lncRNA/miR-29c-Mediated High Expression of LOX Can Influence the Immune Status and Chemosensitivity and Can Forecast the Poor Prognosis of Gastric Cancer

Long Non-Coding RNAs in Drug Resistance of Gastric Cancer: Complex Mechanisms and Potential Clinical Applications

Gastric cancer (GC) ranks as the third most prevalent malignancy and a leading cause of cancer-related mortality worldwide. However, the majority of patients with GC are diagnosed at an advanced stage, highlighting the urgent need for effective perioperative and postoperative chemotherapy to prevent relapse and metastasis. The current treatment strategies have limited overall efficacy because of intrinsic or acquired drug resistance. Recent evidence suggests that dysregulated long non-coding RNAs (lncRNAs) play a significant role in mediating drug resistance in GC. Therefore, there is an imperative to explore novel molecular mechanisms underlying drug resistance in order to overcome this challenging issue. With advancements in deep transcriptome sequencing technology, lncRNAs-once considered transcriptional noise-have garnered widespread attention as potential regulators of carcinogenesis, including tumor cell proliferation, metastasis, and sensitivity to chemo- or radiotherapy through multiple regulatory mechanisms. In light of these findings, we aim to review the mechanisms by which lncRNAs contribute to drug therapy resistance in GC with the goal of providing new insights and breakthroughs toward overcoming this formidable obstacle.

Identification of differentially expressed mRNAs as novel predictive biomarkers for gastric cancer diagnosis and prognosis

BACKGROUND

Gastric cancer (GC) has a high mortality rate worldwide. Despite significant progress in GC diagnosis and treatment, the prognosis for affected patients still remains unfavorable.

AIM

To identify important candidate genes related to the development of GC and identify potential pathogenic mechanisms through comprehensive bioinformatics analysis.

METHODS

The Gene Expression Omnibus database was used to obtain the GSE183136 dataset, which includes a total of 135 GC samples. The limma package in R software was employed to identify differentially expressed genes (DEGs). Thereafter, enrichment analyses of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed for the gene modules using the clusterProfile package in R software. The protein-protein interaction (PPI) networks of target genes were constructed using STRING and visualized by Cytoscape software. The common hub genes that emerged in the cohort of DEGs that was retrieved from the GEPIA database were then screened using a Venn Diagram. The expression levels of these overlapping genes in stomach adenocarcinoma samples and non-tumor samples and their association with prognosis in GC patients were also obtained from the GEPIA database and Kaplan-Meier curves. Moreover, real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting were performed to determine the mRNA and protein levels of glutamic-pyruvic transaminase (GPT) in GC and normal immortalized cell lines. In addition, cell viability, cell cycle distribution, migration and invasion were evaluated by cell counting kit-8, flow cytometry and transwell assays. Furthermore, we also conducted a retrospective analysis on 70 GC patients diagnosed and surgically treated in Wenzhou Central Hospital, Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University between January 2017 to December 2020. The tumor and adjacent normal samples were collected from the patients to determine the potential association between the expression level of GPT and the clinical as well as pathological features of GC patients.

RESULTS

We selected 19214 genes from the GSE183136 dataset, among which there were 250 downregulated genes and 401 upregulated genes in the tumor samples of stage III-IV in comparison to those in tumor samples of stage I-II with a P-value < 0.05. In addition, GO and KEGG results revealed that the various upregulated DEGs were mainly enriched in plasma membrane and neuroactive ligand-receptor interaction, whereas the downregulated DEGs were primarily enriched in cytosol and pancreatic secretion, vascular smooth muscle contraction and biosynthesis of the different cofactors. Furthermore, PPI networks were constructed based on the various upregulated and downregulated genes, and there were a total 15 upregulated and 10 downregulated hub genes. After a comprehensive analysis, several hub genes, including runt-related transcription factor 2 (RUNX2), salmonella pathogenicity island 1 (SPI1), lysyl oxidase (LOX), fibrillin 1 (FBN1) and GPT, displayed prognostic values. Interestingly, it was observed that GPT was downregulated in GC cells and its upregulation could suppress the malignant phenotypes of GC cells. Furthermore, the expression level of GPT was found to be associated with age, lymph node metastasis, pathological staging and distant metastasis (P < 0.05).

CONCLUSION

RUNX2, SPI1, LOX, FBN1 and GPT were identified key hub genes in GC by bioinformatics analysis. GPT was significantly associated with the prognosis of GC, and its upregulation can effectively inhibit the proliferative, migrative and invasive capabilities of GC cells.

