Exploration of inflammation-prognosis correlation and potential regulatory molecules in adamantinomatous craniopharyngioma

doi:10.21203/rs.3.rs-977629/v2

Download PDF

Research Article

Exploration of inflammation-prognosis correlation and potential regulatory molecules in adamantinomatous craniopharyngioma

https://doi.org/10.21203/rs.3.rs-977629/v2

This work is licensed under a CC BY 4.0 License

Version 2

posted

You are reading this latest preprint version

Purpose

To explore the inflammation-prognosis correlation and potential regulatory molecules in adamantinomatous craniopharyngioma (ACP)

Methods

61 ACP patients who received surgery by either sub-resection or total-resection were included. Kaplan-Meier Curves were drafted to clarify patients’ prognosis in different sub-groups. Kinds of histological staining were used to evaluate the infiltration and activation of inflammatory cells. The expression dataset of GSE94349 was downloaded from Gene Expression Omnibus (GEO) database for series of bioinformatic analysis. Online bioinformatic analysis databases (Oncomine, GEPIA, TIMER, and NetworkAnalyst, et al) were used for a pan-cancer analysis on potential molecules. Finally, fluorescence in situ hybridization (FISH) and western bolt were conducted to verify the connection between target biomarkers and macrophages.

Results

The extent of resection was irrelevant to the progress free survival (PFS) of the ACP patients. Patients with high grade of inflammation showed worse prognosis than those with low and medium grade. More inflammatory cells infiltrated in recurrent tumor but represented with an immune inhibitory phenotype. Fraction of immune cells was calculated, and ACP was loaded with more M0 macrophages and plasma cells. SERPINs were identified and then a pan-cancer analysis was conducted to verify its value in clinic. At last, single cell sequencing database and FISH results reveals SERPINs mainly expressed in macrophages and monocytes.

Conclusion

Our study reveals a connection between inflammation response and poor prognosis in ACP patients. And SERPINs, especially SERPINE1 might be key inflammatory gene, which is relevant to macrophages.

Craniopharyngioma is the most prevalent sellar tumors in children. Adamantinomatous craniopharyngioma (ACP), one of the two CP subtypes, is usually associated with worse clinic outcome and higher rate of recurrence(1). There used to remain controversy about decision on surgical resection extent, which seems that more scholars reach the agreement that sub-resection aimed at critical structure protection, followed with post-surgical adjuvant therapy may have better outcome for ACP patients(2–4). This dilemma makes it essential to control the progress of tumor effectively, whenever pre- or post-surgery.

In recent years, tumor immune microenvironment (TME) and the connection between inflammation and cancers become most highlighted subject in mechanism study(5). Various cytokines and immune cells participate in this crosstalk. For instance, tumor associated macrophages (TAMs), have been considered as key players in TME re-structuring, and the two phenotypes, M1 and M2, usually show as anti- or pro-tumor type. Notwithstanding, there are a host of M1 macrophages observed in TME in progressive tumor, implicating much more obscure immune suppressing exists(6, 7). More notably, researchers found the secretion pattern of ACP is much more different from other pediatric benign brain tumor(8). Similar with kinds of malignant type, ACP is characterized with intense inflammatory response(8–10), while the key player is still unknown.

Serine protease inhibitors (SERPINs) family, function mainly as inhibiting serine protease, and a few serpins can also inhibit caspase and some cysteine proteases. Even more, some serpins do not show any protease inhibitory effect but are presented as other functions. SERPINB family has been found to especially have a strong correlation with epithelial tumor, and SERPINE1 (PAI-1) has much more complex function in cancer progression and metastasis.(11–13). Despite the fact that urokinase-type plasminogen activator (uPA), coupled with PAI-1, have been treated as reliable biomarkers and prognosticators in many cancer types, clear and definite role of the genes are still hiding behind(14).

In this study, we intend to evaluate the relationship of ACP patients’ outcome, with inflammation in tumor and resection of surgery, aiming at identifying potential members in tumor immune environment, exploring their function and discussing its feasibility in further clinic application.

Patients and Tumor Tissue Samples

The study was approved by the Ethic Committee of Xi Jing Hospital, and it was conducted according to the principles expressed in the Declaration of Helsinki.

Clinical data of 61 CP patients who were operated and pathologically diagnosed in Xi Jing Hospital from 2010 to 2020 were collected. Through outpatient clinic follow-up, telephone follow-up and other ways to acquire the prognosis and survival information of the patient. The age, gender, time of initial or recurrence, surgical approach, operation and anesthesia time, hospital stay, postoperative hormone and electrolyte test indexes, tumor pathological type were also gathered. The extent of tumor resection was evaluated according to the intraoperative observation and the scans of head CT or/and MRI. Two groups, gross total resection (GTR) and subtotal resection (SR), were produced based on the extent of tumor resection. The progress-free survival (PFS) was counted from the day of surgical operation till the day of death, relapse or the last follow-up. 25 ACP patients which were available for paraffin tissue were collected for further inflammatory grading analysis.

