Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis

Plumbagin has an inhibitory effect on the growth of TSCC PDX model and it enhances the anticancer efficacy of cisplatin

BACKGROUND

Head and neck squamous cell carcinomas are the sixth most common malignant tumors worldwide. Tongue squamous cell carcinoma is a common malignant tumor of this type, and it is associated with poor prognosis, a high rate of recurrence and a low survival rate. Plumbagin is derived from Plumbago zeylanica L, several studies report that plumbagin could inhibit cell, tumor metastasis, induce apoptosis in various cancer cells. Patient-derived xenograft (PDX) model can maintain the heterogeneity and microenvironment of human tumors, is a powerful research tool for developing potentially effective therapies for TSCC.

METHODS

Tumor tissues obtained from TSCC patients were implanted into immunodeficient mice to establish TSCC PDX models. Subsequently, the PDX models were used to evaluate the anti-tumor effects of plumbagin on TSCC. Furthermore, we conducted next-generation sequencing (NGS) and explored the mRNA expression profiles between the treatment and control groups. We selected eight mRNAs related to the characteristics and prognosis of TSCC patients for further analysis.

RESULTS

Plumbagin could inhibit the growth of TSCC PDX models and inhibit expression of Akt/mTOR pathway. In addition, plumbagin was shown to increase drug sensitivity to cisplatin. The eight mRNAs selected for further analysis, AXL, SCG5, VOPP1, DCBLD2 and DRAM1 are cancer-promoting genes, DUSP1, AQP5 and BLNK are cancer suppressor genes. And they were related to the diagnosis, growth, prognosis, and immune cell infiltration in TSCC patients.

CONCLUSION

Plumbagin exhibits an inhibitory effect on the growth of the PDX model of TSCC. Moreover, plumbagin enhances the inhibitory effects of cisplatin.

Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients

Gastric cancer (GC) has been a common tumor type with high mortality. Distal metastasis is one of the main causes of death in GC patients, which is also related to poor prognosis. The mRNA profiles and clinical information of GC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Univariate Cox and LASSO Cox analyses were used to screen the optimal metastasis-related genes (MRGs) to establish a prognostic Risk Score model for GC patients. The nomogram was used to visualize the Risk Score and predict the 1-, 3-, 5-year survival rate. The immune cell infiltration was analyzed by CIBERSORT and the ratio of immune-stromal component was calculated by the ESTIMATE algorithm. A total of 142 differentially expressed genes were identified between metastatic and non-metastatic GC samples. The optimal 8 genes, comprising GAMT (guanidinoacetate N-methyltransferase), ABCB5 (ATP-binding cassette subfamily B member 5), ITIH3 (inter-alpha-trypsin inhibitor heavy chain 3), GDF3 (growth differentiation factor 3), VSTM2L (V-set and transmembrane domain-containing 2 like), CIDEA (cell death inducing DFFA like effector a), NPTX1 (neuronal pentraxin-1), and UMOD (uromodulin), were further screened to establish a prognostic Risk Score, which proved to be an independent prognostic factor. Patients in high-risk group had a poor prognosis. There were significant differences in the proportion of 11 tumor-infiltrating immune cells between high-risk and low-risk subgroups. In addition, the StromalScore, ImmuneScore, and ESTIMATEScore in high-risk group were higher than those in low-risk group, indicating that the tumor microenvironment of the high-risk group was more complex. A Risk Score model based on eight metastasis-related genes could clearly distinguish the prognosis of GC patients. The poor prognosis of patients with high-Risk Score might be associated with the complex tumor microenvironments.

