Identification of an EMT-Related Gene Signature for Predicting Overall Survival in Gastric Cancer

Three-dimensional matrix stiffness modulates mechanosensitive and phenotypic alterations in oral squamous cell carcinoma spheroids

Extracellular biophysical cues such as matrix stiffness are key stimuli tuning cell fate and affecting tumor progression in vivo. However, it remains unclear how cancer spheroids in a 3D microenvironment perceive matrix mechanical stiffness stimuli and translate them into intracellular signals driving progression. Mechanosensitive Piezo1 and TRPV4 ion channels, upregulated in many malignancies, are major transducers of such physical stimuli into biochemical responses. Most mechanotransduction studies probing the reception of changing stiffness cues by cells are, however, still limited to 2D culture systems or cell-extracellular matrix models, which lack the major cell-cell interactions prevalent in 3D cancer tumors. Here, we engineered a 3D spheroid culture environment with varying mechanobiological properties to study the effect of static matrix stiffness stimuli on mechanosensitive and malignant phenotypes in oral squamous cell carcinoma spheroids. We find that spheroid growth is enhanced when cultured in stiff extracellular matrix. We show that the protein expression of mechanoreceptor Piezo1 and stemness marker CD44 is upregulated in stiff matrix. We also report the upregulation of a selection of genes with associations to mechanoreception, ion channel transport, extracellular matrix organization, and tumorigenic phenotypes in stiff matrix spheroids. Together, our results indicate that cancer cells in 3D spheroids utilize mechanosensitive ion channels Piezo1 and TRPV4 as means to sense changes in static extracellular matrix stiffness, and that stiffness drives pro-tumorigenic phenotypes in oral squamous cell carcinoma.

MiRNA-145-5p inhibits gastric cancer progression via the serpin family E member 1- extracellular signal-regulated kinase-1/2 axis

BACKGROUND

MicroRNAs (miRNAs) regulate gene expression and play a critical role in cancer physiology. However, there is still a limited understanding of the function and regulatory mechanism of miRNAs in gastric cancer (GC).

AIM

To investigate the role and molecular mechanism of miRNA-145-5p (miR145-5p) in the progression of GC.

METHODS

Real-time polymerase chain reaction (RT-PCR) was used to detect miRNA expression in human GC tissues and cells. The ability of cancer cells to migrate and invade was assessed using wound-healing and transwell assays, respectively. Cell proliferation was measured using cell counting kit-8 and colony formation assays, and apoptosis was evaluated using flow cytometry. Expression of the epithelial-mesenchymal transition (EMT)-associated protein was determined by Western blot. Targets of miR-145-5p were predicated using bioinformatics analysis and verified using a dual-luciferase reporter system. Serpin family E member 1 (SERPINE1) expression in GC tissues and cells was evaluated using RT-PCR and immunohistochemical staining. The correlation between SERPINE1 expression and overall patient survival was determined using Kaplan-Meier plot analysis. The association between SERPINE1 and GC progression was also tested. A rescue experiment of SERPINE1 overexpression was conducted to verify the relationship between this protein and miR-145-5p. The mechanism by which miR-145-5p influences GC progression was further explored by assessing tumor formation in nude mice.

RESULTS

GC tissues and cells had reduced miR-145-5p expression and SERPINE1 was identified as a direct target of this miRNA. Overexpression of miR-145-5p was associated with decreased GC cell proliferation, invasion, migration, and EMT, and these effects were reversed by forcing SERPINE1 expression. Kaplan-Meier plot analysis revealed that patients with higher SERPINE1 expression had a shorter survival rate than those with lower SERPINE1 expression. Nude mouse tumorigenesis experiments confirmed that miR-145-5p targets SERPINE1 to regulate extracellular signal-regulated kinase-1/2 (ERK1/2).

CONCLUSION

This study found that miR-145-5p inhibits tumor progression and is expressed in lower amounts in patients with GC. MiR-145-5p was found to affect GC cell proliferation, migration, and invasion by negatively regulating SERPINE1 levels and controlling the ERK1/2 pathway.

