCA. Tumor
ESCA. Normal
GBM. Tumor
HNSC. Tumor
HNSC.Normal
HNSC-HPVpos. Tumor
HNSC-HPVneg. Tumor
KICH. Tumor
KICH. Normal
KIRC. Tumor
KIRC. Normal
KIRP. Tumor
KIRP.Normal
LAML. Tumor
LGG. Tumor
LIHC. Tumor
LIHC. Normal
LUAD. Tumor
LUAD.Normal
LUSC. Tumor
LUSC.Normal
MESO. Tumor
OV.Tumor
PAAD. Tumor
PCPG. Tumor
PRAD. Tumor
PRAD.Normal
READ. Tumor
READ.Normal
SARC. Tumor
SKCM. Tumor
SKCM.Metastasis
STAD. Tumor
STAD.Normal
TGCT.Tumor
THCA. Tumor
THCA.Normal
THYM. Tumor
UCEC. Tumor
UCEC.Normal
UCS. Tumor
UVM. Tumor
Ovarian Cancer
1
Pancreatic Cancer
Prostate Cancer
Sarcoma
Significant Unique Analyses Total Unique Analyses
20
1
260
1
5
10
10
5
1
%
C
ACC
P=4.3e-04
BRCA
P=9.5e-32
ESCA
P=1.84e-02
GBM
P=4.22e-03
5
6
6
5
4
4
4
3
-
4
İ
/
1
I
3
₿
3
L
:
₿
·
2
C
2
2
2
1
1
9
CIMP-high
CIMP-inter mediate
CIMP-low
Basal
Her2
LumA
LumB
Normal
CIN
ESCC
GS
HM-SNV
HM-indel
Classic-like
G-CIMP-high
G-CIMP-low
LGm6-GBM
Mesenchymal-like
HNSC
P=1.28e-02
KIRP
P=1.3e-04
LGG
P=8.33e-48
LUSC
P=3.66e-02
Expression(log2CPM)
5
5
6
4
4
4
3
3
.
I
!
S
i
3
i
:
4
-
S
1
1
2
2
H
!
S
!
.
₹
2
1
1
1
Atypical
Basal
Atypical
Mesenchymal
C1
C2a
C2b
C2c-CIMP
Classic-like
Codel
G-CIMP-high
G-CIMP-low
Mesenchymal-like
PA-like
basal
classical
primitive
secretory
OV
P=1.85e-02
5
PRAD
P=3.88e-02
STAD
P=2.88e-12
UCEC
P=3.71e-08
6
4
6
6
$
8
I
:
5
3
8
6
U
8
8
O
4
8
i
I
8
2
8
$
A
9
8
2
2
S
1
0
2
Differentiated
Immunoreactive
Mesenchymal
Proliferative
ERG
ETV1
ETV4
FLI-1
SPOP
FOXA1
IDHI
other
CIN
EBV
GS
HM-SNV
HM-indel
CN-HIGH
CN-LOW
MSI
POLE
Molecular Subtype
A
log 10(HR)
0.5
ACC BLCA
0.0
BRCA
CESC
CHOL
COAD
DLBC
ESCA
GBM
HNSC
KICH
KIRC
KIRP
LAML
LGG
LIHC
LUAD
LUSC
MESO
OV
PAAD
PCPG
PRAD
READ
SARC
SKCM
STAD
TGCT
THCA
THYM
UCEC
UCS
UVM
-0.5
B
ACC
Overall Survival
KICH
Overall Survival
LAML
Overall Survival
LGG
Overall Survival
0
LOW PDCD2L Group
0
:
2
High’PDCD2L Group
Low PDCD2L Group
9
High PDCD2L Group
High PDCD2L Group
Low PDCD2L Group
Logrank p=1e-04 HR(high)=5.6
“Logrank p=0.0075
High PDCD2L Group
HR(high)=10
Logrank p=0.0032 HR(high)=2.3
Logrank p=0.013 HR(high)=1.6
:
P(HR)=0.00053
2
P(HR)=0.03
0.8
P(HR)=0.0041
2
p(HR)=0.014
Percent survival
n(high)=38
n(low)=38
Percent survival
n(high)=30
“How) 3º
Percent survival
n(high)=53
Percent survival
0.6
0.6
n(low)=53
n(high)=257
0.6
n(low)=257
IL
0.4
0.4
0.4
2
0
S
2
8
8
0.0
S
0
50
100
150
0
50
100
150
0
20
40
60
80
0
50
100
150
200
Months
Months
Months
Months
LIHC
Overall Survival
MESO
Overall Survival
UCEC
Overall Survival
UVM
Overall Survival
9
Low High PDCD2L Group
0
Low
2
High PDCD2L Group
Low Group High PDCD2L Group
2
LOW PDCD2L’
Logrank p=0.044
HR(high)=1.4
Logrank p=0.0077 HR(high)=1.9
Logrank p=0.039
High PDCD2L Group
0
p(HR)=0.045
8
p(HR)=0.0084
O
HR(high)=0.46
Logrank p=0.016
p(HR)=0.044
0.8
HR(high)=3.1
p(HR)=0.021
Percent survival
n(high)=182
n[low)=182
Percent survival
n(high)=41
n(low)=41
Percent survival
n(high)=86
n(low)=86
Percent survival
n[high)=39
0.5
0.6
0.6
0.6
n(low)=39
0.4
0.4
0.4
0.4
2
0
2
0
0.0
S
0.0
A
0
20
40
60
80
100
120
0
20
40
60
80
0
20
40
60
80
100
120
140
0
20
40
60
80
Months
Months
Months
Months
C
log 10(HR)
0.25
ACC BLCA
0.00
BRCA
CESC
CHOL
COAD
DLBC
ESCA
GBM
HNSC
KICH
KIRC
KIRP
LAML
LGG
LIHC
LUAD
LUSC
MESO
OV
PAAD
PCPG
PRAD
READ
SARC
SKCM
STAD
TGCT
THCA
THYM
UCEC
UCS
UVM
-0.25
D
ACC 0
