Identification of lactylation related model to predict prognostic, tumor infiltrating immunocytes and response of immunotherapy in gastric cancer

Role of novel protein acylation modifications in immunity and its related diseases

The cross-regulation of immunity and metabolism is currently a research hotspot in life sciences and immunology. Metabolic immunology plays an important role in cutting-edge fields such as metabolic regulatory mechanisms in immune cell development and function, and metabolic targets and immune-related disease pathways. Protein post-translational modification (PTM) is a key epigenetic mechanism that regulates various biological processes and highlights metabolite functions. Currently, more than 400 PTM types have been identified to affect the functions of several proteins. Among these, metabolic PTMs, particularly various newly identified histone or non-histone acylation modifications, can effectively regulate various functions, processes and diseases of the immune system, as well as immune-related diseases. Thus, drugs aimed at targeted acylation modification can have substantial therapeutic potential in regulating immunity, indicating a new direction for further clinical translational research. This review summarises the characteristics and functions of seven novel lysine acylation modifications, including succinylation, S-palmitoylation, lactylation, crotonylation, 2-hydroxyisobutyrylation, β-hydroxybutyrylation and malonylation, and their association with immunity, thereby providing valuable references for the diagnosis and treatment of immune disorders associated with new acylation modifications.

Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer

Gastric cancer (GC) is one of the most common cancers worldwide. Most patients are diagnosed at the progressive stage of the disease, and current anticancer drug advancements are still lacking. Therefore, it is crucial to find relevant biomarkers with the accurate prediction of prognoses and good predictive accuracy to select appropriate patients with GC. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have enabled the approach of GC biology at multiple levels of omics interaction networks. Systemic biological analyses, such as computational inference of "big data" and advanced bioinformatic approaches, are emerging to identify the key molecular biomarkers of GC, which would benefit targeted therapies. This review summarizes the current status of how bioinformatics analysis contributes to biomarker discovery for prognosis and prediction of therapeutic efficacy in GC based on a search of the medical literature. We highlight emerging individual multi-omics datasets, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics, for validating putative markers. Finally, we discuss the current challenges and future perspectives to integrate multi-omics analysis for improving biomarker implementation. The practical integration of bioinformatics analysis and multi-omics datasets under complementary computational analysis is having a great impact on the search for predictive and prognostic biomarkers and may lead to an important revolution in treatment.

Lactate and lactylation in macrophage metabolic reprogramming: current progress and outstanding issues

It is commonly known that different macrophage phenotypes play specific roles in different pathophysiological processes. In recent years, many studies have linked the phenotypes of macrophages to their characteristics in different metabolic pathways, suggesting that macrophages can perform different functions through metabolic reprogramming. It is now gradually recognized that lactate, previously overlooked as a byproduct of glycolytic metabolism, acts as a signaling molecule in regulating multiple biological processes, including immunological responses and metabolism. Recently, lactate has been found to mediate epigenetic changes in macrophages through a newfound lactylation modification, thereby regulating their phenotypic transformation. This novel finding highlights the significant role of lactate metabolism in macrophage function. In this review, we summarize the features of relevant metabolic reprogramming in macrophages and the role of lactate metabolism therein. We also review the progress of research on the regulation of macrophage metabolic reprogramming by lactylation through epigenetic mechanisms.

Lactylproteome analysis indicates histone H4K12 lactylation as a novel biomarker in triple-negative breast cancer

Objective

The established link between posttranslational modifications of histone and non-histone lysine (K) residues in cell metabolism, and their role in cancer progression, is well-documented. However, the lactylation expression signature in triple-negative breast cancer (TNBC) remains underexplored.

Methods

We conducted a comprehensive lactylproteome profiling of eight pairs of TNBC samples and their matched adjacent tissues. This was achieved through 4-Dimensional label-free quantitative proteomics combined with lactylation analysis (4D-LFQP-LA). The expression of identified lactylated proteins in TNBC was detected using immunoblotting and immunohistochemistry (IHC) with specific primary antibodies, and their clinicopathological and prognostic significance was evaluated.

Results

Our analysis identified 58 lactylation sites on 48 proteins, delineating the protein lactylation alteration signature in TNBC. Bioinformatic and functional analyses indicated that these lactylated proteins play crucial roles in regulating key biological processes in TNBC. Notably, lactylation of lysine at position 12 (H4K12lac) in the histone H4 domain was found to be upregulated in TNBC. Further investigations showed a high prevalence of H4K12lac upregulation in TNBC, with positive rates of 93.19% (137/147) and 92.93% (92/99) in TNBC tissue chip and validation cohorts, respectively. H4K12lac expression correlated positively with Ki-67 and inversely with overall survival (OS) in TNBC (HR [hazard ratio] =2.813, 95%CI [credibility interval]: 1.242-6.371, P=0.0164), suggesting its potential as an independent prognostic marker (HR=3.477, 95%CI: 1.324-9.130, P=0.011).