The phase separation of extracellular matrix protein matrilin-3 from cancer-associated fibroblasts contributes to gastric cancer invasion

Cancer-associated fibroblast (CAF) has emerged as a key contributor to the remodeling of tumor microenvironment through the expression and secretion of extracellular matrix (ECM) proteins, thereby promoting carcinogenesis. However, the precise contribution of ECM proteins from CAFs to gastric carcinogenesis remains poorly understood. In this study, we find that matrilin-3 (MATN3), an upregulated ECM protein associated with poorer prognosis in gastric cancer patients, originates from CAFs in gastric cancer tissues. Ectopic expression of MATN3 in CAFs significantly promotes the invasion of gastric cancer cells, which can be attenuated by neutralizing MATN3 with its antibody. Notably, a portion of MATN3 protein is found to form puncta in gastric cancer tissues ECM. MATN3 undergoes phase separation, which is mediated by its low complexity (LC) and coiled-coil (CC) domains. Moreover, overexpression of MATN3 deleted with either LC or CC in CAFs is unable to promote the invasion of gastric cancer cells, suggesting that LC or CC domain is required for the effect of CAF-secreted MATN3 in gastric cancer cell invasion. Additionally, orthotopic co-injection of gastric cancer cells and CAFs expressing MATN3, but not its ΔLC and ΔCC mutants, leads to enhanced gastric cancer cell invasion in mouse models. Collectively, our works suggest that MATN3 is secreted by CAFs and undergoes phase separation, which promotes gastric cancer invasion.

EMT-related gene risk model establishment for prognosis and drug treatment efficiency prediction in hepatocellular carcinoma

This study was designed to evaluate the prognosis and pharmacological therapy sensitivity of epithelial mesenchymal transition-related genes (EMTRGs) that obtained from the EMTome database in hepatocellular carcinoma (HCC) using bioinformatical method. The expression status of EMTRGs were also investigated using the clinical information of HCC patients supported by TCGA database and the ICGC database to establish the TCGA cohort as the training set and the ICGC cohort as the validation set. Analyze the EMTRGs between HCC tissue and liver tissue in the TCGA cohort in the order of univariate COX regression, LASSO regression, and multivariate COX regression, and construct a risk model for EMTRGs. In addition, enrichment pathways, gene mutation status, immune infiltration, and response to drugs were also analyzed in the high-risk and low-risk groups of the TCGA cohort, and the protein expression status of EMTRGs was verified. The results showed a total of 286 differentially expressed EMTRGs in the TCGA cohort, and EZH2, S100A9, TNFRSF11B, SPINK5, and CCL21 were used for modeling. The TCGA cohort was found to have a worse outcome in the high-risk group of HCC patients, and the ICGC cohort confirmed this finding. In addition, EMTRGs risk score was shown to be an independent prognostic factor in both cohorts by univariate and multivariate COX regression. The results of GSEA analysis showed that most of the enriched pathways in the high-risk group were associated with tumor, and the pathways enriched in the low-risk group were mainly associated with metabolism. Patients in various risk groups had varying immunological conditions, and the high-risk group might benefit more from targeted treatments. To sum up, the EMTRGs risk model was developed to forecast the prognosis for HCC patients, and the model might be useful in assisting in the choice of treatment drugs for HCC patients.

Identification of novel lactate metabolism-related lncRNAs with prognostic value for bladder cancer