Data Source and Processing

Clinical baseline and mRNA data of patients from The Cancer Genome Atlas (TCGA) cohort were downloaded from the Gene Expression Profiling Interactive Analysis (GEPIA2; gepia2.cancer-pku.cn)(15). Transcriptional expression profile of ACP, GSE94349, was download from GEO database (ncbi.nlm.nih.gov/geo)(8). Differently expressed (DEGs) were obtained via NetworkAnalyst (networkanalyst.ca)(16). The DEGs were then introduced to R for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Gene Set Enrichment Analysis (GSEA, 4.0.3) were used for pathway enrichment and hub genes selecting. Tumor Immune Estimation Resource (TIMER; timer.cistrome.org/) and Oncomine database (oncomine.org) were used to visually display the mRNA levels of certain molecule in pan-cancer way(17, 18). CIBERSORT (cibersortx.stanford.edu) and Tumor Immune Single-Cell Hub (TISCH; tisch.comp-genomics.org) were used to comprehensively visualize and explore the TME(19, 20). Using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING; string-db.org) to explore the protein-protein interaction (PPI) network, and the network was visualized via Cytoscape (3.9.1)(21). All datasets were retrieved from the published literature, so it was confirmed that all written informed consent was obtained.

Grading of Inflammatory Response in Craniopharyngioma

Two pathologists evaluated the inflammation grades of ACP in a single-blind way (pathologists who were blinded to the clinical details of the case). According to the number of inflammatory cells near the junction of tumor and normal tissue, the evaluation method is executed as follows(22): (1) Continuously observe 10 fields at the junction between the solid and non-solid part of tumor tissue under 400 times light microscope and count the inflammatory cells in each high-power field of vision; (2)The inflammatory cells were averaged in the above 10 fields, and this average was re-averaged between the two pathological observers. The final score of inflammatory cells was used to make a grading, ie, 【Grade 0 (inflammatory cells is zero), Grade 1 (inflammatory cells < 15), Grade 2 (inflammatory cells 15-50 ), Grade 3 (inflammatory cells > 50 )】. The tissue sample would be re-evaluated if its inflammatory cell number reported by the two observers showed a deviation of 10 cells or more. The patients were divided into three subgroups by their inflammatory grade of tumor: (1) Low inflammatory response group with Grade 0-1; (2) Medium inflammatory response group with Grade 2; (3) High inflammatory response group with Grade 3.

HE and IHC/IF Staining

For HE staining, all sections were processed in the following procedures: (1)Dewaxed in routine, dehydrated in gradient alcohol;（2）Dyed with hematoxylin for 8 mins, washed with running water and 1% hydrochloric acid alcohol for color separation, slightly washed with water until returning to blue, rinsed with phosphate buffer for 5 min; (3) Eosin staining for 1 min; (4) Dehydrated, transparent and neutral resin sealed; (5)observed under microscope, photographed.

For immunofluorescence staining, all tissue sections underwent the following steps: (1) Dewaxed, dehydrated; (2) Immersed in fresh 0.05% Triton ×100 for 20 min at 100 ℃ with the membrane broken, incubated in 3% hydrogen peroxide for 30 min; (3)Endogenous peroxidase was removed and washed with PBS for 3 times with each time 5min; (4) The antigen was repaired by microwave and serum blocking solution was added for 1 h; (5) After incubated at 4 ℃ for 24h, the sections were washed with PBS for 3 times; (6) After incubated for 4 hours at room temperature, they were dyed for 5 mins in DAPI staining solution; (7) After cleaned, sections were sealed with anti-fluorescence quencher medium and photographed. PBS was used as negative control instead of primary antibody.

Paraffin-Fluorescence Probe FISH

Tissue block was cleanly washed and then immediately placed in the fixed fluid (DEPC) about 12h for fixation. The tissue was dehydrated and sections were produced before dewaxed, dehydrated, and digested. Sections were added with pre-hybridization solution and incubated for 1 h at 37℃. Next, remove the pre-hybridization solution, then add the probe hybridization solution. Then the sections were incubated in a humidity chamber and hybridized for overnight. Remove the hybridization solution. The sections were washed respectively in 2×SSC for 10 min at 37℃ ，in 1×SSC two times for 5 min each at 37℃, and then in 0.5×SSC for 10 min at room temperature. The following steps are the same to the IF staining procedures.

Statistical Analysis

The relationship between inflammation grades and clinic characteristics of ACP patients was evaluated by Fisher Exact Test. The gene expression and cases of complications was compared between 2 groups by Student t test. Comparisons of immune cells fraction were performed by Kruskal-Wallis test, followed by One-Way ANOVA. Kaplan–Meier curves were constructed to compare progress-free survival (PFS), overall survival (OS) and disease-free survival (RFS) in patient subgroups, and the significance was determined by log-rank test. In CIBERSORT and GSEA, permutations for significance analysis were set as 100 times. Correlations were assessed by Pearson correlation analysis. Clinical data statistical analyses were carried out using SPSS Statistics 24.0. All statistical tests were 2-tailed and P < 0.05 was considered statistically significant.

