Identification of candidate diagnostic and prognostic biomarkers for pancreatic carcinoma

Effects of transmembrane serine protease 4 on the survival in patients with pancreatic ductal adenocarcinoma undergoing surgery followed by adjuvant chemotherapy

PURPOSE

The transmembrane serine protease 4 (TMPRSS4) gene is upregulated in various human cancers. However, its biological functions in pancreatic ductal adenocarcinoma remain unclear. We examined the expression of TMPRSS4 in pancreatic ductal adenocarcinoma tissues and its correlation with clinicopathological parameters in patients with pancreatic ductal adenocarcinoma who underwent surgery.

METHODS

The TMPRSS4 expression was immunohistochemically examined in 81 PDAC patients with pancreatic ductal adenocarcinoma. We analyzed the association between the TMPRSS4 expression and clinicopathological factors, the recurrence-free survival (RFS), and the overall survival (OS) and examined the effect of TMPRSS4 expression on cell migration and sensitivity to 5-fluorouracil.

RESULTS

The expression rate of TMPRSS4 in the samples was 62.9% (51/81). The TMPRSS4 expression was not correlated with any clinicopathological feature. The five-year overall and recurrence-free survival rates were significantly lower in the TMPRSS4-positive group than in the TMPRSS4-negative group. On a multivariate analysis, TMPRSS4 positivity, poorly differentiated histology, and non-adjuvant chemotherapy predicted a poor OS, while TMPRSS4 positivity and poorly differentiated histology predicted a poor RFS. TMPRSS4-silenced pancreatic ductal adenocarcinoma cells showed higher sensitivity to 5- fluorouracil than did the control siRNA-transfected cells.

CONCLUSIONS

TMPRSS4 can be considered a prognostic factor and therapeutic target for pancreatic ductal adenocarcinoma.

Analysis of the role of CHPF in colorectal cancer tumorigenesis and immunotherapy based on bioinformatics and experiments

BACKGROUND

Chondroitin polymerizing factor (CHPF) has been found to be involved in the development of numerous cancers and correlated with poor prognosis. However, its role in the tumorigenesis and development of colorectal cancer (CRC) remains unknown.

METHODS

In our research, we explored CHPF expression and clinicopathological characteristics using The Cancer Genome Atlas Program (TCGA), UALCAN, GSE9348, TIMER2.0 and The Human Protein Atlas (HPA) database, in addition, we validated CHPF expression in CRC cell lines by Real-Time Quantitative PCR (qRT-PCR) and Western blot (WB). KM-Plotter, PrognoScan and TCGA were also utilized to verify its prognosis value in CRC. Small-interfer RNA (Si-RNA) was used to perform Cell Counting Kit-8 (CCK8), colony formation, 5-ethynyl-2'-deoxyuridine (EDU), transwell and wound healing assays to testify its function on the tumor progression. Based on TCGA database, we probed potential biological mechanism by which CHPF play its role via clusterProfiler package and GEPIA database and we validated their correlation by WB assay. Moreover, we explored its potential association with the tumor microenvironment (TME), immune infiltrated cells, immune checkpoints, tumor mutation burden (TMB) as well as microsatellite instability (MSI), and investigated immunotherapy sensitivity via Tumor Immune Dysfunction and Exclusion (TIDE) algorithm as well as potentially effective therapeutic drugs via pRRophetic algorithm.

RESULTS

CHPF was identified upregulated in CRC tissues and cells, correlated with poor prognosis, and nodal metastasis status, stage and histological subtype. Down-regulation of CHPF inhibited CRC cell proliferation, migration and its expression correlated with wnt pathway key molecules. In addition, high expression of CHPF was positively correlated with TME scores, Regulatory T cells (Tregs) cell infiltration degree, Programmed death-1 (PD-1), MSI-high (MSI-H), and TIDE scores, however, not with TMB. Targeted drug analysis showed that patients with high CHPF expression were more sensitive to telatinib, recaparib, serdemetan, and trametinib.

CONCLUSION

CHPF could promote the proliferation and migration of CRC cells and lead to poor prognosis, possibly through wnt pathways as well as changes in TME. Patients with high expression of CHPF had poor efficacy in immunotherapy, which might be related to Tregs cell infiltration. Above all, it might offer more reliable guidance for future immunotherapy.

Characterization of a ferroptosis-related gene signature predicting survival and immunotherapeutic response in lung adenocarcinoma

Lung cancer remains the leading cause of cancer-related death worldwide, and drug resistance represents the main obstacle responsible for the poor mortality and prognosis. Here, to identify a novel gene signature for predicting survival and drug response, we jointly investigated RNA sequencing data of lung adenocarcinoma patients from TCGA and GEO databases, and identified a ferroptosis-related gene signature. The signature was validated in the validation set and two external cohorts. The high-risk group had a reduced survival than the low-risk group (P < 0.05). Moreover, the established gene signature was associated with tumor mutation burden, microsatellite instability, and response to immune checkpoint blockade. In addition, four candidate oncogenes (RRM2, SLC2A1, DDIT4, and VDAC2) were identified to be candidate oncogenes using in silico and wet experiments, which could serve as potential therapeutic targets. Collectively, this study developed a novel ferroptosis-related gene signature for predicting prognosis and drug response, and identified four candidate oncogenes for lung adenocarcinoma.

Sciellin promotes the development and progression of thyroid cancer through the JAK2/STAT3 signaling pathway

Thyroid cancer (TC) is one of the most common endocrine tumors worldwide. Sciellin (SCEL) is involved in various disease processes, including burn wound healing and neutrophil extracellular traps (NETs); it is highly expressed in TC. However, its biological impact on TC and related mechanisms remain unclear. This study aimed to investigate the effect of SCEL on the function of human TC cell lines B-CPAP and OCUT-2C (cancer cell lines with BRAF V600E mutations). Analyses of data sets and clinical samples revealed enhanced expression of SCEL in TC than in adjacent normal tissue. SCEL knockout suppresses proliferation and cell cycle progression in TC cells, and these results were reversed by the upregulated SCEL expression in TC. SCEL knockout inhibited tumor development in xenograft mouse models. Western blot (WB) demonstrated that the expression of p-JAK2 and p-STAT3 was reduced in SCEL-knockdown TC. These results suggest that SCEL plays a key role in TC progression through the JAK2-STAT3 pathway. Therefore, SCEL can be considered a potential diagnostic biomarker and therapeutic target for TC.

Identification of allograft inflammatory factor-1 suppressing the progression and indicating good prognosis of osteosarcoma

BACKGROUND

Osteosarcoma is one of the most common cancers worldwide. Intense efforts have been made to elucidate the pathogeny, but the mechanisms of osteosarcoma are still not well understood. We aimed to investigate the potential biomarker, allograft inflammatory factor-1 (AIF1), affecting the progression and prognosis of osteosarcoma.

METHODS

Three microarray datasets were downloaded from GEO datasets and one was obtained from the TCGA dataset. The differentially expressed genes (DEGs) were identified. GO and KEGG functional enrichment analyses of overlapped DEGs were performed. The PPI network of overlapped DEGs was constructed by STRING and visualized with Cytoscape. Overall survival (OS) and Metastasis free survival (MFS) were analyzed from GSE21257. Finally, the effect of the most relevant core gene affecting the progression of osteosarcoma was examined in vitro.

RESULTS

One hundred twenty six DEGs were identified, consisting of 65 upregulated and 61 downregulated genes. Only AIF1 was significantly associated with OS and MFS. It was found that AIF1 could be enriched into the NF-κB signaling pathway. GSEA and ssGSEA analyses showed that AIF1 was associated with the immune invasion of tumors. Cell experiments showed that AIF1 was underexpressed in osteosarcoma cell lines, while the malignant propriety was attenuated after overexpressing the expression of AIF1. Moreover, AIF1 also affects the expression of the NF-κB pathway.

CONCLUSION

In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the carcinogenesis and progression of osteosarcoma, and provide candidate targets for diagnosis and treatment of osteosarcoma.

Preoperative plasma fibrinogen and C-reactive protein/albumin ratio as prognostic biomarkers for pancreatic carcinoma

Objective

Pancreatic carcinoma is characterised by high aggressiveness and a bleak prognosis; optimising related treatment decisions depends on the availability of reliable prognostic markers. This study was designed to compare various blood biomarkers, such as neutrophil/lymphocyte ratio (NLR), lymphocyte/monocyte ratio (LMR), platelet/lymphocyte ratio (PLR), C-reactive protein (CRP), albumin (Alb), plasma fibrinogen (PF), and CRP/Alb in patients with pancreatic carcinoma.

Methods

Our study retrospectively reviewed 250 patients with pancreatic carcinoma diagnosed between July 2007 and December 2018. The Cutoff Finder application was used to calculate the optimal values of CRP/Alb and PF. The Chi-square test or Fisher's exact test was used to analyse the correlation of CRP/Alb and PF with other clinicopathological factors. Conducting univariate and multivariate analyses allowed further survival analysis of these prognostic factors.