Background: Bladder cancer (BCA) has high recurrence and metastasis rates, and current treatment options show limited efficacy and significant adverse effects. It is crucial to find diagnostic markers and therapeutic targets with clinical value. This study aimed to identify lactate metabolism-related lncRNAs (LM_lncRNAs) to establish a model for evaluating bladder cancer prognosis. Method: A risk model consisting of lactate metabolism-related lncRNAs was developed to forecast bladder cancer patient prognosis using The Cancer Genome Atlas (TCGA) database. Kaplan‒Meier survival analysis, receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA) were used to evaluate the reliability of risk grouping for predictive analysis of bladder cancer patients. The results were also validated in the validation set. Chemotherapeutic agents sensitive to lactate metabolism were assessed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Results: As an independent prognostic factor for patients, lactate metabolism-related lncRNAs can be used as a nomogram chart that predicts overall survival time (OS). There were significant differences in survival rates between the high-risk and low-risk groups based on the Kaplan‒Meier survival curve. decision curve analysis and receiver operating characteristic curve analysis confirmed its good predictive capacity. As a result, 22 chemotherapeutic agents were predicted to positively affect the high-risk group. Conclusion: An lactate metabolism-related lncRNA prediction model was proposed to predict the prognosis for patients with bladder cancer and chemotherapeutic drug sensitivity in high-risk groups, which provided a new idea for the prognostic evaluation of the clinical treatment of bladder cancer.

Identification and validation of a novel prognostic model for gastric cancer based on m7G-related genes

Background

The role of N7-methyladenosine (m7G)-related genes in the progression and prognosis of gastric cancer (GC) remains unclear. This study aimed to explore prognostic biomarkers for GC based on m7G methylation regulators and to construct a prognostic risk model.

Methods

RNA sequencing profiles with corresponding clinicopathological information associated with GC of which the histological type was stomach adenocarcinoma (STAD) were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. A total of 29 m7G regulators were extracted from previous studies. According to the expression similarity of m7G regulators, the GC samples obtained from TCGA were further classified into 2 clusters demonstrating different overall survival (OS) rates and genetic heterogeneity, and the differentially expressed genes (DEGs) between these 2 clusters were defined as m7G-related genes. Univariate regression analysis and regression analysis were then used to obtain the prognostic m7G-related genes. The samples in TCGA and Genotype-Tissue Expression (GTEx) were used to verify the differential expression and prognostic value of these m7G-related genes contained in the prognostic model. Subsequently, the risk score was combined with other prognostic factors to develop a nomogram. The predictive ability of the nomogram was evaluated by the standard receiver operating characteristic (ROC) curve. Gene set enrichment analysis (GSEA) was used to identify activation pathways in both groups. Finally, the association between the prognostic model and the immune characteristics of GC were appraised.

Results

A prognostic model consisting of 11 m7G-related genes was constructed. GC patients in the high-risk group were shown to have a poor prognosis and this result was further demonstrated in each group. The risk model can be applied for patients with different clinical features. The results of GSEA showed that cell adhesion, cell junction, and focal adhesion were highly enriched in the high-risk group. In addition, we found that the expression of programmed cell death ligand 1 (PD-L1) was significantly elevated in the low-risk group, whereas programmed cell death ligand 2 (PD-L2) and tumor necrosis factor receptor superfamily member 4 (TNFRSF4) were overexpressed in the high-risk group.

Conclusions

We successfully built and verified a m7G relevant prognostic model for predicting prognosis and providing a new train of thought for improving the treatment of GC.

Identification and validation of biomarkers for epithelial-mesenchymal transition-related cells to estimate the prognosis and immune microenvironment in primary gastric cancer by the integrated analysis of single-cell and bulk RNA sequencing data

BACKGROUND

The epithelial-mesenchymal transition (EMT) is associated with gastric cancer (GC) progression and immune microenvironment. To better understand the heterogeneity underlying EMT, we integrated single-cell RNA-sequencing (scRNA-seq) data and bulk sequencing data from GC patients to evaluate the prognostic utility of biomarkers for EMT-related cells (ERCs), namely, cancer-associated fibroblasts (CAFs) and epithelial cells (ECs).