Patients with different extent of resection shows no difference in prognosis, while inflammatory response in ACP is relevant to poor clinical outcome

In 61 cases, total resection was performed in 36 cases and subtotal resection was in 25 cases (residual part adhered to important structures, tumor or cystic part that is hard to separate) (Table. 1). By comparing the differences of different resection methods and surgical approaches, it was observed that there was no significant difference between postoperative complications and long-term no progress of children (Supplemental Table S1 and S2)

At the end of the follow-up, there were tumor recurrences in 18 patients among all the 59 survived, and the rest two died of electrocytes imbalance and hypothalamus reactions during admission. The relapse time was 6-70 (median 24) months, and the follow-up time was 1-120 (median 21) months. There was no significant difference in recurrence rate in the gender (P = 0.515), and in surgical approaches (P = 0.381). PFS calculated by Kaplan-Meier curve and log rank test revealed that there was no significant difference between the degree of tumor resection and PFS of patients with progression free survival (P = 0.693), that is, compared with the total resection group, the recurrence rate of patients with partial tumor resection was not increased (Fig. 1a).

Among 25 patients who were diagnosed as ACP by postoperative pathology, and accessible to surgical slices, there were 3 cases of low-grade inflammatory response, 12 cases of medium-grade and 10 cases of high-grade, Fisher Exact Test showed that there was no significant difference in the degree of surgical resection between different inflammatory grades (P = 0.276), but there was a high correlation between the degree of surgical resection and tumor progression (P < 0.001). Meanwhile, the survival analysis showed that the prognosis of high-grade group was significantly worse than that of low-grade group (P = 0.022) (Fig. 1b). HE and IHC results showed that more calcification and inflammatory cells were either in recurrent tumor or tumor with sub-resection (Fig. 1c). At the same time, in 6 cases of recurrent tumor tissue, 5 cases were high inflammatory infiltration state. Comparison between before and after the recurrence of the same case, showed more activated M2 (Arg-1⁺) and less M1 (CD86⁺) phenotype of macrophages/microglia, while it was interesting to find that proportion of Iba-1⁺ cells decreased in relapsed tumor (Fig. 1c, d). These results suggested the evidence that inflammatory response might influence the progress of ACP.

Serpins family are potential players in the inflammation response of ACP TME

The results above hinted that inflammation might influence the progress of tumor and ACP patients’ outcome. On the evidence that macrophages and microglia in brain are critical in TME re-building. With GSE94349, we used NetworkAnalyst and GSEA to screen potential functional molecules associated with TAMs and inflammation (Fig. 2a, c). Via GO/KEGG enrichment analysis on differently expressed genes (DEGs), it demonstrated that keratinization, skin and epidermis development are the main physiological activity (Fig. 2b). And it indicated that SERPINs family (SERPINB2, SERPINB5, SERPINE1, SERPING1) were respectively involved in various functional gene sets like macrophages, microglia, inflammatory response and classic inflammation pathway NF-κB (Fig. 2c). Apart from the four genes, we chose top 5 genes in each gene set to demonstrate their relationship. Correlation heatmap showed the potential relationship among those hub genes in different gene sets, and SERPINE1 had significant correlation with SERPINB2, SERPINB5. What’s more, SERPINE1 was also associated with either PRRG4, TNFSF10, DSC2 or SDC1, suggesting a close relationship of these five genes with tumor proliferation, invasion and metastasis (Fig. 2d). And it was worth noting that expression level of SERPING1 showed negative correlation with other genes, suggesting it might participate in different pathways from SERPINE1. IL15, known as functional immune inducing and activation molecules, also showed pertinent connection with SERPINE1, SERPINB2 and SERPING1.

We next used CIBERSORT to verify the immune environment of kinds of brain tumor (ACP, pilocytic astrocytoma, glioblastoma, ependymoma and medulloblastoma) and normal brain tissues, and the results showed high correlation and percentage of M0 macrophage, M2 macrophage, CD4⁺T memory cells, which accounted for more than 60%, indicating involvement of macrophages in tumor environment (Fig. 2e). To evaluate the TME difference between ACP and other brain tumors, comparisons between various immune cells fraction of ACP (n=24), pilocytic astrocytoma (n=10), medulloblastoma (n=15), glioblastoma(n=10), ependymoma (n=34) and normal brain (n=27) tissues were performed. The results revealed that T cells CD8+ and T cells CD4+ activated were lower in all kinds of tumor, and correspondingly, the proportion of T cells CD4+ resting increased, indicating the condition of immune inhibition. More interestingly, the fraction of macrophages M0 significantly boosted exclusively in ACP, and meanwhile the expression of macrophages M2 and plasma cells in ACP were more similar with other aggressive tumors, which described a TME with more inflammatory cells infiltration but weakened immune activity (Fig. 3).