Results

Multivariate analysis revealed that, in a cohort of 232 patients with pancreatic ductal adenocarcinoma (PDAC), the PF level exhibited statistical significance for overall survival (hazard ratio (HR) = 0.464; p = 0.023); however, this correlation was not found in the entire group of 250 patients with pancreatic carcinoma. Contrastingly, the CRP/Alb ratio was demonstrated statistical significance in both the entire pancreatic carcinoma cohort (HR = 0.471; p = 0.026) and the PDAC subgroup (HR = 0.484; p = 0.034). CRP/Alb and PF demonstrated a positive association (r=0.489, p<0.001) as indicated by Spearman's rank correlation analysis. Additionally, in 232 PDAC patients, the combination of the CRP/Alb ratio and PF had synergistic effects on prognosis when compared with either the CRP/Alb ratio or the PF concentration alone.

Conclusion

PF concentration is a convenient, rapid, and noninvasive biomarker, and its combination with the CRP/Alb ratio could significantly enhance the accuracy of prognosis prediction in pancreatic carcinoma patients, especially those with the most common histological subtype of PDAC.

EPYC functions as a novel prognostic biomarker for pancreatic cancer

Pancreatic cancer (PC) has become a worldwide challenge attributed to its difficult early diagnosis and rapid progression. Treatments continue to be limited besides surgical resection. Hence, we aimed to discover novel biological signatures as clinically effective therapeutic targets for PC via the mining of public tumor databases. We found that epiphycan (EPYC) could function as an independent risk factor to predict the poor prognosis in PC based on integrated bioinformatics analysis. We downloaded associated PC data profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) online websites, then applied the software Rstudio to filter out genes under the strict criteria. After the batch survival analysis using Log-rank test and univariate cox regression, we obtained 39 candidate genes. Subsequently, we narrowed the scope to 8 genes by establishing a Lasso regression model. Eventually, we focused on 2 genes (EPYC and MET) by further building a multivariate cox regression model. Given that the role of EPYC in PC remains obscure, we then performed a series of molecular functional experiments, including RT-qPCR, CCK8, EdU, colony formation, Transwell, western blot, cell live-dead staining, subcutaneous tumor formation, to enhance our insight into its underlying molecular mechanisms. The above results demonstrated that EPYC was highly expressed in PC cell lines and could promote the proliferation of PCs via PI3K-AKT signaling pathway in vivo and in vitro. We arrived at a conclusion that EPYC was expected to be a biological neo-biomarker for PC followed by being a potential therapeutic target.

CENPF Upregulation is Associated with Immunosuppressive Status and Poor Clinical Outcomes in Lung Adenocarcinoma Validated by qRT-PCR

OBJECTIVE

CENPF-differentially expressed in various types of cancers-is a marker of poor prognosis. However, studies on the impact of CENPF on patient prognosis in lung adenocarcinoma regarding immune infiltration are lacking.

METHODS

CENPF expression profiles were analyzed in the GEO and TCGA databases. qRT-PCR was used to verify CENPF mRNA expression in lung adenocarcinoma cell lines. The prognostic value of CENPF was evaluated by combining data from clinical samples in the GEPIA2 and TCGA databases. Metascape and WebGestalt were used for enrichment analysis of gene sets most positively associated with CENPF. Immune cell infiltration score data were retrieved from TCGA and the correlation between CENPF expression and immune cell infiltration was analyzed.

RESULTS

CENPF expression was elevated in 29 types of cancer. CENPF was highly expressed and increased with tumor grade in lung adenocarcinoma. Immunohistochemical and qRT-PCR analyses revealed that CENPF expression was upregulated in lung adenocarcinoma tissues and cells. High expression of CENPF significantly worsened prognoses in patients with multiple malignancies, including lung adenocarcinoma. Results from gene set enrichment analysis indicated significant enrichment of the progesterone-mediated oocyte maturation pathway. Immune infiltration analysis revealed that CD4+ Th2 cell infiltration was significantly higher in the high CENPF expression group.

CONCLUSION

Upregulation of CENPF expression was related to poor progression-free survival, disease- free survival, and overall survival in patients with lung adenocarcinoma. High expression of CENPF was markedly related to genes associated with the immune checkpoint. Lung adenocarcinoma samples with high CENPF expression had increased CD4+ Th2 cell infiltration. Our findings indicate that CENPF promotes CD4+ Th2 cell infiltration through oncogenic activity and may be used as a biomarker for predicting patient outcomes in lung adenocarcinoma.

CBX8 promotes lung adenocarcinoma growth and metastasis through transcriptional repression of CDKN2C and SCEL

Dysregulation of polycomb group (PcG) proteins that mediate epigenetic gene silencing contributes to tumorigenesis. As core components of the polycomb repressive complex 1 (PRC1), chromobox (CBX) proteins recognize H3K27me3 to recruit PRC1 to maintain a repressive transcriptional state. However, the individual biological functions of these CBX proteins in tumorigenesis warrant in-depth investigation. In this study, we analyzed the mRNA expression of CBX family genes across multiple cancers using The Cancer Genome Atlas data and found different expression patterns of the five CBX genes in different types of cancer. This analyses together with the result of immunohistochemistry indicated that CBX8 expression was significantly higher in lung adenocarcinoma (LUAD) tissues compared to adjacent nontumor tissues. Overexpression approaches demonstrated that CBX8 facilitated LUAD cell proliferation and migration in vitro. Consistently, CBX8 knockdown reduced LUAD cell proliferation and migration in both cell culture and mouse models. RNA sequencing combined with real-time RT-PCR assays revealed CDKN2C and SCEL as target genes of CBX8. Furthermore, chromatin immunoprecipitation assays indicated that CBX8 directly bound to the promoters of CDKN2C and SCEL to establish H2AK119ub. CBX8 depletion reduced the enrichment of H2AK119ub on CDKN2C and SCEL promoters. Moreover, depletion of CDKN2C and SCEL restored the repressed growth and invasion ability of LUAD cells caused by CBX8 knockdown. These findings demonstrate that CBX8 promotes LUAD growth and metastasis through the transcriptional repression of CDKN2C and SCEL. Our study uncovers the oncogenic role of CBX8 in LUAD progression and provides a new target for the diagnosis and therapy of LUAD.

Development and Validation of a Novel Prognosis Model Based on a Panel of Three Immunogenic Cell Death-Related Genes for Non-Cirrhotic Hepatocellular Carcinoma

Purpose

The accurate prediction of non-cirrhotic hepatocellular carcinoma (NCHCC) risk facilitates improved surveillance strategy and decreases cancer-related mortality. This study aimed to explore the correlation between immunogenic cell death (ICD) and NCHCC prognosis using The Cancer Genome Atlas (TCGA) datasets, and the potential prognostic value of ICD-related genes in NCHCC.

Methods

Clinical and transcriptomic data of patients with NCHCC patients were retrieved from TCGA database. Weighted gene co-expression network analysis was performed to obtain the NCHCC phenotype-related module genes. Consensus clustering analysis was performed to classify the patients into two clusters based on intersection genes among differentially expressed genes (DEGs) between cancer and adjacent tissues, NCHCC phenotype-related genes, and ICD-related genes. NCHCC-derived tissue microarray was used to evaluate the correlation of the expression levels of key genes with NCHCC prognosis using immunohistochemical staining.

Results

Cox regression analyses were performed to construct a prognostic risk score model comprising three genes (TMC7, GRAMD1C, and GNPDA1) based on DEGs between two clusters. The model stratified patients with NCHCC into two risk groups. The overall survival (OS) of the high-risk group was significantly lower than that of the low-risk group. Univariable and multivariable Cox regression analyses revealed that these signature genes are independent predictors of OS. Functional analysis revealed differential immune status between the two risk groups. Next, a nomogram was constructed, which demonstrated the potent distinguishing ability of the developed model based on receiver operating characteristic curves. In vitro functional validation revealed that the migration and invasion abilities of HepG2 and Huh7 cells were upregulated upon GRAMD1C knockdown but downregulated upon TMC7 knockdown.

Conclusion

This study developed a prognostic model comprising three genes, which can aid in predicting the survival of patients with NCHCC and guide the selection of drugs and molecular markers for NCHCC.

Non-synonymous SNPs variants of PRKCG and its association with oncogenes predispose to hepatocellular carcinoma

BACKGROUND

PRKCG encodes PKC γ, which is categorized under the classical protein kinase C family. No studies have specifically established the relationship between PRKCG nsSNPs with structural and functional variations in PKC γ in the context of hepatocellular carcinoma (HCC). The present study aims to uncover this link through in-silico and experimental studies.

METHODS

The 3D structure of PKC γ was predicted. Molecular Dynamic (MD) Simulations were run and estimates were made for interactions, stability, conservation and post-translational alterations between wild and mutant structures. The association of PRKCG levels with HCC survival rate was determined. Genotyping analyses were conducted to investigate the deleterious PRKCG nsSNP association with HCC. mRNA expression of PKC γ, HIF-1 alpha, AKT, SOCS3 and VEGF in the blood of controls and HCC patients was analyzed and a genetic cascade was constructed depicting these interactions.

