LHPP is associated with favorable survival across diverse cancers with tumor suppressor properties in stomach adenocarcinoma: a pan-cancer analysis

doi:10.21203/rs.3.rs-1755397/v1

Background

The down-regulation of LHPP has been reported as a tumor suppressor gene in several malignancies. This study aims to explore the potential roles of LHPP across 33 types of tumors.

Methods

The TCGA database was mainly used to investigate the correlation of LHPP expression pattern with clinical prognosis and other function related gene sets. Additionally, immunohistochemistry and western blot assay were used to detect the expression level of LHPP in tissue samples for stomach adenocarcinoma (STAD) patients. We next established STAD cell lines with exogenous silencing/ overexpression of LHPP. qRT-PCR, western blot assay, CCK-8 assay and colony formation assays were performed for cell function identifications.

Results

LHPP was widely down-regulated in tumor tissues compared with normal tissues in pan-cancer across 13 cancer types. The expression level of LHPP was associated with favorable survival across diverse cancers. Moreover, we observed that LHPP expression was significantly correlated with immune infiltration, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair genes (MMRs), and DNA methyltransferases in many tumors. Validation in clinical tissue samples confirmed LHPP was down-regulated in STAD. Functional experiments demonstrated that LHPP suppressed cell proliferation of STAD via down-regulating p‑PI3K/p‑AKT expression levels.

Conclusion

Our first pan-cancer study provided insight into the role of LHPP in tumorigenesis. Besides, LHPP may acts as a tumor suppressor gene in STAD.

LHPP

Pan-Cancer

Prognosis

STAD

PI3K-AKT.

LHPP gene is located on chromosome 10q26.13 which encodes a highly evolutionarily conserved histidine phosphatase. Its single-nucleotide polymorphism is reported to involve in neurological disorders, including major depression and alcohol dependence ^1–3. Recently, surging evidence has elucidated the pivotal role of LHPP on antitumor effect in multiple cancers. Overall, decreased LHPP gene expression and its transcriptional signature has frequently been detected in a wide range of cancers, including PRAD, LIHC, COAD, READ, PAAD, BLCA, LUAD, THCA, and GBM ^4–13. Moreover, LHPP is reported as a favorable prognostic biomarker for patient survival and exerts its antitumor strength by modulating PI3K/AKT and Wnt/β-catenin pathways ^{6, 8–10,12}. Nevertheless, the above LHPP related studies used different detection methods with a limited sample size, warranting a need for a systematic analysis of the aberrant expression of LHPP in a pan-cancer setting.

In the current study, for the first time, we conducted a comprehensive bioinformatics analysis of LHPP in pan-cancer by using the Cancer Genome Atlas (TCGA) database, the GTEx dataset, and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. The correlation between LHPP gene expression profile and survival status, immune infiltration, tumor mutational burden (TMB), microsatellite instability (MSI), mismatch repair genes (MMRs), DNA methyltransferases, and relevant cellular pathway were investigated to explore the potential molecular mechanism of LHPP in the pathogenesis of different cancers.

By using the bioinformatics approaches mentioned above, we found that dysregulated LHPP may participate in human tumorigenesis. Nevertheless, this hypothesis requires further experimental testing. To this end, we attempted to explore the effects of LHPP on stomach adenocarcinoma (STAD) progression. We found that LHPP was down-regulated in both STAD tumor tissue samples and STAD cell lines compared to their normal control subjects. Additionally, functional studies identified that LHPP modulates cell proliferation of STAD via regulating p‑PI3K/p‑AKT expression levels. Collectively, we conducted a pan-cancer expression analysis of LHPP to assess its correlation with clinical prognosis and potential molecular mechanisms. Subsequent molecular and cell biology experiments revealed that LHPP may be served as a tumor suppressor gene and inhibited tumorigenesis in STAD.

The study protocol was approved by Shaanxi Provincial People's Hospital, and all subjects provided written informed consent to participate. All experiments were performed in accordance with relevant guidelines and regulations.

Sample information and LHPP expression analysis in human pan-cancer

TCGA transcriptome sequencing data for LHPP in 33 different tumor types were retrieved from the UCSC Xena dataset (http://xena.ucsc.edu). The expression difference of LHPP was detected between tumor tissues and adjacent normal tissues. For those tumors that lack normal controls in TCGA project (ACC, DLBC, LAML, LGG, MESO, OV, TGCT, UCS, and UVM), GTEx dataset with LHPP expression level in normal samples was included in our study. The Wilcox. test was used to examine the difference between each group, two-tailed P < 0.05 was considered statistically significant. Additionally, we also conducted LHPP total protein analysis based on CPTAC dataset in BRCA, OV, COAD, RCC, UCEC, and LUAD by accessing the UALCAN portal (http://ualcan.path.uab.edu/analysis-prot.html). We also performed a subgroup analysis between LHPP expression level and TNM stage in all tumors.

Prognostic analysis in pan-cancer levels

To evaluate whether the LHPP expression level was associated with tumor prognosis in various cancers, survival analysis was performed using the Kaplan-Meier method. We divided patients into high-risk and low-risk groups based on the median value of gene expression level. We chose OS (overall survival), DSS (disease-specific survival), and PFI (progression-free survival) as prognostic evaluation indicators. Log-rank test was applied for difference comparison among measurement data. A P-value lower than 0.05 was considered significant.

