Metabolic Compartmentalization at the Leading Edge of Metastatic Cancer Cells

Advances in mass spectrometry-based multi-scale metabolomic methodologies and their applications in biological and clinical investigations

Metabolomics is a nascent field of inquiry that emerged in the late 20th century. It encompasses the comprehensive profiling of metabolites across a spectrum of organisms, ranging from bacteria and cells to tissues. The rapid evolution of analytical methods and data analysis has greatly accelerated progress in this dynamic discipline over recent decades. Sophisticated techniques such as liquid chromatograph mass spectrometry (MS), gas chromatograph MS, capillary electrophoresis MS, and nuclear magnetic resonance serve as the cornerstone of metabolomic analysis. Building upon these methods, a plethora of modifications and combinations have emerged to propel the advancement of metabolomics. Despite this progress, scrutinizing metabolism at the single-cell or single-organelle level remains an arduous task over the decades. Some of the most thrilling advancements, such as single-cell and single-organelle metabolic profiling techniques, offer profound insights into the intricate mechanisms within cells and organelles. This allows for a comprehensive study of metabolic heterogeneity and its pivotal role in multiple biological processes. The progress made in MS imaging has enabled high-resolution in situ metabolic profiling of tissue sections and even individual cells. Spatial reconstruction techniques enable the direct representation of metabolic distribution and alteration in three-dimensional space. The application of novel metabolomic techniques has led to significant breakthroughs in biological and clinical studies, including the discovery of novel metabolic pathways, determination of cell fate in differentiation, anti-aging intervention through modulating metabolism, metabolomics-based clinicopathologic analysis, and surgical decision-making based on on-site intraoperative metabolic analysis. This review presents a comprehensive overview of both conventional and innovative metabolomic techniques, highlighting their applications in groundbreaking biological and clinical studies.

Onco-condensates: formation, multi-component organization, and biological functions

Numerous cellular processes occur in the context of condensates, a type of large, membrane-less biomolecular assembly generated through phase separation. These condensates function as a hub of diversified cellular events by concentrating the required components. Cancer frequently coopts biomolecular condensation mechanisms to promote survival and/or proliferation. Onco-condensates, which refer to those that have causal roles or are critically involved in tumorigenicity, operate to abnormally elevate biological output of a proliferative process, or to suppress a tumor-suppressive pathway, thereby promoting oncogenesis. Here, we summarize advances regarding how multi-component onco-condensates are established and organized to promote oncogenesis, with those related to chromatin and transcription deregulation used as showcases. A better understanding should enable development of new means of targeting onco-condensates as potential therapeutics.

Actin cytoskeletal dynamics do not impose an energy drain on growth cone bioenergetics

The regulation of the intracellular level of ATP is a fundamental aspect of bioenergetics. Actin cytoskeletal dynamics have been reported to be an energetic drain in developing neurons and platelets. We addressed the role of actin dynamics in primary embryonic chicken neurons using luciferase assays, and by measurement of the ATP/ADP ratio using the ratiometric reporter PercevalHR and the ATP level using the ratiometric reporter mRuby-iATPSnFR. None of the methods revealed an effect of suppressing actin dynamics on the decline in the neuronal ATP level or the ATP/ADP ratio following shutdown of ATP production. Similarly, we find that treatments that elevate or suppress actin dynamics do not alter the ATP/ADP ratio in growth cones, the subcellular domain with the highest actin dynamics in developing neurons. Collectively, the data indicate that actin cytoskeletal dynamics are not a significant energy drain in developing neurons and that the ATP/ADP ratio is maintained when energy utilization varies. Discrepancies between prior work and the current data are discussed with emphasis on methodology and interpretation of the data.

Monitoring Stress Response Difference in Nucleolus Morphology and ATP Content Changes during Hyperthermia Cell Apoptosis with Plasmonic Fluorescent Nanoprobes

The nucleolus, as a main "cellular stress receptor", is the hub of the stress response driving cancer development and has great research value in the field of organelle-targeting photothermal therapy. However, there are few studies focused on monitoring nucleolar stress response and revealing how the energy metabolism of cells regulates the nucleolar stress response during photothermal therapy. Herein, by designing a nucleolus-targeting and ATP- and photothermal-responsive plasmonic fluorescent nanoprobe (AuNRs-CDs) based on gold nanorods (AuNRs) and fluorescent carbon quantum dots (CDs), we achieved real-time fluorescence imaging of nucleus morphology while monitoring changes of ATP content at the subcellular level. We found that the green fluorescence diminished at 5 min of photothermal therapy, and the nucleolus morphology began to shrink and became smaller in cancerous HepG2 cells. In contrast, there is no significant change of green fluorescence in the nucleolar region of normal HL-7702 cells. ATP content monitoring also showed similar results. Apparently, in response to photothermal stimuli, cancerous cells produce more ATP (energy) along with obvious change in nucleolus morphology and state compared to normal cells under the hyperthermia-induced cell apoptosis. The developed AuNRs-CDs as a nucleolus imaging nanoprobe and effective photothermal agent present promising applications for nucleolar stress studies and targeted photothermal therapy.

