Prognostic Significance of Pregnancy Zone Protein and Its Correlation with Immune Infiltrates in Hepatocellular Carcinoma

Host-defence caerin 1.1 and 1.9 peptides suppress glioblastoma U87 and U118 cell proliferation through the modulation of mitochondrial respiration and induce the downregulation of CHI3L1

Glioblastoma, the most aggressive form of brain cancer, poses a significant global health challenge with a considerable mortality rate. With the predicted increase in glioblastoma incidence, there is an urgent need for more effective treatment strategies. In this study, we explore the potential of caerin 1.1 and 1.9, host defence peptides derived from an Australian tree frog, in inhibiting glioblastoma U87 and U118 cell growth. Our findings demonstrate the inhibitory impact of caerin 1.1 and 1.9 on cell growth through CCK8 assays. Additionally, these peptides effectively curtail the migration of glioblastoma cells in a cell scratch assay, exhibiting varying inhibitory effects among different cell lines. Notably, the peptides hinder the G0/S phase replication in both U87 and U118 cells, pointing to their impact on the cell cycle. Furthermore, caerin 1.1 and 1.9 show the ability to enter the cytoplasm of glioblastoma cells, influencing the morphology of mitochondria. Proteomics experiments reveal intriguing insights, with a decrease in CHI3L1 expression and an increase in PZP and JUNB expression after peptide treatment. These proteins play roles in cell energy metabolism and inflammatory response, suggesting a multifaceted impact on glioblastoma cells. In conclusion, our study underscores the substantial anticancer potential of caerin 1.1 and 1.9 against glioblastoma cells. These findings propose the peptides as promising candidates for further exploration in the realm of glioblastoma management, offering new avenues for developing effective treatment strategies.

High-Level Secretion of Pregnancy Zone Protein Is a Novel Biomarker of DNA Damage-Induced Senescence and Promotes Spontaneous Senescence

Identification of unique and specific biomarkers to better detect and quantify senescent cells remains challenging. By a global proteomic profiling of senescent human skin BJ fibroblasts induced by ionizing radiation (IR), the cellular level of pregnancy zone protein (PZP), a presumable pan-protease inhibitor never been linked to cellular senescence before, was found to be decreased by more than 10-fold, while the level of PZP in the conditioned medium was increased concomitantly. This observation was confirmed in a variety of senescent cells induced by IR or DNA-damaging drugs, indicating that high-level secretion of PZP is a novel senescence-associated secretory phenotype. RT-PCR examination verified that the transcription of the PZP gene is enhanced in various cells at senescence or upregulated following DNA damage treatment in a p53-independent manner. Moreover, pretreatment with late pregnancy serum containing a high level of PZP led to inhibition of doxorubicin-induced senescence in A549 cells, and depletion of PZP in the pregnancy serum could enhance such inhibition. Finally, the addition of immuno-precipitated PZP complexes into tissue culture attenuated the growth of A549 cells and promoted the spontaneous senescence. Therefore, we revealed that high-level secretion of PZP is a novel and unique feature associated with DNA damage-induced senescence, and secreted PZP is a positive regulator of cellular senescence, particularly during the late stage of gestation.

Pregnancy Zone Protein Serves as a Prognostic Marker and Favors Immune Infiltration in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is a public enemy with a very high incidence and mortality rate, for which there is no specific detectable biomarker. Pregnancy zone protein (PZP) is an immune-related protein; however, the functions of PZP in LUAD are unclear. In this study, a series of bioinformatics methods, combined with immunohistochemistry (IHC), four-color multiplex fluorescence immunohistochemistry (mIHC), quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA), were utilized to explore the prognostic value and potential role of PZP in LUAD. Our data revealed that PZP expression was markedly reduced in LUAD tissues, tightly correlated with clinical stage and could be an independent unfavorable prognostic factor. In addition, pathway analysis revealed that high expression of PZP in LUAD was mainly involved in immune-related molecules. Tumor immune infiltration analysis by CIBERSORT showed a significant correlation between PZP expression and several immune cell infiltrations, and IHC further confirmed a positive correlation with CD4+ T-cell infiltration and a negative correlation with CD68+ M0 macrophage infiltration. Furthermore, mIHC demonstrated that PZP expression gave rise to an increase in CD86+ M1 macrophages and a decrease in CD206+ M2 macrophages. Therefore, PZP can be used as a new biomarker for the prediction of prognosis and may be a promising immune-related molecular target for LUAD.

Identification of HM13 as a prognostic indicator and a predictive biomarker for immunotherapy in hepatocellular carcinoma

Background

Histocompatibility minor 13 (HM13) is a signal sequence stubbed intramembrane cleavage catalytic protein that is essential for cell signaling, intracellular communication, and cancer. However, the expression of HM13 and its prognostic value, association with tumor-infiltrating immune cells (TIICs) in the microenvironment, and potential to predict immunotherapeutic response in HCC are unknown.

