A pan-cancer transcriptomic study showing tumor specific alterations in central metabolism

TBK1 Reprograms Metabolism in Breast Cancer: An Integrated Omics Approach

Metabolic rewiring is required for cancer cells to survive in harsh microenvironments and is considered to be a hallmark of cancer. Specific metabolic adaptations are required for a tumor to become invasive and metastatic. Cell division and metabolism are inherently interconnected, and several cell cycle modulators directly regulate metabolism. Here, we report that TBK1, which is a noncanonical IKK kinase with known roles in cell cycle regulation and TLR signaling, affects cellular metabolism in cancer cells. While TBK1 is reported to be overexpressed in several cancers and its enhanced protein level correlates with poor prognosis, the underlying molecular mechanism involved in the tumor-promoting role of TBK1 is not fully understood. In this study, we show a novel role of TBK1 in regulating cancer cell metabolism using combined metabolomics, transcriptomics, and pharmacological approaches. We find that TBK1 mediates the regulation of nucleotide and energy metabolism through aldo-keto reductase B10 (AKRB10) and thymidine phosphorylase (TYMP) genes, suggesting that this TBK1-mediated metabolic rewiring contributes to its oncogenic function. In addition, we find that TBK1 inhibitors can act synergistically with AKRB10 and TYMP inhibitors to reduce cell viability. These findings raise the possibility that combining these inhibitors might be beneficial in combating cancers that show elevated levels of TBK1.

Charting the transcriptomic landscape of primary and metastatic cancers in relation to their origin and target normal tissues

Metastasis is a leading cause of cancer-related deaths, yet understanding how metastatic tumors adapt from their origin to their target tissues remains a fundamental challenge. To address this, we assessed whether primary and metastatic tumors more closely resemble their tissues of origin or target tissues in terms of gene expression. We analyzed expression profiles from multiple cancer types and normal tissues, including single-cell and bulk RNA sequencing data from both paired and unpaired patient cohorts. Primary tumors were overall more transcriptomically similar to their tissues of origin, while metastases shifted toward their target tissues. However, pathway-level analysis highlighted critical metabolic and immune transcriptomic changes toward target tissues during metastasis in both primary and metastatic tumors. In addition, primary tumors exhibited higher activity in cancer hallmarks such as "Activating Invasion and Metastasis" when compared to metastases. This comprehensive analysis provides a transcriptome-wide view of the processes through which cancer tumors adapt to their metastatic environments before and after metastasis.

Importance of Michaelis Constants for Cancer Cell Redox Balance and Lactate Secretion-Revisiting the Warburg Effect

Cancer cells metabolize a large fraction of glucose to lactate, even under a sufficient oxygen supply. This phenomenon-the "Warburg Effect"-is often regarded as not yet understood. Cancer cells change gene expression to increase the uptake and utilization of glucose for biosynthesis pathways and glycolysis, but they do not adequately up-regulate the tricarboxylic acid (TCA) cycle and oxidative phosphorylation (OXPHOS). Thereby, an increased glycolytic flux causes an increased production of cytosolic NADH. However, since the corresponding gene expression changes are not neatly fine-tuned in the cancer cells, cytosolic NAD+ must often be regenerated by loading excess electrons onto pyruvate and secreting the resulting lactate, even under sufficient oxygen supply. Interestingly, the Michaelis constants (KM values) of the enzymes at the pyruvate junction are sufficient to explain the priorities for pyruvate utilization in cancer cells: 1. mitochondrial OXPHOS for efficient ATP production, 2. electrons that exceed OXPHOS capacity need to be disposed of and secreted as lactate, and 3. biosynthesis reactions for cancer cell growth. In other words, a number of cytosolic electrons need to take the "emergency exit" from the cell by lactate secretion to maintain the cytosolic redox balance.

Role of Glycolytic and Glutamine Metabolism Reprogramming on the Proliferation, Invasion, and Apoptosis Resistance through Modulation of Signaling Pathways in Glioblastoma

Glioma cells exhibit genetic and metabolic alterations that affect the deregulation of several cellular signal transduction pathways, including those related to glucose metabolism. Moreover, oncogenic signaling pathways induce the expression of metabolic genes, increasing the metabolic enzyme activities and thus the critical biosynthetic pathways to generate nucleotides, amino acids, and fatty acids, which provide energy and metabolic intermediates that are essential to accomplish the biosynthetic needs of glioma cells. In this review, we aim to explore how dysregulated metabolic enzymes and their metabolites from primary metabolism pathways in glioblastoma (GBM) such as glycolysis and glutaminolysis modulate anabolic and catabolic metabolic pathways as well as pro-oncogenic signaling and contribute to the formation, survival, growth, and malignancy of glioma cells. Also, we discuss promising therapeutic strategies by targeting the key players in metabolic regulation. Therefore, the knowledge of metabolic reprogramming is necessary to fully understand the biology of malignant gliomas to improve patient survival significantly.

