Independent prognostic genes and mechanism investigation for colon cancer

Identification and validation of a prognostic signature based on six immune-related genes for colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a prevalent malignancy with high mortality and morbidity rates. Although the significant efficacy of immunotherapy is well established, it is only beneficial for a limited number of individuals with CRC.

METHODS

Differentially expressed immune-related genes (DE-IRGs) were retrieved from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and ImmPort databases. A prognostic signature comprising DE-IRGs was developed using univariate, LASSO, and multivariate Cox regression analyses. A nomogram integrating the independent prognostic factors was also developed. CIBERSORT was used to assess immune cell infiltration (ICI). Furthermore, wound-healing, colony formation, migration, and invasion assays were performed to study the involvement of ACTG1 in CRC.

RESULTS

A signature including six DE-IRGs was developed. The overall survival (OS) rate was accurately estimated for TCGA and GSE38832 cohorts. The risk score (RS) of the signature was an independent factor for OS. Moreover, a nomogram encompassing age, RS, and pathological T stage accurately predicted the long-term OS probability of individuals with CRC. The high-risk group had an elevated proportion of patients treated with ICIs, including native B cells, relative to the low-risk group. Additionally, ACTG1 expression was upregulated, which supported the proliferation, migration, and invasion abilities of CRC cells.

CONCLUSIONS

An immune-related prognostic signature was developed for predicting OS and for determining the immune status of individuals with CRC. The present study provides new insights into accurate immunotherapy for individuals with CRC. Moreover, ACTG1 may serve as a new immune biomarker.

Phototherapy Restores Deficient Type I IFN Production and Enhances Antitumor Responses in Mycosis Fungoides

Transcriptional profiling demonstrated markedly reduced type I IFN gene expression in untreated mycosis fungoides (MF) skin lesions compared with that in healthy skin. Type I IFN expression in MF correlated with antigen-presenting cell-associated IRF5 before psoralen plus UVA therapy and epithelial ULBP2 after therapy, suggesting an enhancement of epithelial type I IFN. Immunostains confirmed reduced baseline type I IFN production in MF and increased levels after psoralen plus UVA treatment in responding patients. Effective tumor clearance was associated with increased type I IFN expression, enhanced recruitment of CD8+ T cells into skin lesions, and expression of genes associated with antigen-specific T-cell activation. IFNk, a keratinocyte-derived inducer of type I IFNs, was increased by psoralen plus UVA therapy and expression correlated with upregulation of other type I IFNs. In vitro, deletion of keratinocyte IFNk decreased baseline and UVA-induced expression of type I IFN and IFN response genes. In summary, we find a baseline deficit in type I IFN production in MF that is restored by psoralen plus UVA therapy and correlates with enhanced antitumor responses. This may explain why MF generally develops in sun-protected skin and suggests that drugs that increase epithelial type I IFNs, including topical MEK and EGFR inhibitors, may be effective therapies for MF.

Candidate pathway analysis of surfactant proteins identifies CTSH and SFTA2 that influences lung cancer risk

Pulmonary surfactant is a lipoprotein synthesized and secreted by alveolar type II cells in lung. We evaluated the associations between 200,139 single nucleotide polymorphisms (SNPs) of 40 surfactant-related genes and lung cancer risk using genotyped data from two independent lung cancer genome-wide association studies. Discovery data included 18,082 cases and 13,780 controls of European ancestry. Replication data included 1,914 cases and 3,065 controls of European descent. Using multivariate logistic regression, we found novel SNPs in surfactant-related genes CTSH [rs34577742 C > T, odds ratio (OR) = 0.90, 95% confidence interval (CI) = 0.89-0.93, P = 7.64 × 10-9] and SFTA2 (rs3095153 G > A, OR = 1.16, 95% CI = 1.10-1.21, P = 1.27 × 10-9) associated with overall lung cancer in the discovery data and validated in an independent replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.80-0.96, P = 5.76 × 10-3) and SFTA2 (rs3095153 G > A, OR = 1.14, 95% CI = 1.01-1.28, P = 3.25 × 10-2). Among ever smokers, we found SNPs in CTSH (rs34577742 C > T, OR = 0.89, 95% CI = 0.85-0.92, P = 1.94 × 10-7) and SFTA2 (rs3095152 G > A, OR = 1.20, 95% CI = 1.14-1.27, P = 4.25 × 10-11) associated with overall lung cancer in the discovery data and validated in the replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.79-0.97, P = 1.64 × 10-2) and SFTA2 (rs3095152 G > A, OR = 1.15, 95% CI = 1.01-1.30, P = 3.81 × 10-2). Subsequent transcriptome-wide association study using expression weights from a lung expression quantitative trait loci study revealed genes most strongly associated with lung cancer are CTSH (PTWAS = 2.44 × 10-4) and SFTA2 (PTWAS = 2.32 × 10-6).

Transcriptomic patterns in early-secretory and mid-secretory endometrium in a natural menstrual cycle immediately before in vitro fertilization and embryo transfer

OBJECTIVE

This study aimed to evaluate the endometrial transcriptomic patterns in the early secretory phase (ESP) and mid-secretory phase (MSP) of the natural menstrual cycle before in vitro fertilization and embryo transfer (IVF-ET).

