Complex Alterations of Fatty Acid Metabolism and Phospholipidome Uncovered in Isolated Colon Cancer Epithelial Cells

The Utility of Lipidomic Analysis in Colorectal Cancer Diagnosis and Prognosis-A Systematic Review of Recent Literature

Colorectal cancer (CRC) is among the most prevalent and lethal malignancies. Lipidomic investigations have revealed numerous disruptions in lipid profiles across various cancers. Studies on CRC exhibit potential for identifying novel diagnostic or prognostic indicators through lipidomic signatures. This review examines recent literature regarding lipidomic markers for CRC. PubMed database was searched for eligible articles concerning lipidomic biomarkers of CRC. After selection, 36 articles were included in the review. Several studies endeavor to establish sets of lipid biomarkers that demonstrate promising potential to diagnose CRC based on blood samples. Phosphatidylcholine, phosphatidylethanolamine, ceramides, and triacylglycerols (TAGs) appear to offer the highest diagnostic accuracy. In tissues, lysophospholipids, ceramides, and TAGs were among the most altered lipids, while unsaturated fatty acids also emerged as potential biomarkers. In-depth analysis requires both cell culture and animal studies. CRC involves multiple lipid metabolism alterations. Although numerous lipid species have been suggested as potential diagnostic markers, the establishment of standardized methods and the conduct of large-scale studies are necessary to facilitate their clinical application.

UHPLC-HRMS-based Multiomics to Explore the Potential Mechanisms and Biomarkers for Colorectal Cancer

BACKGROUND

Understanding the metabolic changes in colorectal cancer (CRC) and exploring potential diagnostic biomarkers is crucial for elucidating its pathogenesis and reducing mortality. Cancer cells are typically derived from cancer tissues and can be easily obtained and cultured. Systematic studies on CRC cells at different stages are still lacking. Additionally, there is a need to validate our previous findings from human serum.

METHODS

Ultrahigh-performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS)-based metabolomics and lipidomics were employed to comprehensively measure metabolites and lipids in CRC cells at four different stages and serum samples from normal control (NR) and CRC subjects. Univariate and multivariate statistical analyses were applied to select the differential metabolites and lipids between groups. Biomarkers with good diagnostic efficacy for CRC that existed in both cells and serum were screened by the receiver operating characteristic curve (ROC) analysis. Furthermore, potential biomarkers were validated using metabolite standards.

RESULTS

Metabolite and lipid profiles differed significantly among CRC cells at stages A, B, C, and D. Dysregulation of glycerophospholipid (GPL), fatty acid (FA), and amino acid (AA) metabolism played a crucial role in the CRC progression, particularly GPL metabolism dominated by phosphatidylcholine (PC). A total of 46 differential metabolites and 29 differential lipids common to the four stages of CRC cells were discovered. Eight metabolites showed the same trends in CRC cells and serum from CRC patients compared to the control groups. Among them, palmitoylcarnitine and sphingosine could serve as potential biomarkers with the values of area under the curve (AUC) more than 0.80 in the serum and cells. Their panel exhibited excellent performance in discriminating CRC cells at different stages from normal cells (AUC = 1.00).

CONCLUSIONS

To our knowledge, this is the first research to attempt to validate the results of metabolism studies of serum from CRC patients using cell models. The metabolic disorders of PC, FA, and AA were closely related to the tumorigenesis of CRC, with PC being the more critical factor. The panel composed of palmitoylcarnitine and sphingosine may act as a potential biomarker for the diagnosis of CRC, aiding in its prevention.

