Deep computational analysis details dysregulation of eukaryotic translation initiation complex eIF4F in human cancers

mTORC1 regulates cell survival under glucose starvation through 4EBP1/2-mediated translational reprogramming of fatty acid metabolism

Energetic stress compels cells to evolve adaptive mechanisms to adjust their metabolism. Inhibition of mTOR kinase complex 1 (mTORC1) is essential for cell survival during glucose starvation. How mTORC1 controls cell viability during glucose starvation is not well understood. Here we show that the mTORC1 effectors eukaryotic initiation factor 4E binding proteins 1/2 (4EBP1/2) confer protection to mammalian cells and budding yeast under glucose starvation. Mechanistically, 4EBP1/2 promote NADPH homeostasis by preventing NADPH-consuming fatty acid synthesis via translational repression of Acetyl-CoA Carboxylase 1 (ACC1), thereby mitigating oxidative stress. This has important relevance for cancer, as oncogene-transformed cells and glioma cells exploit the 4EBP1/2 regulation of ACC1 expression and redox balance to combat energetic stress, thereby supporting transformation and tumorigenicity in vitro and in vivo. Clinically, high EIF4EBP1 expression is associated with poor outcomes in several cancer types. Our data reveal that the mTORC1-4EBP1/2 axis provokes a metabolic switch essential for survival during glucose starvation which is exploited by transformed and tumor cells.

Computational inference of eIF4F complex function and structure in human cancers

The canonical eukaryotic initiation factor 4F (eIF4F) complex, composed of eIF4G1, eIF4A1, and the cap-binding protein eIF4E, plays a crucial role in cap-dependent translation initiation in eukaryotic cells. An alternative cap-independent initiation can occur, involving only eIF4G1 and eIF4A1 through internal ribosome entry sites (IRESs). This mechanism is considered complementary to cap-dependent initiation, particularly in tumors under stress conditions. However, the selection and molecular mechanism of specific translation initiation remains poorly understood in human cancers. Thus, we analyzed gene copy number variations (CNVs) in TCGA tumor samples and found frequent amplification of genes involved in translation initiation. Copy number gains in EIF4G1 and EIF3E frequently co-occur across human cancers. Additionally, EIF4G1 expression strongly correlates with genes from cancer cell survival pathways including cell cycle and lipogenesis, in tumors with EIF4G1 amplification or duplication. Furthermore, we revealed that eIF4G1 and eIF4A1 protein levels strongly co-regulate with ribosomal subunits, eIF2, and eIF3 complexes, while eIF4E co-regulates with 4E-BP1, ubiquitination, and ESCRT proteins. Utilizing Alphafold predictions, we modeled the eIF4F structure with and without eIF4E binding. For cap-dependent initiation, our modeling reveals extensive interactions between the N-terminal eIF4E-binding domain of eIF4G1 and eIF4E. Furthermore, the eIF4G1 HEAT-2 domain positions eIF4E near the eIF4A1 N-terminal domain (NTD), resulting in the collaborative enclosure of the RNA binding cavity within eIF4A1. In contrast, during cap-independent initiation, the HEAT-2 domain directly binds the eIF4A1-NTD, leading to a stronger interaction between eIF4G1 and eIF4A1, thus closing the mRNA binding cavity without the involvement of eIF4E.

Computational inference of eIF4F complex function and structure in human cancers

The canonical eukaryotic initiation factor 4F (eIF4F) complex, composed of eIF4G1, eIF4A1, and the cap-binding protein eIF4E, plays a crucial role in cap-dependent translation initiation in eukaryotic cells (1). However, cap-independent initiation can occur through internal ribosomal entry sites (IRESs), involving only eIF4G1 and eIF4A1 present, which is considered to be a complementary process to cap-dependent initiation in tumors under stress conditions (2). The selection and molecular mechanism of specific translation initiation in human cancers remains poorly understood. Thus, we analyzed gene copy number variations (CNVs) in TCGA tumor samples and found frequent amplification of genes involved in translation initiation. Copy number gains in EIF4G1 and EIF3E frequently co-occur across human cancers. Additionally, EIF4G1 expression strongly correlates with genes from cancer cell survival pathways including cell cycle and lipogenesis, in tumors with EIF4G1 amplification or duplication. Furthermore, we revealed that eIF4G1 and eIF4A1 protein levels strongly co-regulate with ribosomal subunits, eIF2, and eIF3 complexes, while eIF4E co-regulates with 4E-BP1, ubiquitination, and ESCRT proteins. Using Alphafold predictions, we modeled the eIF4F structure with and without eIF4G1-eIF4E binding. The modeling for cap-dependent initiation suggests that eIF4G1 interacts with eIF4E through its N-terminal eIF4E-binding domain, bringing eIF4E near the eIF4A1 mRNA binding cavity and closing the cavity with both eIF4G1 HEAT-2 domain and eIF4E. In the cap-independent mechanism, α-helix 5 of eIF4G1 HEAT-2 domain instead directly interacts with the eIF4A1 N-terminal domain to close the mRNA binding cavity without eIF4E involvement, resulting in a stronger interaction between eIF4G1 and eIF4A1.