METHODS

Thirty patients whose endometrial tissues were obtained from the ESP or MSP of a natural menstrual cycle immediately before IVF-ET were included. Endometrial dating was histologically confirmed as ESP (cycle days 16-18) or MSP (cycle days 19-21), according to the noyes criteria. The patients were divided into two groups depending on the IVF-ET outcome: pregnant (n=14; 7 in ESP and 7 in MSP) or non-pregnant (n=16; 8 in ESP and 8 in MSP). Differentially expressed genes (DEGs) in the MSP, compared to the ESP, were identified using NanoString nCounter (NanoString Technologies, Seattle, WA, USA) data for both the pregnant and non-pregnant groups.

RESULTS

Thirteen DEGs in the pregnant group and 11 DEGs in the non-pregnant group were identified in the MSP compared to those in the ESP. In both groups, adrenoceptor alpha 2A, interleukin 1 receptor-associated kinase 2, a disintegrin and metalloproteinase with thrombospondin repeats 15 (ADAMTS15), serpin family E member 1, integrin subunit beta 3, transmembrane protein 252 (TMEM252), huntingtin associated protein 1, C2 calcium-dependent domain containing 4A, and integrin subunit alpha 2 were upregulated in the MSP, compared to the ESP. TMEM37, galactosidase beta 1 like 2, Rho family GTPase 3, and cytochrome P450 family 24 subfamily A member 1 were upregulated in the MSP only in the pregnant group. ADAMTS8 was downregulated and monoamine oxidase A was upregulated in the MSP only in the non-pregnant group.

CONCLUSION

Transcriptomic patterns in the endometrium immediately before IVF-ET appear to differ according to the IVF-ET outcome. These novel DEGs, which have not been previously studied, may have functional significance during the window of implantation and serve as potential biomarkers of endometrial receptivity.

Constructing a cancer stem cell related prognostic model for predicting immune landscape and drug sensitivity in colorectal cancer

Background: Colorectal cancer (CRC) ranks the second malignancy with high incidence and mortality worldwide. Cancer stem cells (CSCs) function critically in cancer progression and metastasis via the interplay with immune cells in tumor microenvironment. This study aimed to identify important CSC marker genes and parsed the role of these marker genes in CRC. Materials and methods: CRC samples' single-cell RNA sequencing data and bulk transcriptome data were utilized. Seurat R package annotated CSCs and identified CSC marker genes. Consensus clustering subtyped CRC samples based on CSC marker genes. Immune microenvironment, pathway and oxidative stress analysis was performed using ESTIMATE, MCP-counter analysis and ssGSEA analysis. A prognostic model was established by Lasso and stepAIC. Sensitivity to chemotherapeutic drugs was determined by the biochemical half maximal inhibitory concentration with pRRophetic R package. Results: We identified a total of 29 CSC marker genes related to disease-specific survival (DSS). Two clusters (CSC1 and CSC2) were determined, and CSC2 showed shorter DSS, a larger proportion of late-stage samples, and higher oxidative stress response. Two clusters exhibited differential activation of biological pathways associated with immune response and oncogenic signaling. Drug sensitivity analysis showed that 44 chemotherapy drugs were more sensitive to CSC2 that those in CSC1. We constructed a seven-gene prognostic model (DRD4, DPP7, UCN, INHBA, SFTA2, SYNPO2, and NXPH4) that was effectively to distinguish high-risk and low-risk patients. 14 chemotherapy drugs were more sensitive to high-risk group and 13 chemotherapy drugs were more sensitive to low-risk group. Combination of higher oxidative stress and risk score indicated dismal prognosis. Conclusion: The CSC marker genes we identified may help to further decipher the role of CSCs in CRC development and progression. The seven-gene prognostic model could serve as an indicator for predicting the response to immunotherapy and chemotherapy as well as prognosis of CRC patients.

Regularized survival learning and cross-database analysis enabled identification of colorectal cancer prognosis-related immune genes

Colon adenocarcinoma is the most common type of colorectal cancer. The prognosis of advanced colorectal cancer patients who received treatment is still very poor. Therefore, identifying new biomarkers for prognosis prediction has important significance for improving treatment strategies. However, the power of biomarker analyses was limited by the used sample size of individual database. In this study, we combined Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases to expand the number of healthy tissue samples. We screened differentially expressed genes between the GTEx healthy samples and TCGA tumor samples. Subsequently, we applied least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis to identify nine prognosis-related immune genes: ANGPTL4, IDO1, NOX1, CXCL3, LTB4R, IL1RL2, CD72, NOS2, and NUDT6. We computed the risk scores of samples based on the expression levels of these genes and divided patients into high- and low-risk groups according to this risk score. Survival analysis results showed a significant difference in survival rate between the two risk groups. The high-risk group had a significantly lower overall survival rate and poorer prognosis. We found the receiver operating characteristic based on the risk score was showed to accurately predict patients' prognosis. These prognosis-related immune genes may be potential biomarkers for colorectal cancer diagnosis and treatment. Our open-source code is freely available from GitHub at https://github.com/gutmicrobes/Prognosis-model.git.

