SLC1A5 Prefers to Play as an Accomplice Rather Than an Opponent in Pancreatic Adenocarcinoma

Constructing a personalized prognostic risk model for colorectal cancer using machine learning and multi-omics approach based on epithelial-mesenchymal transition-related genes

The progression and the metastatic potential of colorectal cancer (CRC) are intricately linked to the epithelial-mesenchymal transition (EMT) process. The present study harnesses the power of machine learning combined with multi-omics data to develop a risk stratification model anchored on EMT-associated genes. The aim is to facilitate personalized prognostic assessments in CRC. We utilized publicly accessible gene expression datasets to pinpoint EMT-associated genes, employing a CoxBoost algorithm to sift through these genes for prognostic significance. The resultant model, predicated on gene expression levels, underwent rigorous independent validation across various datasets. Our model demonstrated a robust capacity to segregate CRC patients into distinct high- and low-risk categories, each correlating with markedly different survival probabilities. Notably, the risk score emerged as an independent prognostic indicator for CRC. High-risk patients were characterized by an immunosuppressive tumor milieu and a heightened responsiveness to certain chemotherapeutic agents, underlining the model's potential in steering tailored oncological therapies. Moreover, our research unearthed a putative repressive interaction between the long non-coding RNA PVT1 and the EMT-associated genes TIMP1 and MMP1, offering new insights into the molecular intricacies of CRC. In essence, our research introduces a sophisticated risk model, leveraging machine learning and multi-omics insights, which accurately prognosticates outcomes for CRC patients, paving the way for more individualized and effective oncological treatment paradigms.

CDKN2A was a cuproptosis-related gene in regulating chemotherapy resistance by the MAGE-A family in breast cancer: based on artificial intelligence (AI)-constructed pan-cancer risk model

BACKGROUND

Before the discovery of cuproptosis, copper-loaded nanoparticle is a wildly applied strategy for enhancing the tumor-cell-killing effect of chemotherapy. Although copper(ii)-related researches are wide, details of cuproptosis-related bioprocess in pan-cancer are not clear yet now, especially for prognosis and drug sensitivity prediction yet now.

METHODS

In this study, VOSviewer is used for the literature review, and R4.2.0 is used for data analysis. Public data are collected from TCGA and GEO, local breast cancer cohort is collected to verify the expression level of CDKN2A.

RESULTS

7036 published articles exhibited a time-dependent linear relationship (R=0.9781, p<0.0001), and breast cancer (33.4%) is the most researched topic. Cuproptosis-related-genes (CRGs)-based unsupervised clustering divides pan-cancer subgroups into four groups (CRG subgroup) with differences in prognosis and tumor immunity. 44 tumor-driver-genes (TDGs)-based prediction model of drug sensitivity and prognosis is constructed by artificial intelligence (AI). Based on TDGs and clinical features, a nomogram is (C- index: 0.7, p= 6.958e- 12) constructed to predict the prognosis of breast cancer. Importance analysis identifies CDKN2A has a pivotal role in AI modeling, whose higher expression indicates worse prognosis in breast cancer. Furthermore, inhibition of CDKN2A down-regulates decreases Snail1, Twist1, Zeb1, vimentin and MMP9, while E-cadherin is increased. Besides, inhibition of CDKN2A also decreases the expression of MEGEA4, phosphorylated STAT3, PD-L1, and caspase3, while cleaved-caspase3 is increased. Finally, we find down-regulation of CDKN2A or MAGEA inhibits cell migration and wound healing, respectively.

CONCLUSIONS

AI identified CRG subgroups in pan-cancer based on CRGs-related TDGs, and 44-gene-based AI modeling is a novel tool to identify chemotherapy sensitivity in breast cancer, in which CDKN2A/MAGEA4 pathway played the most important role.

Ferroptosis regulator NOS2 is closely associated with the prognosis and cell malignant behaviors of hepatoblastoma: a bioinformatic and in vitro study

Background

Hepatoblastoma (HB) is the most common liver tumor in children with easy metastasis. The emergence of ferroptosis as a novel form of cell death has gained increased attention in various human cancers. However, the roles of ferroptosis-related (FR) genes in HB remain elusive.