Predicted functions of the SERPINs and its expression may correlated with macrophages

Based on the results that TME of ACP is probably similar with brain invasive tumor (low grade glioma),(10) and on the existed evidence that ACP is capable to malignantly transform into squamous cancer, we compared the transcriptional levels of SERPINs family in tumors with normal tissue in Oncomine database (Supplemental Fig. S1b). It showed SERPINE1 was significantly upregulated in Brain, HNSC and Esophageal Cancer. SERPINB2 and SERPINB5 were more tendinous increasing in Lung Cancer and Gastrointestinal Cancer. The expression level of SERPING1 was higher in Brain, Esophageal Cancer and Lymphoma. The mRNA expression levels of SERPINE1 were significantly in patients of glioma and squamous cancer (Supplemental Table S3).

In addition, pan-cancer analysis in TIMER also showed that the family increased in various cancer like COAD, HNSC, LUSC (P<0.001) (Supplemental Fig. S1a). We then tried to find if there existed similar expression patterns of SERPINs in other relevant cancer type. In GEPIA we chose GBM, LGG and HNSC to explore transcriptional level of SERPINs between tumor and normal tissue. It was found that SERPINE1 and SERPING1 were significantly upregulated in all three cancers. In HNSC, SERPINB5 was higher in tumor tissues while SERPINB2 was lower than normal tissue (Supplemental Fig. S1c).

Correlation between SERPINs expression level and tumor grades (stage) revealed that SERPINs had significant relevance with grades of GBM, while it seemed to have no influence in HNSC (Supplemental Fig. S2a). Kaplan–Meier curves demonstrated SERPINE1, SERPINB2 and SERPING1 were associated with RFS but not OS in GBM patients (P<0.05) (Supplemental Fig. S2b). And all SERPINs had no statistical difference both in OS and RFS in HNSC patients (Supplemental Fig. S3).

PPI network among SERPINs had been established to explore the relationship between upstream and downstream connection and GO/KEGG enrichment was used to explore probable pathway involved with tumor metastasis, invasion and activation of macrophages (Fig. 4a, b). Enrichment pathways consisted of various tumor inflammation pathway, such as matrix constructure, angiogenesis and so on. In TIMER, via kinds of immune infiltration algorithm, there revealed a positive correlation between SERPINs levels and the infiltration levels of macrophages (Fig. 4c).

Using TISCH, we sourced single-cell datasets GSE141982 and GSE131928 to reach a comprehensive exploration of SERPINs and TME. Cell cluster profiles showed that SERPINE1 evidently collocate in macrophages and mononucytes clusters, with slight enrichment in malignant cells and less in other cell types (Fig. 5a). At the same time, SERPING1 had a minor expression level. SERPINB2 and SERPINB5 were both expressed with basic levels in all kinds of cells (Fig. 5b). Gene-gene correlation showed SERPINE1 had a certain relation with SERPINB2 and SERPING1. Besides other SERPINs, SERPINE1 also indicated significant correlation with CD68, CD86, CD163 and CD206 (Supplemental Fig. S4).

At last, we conducted FISH to validate whether there exists colocation between SERPINs and macrophages in ACP, and the result showed there existed evident accumulation of SERPINE1 in macrophages. It was noticeable that SERPINE1⁺ macrophages were more likely located surrounding solid tumor while SERPING1⁺ in cystic part (Fig. 5c).

ACP is one of the most prevalent sellar tumors, which usually results in severe visual impairment, dysplasia and endocrine disorders. Worse primary location and poor prognosis, require that more comprehensive knowledge and systemic treatment are needed in ACP patients(1).

In this study, from clinic perspective, we conducted retrospective study to explore the relationship between inflammation and clinic outcomes of ACP patients, providing further evidence for the research on the relationship between prognosis and inflammation.

Generally, it’s found in most tumors that inflammation has a significant correlation with the progress(23). Current understanding is normally about severe tissue adhesion and calcification, which indirectly affected the difficulty of surgery(24). Thus, based on the hypothesis that inflammation inducing tumor adhesion to surrounding tissues might influence the extent of surgery. We drafted Kaplan-Meier curves to evaluate the prognosis of 61 ACP patients. The results showed that two groups with different extent of resection didn’t have difference in PFS, as well as other post-surgery complications. And by comparing the prognosis of patients with different inflammation cells infiltration grades, we found that inflammation response could also be a key factor that influence the progress of the ACP. In the meanwhile, it’s untrustworthy of evaluating the inflammation response by degree of resection. In actual, reducing the extra damage caused by surgical intervention might be helpful to improve the endocrine condition of patient, and accompanied with adjuvant therapy, ideal therapeutic target can be accomplished.