Immune correlation analysis

In this part, we investigated whether the expression of LHPP is related to immune infiltrates across all TCGA tumors. We used the ESTIMATE algorithm to evaluate the immune cell infiltration level (including immune score and stromal score) of pan-cancer data from the TCGA database. Meanwhile, The CIBERSORT method was employed to assess the relative proportion of immune infiltrates across multiple cancers. In addition, 40 immune checkpoint genes, including monoclonal antibody class immune checkpoint inhibitors, therapeutic antibodies, cancer vaccines, cell therapy, and small molecule inhibitors, were collected for co-expression analysis with LHPP via correlation modules. We used Spearman rank correlation coefficient for statistical analysis and a P-value lower than 0.05 was considered significant.

Correlation analysis of LHPP expression with TMB and MSI

TMB is defined as the average number of total mutation incidences per million tumor genome. MSI refers to the number of insertion or deletion events in a repeating unit of genes. In this study, the relationship of LHPP expression with TMB/MSI was calculated by the Spearman rank correlation coefficient. A P-value lower than 0.05 was considered significant.

Correlation analysis of LHPP expression with MMRs and DNA Methyltransferase

Pearson correlation analysis was used to evaluate the relationship between LHPP and five MMR genes, namely MLH1, MSH2, MSH6, PMS2, and EPCAM mutations. Moreover, we obtained the pan-cancer expression profile of four methyltransferases (DNMT1, TRDMT1, DNMT3A, and DNMT3B), which play an important role in regulating DNA methylation, from the TCGA database. In this study, we also used Pearson correlation analysis to estimate the relationship between LHPP expression and DNMTs. A P-value lower than 0.05 was considered significant.

LHPP-related gene enrichment analysis

We first acquired PPI information of LHPP by STRING (Search Tool for the Retrieval of Interacting Genes) website (https://string-db.org/). Subsequently, we used the “Similar gene detection’ function of GEPIA2 (Gene Expression Profiling Interactive Analysis, version 2) webserver (http://gepia2.cancer-pku.cn/#analysis) to obtain the top 100 LHPP-related targeting genes based on pan-cancer data from the TCGA database. Moreover, four representational LHPP-related genes were further analyzed in the “Gene_Corr” module of TIMER2 (tumor immune estimation resource, version 2) database (http://timer.cistrome.org/), which contains the partial correlation (cor) and P-value in the purity-adjusted Spearman’s rank correlation test. A P-value lower than 0.05 was considered significant.

We next combined the LHPP-binding and interacted genes together to perform KEGG (Kyoto encyclopedia of genes and genomes) pathway analysis. 150 genes mentioned above were uploaded to DAVID (Database for annotation, visualization, and integrated discovery) webserver (https://david.ncifcrf.gov/) for GO (Gene ontology) enrichment analysis. We extracted data for LHPP related BP (Biological process), CC (Cellular component), and MF (Molecular function) and pathways.

Patients and clinical specimens

The study material consisted of 52 tumor tissue samples, paired para-cancerous histological normal tissues (PCHNTs) which are obtained during curative surgery. None of the experimental subjects had received prior gastric resection or preoperative chemotherapy/radiation therapy. All samples were immediately frozen and stored at − 80℃. All patients voluntarily joined this study with written informed consent to have their biological specimens analyzed. This study was announced by the Ethical Committee of the Shaanxi Provincial People's Hospital.

Immunohistochemistry (IHC)

Immunohistochemistry was performed as previously described ⁶. Primary rabbit polyclonal antibodies for LHPP (Proteintech, USA) were incubated with tissue sections overnight at 4˚C. LHPP expression was evaluated by using IHC scores. Each field was scored independently by two pathologists.

Cell culture and transfection

The human STAD cell lines (HGC-27, AGS, SNU-1, and NCI-N87), as well as immortalized gastric mucosal epithelial cell line (GES-1) were cultured in RPMI-1640 medium containing 10% fetal bovine serum. All those cells were maintained at 37˚C in a cell incubator with 5% CO₂. For LHPP overexpression, lentiviruses containing overexpression vectors of LHPP or negative control lentiviruses (Shanghai China, GeneChem) were transfected into AGS cells following the manufacturer’s protocols. For LHPP knockdown, lentiviruses expressing shRNA targeting LHPP were transfected into AGS cells when they reached 30%-40% confluence. The shLHPP sequences are as follows, sh-228: CTGTGCTCATATCACTGGGAA, sh-229: CAGCTTCAGAGGCTGGGATTT, sh-230: TGCCAGATCCTGAAGGAGCAA.

Real-time quantitative PCR assay

Fastagen 200 kit (Shanghai, China) and TRIzol reagent (Ambion, life technologies, USA) were used to extract RNA from cells and tissues according to the manufacturer’s instructions, respectively. cDNA was synthesized by reverse transcription (RT) using a Primescript RT reagent kit with random primers according to manufacturer-provided protocols (TaKaRa). The qRT-PCR was achieved using SYBR Premix Ex Taq™ II (Tli RNaseH Plus) (TaKaRa) on CFX96 Real-Time PCR Detection System ( Bio-Rad, California, USA) following the manufacturer's instructions. The following primers were used: GAPDH: forward:5-CACCCACTCCTCCACCTTTGA-3, reverse: 5-TCTCTCTTCCTCTTGTGCTCTTGC-3. LHPP: forward: 5'‑GCTTCAGAGGCTGGGATTTGAC‑3', reverse, 5'‑AATTACCACACAGTTTGGGTTGGA ‑3'. All reactions were performed in triplicate.