Disease Free Survival
BLCA
Disease Free Survival
CESC
Disease Free Survival
Low PDCD2L Group
2
High PDCD2L
Low
0
Low PDCD2L Group
Logrank p=0.039
High PDCD2L Group
0.8
HR(high)=2
Logrank p=0.048
High PDCD2L
P(HR)=0.041
0.8
HR(high)=1.4
Logrank p=0.014
p(HR)=0.049
0.8
HR(high)=2.1
p(HR)=0.016
Percent survival
n(high)=38
Percent survival
n(high)=201 m(Tów)=201
Percent survival
megh) 1.46
0.6
n(low)=38
0.6
0.6
n(low)=146
0.4
0.4
0.4
5
0.2
5
0.0
0.0
0.0
0
50
100
150
0
50
100
150
0
50
100
150
200
Months
Months
Months
KIRC
Disease Free Survival
RP
Disease Free Survival
LGG
Disease Free Survival
9
Low
9
High PDCD2L Group
LOW PDCD2L’Group
9
High PDCD2L Group
Low PDCD2L Group
Logrank p=0.031
Logrank p=0.041
High PDCD2L Group
Logrank p=0.043
0.8
HR(high)=1.5
p(HR)=0.033
0.8
HR(high)=1.8
0.8
HR(high)=1.4
n(high)=258
p(HR)=0.044
Percent survival
Percent survival
p(HR)=0.044 n(high)=141
Percent survival
n(high)=257
0.6
(low)=257
0.6
n(low)=141
0.6
η(low)=257
0.4
0.4
0.4
0.2
0.2
8
0.0
0.0
0.0
0
20
40
60
80
100
120
140
0
50
100
150
200
0
50
100
150
Months
Months
Months
LIHC 9.
Disease Free Survival
PAAD
Disease Free Survival
UVM Disease Free Survival
Low PDCD2L Group
1
High PDCD2L
Low
2
Low PDCD2L Group
Logrank p=0.021 HR(high)=1.4
High PDCD2L Group
Logrank p=0.043
High
Logrank p=0.016
0.8
p(HR)=0.021
0.8
HR(high)=0.63
p(HR)=0.045
3
HR(high)=3.1
n(high)=182 n(low)=182
n(high)=88 n(low)=88
p(HR)=0.022
Percent survival
Percent survival
Percent survival
n(high)=39
0.6
0.6
0.6
now)=39
0.4
0.4
0.4
0,2
0.2
0.2
0.0
0.0
0
0
20
40
60
80
100
120
0
20
40
60
80
0
20
40
60
80
Months
Months
Months
Fig. 2 Prognostic value of PDCD2L expression in pan-cancer. Relationship between PDCD2L expression in different tumors from TCGA and overall survival (A, B) or diseases free survival (C, D) by GEPIA2. Only positive data of survival map and Kaplan-Meier curves were shown
A
LSM14B
FXR1
~
RPS2
FXR2
NUFIP1
SRP14
LSM14A
PRMT3
FMR1
4
MRPS5
PDCD2L
SLC35B4
SLX4IP
NAP1L5
ITGB1BP2
DẠO
PDCD1
BMX
PCBP3
MAEL
B
C
Biological Process
Cellular Component
anaphase-promoting complex-dependent catabolic process
U1 snRNP
chromosome segregation
condensed chromosome kinetochore
CENP-A containing nucleosome assembly
membrane
gene silencing by RNA
small nucleolar ribonucleoprotein complex
mitotic spindle organization
cytoplasm
mRNA splicing, via spliceosome
box C/D snoRNP complex
rRNA processing
nucleus
sister chromatid cohesion
chromosome, centromeric region
mitotic nuclear division
nucleolus
cell division
nucleoplasm
0
5
10
15
0
5
10
15
20
25
-LOG10 (P value)
-LOG10 (P value)
D
E
Molecular Function
KEGG Pathways
mRNA binding
snoRNA binding
p53 signaling pathway
ATP binding
Ribosome
methyltransferase activity
Progesterone-mediated oocyte maturation
DNA-directed RNA polymerase activity
RNA polymerase
centromeric DNA binding
Pyrimidine metabolism
U1 snRNP binding
Ribosome biogenesis in eukaryotes
protein binding
Spliceosome-
RNA binding
RNA transport-
poly(A) RNA binding
Cell cycle
0
5
10
15
20
0
1
2
3
4
5
-LOG10 (P value)
-LOG10 (P value)
Fig. 3 Co-expression network of PDCD2L and enrichment pathway analysis. A The binding proteins of PDCD2L by STRING website. B Biological process, C cellular component, D molecular function, E KEGG pathways based on PDCD2L binding proteins and interactive genes