Though various of inflammatory modulators have been found up-regulating in ACP, the function of these cytokines is still unknown. Through comparing the infiltration and activation of inflammatory cells between primary tumor and tumor with relapse, we found that while total amount of inflammatory cells arisen, the immune response wielding anti-tumor function might be weakened. The role of inflammation in tumor has been debated for a long time, and in paradigm, researchers usually categorize inflammation into pro- or anti- types, such as TAMs(6), which are recognized as M1 or M2 phenotype. It’s intelligible that M2 are more predominant in tumor with progressiveness. However, as matter of fact, M1 type is also abundant in various tumor tissue, and probably associated with tumor metastasis(25). IF and IHC results showed more M2 macrophages were activated and recruited in recurrent tumor, compared with the primary, while Iba-1⁺ cells were less in recurrent tumor. Overall, the phenotype of inflammation is predisposed to be inhibitory.

Similar fierce inflammation response with malignant TME hints that ACP may share a certain series of molecules associated with tumor progress or recurrence(8, 9, 22).Uncovering the behind mechanism and intending to target definite molecules are critical. In GSE94349, we used CIBERSORT to evaluate immune cells fraction in ACP, and other prevalent pediatric brain tumors. Results showed that the percentage of M0 macrophages in ACP are much higher than other brain tumors. At the same time, rather than PA, the proportion of macrophages M2 and plasma cells in ACP were more similar with other aggressive tumors, indicating its TME being consistent with its malignant biological behaviors. Nevertheless, this kind of immune inhibiting mechanism needs further exploration and more comprehensive understanding beyond traditional classification based on surface markers is needed. We also applied the same series for DEGs and gene set enrichment analysis, and various immune and inflammatory pathway were activated in ACP. Among those hub genes, SERPINs were significantly enriched. TME analysis showed macrophages were prominent in ACP tissue and SERPINs family (SERPINE1, SERPINB2, SERPINB5 and SERPING1), which was closely related to various inflammatory mediators, might participate into the reaction in some way.

SERPINs belong to a protein inhibitors super-family with the most members, presented with complex function like maintaining signals in proliferation, anti-apoptosis, angiogenesis, causing oxidative stress, inducing inflammation response in tumor and facilitating metastasis(26).

Apart from the evidence that ACP shows more aggressive biological behavior than any other benign brain tumors and is characterized with malignant clinic course,(10) there also exists kinds of viewpoint that the tumor might result in gliosis(27, 28), or the reactive ependymoma appearing after partial resection of a craniopharyngioma and repeated postoperative radiotherapy(29, 30). What’s more, SERPINE1 has already been confirmed as the regulator of glioblastoma growth and invasion(31). Therefore, it is speculated that ACP may share kinds of certain biological process similar with malignant tumor like glioma. Thus, we validated clinic value of SERPINs for expression level and prognosis prediction in glioblastoma. In present study, it’s found that all four SERPINs were overexpressed in GBM and significantly associated with cancer progress. Single cells profiles showed SERPINE1 was evidently enriched in macrophages, providing proof about its intervention in recruitment and polarization of TAMs. Function verification experiments are needed in further research.

SERPINE1 (plasminogen activator inhibitor-1, PAI-1) is upregulated in various of tumors, and has been recognized as a strong predictor of poor outcome and worse response to treatment(11, 14). Apart from inducing angiogenesis, it also has been found be able to promote the recruitment of macrophages and M2 polarization. SERPINE1 is also observed to be effective in the migration of mononuclear cells, thus it’s probably that in ACP, SERPINE1 also function as key driver to recruit macrophages and other immune cells to tumor, which then proceed the re-building of TME. And the complex crosstalk between PAI-1, IL-6, IL-10 and other cytokines make it need more precise experiment to clarify certain mechanism(11, 32). In this study, we found SERPINE1 has potential predictive value and has similar expression profile in ACP and GBM, suggesting the molecule can be treated as target in prognosis prediction or therapy.

SERPINB2 and SERPINB5 have been recognized as tumor suppressor genes, especially in gastrointestinal and other epithelial tumor(12, 13, 33). Theoretically, downregulating these genes may lead to tumor growth invasion and metastasis, and some studies indeed have verified it. However, similar with SERPINE1, SERPINB2 and SERPINB5 seem not simply downregulated in tumors, both two can also have higher transcriptional levels in some epithelial-origins tumors. This paradoxical phenomenon indicates the complexity of TME, and further exploration is needed.(11) What’s more, SERPING1, normally having negative correlation with clinic outcome in other cancer or immune dysregulating disease(34, 35), shows positive correlation with other genes in GBM while negative in ACP. Thus, we hypothesize SERPING1 has a more intricate crosstalk in inflammation mediator network.

In summary, the study firstly analyzed the correlation between inflammation in ACP and clinic factors, via a single-center retrospective study, coupled with histological results which showed the accumulation of macrophages and other inflammatory cells. Furthermore, through various of biological information methods, we provided a landscape of TME in ACP, to sketch this inflammatory crosstalk. From the molecular level, we selected SERPINs as potential players related to inflammation response. Additionally, through a series of pan-cancer analysis, we evaluated the predictive potentials of SERPINs, from clinic prognosis to probable biological activity, revealing the possibility of functional molecules for treatment target and prediction of prognosis. And it’s plausible to conjecture that SERPINE1 has a close relationship with macrophages. While treatment targeting SERPINs is still challenging, for definite roles of them are still sophisticated, it’s worth using them as supplementary predication markers. More validating experiments are needed, regardless of the difficulties like lack of stable ACP cell lines in vitro and animal models. We hope our data can provide additional clues and evidence for other research in ACP inflammation and at last, enhancing the welfare of ACP patients.