Western blot analysis

RIPA buffer with protease inhibitors was used to extract total protein of each sample. Protein concentration was measured by the BCA Protein Assay Kit (Tiangen Biotech, China). Proteins were separated by SDS-PAGE and then transfer to PVDF membrane. The membrane was then sealed with non-fat milk and sequentially incubated with primary antibodies (LHPP, Proteintech, USA; GAPDH, Proteintech, USA; AKT, Proteintech, USA; p‑AKT, SAB, USA; PI3K, SAB, USA; p‑PI3K, SAB, USA) and secondary antibody. Immunoreactivity was determined by using GE Amersham Imager 600 system (GE Healthcare).

Cell proliferation assay

STAD cell viability was assessed by the Cell Counting Kit-8 (CCK-8) assay (Solarbio, China). Briefly, 1000 cells/well were incubated 96-well plates, 10 µL of CCK-8 solution into each well for 2h. The results were determined by a plate reader at 450 and 600 nm at intervals of 24, 48, 72, and 96 h (Bio-Rad, Hercules, CA, USA.)

Colony formation analysis

1 × 10³ cells/well were incubated into 6-well plate and incubated for 2–3 weeks. Then the colonies were fixed with methanol and subsequently stained with crystal violet solution for 15min. Finally, the plates were imaged for further analysis.

Transwell analysis

200 µl of serum-free cell suspensions containing 2 × 10⁴ cells were transferred into the upper chamber. Then we placed the chamber into lower wells that were filled with a complete medium containing 15% fetal bovine serum. Cells were cultured for 24h and stained for observation with an inverted microscope.

Statistical analysis

Statistical analyzes were performed with the SPSS 13.0 software (SPSS, Chicago, IL, USA), GraphPad Prism 5.0 (GraphPad Software, La Jolla, CA), and R software version 3.6.1 (http://www.rproject.org) for windows. The t-test was used to compare mean values between the two groups, and a one-way analysis of variance was used to compare the mean values between multiple groups. The χ2 test was used to evaluate the association between LHPP expression and clinical characteristics of the patients with STAD. P < 0.05 was considered statistically significant.

LHPP gene expression in pan-cancer

To comprehensively investigate the difference of LHPP expression status across various cancer types, we examined the mRNA expression levels of LHPP in 33 different tumor entities using TCGA database. As shown in Fig. 1a, the expression levels of LHPP was found to be down-regulated in BLCA (P < 0.05), CHOL (P < 0.001), COAD (P < 0.001), GBM (P < 0.01), HNSC (P < 0.01), KICH (P < 0.001), KIRC (P < 0.001), PCRG (P < 0.05), PRAD (P < 0.001), READ (P < 0.05), SARC (P < 0.05), STAD (P < 0.001) but up-regulated in LUAD (P < 0.001) as compared with the normal tissues.

Then we integrated the GTEx dataset with the TCGA dataset for further evaluation of the expression difference of LHPP between normal and tumor tissues. Results showed that LHPP expression was up-regulated in DLBC (P < 0.05) and OV (P < 0.05) while down-regulated in TGCT (P < 0.05) as compared with the normal tissues (Fig. 1b). The difference of LHPP expression level between normal and tumor tissue samples was insignificant in ACC, LAML, LGG, MESO, UCS, and UVM. We also analyzed the LHPP total protein level from the CPTAC database. Compared with normal controls, LHPP protein was significantly lower in BRCA, KIRC, UCEC, LUAD, COAD, and OV tissue samples (Fig. 1c) (All P < 0.001).

We subsequently stratified LHPP mRNA data according to TNM stages and analyzed their correlation in each type of tumor. Results showed that KIRC patients with advanced-stage disease exhibited a higher LHPP expression level, while a negative correlation was observed in KIRP patients. Interestingly, compared with stage Ⅲ of LIHC, LHPP mRNA level was significantly higher in both early (stageⅠ) and advanced stage (stage Ⅳ) (All P < 0.05), although the difference of the latter two subgroups was insignificant (P = 0.15) (Fig. 1d).

Full prognostic role of LHPP in pan-cancer

We divided our research subjects into high-expression and low-expression groups based on the median expression level of LHPP and explored the correlation of LHPP expression with the prognosis of patients with different tumors. We found that highly expressed LHPP was linked to poor prognosis of OS in KIRC (P = 0.013) but with well OS in KIRP (P = 0.02) and LGG (P < 0.001) (Fig. 2a). DSS analysis data showed high level of LHPP expression predicted better prognosis among KIRP (P = 0.027), LGG (P < 0.001) and READ (P = 0.043) patients while may indicated worse prognosis in KIRC (P = 0.007) patients (Fig. 2b). Additionally, high expression of the LHPP gene was related to longer PFI for CESC (P = 0.045), KIRP (P = 0.034), LGG (P = 0.002) and PRAD (P = 0.028). However, it may associated with shorter PFI in KIRC patients (P = 0.001) (Fig. 2c).

Analysis of LHPP with immune infiltration and tumor microenvironment

Tumor microenvironment was closely linked to the initiation, progression or metastasis of cancer¹⁴. In the study, we used stromal score and immune score which were calculated based on ESTIMATE algorithm to measure the level of tumor infiltrating stromal cells and tumor infiltrating immune cells, respectively. As shown in Fig. 3a, we found significant positive correlation between LHPP and stromal score in KICH (r = 0.46, P < 0.001), SKCM (r = 0.22, P < 0.001) and TGCT (r = 0.31, P < 0.001). However, LHPP expression was inversely correlated with stromal score in KIRP (r = -0.22, P < 0.001) and THCA (r = -0.28, P < 0.001). As to immune cell infiltrates, LHPP expression was positively correlated with immune score in BRCA (r = 0.1, P < 0.001), KICH (r = 0.43, P < 0.001), KIRC (r = 0.15, P < 0.001), SARC (r = 0.21, P < 0.001), SKCM (r = 0.38, P < 0.001) while negatively correlated with that in THCA (r = -0.31, P < 0.001) (Fig. 3b).