Conclusions

Lactylation is a significant post-translational modification in TNBC proteins. H4K12lac emerges as a promising biomarker for TNBC, offering insights into the lactylation profiles of TNBC proteins and linking histone modifications to clinical implications in TNBC.

Emerging therapeutic frontiers in cancer: insights into posttranslational modifications of PD-1/PD-L1 and regulatory pathways

The interaction between programmed cell death ligand 1 (PD-L1), which is expressed on the surface of tumor cells, and programmed cell death 1 (PD-1), which is expressed on T cells, impedes the effective activation of tumor antigen-specific T cells, resulting in the evasion of tumor cells from immune-mediated killing. Blocking the PD-1/PD-L1 signaling pathway has been shown to be effective in preventing tumor immune evasion. PD-1/PD-L1 blocking antibodies have garnered significant attention in recent years within the field of tumor treatments, given the aforementioned mechanism. Furthermore, clinical research has substantiated the efficacy and safety of this immunotherapy across various tumors, offering renewed optimism for patients. However, challenges persist in anti-PD-1/PD-L1 therapies, marked by limited indications and the emergence of drug resistance. Consequently, identifying additional regulatory pathways and molecules associated with PD-1/PD-L1 and implementing judicious combined treatments are imperative for addressing the intricacies of tumor immune mechanisms. This review briefly outlines the structure of the PD-1/PD-L1 molecule, emphasizing the posttranslational modification regulatory mechanisms and related targets. Additionally, a comprehensive overview on the clinical research landscape concerning PD-1/PD-L1 post-translational modifications combined with PD-1/PD-L1 blocking antibodies to enhance outcomes for a broader spectrum of patients is presented based on foundational research.

Prognostic analysis of related factors of adverse reactions to immunotherapy in advanced gastric cancer and establishment of a nomogram model

BACKGROUND

Immunotherapy for advanced gastric cancer has attracted widespread attention in recent years. However, the adverse reactions of immunotherapy and its relationship with patient prognosis still need further study. In order to determine the association between adverse reaction factors and prognosis, the aim of this study was to conduct a systematic prognostic analysis. By comprehensively evaluating the clinical data of patients with advanced gastric cancer treated by immunotherapy, a nomogram model will be established to predict the survival status of patients more accurately.

AIM

To explore the characteristics and predictors of immune-related adverse reactions (irAEs) in advanced gastric cancer patients receiving immunotherapy with programmed death protein-1 (PD-1) inhibitors and to analyze the correlation between irAEs and patient prognosis.

METHODS

A total of 140 patients with advanced gastric cancer who were treated with PD-1 inhibitors in our hospital from June 2021 to October 2023 were selected. Patients were divided into the irAEs group and the non-irAEs group according to whether or not irAEs occurred. Clinical features, manifestations, and prognosis of irAEs in the two groups were collected and analyzed. A multivariate logistic regression model was used to analyze the related factors affecting the occurrence of irAEs, and the prediction model of irAEs was established. The receiver operating characteristic (ROC) curve was used to evaluate the ability of different indicators to predict irAEs. A Kaplan-Meier survival curve was used to analyze the correlation between irAEs and prognosis. The Cox proportional risk model was used to analyze the related factors affecting the prognosis of patients.

RESULTS

A total of 132 patients were followed up, of whom 63 (47.7%) developed irAEs. We looked at the two groups' clinical features and found that the two groups were statistically different in age ≥ 65 years, Ki-67 index, white blood cell count, neutrophil count, and regulatory T cell (Treg) count (all P < 0.05). Multivariate logistic regression analysis showed that Treg count was a protective factor affecting irAEs occurrence (P = 0.030). The ROC curve indicated that Treg + Ki-67 + age (≥ 65 years) combined could predict irAEs well (area under the curve = 0.753, 95% confidence interval: 0.623-0.848, P = 0.001). Results of the Kaplan-Meier survival curve showed that progression-free survival (PFS) was longer in the irAEs group than in the non-irAEs group (P = 0.001). Cox proportional hazard regression analysis suggested that the occurrence of irAEs was an independent factor for PFS (P = 0.006).

