Development and validation of prognostic model based on the analysis of autophagy-related genes in colon cancer

Combination of pemetrexed with bevacizumab for non-small-cell lung cancer: a meta-analysis study

BACKGROUND

Combining pemetrexed with bevacizumab may have some potential in improving the efficacy in patients with non-small-cell lung cancer (NSCLC), and this meta-analysis aims to explore the impact of pemetrexed addition to bevacizumab on treatment efficacy for NSCLC.

METHODS

PubMed, EMbase, Web of science, EBSCO, and Cochrane library databases were systematically searched, and we included randomized controlled trials (RCTs) assessing the effect of pemetrexed addition to bevacizumab on treatment efficacy in patients with NSCLC. Overall survival and progression-free survival were included in this meta-analysis.

RESULTS

Four RCTs were finally included in the meta-analysis. Overall, compared with bevacizumab for NSCLC, pemetrexed addition showed significantly improved overall survival (hazard ratio [HR] = 0.87; 95% confidence interval [CI] = 0.76 to 0.99; P = 0.03), survival rate (odd ratio [OR] = 1.41; 95% CI = 1.06 to 1.86; P = 0.02), progression-free survival (HR = 0.63; 95% CI = 0.55 to 0.72; P < 0.00001) and progression-free survival rate (OR = 1.92; 95% CI = 1.38 to 2.67; P < 0.00001), but led to the increase in grade ≥ 3 adverse events (OR = 2.15; 95% CI = 1.62 to 2.84; P < 0.00001).

CONCLUSIONS

Pemetrexed addition may be effective to improve treatment efficacy for NSCLC compared to bevacizumab treatment.

Curcumin and its anti-colorectal cancer potential: From mechanisms of action to autophagy

Colorectal cancer (CRC) development and progression, one of the most common cancers globally, is supported by specific mechanisms to escape cell death despite chemotherapy, including cellular autophagy. Autophagy is an evolutionarily highly conserved degradation pathway involved in a variety of cellular processes, such as the maintenance of cellular homeostasis and clearance of foreign bodies, and its imbalance is associated with many diseases. However, the role of autophagy in CRC progression remains controversial, as it has a dual function, affecting either cell death or survival, and is associated with cellular senescence in tumor therapy. Indeed, numerous data have been presented that autophagy in cancers serves as an alternative to cell apoptosis when the latter is ineffective or in apoptosis-resistant cells, which is why it is also referred to as programmed cell death type II. Curcumin, one of the active constituents of Curcuma longa, has great potential to combat CRC by influencing various cellular signaling pathways and epigenetic regulation in a safe and cost-effective approach. This review discusses the efficacy of curcumin against CRC in vitro and in vivo, particularly its modulation of autophagy and apoptosis in various cellular pathways. While clinical studies have assessed the potential of curcumin in cancer prevention and treatment, none have specifically examined its role in autophagy. Nonetheless, we offer an overview of potential correlations to support the use of this polyphenol as a prophylactic or co-therapeutic agent in CRC.

Ferroptosis is a protective factor for the prognosis of cancer patients: a systematic review and meta-analysis

BACKGROUND

Cancer is a leading global cause of death. Conventional cancer treatments like surgery, radiation, and chemotherapy have associated side effects. Ferroptosis, a nonapoptotic and iron-dependent cell death, has been identified and differs from other cell death types. Research has shown that ferroptosis can promote and inhibit tumor growth, which may have prognostic value. Given the unclear role of ferroptosis in cancer biology, this meta-analysis aims to investigate its impact on cancer prognosis.

METHODS

This systematic review and meta-analysis conducted searches on PubMed, Embase, and the Cochrane Library databases. Eight retrospective studies were included to compare the impact of ferroptosis inhibition and promotion on cancer patient prognosis. The primary endpoints were overall survival (OS) and progression-free survival (PFS). Studies lacking clear descriptions of hazard ratios (HR) and 95% confidence intervals for OS and PFS were excluded. Random-effects meta-analysis and meta-regression were performed on the included study data to assess prognosis differences between the experimental and control groups. Meta-analysis results included HR and 95% confidence intervals. This study has been registered with PROSPERO, CRD 42023463720 on September 27, 2023.

RESULTS

A total of 2,446 articles were screened, resulting in the inclusion of 5 articles with 938 eligible subjects. Eight studies were included in the meta-analysis after bias exclusion. The meta-analysis, after bias exclusion, demonstrated that promoting ferroptosis could increase cancer patients' overall survival (HR 0.31, 95% CI 0.21-0.44) and progression-free survival (HR 0.26, 95% CI 0.16-0.44) compared to ferroptosis inhibition. The results showed moderate heterogeneity, suggesting that biological activities promoting cancer cell ferroptosis are beneficial for cancer patient's prognosis.