We next explored the correlation between the specific infiltration levels of immune cells and LHPP expression in diverse cancer types of TCGA. The scatterplot data showed that LHPP expression was significantly associated with infiltrating immune cells (CD4 + T cell, CD8 + T cell, etc.) in 21 out of 33 types of tumor (BLCA, BRCA, CESC, DLBC, GBM, HNSC, KIRC, KIRP, LAML, LGG, LIHC, LUAD, LUSC, PCPG, PRAD, SKCM, STAD, TGCT, THCA, THYM, and UCEC) (All P < 0.05) (Fig. 4).

Given that LHPP expression may affect immune infiltration in various tumors, we further tested the correlation between LHPP expression and immune checkpoint gene expression. 47 immune checkpoint genes were selected for the co-expression analysis with LHPP across TCGA cohorts. As shown in Fig. 5, the immune-related gene set was closely related to LHPP expression, especially in LGG, SKCM, and THCA. Overall, the above data indicated that LHPP may be involved in the formulation of tumor microenvironment.

Analysis of LHPP with TMB and MSI in human pan-cancer

TMB, which refers to the number of mutations in tumor cells, has been widely used as prognostic biomarkers in many kinds of tumors. We examined the TMB in all types of tumors according to the TCGA project to explore whether it related to LHPP activity. A significant correlation was detected concerning LHPP expression and TMB in BLCA, HNSC, LGG, PRAD, SARC, STAD, THCA, THYM, UCEC, and UVM (All P < 0.05) (Fig. 6a). We observed the highest and lowest coefficients in UVM and in LGG, respectively.

Microsatellite instability, which refers to a pattern of genomic microsatellites hypermutation caused by mismatch repair system dysfunction, is reported to plays an important role in tumorigenesis. We next examined the association of LHPP expression with MSI status in the TCGA pan-cancer database. As shown in Fig. 6b, LHPP expression was closed related to MSI in THYM, UCEC, LUSC, CESC, STAD, SARC, and TGCT (All P < 0.05).

Analysis of LHPP with MMRs and DNA Methyltransferases

The relationship of LHPP expression with MMR defects was investigated in our study by analyzing the TCGA datasets. According to the correlation heatmap exhibited in Fig. 7a, LHPP was significantly associated with MMR genes in most of these cancer types. A similar co-expression analysis was conducted to explore the connection between LHPP expression and DNA methyltransferases. As shown in Fig. 7b, four key DNMT showed a significant correlation with LHPP expression in broad cancer types.

Enrichment analysis of LHPP-related partners

To further determine the effect of LHPP on tumors, we applied the STRING approach to identify LHPP expression-correlated genes as well as targeting LHPP-binding proteins for subsequent pathway enrichment analyses. 50 LHPP related proteins were achieved and the interaction network of these proteins was displayed in Fig. 8a. Additionally, 100 genes related to LHPP expression were screened out from the TCGA project by using the GEPIA2 tool. GPR62 (G Protein-Coupled Receptor 62) exhibited the highest correlation with LHPP expression (R = 0.8, P < 0.001), followed by MOG (Myelin Oligodendrocyte Glycoprotein) (R = 0.78, P < 0.001), MBP (Myelin Basic Protein) (R = 0.77, P < 0.001) and PRR18 (Proline Rich 18, P < 0.001) (R = 0.76), etc (Fig. 8b). The corresponding heatmap data exhibited the correlation between LHPP and the above four genes in each specific cancer type (Fig. 8c). Those two datasets above were combined to perform subsequent KEGG and GO enrichment analyses. All 150 genes were analyzed by DAVID software and the results of GO analysis indicated that “positive regulation of protein localization to Cajal body”, “chaperonin-containing T-complex” and “unfolded protein binding” were the most significant Gene Ontology (GO) terms for biological processes (BP), cell component (CC) and molecular function (MF), respectively (Table 1). Moreover, consistent with our previous study ⁶, ‘the PI3K/AKT signaling pathway’ was demonstrated as the most significant pathway in KEGG signaling pathways analysis (Table 2).