Significance Statement

Translation initiation is primarily governed by eIF4F, employing a "cap-dependent" mechanism, but eIF4F dysregulation may lead to a "cap-independent" mechanism in stressed cancer cells. We found frequent amplification of translation initiation genes, and co-occurring copy number gains of EIF4G1 and EIF3E genes in human cancers. EIF4G1 amplification or duplication may be positively selected for its beneficial impact on the overexpression of cancer survival genes. The co-regulation of eIF4G1 and eIF4A1, distinctly from eIF4E, reveals eIF4F dysregulation favoring cap-independent initiation. Alphafold predicts changes in the eIF4F complex assembly to accommodate both initiation mechanisms. These findings have significant implications for evaluating cancer cell vulnerability to eIF4F inhibition and developing treatments that target cancer cells with dependency on the translation initiation mechanism.

Therapeutic targeting of eukaryotic initiation factor (eIF) 4E

Fundamental studies unraveled the role of eukaryotic initiation factor (eIF) 4E in mRNA translation and its control. Under physiological conditions, regulation of translation by eIF4E is essential to cellular homeostasis. Under stress, gene flow information is parsed by eIF4E to support adaptive mechanisms that favor cell survival. Dysregulated eIF4E activity fuels tumor formation and progression and modulates response to therapy. Thus, there has been heightened interest in understanding eIF4E function in controlling gene expression as well as developing strategies to block its activity to treat disease.

Protocol to analyze dysregulation of the eIF4F complex in human cancers using R software and large public datasets

Understanding dysregulation of the eukaryotic initiation factor 4F (eIF4F) complex across tumor types is critical to cancer treatment development. We present a protocol and accompanying R package "eIF4F.analysis". We describe analysis of copy number status, gene abundance and stoichiometry, survival probability, expression covariation, correlating genes, mRNA/protein correlation, and protein co-expression. Using publicly available large multi-omics data, eIF4F.analysis permits computationally derived and statistically powerful inferences regarding initiation factor regulation in human cancers and clinical relevance of protein interactions within the eIF4F complex. For complete details on the use and execution of this protocol, please refer to Wu and Wagner (2021).¹.

EIF4G1 Is a Potential Prognostic Biomarker of Breast Cancer

BACKGROUND

Breast cancer (BRCA) is one of the most common cancers in women worldwide and a leading cause of death from malignancy. This study was designed to identify a novel biomarker for prognosticating the survival of BRCA patients.

METHODS

The prognostic potential of eukaryotic translation initiation factor 4 gamma 1 (EIF4G1) was assessed using RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) as training cohort and validation set, respectively. The functional enrichment analysis of differentially expressed genes (DEGs) was performed. The relationship between EIF4G1 and tumor microenvironment (TME) was analyzed. Immunotherapy responses were explored by the immunophenoscores (IPS) and tumor immune dysfunction and exclusion (TIDE) score. The Connectivity Map (CMap) was used to discover potentially effective therapeutic molecules against BRCA. Immunohistochemistry (IHC) was applied to compare the protein levels of EIF4G1 in normal and cancer tissues and to verify the prognostic value of EIF4G1.

RESULTS

BRCA patients with increased expression of EIF4G1 had a shorter overall survival (OS) in all cohorts and results from IHC. EIF4G1-related genes were mainly involved in DNA replication, BRCA metastasis, and the MAPK signaling pathway. Infiltration levels of CD4⁺-activated memory T cells, macrophages M0, macrophages M1, and neutrophils were higher in the EIF4G1 high-expression group than those in the EIF4G1 low-expression group. EIF4G1 was positively correlated with T cell exhaustion. Lower IPS was revealed in high EIF4G1 expression patients. Five potential groups of drugs against BRCA were identified.