Novel six-gene prognostic signature based on colon adenocarcinoma immune-related genes

Background

Colon adenocarcinoma (COAD) is one of the most common gastrointestinal tumors worldwide, and immunotherapy is one of the most promising treatments for it. Identifying immune genes involved in the development and maintenance of cancer is key to the use of tumor immunotherapy. This study aimed to determine the prognostic value of immune genes in patients with COAD and to establish an immune-related gene signature. Differentially expressed genes, immune-related genes (DEIGs), and transcription factors (DETFs) were screened using the following databases: Cistrome, The Cancer Genome Atlas (TCGA), the Immunology Database and Analysis Portal, and InnateDB. We constructed a network showing the regulation of DEIGs by DETFs. Using weighted gene co-expression network analysis, we prepared 5 co-expressed gene modules; 6 hub genes (CD1A, CD1B, FGF9, GRP, SERPINE1, and F2RL2) obtained using univariate and multivariate regression analysis were used to construct a risk model. Patients from TCGA database were divided into high- and low-risk groups based on whether their risk score was greater or less than the mean; the public dataset GSE40967, which contains gene expression profiles of 566 colon cancer patients, was used for validation.

Results

Survival analysis, somatic gene mutations, and tumor-infiltrating immune cells differed significantly between the high- and low-risk groups.

Conclusions

This immune-related gene signature could play an important role in guiding treatment, making prognoses, and potentially developing future clinical applications.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04909-2.

Transcriptomic and immunologic implications of the epithelial–mesenchymal transition model reveal a novel role of SFTA2 in prognosis of non-small-cell lung carcinoma

Non-small-cell lung cancer (NSCLC) is the second most common cancer worldwide, and most deaths are associated with epithelial–mesenchymal transition (EMT). Therefore, this study aimed to explore the role of EMT-related transcriptomic profiles in NSCLC and the effect of EMT-based signatures on clinical diagnosis, prognosis, and treatment responses for patients with NSCLC. After integrating the transcriptomics and clinicopathological data, we first constructed EMT clusters (C1 and C2) using machine learning algorithms, found the significant relationship between EMT clusters and survival outcomes, and then explored the impact of EMT clusters on the tumor heterogeneity, drug efficiency, and immune microenvironment of NSCLC. Prominently, differential-enriched tumor-infiltrated lymphocytes were found between EMT clusters, especially the macrophages and monocyte. Next, we identified the most significantly down-regulated gene SFTA2 in the EMT clusters C2 with poor prognosis. Using RT-qPCR and RNA-seq data from the public database, we found prominently elevated SFTA2 expression in NSCLC tissues compared with normal lung tissues, and the tumor suppressor role of SFTA2 in 82 Chinese patients with NSCLC. After Cox regression and survival analysis, we demonstrated that higher SFTA2 expression in tumor samples significantly predicts favorable prognosis of NSCLC based on multiple independent cohorts. In addition, the prognostic value of SFTA2 expression differs for patients with lung adenocarcinoma and squamous cell carcinoma. In conclusion, this study demonstrated that the EMT process is involved in the malignant progression and the constructed EMT clusters exerted significant predictive drug resistance and prognostic value for NSCLC patients. In addition, we first identified the high tumoral expression of SFTA2 correlated with better prognosis and could serve as a predictive biomarker for outcomes and treatment response of NSCLC patients.

Exploring immune-related signatures for predicting immunotherapeutic responsiveness, prognosis, and diagnosis of patients with colon cancer

The present study focused on identifying the immune-related signatures and exploring their performance in predicting the prognosis, immunotherapeutic responsiveness, and diagnosis of patients with colon cancer. Firstly, the immunotherapeutic response-related differential expressed genes (DEGs) were identified by comparing responders and non-responders from an anti-PD-L1 cohort using the edgeR R package. Then, the immunotherapeutic response related DEGs was intersected with immune-related genes (IRGs) to obtain the immunotherapeutic response and immune-related genes (IRIGs). Then, an immunotherapeutic response and immune-related risk score (IRIRScore) model consisting of 6 IRIGs was constructed using the univariable Cox regression analysis and multivariate Cox regression analysis based on the COAD cohort from the cancer genome atlas (TCGA) database, which was further validated in two independent gene expression omnibus database (GEO) datasets (GSE39582 and GSE17536) and anti-PD-L1 cohort. A nomogram with good accuracy was established based on the immune-related signatures and clinical factors (C-index = 0.75). In the training dataset and GSE39582, higher IRIRScore was significantly associated with higher TMN and advanced pathological stages. Based on the anti-PD-L1 cohort, patients who were sensitive to immunotherapy had significantly lower risk score than non-responders. Furthermore, we explored the immunotherapy-related signatures based on the training dataset. Kaplan-Meier curve revealed a high level of T cells regulatory (Tregs) was significantly related to poor overall survival (OS), while a high level of T cells CD4 memory resting was significantly related to better OS. Besides, the TMB value of patients in the high-risk group was significantly higher than those in a low-risk group. Moreover, patients in the high-risk group had significantly higher expression levels of immune checkpoint inhibitors. In addition, the immune-related signatures were applied to establish prediction models using the random forest algorithm. Among them, TDGF1 and NRG1 revealed excellent diagnostic predictive performance (AUC >0.8). In conclusion, the current findings provide new insights into immune-related immunotherapeutic responsiveness, prognosis, and diagnosis of colon cancer.