enrichment indicated that these genes were significantly related with poly(A) RNA binding, RNA binding, protein binding, U1 snRNP binding, centromeric DNA binding, DNA-directed RNA polymerase activity, methyltrans- ferase activity, ATP binding, snoRNA binding, mRNA binding and others (Fig. 3B-D). Furthermore, we found that PDCD2Lwas involved in tumorigenesis through cell cycle, RNA transport, Spliceosome, Ribosome biogenesis in eukaryotes, Pyrimidine metabolism, RNA polymerase, Progesterone-mediated oocyte maturation, Ribosome, and p53 signaling pathway (Fig. 3E).
Negative correlation between PDCD2L expression and CAF
The tumor microenvironment (TME) provides a cross- talk between tumor cells and the microenvironment and TME is composed of four major components: immune component, vascular component, extracellular matrix and stromal component. Immune component includes many immune cells such as T cells and B cells, while stro- mal component is composed of CAF and mesenchymal stem cells [18].Recently multiple studies have highlighted the vital role of CAF in cancer progression and immune response [19]. To elucidate the role of PDCD2L in TME, we analyzed the correlation between PDCD2L expres- sion and TME components in pan-cancer by TIMER 2.0 website. We obtained a consistent result that PDCD2L expression was negatively related with CAF in BLCA, BRCA, BRCA-Basal, LUSC, SARC, STAD and TGCT by EPIC, MCPCOUNTER, XCELL and TIDE algorithms (Fig. 4A and B). To further investigate the underlying mechanism of the correlation between PDCD2L expres- sion and CAF, we analyzed the expression markers of CAF in pan-cancer. We found that PDCD2L expres- sion was significantly associated with immune subtype including C1(wound healing), C2(IFN-gamma domi- nant), C3(inflammatory), C4(lymphocyte depleted), C5(immunologically), C6(TGF-b dominant).
of BLCA, BRCA, COAD, KICH, KIRC, KIRP, LGG, LIHC, LUAD, LUSC, OV, PAAD, PRAD, SARC, STAD, TGCT and UCEC (Fig. 4C). While the expression of PDCD2L in the immune subtype of ACC, CESC, CHOL, ESCA, GBM, HNSC, MESO and PCPG was not statisti- cally different (data not shown).
Expression pattern of PDCD2L in single cell and its relationship with cancer functional status
Since the complexity of tumor cells, single-cell transcrip- tomic sequencing is a key technique to analyze diverse cancer cells, immune cells, endothelial cells and stromal cells [20]. In order to verify the expression of PDCD2L in single cell in different cancers and its relationship with tumor functional status, we found that PDCD2L
expression in prostatic cancer (PC) was significantly positively associated with apoptosis, PDCD2L expres- sion in renal cell carcinoma (RCC) was significantly positively associated with cycle, and PDCD2L expres- sion in Acute myeloid leukemia(AML) was significantly positively associated with invasion through CANCER- SEA website (Fig. 5A). Figure 5B showed the relation- ship between PDCD2L expression and apoptosis in PC, PDCD2L expression and cell cycle in RCC, and PDCD2L expression and invasion in AML.PDCD2L expression profiles were shown in single cells of PC, RCC and AML by T-SNE diagram (Fig. 5C).The results suggest that PDCD2L might play a crucial role in the process of can- cer progression.