Orchestral role of lipid metabolic reprogramming in T-cell malignancy

The immune function of normal T cells partially depends on the maneuvering of lipid metabolism through various stages and subsets. Interestingly, T-cell malignancies also reprogram their lipid metabolism to fulfill bioenergetic demand for rapid division. The rewiring of lipid metabolism in T-cell malignancies not only provides survival benefits but also contributes to their stemness, invasion, metastasis, and angiogenesis. Owing to distinctive lipid metabolic programming in T-cell cancer, quantitative, qualitative, and spatial enrichment of specific lipid molecules occur. The formation of lipid rafts rich in cholesterol confers physical strength and sustains survival signals. The accumulation of lipids through de novo synthesis and uptake of free lipids contribute to the bioenergetic reserve required for robust demand during migration and metastasis. Lipid storage in cells leads to the formation of specialized structures known as lipid droplets. The inimitable changes in fatty acid synthesis (FAS) and fatty acid oxidation (FAO) are in dynamic balance in T-cell malignancies. FAO fuels the molecular pumps causing chemoresistance, while FAS offers structural and signaling lipids for rapid division. Lipid metabolism in T-cell cancer provides molecules having immunosuppressive abilities. Moreover, the distinctive composition of membrane lipids has implications for immune evasion by malignant cells of T-cell origin. Lipid droplets and lipid rafts are contributors to maintaining hallmarks of cancer in malignancies of T cells. In preclinical settings, molecular targeting of lipid metabolism in T-cell cancer potentiates the antitumor immunity and chemotherapeutic response. Thus, the direct and adjunct benefit of lipid metabolic targeting is expected to improve the clinical management of T-cell malignancies.

Metabolically Active Zones Involving Fatty Acid Elongation Delineated by DESI-MSI Correlate with Pathological and Prognostic Features of Colorectal Cancer

Colorectal cancer (CRC) is the second leading cause of cancer deaths. Despite recent advances, five-year survival rates remain largely unchanged. Desorption electrospray ionization mass spectrometry imaging (DESI) is an emerging nondestructive metabolomics-based method that retains the spatial orientation of small-molecule profiles on tissue sections, which may be validated by ‘gold standard’ histopathology. In this study, CRC samples were analyzed by DESI from 10 patients undergoing surgery at Kingston Health Sciences Center. The spatial correlation of the mass spectral profiles was compared with histopathological annotations and prognostic biomarkers. Fresh frozen sections of representative colorectal cross sections and simulated endoscopic biopsy samples containing tumour and non-neoplastic mucosa for each patient were generated and analyzed by DESI in a blinded fashion. Sections were then hematoxylin and eosin (H and E) stained, annotated by two independent pathologists, and analyzed. Using PCA/LDA-based models, DESI profiles of the cross sections and biopsies achieved 97% and 75% accuracies in identifying the presence of adenocarcinoma, using leave-one-patient-out cross validation. Among the m/z ratios exhibiting the greatest differential abundance in adenocarcinoma were a series of eight long-chain or very-long-chain fatty acids, consistent with molecular and targeted metabolomics indicators of de novo lipogenesis in CRC tissue. Sample stratification based on the presence of lympovascular invasion (LVI), a poor CRC prognostic indicator, revealed the abundance of oxidized phospholipids, suggestive of pro-apoptotic mechanisms, was increased in LVI-negative compared to LVI-positive patients. This study provides evidence of the potential clinical utility of spatially-resolved DESI profiles to enhance the information available to clinicians for CRC diagnosis and prognosis.

Hypoxia increases cellular levels of phosphatidic acid and lysophospholipids in undifferentiated Caco-2 cells

Cancer cells are known to survive in a hypoxic microenvironment by altering their lipid metabolism as well as their energy metabolism. In this study, Caco-2 cells derived from human colon cancer, were found to have elevated intracellular levels of phosphatidic acid and its lysoform, lysophosphatidic acid (LPA), under hypoxic conditions. Our results suggested that the elevation of LPA in Caco-2 cells was mainly due to the combined increases in cellular levels of lysophosphatidylcholine and lysophosphatidylethanolamine by phospholipase A₂ and subsequent hydrolysis to LPA by lysophospholipase D. We detected the Ca²⁺ -stimulated choline-producing activities toward exogenous lysophosphatidylcholines in whole Caco-2 cell homogenates, indicating their involvement in the LPA production in intact Caco-2 cells.