MiR-17-5p Targets and Downregulates CADM2, Activating the Malignant Phenotypes of Colon Cancer Cells

Accumulating studies have demonstrated that CADM2 modulated malignant phenotype of various cancer cells, while its regulatory function and mechanism have not yet been reported. In this study, qRT-PCR was utilized to measure CADM2 mRNA level in normal cells and colon cancer cells, also, IHC and WB were applied to detect CADM2 protein expression in colon tissues, exhibiting low mRNA and protein levels of CADM2 in colon cancer. Applying cell function experiments, the impacts of CADM2 on colon cell phenotypes were examined, and the results illustrated that upregulating CADM2 remarkably repressed proliferation, invasion, migration, cell cycle of colon cancer cells, and facilitated cell apoptosis. Thus, it could be considered that CADM2 served as a tumor repressor gene in colon cancer. Moreover, the outcomes of dual-luciferase assay displayed that miR-17-5p could target CADM2, and overexpressing miR-17-5p could notably inhibit the mRNA and protein expression levels of CADM2. We, therefore, assumed that CADM2 was a downstream target of miR-139-5p. qRT-PCR was conducted to assess miR-17-5p level in colon cancer cells and normal cells, verifying a high miR-17-5p expression in the cancer cells. The effects of miR-17-5p on colon cell phenotypes were examined as well, where we determined that miR-17-5p served as a tumor-promoting factor. Finally, the rescue experiments exhibited that miR-17-5p could activate tumor-promoting phenotypes, while such activating effects could be reversed by upregulating CADM2. In short, the study proved that miR-17-5p facilitated malignant progression of colon cancer through targeting CADM2 at a post-transcriptional level. Our findings offer new insight into molecular therapy of colon cancer patients.

Identification of a novel immune signature for optimizing prognosis and treatment prediction in colorectal cancer

BACKGROUND

Globally, colorectal cancer (CRC) is one of the most lethal malignant diseases. However, the currently approved therapeutic options for CRC failed to acquire satisfactory treatment efficacy. Tailoring therapeutic strategies for CRC individuals can provide new insights into personalized prediction approaches and thus maximize clinical benefits.

METHODS

In this study, a multi-step process was used to construct an immune-related genes (IRGs) based signature leveraging the expression profiles and clinical characteristics of CRC from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. An integrated immunogenomic analysis was performed to determine the association between IRGs with prognostic significance and cancer genotypes in the tumor immune microenvironment (TIME). Moreover, we performed a comprehensive in silico therapeutics screening to identify agents with subclass-specific efficacy.

RESULTS

The established signature was shown to be a promising biomarker for evaluating clinical outcomes in CRC. The immune risk score as calculated by this classifier was significantly correlated with over-riding malignant phenotypes and immunophenotypes. Further analyses demonstrated that CRCs with low immune risk scores achieved better therapeutic benefits from immunotherapy, while AZD4547, Cytochalasin B and S-crizotinib might have potential therapeutic implications in the immune risk score-high CRCs.

CONCLUSIONS

Overall, this IRGs-based signature not only afforded a useful tool for determining the prognosis and evaluating the TIME features of CRCs, but also shed new light on tailoring CRCs with precise treatment.

Comprehensive Analysis of Glycolysis-Related Genes for Prognosis, Immune Features, and Candidate Drug Development in Colon Cancer

The dysregulated expression of glycolysis-related genes (GRGs) is closely related to the occurrence of diverse tumors and regarded as a novel target of tumor therapy. However, the role of GRGs in colon cancer is unclear. We obtained 226 differential GRGs (DE-GRGs) from The Cancer Genome Atlas (TCGA) database. Cox regression analysis was used to construct a DE-GRG prognostic model, including P4HA1, PMM2, PGM2, PPARGC1A, PPP2CB, STC2, ENO3, and CHPF2. The model could accurately predict the overall survival rate of TCGA and GSE17536 patient cohorts. The risk score of the model was closely related to a variety of clinical traits and was an independent risk factor for prognosis. Enrichment analysis revealed the activation of a variety of glycolysis metabolism and immune-related signaling pathways in the high-risk group. High-risk patients displayed low expression of CD4+ memory resting T cells and resting dendritic cells and high expression of macrophages M0 compared with the expression levels in the low-risk patients. Furthermore, patients in the high-risk group had a higher tumor mutation load and tumor stem cell index and were less sensitive to a variety of chemotherapeutic drugs. Quantitative reverse transcription polymerase chain reaction and immunohistochemistry analyses validated the expression of eight GRGs in 43 paired clinical samples. This is the first multi-omics study on the GRGs of colon cancer. The establishment of the risk model may benefit the prognosis and drug treatment of patients.

miRNA Profile and Bioinformatic Analysis for Diagnosis in Patients with Stage IIIA Colon Cancer

Early diagnosis is a critical factor in deciding the outcome of colon cancer, as is the case with other types of cancers. Recent scientific developments have enabled the use of biomarkers for diagnosis and for designing treatment strategies for various cancer types. Further, identification of potential targets of these biomarkers will facilitate a better understanding of molecular processes. The aim of this study is to analyze microRNA expression profile, and through bioinformatic analyses determine the cellular processes of potential target genes and understand their molecular mechanism in stage IIIA colon cancer patients. The microRNA expression profiles of both normal and tumor tissues of seven patients were analyzed using the Affymetrix microarray system. The target genes were identified by performing a KEGG pathway analysis on eight miRNAs (hsa-miR-362-3p, hsa-miR-34c-5p, hsa-miR-34c-3p, hsa-miR-34a-3p, hsa-miR-19b-1-3p, hsa-miR-371a-5p, hsa-miR-941 ad hsa-miR-7-5p), which were selected through an array scan by using DIANA-miRPath v.3 bioinformatic analysis tool. Biological pathway and cellular component analyses were performed on 30 genes targeted by miRNAs using FunRich Gene Enrichment tool. These analyses indicated that the genes targeted by these eight miRNAs played a role in either cell communication (53%), signal transduction (60%) or apoptosis (20%) in stage IIIA colon cancer. Taken together, these data suggest that these miRNAs can be used as biomarkers in Stage IIIA colon cancer.