CONCLUSIONS

This systematic review and meta-analysis demonstrated that the promotion of ferroptosis yields substantial benefits for cancer prognosis. These findings underscore the untapped potential of ferroptosis as an innovative anti-tumor therapeutic strategy, capable of addressing challenges related to drug resistance, limited therapeutic efficacy, and unfavorable prognosis in cancer treatment.

REGISTRATION

CRD42023463720.

Prognostic value and immunological role of PD-L1 gene in pan-cancer

OBJECTIVE

PD-L1, a target of immune checkpoint blockade, has been proven to take the role of an oncogene in most human tumors. However, the role of PD-L1 in human pan-cancers has not yet been fully investigated.

MATERIALS AND METHODS

Pan-cancer analysis was conducted to analyze expression, genetic alterations, prognosis analysis, and immunological characteristics of PD-L1. Estimating the correlation between PD-L1 expression and survival involved using pooled odds ratios and hazard ratios with 95% CI. The Kaplan-Meier (K-M) technique, COX analysis, and receiver operating characteristic (ROC) curves were applied to the survival analysis. Additionally, we investigated the relationships between PD-L1 and microsatellite instability (MSI), tumor mutational burden (TMB), DNA methyltransferases (DNMTs), the associated genes of mismatch repair (MMR), and immune checkpoint biomarkers using Spearman's correlation analysis. Also, immunohistochemical analysis and qRT-PCR were employed in evaluating PD-L1's protein and mRNA expression in pan-caner.

RESULTS

PD-L1 showed abnormal mRNA and protein expression in a variety of cancers and predicted prognosis in cancer patients. Furthermore, across a variety of cancer types, the aberrant PD-L1 expression was connected to the MSI, MMR, TMB, drug sensitivity, and tumor immune microenvironment (TIME). Moreover, PD-L1 was significantly correlated with infiltrating levels of immune cells (T cell CD8 + , neutrophil, and so on).

CONCLUSION

Our study provides a better theoretical basis and guidance for the clinical treatment of PD-L1.

Identification of AP002498.1 and LINC01871 as prognostic biomarkers and therapeutic targets for distant metastasis of colorectal adenocarcinoma

BACKGROUND

Increasing evidence suggests that lncRNA (Long non-coding RNA, lncRNA)-mediated ceRNA (competing endogenous RNA, ceRNA) networks are involved in the occurrence and progression of colorectal cancer (CRC). However, the roles of the lncRNA-miRNA-mRNA ceRNA network in distant metastasis of CRC are still unclear.

METHODS

In this study, we constructed a specific ceRNA network to identify potential biomarkers and therapeutic targets for distant metastasis of CRC. Specifically, RNA-Seq data from The Cancer Genome Atlas (TCGA) were used to screen for differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) related to metastasis. After validation and selection by qRT-PCR and univariate and multivariate analysis of the metastasis- and prognosis-related lncRNAs, the regulated microRNAs (miRNAs) and coexpressed mRNAs were used to construct a ceRNA network for distant metastasis of CRC.

RESULTS

Two key distant metastasis-related DElncRNAs, AP002498.1 and LINC01871, were identified by univariate and multivariate analysis in combination with analyses of clinical data and expression levels. Furthermore, lncRNA-associated ceRNA subnetworks were constructed from the predicted miRNAs and 13 coexpressed DEmRNAs (SERPINA1, ITLN1, REG4, L1TD1, IGFALS, MUC5B, CIITA, CXCL9, CXCL10, GBP4, GNLY, IDO1, and NOS2). The AP002498.1- and LINC01871-associated ceRNA subnetworks regulated the expression of the target genes SERPINA1 and MUC5B and GNLY, respectively, through the associated miRNAs.

CONCLUSION

The DElncRNA AP002498.1 and the LINC01871/miR-4644 and miR-185-5p/GNLY axes were identified as being closely associated with distant metastasis and could represent independent prognostic biomarkers or therapeutic targets in colorectal adenocarcinoma.

Identification of cuproptosis-based molecular subtypes, construction of prognostic signature and characterization of immune landscape in colon cancer

Background

Cuproptosis is a newly discovered form of cell death induced by targeting lipoacylated proteins involved in the tricarboxylic acid cycle. However, the roles of cuproptosis-related genes (CRGs) in the clinical outcomes and immune landscape of colon cancer remain unknown.