Taken together, the results of the study demonstrated that under the condition of protecting neurological function and being supplemented by necessary adjuvant treatments, sub-resection and total resection show no difference in ACP progress or recurrence. At the same time, inflammation response in ACP may be key factor that influences the prognosis of the patient. What’s more, despite that numerous of inflammatory and immune cells accumulate in ACP, the immune response in ACP might be under inhibition. SERPINs, especially SERPINE1, is found to be up regulated, and involved in the interaction with inflammatory regulating genes. Apart from that, we found that SERPINE1 may have a certain correlation with macrophages, of which value in clinic prognosis was also proved via pan-cancer analysis. Thus, evaluating or regulating inflammation in ACP can be helpful to better improve the prognosis of the patients, and targeting SERPINE1 may have a therapeutic promise.

CP: Craniopharyngioma; ACP: Adamantinomatous craniopharyngioma; GEO: Gene Expression Omnibus; TME: Tumor microenvironment; PFS: progress free survival; OS： Overall survival; RFS: Disease-free survival; DEGs: Differently expressed genes; GO: Gene ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; PPI: Protein–protein interaction; GSEA: Gene set enrichment analysis; SERPINs: Serine protease inhibitors; PAI-1: Plasminogen activator inhibitor-1; uPA : Urokinase-type plasminogen activator; TAMs: Tumor associated macrophages; GTR: Gross total resection; SR: subtotal resection; TCGA: The Cancer Genome Atlas; IHC/IF: Immunohistochemistry/Immunofluorescence; FISH: Fluorescence in situ hybridization.

Acknowledgement

We thank Dr. Donson for the generosity of data sharing.

Author Contributions

Y. J. and G. W. designed the study. J. W. and E. K. collected the data, carried out data analyses. Y. Y. produced the initial draft of the manuscript. Y. J. and G. W. contributed to drafting and finishing the manuscript. J. W. was responsible for pathologic and histologic experiments. All authors had read and approved the final submitted manuscript.

Funding

The present work was supported by the Natural Science Foundation of China (NSFC) grant to Xiaosheng He (Nos. 81971156)

Availability of data and materials

The datasets generated during and/or analyzed during the current study are available in the Gene Expression Omnibus (GEO) datasets (http://www.ncbi.nlm.nih.gov/geo/).

Ethics approval and consent to participate

This study was approved by the Ethics Committee of Xi Jing Hospital (approval number: KY20212135-F-1)