Investigation and verification of the clinical significance and perspective of natural killer group 2 member D ligands in colon adenocarcinoma

This study investigated and verified the diagnostic and prognostic values of natural killer group 2 member D ligand (NKG2DL) genes in colon adenocarcinoma (COAD). We downloaded NKG2DLs expression data and corresponding clinical parameters from The Cancer Genome Atlas (TCGA) and used bioinformatics techniques to investigate the values of NKG2DLs in COAD. Then, we used the GSE40967 cohort to verify the prognostic value of NKG2DLs. Finally, we verified the ULBP2 expression level in tissues, and also investigated the diagnostic and prognostic values of ULBP2 in COAD. The diagnostic receiver operating characteristic curves showed that ULBP1, ULBP2, ULBP3, and RAET1L had high diagnostic values in COAD [Area Under Curve (AUC) > 0.9]. In TCGA cohort, the univariate and multivariate survival analyses suggested that ULBP2 was correlated with the prognosis of COAD recurrence-free survival (RFS) and overall survival (OS). In GSE40967 cohort, ULBP2 was associated with CC RFS and OS. Reverse transcription-quantitative polymerase chain reaction and immunohistochemistry results showed that ULBP2 was highly expressed in COAD tumor tissues (P < 0.05) and both had diagnostic values (AUC > 0.7). Validated survival analysis showed that the high expression of ULBP2 had a worse prognosis in COAD OS and RFS. Thus, ULBP2 might be an independent diagnostic and prognostic biomarker of COAD.

Identification of novel hub genes and lncRNAs related to the prognosis and progression of pancreatic cancer by microarray and integrated bioinformatics analysis

BACKGROUND

Pancreatic cancer (PC) is one of the most invasive and metastatic neoplasms among the fatal malignancies of the digestive system. Abnormal expression of genes and long non-coding RNAs (lncRNAs) are reportedly linked to multiple cancers. However, the lncRNA-mRNA expression profiles and their molecular mechanisms in PC progression are poorly known. This study aimed to map the hub genes and lncRNAs which might play core roles in the development of PC.

METHODS

This study used microarray expression analysis to screen for both differentially expressed genes (DEGs) and differentially expressed lncRNAs (DElncRNAs) between PC and matched adjacent non-tumor (AN) tissues. In order to clarify the functional classification of DEGs, we conducted GO and KEGG pathway enrichment analyses via the Enrichr database. LncRNA-mRNA co-expressed networks were also constructed to explore the probable core regulating DEGs and DElncRNAs. Subsequently, the hub genes and lncRNAs were validated via the ONCOMINE and GEPIA databases and the co-expressed networks.

RESULTS

By analyzing an mRNA-lncRNA microarray, we identified 943 mRNAs and 1,138 lncRNAs differentially expressed in PC tumors compared with the matched AN tissues. GO analysis confirmed that both up-regulated and down-regulated DEGs were enriched in multiple terms. The KEGG pathways enrichment analyses revealed that DEGs were mostly enriched in the focal adhesion and glutathione metabolism pathways, amongst others. Co-expressed networks were established to reveal the differential interactions between DEGs and DElncRNAs, and to indicate the core regulatory factors located at the core nodes of the co-expressed networks. The expression levels of potential core-regulating DEGs were validated by the GEPIA and ONCOMINE databases, and the relationship between overall survival and tumor stage and the potential core-regulating DEGs was analyzed using the GEPIA database. As a result, five genes and sixteen lncRNAs were finally considered as the hub transcripts in PC.

CONCLUSIONS

This study identified DEGs and DElncRNAs between PC tumors and matched AN tissues, and these transcripts were connected with malignant phenotypes in PC through different BPs and signaling pathways. Furthermore, five hub genes and sixteen lncRNAs were identified, which are expected to represent candidate diagnostic biomarkers or potential therapeutic targets for PC.

SHP-2 Interacts with CD81 and Regulates the Malignant Evolution of Colorectal Cancer by Inhibiting Epithelial-Mesenchymal Transition

PURPOSE

Colon cancer is a common malignant tumor of the digestive system. This project verified the negative role of protein tyrosine phosphatase (SHP-2) in the regulation of colon cancer and further clarified the key targets and molecular mechanisms in the regulation process.

PATIENTS AND METHODS

The expression levels of SHP-2 in colon cancer tissues, adjacent tissues, normal colon cell lines, and cancer cell lines were detected via Quantitative Real-time PCR (qRT-PCR). The effect of SHP-2 on colon cancer cell function was verified using cell proliferation, Transwell, scratch, and apoptotic assays. CD81 was identified as the interaction protein of SHP-2 by immunoprecipitation.