Table 1

Gene ontology analysis of LHPP related genes
Category	Term	Count	%	P Value	FDR
GOTERM_BP_DIRECT	GO:1904871 ~ positive regulation of protein localization to Cajal body	7	0.04	1.80E-12^*	1.11E-09
GOTERM_BP_DIRECT	GO:1904874 ~ positive regulation of telomerase RNA localization to Cajal body	7	0.04	3.11E-10^*	9.52E-08
GOTERM_BP_DIRECT	GO:1904851 ~ positive regulation of establishment of protein localization to telomere	6	0.03	1.30E-09^*	2.65E-07
GOTERM_BP_DIRECT	GO:0032212 ~ positive regulation of telomere maintenance via telomerase	7	0.04	5.14E-08^*	7.88E-06
GOTERM_BP_DIRECT	GO:1901998 ~ toxin transport	7	0.04	1.08E-07^*	1.33E-05
GOTERM_BP_DIRECT	GO:0046323 ~ glucose import	5	0.03	7.99E-07^*	8.16E-05
GOTERM_CC_DIRECT	GO:0005832 ~ chaperonin-containing T-complex	8	0.04	1.42E-14^*	2.03E-12
GOTERM_CC_DIRECT	GO:0043209 ~ myelin sheath	14	0.07	1.85E-11^*	1.32E-09
GOTERM_CC_DIRECT	GO:0002199 ~ zona pellucida receptor complex	6	0.03	1.29E-09^*	6.15E-08
GOTERM_CC_DIRECT	GO:0044297 ~ cell body	8	0.04	1.63E-07^*	5.84E-06
GOTERM_CC_DIRECT	GO:0005577 ~ fibrinogen complex	5	0.03	2.05E-07^*	5.87E-06
GOTERM_CC_DIRECT	GO:0005874 ~ microtubule	12	0.06	5.67E-06^*	1.35E-04
GOTERM_MF_DIRECT	GO:0051082 ~ unfolded protein binding	10	0.05	2.10E-08^*	4.12E-06
GOTERM_MF_DIRECT	GO:0005351 ~ sugar:proton symporter activity	5	0.03	5.99E-07^*	5.87E-05
GOTERM_MF_DIRECT	GO:0005355 ~ glucose transmembrane transporter activity	5	0.03	1.63E-06^*	1.06E-04
GOTERM_MF_DIRECT	GO:0055056 ~ D-glucose transmembrane transporter activity	4	0.02	1.17E-05^*	5.75E-04
GOTERM_MF_DIRECT	GO:0019911 ~ structural constituent of myelin sheath	3	0.02	0.001^*	0.06
GOTERM_MF_DIRECT	GO:0044183 ~ protein binding involved in protein folding	3	0.02	0.003^*	0.10
*indicates P-value < 0.05 (2-tailed).

Table 2

KEGG pathway analysis of LHPP related expressed genes
Pathway ID	Name	Count	%	p-Value	Genes
hsa04151	PI3K-AKT signaling pathway	10	0.05	5.10E-05^*	ANGPT4, TNXB, ANGPT2, ANGPT1, PPP2R2B, PDPK1, TNN, TNC, TNR, FGF1
hsa00670	One carbon pool by folate	3	0.02	0.004769^*	ATIC, MTHFD1, MTHFD1L
hsa04512	ECM-receptor interaction	4	0.020644	0.010326^*	TNXB, TNN, TNC, TNR
hsa04510	Focal adhesion	5	0.03	0.021752^*	TNXB, PDPK1, TNN, TNC, TNR
hsa04015	Rap1 signaling pathway	5	0.03	0.02316^*	GNAO1, ANGPT4, ANGPT2, ANGPT1, FGF1
hsa03320	PPAR signaling pathway	3	0.02	0.047612^*	PDPK1, SCD5, ANGPTL4
hsa04610	Complement and coagulation cascades	3	0.02	0.050193^*	FGB, FGA, FGG
hsa04066	HIF-1 signaling pathway	3	0.02	0.089448^*	ANGPT4, ANGPT2, ANGPT1
*indicates P-value < 0.05 (2-tailed).

Expression profile of LHPP gene in STAD patients and cell lines

As shown in Fig. 9, the protein level of LHPP was dramatically lower in 52 STAD tissues compared with paired adjacent normal tissues (P < 0.05). We chose IHC score of 3 points as the cut-off value and divided STAD patients into LHPP high-expression and low-expression groups. Clinicopathological data of the two groups were analyzed and no correlation was found of LHPP expression level with age, gender, pathological pattern, depth of tumor invasion, lymph node metastasis, and TNM stage (All P > 0.05) (Table 3). Additionally, comparing with gastric mucosal epithelial cell line (GES-1), significant lower expression level of LHPP was observed in all 4 STAD cell lines (All P < 0.05) (Fig. 10). Those results indicated that LHPP expression is down-regulated in STAD.

Table 3

Association between LHPP expression and clinicopathological characteristics of patients with stomach adenocarcinoma
Parameters	Number of cases	LHPP expression		P value
Parameters	Number of cases	Low	High	P value
Age
<60	18	9	9	0.41 ^a
≥60	34	21	13	0.41 ^a
Gender
Male	37	21	16	0.83 ^a
Female	15	9	6	0.83 ^a
Pathological differentiation
Well + moderate	23	10	13	0.07 ^a
Poor + undifferentiation	29	20	9	0.07 ^a
Depth of tumor invasion
T1 + T2	14	8	6	0.96 ^a
T3 + T4	38	22	16	0.96 ^a
Lymph node metastasis
Present	21	10	11	0.23 ^a
Absent	31	20	11	0.23 ^a
TNM Stage
Ⅰ, Ⅱ	20	14	6	0.16 ^a
Ⅲ, Ⅳ	32	16	16	0.16 ^a
^a Usingχ2 test for this statistic

LHPP suppresses cell proliferation of STAD via down-regulating p‑PI3K/p‑AKT expression levels.