RESULTS

The expression level of studied oncogenes was compared to tumour suppressor genes. Through Alphafold, the 3D structure of PKC γ was explored. Fifteen SNPs were narrowed down for in-silico analyses that were identified in exons 5, 10 and 18 and the regulatory and kinase domain of PKC γ. Root mean square deviation and fluctuation along with the radius of gyration unveiled potential changes between the wild and mutated variant structures. Mutant genotype AA (homozygous) corresponding to nsSNP, rs386134171 had more frequency in patients with OR (2.446), RR (1.564) and P-values (< 0.0029) that highlights its significant association with HCC compared to controls in which the wild genotype GG was found more prevalent.

CONCLUSION

nsSNP rs386134171 can be a genetic marker for HCC diagnosis and therapeutic studies. This study has laid down a road map for future studies to be conducted on HCC.

MFAP2 enhances cisplatin resistance in gastric cancer cells by regulating autophagy

Background

Cisplatin (CDDP) is of importance in cancer treatment and widely used in advanced gastric cancer (GC). However, its clinical usage is limited due to its resistance, and the regulatory mechanism of CDDP resistance in GC has not yet been fully elucidated. In this study, we first conducted a comprehensive study to investigate the role of MFAP2 through bioinformatics analysis.

Methods

The Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were applied to downloadgene expression data and clinicopathologic data, and the differentially expressed genes (DEGs) were further analyzed. Then, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and survival analysis were conducted. Furthermore, according to the clinicopathological characteristics of TCGA, clinical correlation analysis was conducted, and a receiver operating characteristic curve (ROC) was plotted.

Results

We revealed that FAP, INHBA and MFAP2 were good diagnostic factors of GC. However, the mechanism of MFAP2 in GC remains elusive, especially in the aspect of chemotherapy resistance. We developed the CDDP-resistant cell line, and found that MFAP2 was upregulated in CDDP-resistant cells, and MFAP2-knockdown improved CDDP sensitivity. Finally, we found that MFAP2 enhanced CDDP resistance by inducing autophagy in drug-resistant cell lines.

Conclusions

The above results suggested that MFAP2 could affect the chemotherapy resistance by altering the level of autophagy in GC patients as a potential therapeutic target.

Integrative analysis developing and validating potential candidate biomarkers for cancer stemness features of pan-renal cell carcinoma

In our study, 49 key genes significantly associated with renal cell carcinoma (RCC) stemness were obtained. Next, we developed a molecular prognostic signature associated with stemness features of pan-RCC. The difference in OS between high-risk and low-risk group was statistically significant (P < 0.05). The area under ROC curve for 1-years OS, 5-years OS and 10-years OS was 0.759, 0.712 and 0.918, respectively. The results of validation in TCGA cohort and ICGC cohort revealed the predictive capability of this signature. Further, we selected three genes and further validation showed that these three hub genes were potential hub biomarkers for pan-RCC stemness features.

Deciphering the Prognostic and Therapeutic Significance of Cell Cycle Regulator CENPF: A Potential Biomarker of Prognosis and Immune Microenvironment for Patients with Liposarcoma

Liposarcoma (LPS) is one of the most common subtypes of sarcoma with a high recurrence rate. CENPF is a regulator of cell cycle, differential expression of which has been shown to be related with various cancers. However, the prognostic value of CENPF in LPS has not been deciphered yet. Using data from TCGA and GEO datasets, the expression difference of CENPF and its effects on the prognosis or immune infiltration of LPS patients were analyzed. As results show, CENPF was significantly upregulated in LPS compared to normal tissues. Survival curves illustrated that high CENPF expression was significantly associated with adverse prognosis. Univariate and multivariate analysis suggested that CENPF expression could be an independent risk factor for LPS. CENPF was closely related to chromosome segregation, microtubule binding and cell cycle. Immune infiltration analysis elucidated a negative correlation between CENPF expression and immune score. In conclusion, CENPF not only could be considered as a potential prognostic biomarker but also a potential malignant indicator of immune infiltration-related survival for LPS. The elevated expression of CENPF reveals an unfavorable prognostic outcome and worse immune score. Thus, therapeutically targeting CENPF combined with immunotherapy might be an attractive strategy for the treatment of LPS.

Clinical significance and diagnostic value of QPCT, SCEL and TNFRSF12A in papillary thyroid cancer

PURPOSE

To identify specific novel genes that could be used as diagnostic and prognostic factors in papillary thyroid carcinoma (PTC).

METHODS

Screening of differential genes by RNA sequencing (RNA-Seq) in normal thyroid, Hashimoto's thyroiditis, PTC combined with Hashimoto's thyroiditis and PTC tissues. The genes QPCT, SCEL and TNFRSF12A were selected by qRT-PCR and immunohistochemical pre-experiments. The GEPIA2 database, qRT-PCR, and immunohistochemical studies were used to confirm the target genes QPCT, SCEL, and TNFRSF12A. ROC curves were used to assess the diagnostic usefulness of these 3 genes for PTC in more detail.

RESULTS

Functional enrichment analysis showed that QPCT, SCEL and TNFRSF12A were enriched in the pathways for peptidyl-pyroglutamic acid biosynthesis, keratinocyte differentiation, WNT signaling, apoptosis. GEPIA2 database analysis revealed that QPCT, SCEL and TNFRSF12A were high in thyroid cancer, and TC patients with lower TNFRSF12A levels had short survival. QPCT, SCEL and TNFRSF12A were elevated in PTC and thyroid adenoma. The mRNA diagnostic values were as follows: for QPCT, AUROC = 0.891, 95% CI, 0.835-0.947; for SCEL, AUROC = 0.921, 95% CI, 0.869-0.974; for TNFRSF12A, AUROC = 0.884, 95% CI, 0.809-0.958. Immunohistochemical results showed that QPCT, SCEL, and TNFRSF12A differed to varying degrees between subgroups of thyroid tissue. SCEL was associated with BRAF V600E mutation status and stratification of recurrence risk, while TNFRSF12A was associated with Cyclin D1. The protein diagnostic values were as follows: for QPCT, AUROC = 0.752, 95% CI, 0.685-0.819; for SCEL, AUROC = 0.715, 95% CI, 0.645-0.784; for TNFRSF12A, AUROC = 0.660, 95% CI, 0.587-0.734.

CONCLUSION

QPCT, SCEL and TNFRSF12A are expected to be diagnostic markers for PTC.

Identification of EMT-related alternative splicing event of TMC7 to promote invasion and migration of pancreatic cancer

Objective

Epithelial-to-mesenchymal transition (EMT) is tightly associated with the invasion and metastasis of pancreatic cancer with rapid progression and poor prognosis. Notably, gene alternative splicing (AS) event plays a critical role in regulating the progression of pancreatic cancer. Therefore, this study aims to identify the EMT-related AS event in pancreatic cancer.

Methods

The EMT-related gene sets, transcriptomes, and matched clinical data were obtained from the MSigDB, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. Key gene AS events associated with liver metastasis were identified by prognostic analysis, gene set variation analysis (GSVA), and correlation analysis in pancreatic cancer. The cell line and organoid model was constructed to evaluate these key gene AS events in regulating pancreatic cancer in vitro. Furthermore, we established an EMT-related gene set consisting of 13 genes by prognostic analysis, the role of which was validated in two other databases. Finally, the human pancreatic cancer tissue and organoid model was used to evaluate the correlation between the enrichment of this gene set and liver metastasis.

Results

Prognostic analysis and correlation analysis revealed that eight AS events were closely associated with the prognosis of pancreatic cancer. Furthermore, the expression of TMC7 and CHECK1 AS events was increased in the metastatic lesions of the human tissue and organoid model. Additionally, the knockdown of exon 17 of TMC7 significantly inhibited the proliferation, invasion, and migration of pancreatic cancer cells in 2D and 3D cell experiments. Finally, the expression of exon 17 of TMC17 exhibited a significant correlation with the poor prognosis in pancreatic ductal adenocarcinoma (PDAC).

Conclusion

The AS events of TMC7 and CHECK1 were associated with liver metastasis in pancreatic cancer. Moreover, exon 17 of TMC7 could be a potential therapeutic target in pancreatic cancer.

Robust identification of common genomic biomarkers from multiple gene expression profiles for the prognosis, diagnosis, and therapies of pancreatic cancer

Pancreatic cancer (PC) is one of the leading causes of cancer-related death globally. So, identification of potential molecular signatures is required for diagnosis, prognosis, and therapies of PC. In this study, we detected 71 common differentially expressed genes (cDEGs) between PC and control samples from four microarray gene-expression datasets (GSE15471, GSE16515, GSE71989, and GSE22780) by using robust statistical and machine learning approaches, since microarray gene-expression datasets are often contaminated by outliers due to several steps involved in the data generating processes. Then we detected 8 cDEGs (ADAM10, COL1A2, FN1, P4HB, ITGB1, ITGB5, ANXA2, and MYOF) as the PC-causing key genes (KGs) by the protein-protein interaction (PPI) network analysis. We validated the expression patterns of KGs between case and control samples by box plot analysis with the TCGA and GTEx databases. The proposed KGs showed high prognostic power with the random forest (RF) based prediction model and Kaplan-Meier-based survival probability curve. The KGs regulatory network analysis detected few transcriptional and post-transcriptional regulators for KGs. The cDEGs-set enrichment analysis revealed some crucial PC-causing molecular functions, biological processes, cellular components, and pathways that are associated with KGs. Finally, we suggested KGs-guided five repurposable drug molecules (Linsitinib, CX5461, Irinotecan, Timosaponin AIII, and Olaparib) and a new molecule (NVP-BHG712) against PC by molecular docking. The stability of the top three protein-ligand complexes was confirmed by molecular dynamic (MD) simulation studies. The cross-validation and some literature reviews also supported our findings. Therefore, the finding of this study might be useful resources to the researchers and medical doctors for diagnosis, prognosis and therapies of PC by the wet-lab validation.