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests

Muller HL, Merchant TE, Warmuth-Metz M, Martinez-Barbera JP, Puget S (2019) Craniopharyngioma[J]. Nat Rev Dis Primers,2019,5(1):75.10.1038/s41572-019-0125-9
Muller HL (2011) Consequences of craniopharyngioma surgery in children[J]. J Clin Endocrinol Metab 2011 96(7):1981–1991 10.1210/jc.2011 – 0174
Muller HL (2006) More or less? Treatment strategies in childhood craniopharyngioma[J]. Childs Nerv Syst,2006,22(2):156-157.10.1007/s00381-005-1192-7
Sadashivam S, Menon G, Abraham M, Nair SN (2020) Adult craniopharyngioma: The role of extent of resection in tumor recurrence and long-term functional outcome[J]. Clin Neurol Neurosurg,2020,192:105711.10.1016/j.clineuro.2020.105711
Hui L, Chen Y (2015) Tumor microenvironment: Sanctuary of the devil[J]. Cancer Lett,2015,368(1):7-13.10.1016/j.canlet.2015.07.039
Pathria P, Louis TL, Varner JA (2019) Targeting Tumor-Associated Macrophages in Cancer[J]. Trends Immunol,2019,40(4):310-327.10.1016/j.it.2019.02.003
Hambardzumyan D, Gutmann DH, Kettenmann H (2016) The role of microglia and macrophages in glioma maintenance and progression[J]. Nat Neurosci,2016,19(1):20-27.10.1038/nn.4185
Donson AM, Apps J, Griesinger AM, Amani V, Witt DA, Anderson R, Niazi TN, Grant G, Souweidane M, Johnston JM, Jackson EM, Kleinschmidt-Demasters BK, Handler MH, Tan AC, Gore L (2017) Molecular Analyses Reveal Inflammatory Mediators in the Solid Component and Cyst Fluid of Human Adamantinomatous Craniopharyngioma[J]. J Neuropathol Exp Neurol,2017,76(9):779-788.10.1093/jnen/nlx061
Whelan R, Prince E, Gilani A, Hankinson T (2020) The Inflammatory Milieu of Adamantinomatous Craniopharyngioma and Its Implications for Treatment[J]. J Clin Med,2020,9(2).10.3390/jcm9020519
Petralia F, Tignor N, Reva B, Koptyra M, Chowdhury S, Rykunov D, Krek A, Ma W, Zhu Y, Ji J, Calinawan A, Whiteaker JR, Colaprico A, Stathias V, Omelchenko T (2020) Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer[J]. Cell,2020,183(7):1962-1985.10.1016/j.cell.2020.10.044
Kubala MH, Declerck YA (2019) The plasminogen activator inhibitor-1 paradox in cancer: a mechanistic understanding[J]. Cancer Metastasis Rev,2019,38(3):483-492.10.1007/s10555-019-09806-4
Bodenstine TM, Seftor RE, Khalkhali-Ellis Z, Seftor EA, Pemberton PA, Hendrix MJ (2012) Maspin: molecular mechanisms and therapeutic implications[J]. Cancer Metastasis Rev,2012,31(3–4):529-551.10.1007/s10555-012-9361-0
Dzinic SH, Bernardo MM, Li X, Fernandez-Valdivia R, Ho YS, Mi QS, Bandyopadhyay S, Lonardo F, Vranic S, Oliveira DS, Bonfil RD, Dyson G, Chen K, Omerovic A, Sheng X (2017) An Essential Role of Maspin in Embryogenesis and Tumor Suppression[J]. Cancer Res,2017,77(4):886-896.10.1158/0008-5472.CAN-16-2219
Kubala MH, Punj V, Placencio-Hickok VR, Fang H, Fernandez GE, Sposto R, Declerck YA (2018) Plasminogen Activator Inhibitor-1 Promotes the Recruitment and Polarization of Macrophages in Cancer[J]. Cell Rep,2018,25(8):2177-2191.10.1016/j.celrep.2018.10.082
Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z (2017) GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses[J]. Nucleic Acids Res,2017,45(W1):W98-W102.10.1093/nar/gkx247
Zhou G, Soufan O, Ewald J, Hancock R, Basu N, Xia J (2019) NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis[J]. Nucleic Acids Res,2019,47(W1):W234-W241.10.1093/nar/gkz240
Li B, Severson E, Pignon JC, Zhao H, Li T, Novak J, Jiang P, Shen H, Aster JC, Rodig S, Signoretti S, Liu JS, Liu XS (2016) Comprehensive analyses of tumor immunity: implications for cancer immunotherapy[J]. Genome Biol,2016,17(1):174.10.1186/s13059-016-1028-7
Rhodes DR, Yu J, Shanker K, Deshpande N, Varambally R, Ghosh D, Barrette T, Pandey A, Chinnaiyan AM (2004) ONCOMINE: a cancer microarray database and integrated data-mining platform[J]. Neoplasia,2004,6(1):1-6.10.1016/s1476-5586(04)80047-2
Sun D, Wang J, Han Y, Dong X, Ge J, Zheng R, Shi X, Wang B, Li Z, Ren P, Sun L, Yan Y, Zhang P, Zhang F, Li T (2021) TISCH: a comprehensive web resource enabling interactive single-cell transcriptome visualization of tumor microenvironment[J]. Nucleic Acids Res,2021,49(D1):D1420-D1430.10.1093/nar/gkaa1020
Newman AM, Steen CB, Liu CL, Gentles AJ, Chaudhuri AA, Scherer F, Khodadoust MS, Esfahani MS, Luca BA, Steiner D, Diehn M, Alizadeh AA (2019) Determining cell type abundance and expression from bulk tissues with digital cytometry[J]. Nat Biotechnol,2019,37(7):773-782.10.1038/s41587-019-0114-2
Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, Kuhn M, Bork P, Jensen LJ, von Mering C (2015) STRING v10: protein-protein interaction networks, integrated over the tree of life[J]. Nucleic Acids Res,2015,43(Database issue):D447-D452.10.1093/nar/gku1003
Peng J, Yang L, Pan J, Wang C, Nie J, Liu Y, Fan J, Zhou J, Qi S (2021) Clinical features and prognosis of pediatric infradiaphragmatic craniopharyngioma relative to the tumor inflammatory response[J]. Pediatr Res,2021,89(5):1119-1125.10.1038/s41390-020-1013-4
Kinoshita T, Goto T (2021) Links between Inflammation and Postoperative Cancer Recurrence[J]. J Clin Med,2021,10(2).10.3390/jcm10020228
Chen M, Zhang Z, Yang M, Li ST (2019) Prediction of calcification tendency in pediatric cystic adamantinomatous craniopharyngioma by using inflammatory markers, hormone markers, and radiological appearances[J]. Childs Nerv Syst,2019,35(7):1173-1180.10.1007/s00381-019-04178-0
Cho U, Kim B, Kim S, Han Y, Song YS (2018) Pro-inflammatory M1 macrophage enhances metastatic potential of ovarian cancer cells through NF-kappaB activation[J]. Mol Carcinog,2018,57(2):235-242.10.1002/mc.22750
Guadagno NA, Moriconi C, Licursi V, D'Acunto E, Nisi PS, Carucci N, De Jaco A, Cacci E, Negri R, Lupo G, Miranda E (2017) Neuroserpin polymers cause oxidative stress in a neuronal model of the dementia FENIB[J]. Neurobiol Dis,2017,103:32-44.10.1016/j.nbd.2017.03.010
Pettorini BL, Inzitari R, Massimi L, Tamburrini G, Caldarelli M, Fanali C, Cabras T, Messana I, Castagnola M, Di Rocco C (2010) The role of inflammation in the genesis of the cystic component of craniopharyngiomas[J]. Childs Nerv Syst,2010,26(12):1779-1784.10.1007/s00381-010-1245-4
Tena-Suck ML, Morales-Del AA, Hernandez-Campos ME, Fernandez-Valverde F, Ortiz-Plata A, Hernandez AD, Santamaria A (2015) Ultrastructural characterization of craniopharyngioma at the tumor boundary: A structural comparison with an experimental toxic model using "oil machinery" fluid, with emphasis on Rosenthal fibers[J]. Acta Histochem,2015,117(8):696-704.10.1016/j.acthis.2015.09.006
Tolnay M, Kaim A, Probst A, Ulrich J (1996) Subependymoma of the third ventricle after partial resection of a craniopharyngioma and repeated postoperative irradiation[J]. Clin Neuropathol,1996,15(2):63–66
Ho KC, Meyer G, Caya J, Tieu TM, Prentiss A (1987) Craniopharyngioma and "reactive" subependymoma of the third ventricle–a case report[J]. Clin Neuropathol,1987,6(1):12–15
Seker F, Cingoz A, Sur-Erdem 0, Erguder N, Erkent A, Uyulur F, Esai Selvan M, Gümüş ZH, Gönen M, Bayraktar H, Wakimoto H, Bagci-Onder T (2019) Identification of SERPINE1 as a Regulator of Glioblastoma Cell Dispersal with Transcriptome Profiling[J]. Cancers,2019,11(11):1651.10.3390/cancers11111651
Zhou J, Zhang C, Pan J, Chen L, Qi ST (2017) Interleukin6 induces an epithelialmesenchymal transition phenotype in human adamantinomatous craniopharyngioma cells and promotes tumor cell migration[J]. Mol Med Rep,2017,15(6):4123-4131.10.3892/mmr.2017.6538
Westrick RJ, Rojkjaer LP, Yang AY, Roh MH, Siebert AE, Ginsburg D (2020) Deficiency of plasminogen activator inhibitor-2 results in accelerated tumor growth[J]. J Thromb Haemost,2020,18(11):2968-2975.10.1111/jth.15054
Mete GN, Gulbahar O, Onay H, Peker KZ, Ozgul S, Kose T, Gelincik A, Buyukozturk S, Sin AZ (2019) Deletions in SERPING1 Lead to Lower C1 Inhibitor Function: Lower C1 Inhibitor Function Can Predict Disease Severity[J]. Int Arch Allergy Immunol,2019,178(1):50-59.10.1159/000492583
Jovcevska I (2019) Genetic secrets of long-term glioblastoma survivors[J]. Bosn J Basic Med Sci,2019,19(2):116-124.10.17305/bjbms.2018.3717