Machine learning-based cell death signature for predicting the prognosis and immunotherapy benefit in stomach adenocarcinoma

Stomach adenocarcinoma (STAD) is a one of most common malignancies with high mortality-to-incidence ratio. Programmed cell death (PCD) exerts vital functions in the progression of cancer. The role of PCD-related genes (PRGs) in STAD are not fully clarified. Using TCGA, GSE15459, GSE26253, GSE62254 and GSE84437 datasets, PCD-related signature (PRS) was constructed with an integrative procedure including 10 machine learning methods. The role of PRS in predicting the immunotherapy benefits was evaluated by several predicting score and 3 immunotherapy datasets (GSE91061, GSE78220, and IMvigor210). The model developed by Lasso + CoxBoost algorithm having a highest average C-index of 0.66 was considered as the optimal PRS. As an independent risk factor for STAD patients, PRS had a good performance in predicting the overall survival rate of patients, with an AUC of 1-, 3-, and 5-year ROC curve being 0.771, 0.751 and 0.827 in TCGA cohort. High PRS score demonstrated a lower gene set score of some immune-activated cells and immune-activated activities. Patient with high PRS score had a higher TIDE score, higher immune escape score, lower PD1&CTLA4 immunophenoscore, lower TMB score, lower response rate and poor prognosis, indicating a less immunotherapy response. The IC50 value of some drugs correlated with chemotherapy and targeted therapy was higher in high PRS score group. Our investigation developed an optimal PRS in STAD and it acted as an indicator for predicting the prognosis, stratifying risk and guiding treatment for STAD patients.

CDK12 Promotes the Proliferation, Migration, and Angiogenesis of Gastric Carcinoma via Activating the PI3K/AKT/mTOR Signaling Pathway

Cyclin-dependent kinase 12 (CDK12) has been found to regulate tumor progression. However, its function in gastric carcinoma (GC) remains controversial. This work aimed to explore the exact effect of CDK12 on GC progression. We detected the expression of CDK12 in GC cells and normal gastric mucosal epithelial cells. Then CDK12 function on GC cell proliferation, migration, and angiogenesis was researched by colony formation experiment, Transwell experiment, and angiogenesis assay. Moreover, CDK12 effect on the PI3K/AKT/mTOR pathway activity was explored by western blot. Further, we used LY294002 (10 μM) to treat GC cells to verify whether CDK12 regulates GC progression by activating the PI3K/AKT/mTOR pathway. Additionally, CDK12 effect on the expression of prognostic factors of GC was detected by western blot, including alkaline phosphatase (ALP) and Ki67. Quantitative real-time polymerase chain reaction and western blot were utilized to evaluate the expression of mRNAs and proteins. As a result, CDK12 was upregulated in GC cells. CDK12 overexpression facilitated the proliferation, migration, and angiogenesis of GC cells. However, CDK12 silencing showed an opposite result. CDK12 overexpression activated the PI3K/AKT/mTOR pathway, but CDK12 silencing inactivated it in GC cells. The blockage of the PI3K/AKT/mTOR pathway induced by LY294002 treatment counteracted the promotion of CDK12 on the proliferation, migration, and angiogenesis of GC. Further, CDK12 silencing suppressed the expression of ALP and Ki67 proteins in GC cells. Taken together, CDK12 promotes the proliferation, migration, and angiogenesis of GC by activating the PI3K/AKT/mTOR pathway. It may be a novel target for GC treatment.

LncRNA and its role in gastric cancer immunotherapy

Gastric cancer (GC) is a potential dominant disease in tumor immunotherapy checkpoint inhibitors, and adoptive cell therapy have brought great hope to GC patients. However, only some patients with GC can benefit from immunotherapy, and some patients develop drug resistance. More and more studies have shown that long non-coding RNAs (lncRNAs) may be important in GC immunotherapy's prognosis and drug resistance. Here, we summarize the differential expression of lncRNAs in GC and their impact on the curative effect of GC immunotherapy, discuss potential mechanisms of activity in GC immunotherapy resistance regulated by lncRNAs. This paper reviews the differential expression of lncRNA in GC and its effect on immunotherapy efficacy in GC. In terms of genomic stability, inhibitory immune checkpoint molecular expression, the cross-talk between lncRNA and immune-related characteristics of GC was summarized, including tumor mutation burden (TMB), microsatellite instability (MSI), and Programmed death 1 (PD-1). At the same time, this paper reviewed the mechanism of tumor-induced antigen presentation and upregulation of immunosuppressive factors, as well as the association between Fas system and lncRNA, immune microenvironment (TIME) and lncRNA, and summarized the functional role of lncRNA in tumor immune evasion and immunotherapy resistance.