Methods

The GSE133039, GSE131329, and GSE81928 datasets were utilized for screening core FR genes in HB. Through Lasso regression analysis and using the support vector machine recursive feature elimination (SVM-RFE) algorithm, three candidate FR genes were obtained for characterizing HB. Their expression patterns and their clinical associations were explored through the 'Limma' R package, and their diagnostic potential was evaluated using ROC curves. Nitric oxide synthase 2 (NOS2) emerged as a candidate for further analyses. The CIBERSORT algorithm and GSEA dataset were used to respectively investigate the immune and metabolism effects of NOS2; the former was validated through immunofluorescence. The GSDC database was employed to analyze the correlation between NOS2 expression and the therapeutic efficacy of multiple drugs. PCR, Western blotting, colony formation assays, and Transwell experiments, were used to determine biological functions of NOS2 in HB cells. Potential upstream transcription factors of NOS2 were predicted through the TRRUST, hTFtarget, GeneCards, and JASPAR databases.

Results

NQO1, SLC1A4, and NOS2 were identified as potential genes in HB and found to be significantly upregulated in tumor samples. Nevertheless, only NOS2 was closely associated with HB clinicopathological characteristics; high NOS2 expression indicated poor prognosis, metastatic tendency, and late clinical stage. Immune analyses indicated that high NOS2 expression was concomitant with decreased infiltration levels of CD8+ T cells but increased infiltration levels of macrophages. GSEA revealed that NOS2 failed to affect the enrichments of glycolysis, fatty acid metabolism, and cholesterol biosynthesis in HB. Moreover, NOS2 was positively correlated with the IC50 values of trametinib, lapatinib, and cisplatin. NOS2 overexpression promoted the proliferation, migration and invasion of HepG2 and HuH-6 cells. JUND was identified as a potential transcriptional regulator of NOS2 by binding to its promoter (5'-TTCTGACTCTTTT-3').

Conclusion

NOS2 plays a significant role in HB clinical assessments and holds promise as a novel therapeutic target.

The Regulation of Ferroptosis by Noncoding RNAs

As a novel form of regulated cell death, ferroptosis is characterized by intracellular iron and lipid peroxide accumulation, which is different from other regulated cell death forms morphologically, biochemically, and immunologically. Ferroptosis is regulated by iron metabolism, lipid metabolism, and antioxidant defense systems as well as various transcription factors and related signal pathways. Emerging evidence has highlighted that ferroptosis is associated with many physiological and pathological processes, including cancer, neurodegeneration diseases, cardiovascular diseases, and ischemia/reperfusion injury. Noncoding RNAs are a group of functional RNA molecules that are not translated into proteins, which can regulate gene expression in various manners. An increasing number of studies have shown that noncoding RNAs, especially miRNAs, lncRNAs, and circRNAs, can interfere with the progression of ferroptosis by modulating ferroptosis-related genes or proteins directly or indirectly. In this review, we summarize the basic mechanisms and regulations of ferroptosis and focus on the recent studies on the mechanism for different types of ncRNAs to regulate ferroptosis in different physiological and pathological conditions, which will deepen our understanding of ferroptosis regulation by noncoding RNAs and provide new insights into employing noncoding RNAs in ferroptosis-associated therapeutic strategies.

PTPRC promoted CD8+ T cell mediated tumor immunity and drug sensitivity in breast cancer: based on pan-cancer analysis and artificial intelligence modeling of immunogenic cell death-based drug sensitivity stratification

Background

Immunogenic cell death (ICD) is a result of immune cell infiltration (ICI)-mediated cell death, which is also a novel acknowledgment to regulate cellular stressor-mediated cell death, including drug therapy and radiotherapy.

Methods

In this study, TCGA and GEO data cohorts were put into artificial intelligence (AI) to identify ICD subtypes, and in vitro experiments were performed.

Results

Gene expression, prognosis, tumor immunity, and drug sensitivity showed significance among ICD subgroups, Besides, a 14-gene-based AI model was able to represent the genome-based drug sensitivity prediction, which was further verified in clinical trials. Network analysis revealed that PTPRC was the pivotal gene in regulating drug sensitivity by regulating CD8+ T cell infiltration. Through in vitro experiments, intracellular down-regulation of PTPRC enhanced paclitaxel tolerance in triple breast cancer (TNBC) cell lines. Meanwhile, the expression level of PTPRC was positively correlated with CD8+ T cell infiltration. Furthermore, the down-regulation of PTPRC increased the level of TNBC-derived PD-L1 and IL2.