Identification of a metabolism-related gene signature predicting overall survival for bladder cancer

Reprogramming of metabolism is becoming a novel hallmark of cancer. This study aims to perform bioinformatics analysis of metabolism-related genes in bladder cancer, and to construct a signature of metabolism-related genes for predicting the prognosis. A total of 373 differentially expressed metabolism-related genes were identified from TCGA database. Taking survival time and clinical information into consideration, we constructed a risk score to predict clinical prognosis. Low-risk patients had a better prognosis than high-risk patients. Multivariate analysis showed that risk score was an independent prognostic indicator in bladder cancer. ROC curve also proved that risk score had better ability to predict prognosis than other individual indicators. Nomogram also showed a clinical net benefit to evaluate the prognosis of bladder cancer patients. GSEA revealed several metabolism-related pathways that were differentially enriched in the high-risk and low-risk groups, which might help to explain the underlying mechanisms. This signature was confirmed to be an effective prognostic biomarker in bladder cancer.

Reduced serum high-density lipoprotein cholesterol levels and aberrantly expressed cholesterol metabolism genes in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a common malignant tumor of the gastrointestinal tract. Lipid metabolism, as an important part of material and energy circulation, is well known to play a crucial role in CRC.

AIM

To explore the relationship between serum lipids and CRC development and identify aberrantly expressed cholesterol metabolism genes in CRC.

METHODS

We retrospectively collected 843 patients who had confirmed CRC and received surgical resection from 2013 to 2015 at the Cancer Hospital of the Chinese Academy of Medical Sciences as our research subjects. The levels of serum total cholesterol (TC), triglycerides, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), LDL-C/HDL-C and clinical features were collected and statistically analyzed by SPSS. Then, we used the data from Oncomine to screen the differentially expressed genes (DEGs) of the cholesterol metabolism pathway in CRC and used Gene Expression Profiling Interactive Analysis to confirm the candidate DEGs. PrognoScan was used to analyze the prognostic value of the DEGs, and Search Tool for the Retrieval of Interacting Genes was used to construct the protein–protein interaction network of DEGs.

RESULTS

The serum HDL-C level in CRC patients was significantly correlated with tumor size, and patients whose tumor size was more than 5 cm had a lower serum HDL-C level (1.18 ± 0.41 mmol/L vs 1.25 ± 0.35 mmol/L, P < 0.01) than their counterparts. In addition, TC/HDL (4.19 ± 1.33 vs 3.93 ± 1.26, P < 0.01) and LDL-C/HDL-C (2.83 ± 1.10 vs 2.61 ± 0.96, P < 0.01) were higher in patients with larger tumors. The levels of HDL-C (P < 0.05), TC/HDL-C (P < 0.01) and LDL-C/HDL-C (P < 0.05) varied in different stages of CRC patients, and the differences were significant. We screened 14 differentially expressed genes (DEGs) of the cholesterol metabolism pathway in CRC and confirmed that lipoprotein receptor-related protein 8 (LRP8), PCSK9, low-density lipoprotein receptor (LDLR), MBTPS2 and FDXR are upregulated, while ABCA1 and OSBPL1A are downregulated in cancer tissue. Higher expression of LDLR (HR = 3.12, 95%CI: 1.77-5.49, P < 0.001), ABCA1 (HR = 1.66, 95%CI: 1.11-2.48, P = 0.012) and OSBPL1A (HR = 1.38, 95%CI: 1.01-1.89, P = 0.041) all yielded significantly poorer DFS outcomes. Higher expression of FDXR (HR = 0.7, 95%CI: 0.47-1.05, P = 0.002) was correlated with longer DFS. LDLR, ABCA1, OSBPL1A and FDXR were involved in many important cellular function pathways.

CONCLUSION

Serum HDL-C levels are associated with tumor size and stage in CRC patients. LRP8, PCSK9, LDLR, MBTPS2 and FDXR are upregulated, while ABCA1 and OSBPL1A are downregulated in CRC. Among them, LDLR, ABCA1, OSBPL1A and FDXR were valuable prognostic factors of DFS and were involved in important cellular function pathways.

SI-MOIRAI: A new method to identify and quantify the metabolic fate of nucleotides

Since the discovery of nucleotides over 100 years ago, extensive studies have revealed the importance of nucleotides for homeostasis, health, and disease. However, there remains no established method to investigate quantitively and accurately intact nucleotide incorporation into RNA and DNA. Herein, we report a new method, Stable-Isotope Measure Of Influxed Ribonucleic Acid Index (SI-MOIRAI), for the identification and quantification of the metabolic fate of ribonucleotides and their precursors. SI-MOIRAI, named after Greek goddesses of fate, combines a stable isotope-labeling flux assay with mass spectrometry to enable quantification of the newly synthesized ribonucleotides into r/m/tRNA under a metabolic stationary state. Using glioblastoma U87MG cells and a patient-derived xenograft (PDX) glioblastoma mouse model, SI-MOIRAI analyses showed that newly synthesized GTP was particularly and disproportionally highly utilized for rRNA and tRNA synthesis but not for mRNA synthesis in glioblastoma (GBM) in vitro and in vivo. Furthermore, newly synthesized pyrimidine nucleotides exhibited a significantly lower utilization rate for RNA synthesis than newly synthesized purine nucleotides. The results reveal the existence of discrete pathways and compartmentalization of purine and pyrimidine metabolism designated for RNA synthesis, demonstrating the capacity of SI-MOIRAI to reveal previously unknown aspects of nucleotide biology.