System Analysis Based on Pancreatic Cancer Progression Identifies BRINP2 as a Novel Prognostic Biomarker

Pancreatic adenocarcinoma (PAAD) is a malignant tumor of the digestive system, which develops rapidly and has no obvious early symptoms. This study aims to discover the biomarkers associated with PAAD development. We obtained RNA expression of PAAD patient samples and corresponding clinical data from The cancer genome atlas (TCGA), and screened out BMP/RA-inducible neural-specific protein 2 (BRINP2) gene which is highly associated with PAAD severity. Then, gene ontology (GO) enrichment, Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis and single-sample gene set enrichment analysis (ssGSEA) analysis were performed to explore the biological functions of BRINP2. Subsequently, long non-coding RNA (lncRNAs) associated with BRINP2 were screened out via correlation analysis, and Cox regression analysis and least absolute shrinkage selection operator (LASSO) regression analysis were used to construct the risk prediction model. We further validated the expression level of BRINP2 and its associated lncRNAs in BRINP2-associated lncRNAs prognostic model in vitro. We proposed that BRINP2 might be correlated to the tumor immune microenvironment and could also be used as a biomarker for PAAD progression. GO enrichment analysis and KEGG pathway analysis showed that the prognostic model was highly correlated to immune microenvironment-related pathways. Additionally, we established a BRINP2-associated lncRNAs prognostic model consisting of three lncRNAs. We validated the expression trends of BRINP2 and its associated lncRNAs in BRINP2-associated lncRNAs prognostic model in PAAD cells with various severity of metastatic potential using the quantitative real-time PCR (qRT-PCR). Meanwhile, pRRophetic R package was employed to predict potential therapeutic drugs for BRINP2-associated lncRNAs prognostic model of PAAD. The results suggest that BRINP2 can be used as a novel prognostic biomarker for PAAD.

Molecular logic of salt taste reception in special reference to transmembrane channel-like 4 (TMC4)

The taste is biologically of intrinsic importance. It almost momentarily perceives environmental stimuli for better survival. In the early 2000s, research into taste reception was greatly developed with discovery of the receptors. However, the mechanism of salt taste reception is not fully elucidated yet and many questions still remain. At present, next-generation sequencing and genome-editing technologies are available which would become pivotal tools to elucidate the remaining issues. Here we review current mechanisms of salt taste reception in particular and characterize the properties of transmembrane channel-like 4 as a novel salt taste-related molecule that we found using these sophisticated tools.

TMPRSS4 is a novel biomarker and correlated with immune infiltration in thyroid carcinoma

Transmembrane protease serine 4 (TMPRSS4) is a cancer-associated protease associated with prognosis in various types of cancer. Mechanistically, TMPRSS4 mainly regulates malignant phenotypes, such as tumor invasion and metastasis, by either the epithelial to mesenchymal transition (EMT) program or promoting the proliferation of cancer cells. To date, TMPRSS4 and immune infiltration in thyroid carcinoma (TC) are largely unknown. Thus, this paper evaluated the expression of TMPRSS4 in tumor tissue through the Tumor Immune Estimation Resource (TIMER) database, and Oncomine, and its correlation with clinical parameters by UALCAN databases. Furthermore, we analyzed its prognostic value from Kaplan-Meier Plotter database, and the relationship between TMPRSS4 and the abundance of tumor-infiltrating lymphocytes (TILs) in TC in TISIDB, screening potential immune targets to explore novel mechanisms for the clinical management of TC. Finally, we assessed the correlation between TMPRSS4 and some immune markers to uncover a potential immune-related biomarker in TC patients by TIMER2.0. The results revealed that TMPRSS4 was highly expressed in TC and was also associated with lymphatic metastasis, advanced stage, histological subtype, and favorable clinical outcome. The stratified analysis based on immune cell content showed that decreased TMPRSS4 had worse prognosis in CD8⁺ T cell-enriched TC patients. TMPRSS4 was positively correlated with tumor immune infiltration and the expression of gene markers of immune cells. Notably, its expression was lower in the lymphocyte-depleted subtype than in other immunosubtypes in TC. Moreover, TMPRSS4 was closely related to chemokines as well as their receptors and the immunosuppressive checkpoints CTLA-4, PD-1, and HLA-G. In conclusion, TMPRSS4 may act as a novel biomarker predicting prognosis and immune infiltration in TC.

Identification of Potential Biomarkers for Cancer Cachexia and Anti-Fn14 Therapy

BACKGROUND

Developing therapies for cancer cachexia has not been successful to date, in part due to the challenges of achieving robust quantitative measures as a readout of patient treatment. Hence, identifying biomarkers to assess the outcomes of treatments for cancer cachexia is of great interest and important for accelerating future clinical trials.

METHODS

We established a novel xenograft model for cancer cachexia with a cachectic human PC3* cell line, which was responsive to anti-Fn14 mAb treatment. Using RNA-seq and secretomic analysis, genes differentially expressed in cachectic and non-cachectic tumors were identified and validated by digital droplet PCR (ddPCR). Correlation analysis was performed to investigate their impact on survival in cancer patients.

RESULTS

A total of 46 genes were highly expressed in cachectic PC3* tumors, which were downregulated by anti-Fn14 mAb treatment. High expression of the top 10 candidates was correlated with low survival and high cachexia risk in different cancer types. Elevated levels of LCN2 were observed in serum samples from cachectic patients compared with non-cachectic cancer patients.

CONCLUSION

The top 10 candidates identified in this study are candidates as potential biomarkers for cancer cachexia. The diagnostic value of LCN2 in detecting cancer cachexia is confirmed in patient samples.

Systems biology and OMIC data integration to understand gastrointestinal cancers

Gastrointestinal (GI) cancers are a set of diverse diseases affecting many parts/ organs. The five most frequent GI cancer types are esophageal, gastric cancer (GC), liver cancer, pancreatic cancer, and colorectal cancer (CRC); together, they give rise to 5 million new cases and cause the death of 3.5 million people annually. We provide information about molecular changes crucial to tumorigenesis and the behavior and prognosis. During the formation of cancer cells, the genomic changes are microsatellite instability with multiple chromosomal arrangements in GC and CRC. The genomically stable subtype is observed in GC and pancreatic cancer. Besides these genomic subtypes, CRC has epigenetic modification (hypermethylation) associated with a poor prognosis. The pathway information highlights the functions shared by GI cancers such as apoptosis; focal adhesion; and the p21-activated kinase, phosphoinositide 3-kinase/Akt, transforming growth factor beta, and Toll-like receptor signaling pathways. These pathways show survival, cell proliferation, and cell motility. In addition, the immune response and inflammation are also essential elements in the shared functions. We also retrieved information on protein-protein interaction from the STRING database, and found that proteins Akt1, catenin beta 1 (CTNNB1), E1A binding protein P300, tumor protein p53 (TP53), and TP53 binding protein 1 (TP53BP1) are central nodes in the network. The protein expression of these genes is associated with overall survival in some GI cancers. The low TP53BP1 expression in CRC, high EP300 expression in esophageal cancer, and increased expression of Akt1/TP53 or low CTNNB1 expression in GC are associated with a poor prognosis. The Kaplan Meier plotter database also confirmed the association between expression of the five central genes and GC survival rates. In conclusion, GI cancers are very diverse at the molecular level. However, the shared mutations and protein pathways might be used to understand better and reveal diagnostic/prognostic or drug targets.

A Risk-Assessing Signature Based on Hypoxia- and Immune-Related Genes for Prognosis of Lung Adenocarcinoma Patients

Lung Adenocarcinoma (LUAD) drastically influences human health. Tumor hypoxia and immunity impact hugely on the immunotherapeutic effect of LUAD patients. This study is aimed at exploring the prognostic markers associated with hypoxia and immunity in LUAD patients and evaluates their reliability. The relationship between hypoxia and immune-related genes and prognoses of LUAD patients was investigated by the univariate regression analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) methods were used to reveal the enriched pathways and biological processes of prognosis-related genes. Univariate, LASSO, and multivariate Cox regression analyses were used to construct a prognostic signature and verify its independence. The reliability of the signature was evaluated by the Principal Component Analysis (PCA), the Kaplan-Meier (K-M) curve, and the receiver operating characteristic (ROC) curve. Gene set enrichment analysis (GSEA), tumor mutational burden (TMB), and single-sample GSEA (ssGSEA) further verified the performance of the signature. Finally, a prognostic signature for LUAD was constructed based on 7 hypoxia- and immune-related genes. According to riskScores acquired from the signature, the test set was divided into groups, where the prognosis of high-risk patients was poor. The feature genes had good reliability, and the riskScore could be used as an independent prognostic factor for LUAD patients. Meanwhile, high TMB scores and low immune scores were found in high-risk patients, and feature genes were enriched in signaling pathways such as cell cycle and p53 signaling pathway. In sum, a prognostic signature based on 7 hypoxia- and immune-related genes was constructed.