High PDCD2L expression in our CRC samples and down-regulation of PDCD2L expression promotes apoptosis in CRC cells
According to the above results, PDCD2L was highly expressed in CRC tissues compared with non-tumor adjacent tissues. In order to validate PDCD2L expres- sion in our CRC samples and study the role of PDCD2L in CRC progression. Firstly, we performed IHC to detect PDCD2L expression in 126 pairs of paraffin-embed- ded tissues of CRC and non-tumor adjacent colorectal mucosa tissues. Our result showed that positive PDCD2L signal was located in cytoplasm of carcinoma cell in our CRC samples (Fig. 6A). And PDCD2L was highly expressed in CRC tissues compared with non-tumor colorectal mucosa tissues (Fig. 6B). To analyze the cor- relation between PDCD2L expression and clinicopatho- logical characteristics of CRC patients, we divided our samples were into two groups according to the median (score as 2.7) of PDCD2L expression, among which the low PDCD2L expression group was less than 2.7 and high PDCD2L expression group was above or equal 2.7.Also, our study showed that PDCD2L expression was signifi- cant associated with histological differentiation and sex of CRC patients, while PDCD2L expression was not differ in other characteristics such as age, tumor size, vascular tumor thrombus, perineural invasion, T classi- fication, N classification, M classification and TNM stage (Table 1). However, PDCD2L expression was not associ- ated with the overall survival and diseases free survival of CRC patients (data not shown). By collecting 10 pairs of fresh CRC tissues and corresponding adjacent tissues for qPCR and WB detection, we found that the transcrip- tion level and protein level of PDCD2L in CRC tissues were significantly higher than those in non-tumor adja- cent colorectal mucosa tissues (Fig. 6C and D). We also detected PDCD2L mRNA and protein expression in CRC cell lines and colon mucosal epithelial cell line NCM460.
A
MCPCOUNTER
B
6 $ a 0 BRCA 5 - - PDCD2L Expression Level (log2 TPM) PDCD2L Expression Level (log2 TPM) PDCD2L Expression Level (log2 TPM) PDCD2L Expression Level (log2 TPM) LUSC 5 - 1 S -
Purity
Cancer associated fibroblast_TIDE
. PDCD2L Expression Level (log2 TPM) PDCD2L Expression Level (log2 TPM) PDCD2L Expression Level (log2 TPM) PDCD2L Expression Level (log2 TPM) S A 3 1
Purity
Cancer associated fibroblast_TIDE
8
p > 0.05
XCELL TIDE
A
D - 2 240.04
Rho - 0.169
1
p = 2.55€-02
Rho - 0.253
EPIC
p = 7.60€-04
p ≤ 0.05
ACC (n=79)
BRCA-Basal
BLCA (n=408)
BRCA (n=1100)
€
BRCA-Basal (n=191)
BRCA-Her2 (n=82)
X
*
BRCA-LumA (n=568)
0.25
0.50
0.75
1.00-0.25
0.00
0.25
0.25
0.50
Infiltration Level
0.50
0.75
1.00
-0.2
-0.1
0.0
0.1
0.2
BRCA-LumB (n=219)
Purity
Purity
Infiltration Level
CESC (n=306)
CHOL (n=36)
Purity
Cancer associated fibroblast_XCELL
Purity
Cancer associated fibroblast_TIDE
Cancer associated fibroblast
COAD (n=458)
Rhor- 0.159
..
Rho - 9.265 p = 1.9de-17
91.42663
Rho - 0211 p = 8.064-08
DLBC (n=48)
ESCA (n=185)
BRCA-LumA
GBM (n=153)
X
HNSC (n=522)
HNSC-HPV- (n=422)
HNSC-HPV+ (n=98)
X
KICH (n=66)
KIRC (n=533)
0.25
0.50
0.3
Purity
0.75
1.00 0.0
0.1
0.2
0.25
0.50
0.75
1.00
0.2
0.0
0.2
KIRP (n=290)
Infiltration Level
Purity
Infiltration Level
LGG (n=516)
Purity
Cancer associated fibroblast_TIDE
LIHC (n=371)
Purity
Cancer associated fibroblast_EPIC
Rua - 8212
.4
6159.83
Rho -0,339
Rho - 0.240 p 1.076-04
Rho
LUAD (n=515)
1
LUSC (n=501)
MESO (n=87)
0
OV (n=303)
SARC
-1
PAAD (n=179)
PCPG (n=181)
PRAD (n=498)
READ (n=166)
SARC (n=260)
0.00
0.25
0.50
0.75
1.00
0.2
0.0
0.2
0.25
0.50
0.75
1.000.00
0.25
0.50
0.75
Infiltration Level
1.00
Purity
Purity
Infiltration Level
SKCM (n=471)
SKCM-Metastasis (n=368)
Purity
Cancer associated fibroblast_XCELL
Purity
cer associated fibroblast_MCPCOUNT
SKCM-Primary (n=103)
Rho - 0.088
P-5.69668
5
DO 2.386-19
*
STAD (n=415)
TGCT (n=150)
5
THCA (n=509)
STAD
TGCT
THYM (n=120)
UCEC (n=545)
UCS (n=57)
UVM (n=80)
:
0.25
0.50
0.75
1.00 0.0
0.2
0.4
0.6
0,25
0.50
1.00 0
20000
40000
Purity
Infiltration Level
0.75
Purity
Infiltration Level
C
BLCA
P=le-04
BRCA
P=2.33e-34
COAD
P=2.08e-03
KICH
P=3.73e-03
6
6
6
3
₿
4
H
H
1
4
4
H
H
H
2
!