We used the AGS cell line for subsequent analyses as it presented with a median expression level of LHPP. We first examined the effects of LHPP on cell proliferation of STAD in vitro. We found that the viability of AGS cells were decreased in the AGS OE‑LHPP group than in the AGS NC-LHPP group (Fig. 11) (All P < 0.05). On the contrary, down-regulation of LHPP could significantly promote cell proliferation (Fig. 12) (All P < 0.05). We next investigated the potential mechanism of LHPP in the development of STAD. Based on the enrichment analysis above, we speculated that LHPP may influence cell function by regulating PI3K/AKT pathway. Therefore, the protein expression levels of AKT, p-AKT (Thr473), PI3K and p-PI3K were detected in the present study. We observed that LHPP overexpression markedly decreased the expression intensity of p-AKT and p-PI3K (Thr473) (Fig. 13). In the meantime, LHPP silencing increased the level of p-AKT and p-PI3K (Thr473) (Fig. 14) in AGS cell line. Collectively, our results indicated that LHPP may act as a tumor suppressor to decrease cancer growth by modulating the PI3K/AKT signaling pathway.

Pan-cancer gene expression analysis can give researchers a comprehensive overview of gene biological functions as well as potential molecular mechanisms in the process of tumorigenesis. Recently, emerging publications have examined tumor-related genes in a pan-cancer landscape, revealing the homogeneity and heterogeneity of gene function in the occurrence and development of cancer, which is of importance for exploring therapeutic targets and guiding individualized treatment. Our previous study indicated that LHPP functions as a tumor suppressor gene and could inhibit CRC cell growth and proliferation via the PI3K/AKT signaling pathway ⁶. However, whether LHPP impacts oncogenesis in different types of cancers through certain common molecular mechanisms remains largely unclear. Herein, we performed a pan-cancer analysis of LHPP in a total of 33 cancer types based on the data of the TCGA, the GTEx and the CPTAC databases. Furthermore, we validated the expression profile of LHPP gene in STAD patients from our center and conducted in vitro functional experiments in LHPP overexpression and knockdown STAD cell lines. We for the first time reported that LHPP is associated with favorable survival across diverse cancers and functions as a tumor suppressor gene in STAD.

We observed a distinct expression profile of LHPP between cancer and normal tissues in the TCGA database. Compared with adjacent normal tissues, we found that LHPP was significantly down-regulated in BLCA, CHOL, COAD, GBM, HNSC, KICH, KIRC, PCRG, PRAD, READ, SARC, STAD, and TCGT while up-regulated in LUAD, DLBC, and OV. This observation stays in agreement with previous literatures ^{4, 6–8,11,13}. However, unlike published literatures, we failed to detect the difference of LHPP expression between normal and tumor tissue samples in THCA, LIHC, and CESC ^9,10,12. The reasons in causing the inconsistent results are various. Firstly, selection bias, such as racial difference, is inevitable when researchers conducting a single-center-based cohort study. Secondly, different sample size may yield different experimental results. The limited sample size of a single-center study may also affect the accuracy of experimental conclusions. Thirdly, different detection methods may also contribute to the discrepancy of research conclusions. In this study, the evaluation of LHPP expression is based entirely on transcription levels from the TCGA database. On account of post-transcription modification and/or regulated proteolysis that may affect protein activity, previous studies also used immunohistochemical staining methods and western blot assay to evaluate the protein level of LHPP. Thus, further studies regarding the differential expression of LHPP on malignancies require additional investigation.

We further focused our attention on the prognostic value of LHPP in pan-cancer. As far as we know, only a few studies have investigated the clinical significance of LHPP in several types of cancer. Decreased LHPP was reported to correlate with poor prognosis in CHOL, CRC, THCA, LIHC, and CESC ^{6, 8–10,12}. In this study, we found that high expression levels of LHPP correlated with a survival advantage in KIRP, LGG, READ, CESC, and PRAD. Interestingly, elevated LHPP expression seems to be linked to poor clinical prognosis of KIRC cases (OS, DSS, and PFI, all P < 0.01). We speculated that although our findings are similar to previous studies about LHPP with anti-tumoral activities, it may also have a dual role in promoting tumor progression under certain circumstances. Thus, the function of LHPP and its correlation with patient clinical characteristics still needs to be investigated in those malignancies.

Recent studies have shown that tumor microenvironment, which contains tumor-infiltrating lymphocytes as well as other immune cells, plays an important role in tumor progression^15–19. In this study, we found that high LHPP expression indicated high degrees of immune and stromal cell infiltration in KICH and SKCM while negatively correlated with those in THCA based on the ESTIMATE algorithm. We also observed that LHPP expression was closed related to immune infiltration cells in various types of cancer, especially in BRCA, THCA, KIRC, and SKCM. Additionally, correlation analysis also showed that LHPP expression was associated with some immune checkpoint genes. Those findings are in line with previous literatures, where KIRC and SKCM are two types of the most malignant tumors with low sensitivity to chemoradiotherapy, but response to immunotherapy. Recently, Sylvia et. al²⁰ found that immune checkpoint blockade is the most investigated form of immunotherapy in breast cancer. Using immune checkpoint blockade as monotherapy has achieved objective responses in patients with breast cancer, with higher rates seen when administered in earlier lines of therapy. Thus, our study provided insight into the important role of LHPP in tumor immunity.

We have also tested the association between LHPP expression and TMB or MSI in some cancer types, and presented evidence of potential co-expression of LHPP with the major MMR genes and methylation transferases. Moreover, we carried out a series of enrichment analyses with integrated information of LHPP-bind components and LHPP expression-related genes. Results showed that LHPP was found to be mainly involved in the regulation of the PI3K-AKT signaling pathway, which was in line with our previous study in CRC ⁶.