Management of Metastatic Pancreatic Cancer-Comparison of Global Guidelines over the Last 5 Years

Pancreatic cancer (PC) is usually diagnosed at an advanced stage of its development, which results in lower overall survival (OS). Prognosis is also poor even with curative-intent surgery. Approximately 80% of patients with localized PDAC have micrometastases at the time of diagnosis, which leads to a worse prognosis than in other cancers. The objective of this study is to present the progress in the treatment of metastatic pancreatic cancer based on the recommendations of oncological scientific societies, such as ESMO, NCCN, ASCO, NICE and SEOM, over the last 5 years. Combined FOLFIRINOX therapy is mostly a recommended therapy among patients with good performance statuses, while gemcitabine is recommended for more fragile patients as a first-line treatment. The newest guidelines suggest that molecular profiling of the tumor should be the first step in determining the course of treatment. The use of modern molecular therapies in patients with specific gene mutations should extend the survival of patients with this disease.

Molecular and metabolic regulation of immunosuppression in metastatic pancreatic ductal adenocarcinoma

Immunosuppression is a hallmark of pancreatic ductal adenocarcinoma (PDAC), contributing to early metastasis and poor patient survival. Compared to the localized tumors, current standard-of-care therapies have failed to improve the survival of patients with metastatic PDAC, that necessecitates exploration of novel therapeutic approaches. While immunotherapies such as immune checkpoint blockade (ICB) and therapeutic vaccines have emerged as promising treatment modalities in certain cancers, limited responses have been achieved in PDAC. Therefore, specific mechanisms regulating the poor response to immunotherapy must be explored. The immunosuppressive microenvironment driven by oncogenic mutations, tumor secretome, non-coding RNAs, and tumor microbiome persists throughout PDAC progression, allowing neoplastic cells to grow locally and metastasize distantly. The metastatic cells escaping the host immune surveillance are unique in molecular, immunological, and metabolic characteristics. Following chemokine and exosomal guidance, these cells metastasize to the organ-specific pre-metastatic niches (PMNs) constituted by local resident cells, stromal fibroblasts, and suppressive immune cells, such as the metastasis-associated macrophages, neutrophils, and myeloid-derived suppressor cells. The metastatic immune microenvironment differs from primary tumors in stromal and immune cell composition, functionality, and metabolism. Thus far, multiple molecular and metabolic pathways, distinct from primary tumors, have been identified that dampen immune effector functions, confounding the immunotherapy response in metastatic PDAC. This review describes major immunoregulatory pathways that contribute to the metastatic progression and limit immunotherapy outcomes in PDAC. Overall, we highlight the therapeutic vulnerabilities attributable to immunosuppressive factors and discuss whether targeting these molecular and immunological "hot spots" could improve the outcomes of PDAC immunotherapies.

An amino acid metabolism-based seventeen-gene signature correlates with the clinical outcome and immune features in pancreatic cancer

Background: Pancreatic cancer is an aggressive tumor with a low 5-year survival rate and primary resistance to most therapy. Amino acid (AA) metabolism is highly correlated with tumor growth, crucial to the aggressive biological behavior of pancreatic cancer; nevertheless, the comprehensive predictive significance of genes that regulate AA metabolism in pancreatic cancer remains unknown. Methods: The mRNA expression data downloaded from The Cancer Genome Atlas (TCGA) were derived as the training cohort, and the GSE57495 cohort from Gene Expression Omnibus (GEO) database was applied as the validation cohort. Random survival forest (RSF) and the least absolute shrinkage and selection operator (LASSO) regression analysis were employed to screen genes and construct an AA metabolism-related risk signature (AMRS). Kaplan-Meier analysis and receiver operating characteristic (ROC) curve were performed to assess the prognostic value of AMRS. We performed genomic alteration analysis and explored the difference in tumor microenvironment (TME) landscape associated with KRAS and TP53 mutation in both high- and low-AMRS groups. Subsequently, the relationships between AMRS and immunotherapy and chemotherapy sensitivity were evaluated. Results: A 17-gene AA metabolism-related risk model in the TCGA cohort was constructed according to RSF and LASSO. After stratifying patients into high- and low-AMRS groups based on the optimal cut-off value, we found that high-AMRS patients had worse overall survival (OS) in the training cohort (a median OS: 13.1 months vs. 50.1 months, p < 0.0001) and validation cohort (a median OS: 16.2 vs. 30.5 months, p = 1e-04). Genetic mutation analysis revealed that KRAS and TP53 were significantly more mutated in high-AMRS group, and patients with KRAS and TP53 alterations had significantly higher risk scores than those without. Based on the analysis of TME, low-AMRS group displayed significantly higher immune score and more enrichment of T Cell CD8⁺ cells. In addition, high-AMRS-group exhibited higher TMB and significantly lower tumor immune dysfunction and exclusion (TIDE) score and T Cells dysfunction score, which suggested a higher sensitive to immunotherapy. Moreover, high-AMRS group was also more sensitive to paclitaxel, cisplatin, and docetaxel. Conclusion: Overall, we constructed an AA-metabolism prognostic model, which provided a powerful prognostic predictor for the clinical treatment of pancreatic cancer.