CONCLUSION

The number of Treg cells is a separate factor that affects irAEs in advanced gastric cancer patients receiving PD-1 inhibitor immunotherapy. irAEs can affect the patients' PFS and result in longer PFS. Treg + Ki-67 + age (≥ 65 years old) combined can better predict the occurrence of adverse reactions.

A multi-dimensional approach to unravel the intricacies of lactylation related signature for prognostic and therapeutic insight in colorectal cancer

BACKGROUND

Lactylation, a novel contributor to post-translational protein modifications, exhibits dysregulation across various tumors. Nevertheless, its intricate involvement in colorectal carcinoma, particularly for non-histone lactylation and its intersection with metabolism and immune evasion, remains enigmatic.

METHODS

Employing immunohistochemistry on tissue microarray with clinical information and immunofluorescence on colorectal cell lines, we investigated the presence of global lactylation and its association with development and progression in colorectal cancer as well as its functional location. Leveraging the AUCell algorithm alongside correlation analysis in single-cell RNA sequencing data, as well as cox-regression and lasso-regression analysis in TCGA dataset and confirmed in GEO dataset, we identified a 23-gene signature predicting colorectal cancer prognosis. Subsequently, we analyzed the associations between the lactylation related gene risk and clinical characteristics, mutation landscapes, biological functions, immune cell infiltration, immunotherapy responses, and drug sensitivity. Core genes were further explored for deep biological insights through bioinformatics and in vitro experiments.

RESULTS

Our study innovatively reveals a significant elevation of global lactylation in colorectal cancer, particularly in malignant tumors, confirming it as an independent prognostic factor for CRC. Through a comprehensive analysis integrating tumor tissue arrays, TCGA dataset, GEO dataset, combining in silico investigations and in vitro experiments, we identified a 23-gene Lactylation-Related Gene risk model capable of predicting the prognosis of colorectal cancer patients. Noteworthy variations were observed in clinical characteristics, biological functions, immune cell infiltration, immune checkpoint expression, immunotherapy responses and drug sensitivity among distinct risk groups.

CONCLUSIONS

The Lactylation-Related Gene risk model exhibits significant potential for improving the management of colorectal cancer patients and enhancing therapeutic outcomes, particularly at the intersection of metabolism and immune evasion. This finding underscores the clinical relevance of global lactylation in CRC and lays the groundwork for mechanism investigation and targeted therapeutic strategies given the high lactate concentration in CRC.

Lactylation-related gene signature for prognostic prediction and immune infiltration analysis in breast cancer

Background

Lactylation is implicated in various aspects of tumor biology, but its relation to breast cancer remains poorly understood. This study aimed to explore the roles of the lactylation-related genes in breast cancer and its association with the tumor microenvironment.

Methods

The expression and mutation patterns of lactylation-related genes were analyzed using the breast cancer data from The Cancer Genome Atlas (TCGA) database and GSE20685 datasets. Unsupervised clustering was used to identify two lactylation clusters. A lactylation-related gene signature was developed and validated using the training and validation cohorts. Immune cell infiltration and drug response were assessed.

Results

We analyzed the mRNA expression, copy number variations, somatic mutations, and correlation networks of 22 lactylation-related genes in breast cancer tissues. We identified two distinct lactylation clusters with different survival outcomes and immune microenvironments. We further classified the patients into two gene subtypes based on lactylation clusters and identified a 7-gene signature for breast cancer survival prognosis. The prognostic score based on this signature demonstrated prognostic value and predicted the therapeutic response.

Conclusion

Lactylation-related genes play a critical role in breast cancer by influencing tumor growth, immune microenvironment, and drug response. This lactylation-related gene signature may serve as a prognostic marker and a potential therapeutic target for breast cancer.

Identification of lactylation gene CALML5 and its correlated lncRNAs in cutaneous melanoma by machine learning

As a product of glycolysis, lactate contributes to cancer proliferation, immunosuppression, and metastasis via histone lactylation. However, the relationship between cutaneous melanoma (CM) and lactylation-associated genes and lncRNAs has remained unclear. In this study, 4 mechanism learning algorithms and integrated bioinformatic analyses were employed to identify the core lactylation-associated genes and lncRNAs. Subsequently, 2 risk signatures based on the hub lactylation-associated genes and lncRNAs were constructed for CM patients. As a result, CALML5 was identified as a core lactylation-associated gene in CM, and its expression was found to be associated with patients survival and immune infiltration, suggesting its relevance as a potential therapeutic target. Additionally, this study provided clarification on hub CALML5-associated lncRNAs in CM, offering insights into their roles in the disease. Meanwhile, 2 identified risk signatures were both strongly linked to the prognosis and cancer growth of CM, underscoring their potential as valuable prognostic indicators. Furthermore, mechanistic analyses suggested a significant association between the risk signature and the immune microenvironment in CM, highlighting potential immune-related implications in disease progression. In conclusion, we propose that lactylation-associated genes and lncRNAs hold promise as potential targets in CM. Moreover, our findings revealed a significant correlation between lactylation and the immune microenvironment, providing crucial insights for guiding individualized treatment strategies in CM.