Discussion

ICD-based subtype clustering of pan-cancer was helpful to evaluate chemotherapy sensitivity and immune cell infiltration, and PTPRC was a potential target to against drug resistance of breast cancer.

Ferroptosis-Related Gene SLC1A5 Is a Novel Prognostic Biomarker and Correlates with Immune Microenvironment in HBV-Related HCC

(1) Background: Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide with limited treatment satisfaction. Finding new therapeutic targets has remained a major challenge. Ferroptosis is an iron-dependent cell death program that plays a regulatory role in HBV infection and HCC development. It is necessary to classify the roles of ferroptosis or ferroptosis-related genes (FRGs) in HBV-related HCC progression. (2) Methods: We conducted a matched case-control study from the TCGA database, retrospectively collecting demographic data and common clinical indicators from all subjects. The Kaplan-Meier curve, univariate and multivariate cox regression analysis of the FRGs were used to explore the risk factors for HBV-related HCC. The CIBERSORT algorithm and TIDE algorithm were executed to evaluate the functions of FRGs in the tumor-immune environment. (3) Results: A total of 145 HBV-positive HCC patients and 266 HBV-negative HCC patients were enrolled in our study. Four ferroptosis related genes (FANCD2, CS, CISD1 and SLC1A5) were positively correlated with the progression of HBV-related HCC. Among them, SLC1A5 was an independent risk factor for HBV-related HCC, and correlated with poor prognosis, advanced progression and an immunosuppression microenvironment. (4) Conclusions: Here, we revealed that a ferroptosis-related gene, SLC1A5, may be an excellent predictor of HBV-related HCC and may provide insight into the development of innovative possible therapeutic techniques.

Cuproptosis regulatory genes greatly contribute to clinical assessments of hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common abdominal cancer with dissatisfactory therapeutic effects. The discovery of cuproptosis lights on new approach for cancer treatment and assessment. So far, there is extremely limited research investigating the roles of cuproptosis-related (CR) genes in cancers.

METHODS

A novel CR risk signature was constructed using the Lasso regression analysis. Its prognostic value was assessed via a series of survival analyses and validated in three GEO cohorts. The effects of CR risk signature on tumor immune microenvironment (TIM) were explored through CIBERSORT, ESTIMATE, and ssGSEA algorithms. Using GESA, we investigated its impacts on various metabolism process. The somatic mutation features of CR signature genes were also explored via cBioPortal database. Using tumor mutation burden, expressions of immune checkpoints, TIDE score, IMvigor 210 cohort, and GSE109211 dataset, we explored the potential associations of CR risk score with the efficacy of immune checkpoint inhibitors (ICIs) and sorafenib. Finally, the biofunctions of DLAT in HCC cells were ascertained through qPCR, immunohistochemistry, colony formation, and Transwell assays.

RESULTS

FDX1, DLAT, CDKN2A and GLS constituted the CR risk signature. CR risk signature possessed high prognostic value and was also applicable to three validation cohorts. Meanwhile, it could improve the accuracy and clinical making-decision benefit of traditional prognostic model. Moreover, high CR risk was indicative of unfavorable anti-tumor immune response and active metabolisms of glycolysis and nucleotide. As for therapeutic correlation, CR risk score was a potential biomarker for predicting the efficacy of ICIs and sorafenib. Through qPCR and immunohistochemistry detection in clinical samples, we reconfirmed DLAT was significantly upregulated in HCC samples. Overexpression of DLAT could promote the proliferation, migration, and invasion of HepG2 and HuH-7 cells.

CONCLUSIONS

The novel CR risk signature greatly contributed to the clinical assessment of HCC. Cuproptosis regulatory gene DLAT possessed cancer-promoting capacities and was expected to be a promising therapeutic target for HCC.