Identification of Metastasis-Associated Genes in Cutaneous Squamous Cell Carcinoma Based on Bioinformatics Analysis and Experimental Validation

INTRODUCTION

Cutaneous squamous cell carcinoma (cSCC) is a global malignant tumor with a high degree of malignancy. Once metastasis occurs, it will lead to poor prognosis and even death. This study attempts to find out the central genes closely related to cSCC metastasis, so as to clarify the molecular regulatory mechanism of cSCC metastasis and open up new ideas for clinical treatment.

METHODS

Firstly, cSCC data set GSE98767 was used to establish a tumor metastasis model via clustering analysis. The key module and hub genes associated with cSCC metastasis were analyzed by weighted gene co-expression analysis (WGCNA). Next, the prognostic functions of hub genes were identified by functional and pathway enrichment analysis, pan-cancer analysis, and receiver operating characteristic-area under the curve (ROC-AUC) validation. Finally, the key genes were verified by clinical sample detection and biological in vitro test.

RESULTS

A total of 19 hub genes related to cSCC metastasis were identified. They were highly expressed in cSCC metastatic tissues and were mainly enriched in cellular material and energy metabolism pathways. Overall survival (OS) and disease-free survival (DFS) results from pan-cancer analysis showed that eight and six highly expressed genes, respectively, with PAPSS2 and SCG5 had highly reliable ROC-AUC validation values and were poor prognostic factors. Clinical and biological tests also confirmed the upregulation of PAPSS2 and SCG5 in cSCC. Deletion of PAPSS2 and SCG5 resulted in decreased viability, migration, and invasion of A-431 cells.

CONCLUSION

PAPSS2 and SCG5 may be important factors for cSCC metastasis, and they are involved in the regulation of cSCC cell viability, migration, and invasion.

Molecular Landscape and Prognostic Biomarker Analysis of Advanced Pancreatic Cancer and Predictors of Treatment Efficacy of AG Chemotherapy

Purpose

Although mutational analysis of pancreatic cancer has provided valuable clinical information, it has not significantly changed treatment prospects. The purpose of this study is to further investigate molecular alterations in locally advanced pancreatic cancer and identify predictors of the efficacy of nab-paclitaxel plus gemcitabine (AG) chemotherapy.

Experimental design

Tumor samples from 118 pancreatic cancer patients who received AG chemotherapy as first-line treatment were sequenced and genomic profile was generated. Molecular alterations and the involved signaling pathways were analyzed. Genes with a significant difference in mutation frequency between primary and metastatic tumors were identified, and prognostic-related mutant genes were screened using SPSS version 22.0.

Results

The most common altered genes in the patients were KRAS (94.9%), TP53 (81.4%), CDKN2A (36.4%), and SMAD4 (22.9%). The mutational frequencies of CDKN2B (14.8% vs. 0%, p = 0.001), FAT3 (7.4% vs. 0%, p = 0.041), MTAP (13% vs. 1.6%, p = 0.023), and SMAD4 (31.4% vs. 15.6%, p = 0.049) in metastatic tumors were significantly higher than that in primary tumors. TP35 and KRAS mutations were significantly correlated with objective response rate, while EPHA7, RNF43, and HMGA2 mutations were significantly correlated with disease control rate. Additionally, patients with TGFR2B, FGF23, EPHA7, SMARCA4, CARD11, ADGRA2, CCNE1, and ACVR2A alterations had a worse overall survival. Further, EPHA7, CARD11, NOTCH1, GATA6, ACVR2A, and HMGA2 mutations indicated undesirable progression-free survival.