Emerging roles of polyunsaturated fatty acid synthesis pathway in colorectal cancer

The development of colorectal cancer typically involves the accumulated influences of genetic alterations, medical issues, lifestyle, and diet. Dietary fatty acids appear to affect the tumorigenesis and progression of colorectal cancer. Despite conflicting results, the current consensus on the effects of very long-chain polyunsaturated fatty acids on colorectal cancer is that low levels of eicosapentaenoic acid and docosahexaenoic acid, and high levels of arachidonic acid are associated with an increased risk of colorectal cancer. Altered levels of arachidonic acid in membrane phospholipids can change the levels of prostaglandin E₂, which affect the biological activities of cancer cells in multiple stages. Arachidonic acid and other very long-chain polyunsaturated fatty acids can affect tumorigenesis in prostaglandin E₂-independent manners as well, including stabilization of β-catenine, ferroptosis, ROS generation, regulation of transcription factors, and de novo lipogenesis. Recent studies have revealed an association between the activities of enzymes synthesizing very long-chain polyunsaturated fatty acids and tumorigenesis and cancer progression, although the mechanisms are still unknown. In this study, PUFA effects on tumorigenesis, the endogenous very long-chain polyunsaturated fatty acid synthesis pathway, metabolites of arachidonic acid and their effects on tumorigenesis and progression of CRC, and current knowledge that supports the association of the enzymes involved in the polyunsaturated fatty acid synthesis pathway with colorectal cancer tumorigenesis and progression are reviewed.

A novel enterocyte-related 4-gene signature for predicting prognosis in colon adenocarcinoma

Background

Colon adenocarcinoma (COAD) is a fatal disease, and its cases are constantly increasing worldwide. Further, the therapeutic and management strategies for patients with COAD are still unsatisfactory due to the lack of accurate patient classification and prognostic models. Therefore, our study aims to identify prognostic markers in patients with COAD and construct a cell subtype-specific prognostic model with high accuracy and robustness.

Methods

Single-cell transcriptomic data of six samples were retrieved from the Gene expression omnibus (GEO) database. The cluster annotation and cell-cell communication analysis identified enterocytes as a key player mediating signal communication networks. A four-gene signature prognostic model was constructed based on the enterocyte-related differentially expressed genes (ERDEGs) in patients with COAD of the Cancer Genome Atlas cohort. The prognostic model was validated on three external validation cohorts from the GEO database. The correlation between immune cell infiltration, immunotherapy response, drug sensitivity, and the four-gene signature prognostic model was investigated. Finally, immunohistochemistry (IHC) was performed to determine the expression of the four genes.

Results

We found that the proportion of epithelial cells was obviously large in COAD samples. Further analysis of epithelial cells showed that the activity of the enterocytes was highest in the cell-cell communication network. Based on enterocyte data, 30 ERDEGs were identified and a 4-gene prognostic model including CPM, CLCA4, ELOVL6, and ATP2A3 was developed and validated. The risk score derived from this model was considered as an independent variable factor to predict overall survival. The patients were divided into high- and low-risk groups based on the median riskscore value. The correlation between immune cell infiltration, immunotherapy response, immune status, clinical characteristics, drug sensitivity, and risk score was analyzed. IHC confirmed the expression of signature genes in tissues from normal individuals, patients with polyps, and COAD.

Conclusion

In this study, we constructed and validated a novel four-gene signature prognostic model, which could effectively predict the response to immunotherapy and overall survival in patients with COAD. More importantly, this model provides useful insight into the management of colon cancer patients and aids in designing personalized therapy.

Understanding the versatile roles and applications of EpCAM in cancers: from bench to bedside

Epithelial cell adhesion molecule (EpCAM) functions not only in physiological processes but also participates in the development and progression of cancer. In recent decades, extensive efforts have been made to decipher the role of EpCAM in cancers. Great advances have been achieved in elucidating its structure, molecular functions, pathophysiological mechanisms, and clinical applications. Beyond its well-recognized role as a biomarker of cancer stem cells (CSCs) or circulating tumor cells (CTCs), EpCAM exhibits novel and promising value in targeted therapy. At the same time, the roles of EpCAM in cancer progression are found to be highly context-dependent and even contradictory in some cases. The versatile functional modules of EpCAM and its communication with other signaling pathways complicate the study of this molecule. In this review, we start from the structure of EpCAM and focus on communication with other signaling pathways. The impacts on the biology of cancers and the up-to-date clinical applications of EpCAM are also introduced and summarized, aiming to shed light on the translational prospects of EpCAM.