Methods

The HM13 expression, clinicopathology analysis, and its influence on survival were analyzed in multiple public databases and further verified in collected HCC and normal tissues by qRT-PCR and immunohistochemistry staining assay (IHC). Furthermore, the lentivirus vector encoding HM13-shRNA to manipulate HM13 expression was selected to investigate whether HM13 could influence the malignant growth and metastasis potential of HCC cells. Finally, significant impacts of HM13 on the HCC tumor microenvironment (TME) and reaction to immune checkpoint inhibitors were analyzed.

Results

Upregulated HM13 was substantially correlated with poor prognosis in patients with HCC, and could facilitate the proliferation and migratory potential of HCC cells. Additionally, patients with high HM13 expression might be more sensitive to immunotherapy.

Conclusions

HM13 might be a prognostic biomarker and potential molecular therapeutic target for HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09987-2.

Identification of two immune-related risk score signatures through integrated analysis of multi-omics data in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide. Immunotherapy has become a major treatment for advanced HCC, but the therapeutic effects remain unsatisfactory. In this study, we constructed an immune cell risk score (ICS) and an immune cell-related gene risk score (ICRGS) for the prognosis prediction of HCC through integrated analysis of bulk and single-cell RNA (scRNA) sequencing data. These two risk score signatures both showed good predictive values in the training and validation cohorts. The potential interactions among these prognostic immune cell types were elucidated by cell-cell communication analysis. The results of enrichment analysis and gene set enrichment analysis (GSEA) of the prognostic genes showed that metabolic-related processes were involved in the immune response of HCC. Furthermore, the results of correlation analyses further confirmed the hub genes that were strongly correlated with immune cells. Finally, potential therapeutic drugs targeting these hub genes were screened by CellMiner based on NCI-60 cell line set. Taken together, two useful models for the prognosis prediction of HCC patients were constructed in this study. The functional differences between the two groups of HCC patients separated by ICS or ICRGS provide fundamental knowledge for finding synergistic therapeutic targets for HCC immunotherapy.

Platelet-Related Molecular Subtype to Predict Prognosis in Hepatocellular Carcinoma

Purpose

Complex crosstalk between tumor cells and platelets is closely related to the development, relapse, and drug resistance of hepatocellular carcinoma (HCC). Therefore, an intensive analysis of the relationship between platelet-related genes and the effectiveness of immunotherapy is necessary for improving the poor prognosis of HCC patients.

Methods

Genes associated with platelets in the GeneCards database were collected and were used to identify molecular subtypes using a non-negative matrix decomposition algorithm (NMF) and constructed a platelet-related genes-based prognostic stratification model by the LASSO-Cox regression and stepwise Cox regression analysis. The effect of this feature on the immune microenvironment of HCC and the response to immune checkpoint inhibitors was also explored.

Results

After identifying two molecular subtypes, we constructed a platelet-related genes-based prognostic stratification model that can be effectively used for immune checkpoint inhibitor (PD1, PD-L1, PD-L2, and CTLA4) efficacy and prognosis prediction in HCC patients, which was subsequently validated using patient samples from ICGC, GSE14520 and a small sample size clinical cohort. We also found downregulation of PAFAH1B3 remarkably inhibited the proliferation and migration ability of Hep3B cells by cytological experiments.

Conclusion

We constructed a prognostic classifier based on platelet-related genes that could effectively classify HCC patients for prognostic prediction and provide new light on the selection of optimal individualized antiplatelet therapy for HCC patients in future clinical practice.

Identification and Validation of a Novel Six-Gene Expression Signature for Predicting Hepatocellular Carcinoma Prognosis

Background

Hepatocellular carcinoma (HCC) is a highly lethal disease. Effective prognostic tools to guide clinical decision-making for HCC patients are lacking.

Objective

We aimed to establish a robust prognostic model based on differentially expressed genes (DEGs) in HCC.

Methods

Using datasets from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the International Genome Consortium (ICGC), DEGs between HCC tissues and adjacent normal tissues were identified. Using TCGA dataset as the training cohort, we applied the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analyses to identify a multi-gene expression signature. Proportional hazard assumptions and multicollinearity among covariates were evaluated while building the model. The ICGC cohort was used for validation. The Pearson test was used to evaluate the correlation between tumor mutational burden and risk score. Through single-sample gene set enrichment analysis, we investigated the role of signature genes in the HCC microenvironment.