Our preliminary data predicted the molecular functions of LHPP in pan-cancer through bioinformatics, we next validated those conclusions in tissue samples as well as cell lines from one of the tumors of which LHPP is aberrantly expressed. Since our research group mainly concentrated on gastrointestinal tumors, we decided to validated gene function and possible regulatory pathway of LHPP in STAD. Subsequent experiments showed that low expression of LHPP was observed in STAD patients and cell lines. By in vitro functional experiments, we found that down-regulation of LHPP inhibited cell proliferation. Interestingly, PI3K and AKT (S473) phosphorylation were also inhibited by the overexpression of LHPP. Those results were consistent with other studies and bioinformatic analysis above.

AKT, also known as protein kinase B, is a serine–threonine kinase downstream of the PI3K signaling pathway. It controls a variety of cellular processes, including cell survival, proliferation, differentiation, metabolism, and cytoskeleton re-organization^21,22. As a major effector protein of the PI3K pathway, AKT regulates normal cellular physiology. However, in cancer cells, AKT is one of the most hyperactivated kinases that affect various biological processes in tumorigenesis²³. Frequent activation of AKT has also been reported in approximately 78% of STAD²⁴. Therefore, accumulating evidence indicates that AKT may serve as a promising target for the effective treatment of STAD.

Taken together, our study comprehensively analyzed the correlation of LHPP expression profile with prognostic value, immune cell infiltration, tumor mutational burden, microsatellite instability, mismatch repair genes, and DNA methyltransferases in pan-cancer based on bioinformatics analysis, and investigated the function of LHPP in STAD through in vitro experiments. Our study provides insight into the role of LHPP in tumorigenesis. Further studies are still needed to explore the relationship of LHPP with tumor immunity and the precise mechanism of LHPP in the initiation and progression of STAD.

ACC, Adrenocortical carcinoma; BLCA, Bladder urothelial carcinoma; BRCA, Breast invasive carcinoma; CESC, Cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOL, Cholangiocarcinoma; COAD, Colon adenocarcinoma; CPTAC, Clinical Proteomic Tumor Analysis Consortium dataset; DLBC, Lymphoid neoplasm diffuse large B-cell lymphoma; DSS, Disease specific survival; ESCA, Esophageal carcinoma; GBM, Glioblastoma multiforme; HNSC, Head and neck squamous cell carcinoma; KEGG, Kyoto encyclopedia of genes and genomes; KICH, Kidney chromophobe; KIRC, Kidney renal clear cell carcinoma; KIRP, Kidney renal papillary cell carcinoma; LAML, Acute myeloid leukemia; LGG, Brain Lower grade glioma; LIHC, Liver hepatocellular carcinoma; LUAD, Lung adenocarcinoma; LUSC, Lung squamous cell carcinoma; MESO, Mesothelioma; MMRs, Mismatch repair genes; MSI, Microsatellite instability, OS, Overall survival; OV, Ovarian serous cystadenocarcinoma; PAAD, Pancreatic adenocarcinoma; PCPG, Pheochromocytoma and paraganglioma; PFI, Progression free survival; PRAD, Prostate adenocarcinoma; READ, Rectum adenocarcinoma; SARC, Sarcoma; SKCM, Skin Cutaneous melanoma; STAD, Stomach adenocarcinoma; TCGA, the Cancer Genome Atlas; TGCT, Testicular germ cell tumors; THCA, Thyroid carcinoma; THYM, Thymoma; TMB Tumor mutational burden; UCEC, Uterine corpus endometrial carcinoma; UCS, Uterine carcinosarcoma; UVM, Uveal melanoma;

Acknowledgments

This work was supported by grants from Shaanxi Province Key industries Innovation Groups (2019ZDLSF03-05) and the key R & D program of Shaanxi Provinces (2022SF-291).

Authors’ contributions

WHL conceived this study and wrote the manuscript. DFW conducted the in vitro experiments, draft writing and data analysis. JHL provided assistance for revising the manuscript. All authors read the manuscript and approved for publication.

Data availability statement

The datasets generated and/or analysed during the current study are available in the ScienceDB repository https://www.scidb.cn/anonymous/ZWVxRVJy.

Additional Information

The authors declare no competing interests. All experimental schemes were approved by the Ethics Committee of Shaanxi Provincial People’s Hospital.