Fat Checking: Emerging Role of Lipids in Metabolism and Disease

Lipids are hydrophobic molecules involved in a plethora of biological functions; for example, they are employed for the storage of energy, serve as essential constituents of cell membranes and participate in the assembly of bilayer configuration [...].

Rapid Evaporative Ionization Mass Spectrometry-Based Lipidomics for Identification of Canine Mammary Pathology

The present work proposes the use of a fast analytical platform for the mass spectrometric (MS) profiling of canine mammary tissues in their native form for the building of a predictive statistical model. The latter could be used as a novel diagnostic tool for the real-time identification of different cellular alterations in order to improve tissue resection during veterinary surgery, as previously validated in human oncology. Specifically, Rapid Evaporative Ionization Mass Spectrometry (REIMS) coupled with surgical electrocautery (intelligent knife—iKnife) was used to collect MS data from histologically processed mammary samples, classified into healthy, hyperplastic/dysplastic, mastitis and tumors. Differences in the lipid composition enabled tissue discrimination with an accuracy greater than 90%. The recognition capability of REIMS was tested on unknown mammary samples, and all of them were correctly identified with a correctness score of 98–100%. Triglyceride identification was increased in healthy mammary tissues, while the abundance of phospholipids was observed in altered tissues, reflecting morpho-functional changes in cell membranes, and oxidized species were also tentatively identified as discriminant features. The obtained lipidomic profiles represented unique fingerprints of the samples, suggesting that the iKnife technique is capable of differentiating mammary tissues following chemical changes in cellular metabolism.

A novel fatty acid metabolism-related gene signature predicts the prognosis, tumor immune properties, and immunotherapy response of colon adenocarcinoma patients

Colon adenocarcinoma (COAD) has a high incidence and death rate. Despite the fact that change in fatty acid metabolism promotes tumor growth and metastasis to the greatest degree among metabolite profiles, a thorough investigation on the involvement of fatty acid metabolism-related genes (FAMRGs) in COAD has yet not been conducted. Here, the clinical data as well as the gene expression profiles were extracted from The Cancer Genome Atlas (TCGA) database. Based on the FAMRG expression data and clinical information, a FAMRG risk signature was developed using LASSO as well as multivariate and univariate Cox regression analyses. Then, the nomogram was used to create a customized prognostic prediction model, and the calibration and receiver operating characteristic curves were used to evaluate the nomogram's prediction performance and discriminative capability. Lastly, a number of studies were conducted to assess the influence of independent FAMRGs on COAD, including unsupervised cluster analysis, functional analysis, and drug sensitivity analysis. Three hundred and sixty-seven patients were included in this study, and a 12-FAMRG risk signature was discovered in the training cohort based on a detailed examination of the FAMRGs expression data and clinical information. After that, risk scores were computed to classify patients into low or high-risk groups, and the Kaplan-Meier curve analysis revealed that patients in the low-risk group exhibited an elevated overall survival (OS) rate. The FAMRG was shown to be substantially correlated with prognosis in multivariate Cox regression analysis and was validated using the validation dataset. Then, using the clinical variables and risk signature, we developed and validated a prediction nomogram for OS. Functional characterization showed a strong correlation between this signature and immune cell infiltration and immune modulation. Additionally, by evaluating the GDSC database, it was determined that the high-risk group exhibited medication resistance to many chemotherapeutic and targeted medicines, including VX.680, gemcitabine, doxorubicin, and paclitaxel. Overall, we have revealed the significance of a FAMRG risk signature for predicting the prognosis and response to immunotherapy in COAD, and our findings might contribute to an enhanced comprehension of metabolic pathways and the future development of innovative COAD therapeutic methods.

Inhibition of Aryl Hydrocarbon Receptor (AhR) Expression Disrupts Cell Proliferation and Alters Energy Metabolism and Fatty Acid Synthesis in Colon Cancer Cells

Simple Summary

Cancer cells undergo metabolic modifications in order to meet their high energetic demand. The aryl hydrocarbon receptor (AhR) is a ligand-activated transcriptional factor primarily known as a xenobiotic sensor. However, this receptor seems to have a wide range of physiological roles in many processes including cell proliferation, migration or control of immune responses. AhR is often overexpressed in tumor cells of various tissue origin, and several studies have indicated that AhR may also contribute to regulation of cellular metabolism, including synthesis of fatty acids (FA), one of the major steps in metabolic transition. Potential links between the AhR and the control of tumor cell proliferation and metabolism thus deserve more attention.