RESULTS

The expression of SHP-2 was decreased in colorectal cancer compared with that in adjacent tissues. This expression was also decreased in colon cancer cells compared with that in intestinal epithelial cells. In addition, the tumor tissues of patients with metastatic colon cancer exhibited downregulated expression of SHP-2 compared with those of patients with non-metastatic colon cancer. Cell proliferation, Transwell, scratch, and apoptotic assay showed that the overexpression of SHP-2 inhibited proliferation, adhesion, and metastasis of colon cancer cell lines and promoted apoptosis. CO-IP proved that SHP-2 could interact with CD81 and inhibit the function of CD81. Recovery experiments confirmed that the overexpression of CD81 reversed the anti-cancer effect of SHP-2.

CONCLUSION

Overexpression of SHP-2 inhibited malignant progression of colon cancer. Mechanism experiments showed that the anti-cancer effect of SHP-2 was realized through the interaction with CD81. This study elucidated the molecular mechanism of SHP-2 regulation in colon cancer and provided guidance for the diagnosis and prognosis assessment of colon cancer.

The Neuropeptide System and Colorectal Cancer Liver Metastases: Mechanisms and Management

Colorectal cancer (CRC), classified as the third most prevalent cancer worldwide, remains to be a clinical and research challenge. It is estimated that ~50% of CRC patients die from distant metastases, with treatment of this complication still posing significant difficulties. While liver metastasis (LM) cascade is known in the literature, its mechanisms are still unclear and remain studied in different research models. A connection is suggested between nervous system dysfunctions and a range of Neurotransmitters (Nts) (including Neuropeptides, NPs), Neurotrophins (Ntt) and their receptors (Rs) in CRC liver metastasis development. Studies on the role of NP/NP-Rs in the progression and metastasis of CRC, show the complexity of brain–tumor interactions, caused by their different forms of release to the extracellular environment (endocrine, autocrine, paracrine and neurocrine). Many stages of LM are connected to the activity of pro-inflammatory, e.g., Corticotropin-releasing Hormone Receptor 1 (CRHR1), Neuropeptide Y (NPY) and Neurotensin (NT), anti-inflammatory, e.g., Calcitonin Gene-related Peptide (CGRP), CRHR2 and Vasoactive Intestinal Polypeptide (VIP) or dual role neuropeptides, e.g., Substance P (SP). The regulation of the local immunological profile (e.g., CRH/CRHRs), dysfunctions of enteroprotective role of NPs on epithelial cells (e.g., NT/NT-R), as well as structural-functional changes in enteric nervous system innervation of the tumor are also important. More research is needed to understand the exact mechanisms of communication between the neurons and tumor cells. The knowledge on the mechanisms regulating tumor growth and different stages of metastasis, as well as effects of the action of a numerous group of Nts/NPs/Ntt as growth factors, have implications for future therapeutic strategies. To obtain the best treatment outcomes, it is important to use signaling pathways common for many NPs, as well to develop a range of broad-spectrum antagonists. This review aims to summarize the current knowledge on the importance of neuroactive molecules in the promotion of the invasion-metastasis cascade in CRC, as well as the improvements of clinical management of CRC liver metastasis.

The Neuropeptide System and Colorectal Cancer Liver Metastases: Mechanisms and Management

Colorectal cancer (CRC), classified as the third most prevalent cancer worldwide, remains to be a clinical and research challenge. It is estimated that ~50% of CRC patients die from distant metastases, with treatment of this complication still posing significant difficulties. While liver metastasis (LM) cascade is known in the literature, its mechanisms are still unclear and remain studied in different research models. A connection is suggested between nervous system dysfunctions and a range of Neurotransmitters (Nts) (including Neuropeptides, NPs), Neurotrophins (Ntt) and their receptors (Rs) in CRC liver metastasis development. Studies on the role of NP/NP-Rs in the progression and metastasis of CRC, show the complexity of brain–tumor interactions, caused by their different forms of release to the extracellular environment (endocrine, autocrine, paracrine and neurocrine). Many stages of LM are connected to the activity of pro-inflammatory, e.g., Corticotropin-releasing Hormone Receptor 1 (CRHR1), Neuropeptide Y (NPY) and Neurotensin (NT), anti-inflammatory, e.g., Calcitonin Gene-related Peptide (CGRP), CRHR2 and Vasoactive Intestinal Polypeptide (VIP) or dual role neuropeptides, e.g., Substance P (SP). The regulation of the local immunological profile (e.g., CRH/CRHRs), dysfunctions of enteroprotective role of NPs on epithelial cells (e.g., NT/NT-R), as well as structural-functional changes in enteric nervous system innervation of the tumor are also important. More research is needed to understand the exact mechanisms of communication between the neurons and tumor cells. The knowledge on the mechanisms regulating tumor growth and different stages of metastasis, as well as effects of the action of a numerous group of Nts/NPs/Ntt as growth factors, have implications for future therapeutic strategies. To obtain the best treatment outcomes, it is important to use signaling pathways common for many NPs, as well to develop a range of broad-spectrum antagonists. This review aims to summarize the current knowledge on the importance of neuroactive molecules in the promotion of the invasion-metastasis cascade in CRC, as well as the improvements of clinical management of CRC liver metastasis.

Clinicopathological Features of Programmed Cell Death-ligand 1 Expression in Patients with Oral Squamous Cell Carcinoma

Objective

Programmed cell death-ligand 1 (PD-L1) expression has been shown to play important roles in various types of cancer. However, the role of PD-L1 expression has not been conclusively reported in patients with oral squamous cell carcinoma (OSCC). Accordingly, in this meta-analysis, we investigated the clinicopathological value of PD-L1 expression in patients with OSCC.