METHODS

scRNA-seq data from primary GC tumor samples were obtained from the Gene Expression Omnibus (GEO) database to identify ERC marker genes. Bulk GC datasets from the Cancer Genome Atlas (TCGA) and GEO were used as training and validation sets, respectively. Differentially expressed markers were identified from the TCGA database. Univariate Cox, least-absolute shrinkage, and selection operator regression analyses were performed to identify EMT-related cell-prognostic genes (ERCPGs). Kaplan-Meier, Cox regression, and receiver-operating characteristic (ROC) curve analyses were adopted to evaluate the prognostic utility of the ERCPG signature. An ERCPG-based nomogram was constructed by integrating independent prognostic factors. Finally, we evaluated the correlations between the ERCPG signature and immune-cell infiltration and verified the expression of ERCPG prognostic signature genes by in vitro cellular assays.

RESULTS

The ERCPG signature was comprised of seven genes (COL4A1, F2R, MMP11, CAV1, VCAN, FKBP10, and APOD). Patients were divided into high- and low-risk groups based on the ERCPG risk scores. Patients in the high-risk group showed a poor prognosis. ROC and calibration curves suggested that the ERCPG signature and nomogram had a good prognostic utility. An immune cell-infiltration analysis suggested that the abnormal expression of ERCPGs induced the formation of an unfavorable tumor immune microenvironment. In vitro cellular assays showed that ERCPGs were more abundantly expressed in GC cell lines compared to normal gastric tissue cell lines.

CONCLUSIONS

We constructed and validated an ERCPG signature using scRNA-seq and bulk sequencing data from ERCs of GC patients. Our findings support the estimation of patient prognosis and tumor treatment in future clinical practice.

Use of machine learning-based integration to develop an immune-related signature for improving prognosis in patients with gastric cancer

Gastric cancer is one of the most common malignancies. Although some patients benefit from immunotherapy, the majority of patients have unsatisfactory immunotherapy outcomes, and the clinical significance of immune-related genes in gastric cancer remains unknown. We used the single-sample gene set enrichment analysis (ssGSEA) method to evaluate the immune cell content of gastric cancer patients from TCGA and clustered patients based on immune cell scores. The Weighted Correlation Network Analysis (WGCNA) algorithm was used to identify immune subtype-related genes. The patients in TCGA were randomly divided into test 1 and test 2 in a 1:1 ratio, and a machine learning integration process was used to determine the best prognostic signatures in the total cohort. The signatures were then validated in the test 1 and the test 2 cohort. Based on a literature search, we selected 93 previously published prognostic signatures for gastric cancer and compared them with our prognostic signatures. At the single-cell level, the algorithms "Seurat," "SCEVAN", "scissor", and "Cellchat" were used to demonstrate the cell communication disturbance of high-risk cells. WGCNA and univariate Cox regression analysis identified 52 prognosis-related genes, which were subjected to 98 machine-learning integration processes. A prognostic signature consisting of 24 genes was identified using the StepCox[backward] and Enet[alpha = 0.7] machine learning algorithms. This signature demonstrated the best prognostic performance in the overall, test1 and test2 cohort, and outperformed 93 previously published prognostic signatures. Interaction perturbations in cellular communication of high-risk T cells were identified at the single-cell level, which may promote disease progression in patients with gastric cancer. We developed an immune-related prognostic signature with reliable validity and high accuracy for clinical use for predicting the prognosis of patients with gastric cancer.

EMT-Related Genes Have No Prognostic Relevance in Metastatic Colorectal Cancer as Opposed to Stage II/III: Analysis of the Randomised, Phase III Trial FIRE-3 (AIO KRK 0306; FIRE-3)

INTRODUCTION

There is no standard treatment after resection of colorectal liver metastases and the role of systemic therapy remains controversial. To avoid over- or undertreatment, proper risk stratification with regard to postoperative treatment strategy is highly needed. We recently demonstrated the prognostic relevance of EMT-related (epithelial-mesenchymal transition) genes in stage II/III CRC. As EMT is a major step in CRC progression, we now aimed to analyse the prognostic relevance of EMT-related genes in stage IV CRC using the study cohort of the FIRE-3 trial, an open-label multi-centre randomised controlled phase III trial of patients with metastatic CRC.