Abstract

The aryl hydrocarbon receptor (AhR) plays a wide range of physiological roles in cellular processes such as proliferation, migration or control of immune responses. Several studies have also indicated that AhR might contribute to the regulation of energy balance or cellular metabolism. We observed that the AhR is upregulated in tumor epithelial cells derived from colon cancer patients. Using wild-type and the corresponding AhR knockout (AhR KO) variants of human colon cancer cell lines HCT116 and HT-29, we analyzed possible role(s) of the AhR in cell proliferation and metabolism, with a focus on regulation of the synthesis of fatty acids (FAs). We observed a decreased proliferation rate in the AhR KO cells, which was accompanied with altered cell cycle progression, as well as a decreased ATP production. We also found reduced mRNA levels of key enzymes of the FA biosynthetic pathway in AhR KO colon cancer cells, in particular of stearoyl-CoA desaturase 1 (SCD1). The loss of AhR was also associated with reduced expression and/or activity of components of the PI3K/Akt pathway, which controls lipid metabolism, and other lipogenic transcriptional regulators, such as sterol regulatory element binding transcription factor 1 (SREBP1). Together, our data indicate that disruption of AhR activity in colon tumor cells may, likely in a cell-specific manner, limit their proliferation, which could be linked with a suppressive effect on their endogenous FA metabolism. More attention should be paid to potential mechanistic links between overexpressed AhR and colon tumor cell metabolism.

Single-Cell RNA Sequencing Reveals the Role of Epithelial Cell Marker Genes in Predicting the Prognosis of Colorectal Cancer Patients

Single-cell RNA sequencing (scRNA-seq) is increasingly used in studies on gastrointestinal cancers. This study investigated the prognostic value of epithelial cell-associated biomarkers in colorectal cancer (CRC) using scRNA-seq data. We downloaded and analysed scRNA-seq data from four CRC samples from the Gene Expression Omnibus (GEO), and we identified marker genes of malignant epithelial cells (MECs) using CRC transcriptome and clinical data downloaded from The Cancer Genome Atlas (TCGA) and GEO as training and validation cohorts, respectively. In the TCGA training cohort, weighted gene correlation network analysis, univariate Cox proportional hazard model (Cox) analysis, and least absolute shrinkage and selection operator regression analysis were performed on the marker genes of MEC subsets to identify a signature of nine prognostic MEC-related genes (MECRGs) and calculate a risk score based on the signature. CRC patients were divided into high- and low-risk groups according to the median risk score. We found that the MECRG risk score was significantly correlated with the clinical features and overall survival of CRC patients, and that CRC patients in the high-risk group showed a significantly shorter survival time. The univariate and multivariate Cox regression analyses showed that the MECRG risk score can serve as an independent prognostic factor for CRC patients. Gene set enrichment analysis revealed that the MECRG signature genes are involved in fatty acid metabolism, p53 signalling, and other pathways. To increase the clinical application value, we constructed a MECRG nomogram by combining the MECRG risk score with other independent prognostic factors. The validity of the nomogram is based on receiver operating characteristics and calibration curves. The MECRG signature and nomogram models were well validated in the GEO dataset. In conclusion, we established an epithelial cell marker gene-based risk assessment model based on scRNA-seq analysis of CRC samples for predicting the prognosis of CRC patients.

Identification of a Prognostic Model Based on Fatty Acid Metabolism-Related Genes of Head and Neck Squamous Cell Carcinoma