H
H
H
H
i
!
I
!
1
2
2
!
8
2
8
0
C1
C2
C3
C4
C6
C1
C2
C3
C4
C6
C1
C2
C3
C4
C6
C1
C3
C4
C5
KIRC
P=8.93e-11
KIRP
P=2.43e-06
LGG
P=2.92e-05
LIHC
P=4.23e-06
6
4
6
4
4
4
Expression(log2CPM)
2
!
!
8
3.
i
H
2
i
8
₿
3
İ
1
H
!
2
2
:
H
0
0
1
0
C1
C2
C3
C4
C5
C6
C1
C2
C3
C4
C5
C6
C3
C4
C5
C6
C1
C2
C3
C4
C6
LUAD
P=5.38e-18
LUSC
P=6.26e-06
Ov
P=5.73e-04
P=1.64e-02
5
PAAD
6
6
6
4
4
H
H
!
U
4
H
i
!
!
4
8
H
8
3
8
H
U
i
2
2
8
P
H
2
2
1
C1
C2
C3
C4
C6
C1
C2
C3
C4
C6
C1
C2
C3
C4
C1
C2
C3
C4
C6
PRAD
P=1.53e-14
SARC
P=1.09e-02
STAD
P=8.27e-13
TGCT
P=9.02e-07
UCEC
P=4e-03
5
4
6
6
4
6
i
!
:
I
A
B
I
!
A
4
!
!
H
8
4
3
2
8
4
2
!
8
B
H
H
H
2
2
2
0
C1
C2
C3
C4
C1
C2
C3
C4
C6
C1
C2
C3
C4
C6
C1
C2
C3
C4
C1
C2
C3
C4
C6
Immune Subtype
Fig. 4 Negative correlation between PDCD2L expression and CAF. A and B correlation between PDCD2L expression and cancer associated fibroblasts was performed by TIMER2.0. C PDCD2L expression level in immune subtypes in BLCA, BRCA, COAD, KICH, KIRC, KIRP, LGG, LIHC, LUAD, LUSC, OV, PAAD, PRAD, SARC, STAD, TGCT and UCEC based on TISDB
A
Angiogenesis
Apoptosis
CellCycle
Differentiation
DNAdamage
DNArepair
Hypoxia
Inflammation Invasion
B
PDCD2L
EMT
Metastasis
Proliferation
Quiescence
Stemness
Correlation 0.6
P value *
AML
*
Apoptosis
BRCA
AST
GBM
PDCD2L
Glioma
Correlation 0.54
HNSCC
P value *
RCC
*
Cell cycle
LUAD
NSCLC
PC
*
PDCD2L
MEL
Correlation 0.52
P value *
Invasion
-0.5
0
0.5
C
PC
RCC
AML
Expression distribution with t-SNE plot
Expression distribution with t-SNE plot
Expression distribution with t-SNE plot
7.5
400
15
5
10
200
2.5
5
· t …
ISNEZ
ISNEZ
ISNE2
0
0
0
-2.5
-5
-200
-5
-10
-7.5
-15
.
-4
-2
0
2
4
6
-400
-300
-200
-100
0
100
200
300
400
-7.5
-5
-2.5
0
2.5
5
7.5
ISNE1
ISNE1
ISNE1
The results showed that the transcription level and pro- tein level of PDCD2L in CRC cell lines were significantly higher than those in NCM460 (Fig. 6E and F).
Next, we performed functional experiment in HT29and SW480 cell lines, which had high expression of PDCD2L.PDCD2L mRNA expression decreased in HT29 transfected with three different PDCD2L siRNA by qPCR, respectively. The effect of si-PDCD2L-3 was the most significant (Fig. 7A). Therefore, we selected si- PDCD2L-3for functional experiments. The transcription level and protein level of PDCD2L in HT29 and SW480 transfected with si-PDCD2L-3decreased significantly by (Fig. 7B and C). While the above single cell sequenc- ing results suggested that PDCD2L expression was closely related with tumor apoptosis, we focused on the effect of PDCD2L on apoptosis of CRC cells. Apopto- sis assay showed that PDCD2L expression knockdown significantly increased the total apoptosis rate of HT29 and SW480, respectively (Fig. 7D-F). To investigate the effect of PDCD2L on celluar proliferation of CRC cells, we performed CCK8 and EdU assays using siRNA. Inter- estingly, CCK8 assay showed that that PDCD2L knock- down significantly enhanced the proliferation of HT29 and SW480 compared with the control groups (Fig. 7G and H), which were verified by EdU assay (Fig. 7I and
J). Our result revealed that downregulation of PDCD2L enhanced total apoptosis rate and proliferation of CRC cells, we hypothesized that PDCD2L might be involved in apoptosis induced proliferation (AiP) on the progression of CRC. Since KEGG results suggested that PDCD2L was significantly associated with P53 signaling pathways, our result revealed that PDCD2L knockdown inhibited P53 expression and increased c-MYC expression by western blot assay (Fig. 7K).