METHODS

Overall and progression free survival were considered as endpoints (n = 350). To investigate the prognostic relevance of EMT-related genes on either endpoint, we compared predictive performance of different models using clinical data only to models using gene data in addition to clinical data, expecting better predictive performance if EMT-related genes have prognostic value. In addition to baseline models (Kaplan Meier (KM), (regularised) Cox), Random Survival Forest (RSF), and gradient boosted trees (GBT) were fit to the data. Repeated, nested five-fold cross-validation was used for hyperparameter optimisation and performance evaluation. Predictive performance was measured by the integrated Brier score (IBS).

RESULTS

The baseline KM model showed the best performance (OS: 0.250, PFS: 0.251). None of the other models were able to outperform the KM when using clinical data only according to the IBS scores (OS: 0.253 (Cox), 0.256 (RSF), 0.284 (GBT); PFS: 0.254 (Cox), 0.256 (RSF), 0.276 (GBT)). When adding gene data, performance of GBT improved slightly (OS: 0.262 vs. 0.284; PFS: 0.268 vs. 0.276), however, none of the models performed better than the KM baseline.

CONCLUSION

Overall, the results suggest that the prognostic relevance of EMT-related genes may be stage-dependent and that EMT-related genes have no prognostic relevance in stage IV CRC.

Epithelial-mesenchymal transition-related long noncoding RNAs in gastric carcinoma

As an evolutionarily phenotypic conversion program, the epithelial-mesenchymal transition (EMT) has been implicated in tumour deterioration and has facilitated the metastatic ability of cancer cells via enhancing migration and invasion. Gastric cancer (GC) remains a frequently diagnosed non-skin malignancy globally. Most GC-associated mortality can be attributed to metastasis. Recent studies have shown that EMT-related long non-coding RNAs (lncRNAs) play a critical role in GC progression and GC cell motility. In addition, lncRNAs are associated with EMT-related transcription factors and signalling pathways. In the present review, we comprehensively described the EMT-inducing lncRNA molecular mechanisms and functional perspectives of EMT-inducing lncRNAs in GC progression. Taken together, the statements of this review provided a clinical implementation in identifying lncRNAs as potential therapeutic targets for advanced GC.

A novel cuproptosis-related lncRNA nomogram to improve the prognosis prediction of gastric cancer

Background

Cuproptosis is a copper-triggered modality of mitochondrial cell death and cuproptosis process may play important roles in gastric cancer development. However, little is known about cuproptosis-related lncRNAs in gastric adenocarcinoma (STAD). This study is aimed to investigate the potential prognostic signatures of cuproptosis-related lncRNAs in STAD.

Methods

The Cancer Genome Atlas (TCGA) database were used to obtain gene expression profiles, clinicopathological, and OS information for STAD. Cuproptosis-related genes were collected based on previous studies and cuproptosis-related lncRNAs were screened out by co-expression analysis. The nomogram constructed by Cox regression analysis with the minimum absolute contraction and selection operator (lasso) algorithm. In addition, the potential response of ICB therapy and immune evasion incidence were estimated with Tumor Immune Dysfunction and Exclusion (TIDE) algorithm. Immune checkpoint expressions associated with risk scores were also analyzed. The correlation of immune checkpoint CD209 and HAVCR2 expressions associated with risk scores were experimentally testified by RT-qPCR, Western Blot, and IHC.

Results

Patients were classified into high-risk and low-risk groups based on the risk score calculated in this model. The Kaplan–Meier survival curve analysis revealed that the high-risk group was associated with poor prognosis. Multivariate Cox regression analysis suggested that this lncRNA prediction model was an independent risk factor affecting the OS rate. Furthermore, ROC curve indicates that the nomogram was superior to traditional clinicopathological features in predicting STAD prognosis. Finally, functional enrichment analysis and immune checkpoint investigation revealed that the nomogram is notably associated with cholesterol metabolism and immune functions, RT-qPCR and Western Blotting demonstrated the co-expression relationship of LINC01150 with CD209 and HAVCR2.