Conclusions

CDKN2B, FAT3, MTAP, and SMAD4 may be biomarkers that distinguish primary tumors from metastases. EPHA7 mutation may serve as a prognostic biomarker to predict the treatment efficacy of AG chemotherapy in locally advanced pancreatic cancer.

Small extracellular vesicles (exosomes) and their cargo in pancreatic cancer: Key roles in the hallmarks of cancer

Pancreatic cancer (PC) is a devastating disease, offering poor mortality rates for patients. The current challenge being faced is the inability to diagnose patients in a timely manner, where potentially curative resection provides the best chance of survival. Recently, small/nanosized extracellular vesicles (sEVs), including exosomes, have gained significant preclinical and clinical attention due to their emerging roles in cancer progression and diagnosis. Extracellular vesicles (EVs) possess endogenous properties that offer stability and facilitate crossing of biological barriers for delivery of molecular cargo to cells, acting as a form of intercellular communication to regulate function and phenotype of recipient cells. This review provides an overview of the role of EVs, their subtypes and their oncogenic cargo (as characterised by targeted studies as well as agnostic '-omics' analyses) in the pathobiology of pancreatic cancer. The discussion covers the progress of 'omics technology' that has enabled elucidation of the molecular mechanisms that mediate the role of EVs and their cargo in pancreatic cancer progression.

Ultrasound-targeted microbubble destruction-mediated silencing of FBXO11 suppresses development of pancreatic cancer

Ultrasound-targeted microbubble destruction (UTMD) has been a promising noninvasive tool for organ- or tissue-specific gene or drug delivery. This study aimed to explore the function of F-box protein 11 (FBXO11), an E3 ubiquitin ligase, in the development of pancreatic cancer (PCa). Differentially expressed genes in PCa were identified using the GSE62452 and GSE28735 datasets, and FBXO11 was significantly highly expressed in PCa. UTMD-mediated FBXO11 silencing significantly suppressed growth activity, epithelial-mesenchymal transition, migration, and invasion while reduced apoptosis of PCa cells in vitro and reduced the growth and metastasis of xenograft tumors in vivo. Importantly, UTMD-mediated sh-FBXO11 showed more pronounced tumor-suppressive effects than direct administration of sh-FBXO11 alone. The potential substrates of FBXO11 as an E3 ubiquitin ligase were predicted using the Ubibrowser. TP53 was predicted and validated as a downstream substrate of FBXO11. FBXO11 induced ubiquitination and degradation of the tumor suppressor protein TP53 to induce PCa progression. In conclusion, this study suggests that silencing of FBXO11, especially that mediated by UTMD, might suppress the malignant biological behaviors of PCa cells and serve as a potential therapeutic strategy for PCa management.

Prognostic significance of AP-2α/γ targets as cancer therapeutics

Identifying genes with prognostic importance could improve cancer treatment. An increasing number of reports suggest the existence of successful strategies based on seemingly "untargetable" transcription factors. In addition to embryogenesis, AP-2 transcription factors are known to play crucial roles in cancer development. Members of this family can be used as prognostic factors in oncological patients, and AP-2α/γ transcription factors were previously investigated in our pan-cancer comparative study using their target genes. The present study investigates tumors that were previously found similar with an emphasis on the possible role of AP-2 factors in specific cancer types. The RData workspace was loaded back to R environment and 3D trajectories were built via Monocle3. The genes that met the requirement of specificity were listed using top_markers(), separately for mutual and unique targets. Furthermore, the candidate genes had to meet the following requirements: correlation with AP-2 factor (through Correlation AnalyzeR) and validated prognostic importance (using GEPIA2 and subsequently KM-plotter or LOGpc). Eventually, the ROC analysis was applied to confirm their predictive value; co-dependence of expression was visualized via BoxPlotR. Some similar tumors were differentiated by AP-2α/γ targets with prognostic value. Requirements were met by only fifteen genes (EMX2, COL7A1, GRIA1, KRT1, KRT14, SLC12A5, SEZ6L, PTPRN, SCG5, DPP6, NTSR1, ARX, COL4A3, PPEF1 and TMEM59L); of these, the last four were excluded based on ROC curves. All the above genes were confronted with the literature, with an emphasis on the possible role played by AP-2 factors in specific cancers. Following ROC analysis, the genes were verified using immunohistochemistry data and progression-related signatures. Staining differences were observed, as well as co-dependence on the expression of e.g. CTNNB1, ERBB2, KRAS, SMAD4, EGFR or MKI67. In conclusion, prognostic value of targets suggested AP-2α/γ as candidates for novel cancer treatment. It was also revealed that AP-2 targets are related to tumor progression and that some mutual target genes could be inversely regulated.