Discussion
Pan-cancer analysis provides a comprehensive under- standing on the molecular aberrations of various cancers and is helpful for finding biomarkers in early diagno- sis and target therapies of cancers. Leiserson et al. have identified 14 remarkable mutated subnet works by inves- tigating pan-cancer data of The Cancer Genome Atlas (TCGA), which includes many noted cancer signaling pathways [21]. Aran et al. systematically analyzed the purity of pan-cancer based on the Cancer Genome Atlas, then identified a novel immunotherapy gene signature for many cancers [22]. Ma et al. provided new insight into pan-cancer analysis of 1,699 paediatric cancers, which present a general genomic landscape for paediatric leu- kaemias and solid tumors [23]. Since cancer-associated
A
Normal
Tumor
B
4
200X
PDCD2L IHC Score
3
2
1
400X
0
Normal(N=126)
Tumor(N=126)
C
Relative PDCD2L mRNA level
D
1.5
*
PDCD2L
1N
1T
2N
2T
3N
3T
4N
4T
5N
5T
6N
6T
1.0-
GAPDH
0.5.
7N
7T
8N
ST
9N
9T
10N
10T
PDCD2L
0.0
T
T
Normal(N=10)
Tumor(N=10)
GAPDH
E
F
Relative PDCD2L mRNA level
40
30-
NCM460
**
HT29
HCT116
LOVO
RKO
SW480
SW620
1
T84
20
…
*
PDCD2L
10-
GAPDH
0
NCM460
HT29
HCT116
LOVO
RKO
SW480
SW620
T84
Fig. 6 High PDCD2L expression in our CRC samples. A Positive PDCD2L signal was located in cytoplasm of carcinoma by IHC. B PDCD2L was highly expressed in our 126 pairs of CRC and corresponding non-tumor colorectal tissues by IHC. C and D transcription level and protein level of PDCD2L in fresh CRC tissues and adjacent non-tumor colorectal mucosa tissues. E and F transcription level and protein level of PDCD2L in CRC cell lines and NCM460. ( ** P <. 01; *** P <. 001; **** P <. 0001)
DNA methylation may affect gene expression, Saghafinia et al. analyzed the changes of DNA methylation in pediat- ric tumors, which provided a pan-cancer architecture of aberrant DNA methylation [24].Priestley et al. performed a pan-cancer analysis of metastatic solid tumor genomes, and found that the difference of mutational map and driver genes between metastatic tumor genomes and pri- mary tumors genomes is not obvious [25]. These studies have showed the correlation between tumorigenesis and genome, transcriptome and epigenomics in pan-cancer. The expression of PDCD2L did not significantly affect apoptosis in HEK293T cells by different treatments [2]. Augmented levels of PDCD2L protein inhibit
proliferation of HEK293T cells and block cell cycle pro- gression at S phase [3]. PDCD2L overexpression in pan- creatic beta-cell enhanced palmitate-induced apoptotic rate [4]. PDCD2L is evolutionarily conserved in develop- ment [5].Since the role of PDCD2L in cancer progression remains unclear, we systematically analyzed the expres- sion and prognosis value of PDCD2L in pan-cancer. Our study revealed that PDCD2L was highly expressed in various cancers compared with the corresponding non- tumor tissues. The result suggests PDCD2L might be as oncogene in these cancers.