Lysyl Oxidase Family Proteins: Prospective Therapeutic Targets in Cancer

The lysyl oxidase (LOX) family, consisting of LOX and LOX-like proteins 1–4 (LOXL1–4), is responsible for the covalent crosslinking of collagen and elastin, thus maintaining the stability of the extracellular matrix (ECM) and functioning in maintaining connective tissue function, embryonic development, and wound healing. Recent studies have found the aberrant expression or activity of the LOX family occurs in various types of cancer. It has been proved that the LOX family mainly performs tumor microenvironment (TME) remodeling function and is extensively involved in tumor invasion and metastasis, immunomodulation, proliferation, apoptosis, etc. With relevant translational research in progress, the LOX family is expected to be an effective target for tumor therapy. Here, we review the research progress of the LOX family in tumor progression and therapy to provide novel insights for future exploration of relevant tumor mechanism and new therapeutic targets.

Clinical Significance and Immune Infiltration Analyses of the Cuproptosis-Related Human Copper Proteome in Gastric Cancer

BACKGROUND

The human copper Cu proteome, also termed Cu-binding proteins (CBP), is responsible for transporting "free" Cu to the cell that is related to cuproptosis. However, their role in gastric cancer (GC) has not been reported.

METHODS

RNA expression data of 946 GC patients were collected. A series of machine learning and bioinformatic approaches were combined to build a CBP signature to predict survival and immune microenvironment and guide the priority treatment. Immunohistochemistry and multicolor immunofluorescence (mIF) in 1076 resection slides were used to verify immune features.

RESULTS

A CBP signature was constructed using the machine learning method from TCGA that classifies cases as CBP_low and CBP_high groups. Multivariable Cox analysis confirmed that the CBP signature was an independent prognostic factor in the training and validation cohorts. Additionally, GC patients with low CBPscores showed an increase in anti-tumor immune microenvironment, which was further verified by mIF in pathological resections following immunotherapy. Importantly, patients with low CBPscores had higher levels of TMB/MSI and responded well to immunotherapy.

CONCLUSIONS

We conducted the first and comprehensive CBP analysis of GC patients and established a clinically feasible CBP signature for predicting survival and response to treatment, which will be helpful for guiding personalized medicine.

Identification and validation of roles of lysyl oxidases in the predictions of prognosis, chemotherapy and immunotherapy in glioma

Background: Previous investigations have illustrated that lysyl oxidase family enzymes (LOXs) are contributing factors for tumor progression and remodeling immunomicroenvironment. However, it is scarce regarding comprehensive analysis of LOXs in the predictions of prognosis, chemotherapy and immunotherapy in glioma, the highly invasive brain tumor. Our present work aimed to explore the prognostic value, chemotherapeutic drug sensitivity and immunotherapy according to distinct LOXs expressions in glioma through bioinformatics analysis and experimental verification.

Methods: We collected gene expression data and clinical characteristics from the public databases including Chinese Glioma Genome Atlas (CGGA)-325, CGGA-693, the Cancer Genome Atlas (TCGA), IMvigor210 and Van Allen 2015 cohorts. The correlations between the clinicopathological factors and differential LOXs expressions were analyzed. The ROC curve and Kaplan-Meier analysis were conducted to evaluate the prediction ability of prognosis. Chemotherapeutic drug sensitivity via distinct LOXs expression levels was predicted using the pRRophetic package. Immune score, immune cell infiltration and immune checkpoint expression levels were also analyzed through diverse algorithms in R software. Finally, mRNA and protein expressions of LOXs were validated in glioma cells (T98G and A172) by real-time quantitative PCR and Western blot, respectively.

Results: Our results demonstrated that high levels of LOXs expressions were positively associated with glioma grades, older age and MGMT unmethylated status while elevations of LOXs were negatively correlated with IDH mutation or 1p/19q co-deletion. Furthermore, the glioma patients with low levels of LOXs also exhibited better prognosis. Also, differential LOXs expressions were associated with at least 12 chemotherapeutic drug sensitivity. Besides, it was also found that glioma patients with high LOXs expressions showed higher enrichment scores for immune cell infiltration and increased levels of immune checkpoints, suggesting the critical role of distinct LOXs expression levels for glioma immunotherapy. The predictive roles of LOXs expression in tumor immunotherapy were also validated in two immunotherapy cohorts including IMvigor 210 and Van Allen 2015. Experimental results revealed that expressions of LOX, LOXL1, LOXL2, and LOXL3 were higher in glioma cell lines at mRNA and protein levels.

Conclusion: Our findings altogether indicate that LOXs have potent predictive value for prognosis, chemotherapy and immunotherapy in glioma patients.