Methods

Google Scholar, PubMed, EMBASE, and CNKI databases were searched to find relevant studies published through to September 16, 2019. The relationships between PD-L1 expression in patients with OSCC and clinicopathological features were assessed using risk ratio (RR) and 95% confidence intervals (CIs).

Results

Sixteen studies including 1989 participants were included. The results indicated that high PD-L1 expression was correlated with sex (RR = 1.28, 95% CI: 1.16-1.42, P < 0.001), N stage (RR = 1.19, 95% CI: 1.06-1.33, P = 0.003), M stage (RR = 1.64, 95% CI: 1.01-2.66, P = 0.044), low differentiation (RR = 1.16, 95% CI: 1.01-1.33, P = 0.034), and human papilloma virus infection (RR = 1.38, 95% CI: 1.14-1.68, P = 0.001), but unrelated to TNM stage or T stage. There was no significant publication bias in the studies included in this analysis.

Conclusions

This meta-analysis revealed that high PD-L1 expression in patients with OSCC was correlated with clinicopathological features. Further large-scale studies are necessary to confirm our results.

Identification of Hub Genes Related to Carcinogenesis and Prognosis in Colorectal Cancer Based on Integrated Bioinformatics

The high mortality of colorectal cancer (CRC) patients and the limitations of conventional tumor-node-metastasis (TNM) stage emphasized the necessity of exploring hub genes closely related to carcinogenesis and prognosis in CRC. The study is aimed at identifying hub genes associated with carcinogenesis and prognosis for CRC. We identified and validated 212 differentially expressed genes (DEGs) from six Gene Expression Omnibus (GEO) datasets and the Cancer Genome Atlas (TCGA) database. We investigated functional enrichment analysis for DEGs. The protein-protein interaction (PPI) network was constructed, and hub modules and genes in CRC carcinogenesis were extracted. A prognostic signature was developed and validated based on Cox proportional hazards regression analysis. The DEGs mainly regulated biological processes covering response to stimulus, metabolic process, and affected molecular functions containing protein binding and catalytic activity. The DEGs played important roles in CRC-related pathways involving in preneoplastic lesions, carcinogenesis, metastasis, and poor prognosis. Hub genes closely related to CRC carcinogenesis were extracted including six genes in model 1 (CXCL1, CXCL3, CXCL8, CXCL11, NMU, and PPBP) and two genes and Metallothioneins (MTs) in model 2 (SLC26A3 and SLC30A10). Among them, CXCL8 was also related to prognosis. An eight-gene signature was proposed comprising AMH, WBSCR28, SFTA2, MYH2, POU4F1, SIX4, PGPEP1L, and PAX5. The study identified hub genes in CRC carcinogenesis and proposed an eight-gene signature with good reproducibility and robustness at the molecular level for CRC, which might provide directive significance for treatment selection and survival prediction.

Alpha-1-acid glycoprotein 1 is upregulated in pancreatic ductal adenocarcinoma and confers a poor prognosis

Pancreatic cancer is an aggressive malignancy that carries a high mortality rate. A major contributor to the poor outcome is the lack of effective molecular markers. The purpose of this study was to develop protein markers for improved prognostication and noninvasive diagnosis. A mass spectrometry (MS)-based discovery approach was applied to pancreatic cancer tissues and healthy pancreas. In the verification phase, extracellular proteins with differential expression were further quantified in targeted mode using parallel reaction monitoring (PRM). Next, a tissue microarray (TMA) cohort including 140 pancreatic cancer resection specimens was constructed, in order to validate protein expression status and investigate potential prognostic implications. The levels of protein candidates were finally assessed in a prospective series of 110 serum samples in an accredited clinical laboratory using the automated Cobas system. Protein sequencing with nanoliquid chromatography tandem MS (nano-LC-MS/MS) and targeted PRM identified alpha-1-acid glycoprotein 1 (AGP1) as an upregulated protein in pancreatic cancer tissue. Using TMA and immunohistochemistry, AGP1 expression was significantly associated with shorter overall survival (HR = 2.22; 95% CI 1.30-3.79, P =  0.004). Multivariable analysis confirmed the results (HR = 1.87; 95% CI 1.08-3.24, P  =  0.026). Circulating levels of AGP1 yielded an area under the curve (AUC) of 0.837 for the discrimination of resectable pancreatic cancer from healthy controls. Combining AGP1 with CA 19-9 enhanced the diagnostic performance, with an AUC of 0.963. This study suggests that AGP1 is a novel prognostic biomarker in pancreatic cancer tissue. Serum AGP1 levels may be useful as part of a biomarker panel for early detection of pancreatic cancer but further studies are needed.