Association of the TGFβ gene family with microenvironmental features of gastric cancer and prediction of response to immunotherapy

In the complex tumor microenvironment, TGFβ is a pleiotropic cytokine involved in regulating cellular processes such as cancer cell proliferation, apoptosis and metastasis. TGFβ defines three subtypes (TGFβ1, TGFβ2, and TGFβ3), of which TGFβ is highly expressed in many cancers, especially those showing high dissemination potential. In addition, increased expression of TGFβ in multiple cancers is usually positively correlated with epithelial mesenchymal transition (EMT) and coordinated with the expression of genes driving EMT-related genes. TGFβ signaling in the tumor microenvironment inhibits the antitumor function of multiple immune cell populations, including T cells and natural killer cells, and the resulting immunosuppression severely limits the efficacy of immune checkpoint inhibitors and other immunotherapeutic approaches. As a major pathway to enhance the efficacy of cancer immunotherapy effects, the role of TGFβ signaling inhibitors have been evaluated in many clinical trials. However, the potential functions and mechanisms of TGFβ1, TGFβ2 and TGFβ3 in gastric cancer progression and tumor immunology are unclear. In this study, we comprehensively analyzed TGFβ1, TGFβ2 and TGFβ3 and gastric cancer microenvironmental features, including immune cell infiltration, EMT, hypoxia, mutation, immunotherapy and drug treatment, based on HMUCH sequencing data (GSE184336) and public databases. We also validated the protein expression levels of TGFβ in gastric cancer tissues as well as the role of TGFβ factor in cytology experiments. This report reveals the important role of the TGFβ gene family in gastric cancer and provides possible relationships and potential mechanisms of TGFβ in gastric cancer.

HAMP as a Prognostic Biomarker for Colorectal Cancer Based on Tumor Microenvironment Analysis

Colorectal cancer (CRC) is the most common digestive tumor in the world and has a high mortality rate. The development and treatment of CRC are related to the immune microenvironment, but immune response-related prognostic biomarkers are lacking. In this study, we used The Cancer Genome Atlas (TCGA) to explore the tumor microenvironment (TME) and weighted gene coexpression network analysis (WGCNA) to identify significant prognostic genes. We also identified differentially expressed genes in the TCGA data and explored immune-related genes and transcription factors (TFs). Then, we built a TF regulatory network and performed a comprehensive prognostic analysis of an lncRNA-associated competitive endogenous RNA network (ceRNA network) to build a prognostic model. CCR8 and HAMP were identified both in the WGCNA key module and as immune-related genes. HAMP had good prognostic value for CRC and was highly expressed in CRC tissues and had a negative correlation with CD4⁺ T cells and M0 macrophages based on immunohistochemistry and immunofluorescence staining of clinical specimens.We found that HAMP had high prognostic and therapeutic target value for CRC and was associated with liver metastasis. These analysis results revealed that HAMP may be a candidate immune-related prognostic biomarker for CRC.

Identification and Validation of a Novel Prognostic Gene Model for Colorectal Cancer

Aims

Colon cancer (CRC), with high morbidity and mortality, is a common and highly malignant cancer, which always has a bad prognosis. So it is urgent to employ a reasonable manner to assess the prognosis of patients. We developed and validated a gene model for predicting CRC risk.

Methods

The Gene Expression Omnibus (GEO) database was used to extract the gene expression profiles of CRC patients (N = 181) from GEO to identify genes that were differentially expressed between CRC patients and controls and then stable signature genes by firstly using both robust likelihood-based modeling with 1000 iterations and random survival forest variable hunting algorithms. Cluster analysis using the longest distance method was drawn out, and Kaplan–Meier (KM) survival analysis was used to compare the clusters. Meanwhile, the risk score was evaluated in three independent datasets including the GEO and Illumina HiSeq sequencing platforms. The corresponding risk index was calculated, and samples were clustered into high- and low-risk groups according to the median. And survival ROC analysis was used to evaluate the prognostic model. Finally, the Gene Set Enrichment Analysis (GSEA) was performed for further functional enrichment analyses.

Results

A 10-gene model was obtained, including 7 negative impact factors (SLC39A14, AACS, ERP29, LAMP3, TMEM106C, TMED2, and SLC25A3) and 3 positive ones (CNPY2, GRB10, and PBK), which related with several important oncogenic pathways (KRAS signaling, TNF-α signaling pathway, and WNT signaling pathway) and several cancer-related cellular processes (epithelial mesenchymal transition and cellular apoptosis). By using colon cancer datasets from The Cancer Genome Atlas (TCGA), the model was validated in KM survival analysis (P ≤ 0.001) and significant analysis with recurrence time (P = 0.0018).

Conclusions

This study firstly developed a stable and effective 10-gene model by using novel combined methods, and CRC patients might be able to use it as a prognostic marker for predicting their survival and monitoring their long-term treatment.

A novel prognostic signature of metastasis-associated genes and personalized therapeutic strategy for lung adenocarcinoma patients

Lung adenocarcinoma (LUAD) is a highly invasive and metastatic malignant tumor with high morbidity and mortality. This study aimed to construct a prognostic signature for LUAD patients based on metastasis-associated genes (MAGs). RNA expression profiles were downloaded from the Cancer Genome Atlas (TCGA) database. RRA method was applied to identify differentially expressed MAGs. A total of 192 significantly robust MAGs were determined among seven GEO datasets. MAGs were initially selected through the Lasso Cox regression analysis and 6 MAGs were included to construct a prognostic signature model. Transcriptome profile, patient prognosis, correlation between the risk score and clinicopathological features, immune cell infiltration characteristics, immunotherapy sensitivity and chemotherapy sensitivity differed between low- and high-risk groups after grouping according to median risk score. The reliability and applicability of the signature were further validated in the GSE31210, GSE50081 and GSE68465 cohort. CMap predicted 62 small molecule drugs on the base of the prognostic MAGs. Targeted drug staurosporine had hydrogen bonding with Gln-172 of SLC2A1, which is one of MAGs. Staurosporine could inhibit cell migration in A549 and H1299. We further verified mRNA and protein expression of 6 MAGs in A549 and H1299. The signature can serve as a promising prognostic tool and may provide a novel personalized therapeutic strategy for LUAD patients.

An Inflammatory Response-Related Gene Signature Reveals Distinct Survival Outcome and Tumor Microenvironment Characterization in Pancreatic Cancer

Background: Desmoplasia or rich fibrotic stroma is a typical property of pancreatic cancer (PC), with a significant impact on tumor progression, metastasis, and chemotherapy response. Unusual inflammatory responses are considered to induce fibrosis of tissue, but the expression and clinical significance of inflammatory response-related genes in PC have not been clearly elucidated. Methods: Prognosis-related differentially expressed genes (DEGs) between tumor and normal tissues were identified by comparing the transcriptome data of PC samples based on The Cancer Genome Atlas (TCGA) portal and the Genotype Tissue Expression (GTEx) databases. Samples from the ArrayExpress database were used as an external validation cohort. Results: A total of 27 inflammatory response-related DEGs in PC were identified. Least absolute shrinkage and selection operator (LASSO) analysis revealed three core genes that served as an inflammatory response gene signature (IRGS), and a risk score was calculated. The diagnostic accuracy of the IRGS was validated in the training (n = 176) and validation (n = 288) cohorts, which reliably predicted the overall survival (OS) and disease-free survival (DFS) of patients with PC. Furthermore, multivariate analysis identified the risk score as an independent risk factor for OS and DFS. The comprehensive results suggested that a high IRGS score was correlated with decreased CD8⁺ T-cell infiltration, increased M2 macrophage infiltration, increased occurrence of stroma-activated molecular subtype and hypoxia, enriched myofibroblast-related signaling pathways, and greater benefit from gemcitabine. Conclusion: The IRGS was able to promisingly distinguish the prognosis, the tumor microenvironment characteristics, and the benefit from chemotherapy for PC.

Multiomics Data Analysis and Identification of Immune-Related Prognostic Signatures With Potential Implications in Prognosis and Immune Checkpoint Blockade Therapy of Glioblastoma

Background

In recent years, glioblastoma multiforme (GBM) has been a concern of many researchers, as it is one of the main drivers of cancer-related deaths worldwide. GBM in general usually does not responding well to immunotherapy due to its unique microenvironment.

Methods

To uncover any further informative immune-related prognostic signatures, we explored the immune-related distinction in the genetic or epigenetic features of the three types (expression profile, somatic mutation, and DNA methylation). Twenty eight immune-related hub genes were identified by Weighted Gene Co-Expression Network Analysis (WGCNA). The findings showed that three genes (IL1R1, TNFSF12, and VDR) were identified to construct an immune-related prognostic model (IRPM) by lasso regression. Then, we used three hub genes to construct an IRPM for GBM and clarify the immunity, mutation, and methylation characteristics.