Methods

We performed bioinformatics analysis of the expression data of 13 CRGs identified from a previous study and clinical information of patients with colon cancer obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Colon cancer cases were divided into two CRG clusters and prognosis-related differentially expressed genes. Patient data were separated into three corresponding distinct gene clusters, and the relationships between the risk score, patient prognosis, and immune landscape were analyzed. The identified molecular subtypes correlated with patient survival, immune cells, and immune functions. A prognostic signature based on five genes was identified, and the patients were divided into high- and low-risk groups based on the calculated risk score. A nomogram model for predicting patient survival was developed based on the risk score and other clinical features.

Results

The high-risk group showed a worse prognosis, and the risk score was related to immune cell abundance, microsatellite instability, cancer stem cell index, checkpoint expression, immune escape, and response to chemotherapeutic drugs and immunotherapy. Findings related to the risk score were validated in the imvigor210 cohort of patients with metastatic urothelial cancer treated with anti-programmed cell death ligand 1.

Conclusion

We demonstrated the potential of cuproptosis-based molecular subtypes and prognostic signatures for predicting patient survival and the tumor microenvironment in colon cancer. Our findings may improve the understanding of the role of cuproptosis in colon cancer and lead to the development of more effective treatment strategies.

Machine learning algorithm to construct cuproptosis- and immune-related prognosis prediction model for colon cancer

BACKGROUND

Over the past few years, research into the pathogenesis of colon cancer has progressed rapidly, and cuproptosis is an emerging mode of cellular apoptosis. Exploring the relationship between colon cancer and cuproptosis benefits in identifying novel biomarkers and even improving the outcome of the disease.

AIM

To look at the prognostic relationship between colon cancer and the genes associated with cuproptosis and the immune system in patients. The main purpose was to assess whether reasonable induction of these biomarkers reduces mortality among patients with colon cancers.

METHOD

Data obtained from The Cancer Genome Atlas and Gene Expression Omnibus and the Genotype-Tissue Expression were used in differential analysis to explore differential expression genes associated with cuproptosis and immune activation. The least absolute shrinkage and selection operator and Cox regression algorithm was applied to build a cuproptosis- and immune-related combination model, and the model was utilized for principal component analysis and survival analysis to observe the survival and prognosis of the patients. A series of statistically meaningful transcriptional analysis results demonstrated an intrinsic relationship between cuproptosis and the micro-environment of colon cancer.

RESULTS

Once prognostic characteristics were obtained, the CDKN2A and DLAT genes related to cuproptosis were strongly linked to colon cancer: The first was a risk factor, whereas the second was a protective factor. The finding of the validation analysis showed that the comprehensive model associated with cuproptosis and immunity was statistically significant. Within the component expressions, the expressions of HSPA1A, CDKN2A, and UCN3 differed markedly. Transcription analysis primarily reflects the differential activation of related immune cells and pathways. Furthermore, genes linked to immune checkpoint inhibitors were expressed differently between the subgroups, which may reveal the mechanism of worse prognosis and the different sensitivities of chemotherapy.

CONCLUSION

The prognosis of the high-risk group evaluated in the combined model was poorer, and cuproptosis was highly correlated with the prognosis of colon cancer. It is possible that we may be able to improve patients’ prognosis by regulating the gene expression to intervene the risk score.

Identification and validation of prognostic autophagy-related genes associated with immune microenvironment in human gastric cancer

Autophagy-related genes (ATGs) play critical roles in tumorigenesis and progression in gastric cancer (GC). The present study aimed to identify immune-based prognostic ATGs and verify their functions in tumor immune microenvironment (TIME) in GC. Macrophage infiltration was found to negatively correlate with prognosis in GC patients. After stratifying by infiltration levels of macrophages, we screened The Cancer Genome Atlas and Human Autophagy Database to identify the differentially expressed ATGs (DE-ATGs). Of 1,433 differentially expressed genes between the two groups, seven genes qualified as DE-ATGs. Of these, CXCR4, DLC1, and MAP1LC3C, exhibited strong prognostic prediction ability in Kaplan-Meier survival–log-rank test. High expression of these genes correlated with increased occurrence of advanced grade 3 tumors and poor prognoses. Furthermore, GSEA indicated that they were significantly associated with oncogenic and immune-related pathways. The comprehensive evaluation of TIME via GEPIA, ESTIMATE, CIBERSORT, and TIMER suggested that the three DE-ATGs were closely associated with immune condition, both in terms of immune cells and immune scores. Thus, the outcome of this study may aid in better understanding of the ATGs and their interaction with the immune microenvironment, which would allow the development of novel inhibitors, personalized treatment, and immunotherapy in gastric cancer.