Neurexophilin and PC-esterase domain family member 4 (NXPE4) and prostate androgen-regulated mucin-like protein 1 (PARM1) as prognostic biomarkers for colorectal cancer

Owing to the high morbidity and mortality, novel biomarkers in the occurrence and development of colorectal cancer (CRC) are needed nowadays. In this study, the CRC-related datasets were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. After screening the differentially expressed genes (DEGs) in R software, a total of 238 upregulated and 199 downregulated DEGs were revealed simultaneously. Then the Kaplan-Meier survival analysis and Cox regression analysis were used to reveal the prognostic function of these DEGs. Neurexophilin and PC-esterase domain family member 4 (NXPE4) and prostate androgen-regulated mucin-like protein 1 (PARM1) were two outstanding independent overall survival (OS) and relapse-free survival (RFS) prognostic genes of CRC in TCGA database. We next verified the expression of NXPE4 and PARM1 messenger RNA (mRNA) levels were significantly lower in CRC tumor tissue than in the adjacent noncancerous tissue in our clinical samples, and NXPE4 mRNA expression level was related to the tumor location and tumor size, while PARM1 was related to tumor location, lymph nodes metastasis, and tumor size. This study demonstrated that NXPE4 and PARM1 might be two potential novel prognostic biomarkers for CRC.

TULP3: A potential biomarker in colorectal cancer?

Colorectal cancer (CRC) is the second most common cancer in women and the third most common cancer in men globally. The identification of differentially expressed genes associated to patient's clinical data may represent a useful approach to find important genes in CRC carcinogenesis. Previously, the TULP3 transcription factor was identified as a possible prognostic biomarker in pancreatic ductal adenocarcinoma. Considering that pancreatic and colorectal tissues have the same embryonic origin, we investigated the profile of TULP3 expression in CRC hypothesizing that it may have a role in its development. We comparatively analysed TULP3 gene expression in CRC and normal adjacent colonic tissue and assessed association of expression profiles with survival and clinicopathological information, using publicly available datasets. TULP3 expression levels were increased in CRC when compared to the adjacent non-tumoral tissue. In addition, higher TULP3 gene expression was associated to lymphatic and vascular invasion in colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ), respectively. In summary, our results point to a possible role of TULP3 as a diagnostic and prognostic biomarker in CRC. Additional studies are necessary to confirm these preliminary findings.

Forkhead box O3 promotes colon cancer proliferation and drug resistance by activating MDR1 expression

BACKGROUND

Globally, colon cancer (CC) is the third reason of tumor-related deaths. Previous reports indicate that Forkhead box O3 (FOXO3) is involved in the development of various tumors and may have different effects depending upon the types of tumors. Hence, this study was to examine the effects of FOXO3 on CC cells and uncover the possible mechanisms.

METHODS

MTT and cell count assay were applied to analyze the viability of transfected CC cells. rVista, dual luciferase reporter assay, and chromatin immunoprecipitation assay were used to identify the downstream target of FOXO3 in HCT116 cells. The mRNA and protein abundance of FOXO3 and MDR1 were determined by quantitative PCR and Western blot, respectively.

RESULTS

Forkhead box O3 stimulated the proliferation of both HCT116 and DLD1 cells. Moreover, FOXO3 overexpression inhibited doxorubicin sensitivity of HCT116 cells, while the knockout of FOXO3 by FOXO3 shRNA restored the doxorubicin sensitivity in doxorubicin-resistant HCT116 DR cells. Next, we found that FOXO3 directly bound to the promoter of MDR1 and enhanced MDR1 expression in HCT116 cells. MDR1 overexpression enhanced the viability and doxorubicin resistance of CC cells. Besides, MDR1 overexpression plasmid significantly abrogated the decrease in cell proliferation and resistance of HCT116 cells to doxorubicin caused by FOXO3 knockout.

CONCLUSION

Forkhead box O3 exhibited promotive effects on the proliferation and doxorubicin resistance in CC cells via targeting MDR1.

Identification of a 6-gene signature predicting prognosis for colorectal cancer

BACKGROUND

An accurate and robust gene signature is of the utmost importance in assisting oncologists to make a more accurate evaluation in clinical practice. In our study, we extracted key mRNAs significantly related to colorectal cancer (CRC) prognosis and we constructed an expression-based gene signature to predict CRC patients' survival.

METHODS

mRNA expression profiles and clinicopathological data of colon adenocarcinoma (COAD) cases and rectum adenocarcinoma (READ) were collected from The Cancer Genome Atlas database to investigate gene expression alteration associated to the prognosis of CRC. Differentially expressed mRNAs (DEMs) were detected between COAD/READ and normal tissue samples. Relying on a univariate and multivariate Cox regression analyses, a mRNA panel signature was established and used for predicting the overall survival (OS) in CRC patients. Receiver operating characteristic curve was used to evaluate the prognosis performance of our model through calculating the AUC values corresponding to the 3-year and 5-year survival. To assess the performance of gene signature in the given cancer subgroups (CRC entire cohort, COAD cohort, and READ cohort), a stratified analysis was carried out according to clinical factors.

RESULTS

A total of 5341 and 5594 DEMs were collected from COAD vs. normal tissue samples, and READ vs. normal samples respectively. A univariate regression analysis for the common DEMs between COAD and READ cohorts resulted in 14 common mRNAs related to OS. The multivariate Cox regression analysis revealed that 6 of these mRNAs (EPHA6, TIMP1, IRX6, ART5, HIST3H2BB, and FOXD1) had significant prognostic value allowing the discrimination between high- and low-risk patients, implying poor and good outcomes, respectively. The stratified analysis identified 6-gene signature as an independent prognostic signature in predicting CRC patients' survival.

CONCLUSIONS

The 6-gene signature could act as an independent biomarker for survival prediction of CRC patients.