Conclusion

A novel cuproptosis-related lncRNAs signature impacts on the prognosis and immunological features of GC.

Construction of a novel signature and prediction of the immune landscape in gastric cancer based on necroptosis-related genes

Necroptosis, a type of programmed cell death, has become a potential therapeutic target for solid tumors. Nevertheless, the potential roles of necroptosis-related genes (NRGs) in gastric cancer (GC) remain unknown. The objective of the present study was to create a necroptosis-related prognostic signature that can provide more accurate assessment of prognosis in GC. Using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data, we identified differentially expressed NRGs. Univariate analysis and Lasso regression were performed to determine the prognostic signature. Risk scores were calculated and all GC patients were divided into high- and low-risk score group according to the median risk score value. The robustness of this signature was externally validated with data from GSE84437 cohort (n = 431). Survival analysis revealed high-risk score patients had a worse prognosis. Results evidenced that the signature was an independent prognosis factor for survival. Single-sample sequence set enrichment analysis (ssGSEA) exhibited different enrichment of immune cells and immune-related pathways in the two risk groups. Furthermore, a predictive nomogram was generated and showed excellent predictive performance based on discrimination and calibration. In addition, the risk score positively correlated with tumor mutational burden and was associated with sensitivity to multiple anti-cancer drugs. Overall, our work demonstrates a close relationship between necroptosis and the prognosis of GC. The signature we constructed with potential clinical application value, can be used for prognosis prediction and being a potential therapeutic responses indicator in GC patients.

Metastasis Related Epithelial-Mesenchymal Transition Signature Predicts Prognosis and Response to Immunotherapy in Gastric Cancer

Background

Increasing evidence has revealed the effect of epithelial-mesenchymal transition (EMT) on tumor microenvironment and cancer treatment. However, an EMT-based signature to predict the prognosis and therapeutic effect in gastric cancer (GC) has rarely been established.

Methods

Differentially expressed genes (DEGs) between paired primary gastric and ovarian metastatic tumors were identified through comparative RNA-seq analysis, followed by the construction of metastasis-related EMT signature (MEMTS) based on DEGs and EMT gene set. Then, both The Cancer Genome Atlas (TCGA) cohort and the Asian Cancer Research Group (ACRG) cohort were analyzed to explore the potential association between MEMTS and prognosis in GC. Samsung Medical Center (SMC) cohort and two individual immunotherapy treatment cohorts, including Kim cohort and Hugo cohort, were utilized to evaluate the predictive value of MEMTS on the response to adjuvant therapy and immunotherapy, respectively. Finally, the potential association of MEMTS with tumor environment and immune escape mechanisms was investigated.

Results

High MEMTS predicted a poor prognosis in patients with GC. Patients with low MEMTS potentially gained more benefits from adjuvant chemoradiotherapy than those with high MEMTS. MEMTS reliably predicted the response to immunotherapy in GC (area under the curve = 0.896). MEMTS was significantly associated with cancer-associated fibroblasts and stromal score in the aspect of the tumor microenvironment.

Conclusion

MEMTS serves as a potential biomarker to predict the prognosis and response to adjuvant therapy and immunotherapy in GC. MEMTS-based evaluation of individual tumors enables personalized treatment for GC patients in the future.

A tEMTing target? Clinical and experimental evidence for epithelial-mesenchymal transition in the progression of cutaneous squamous cell carcinoma (a scoping systematic review)