		Extent of Resection
Factors		Gross	Sub-Gross	Total	P Value
		N（%）	N（%）	N
Age	≤6	13（54.2）	11（45.8）	24	0.819
	6~12	16（61.5）	10（38.5）	26
	＞12	7 （63.6）	4 （36.4）	11
Gender	Man	19（65.5）	10（34.5）	29	0.235
	Woman	17（53.1）	15（46.9）	32
Number of Lesions	Single	36（62.1）	22（37.9）	58	0.064
	Multiple	0 （0）	3 （100）	3
Property of Lesions	Cystic-solid	23（71.9）	9 （28.1）	32	0.081
	Cystic	11（47.8）	12（52.2）	23
	Solid	2 （33.3）	4 （66.7）	6
Type of Surgery	Craniotomy	33（58.9）	23（41.1）	56	0.671
	Endoscopy	3 （60）	2 （40）	5
Postoperative Hospital Stays	≤14	24（57.1）	18（42.9）	42	0.451
	＞14	12 （63.2）	7 （36.8）	19

Table 1. Baseline information of patients

No competing interests reported.

supplemental.docx

Download PDF

Version 2

posted

You are reading this latest preprint version

Exploration of inflammation-prognosis correlation and potential regulatory molecules in adamantinomatous craniopharyngioma

Status:

Version 2

Abstract

Purpose

Methods

Results

Conclusion

Figures

Introduction

Material And Method

Results

Discussion

Conclusion

Abbreviations

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 2