Development of a Comprehensive Gene Signature Linking Hypoxia, Glycolysis, Lactylation, and Metabolomic Insights in Gastric Cancer through the Integration of Bulk and Single-Cell RNA-Seq Data

BACKGROUND

Hypoxia and anaerobic glycolysis are cancer hallmarks and sources of the metabolite lactate. Intriguingly, lactate-induced protein lactylation is considered a novel epigenetic mechanism that predisposes cells toward a malignant state. However, the significance of comprehensive hypoxia-glycolysis-lactylation-related genes (HGLRGs) in cancer is unclear. We aimed to construct a model centered around HGLRGs for predicting survival, metabolic features, drug responsiveness, and immune response in gastric cancer.

METHODS

The integration of bulk and single-cell RNA-Seq data was achieved using data obtained from the TCGA and GEO databases to analyze HGLRG expression patterns. A HGLRG risk-score model was developed based on univariate Cox regression and a LASSO-Cox regression model and subsequently validated. Additionally, the relationships between the identified HGLRG signature and multiple metabolites, drug sensitivity and various cell clusters were explored.

RESULTS

Thirteen genes were identified as constituting the HGLRG signature. Using this signature, we established predictive models, including HGLRG risk scores and nomogram and Cox regression models. The stratification of patients into high- and low-risk groups based on HGLRG risk scores showed a better prognosis in the latter. The high-risk group displayed increased sensitivity to cytotoxic drugs and targeted inhibitors. The expression of the HGLRG BGN displayed a strong correlation with amino acids and lipid metabolites. Notably, a significant difference in immune infiltration, such as that of M1 macrophages and CD8 T cells, was correlated with the HGLRG signature. The abundant DUSP1 within the mesenchymal components was highlighted by single-cell transcriptomics.

CONCLUSION

The innovative HGLRG signature demonstrates efficacy in predicting survival and providing a practical clinical model for gastric cancer. The HGLRG signature reflects the internal metabolism, drug responsiveness, and immune microenvironment components of gastric cancer and is expected to boost patients' response to targeted therapy and immunotherapy.

Histone lactylation regulates cancer progression by reshaping the tumor microenvironment

As a major product of glycolysis and a vital signaling molecule, many studies have reported the key role of lactate in tumor progression and cell fate determination. Lactylation is a newly discovered post-translational modification induced by lactate. On the one hand, lactylation introduced a new era of lactate metabolism in the tumor microenvironment (TME), and on the other hand, it provided a key breakthrough point for elucidation of the interaction between tumor metabolic reprogramming and epigenetic modification. Studies have shown that the lactylation of tumor cells, tumor stem cells and tumor-infiltrating immune cells in TME can participate in the development of cancer through downstream transcriptional regulation, and is a potential and promising tumor treatment target. This review summarized the discovery and effects of lactylation, as well as recent research on histone lactylation regulating cancer progression through reshaping TME. We also focused on new strategies to enhance anti-tumor effects via targeting lactylation. Finally, we discussed the limitations of existing studies and proposed new perspectives for future research in order to further explore lactylation targets. It may provide a new way and direction to improve tumor prognosis.

Advances in post-translational modifications of proteins and cancer immunotherapy

Protein post-translational modification (PTM) is a regulatory mechanism for protein activity modulation, localization, expression, and interactions with other cellular molecules. It involves the addition or removal of specific chemical groups on the amino acid residues of proteins. Its common forms include phosphorylation, ubiquitylation, methylation, and acetylation. Emerging research has highlighted lactylation, succinylation, and glycosylation. PTMs are involved in vital biological processes. The occurrence and development of diseases depends on protein abundance and is regulated by various PTMs. In addition, advancements in tumor immunotherapy have revealed that protein PTM is also involved in the proliferation, activation, and metabolic reprogramming of immune cells in tumor microenvironment. These PTMs play an important role in tumor immunotherapy. In this review, we comprehensively summarize the role of several types of PTMs in tumor immunotherapy. This review could provide new insights and future research directions for tumor immunotherapy.