Exploring Immune-Related Prognostic Signatures in the Tumor Microenvironment of Colon Cancer

Background: Colon cancer is a common malignant tumor with poor prognosis. The aim of this study is to explore the immune-related prognostic signatures and the tumor immune microenvironment of colon cancer.

Methods: The mRNA expression data of TCGA-COAD from the UCSC Xena platform and the list of immune-related genes (IRGs) from the ImmPort database were used to identify immune-related differentially expressed genes (DEGs). Then, we constructed an immune-related risk score prognostic model and validated its predictive performance in the test dataset, the whole dataset, and two independent GEO datasets. In addition, we explored the differences in tumor-infiltrating immune cell types, tumor mutation burden (TMB), microsatellite status, and expression levels of immune checkpoints and their ligands between the high-risk and low-risk score groups. Moreover, the potential value of the identified immune-related signature with respect to immunotherapy was investigated based on an immunotherapeutic cohort (Imvigor210) treated with an anti-PD-L1 agent.

Results: Seven immune-related DEGs were identified as prognostic signatures. The areas under the curves (AUCs) of the constructed risk score model for overall survival (OS) were calculated (training dataset: 0.780 at 3 years, 0.801 at 4 years, and 0.766 at 5 years; test dataset: 0.642 at 3 years, 0.647 at 4 years, and 0.629 at 5 years; and the whole dataset: 0.642 at 3 years, 0.647 at 4 years, and 0.629 at 5 years). In the high-risk score group of the whole dataset, patients had worse OS, higher TMN stages, advanced pathological stages, and a higher TP53 mutation rate (p < 0.05). In addition, a high level of resting NK cells or M0 macrophages, and high TMB were significantly related to poor OS (p < 0.05). Also, we observed that high-risk score patients had a high expression level of PD-L1, PD-1, and CTLA-4 (p < 0.05). The patients with high-risk scores demonstrated worse prognosis than those with low-risk scores in multiple datasets (GSE39582: p = 0.0023; GSE17536: p = 0.0008; immunotherapeutic cohort without platinum treatment: p = 0.0014; immunotherapeutic cohort with platinum treatment: p = 0.0027).

Conclusion: We developed a robust immune-related prognostic signature that performed great in multiple cohorts and explored the characteristics of the tumor immune microenvironment of colon cancer patients, which may give suggestions for the prognosis and immunotherapy in the future.

The prognostic and clinical significance of IFI44L aberrant downregulation in patients with oral squamous cell carcinoma

Background

It is a basic task in high-throughput gene expression profiling studies to identify differentially expressed genes (DEGs) between two phenotypes. RankComp, an algorithm, could analyze the highly stable within-sample relative expression orderings (REOs) of gene pairs in a particular type of human normal tissue that are widely reversed in the cancer condition, thereby detecting DEGs for individual disease samples measured by a particular platform.

Methods

In the present study, Gene Expression Omnibus (GEO) Series (GSE) GSE75540, GSE138206 were downloaded from GEO, by analyzing DEGs in oral squamous cell carcinoma based on online datasets using the RankComp algorithm, using the Kaplan-Meier survival analysis and Cox regression analysis to survival analysis, Gene Set Enrichment Analysis (GSEA) to explore the potential molecular mechanisms underlying.