The fatty acid metabolism (FAM) is known to impact tumorigenesis, tumor progression and treatment resistance via enhancing lipid synthesis, storage and catabolism. However, the role of FAM in head and neck squamous cell carcinoma (HNSCC) has remained elusive. In the present study, we obtained a total of 69 differentially expressed FAM-related genes between 502 HNSCC samples and 44 normal samples from The Cancer Genome Atlas (TCGA) database. The HNSCC samples were divided into 2 clusters according to 69 differentially expressed genes (DEGs) via cluster analysis. Then DEGs in the two clusters were found, and 137 prognostic DEGs were identified by univariate analysis. Subsequently, combined with the clinical information of 546 HNSCC patients from TCGA database, a 12-gene prognostic risk model was established (FEPHX3, SPINK7, FCRLA, MASP1, ZNF541, CD5, BEST2 and ZAP70 were down-regulation, ADPRHL1, DYNC1I1, KCNG1 and LINC00460 were up-regulation) using multivariate Cox regression and LASSO regression analysis. The risk scores of 546 HNSCC samples were calculated. According to the median risk score, 546 HNSCC patients were divided into the high- and low-risk (high- and low score) groups. The Kaplan-Meier survival analysis showed that the survival time of HNSCC patients was significantly shorter in the high-risk group than that in the low-risk group (p < 0.001). The same conclusion was obtained in the Gene Expression Omnibus (GEO) dataset. After that, the multivariate Cox regression analysis indicated that the risk score was an independent factor for patients with HNSCC in the TCGA cohort. In addition, single-sample gene set enrichment analysis (ssGSEA) indicated that the level of infiltrating immune cells was relatively low in the high-risk group compared with the low-risk group. In summary, FAM-related gene expression-based risk signature could predict the prognosis of HNSCC independently.

Discovery of Synergistic Drug Combinations for Colorectal Cancer Driven by Tumor Barcode Derived from Metabolomics “Big Data”

The accumulation of cancer metabolomics data in the past decade provides exceptional opportunities for deeper investigations into cancer metabolism. However, integrating a large amount of heterogeneous metabolomics data to draw a full picture of the metabolic reprogramming and to discover oncometabolites of certain cancers remains challenging. In this study, a tumor barcode constructed based upon existing metabolomics “big data” using the Bayesian vote-counting method is proposed to identify oncometabolites in colorectal cancer (CRC). Specifically, a panel of oncometabolites of CRC was generated from 39 clinical studies with 3202 blood samples (1332 CRC vs. 1870 controls) and 990 tissue samples (495 CRC vs. 495 controls). Next, an oncometabolite-protein network was constructed by combining the tumor barcode and its involved proteins/enzymes. The effect of anti-cancer drugs or drug combinations was then mapped into this network by the random walk with restart process. Utilizing this network, potential Irinotecan (CPT-11)-sensitizing agents for CRC treatment were discovered by random forest and Xgboost. Finally, a compound named MK-2206 was highlighted and its synergy with CPT-11 was validated on two CRC cell lines. To summarize, we demonstrate in the present study that the metabolomics “big data”-based tumor barcodes and the subsequent network analyses are potentially useful for drug combination discovery or drug repositioning.

Genetic variation at the catalytic subunit of glutamate cysteine ligase contributes to the susceptibility to sporadic colorectal cancer: a pilot study

BACKGROUND

Glutathione is a tripeptide detoxifying a variety of exogenous and endogenous free radicals and carcinogens, and a deficiency of glutathione is associated with an increased host susceptibility to oxidative stress, a pathological condition implicated in the development and progression of cancer. The catalytic subunit of glutamate-cysteine ligase (GCLC) is an enzyme responsible for the initial and rate-limiting step of glutathione biosynthesis.

METHODS AND RESULTS

The aim of this pilot study was to investigate whether genetic variation at the GCLC gene contributes to the risk of colorectal cancer (CRC). DNA samples from 681 unrelated Russian individuals (283 patients with CRC and 398 age- and sex-matched healthy controls) were genotyped for six common functional SNPs of the GCLC gene (SNPs) such as rs12524494, rs17883901, rs606548, rs636933, rs648595 and rs761142 of the GCLC gene using the MassARRAY-4 system. We found that genotype rs606548-C/T is significantly associated with increased risk of CRC regardless of sex and age (OR 2.24; 95% CI 1.24-4.03; P = 0.007, FDR = 0.04). Moreover, ten GCLC genotype combinations showed association with the risk of CRC (P < 0.05). Functional SNP annotation enabled establishing the CRC-associated polymorphisms are associated with a decreased GCLC expression that may be attributed to epigenetic effects of histone modifications operating in a colon-specific manner.