PANoptosis-based molecular clustering and prognostic signature predicts patient survival and immune landscape in colon cancer

PANoptosis is a newly-discovered cell death pathway that involves crosstalk and co-ordination between pyroptosis, apoptosis, and necroptosis processes. However, the roles of PANoptosis-related genes (PRGs) in prognosis and immune landscape of colon cancer remain widely unknown. Here, we performed a bioinformatics analysis of expression data of nineteen PRGs identified from previous studies and clinical data of colon cancer patients obtained from TCGA and GEO databases. Colon cancer cases were divided into two PRG clusters, and prognosis-related differentially expressed genes (PRDEGs) were identified. The patient data were then separated into two corresponding distinct gene clusters, and the relationship between the risk score, patient prognosis, and immune landscape was analyzed. The identified PRGs and gene clusters correlated with patient survival and immune system and cancer-related biological processes and pathways. A prognosis signature based on seven genes was identified, and patients were divided into high-risk and low-risk groups based on the calculated risk score. A nomogram model for prediction of patient survival was also developed based on the risk score and other clinical features. Accordingly, the high-risk group showed worse prognosis, and the risk score was related to immune cell abundance, cancer stem cell (CSC) index, checkpoint expression, and response to immunotherapy and chemotherapeutic drugs. Results of quantitative real-time polymerase chain reaction (qRT-PCR) showed that LGR5 and VSIG4 were differentially expressed between normal and colon cancer samples. In conclusion, we demonstrated the potential of PANoptosis-based molecular clustering and prognostic signatures for prediction of patient survival and tumor microenvironment (TME) in colon cancer. Our findings may improve our understanding of the role of PANoptosis in colon cancer, and enable the development of more effective treatment strategies.

Immunotherapeutic Value of MAP1LC3C and Its Candidate FDA-Approved Drugs Identified by Pan-Cancer Analysis, Virtual Screening and Sensitivity Analysis

Background: The autophagy pathway within the tumour microenvironment can be regulated to inhibit or promote tumour development. In the fight against tumour growth, immunotherapy induces an anti-tumour immune response, whereas autophagy modulates this immune response. A key protein in the autophagy pathway, microtubule-associated protein 1 light chain 3 (MAP1LC3), has recently become a hotspot for tumour research. As a relatively novel member, the function of MAP1LC3C in tumours still need to be investigated. Therefore, the goal of this study was to look into the possible link between MAP1LC3C and immunotherapy for 33 kinds of human malignancies by using pan-cancer analysis. Methods: High-throughput sequencing data from The Cancer Genome Atlas, Genotype-Tissue Expression Project and Cancer Cell Line Encyclopedia databases, combined with clinical data, were used to analyze the expression of MAP1LC3C in 33 types of cancer, as well as patient prognosis and neoplasm staging. Activity scores were calculated using ssGSEA to assess the MAP1LC3C activity in pan-cancer. Associations between MAP1LC3C and the tumour microenvironment, including immune cell infiltration and immunomodulators, were analyzed. Moreover, tumour tissue ImmuneScores and StromalScores were analyzed using the ESTIMATE algorithm. Additionally, associations between MAP1LC3C and tumour mutational burden/microsatellite instability, were investigated. Finally, based on the expression and structure of MAP1LC3C, the United States Food and Drug Administration (FDA)-approved drugs, were screened by virtual screening, molecular docking and NCI-60 drug sensitivity analysis. Results: Our study found that MAP1LC3C was differentially expressed in tumour and normal tissues in 23 of 33 human cancer types, among which MAP1LC3C had prognostic effects in 12 cancer types, and MAP1LC3C expression was significantly correlated with tumour stage in four cancer types. In addition, MAP1LC3C activity in 14 cancer types was consistent with changes in transcription levels. Moreover, MAP1LC3C strongly correlated with immune infiltration, immune modulators and immune markers. Finally, a number of FDA-approved drugs were identified via virtual screening and drug sensitivity analysis. Conclusion: Our study investigated the prognostic and immunotherapeutic value of MAP1LC3C in 33 types of cancer, and several FDA-approved drugs were identified to be highly related to MAP1LC3C and can be potential cancer therapeutic candidates.