High expression of RNF169 is associated with poor prognosis in pancreatic adenocarcinoma by regulating tumour immune infiltration

Background: Pancreatic adenocarcinoma (PAAD) is a highly deadly and aggressive tumour with a poor prognosis. However, the prognostic value of RNF169 and its related mechanisms in PAAD have not been elucidated. In this study, we aimed to explore prognosis-related genes, especially RNF169 in PAAD and to identify novel potential prognostic predictors of PAAD. Methods: The GEPIA and UALCAN databases were used to investigate the expression and prognostic value of RNF169 in PAAD. The correlation between RNF169 expression and immune infiltration was determined by using TIMER and TISIDB. Correlation analysis with starBase was performed to identify a potential regulatory axis of lncRNA-miRNA-RNF169. Results: The data showed that the level of RNF169 mRNA expression in PAAD tissues was higher than that in normal tissues. High RNF169 expression was correlated with poor prognosis in PAAD. In addition, analysis with the TISIDB and TIMER databases revealed that RNF169 expression was positively correlated with tumour immune infiltration in PAAD. Correlation analysis suggested that the long non-coding RNA (lncRNA) AL049555.1 and the microRNA (miRNA) hsa-miR-324-5p were involved in the expression of RNF169, composing a potential regulatory axis to control the progression of PAAD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that RNF169 plays a role in PAAD through pathways such as TNF, Hippo, JAK-STAT and Toll-like receptor signaling. Conclusion: In summary, the upregulation of RNF169 expression mediated by ncRNAs might influence immune cell infiltration in the microenvironment; thus, it can be used as a prognostic biomarker and a potential therapeutic target in PAAD.

N7-methylguanosine regulatory genes well represented by METTL1 define vastly different prognostic, immune and therapy landscapes in adrenocortical carcinoma

Although N7-methylguanosine (m7G) is one of the most frequent RNA modifications, it has received little attention. Adrenocortical carcinoma (ACC) is a highly malignant and easily metastatic tumor, eagerly needing for novel therapeutic strategy. Herein, a novel m7G risk signature (METTL1, NCBP1, NUDT1 and NUDT5) was constructed using the Lasso regression analysis. It possessed highly prognostic value and could improve the predictive accuracy and clinical making-decision benefit of traditional prognostic model. Its prognostic value was also successfully validated in GSE19750 cohort. Through CIBERSORT, ESTIMATE, ssGSEA and GSEA analyzes, high-m7G risk score was found to be closely associated with increased enrichment of glycolysis and suppression of anti-cancer immune response. Therapeutic correlation of m7G risk signature was also investigated using tumor mutation burden, the expressions of immune checkpoints, TIDE score, IMvigor 210 cohort and TCGA cohort. m7G risk score was a potential biomarker for predicting the efficacy of ICBs and mitotane. Furthermore, we explored the biofunctions of METTL1 in ACC cells through a series of experimentations. Overexpression of METTL1 stimulated the proliferation, migration and invasion of H295R and SW13 cells. Immunofluorescence assays revealed that the infiltrating levels of CD8+ T cells was lower and that of macrophages was higher in clinical ACC samples with high METTL1 expression compared to that in low expression ones. Silencing METTL1 could significantly inhibited tumor growth in mouse xenograft model. Western blot assays showed that METTL1 positively regulated the expression of glycolysis rate-limiting enzyme HK1. Finally, miR-885-5p and CEBPB were predicted as the upstream regulators of METTL1 through data mining of the public databases. In conclusions, m7G regulatory genes well represented by METTL1 profoundly affected the prognosis, tumor immune, therapeutic outcomes, and malignant progression of ACC.

The role of microRNAs in ferroptosis

Ferroptosis is a newly discovered type of programmed cell death, which is closely related to the imbalance of iron metabolism and oxidative stress. Ferroptosis has become an important research topic in the fields of cardiomyopathy, tumors, neuronal injury disorders, and ischemia perfusion disorders. As an important part of non-coding RNA, microRNAs regulate various metabolic pathways in the human body at the post-transcriptional level and play a crucial role in the occurrence and development of many diseases. The present review introduces the mechanisms of ferroptosis and describes the relevant pathways by which microRNAs affect cardiomyopathy, tumors, neuronal injury disorders and ischemia perfusion disorders through regulating ferroptosis. In addition, it provides important insights into ferroptosis-related microRNAs, aiming to uncover new methods for treatment of the above diseases, and discusses new ideas for the implementation of possible microRNA-based ferroptosis-targeted therapies in the future.

Ferroptosis: A Specific Vulnerability of RAS-Driven Cancers?