CONCLUSIONS

The present study was the first to show that genetic variation at the catalytic subunit of glutamate-cysteine ligase may contribute to the risk of colorectal cancer risk. However, further genetic association studies with a larger sample size are required to substantiate the role of GCLC gene polymorphisms in the development of sporadic colorectal cancer.

The dysregulation of unsaturated fatty acid-based metabolomics in the MNNG-induced malignant transformation of Het-1A cells

Studies have shown that environmental carcinogens exerted an important function in the high incidence of esophageal cancer (EC). Nitrosamines have been identified as important environmental carcinogens for EC. This study aimed to investigate the metabolic disturbances and new key toxicological markers in the malignant transformation process of normal esophageal epithelial cells (Het-1A) induced by MNNG (N-methyl-N'-nitro-N-nitrosoguanidine). Untargeted metabolomic and lipidomic profiling analysis by using ultra-high-performance liquid chromatography coupled with mass spectrometry (UHPLC-MS) were applied to explore the metabolic network alterations of Het-1A cells. The metabolomic results showed that significant alterations were observed in metabolic signatures between different generations (P5, P15, P25, P35) and the control cell group (P0). A total of 48 differential endogenous metabolites were screened and identified, mainly containing fatty acids, amino acids, and nucleotides. The differential metabolites were predominantly linked to the pathway of biosynthesis of unsaturated fatty acids metabolism. The cell lipidomic profiling revealed that the most differential lipids contained fatty acids (FAs), phosphatidylcholines (PC), phosphatidylethanolamines (PE), and phosphatidylserines (PS). The enrichment of the lipidomic pathway also confirmed that the lipid metabolism of biosynthesis of unsaturated fatty acids was the significant variation during the cell malignant transformation. Furthermore, we detected the expression of the upstream regulatory enzymes related to the unsaturated fatty acids to explore the regulation mechanism. The expression of stearoyl-CoA desaturase (SCD), ELOVL fatty acid elongase 1 (ELOVL1) promoted, and fatty acid desaturase 1 (FADS1) inhibited the key fatty acids of unsaturated fatty acids metabolism compared to the control cell group. Overall, our results revealed that lipid fatty acid metabolism was involved in the malignant transformation of Het-1A cells induced by MNNG and deepened the awareness of the carcinogenic mechanism of environmental exposure pollutants.

Lipid Metabolism Interplay in CRC—An Update

Colorectal cancer (CRC) to date still ranks as one of the deadliest cancer entities globally, and despite recent advances, the incidence in young adolescents is dramatically increasing. Lipid metabolism has recently received increased attention as a crucial element for multiple aspects of carcinogenesis and our knowledge of the underlying mechanisms is steadily growing. However, the mechanism how fatty acid metabolism contributes to CRC is still not understood in detail. In this review, we aim to summarize our vastly growing comprehension and the accompanied complexity of cellular fatty acid metabolism in CRC by describing inputs and outputs of intracellular free fatty acid pools and how these contribute to cancer initiation, disease progression and metastasis. We highlight how different lipid pathways can contribute to the aggressiveness of tumors and affect the prognosis of patients. Furthermore, we focus on the role of lipid metabolism in cell communication and interplay within the tumor microenvironment (TME) and beyond. Understanding these interactions in depth might lead to the discovery of novel markers and new therapeutic interventions for CRC. Finally, we discuss the crucial role of fatty acid metabolism as new targetable gatekeeper in colorectal cancer.

Multi-Omics Prognostic Signatures Based on Lipid Metabolism for Colorectal Cancer

Background: The potential biological processes and laws of the biological components in malignant tumors can be understood more systematically and comprehensively through multi-omics analysis. This study elaborately explored the role of lipid metabolism in the prognosis of colorectal cancer (CRC) from the metabonomics and transcriptomics.

Methods: We performed K-means unsupervised clustering algorithm and t test to identify the differential lipid metabolites determined by liquid chromatography tandem mass spectrometry (LC-MS/MS) in the serum of 236 CRC patients of the First Hospital of Jilin University (JLUFH). Cox regression analysis was used to identify prognosis-associated lipid metabolites and to construct multi-lipid-metabolite prognostic signature. The composite nomogram composed of independent prognostic factors was utilized to individually predict the outcome of CRC patients. Glycerophospholipid metabolism was the most significant enrichment pathway for lipid metabolites in CRC, whose related hub genes (GMRHGs) were distinguished by gene set variation analysis (GSVA) and weighted gene co-expression network analysis (WGCNA). Cox regression and least absolute shrinkage and selection operator (LASSO) regression analysis were utilized to develop the prognostic signature.