Results

We identified 6 reverse gene pairs with stable REOs. All the 12 genes in these 6 reverse gene pairs have been reported to be associated with cancers. Notably, lower Interferon Induced Protein 44 Like (IFI44L) expression was associated with poorer overall survival (OS) and Disease-free survival (DFS) in oral squamous cell carcinoma patients, and IFI44L expression showed satisfactory predictive efficiency by receiver operating characteristic (ROC) curve. Moreover, low IFI44L expression was identified as risk factors for oral squamous cell carcinoma patients’ OS. IFI44L downregulation would lead to the activation of the FRS-mediated FGFR1, FGFR3, and downstream signaling pathways, and might play a role in the PI3K-FGFR cascades.

Conclusions

Collectively, we identified 6 reverse gene pairs with stable REOs in oral squamous cell carcinoma, which might serve as gene signatures playing a role in the diagnosis in oral squamous cell carcinoma. Moreover, high expression of IFI44L, one of the DEGs in the 6 reverse gene pairs, might be associated with favorable prognosis in oral squamous cell carcinoma patients and serve as a tumor suppressor by acting on the FRS-mediated FGFR signaling.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09058-y.

Exosomal circular RNAs: A new frontier in the metastasis of digestive system tumors

Exosomes are membrane vesicles with a diameter of 30–150 nm. Exosomes are secreted by various types of tumor cell and contain a variety of proteins, circular RNAs (circRNAs), microRNAs and DNA, depending on the host cells. Among them, circRNAs, which are long non-coding endogenous RNAs, form covalently closed and continuous loops that link the 3′ and 5′ terminals generated by back-splicing. circRNAs have become a hotspot of research. Exosomal circRNAs are in volved in the pathogenesis of cancer, especially metastasis, which is mainly ascribed to the frequently abnormal expression levels within neoplasms. Nonetheless, the functions and regulatory mechanisms of exosomal circRNAs in the progression of digestive system tumors (DSTs) remain unclear. More knowledge on the regulation and network interactions of exosomal circRNAs will help identify superior treatment strategies for the metastasis of DSTs. The present review aims to summarize the existing studies on the functions and mechanisms of exosomal circRNAs in tumorigenesis, and evaluate the associations between the dysregulation of exosomal circRNAs and tumor metastasis.

Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics

Pancreatic cancer (PC) is a highly lethal malignancy with a 5-year survival rate of 10%. The occurrence of metastasis, among other hallmarks, is the main contributor to its poor prognosis. Consequently, the elucidation of metastatic genes involved in the aggressive nature of the disease and its poor prognosis will result in the development of new treatment modalities for improved management of PC. There is a deep interest in understanding underlying disease pathology, identifying key prognostic genes, and genes associated with metastasis. Computational approaches, which have become increasingly relevant over the last decade, are commonly used to explore such interests. This review aims to address global studies that have employed global approaches to identify prognostic and metastatic genes, while highlighting their methods and limitations. A panel of 48 prognostic genes were identified across these studies, but only five, including ANLN, ARNTL2, PLAU, TOP2A, and VCAN, were validated in multiple studies and associated with metastasis. Their association with metastasis has been further explored here, and the implications of these genes in the metastatic cascade have been interpreted.

A Novel Immune-Related Prognostic Signature in Head and Neck Squamous Cell Carcinoma