Cutaneous squamous cell carcinoma (cSCC) is a disease with globally rising incidence and poor prognosis for patients with advanced or metastatic disease. Epithelial-mesenchymal transition (EMT) is a driver of metastasis in many carcinomas, and cSCC is no exception. We aimed to provide a systematic overview of the clinical and experimental evidence for EMT in cSCC, with critical appraisal of type and quality of the methodology used. We then used this information as rationale for potential drug targets against advanced and metastatic cSCC. All primary literature encompassing clinical and cell-based or xenograft experimental studies reporting on the role of EMT markers or related signalling pathways in the progression of cSCC were considered. A screen of 3443 search results yielded 86 eligible studies comprising 44 experimental studies, 22 clinical studies, and 20 studies integrating both. From the clinical studies a timeline illustrating the alteration of EMT markers and related signalling was evident based on clinical progression of the disease. The experimental studies reveal connections of EMT with a multitude of factors such as genetic disorders, cancer-associated fibroblasts, and matrix remodelling via matrix metalloproteinases and urokinase plasminogen activator. Additionally, EMT was found to be closely tied to environmental factors as well as to stemness in cSCC via NFκB and β-catenin. We conclude that the canonical EGFR, canonical TGF-βR, PI3K/AKT and NFκB signalling are the four signalling pillars that induce EMT in cSCC and could be valuable therapeutic targets. Despite the complexity, EMT markers and pathways are desirable biomarkers and drug targets for the treatment of advanced or metastatic cSCC.

Cellular Senescence-Related Genes: Predicting Prognosis in Gastric Cancer

Our study aimed to explore the effect of cellular senescence and to find potential therapeutic strategies for gastric cancer. Cellular senescence-related genes were acquired from the CellAge database, while gastric cancer data were obtained from GEO and TCGA databases. SMARCA4 had the highest mutation frequency (6%), and it was linked to higher overall survival (OS) and progression-free survival (PFS). The gastric cancer data in TCGA database served as a training set to construct a prognostic risk score signature, and GEO data were used as a testing set to validate the accuracy of the signature. Patients with the low-risk score group had a longer survival time, while the high-risk score group is the opposite. Patients with low-risk scores had higher immune infiltration and active immune-related pathways. The results of drug sensitivity analysis and the TIDE algorithm showed that the low-risk score group was more susceptible to chemotherapy and immunotherapy. Most patients with mutation genes had a lower risk score than the wild type. Therefore, the risk score signature with cellular senescence-related genes can predict gastric cancer prognosis and identify gastric cancer patients who are sensitive to chemotherapy and immunotherapy.

Pan-Cancer Analyses Reveal Oncogenic and Immunological Role of PLOD2

Some previous studies have shown that PLOD2 has some value in tumorigenesis. However, the broad significance of PLOD2 has not been discussed in depth. This study was aimed at elaborated and summarized the value of PLOD2 in various tumors. First, we integrated GTEx, The Cancer Genome Atlas and Cancer Cell Line Encyclopedia databases to analyze the expression of PLOD2, and found that it was expressed differently in normal tissues and significantly highly expressed in most tumors compared with normal tissues. Second, our analysis revealed that PLOD2 expression was negatively correlated with the prognosis of several tumors. For gastric cancer, the median overall survival time was significantly higher in the PLOD2 low expression group [HR 0.616 (95%CI 0.442–0.858), p = 0.004]. Third, for tumor immunity, PLOD2 was significantly associated with tumor infiltration, including immune infiltrating cells; immune checkpoint expression; immune microenvironment scores (immune score, stromal score and estimate scores); immunotherapy-related scores (tumor mutational burden, microsatellite instability, tumor neoantigen burden); expression of DNA repair genes Mismatch Repairs and methyltransferase; and enrichment analyses identified PLOD2-associated terms and pathways. Lastly, twenty pairs of gastric cancer and adjacent immunohistochemistry showed that PLOD2 was significantly overexpressed in gastric cancer (p < 0.001). Collectively, PLOD2 played a significant role in tumorigenesis and maybe serve as a potential biomarker for diagnosis and prognosis in cancers.

Cross talk between RNA modification writers and tumor development as a basis for guiding personalized therapy of gastric cancer

Background

Gastric cancer (GC) shows high metastasis and low survival. RNA modification writers play critical roles in tumor development. This study examined the clinical significance of RNA modification writers in GC prognosis based on four types of adenosine modifications (m¹A, m⁶A, APA and A-to-I).