Results: Six-lipid-metabolite and five-GMRHG prognostic signatures were developed, indicating favorable survival stratification effects on CRC patients. Using the independent prognostic factors as variables, we established a composite nomogram to individually evaluate the prognosis of CRC patients. The AUCs of one-, three-, and five-year ROC curves were 0.815, 0.815, and 0.805, respectively, showing auspicious prognostic accuracy. Furthermore, we explored the potential relationship between tumor microenvironment (TME) and immune infiltration. Moreover, the mutational frequency of TP53 in the high-risk group was significantly higher than that in the low-risk group (p < 0.001), while in the coordinate mutational status of TP53, the overall survival of CRC patients in the high-risk group was significantly lower than that in low-risk group with statistical differences.

Conclusion: We identified the significance of lipid metabolism for the prognosis of CRC from the aspects of metabonomics and transcriptomics, which can provide a novel perspective for promoting individualized treatment and revealing the potential molecular biological characteristics of CRC. The composite nomogram including a six-lipid-metabolite prognostic signature is a promising predictor of the prognosis of CRC patients.

T-Cell-Specific CerS4 Depletion Prolonged Inflammation and Enhanced Tumor Burden in the AOM/DSS-Induced CAC Model

To better understand the role of sphingolipids in the multifactorial process of inflammatory bowel disease (IBD), we elucidated the role of CerS4 in colitis and colitis-associated cancer (CAC). For this, we utilized the azoxymethane/dextran sodium sulphate (AOM/DSS)-induced colitis model in global CerS4 knockout (CerS4 KO), intestinal epithelial (CerS4 Vil/Cre), or T-cell restricted knockout (CerS4 LCK/Cre) mice. CerS4 KO mice were highly sensitive to the toxic effect of AOM/DSS, leading to a high mortality rate. CerS4 Vil/Cre mice had smaller tumors than WT mice. In contrast, CerS4 LCK/Cre mice frequently suffered from pancolitis and developed more colon tumors. In vitro, CerS4-depleted CD8+ T-cells isolated from the thymi of CerS4 LCK/Cre mice showed impaired proliferation and prolonged cytokine production after stimulation in comparison with T-cells from WT mice. Depletion of CerS4 in human Jurkat T-cells led to a constitutively activated T-cell receptor and NF-κB signaling pathway. In conclusion, the deficiency of CerS4 in T-cells led to an enduring active status of these cells and prevents the resolution of inflammation, leading to a higher tumor burden in the CAC mouse model. In contrast, CerS4 deficiency in epithelial cells resulted in smaller colon tumors and seemed to be beneficial. The higher tumor incidence in CerS4 LCK/Cre mice and the toxic effect of AOM/DSS in CerS4 KO mice exhibited the importance of CerS4 in other tissues and revealed the complexity of general targeting CerS4.

The Crosstalk Between Signaling Pathways and Cancer Metabolism in Colorectal Cancer

Colorectal cancer (CRC) is one of the most frequently diagnosed cancers worldwide. Metabolic reprogramming represents an important cancer hallmark in CRC. Reprogramming core metabolic pathways in cancer cells, such as glycolysis, glutaminolysis, oxidative phosphorylation, and lipid metabolism, is essential to increase energy production and biosynthesis of precursors required to support tumor initiation and progression. Accumulating evidence demonstrates that activation of oncogenes and loss of tumor suppressor genes regulate metabolic reprogramming through the downstream signaling pathways. Protein kinases, such as AKT and c-MYC, are the integral components that facilitate the crosstalk between signaling pathways and metabolic pathways in CRC. This review provides an insight into the crosstalk between signaling pathways and metabolic reprogramming in CRC. Targeting CRC metabolism could open a new avenue for developing CRC therapy by discovering metabolic inhibitors and repurposing protein kinase inhibitors/monoclonal antibodies.