Results

Survival analysis of patients undergoing anti-program cell death protein 1 (anti-PD-1) therapy showed that overall survival was superior in the low-risk group than in the high-risk group. The high-risk group had an association with epithelial-mesenchymal transition (EMT), high immune cell infiltration, immune activation, a low mutation number, and high methylation, while the low-risk group was adverse status.

Conclusions

In conclusion, IRPM is a promising tool to distinguish the prognosis of patients and molecular and immune characteristics in GBM, and the IRPM risk score can be used to predict patient sensitivity to checkpoint inhibitor blockade therapy. Thus, three immune-related signatures will guide us in improving treatment strategies and developing objective diagnostic tools.

Metabolism-Related Bioinformatics Analysis Reveals That HPRT1 Facilitates the Progression of Oral Squamous Cell Carcinoma In Vitro

Objectives

Many studies have shown that dysregulation of metabolism contributes to oncogenesis. However, the exact roles of metabolism-related genes (MRGs) in oral squamous cell carcinoma (OSCC) remain unclear. Thus, we aimed to identify a prognostic signature related to MRGs in OSCC.

Methods

The gene sequencing data of OSCC samples and the MRG set were downloaded from The Cancer Genome Atlas (TCGA) and the Molecular Signatures Database (MSigDB). The Wilcoxon rank-sum test was used to identify differentially expressed MRGs. Then, a prognostic signature was established by multivariate Cox regression analysis. Finally, prognosis-related MRGs were selected and further validated in OSCC tissues and cell lines.

Results

A prognostic signature that included 8 MRGs was constructed. Multiple survival analysis revealed that only HPRT1 might be an independent biomarker and indicator of poor overall survival in OSCC patients. The expression of HPRT1 was then found to be upregulated in OSCC tissues and cell lines, and suppression of HPRT1 gene expression by siRNA inhibited the proliferation, migration, and invasion of OSCC cells in vitro.

Conclusions

MRGs play an important role in the development of OSCC. Furthermore, HPRT1 might be an independent biomarker of OSCC and enhance OSCC proliferation, migration, and invasion in vitro; these results emphasize the potential utility of HPRT1 in OSCC therapy.

Interferon regulatory factor 5‑induced upregulation of zinc‑finger protein 217 promotes pancreatic carcinoma progression

The aim of the present study was to investigate the molecular mechanisms of zinc‑finger protein 217 (ZNF217) in pancreatic carcinoma (PC) progression. ZNF217‑associated expression and survival data from patients with PC were retrieved from the Gene Expression Profiling Interactive Analysis server. The mRNA expression level of ZNF217 was detected by reverse transcription‑quantitative PCR. Cell Counting Kit‑8, colony formation, wound‑healing and Transwell assays were conducted to assess cellular proliferation, migratory and invasive abilities. Proliferation was also examined by immunofluorescence detection of Ki67 expression, and chromatin immunoprecipitation (ChIP) and luciferase reporter assays were performed to detect the interaction between ZNF217 and interferon regulatory factor 5 (IRF5). ZNF217 was found to be significantly upregulated in tumor tissues and cancer cell lines, which was associated with a poor survival rate in patients with PC. ZNF217 silencing markedly suppressed cellular proliferation and migratory and invasive abilities, as well as decreased the expression of Ki67. IRF5 was also upregulated in PC tumor tissues and was shown to positively regulate the activity of the ZNF217 promoter and its mRNA expression levels. Furthermore, ChIP assays demonstrated that IRF5 bound to the promoter region of ZNF217 in vitro. In conclusion, ZNF217 silencing exerted notable inhibitory effects on the progression of PC. Thus, ZNF217 may serve as a potential target for developing novel therapeutic strategies for PC.

Molecular signatures of tumor progression in pancreatic adenocarcinoma identified by energy metabolism characteristics

BACKGROUND

In this study, we performed a molecular evaluation of primary pancreatic adenocarcinoma (PAAD) based on the comprehensive analysis of energy metabolism-related gene (EMRG) expression profiles.

METHODS

Molecular subtypes were identified by nonnegative matrix clustering of 565 EMRGs. An overall survival (OS) predictive gene signature was developed and internally and externally validated based on three online PAAD datasets. Hub genes were identified in molecular subtypes by weighted gene correlation network analysis (WGCNA) coexpression algorithm analysis and considered as prognostic genes. LASSO cox regression was conducted to establish a robust prognostic gene model, a four-gene signature, which performed better in survival prediction than four previously reported models. In addition, a novel nomogram constructed by combining clinical features and the 4-gene signature showed high-confidence clinical utility. According to gene set enrichment analysis (GSEA), gene sets related to the high-risk group participate in the neuroactive ligand receptor interaction pathway.

CONCLUSIONS

In summary, EMRG-based molecular subtypes and prognostic gene models may provide a novel research direction for patient stratification and trials of targeted therapies.

Improper Proteostasis: Can It Serve as Biomarkers for Neurodegenerative Diseases?

Cells synthesize new proteins after multiple molecular decisions. Damage of existing proteins, accumulation of abnormal proteins, and basic requirement of new proteins trigger protein quality control (PQC)-based alternative strategies to cope against proteostasis imbalance. Accumulation of misfolded proteins is linked with various neurodegenerative disorders. However, how deregulated components of this quality control system and their lack of general mechanism-based long-term changes can serve as biomarkers for neurodegeneration remains largely unexplored. Here, our article summarizes the chief findings, which may facilitate the search of novel and relevant proteostasis mechanism-based biomarkers associated with neuronal disorders. Understanding the abnormalities of PQC coupled molecules as possible biomarkers can help to determine neuronal fate and their contribution to the aetiology of several nervous system disorders.

LRP1B is a Potential Biomarker for Tumor Immunogenicity and Prognosis of HCC Patients Receiving ICI Treatment

Background

New predictors of the efficacy of hepatocellular carcinoma (HCC) immunotherapy are needed. The ability of a single gene mutation to predict the therapeutic effect of immune checkpoint inhibitors (ICI) in HCC remains unknown.

Methods

The most frequently mutated genes in HCC were analyzed using the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Mutant genes that correlated with the tumor mutational burden (TMB) and prognosis were obtained. The mutation pattern and immunological function of one of the most frequently mutated genes, LRP1B, were determined. A pan-tumor analysis of LRP1B expression, association with cancer prognosis, and immunological role was also explored. A retrospective clinical study was conducted using 102 HCC patients who received ICI treatment to further verify whether gene mutations can predict the effectiveness of immunotherapy and prognosis of HCC.

Results

LRP1B is among the most frequently mutated genes in HCC cohorts in TCGA and ICGC datasets. TCGA data showed that the LRP1B mutation activated immune signaling pathways and promoted mast cell activation. Patients with LRP1B mutations had significantly higher TMB than those with wild-type LRP1B. LRP1B expression correlated with the cancer-immunity cycle and immune cell infiltration. High LRP1B expression was also associated with poor survival among HCC patients. Results from the clinical study showed that HCC patients in the LRP1B mutation group had a poor response to ICI and worse prognosis than the wild-type group. The LRP1B mutation group had significantly higher TMB and mast cell infiltration in tumor tissues.

Conclusion

This study is the first to report that a single gene LRP1B mutation is associated with a poor clinical response to ICI treatment and negative outcomes in HCC patients. HighLRP1B expression correlated with tumor immunity and HCC prognosis.

Integrated Analysis of Multi-Omics Data to Identify Prognostic Genes for Pancreatic Cancer

Pancreatic cancer (PC) is a common cause of cancer-related deaths. Current research shows that prognostic biomarkers play a key role in the treatment of PC. This study aimed to identify prognostic genes through bioinformatics research. We combined data from 175 cases of PC from the cancer genome atlas (TCGA) database with gene mutation expression, level distribution of methylation, mRNA expression, and through weighted correlation network analysis to nine hub genes. Subsequently, these genes were verified on TCGA and Gene Expression Profiling Interactive Analysis (GEPIA) platforms. Reverse transcription quantitative PCR (RT-qPCR) was performed to investigate the expression levels of 9 genes in PC cells and cancerous and 30 PC cases and corresponding adjacent tissues. CIBERSORT database analysis was conducted for hub genes. Our findings demonstrated that the 9 genes (MST1R, TMPRSS4, PTK6, KLF5, CGN, ABHD17C, MUC1, CAPN8, and B3GNT3) were prognostic biomarkers of PC identified from the top 10 genes of the 2 coexpression modules. The nine genes were then used to divide early PC cases into two subgroups with significant differences in prognosis and differences in function (digestion, extracellular cell adhesion). Further analysis revealed that the nine genes were highly expressed in PC tissues. In addition, MST1R, PTK6, ABHD17C, and CGN mRNA were expressed high in PC cells and clinical tissues. CIBERSORT analysis indicated that the expression of these genes was closely correlated with naive B cells, CD8⁺ T cells, and M0 macrophages. This suggests that these genes could play a carcinogenic role in the preservation of immune-dominant status for the tumor microenvironment. The nine key genes identified in this study could enhance our understanding of the molecular mechanisms associated with PC.