Results

A total of 274 DEGs were identified, and a six-DEG prognostic model was developed. Patients were stratified into low- or high-risk groups based on risk scoring by the model. Kaplan-Meier analysis revealed significant differences in overall survival and progression-free interval. Through univariate and multivariate Cox analyses, the model proved to be an independent prognostic factor compared to other clinic-pathological parameters. Time-dependent receiver operating characteristic curve analysis revealed satisfactory prediction of overall survival, but not progression-free interval. Functional enrichment analysis showed that cancer-related pathways were enriched, while immune infiltration analyses differed between the two risk groups. The risk score did not correlate with levels of PD-1, PD-L1, CTLA4, or tumor mutational burden.

Conclusions

We propose a six-gene expression signature that could help to determine HCC patient prognosis. These genes may serve as biomarkers in HCC and support personalized disease management.

A novel tumor doubling time-related immune gene signature for prognosis prediction in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) has become a global health issue of wide concern due to its high prevalence and poor therapeutic efficacy. Both tumor doubling time (TDT) and immune status are closely related to the prognosis of HCC patients. However, the association between TDT-related genes (TDTRGs) and immune-related genes (IRGs) and the value of their combination in predicting the prognosis of HCC patients remains unclear. The current study aimed to discover reliable biomarkers for anticipating the future prognosis of HCC patients based on the relationship between TDTRGs and IRGs.

Methods

Tumor doubling time-related genes (TDTRGs) were acquired from GSE54236 by using Pearson correlation test and immune-related genes (IRGs) were available from ImmPort. Prognostic TDTRGs and IRGs in TCGA-LIHC dataset were determined to create a prognostic model by the LASSO-Cox regression and stepwise Cox regression analysis. International Cancer Genome Consortium (ICGC) and another cohort of individual clinical samples acted as external validations. Additionally, significant impacts of the signature on HCC immune microenvironment and reaction to immune checkpoint inhibitors were observed.

Results

Among the 68 overlapping genes identified as TDTRG and IRG, a total of 29 genes had significant prognostic relevance and were further selected by performing a LASSO-Cox regression model based on the minimum value of λ. Subsequently, a prognostic three-gene signature including HECT domain and ankyrin repeat containing E3 ubiquitin protein ligase 1 (HACE1), C-type lectin domain family 1 member B (CLEC1B), and Collectin sub-family member 12 (COLEC12) was finally identified by stepwise Cox proportional modeling. The signature exhibited superior accuracy in forecasting the survival outcomes of HCC patients in TCGA, ICGC and the independent clinical cohorts. Patients in high-risk subgroup had significantly increased levels of immune checkpoint molecules including PD-L1, CD276, CTLA4, CXCR4, IL1A, PD-L2, TGFB1, OX40 and CD137, and are therefore more sensitive to immune checkpoint inhibitors (ICIs) treatment. Finally, we first found that overexpression of CLEC1B inhibited the proliferation and migration ability of HuH7 cells.

Conclusions

In summary, the prognostic signature based on TDTRGs and IRGs could effectively help clinicians classify HCC patients for prognosis prediction and individualized immunotherapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02227-w.

Serum exosomal pregnancy zone protein as a promising biomarker in inflammatory bowel disease

BACKGROUND

Inflammatory bowel disease (IBD) is a kind of intestinal immune dysfunction disease, and its occurrence and prevalence are on the rise worldwide. As a chronic gastrointestinal disease, its pathogenesis is still unknown. Exosomes are vesicles in various body fluids that carry a variety of substances. They can mediate intercellular communication and long-distance transport of multiple media. In this study, we investigated the protein profile of serum exosomes from healthy people and IBD patients to explore a new serological biomarker for IBD.

METHODS

Initially, exosomes were extracted from serum samples, and the proteins within the exosomes were identified by label-free liquid chromatography/mass spectrometry (LC-MS/MS). Western blot and ELISA were used to assess the identified protein. To further analyze the target protein, an acute colitis mouse model was established, and exosomes in colonic tissue and serum were extracted to investigate the protein in them.

RESULTS

Firstly, serum exosomes were extracted from samples, and proteins in exosomes were identified by LC-MS/MS. Through statistical analysis, we identified 633 proteins. Among these proteins, pregnancy zone protein (PZP) showed a marked difference between patients with IBD and healthy people, in that its expression level was much higher in the IBD patients This exosomal protein was associated with immunosuppressive effects. Also, the level of PZP in colon tissue exosomes and serum exosomes of acute colitis mice was significantly higher than that of the control group.

CONCLUSIONS

Our findings indicated that serum exosome PZP was present at a high level in the IBD patients. Hence it might be a promising biomarker and enhance auxiliary diagnosis of IBD.

Tumor infiltrating lymphocytes associated competitive endogenous RNA networks as predictors of outcome in hepatic carcinoma based on WGCNA analysis

BACKGROUND

The important regulatory role of competitive endogenous RNAs (ceRNAs) in hepatocellular carcinoma (HCC) has been confirmed. Tumor infiltrating lymphocytes (TILs) are of great significance to tumor outcome and prognosis. This study will systematically analyze the key factors affecting the prognosis of HCC from the perspective of ceRNA and TILs.