Polimanti, R. et al. The Interplay Between Risky Sexual Behaviors and Alcohol Dependence: Genome-Wide Association and Neuroimaging Support for LHPP as a Risk Gene. Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology 42, 598–605, doi:10.1038/npp.2016.153 (2017).
Knowles, E. E. et al. Genome-wide linkage on chromosome 10q26 for a dimensional scale of major depression. Journal of affective disorders 191, 123–131, doi:10.1016/j.jad.2015.11.012 (2016).
Cui, L. et al. Relationship between the LHPP Gene Polymorphism and Resting-State Brain Activity in Major Depressive Disorder. Neural plasticity 2016, 9162590, doi:10.1155/2016/9162590 (2016).
Wu, F., Chen, Y. & Zhu, J. LHPP suppresses proliferation, migration, and invasion and promotes apoptosis in pancreatic cancer. Bioscience reports 40, doi:10.1042/bsr20194142 (2020).
Yang, X. et al. The long intergenic noncoding RNA GAS5 reduces cisplatin-resistance in non-small cell lung cancer through the miR-217/LHPP axis. Aging 13, 2864–2884, doi:10.18632/aging.202352 (2021).
Hou, B. et al. Tumor suppressor LHPP regulates the proliferation of colorectal cancer cells via the PI3K/AKT pathway. Oncology reports 43, 536–548, doi:10.3892/or.2019.7442 (2020).
Li, J. et al. YTHDF2 mediates the mRNA degradation of the tumor suppressors to induce AKT phosphorylation in N6-methyladenosine-dependent way in prostate cancer. Molecular cancer 19, 152, doi:10.1186/s12943-020-01267-6 (2020).
Wang, D. et al. LHPP suppresses tumorigenesis of intrahepatic cholangiocarcinoma by inhibiting the TGFβ/smad signaling pathway. The international journal of biochemistry & cell biology 132, 105845, doi:10.1016/j.biocel.2020.105845 (2021).
Sun, W. et al. LHPP inhibits cell growth and migration and triggers autophagy in papillary thyroid cancer by regulating the AKT/AMPK/mTOR signaling pathway. Acta biochimica et biophysica Sinica 52, 382–389, doi:10.1093/abbs/gmaa015 (2020).
Zheng, J. et al. Down-regulation of LHPP in cervical cancer influences cell proliferation, metastasis and apoptosis by modulating AKT. Biochemical and biophysical research communications 503, 1108–1114, doi:10.1016/j.bbrc.2018.06.127 (2018).
Li, C., Yang, J., Wang, W. & Li, R. LHPP exerts a tumor-inhibiting role in glioblastoma via the downregulation of Akt and Wnt/β-catenin signaling. Journal of bioenergetics and biomembranes 53, 61–71, doi:10.1007/s10863-020-09866-0 (2021).
Hindupur, S. K. et al. The protein histidine phosphatase LHPP is a tumour suppressor. Nature 555, 678–682, doi:10.1038/nature26140 (2018).
Li, Y., Zhang, X., Zhou, X. & Zhang, X. LHPP suppresses bladder cancer cell proliferation and growth via inactivating AKT/p65 signaling pathway. Bioscience reports 39, doi:10.1042/bsr20182270 (2019).
Fridman, W. H. et al. Immune infiltration in human cancer: prognostic significance and disease control. Current topics in microbiology and immunology 344, 1–24, doi:10.1007/82_2010_46 (2011).
Junttila, M. R. & de Sauvage, F. J. Influence of tumour micro-environment heterogeneity on therapeutic response. Nature 501, 346–354, doi:10.1038/nature12626 (2013).
Woo, J. R. et al. Tumor infiltrating B-cells are increased in prostate cancer tissue. Journal of translational medicine 12, 30, doi:10.1186/1479-5876-12-30 (2014).
Berntsson, J., Nodin, B., Eberhard, J., Micke, P. & Jirström, K. Prognostic impact of tumour-infiltrating B cells and plasma cells in colorectal cancer. International journal of cancer 139, 1129–1139, doi:10.1002/ijc.30138 (2016).
Carvajal-Hausdorf, D. E., Mani, N., Velcheti, V., Schalper, K. A. & Rimm, D. L. Objective measurement and clinical significance of IDO1 protein in hormone receptor-positive breast cancer. Journal for immunotherapy of cancer 5, 81, doi:10.1186/s40425-017-0285-7 (2017).
Xu, Y., Lan, S. & Zheng, Q. Prognostic significance of infiltrating immune cell subtypes in invasive ductal carcinoma of the breast. Tumori 104, 196–201, doi:10.5301/tj.5000624 (2018).
Adams, S. et al. Current Landscape of Immunotherapy in Breast Cancer: A Review. JAMA oncology, doi:10.1001/jamaoncol.2018.7147 (2019).
Fruman, D. A. et al. The PI3K Pathway in Human Disease. Cell 170, 605–635, doi:10.1016/j.cell.2017.07.029 (2017).
Janku, F., Yap, T. A. & Meric-Bernstam, F. Targeting the PI3K pathway in cancer: are we making headway? Nature reviews. Clinical oncology 15, 273–291, doi:10.1038/nrclinonc.2018.28 (2018).
Noorolyai, S., Shajari, N., Baghbani, E., Sadreddini, S. & Baradaran, B. The relation between PI3K/AKT signalling pathway and cancer. Gene 698, 120–128, doi:10.1016/j.gene.2019.02.076 (2019).
Nam, S. Y. et al. Akt/PKB activation in gastric carcinomas correlates with clinicopathologic variables and prognosis. APMIS: acta pathologica, microbiologica, et immunologica Scandinavica 111, 1105–1113, doi:10.1111/j.1600-0463.2003.apm1111205.x (2003).

No competing interests reported.

LHPP is associated with favorable survival across diverse cancers with tumor suppressor properties in stomach adenocarcinoma: a pan-cancer analysis

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Background

Methods

Sample information and LHPP expression analysis in human pan-cancer

Prognostic analysis in pan-cancer levels

Immune correlation analysis

Correlation analysis of LHPP expression with TMB and MSI

Correlation analysis of LHPP expression with MMRs and DNA Methyltransferase

LHPP-related gene enrichment analysis

Patients and clinical specimens

Immunohistochemistry (IHC)

Cell culture and transfection

Real-time quantitative PCR assay

Western blot analysis

Cell proliferation assay

Colony formation analysis

Transwell analysis

Statistical analysis

Results

LHPP gene expression in pan-cancer

Full prognostic role of LHPP in pan-cancer

Analysis of LHPP with immune infiltration and tumor microenvironment

Analysis of LHPP with TMB and MSI in human pan-cancer

Analysis of LHPP with MMRs and DNA Methyltransferases

Enrichment analysis of LHPP-related partners

Expression profile of LHPP gene in STAD patients and cell lines

LHPP suppresses cell proliferation of STAD via down-regulating p‑PI3K/p‑AKT expression levels.

Discussion

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1