TMC5 is Highly Expressed in Human Cancers and Corelates to Prognosis and Immune Cell Infiltration: A Comprehensive Bioinformatics Analysis

Background: The oncological role of TMC5 in human cancers has only been revealed partially. We performed integrated bioinformatics analysis to provide a thorough and detailed insight of associations between TMC5 and tumorigenesis, cancer progression, and prognosis.

Methods: With reference to the accessible online databases, the TMC5 expressions in tumor tissues and corresponding normal tissues, different pathological stages, and various cancer cells were analyzed, while the protein levels of TMC5 in different cancers were also inspected. Meanwhile, the prognostic value of TMC5 expression in multiple cancers as well as in advanced-stage patients was investigated. Furthermore, the mutational data of TMC5 and its correlation with cancer prognosis were assessed. Moreover, the association between the TMC5 level and immune cell infiltration was evaluated. Next, TMC5-related pathway alterations and drug responses were summarized. Finally, the TMC5 based protein network was generated, and relevant enrichment was performed.

Results: In our study, the expression level of TMC5 was significantly higher in the tumor tissue than that of the normal tissues in most cancer types. Fluctuations of TMC5 levels were also observed among different pathological stages. In the meantime, the protein level elevated in the tumor tissue in the cancers enrolled. Moreover, the expression of TMC5 was not only prognostic for overall survival (OS) or recurrence free survival (RFS) in various types of cancers but also correlated to OS in patients with more advanced cancers. Additionally, the mutational status of TMC5 is also associated with prognosis in cancer patients. It is worth noting that the TMC5 level was closely related to immune cell infiltrations, especially in ESCA, TGCT, and USC. The TMC5 expression was also identified as an activator for pathways including PI3K/AKT, RAS/MAPK, and TSC/mTOR, proved to be associated with multiple drug responses and assessed to be interactive with the TMEM family.

Conclusion: TMC5 might function as a potential marker for cancer survival and immune responses.

Exosome-mediated lncRNA SNHG11 regulates angiogenesis in pancreatic carcinoma through miR-324-3p/VEGFA axis

Pancreatic carcinoma (PC) is one of the most common and deadly human malignancies worldwide. LncRNAs play significant roles in the occurrence and development of various cancers. LncRNA SNHG11 (SNHG11) has been found to display high expression in serum of PC patients, which implies that dysregulated SNHG11 may be related to the development of PC. However, there is still a knowledge gap concerning the specific function and molecular mechanism of SNHG11 in PC. After conducting experiments with constructed models in vitro or in vivo, we found that exosomal SNHG11 promoted cell proliferation, migration, and angiogenesis but impeded cell apoptosis in PC in vitro, and additionally, it facilitated tumor growth in vivo. Exosome-mediated SNHG11 regulated the expression of VEGFA through sponging miR-324-3p. Rescue assays validated that the inhibitory effect of SNHG11 depletion on cell proliferation, migration, and angiogenesis could be reversed by miR-324-3p downregulation or VEGFA upregulation, and the promoting effect of SNHG11 silence on cell apoptosis could be rescued by transfection of miR-324-3p inhibitor or pcDNA3.1-VEGFA. To conclude, exosomal-mediated SNHG11 could regulate PC progression via miR-324-3p/VEGFA axis. Our findings may provide a novel insight for understanding PC, which might contribute to the development of potential PC biomarker.

Utility of TMPRSS4 as a Prognostic Biomarker and Potential Therapeutic Target in Patients with Gastric Cancer

BACKGROUND

Transmembrane serine protease 4 (TMPRSS4) belongs to the family of type II transmembrane serine proteases that are known to be upregulated in many malignant tumors. However, there is a paucity of studies documenting the clinical impact and biological effects of TMPRSS4 on gastric cancer (GC) patients who underwent surgery.

METHODS

Tissues samples were obtained from 105 patients with GC who underwent gastrectomy followed by adjuvant chemotherapy, excluding those at stage I. The expression of TMPRSS4 was examined through immunohistochemical analysis. The association between TMPRSS4 expression and clinico-pathological features as well as prognosis was assessed. Moreover, the effects of TMPRSS4 expression on cell migration and sensitivity to 5-FU were investigated.

RESULTS

The expression rate of TMPRSS4 was 56.3% (59/105) in GC cases. The expression of TMPRSS4 was positively correlated with the depth of tumor (T) and venous (V) invasion. The 5-year overall survival (OS) and recurrence-free survival (RFS) rates of the TMPRSS4-positive group was significantly lower than that of the TMPRSS4-negative group (p=0.0001 and p=0.005, respectively). Especially, there was significant differences in OS and RFS of patients with stage III cancer between the two groups (p=0.0064 and 0.012, respectively). Multivariate analysis demonstrated that TMPRSS4 expression and the stage of cancer were crucial prognostic factors for RFS. TMPRSS4-silenced GC cells exhibited increased sensitivity to 5-FU when compared with the non-specific control siRNA-transfected cells.

CONCLUSION

TMPRSS4 can be considered as a potential prognostic biomarker, especially for stage III, and a promising therapeutic target for GC.

Identification of a Four Cancer Stem Cell-Related Gene Signature and Establishment of a Prognostic Nomogram Predicting Overall Survival of Pancreatic Adenocarcinoma

BACKGROUND

Cancer stem cells (CSCs) are now being considered as the initial component in the development of pancreatic adenocarcinoma (PAAD). Our aim was to develop a CSCrelated signature to assess the prognosis of PAAD patients for the optimization of treatment.

METHODS

Differentially expressed genes (DEGs) between pancreatic tumor and normal tissue in the Cancer Genome Atlas (TCGA) were screened out, and the weighted gene correlation network analysis (WGCNA) was employed to identify the CSC-related gene sets. Then, univariate, Lasso Cox regression analyses and multivariate Cox regression were applied to construct a prognostic signature using the CSC-related genes. Its prognostic performance was validated in TCGA and ICGC cohorts. Furthermore, Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors in PAAD, and a prognostic nomogram was established.

RESULTS

The Kaplan-Meier analysis, ROC curve and C-index indicated the good performance of the CSC-related signature at predicting overall survival (OS). Univariate Cox regression and multivariate Cox regression revealed that the CSC-related signature was an independent prognostic factor in PAAD. The nomogram was superior to the risk model and AJCC stage in predicting OS. In terms of mutation and tumor immunity, patients in the high-risk group had higher tumor mutation burden (TMB) scores than patients in the low-risk group, and the immune score and the ESTIMATE score were significantly lower in the high-risk group. Moreover, according to the results of principal component analysis (PCA) and Gene Set Enrichment Analysis (GSEA), the low-risk and high-risk groups displayed different stemness statuses based on the risk model.

CONCLUSION

Our study identified four CSC-related gene signatures and established a prognostic nomogram that reliably predicts OS in PAAD. The findings may support new ideas for screening therapeutic targets to inhibit stem characteristics and the development of PAAD.

Systematic Analysis of an Invasion-Related 3-Gene Signature and Its Validation as a Prognostic Model for Pancreatic Cancer

Background

Pancreatic adenocarcinoma (PAAD) is a malignant tumor of the digestive system that is associated with a poor prognosis in patients owing to its rapid progression and high invasiveness.

Methods

Ninety-seven invasive-related genes obtained from the CancerSEA database were clustered to obtain the molecular subtype of pancreatic cancer based on the RNA-sequencing (RNA-seq) data of The Cancer Genome Atlas (TCGA). The differentially expressed genes (DEGs) between subtypes were obtained using the limma package in R, and the multi-gene risk model based on DEGs was constructed by Lasso regression analysis. Independent datasets GSE57495 and GSE62452 were used to validate the prognostic value of the risk model. To further explore the expression of the hub genes, immunohistochemistry was performed on PAAD tissues obtained from a large cohort.

Results

The TCGA-PAAD samples were divided into two subtypes based on the expression of the invasion-related genes: C1 and C2. Most genes were overexpressed in the C1 subtype. The C1 subtype was mainly enriched in tumor-related signaling pathways, and the prognosis of patients with the C1 subtype was significantly worse than those with the C2 subtype. A 3-gene signature consisting of LY6D, BCAT1, and ITGB6 based on 538 DEGs between both subtypes serves as a stable prognostic marker in patients with pancreatic cancer across multiple cohorts. LY6D, BCAT1, and ITGB6 were over-expressed in 120 PAAD samples compared to normal samples.

Conclusions

The constructed 3-gene signature can be used as a molecular marker to assess the prognostic risk in patients with PAAD.

A Prognostic Model of Pancreatic Cancer Based on Ferroptosis-Related Genes to Determine Its Immune Landscape and Underlying Mechanisms

Pancreatic cancer is one of the malignant tumors with the worst prognosis in the world. As a new way of programmed cell death, ferroptosis has been proven to have potential in tumor therapy. In this study, we used the TCGA-PAAD cohort combined with the previously reported 60 ferroptosis-related genes to construct and validate the prognosis model and in-depth analysis of the differences in the function and immune characteristics of different RiskTypes. The results showed that the six-gene signature prognostic model that we constructed has good stability and effectiveness. Further analysis showed that the upregulated genes in the high-risk group were mainly enriched in extracellular matrix receptor-related pathways and other tumor-related pathways and the infiltration of immune cells, such as B, T, and NK cells, was suppressed. In short, our model shows good stability and effectiveness. Further studies have found that the prognostic differences between different RiskTypes may be due to the changes in the ECM-receptor pathway and activation of the immune system. Additionally, ICI drugs can treat pancreatic cancer in high-risk groups.