METHODS

The Cancer Genome Atlas (TCGA) database was used for transcriptome data acquisition of HCC. Through the analysis of the Weighted Gene Co-expression Network Analysis (WCGNA), the two modules for co-expression of the disease were determined, and a ceRNA network was constructed. We used Cox regression and LASSO regression analysis to screen prognostic factors and constructed a risk score model. The Gene Expression Omnibus (GEO) was used to validate the model. The Kyoto Encyclopedia of Genes and Genomes (KEGG) was used for mRNAs functional analysis. The cell composition of TILs was analyzed by the CIBERSORT algorithm, and Pearson correlation analysis was utilized to explore the correlation between TILs and prognostic factors.

RESULTS

We constructed a ceRNA regulatory network composed of 67 nodes through WGCNA, including 44 DElncRNAs, 19 DEGs, and 4 DEmiRNAs. And based on the expression of 4 DEGs in this network (RRM2, LDLR, TXNIP, and KIF23), a prognostic model of HCC with good specificity and sensitivity was developed. CIBERSORT analyzed the composition of TILs in HCC tumor tissues. Correlation analysis showed that RRM2 is significantly correlated with T cells CD4 memory activated, T cells CD4 memory resting, T cells CD8, and T cells follicular helper, and TXNIP is negatively correlated with B cells memory.

CONCLUSIONS

In this study, a ceRNA with prognostic value in HCC was created, and a prognostic risk model for HCC was constructed based on it. This risk score model is closely related to TILs and is expected to become a potential therapeutic target and a new predictive indicator.

A Novel Five-Gene Signature for Prognosis Prediction in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) has been a global health issue and attracted wide attention due to its high incidence and poor outcomes. In this study, our purpose was to explore an effective prognostic marker for HCC. Five cohort profile datasets from GEO (GSE25097, GSE36376, GSE62232, GSE76427 and GSE101685) were integrated with TCGA-LIHC and GTEx dataset to identify differentially expressed genes (DEGs) between normal and cancer tissues in HCC patients, then 5 upregulated differentially expressed genes and 32 downregulated DEGs were identified as common DEGs in total. Next, we systematically explored the relationship between the expression of 37 common DEGs in tumor tissues and overall survival (OS) rate of HCC patients in TCGA and constructed a novel prognostic model composed of five genes (AURKA, PZP, RACGAP1, ACOT12 and LCAT). Furthermore, the predicted performance of the five-gene signature was verified in ICGC and another independent clinical samples cohort, and the results demonstrated that the signature performed well in predicting the OS rate of patients with HCC. What is more, the signature was an independent hazard factor for HCC patients when considering other clinical factors in the three cohorts. Finally, we found the signature was significantly associated with HCC immune microenvironment. In conclusion, the prognostic five-gene signature identified in our present study could efficiently classify patients with HCC into subgroups with low and high risk of longer overall survival time and help clinicians make decisions for individualized treatment.

Discovery and validation of PZP as a novel serum biomarker for screening lung adenocarcinoma in type 2 diabetes mellitus patients

Background

Patients with type 2 diabetes mellitus (T2DM) have an increased risk of suffering from various malignancies. This study aimed to identify specific biomarkers that can detect lung adenocarcinoma (LAC) in T2DM patients for the early diagnosis of LAC.

Methods

The clinical information of hospitalized T2DM patients diagnosed with various cancers was collected by reviewing medical records in Wuxi People’s Hospital Affiliated to Nanjing Medical University from January 1, 2015, to June 30, 2020. To discover diagnostic biomarkers for early-stage LAC in the T2DM population, 20 samples obtained from 5 healthy controls, 5 T2DM patients, 5 LAC patients and 5 T2DM patients with LAC (T2DM + LAC) were subjected to sequential windowed acquisition of all theoretical fragment ion mass spectrum (SWATH-MS) analysis to identify specific differentially-expressed proteins (DEPs) for LAC in patients with T2DM. Then, these results were validated by parallel reaction monitoring MS (PRM-MS) and ELISA analyses.

Results

Lung cancer was the most common malignant tumor in patients with T2DM, and LAC accounted for the majority of cases. Using SWATH-MS analysis, we found 13 proteins to be unique in T2DM patients with early LAC. Two serum proteins were further validated by PRM-MS analysis, namely, pregnancy-zone protein (PZP) and insulin-like growth factor binding protein 3 (IGFBP3). Furthermore, the diagnostic values of these proteins were validated by ELISA, and PZP was validated as a novel serum biomarker for screening LAC in T2DM patients.

Conclusions

Our findings indicated that PZP could be used as a novel serum biomarker for the identification of LAC in T2DM patients, which will enhance auxiliary diagnosis and assist in the selection of surgical treatment at an early stage.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01861-8.