Results

Writers demonstrated high mutation and expression in GC patients. Different expressions of 26 RNA modification writers were differentially associated with GC prognosis. High-WM score group appeared worse overall survival, higher immune infiltration and activation of EMT pathways than low-WM score group. WM score was correlated with both miRNAs-targeted signaling pathways and patients’ sensitivity to chemotherapeutic drugs and efficacy of immunotherapy.

Conclusions

This study further revealed the close association between adenosine-related RNA modifications and progression of GC. A cross talk between EMT and RNA modification was identified to be one of the mechanisms underlying GC development. Our WM scoring system could serve as a clinical indicator for predicting GC prognosis. Importantly, the WM score could guide personalized treatments such as chemotherapy and immunotherapy for GC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-022-00386-z.

Viscoelasticity, Like Forces, Plays a Role in Mechanotransduction

Viscoelasticity and its alteration in time and space has turned out to act as a key element in fundamental biological processes in living systems, such as morphogenesis and motility. Based on experimental and theoretical findings it can be proposed that viscoelasticity of cells, spheroids and tissues seems to be a collective characteristic that demands macromolecular, intracellular component and intercellular interactions. A major challenge is to couple the alterations in the macroscopic structural or material characteristics of cells, spheroids and tissues, such as cell and tissue phase transitions, to the microscopic interferences of their elements. Therefore, the biophysical technologies need to be improved, advanced and connected to classical biological assays. In this review, the viscoelastic nature of cytoskeletal, extracellular and cellular networks is presented and discussed. Viscoelasticity is conceptualized as a major contributor to cell migration and invasion and it is discussed whether it can serve as a biomarker for the cells’ migratory capacity in several biological contexts. It can be hypothesized that the statistical mechanics of intra- and extracellular networks may be applied in the future as a powerful tool to explore quantitatively the biomechanical foundation of viscoelasticity over a broad range of time and length scales. Finally, the importance of the cellular viscoelasticity is illustrated in identifying and characterizing multiple disorders, such as cancer, tissue injuries, acute or chronic inflammations or fibrotic diseases.

Identification of a Four-Gene-Based SERM Signature for Prognostic and Drug Sensitivity Prediction in Gastric Cancer

Background

Gastric cancer (GC) is a highly molecular heterogeneous tumor with poor prognosis. Epithelial-mesenchymal transition (EMT) process and cancer stem cells (CSCs) are reported to share common signaling pathways and cause poor prognosis in GC. Considering about the close relationship between these two processes, we aimed to establish a gene signature based on both processes to achieve better prognostic prediction in GC.

Methods

The gene signature was constructed by univariate Cox and the least absolute shrinkage and selection operator (LASSO) Cox regression analyses by using The Cancer Genome Atlas (TCGA) GC cohort. We performed enrichment analyses to explore the potential mechanisms of the gene signature. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) curves were implemented to assess its prognostic value in TCGA cohort. The prognostic value of gene signature on overall survival (OS), disease-free survival (DFS), and drug sensitivity was validated in different cohorts. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) validation of the prognostic value of gene signature for OS and DFS prediction was performed in the Fudan cohort.

Results

A prognostic signature including SERPINE1, EDIL3, RGS4, and MATN3 (SERM signature) was constructed to predict OS, DFS, and drug sensitivity in GC. Enrichment analyses illustrated that the gene signature has tight connection with the CSC and EMT processes in GC. Patients were divided into two groups based on the risk score obtained from the formula. The Kaplan-Meier analyses indicated high-risk group yielded significantly poor prognosis compared with low-risk group. Pearson’s correlation analysis indicated that the risk score was positively correlated with carboplatin and 5-fluorouracil IC50 of GC cell lines. Multivariate Cox regression analyses showed that the gene signature was an independent prognostic factor for predicting GC patients’ OS, DFS, and susceptibility to adjuvant chemotherapy.

Conclusions

Our SERM prognostic signature is of great value for OS, DFS, and drug sensitivity prediction in GC, which may give guidance to the development of targeted therapy for CSC- and EMT-related gene in the future.