The immune response within the tumor microenvironment plays a key role in tumorigenesis and determines the clinical outcomes of head and neck squamous cell carcinoma (HNSCC). However, to date, very limited robust and reliable immunological biomarkers have been developed that are capable of estimating prognosis in HNSCC patients. In this study, we aimed to identify the effects of novel immune-related gene signatures (IRGs) that can predict HNSCC prognosis. Based on gene expression profiles and clinical data of HNSCC patient cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, a total of 439 highly variable expressed immune-related genes (including 239 upregulated and 200 downregulated genes) were identified by using differential gene expression analysis. Pathway enrichment analysis indicated that these immune-related differentially expressed genes were enriched in inflammatory functions. After process screening in the training TCGA cohort, six immune-related genes (PLAU, STC2, TNFRSF4, PDGFA, DKK1, and CHGB) were significantly associated with overall survival (OS) based on the LASSO Cox regression model. Integrating these genes with clinicopathological features, a multivariable model was built and suggested better performance in determining patients’ OS in the testing cohort, and the independent validation cohort. In conclusion, a well-established model encompassing both immune-related gene signatures and clinicopathological factors would serve as a promising tool for the prognostic prediction of HNSCC.

The Burden of Post-Translational Modification (PTM)-Disrupting Mutations in the Tumor Matrisome

BACKGROUND

To evaluate the occurrence of mutations affecting post-translational modification (PTM) sites in matrisome genes across different tumor types, in light of their genomic and functional contexts and in comparison with the rest of the genome.

METHODS

This study spans 9075 tumor samples and 32 tumor types from The Cancer Genome Atlas (TCGA) Pan-Cancer cohort and identifies 151,088 non-silent mutations in the coding regions of the matrisome, of which 1811 affecting known sites of hydroxylation, phosphorylation, N- and O-glycosylation, acetylation, ubiquitylation, sumoylation and methylation PTM.

RESULTS

PTM-disruptive mutations (PTMmut) in the matrisome are less frequent than in the rest of the genome, seem independent of cell-of-origin patterns but show dependence on the nature of the matrisome protein affected and the background PTM types it generally harbors. Also, matrisome PTMmut are often found among structural and functional protein regions and in proteins involved in homo- and heterotypic interactions, suggesting potential disruption of matrisome functions.

CONCLUSIONS

Though quantitatively minoritarian in the spectrum of matrisome mutations, PTMmut show distinctive features and damaging potential which might concur to deregulated structural, functional, and signaling networks in the tumor microenvironment.

Identification and Analysis of Potential Key Genes Associated With Hepatocellular Carcinoma Based on Integrated Bioinformatics Methods

BACKGROUND

Hepatocellular carcinoma (HCC) is a type of primary liver tumor with poor prognosis and high mortality, and its molecular mechanism remains incompletely understood. This study aimed to use bioinformatics technology to identify differentially expressed genes (DEGs) in HCC pathogenesis, hoping to identify novel biomarkers or potential therapeutic targets for HCC research.

METHODS

The bioinformatics analysis of our research mostly involved the following two datasets: Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). First, we screened DEGs based on the R packages (limma and edgeR). Using the DAVID database, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were carried out. Next, the protein-protein interaction (PPI) network of the DEGs was built in the STRING database. Then, hub genes were screened through the cytoHubba plug-in, followed by verification using the GEPIA and Oncomine databases. We demonstrated differences in levels of the protein in hub genes using the Human Protein Atlas (HPA) database. Finally, the hub genes prognostic values were analyzed by the GEPIA database. Additionally, using the Comparative Toxicogenomics Database (CTD), we constructed the drug-gene interaction network.

RESULTS

We ended up with 763 DEGs, including 247 upregulated and 516 downregulated DEGs, that were mainly enriched in the epoxygenase P450 pathway, oxidation-reduction process, and metabolism-related pathways. Through the constructed PPI network, it can be concluded that the P53 signaling pathway and the cell cycle are the most obvious in module analysis. From the PPI, we filtered out eight hub genes, and these genes were significantly upregulated in HCC samples, findings consistent with the expression validation results. Additionally, survival analysis showed that high level gene expression of CDC20, CDK1, MAD2L1, BUB1, BUB1B, CCNB1, and CCNA2 were connected with the poor overall survival of HCC patients. Toxicogenomics analysis showed that only topotecan, oxaliplatin, and azathioprine could reduce the gene expression levels of all seven hub genes.

CONCLUSION

The present study screened out the key genes and pathways that were related to HCC pathogenesis, which could provide new insight for the future molecularly targeted therapy and prognosis evaluation of HCC.