Targeting Cancer Metabolism and Current Anti-Cancer Drugs

Liang

et al. 2021

Journal of Oncology

Background. Clear cell renal cell carcinoma (ccRCC) is a cancer with abnormal metabolism. The purpose of this study was to investigate the effect of metabolism-related genes on the prognosis of ccRCC patients. Methods. The data of ccRCC patients were downloaded from the TCGA and the GEO databases and clustered using the nonnegative matrix factorization method. The limma software package was used to analyze differences in gene expression. A random forest model was used to screen for important genes. A novel Riskscore model was established using multivariate regression. The model was evaluated based on the metabolic pathway, immune infiltration, immune checkpoint, and clinical characteristics. Results. According to metabolism-related genes, kidney clear cell carcinoma (KIRC) datasets downloaded from TCGA were clustered into two groups and showed significant differences in prognosis and immune infiltration. There were 667 differentially expressed genes between the two clusters, of which 408 were screened by univariate analysis. Finally, 12 differentially expressed genes (MDK, SLC1A1, SGCB, C4orf3, MALAT1, PILRB, IGHG1, FZD1, IFITM1, MUC20, KRT80, and SALL1) were filtered out using the random forest model. The model of Riskscore was obtained by multiplying the expression levels of these 12 genes with the corresponding coefficients of the multivariate regression. We found that the Riskscore correlated with the expression of these 12 genes; the high Riskscore matched the low survival rate verified in the verification set. The analysis found that the Riskscore model was associated with most of the metabolic processes, immune infiltration of cells such as plasma cells, immune checkpoints such as PD-1, and clinical characteristics such as M stage. Conclusion. We established a new Riskscore model for the prognosis of ccRCC based on metabolism. The genes in the model provided several novel targets for the study of ccRCC.

Section: Introductionmentioning

confidence: 99%

“…The upregulation of glycolysis pathway genes is a central event in the pathogenesis of ccRCC [ 14 ]. The research and development of many anticancer drugs are aimed at the changes in these metabolic pathways [ 12 ]. Further studies on the changes in metabolism in ccRCC are needed.…”

Section: Introductionmentioning

confidence: 99%

Identification of Prognostic Metabolism-Related Genes in Clear Cell Renal Cell Carcinoma

Liang

et al. 2021

Journal of Oncology

“…The concentration of lactate is a determinant of the growth rate of organoids. A previous study showed that 5 mM lactate promoted the formation of organoids from cells derived from oral or colorectal tumors [ 24 , 36 ]. However, we found that concentrations lower than 20 mM had minimal effect on the growth of cell line organoids, and 5 mM lactate only slightly activated HIF1α/PI3K/AKT and had no effect on the expression of ENO1.…”

Section: Discussionmentioning

confidence: 99%

Lactate promotes the growth of patient-derived organoids from hepatopancreatobiliary cancers via ENO1/HIF1α pathway and does not affect their drug sensitivities

Wang

et al. 2022

Cell Death Discov.

The long culture duration of patient-derived organoids (PDOs) have severely limited their clinical applications. The aim of this study was to determine the effect of lactate supplementation on the growth, genetic profiles and drug sensitivities of PDOs from hepatopancreatobiliary tumors. LM3, Huh7, Panc02, and RBE cell lines were cultured as organoids in the presence or absence of lactate, and total protein was extracted to measure the expression of α-enolase (ENO1), hypoxia-inducible factor-1α (HIF1α), AKT, and PI3 kinase (PI3K). Thirteen hepatopancreatobiliary tumor specimens were collected during surgical resection and cultured as PDOs with or without l-lactate. Hematoxylin and eosin (H&E) staining and immunohistochemical staining were performed on the original tissues and PDOs to compare their pathological structures, and their genetic profiles were analyzed by whole-exome sequencing (WES). The sensitivity of the PDOs to gemcitabine, 5-fluorouracil, cisplatin, paclitaxel, ivosidenib, infigratinib, and lenvatinib were evaluated in terms of cell viability. Peripheral blood mononuclear cells (PBMCs) were isolated and co-cultured with PDOs to test the sensitivity of PDOs to tislelizumab. The addition of 20 mM lactate significantly promoted the growth of LM3 and Huh 7 organoids by 217% and 36%, respectively, compared to the control group, and the inhibition of lactate transporter decreased their growth. The HIF1α/ENO1/AKT/PI3K pathway was also activated by lactate. The inhibition of enolase also partly decreased the growth of organoids treated with lactate. Furthermore, 20 mM lactate increased the viability of 9 PDOs from 135% to 317% without affecting their pathological features. The genetic similarity, in terms of single nucleotide variations, insertions, and deletions, between original tissues and lactate-treated PDOs ranged from 83.2% to 94.1%, and that between the untreated and lactate-treated PDOs was at least 93.2%. Furthermore, the addition of lactate did not significantly change the dose–response curves of the PDOs to chemotherapeutic drugs, targeted drugs, and immune checkpoint inhibitor, especially for the drugs to which the cells were sensitive. Thus, lactate can be added to the culture medium of PDOs to promote their growth without altering their genetic profiles and drug sensitivities.

“…By inhibiting the key enzymes in folate metabolism, drugs such as MTX induce folic acid deficiency, hindering DNA synthesis and cell division [72]. Today, numerous metabolism-based anti-cancer approaches exist, either already applied in therapeutic regimes, or being tested in clinical and preclinical studies (Figure 3) [73,74].…”

Section: Current Metabolism-based Therapeutic Strategiesmentioning

confidence: 99%

The Neglected Liaison: Targeting Cancer Cell Metabolic Reprogramming Modifies the Composition of Non-Malignant Populations of the Tumor Microenvironment

Iorio

Ganesh

Luise

et al. 2021

Cancers

Metabolic reprogramming is a well-known hallmark of cancer, whereby the development of drugs that target cancer cell metabolism is gaining momentum. However, when establishing preclinical studies and clinical trials, it is often neglected that a tumor mass is a complex system in which cancer cells coexist and interact with several types of microenvironment populations, including endothelial cells, fibroblasts and immune cells. We are just starting to understand how such populations are affected by the metabolic changes occurring in a transformed cell and little is known about the impact of metabolism-targeting drugs on the non-malignant tumor components. Here we provide a general overview of the links between cancer cell metabolism and tumor microenvironment (TME), particularly focusing on the emerging literature reporting TME-specific effects of metabolic therapies.