Several studies of pan-cancer analysis have addressed the significance of aberrant expressed genes in the
| Characteristics | low-PDCD2L No.(%) | high-PDCD2L No.(%) | P value |
|---|---|---|---|
| Age(years) | 0.083 | ||
| Mean ± SD | 56.2±14.1 | 59.4±12.2 | |
| <60 | 45(60.8) | 39(47.0) | |
| ≥60 | 29(39.2) | 44(53.0) | |
| Sex | 0.002 | ||
| Male | 56(75.7) | 43(51.8) | |
| Female | 18(24.3) | 40(48.2) | |
| Tumor size(cm) | 0.519 | ||
| Mean± SD | 4.9±2.4 | 4.2± 1.5 | |
| <5 | 42(58.3) | 52(63.4) | |
| ≥5 | 30(41.7) | 30(36.6) | |
| Histological differentiation | 0.041 | ||
| Poorly | 18(24.7) | 10(12.0) | |
| Moderately and well | 55(75.3) | 73(88.0) | |
| T classification | 0.332 | ||
| T1+T2 | 10(13.5) | 16(19.3) | |
| T3+T4 | 64(86.5) | 67(80.7) | |
| N classification | 0.585 | ||
| N0 | 36(48.6) | 44(53.0) | |
| N1+N2 | 38(51.4) | 39(47.0) | |
| M classification | 0.851 | ||
| M0 | 69(93.2) | 78(94.0) | |
| M1 | 5(6.8) | 5(6.0) | |
| TNM stage | 0.463 | ||
| I+II | 34(45.9) | 43(51.8) | |
| III+ IV | 40(54.1) | 40(48.2) | |
| Vascular tumor thrombus | 0.56 | ||
| Absent | 64(86.5) | 69(83.1) | |
| Present | 10(13.5) | 14(16.9) | |
| Perineural invasion | 0.734 | ||
| Absent | 57(77.0) | 62(74.7) | |
| Present | 17(23.0) | 21(25.3) |
development or progression of CRC. To evaluate the role of antiapoptotic BCL-2 proteins on preclinical CRC models, Scherr et al. have found that BCL-XL is overactivated in CRC, which provides a promising therapeutic target for CRC by analyzing a pan-cancer cohort, [26].High ANKRD6 expression is correlated with poor prognosis of colon cancer based on a pan- cancer analysis, which suggests ANKRD6 plays an important role in the progression of colon cancer [27]. According to a pan-cancer analysis, RRM2ishighlyex- pressed in many cancers, Further experiment has found that RRM2 is significantly upregulated in CRC.RRM2 might serve as a novel potential target for CRC therapy
[28]. Furthermore, we also detected PDCD2L expres- sion in our CRC samples and found that the expression of PDCD2L is significantly higher in CRC tissues than that in corresponding non-tumor colorectal mucosa tissues. The relationship between the expression of PDCD2L and the prognosis of patients with CRC needs further study by expanding sample size.
Currently, tumor microenvironment (TME) has been a hot and trending spot in tumor research [18]. As a major component of TME, CAF has multiple pro-tumorigenic functions during tumorigenesis. Francescone et al. have found that Netrin G1promotes PDAC progression by increasing the tumor-promoting role of CAFs [29]. CAF promotes cholangiocarcinoma progression through a mice model. Pan-CAF signature is significantly correlated with poor survival in patients with cholangiocarcinoma and tumor recurrence [30]. Recent study has revealed that pancreatic cancer cells co-culture with CAF can pro- mote cancer stemness [31]. Intriguingly, some studies showed that CAF could inhibit tumor growth and inva- sion. Ozdemir et al. have reported that depletion of CAF can augment pancreas cancer growth, which suggests that CAF may play a anti-tumor role in some tumors [32].Our above study showed that PDCD2L expression was negatively correlated with CAF in many cancers including BRCA, BRCA-Basal, LUSC, SARC, STAD and TGCT. PDCD2L might play an oncogene role in various cancers, the underlining mechanism of PDCD2L regulat- ing CAF needs further study. Recently six immune sub- types: C1 (Wound Healing), C2 (IFN-y Dominant), C3 (Inflammatory), C4 (Lymphocyte Depleted), C5 (Immu- nologically Quiet), and C6 (TGF-ß Dominant) were first identified by an extensive immunogenomic analysis of 33 different types of cancer. Among them, C1 was char- acterized by increased angiogenesis gene expression, high proliferation rate and Th2 cells tend to adaptive immune infiltration. While the most apparent feature of C2 was the highest M1/M2 macrophage polarization and the optimal TCR diversity, and C2 also exhibited a boost proliferation rate and an augment CD8 signal. C3 showed an up-regulation of Th17 and Th1 genes, low or moderate cancer cell proliferation, and the aneuploidy and overall somatic copy number alterations was also decreased. C4 was highlighted by macrophage character- istics and higher M2 response, while Th1 was inhibited. C5 exhibited the lowest lymphocyte and the strongest macrophage response, which mainly conducted by M2 macrophages. C6 subtype showed the highest TGF-B characteristics and high lymphocyte infiltration, in which type I and type II T cells were evenly distributed [33]. The novel immune subtype can distinct multiple heteroge- neous tumors, which may benefit the targeted immune
A
HT29
B
HT29
SW480
C
Relative PDCD2L mRNA level
1.5
Relative PDCD2L mRNA level
1.5
Relative PDCD2L mRNA level
1.5
si-PDCD2L-3
si-PDCD2L-3
si-NC
si-NC
1.0
1.0
1.0-
PDCD2L
0.5
0.5
0.5
GAPDH
HT29
SW480
0.0
T
0.0
1
0.0
T
si-NC
si-PDCD2L-1
si-PDCD2L-2
si-PDCD2L-3
si-NC
si-PDCD2L-3
si-NC
si-PDCD2L-3
D
HT29
E
SW480
10”
Q1
Q2
1º
Q1
Q2
ª
Q1
Q2
10
Q1
Q2
18
3.32
2.76
+07.
2.94
4.38
182
1.56
3.83
13
1.77
5.07
199
18
18
13º
.