RP11-79H23.3 Inhibits the Proliferation and Metastasis of Non-small-cell Lung Cancer Through Promoting miR-29c

Evidences indicate that long non-coding RNAs (lncRNAs) are closely involved and contributed to tumorigenesis and cancer progression. As a novel lncRNA, RP11-79H23.3 was found to be an anti-oncogene in bladder cancer. However, the essential roles and functions of RP11-79H23.3 in non-small-cell lung cancer (NSCLC) remains to be elucidated. Here, loss of functional assay was applied to gain insights into the functions of RP11-79H23.3 on the proliferation and metastasis capabilities of A549 and H1299 cells. Meantime, Real-time PCR was utilized to measure RP11-79H23.3 and miR-29c expression in NSCLC tissues. Dual-luciferase reporter assay, CCK8, colony formation assay, transwell and Western blot were performed to illustrate the potential molecular basis of RP11-79H23.3 in NSCLC. RP11-79H23.3 downregulation facilitated cell proliferation, migration, and invasion of NSCLC. The result of dual-luciferase reporter assay represented a direct interaction of RP11-79H23.3 with miR-29c, which suppressed miR-29c expression that showed inversely correlation in NSCLC. Moreover, RP11-79H23.3 siRNA facilitated the progression of NSCLC partially via regulating the expression of miR-29c and the activation of Wnt/β-catenin signaling pathway. Our findings highlighted that RP11-79H23.3, served as an anti-oncogene, accelerated NSCLC progression through sequestering miR-29c, providing a promising therapeutic target for NSCLC.

Inhibition of ITGB1-DT expression delays the growth and migration of stomach adenocarcinoma and improves the prognosis of cancer patients using the bioinformatics and cell model analysis

BACKGROUND

The long non-coding RNA, integrin subunit beta 1 (ITGB1) divergent transcript (ITGB1-DT), is known to be involved in cancer progression and associated with the poor prognosis of cancer patients. At present, the role of ITGB1-DT in stomach adenocarcinoma (STAD) has not been reported.

METHODS

The expression level of ITGB1-DT was detected in normal gastric and STAD tissues from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. A receiver operating characteristic (ROC) analysis was used to evaluate the role of ITGB1-DT in diagnosing STAD. The relationship between ITGB1-DT overexpression and clinicopathological features, prognosis, and immune-infiltrated cells in STAD were explored using correlation, survival, and Cox regression analyses. A cell model of ITGB1-DT interference was constructed to explore the roles of ITGB1-DT on STAD cell proliferation and migration, and the signaling mechanism was investigated using Gene Set Enrichment Analysis (GSEA).

RESULTS

ITGB1-DT was expressed up-regulated in STAD tissues. ITGB1-DT overexpression was associated with the T stage, therapeutic effect, overall survival, progression-free interval status, and poor prognosis in STAD patients. ITGB1-DT overexpression was valuable in diagnosing STAD and a negative factor affecting the prognosis of STAD patients. Interference with ITGB1-DT expression inhibited STAD cell proliferation, invasion, and migration. GSEA results showed that ITGB1-DT may be involved in STAD progression through the insulin, p53, mechanistic target of rapamycin kinase (MTOR), and other signaling pathways. Overexpression of ITGB1-DT was significantly correlated with the levels of STAD B cells, T cells, T helper cells, CD8 T cells, cytotoxic cells, and other immune cells.

CONCLUSIONS

ITGB1-DT was overexpressed and associated with poor prognosis in STAD. Interference with ITGB1-DT expression may delay the progression of STAD to improve the prognosis of STAD patients.

Development and Validation of a 7-Gene Inflammatory Signature Forecasts Prognosis and Diverse Immune Landscape in Lung Adenocarcinoma

Background: Inflammatory responses are strongly linked with tumorigenesis and cancer development. This research aimed to construct and validate a novel inflammation response–related risk predictive signature for forecasting the prognosis of patients with LUAD.

Methods: Differential expression analysis, univariate Cox, LASSO, and multivariate Cox regression analyses of 200 inflammatory response–related genes (IRRG) were performed to establish a risk predictive model in the TCGA training cohort. The performance of the IRRG model was verified in eight GEO datasets. GSEA analysis, ESTIMATE algorithms, and ssGSEA analysis were applied to elucidate the possible mechanisms. Furthermore, the relationship analysis between risk score, model genes, and chemosensitivity was performed. Last, we verified the protein expression of seven model genes by immunohistochemical staining or Western blotting.

Results: We constructed a novel inflammatory response–related 7-gene signature (MMP14, BTG2, LAMP3, CCL20, TLR2, IL7R, and PCDH7). Patients in the high-risk group presented markedly decreased survival time in the TCGA cohort and eight GEO cohorts than the low-risk group. Interestingly, multiple pathways related to immune response were suppressed in high-risk groups. The low infiltration levels of B cell, dendritic cell, natural killer cell, and eosinophil can significantly affect the unsatisfactory prognosis of the high-risk group in LUAD. Moreover, the tumor cells’ sensitivity to anticancer drugs was markedly related to risk scores and model genes. The protein expression of seven model genes was consistent with the mRNA expression.

Conclusion: Our IRRG prognostic model can effectively forecast LUAD prognosis and is tightly related to immune infiltration.