CONCLUSION

EIF4G1 might regulate the TME and affect BRCA metastasis, and it is a potential prognostic biomarker and therapeutic target for BRCA.

Integrative pan-cancer analysis and clinical characterization of the N7-methylguanosine (m7G) RNA modification regulators in human cancers

Background: RNA modification is one of the epigenetic mechanisms that regulates post-transcriptional gene expression, and abnormal RNA modifications have been reported to play important roles in tumorigenesis. N7-methylguanosine (m7G) is an essential modification at the 5′ cap of human mRNA. However, a systematic and pan-cancer analysis of the clinical relevance of m7G related regulatory genes is still lacking.

Methods: We used univariate Cox model and Kaplan-Meier analysis to generate the forest plot of OS, PFI, DSS and identified the correlation between the altered expression of m7G regulators and patient survival in 33 cancer types from the TCGA and GTEx databases. Then, the “estimate” R-package, ssGSEA and CIBERSORT were used to depict the pan-cancer immune landscape. Through Spearman’s correlation test, we analyzed the correlation between m7G regulators and the tumor microenvironment (TME), immune subtype, and drug sensitivity of the tumors, which was further validated in NSCLC. We also assessed the changes in the expression of m7G related regulatory genes in NSCLC with regards to the genetic and transcriptional aspects and evaluated the correlation of METTL1 and WDR4 expression with TMB, MSI and immunotherapy in pan-cancer.

Results: High expression of most of the m7G regulators was significantly associated with worse prognosis. Correlation analyses revealed that the expression of majority of the m7G regulators was correlated with tumor immune infiltration and tumor stem cell scores. Drug sensitivity analysis showed that the expression of CYFP1,2 was closely related to drug sensitivity for various anticancer agents (p < 0.001). Analysis of the pan-cancer immune subtype revealed significant differences in the expression of m7G regulators between different immune subtypes (p < 0.001). Additionally, the types and proportions of mutations in METTL1 and WDR4 and their relevance to immunotherapy were further described.

Conclusion: Our study is the first to evaluate the correlation between the altered expression of m7G regulators and patient survival, the degree of immune infiltration, TME and drug sensitivity in pan-cancer datasets.

Identification of N7-methylguanosine related signature for prognosis and immunotherapy efficacy prediction in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is one of the most frequent causes of tumor-related mortality worldwide. Recently, the role of N7-methylguanosine (m7G) in tumors has begun to receive attention, but no investigation on the impact of m7G on LUAD. This study aims to elucidate the significance of m7G on the prognosis and immunotherapy in LUAD.

Methods

Consensus clustering was employed to determine the molecular subtype according to m7G-related regulators extracted from The Cancer Genome Atlas (TCGA) database. Survival, clinicopathological features and tumor mutational burden (TMB) analysis were applied to research molecular characteristics of each subtype. Subsequently, “limma” package was used to screen differentially expressed genes (DEGs) between subtypes. In the TCGA train cohort (n = 245), a prognostic signature was established by univariate Cox regression, lasso regression and multivariate Cox regression analysis according to DEGs and survival analysis was employed to assess the prognosis. Then the prognostic value of the signature was verified by TCGA test cohort (n = 245), TCGA entire cohort (n = 490) and GSE31210 cohort (n = 226). Moreover, the association among immune infiltration, clinical features and the signature was investigated. The immune checkpoints, TMB and tumor immune dysfunction and exclusion (TIDE) were applied to predict the immunotherapy response.

Results

Two novel molecular subtypes (C1 and C2) of LUAD were identified. Compared to C2 subtype, C1 subtype had poorer prognosis and higher TMB. Subsequently, the signature (called the “m7G score”) was constructed according to four key genes (E2F7, FAM83A, PITX3, and HOXA13). The distribution of m7G score were significantly different between two molecular subtypes. The patients with lower m7G score had better prognosis in TCGA train cohort and three verification cohort. The m7G score was intensively related to immune infiltration. Compared with the lower score, the higher m7G score was related to remarkable upregulation of the PD-1 and PD-L1, the higher TMB and the lower TIDE score.

Conclusion

This study established a m7G-related signature for predicting prognosis and immunotherapy in LUAD, which may contribute to the development of new therapeutic strategies for LUAD.