1ª
195
NB”
195
FLIDA:PE-A
FLIDA:PE-A
FLIDA:PE.A
1ª
1ª
.
FLIDA:PE-A
a”
5
13ª
1º
”
1º
1º
1º
1g*
Q4
Q3
Q4
Q3
IR1
Q4
Q3
1g
Q4
Q3
.
92.7
1.20
·
90.9
1.75
.
93.3
1.31
·
90.7
2.46
Đ
so’
187
1º
16ª
10”
1º
182
-
5
+3
10?
16”
”
1º
+5’
-
·
1º
1ª
?
1º
182
18
·
10’
107
-2
15
13
18
FL3.A:APC.A
FL3.A:APC-A
FL3-A: APCA
FL3.A:APC-A
F
si-NC
si-PDCD2L-3
I
si-NC
si-PDCD2L-3
si-NC
si-PDCD2L-3
Cell apoptosis(%total)
10
**
**
8
DAPI
R.
2
6
IL
1
4
O
”
2
EdU
0
T
T
HT29
SW480
G
*
-
2.0-
si-NC
si-PDCD2L-3
MERGE
o
1.5-
**
A.
OD(450nm)
1.0-
0.5-
HT29
SW480
J
K
0.0
T
DAY1
DAY2
DAY3
DAY4
DAY5
H
HT29
1.5
si-NC
Relative positive cells(%)
si-PDCD2L-3
si-PDCD2L-3
0.8
si-NC
si-PDCD2L-3
si-PDCD2L-3
**
P=0.1291
si-NC
si-NC
0.6
OD(450nm)
1.0-
**
PDCD2L
0.4
P53
0.5
0.2
C-MYC
GAPDH
0.0
T
T
T
T
T
DAY1
DAY2
DAY3
DAY4
DAY5
0.0
T
HT29
SW480
HT29
SW480
SW480
therapy of cancer patients. In our study, PDCD2L expres- sion is significant aberrant expressed in different immune subtypes of BLCA, BRCA, COAD, KICH, KIRC, KIRP, LGG, LIHC, LUAD, LUSC, OV, PAAD, PRAD, SARC, STAD, TGCT and UCEC, which suggested that PDCD2L might play an important role in cancer immune therapy.
Since single-cell transcriptomic sequencing study suggested that PDCD2L expression was significantly associated with apoptosis in PC. To elucidate the role of PDCD2L in CRC progression, apoptosis rate of CRC cells significantly increased by downregulat- ing PDCD2L expression in HT29 and SW480, respec- tively. In addition, PDCD2L knockdown also enhanced the proliferation of CRC cells. The results suggest that PDCD2L might inhibit the apoptosis and prolif- eration of CRC cells. Apoptosis-induced proliferation (AiP), a form characterized by a compensatory prolif- eration mechanism, which is trigger by apoptosis [34]. Aip is critical for tissue development and regenera- tion, and persistent Aip may cause tumor repopulation and drives angiogenesis following therapy [35]. Recent study shows that inhibiting DDX3X expression induced cell apoptosis, and also loss of DDX3X caused compen- satory proliferation [36]. Moreover, downregulation of TNFR2, but not TNFR1, triggers apoptosis of Schwann cells, and the apoptosis also increases Schwann cell pro- liferation [37]. Our study first suggests that PDCD2L knockdown might trigger apoptosis induced prolifera- tion in CRC cells. However, the mechanism of PDCD2L regulating Aip in CRC needs further investigation.
In conclusion, our study first provides a comprehen- sive analysis of PDCD2L in pan-cancer and found that PDCD2L expression was high in various cancers and negatively associated with CAF. Our validation experi- ment found that PDCD2L expression was significantly higher in CRC samples than that in corresponding non- tumor tissues, which suggests that PDCD2L could be served as a biomarker of CRC. PDCD2L might play an important role in CRC progression by participating in apoptosis induced proliferation of CRC cells.
Supplementary Information
The online version contains supplementary material available at https://doi. org/10.1186/s12935-022-02525-x.
Additional file 1: Figure S1. The association between PDCD2L expression and molecular subtype of COAD, READ, and some cancers.
Acknowledgements
Not applicable
Authors’ contributions
HG, CX, and JL performed experiment and data analysis. SG collected data. FZ and YT provided the tissue specimen and staining. HS performed the
data analysis. AH designed and revised the manuscript. All authors read and approved the final manuscript.
Funding
This work was supported by National Natural Science Foundation of China (No:81472251, 81272636) and Natural Science Foundation of Guangdong province (No:2021A1515012379).
Availability of data and materials
The original contributions presented in the study are included in the article/ supplementary material. Further inquiries can be directed to the correspond- ing authors.
Declarations
Ethics approval and consent to participate Not applicable.
Consent for publication
All authors consent for publication.
Competing interests
None declared.
Received: 4 October 2021 Accepted: 15 February 2022 Published online: 25 February 2022
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