Ferroptosis has emerged as a new type of programmed cell death that can be harnessed for cancer therapy. The concept of ferroptosis was for the first time proposed in in the early 2000s, as an iron-dependent mode of regulated cell death caused by unrestricted lipid peroxidation (LPO) and subsequent plasma membrane rupture. Since the discovery and characterization of ferroptosis, a wealth of research has improved our understanding of the main pathways regulating this process, leading to both the repurposing and the development of small molecules.

However, ferroptosis is still little understood and several aspects remain to be investigated. For instance, it is unclear whether specific oncogenes, cells of origin or tumor niches impose specific susceptibility/resistance to ferroptosis or if there are some ferroptosis-related genes that may be used as bona fide pan-cancer targetable dependencies. In this context, even though RAS-driven cancer cell lines seemed to be selectively sensitive to ferroptosis inducers, subsequent studies have questioned these results, indicating that in some cases mutant RAS is necessary, but not sufficient to induce ferroptosis. In this perspective, based on publicly available genomic screening data and the literature, we discuss the relationship between RAS-mutation and ferroptosis susceptibility in cancer.

Exploring the Potential of Pyroptosis-Related Genes in Predicting Prognosis and Immunological Characteristics of Pancreatic Cancer From the Perspective of Genome and Transcriptome

Objective

To probe into the role of pyroptosis-related genes in pancreatic carcinoma.

Methods

Herein, we conducted a comprehensive bioinformatics analysis to evaluate tumor-immune infiltration and tumor mutation burden, the correlations between PRGs, and microsatellite instability and found that 33 PRGS were up- or down-regulated in PC. Then we built the PPI network, which was downloaded from the STRING database. Using TCGA cohort median risk score, PC subjects from the Gene Expression Composite cohort (GEO) data resource were stratified into two risk categories, with the low-PC risk group harboring a higher overall survival (OS) (P = 0.011). We employed the ssGSEA approach to quantify immune cell abundance in separate risk groups separated by risk signature while assessing variations in immune cell invasion. Chemotherapeutic drugs were retrieved from the Genomics of Drug Sensitivity in Cancer (GDSC) data resource.

Results

Eight prognostic PRG models (CASP4, GSDMC, IL-18, NLRP1, NLRP2, PLCG1, TIRAP, and TNF) were established via LASSO Cox regression to estimate the OS of PC subjects with medium-to-high accuracy.

Conclusion

Our study is the first to identify a pyroptotic-related prognostic gene feature for PC, providing more options for the prognostic prediction of PC.

N7-Methylguanosine Regulatory Genes Profoundly Affect the Prognosis, Progression, and Antitumor Immune Response of Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is a common abdominal cancer with poor survival outcomes. Although there is growing evidence that N7-methylguanosine (m7G) is closely associated with tumor prognosis, development, and immune response, few studies focus on this topic.

Methods

The novel m7G risk signature was constructed through the Lasso regression analysis. Its prognostic value was evaluated through a series of survival analyses and was tested in ICGC-LIRI, GSE14520, and GSE116174 cohorts. CIBERSORT, ssGSEA, and ESTIMATE methods were applied to explore the effects of the m7G risk score on tumor immune microenvironment (TIM). The GSEA method was used to evaluate the impacts of the m7G risk score on glycolysis, ferroptosis, and pyroptosis. The human protein atlas (HPA) database was used to clarify the histological expression levels of five m7G signature genes. The biofunctions of NCBP2 in hepatocellular cancer (HC) cells were confirmed through qPCR, CCK8, and transwell assays.

Results

Five m7G regulatory genes comprised the novel risk signature. The m7G risk score was identified as an independent prognostic factor of HCC and could increase the decision-making benefit of traditional prognostic models. Besides, we established a nomogram containing the clinical stage and m7G risk score to predict the survival rates of HCC patients. The prognostic value of the m7G model was successfully validated in ICGC and GSE116174 cohorts. Moreover, high m7G risk led to a decreased infiltration level of CD8+ T cells, whereas it increased the infiltration levels of Tregs and macrophages. The glycolysis and pyroptosis processes were found to be enriched in the HCC patients with high m7G risk. Finally, overexpression of NCBP2 could promote the proliferation, migration, and invasion of HC cells.

Conclusions

The m7G risk score was closely related to the prognosis, antitumor immune process, glycolysis, and malignant progression of HCC. NCBP2 has pro-oncogenic abilities, showing promise as a novel treatment target.