A Novel Risk-Score Model With Eight MiRNA Signatures for Overall Survival of Patients With Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer with heterogeneous outcomes and diverse therapeutic responses. To classify patients into different groups and facilitate the suitable therapeutic strategy, we first selected eight microRNA (miRNA) signatures in The Cancer Genome Atlas (TCGA)-LUAD cohort based on multi-strategy combination, including differential expression analysis, regulatory relationship, univariate survival analysis, importance clustering, and multivariate combinations analysis. Using the eight miRNA signatures, we further built novel risk scores based on the predefined cutoff and beta coefficients and divided the patients into high-risk and low-risk groups with significantly different overall survival time (p-value < 2 e-16). The risk-score model was confirmed with an independent dataset (p-value = 4.71 e-4). We also observed that the risk scores of early-stage patients were significantly lower than those of late-stage patients. Moreover, our model can also provide new insights into the current clinical staging system and can be regarded as an alternative system for patient stratification. This model unified the variable value as the beta coefficient facilitating the integration of biomarkers obtained from different omics data.

Comprehensive Analysis of E3 Ubiquitin Ligases Reveals Ring Finger Protein 223 as a Novel Oncogene Activated by KLF4 in Pancreatic Cancer

Pancreatic cancer is one of the major malignancies and causes of mortality worldwide. E3 ubiquitin-protein ligases transfer activated ubiquitin from ubiquitin-conjugating enzymes to protein substrates and confer substrate specificity in cancer. In this study, we first downloaded data from The Cancer Genome Atlas pancreatic adenocarcinoma dataset, acquired all 27 differentially expressed genes (DEGs), and identified genomic alterations. Then, the prognostic significance of DEGs was analyzed, and eight DEGs (MECOM, CBLC, MARCHF4, RNF166, TRIM46, LONRF3, RNF39, and RNF223) and two clinical parameters (pathological N stage and T stage) exhibited prognostic significance. RNF223 showed independent significance as an unfavorable prognostic marker and was chosen for subsequent analysis. Next, the function of RNF223 in the pancreatic cancer cell lines ASPC-1 and PANC-1 was investigated, and RNF223 silencing promoted pancreatic cancer growth and migration. To explore the potential targets and pathways of RNF223 in pancreatic cancer, quantitative proteomics was applied to analyze differentially expressed proteins, and metabolism-related pathways were primarily enriched. Finally, the reason for the elevated expression of RNF223 was analyzed, and KLF4 was shown to contribute to the increased expression of RNF233. In conclusion, this study comprehensively analyzed the clinical significance of E3 ligases. Functional assays revealed that RNF223 promotes cancer by regulating cell metabolism. Finally, the elevated expression of RNF223 was attributed to KLF4-mediated transcriptional activation. This study broadens our knowledge regarding E3 ubiquitin ligases and signal transduction and provides novel markers and therapeutic targets in pancreatic cancer.

Development and validation of a four-lipid metabolism gene signature for diagnosis of pancreatic cancer

Abnormal lipid metabolism is closely related to the malignant biological behavior of tumor cells. Such abnormal lipid metabolism provides energy for rapid proliferation, and certain genes related to lipid metabolism encode important components of tumor signaling pathways. In this study, we analyzed pancreatic cancer datasets from The Cancer Genome Atlas and searched for prognostic genes related to lipid metabolism in the Molecular Signature Database. A risk score model was built and verified using the GSE57495 dataset and International Cancer Genome Consortium dataset. Four molecular subtypes and 4249 differentially expressed genes (DEGs) were identified. The DEGs obtained by Weighted Gene Coexpression Network Construction analysis were intersected with 4249 DEGs to obtain a total of 1340 DEGs. The final prognosis model included CA8, CEP55, GNB3 and SGSM2, and these had a significant effect on overall survival. The area under the curve at 1, 3 and 5 years was 0.72, 0.79 and 0.87, respectively. These same results were obtained using the validation cohort. Survival analysis data showed that the model could stratify the prognosis of patients with different clinical characteristics, and the model has clinical independence. Functional analysis indicated that the model is associated with multiple cancer-related pathways. Compared with published models, our model has a higher C-index and greater risk value. In summary, this four-gene signature is an independent risk factor for pancreatic cancer survival and may be an effective prognostic indicator.

AGT serves as a potential biomarker and drives tumor progression in colorectal carcinoma

BACKGROUND

Colorectal carcinoma (CRC) is one of the most common aggressive tumors worldwide, and it is necessary to identify candidate biomarkers and therapeutic targets in CRC to improve patient outcomes.

METHODS

The differentially expressed genes (DEGs) were obtained from CRC microarray. Functional enrichment was performed to explore the function of DEGs, and core genes were identified by Cytoscape. Then, the diagnosis and prognosis markers were identified by ROC curve and survival analyses. More importantly, a series of in vitro studies were conducted in CRC cells to explore the function of the selected biomarker. Further, the drug response was performed by Cancer Cell Line Encyclopedia (CCLE) and Cancer Therapy Response Portal (CTRP). In addition, the effect of drug on CRC cells was evaluated by functional experiments.

RESULTS

The identified DEGs were mainly associated with the processes relating to tumorigenesis. 25 core genes were selected and angiotensinogen (AGT) was filtered out as a diagnosis and prognosis biomarker. Comprehensive in vitro experiments showed that AGT attributed to the proliferation, migration, and invasion of CRC cells, as well as angiogenesis of HUVECs induced by CRC conditional medium. Furthermore, drug response analysis implied that AGT expression was associated with isoliquiritigenins (ISL). Additionally, ISL could suppress the progression of CRC cells.

CONCLUSIONS

AGT is identified as diagnosis and prognosis prediction of CRC. Moreover, AGT attributes to the progression of CRC. Additionally, AGT exhibits fine drug response to ISL, and ISL is also evaluated as potential therapy drug in CRC.

UGT1A Gene Family Members Serve as Potential Targets and Prognostic Biomarkers for Pancreatic Cancer

Background

Pancreatic cancer (PC) is one of the most common cancers worldwide, with high mortality. The UGT1A gene family plays important roles in pharmacology and toxicology, contributing to interindividual differences in drug disposition. However, mRNA expression and prognostic value of the UGT1A gene family in PC have not been identified.

Methods

Oncomine, GEPIA2, DAVID 6.8, Metascape, Kaplan-Meier plotter, cBioPortal, GeneMANIA, TRRUST v2, TIMER, and R software were used in our study.

Results

The transcriptional levels of UGT1A1/3/6/8/9/10 in PC tissues were significantly higher than those in normal tissues. These results were further validated using five pairs of PC tumor tissues and adjacent nontumor tissues. A significant correlation was found between the expression of UGT1A1/6/10 and the pathological stage of PC. PC patients with lower transcriptional levels of UGT1A1/4/5/6/10 were associated with a better prognosis. The differentially expressed UGT1A gene family functions were primarily related to the glucuronidation pathway, cytokine-cytokine receptor interactions, and the ILK signaling pathway. Our data suggest that HNF1A, AHR, and CDX2 are key transcription factors for the UGT1A gene family. Furthermore, the expression levels of UGT1A1/3/8/9/10 were positively correlated with the activities of tumor-infiltrating immune cells, especially B cells. The expression levels of UGT1A6/9 were negatively correlated with macrophage infiltration levels.

Conclusions

These results suggest that the UGT1A gene family could serve as a potential prognostic biomarker and target for PC. However, future studies are required to validate our findings and promote the clinical utility of the UGT1A gene family in PC.

TMPRSS4 overexpression promotes the metastasis of colorectal cancer and predicts poor prognosis of stage III-IV colorectal cancer

PURPOSE

To study in detail the expression pattern and prognostic significance of TMPRSS4 in colorectal cancer.

METHODS

The expression of TMPRSS4 protein was determined using Western blot in the colorectal cancer tissues and normal tissues. Immunohistochemistry was used to detect the TMPRSS4 expression in colorectal cancer tissues, and the clinicopathologic characteristics and prognostic significance were analyzed.

RESULTS

TMPRSS4 overexpression was associated with tumor budding, lymphovascular invasion, perineural invasion, cancerous emboli, infiltration depth, lymph node metastasis, distant metastasis, and tumor node metastasis stage (P < 0.05 for all). Interestingly, TMPRSS4 expression in the tumor budding, tumor emboli, lymph node, and liver metastatic tumor samples was higher than in the paired primary tumors. In contrast, TMPRSS4 overexpression is inversely correlated with both the overall survival and the disease-free survival of the patients with colorectal cancer (P < 0.05 for both). Also, we found that TMPRSS4 is only of significance in predicting the prognosis of stage III and IV colorectal cancer, not stage I and II.

CONCLUSIONS

TMPRSS4 was shown to be involved in the whole process of metastasis from tumor budding to lymph node and/or distant metastasis in colorectal cancer and predicted the unfavorable prognosis of stage III-IV, indicating that it is a novel target for the precise treatment of colorectal cancer with lymph node or distant organ metastasis.