Charting the transcriptomic landscape of primary and metastatic cancers in relation to their origin and target normal tissues

Metastasis is a leading cause of cancer-related deaths, yet understanding how metastatic tumors adapt from their origin to target tissues is challenging. To address this, we assessed whether primary and metastatic tumors resemble their tissue of origin or target tissue in terms of gene expression. We analyzed gene expression profiles from various cancer types, including single-cell and bulk RNA-seq data, in both paired and unpaired primary and metastatic patient cohorts. We quantified the transcriptomic distances between tumor samples and their normal tissues, revealing that primary tumors are more similar to their tissue of origin, while metastases shift towards the target tissue. Pathway-level analysis highlighted critical transcriptomic changes during metastasis. Notably, primary cancers exhibited higher activity in cancer hallmarks, including Activating Invasion and Metastasis , compared to metastatic cancers. This comprehensive landscape analysis provides insight into how cancer tumors adapt to their metastatic environments, providing a transcriptome-wide view of the processes involved.

O-GlcNAc transferase promotes glioblastoma by modulating genes responsible for cell survival, invasion, and inflammation

Metabolic reprogramming has emerged as one of the key hallmarks of cancer cells. Various metabolic pathways are dysregulated in cancers, including the hexosamine biosynthesis pathway. Protein O-GlcNAcylation is catalyzed by the enzyme O-GlcNAc transferase (OGT), an effector of hexosamine biosynthesis pathway that is found to be upregulated in most cancers. Posttranslational O-GlcNAcylation of various signaling and transcriptional regulators could promote cancer cell maintenance and progression by regulating gene expression, as gene-specific transcription factors and chromatin regulators are among the most highly O-GlcNAcylated proteins. Here, we investigated the role of OGT in glioblastoma. We demonstrate that OGT knockdown and chemical inhibition led to reduced glioblastoma cell proliferation and downregulation of many genes known to play key roles in glioblastoma cell proliferation, migration, and invasion. We show that genes downregulated due to OGT reduction are also known to be transcriptionally regulated by transcriptional initiation/elongation cofactor BRD4. We found BRD4 to be O-GlcNAcylated in glioblastoma cells; however, OGT knockdown/inhibition neither changed its expression nor its chromatin association on promoters. Intriguingly, we observed OGT knockdown led to reduced Pol II-Ser2P chromatin association on target genes without affecting other transcription initiation/elongation factors. Finally, we found that chemical inhibition of BRD4 potentiated the effects of OGT inhibition in reducing glioblastoma cell proliferation, invasion, and migration. We propose BRD4 and OGT act independently in the transcriptional regulation of a common set of genes and that combined inhibition of OGT and BRD4 could be utilized therapeutically for more efficient glioblastoma cell targeting than targeting of either protein alone.

Differential expression of mRNA 3'-end isoforms in cervical and ovarian cancers

Early diagnosis and therapeutic targeting are continuing challenges for gynecological cancers. Here, we focus on cancer transcriptomes and describe the differential expression of 3'UTR isoforms in patients using an algorithm to detect differential poly(A) site usage. We find primarily 3'UTR shortening cases in cervical cancers compared with the normal cervix. We show differential expression of alternate 3'-end isoforms of FOXP1, VPS4B, and OGT in HPV16-positive patients who develop high-grade cervical lesions compared with the infected but non-progressing group. In contrast, in ovarian cancers, 3'UTR lengthening is more evident compared with normal ovary tissue. Nevertheless, highly malignant ovarian tumors have unique 3'UTR shortening events (e.g., CHRAC1, SLC16A1, and TOP2A), some of which correlate with upregulated protein levels in tumors. Overall, our study shows isoform level deregulation in gynecological cancers and highlights the complexity of the transcriptome. This transcript diversity could help identify novel cancer genes and provide new possibilities for diagnosis and therapy.

Prognostic and Predictive Utility of GPD1L in Human Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths worldwide. GPD1L, a member of the glycerol-3-phosphate dehydrogenase family, has emerged as a potential tumour suppressor gene, with high expression associated with a favourable prognosis in various cancers. Despite an intriguing inverse relationship observed with HCC, the precise role and underlying function of GPD1L in HCC remain poorly understood. Here, we aimed to investigate the prognostic significance, molecular characteristics, and predictive potential of GPD1L overexpression in HCC. Analysis of independent datasets revealed a significant correlation between high GPD1L expression and poor survival in HCC patients. Spatial and single cell transcriptome datasets confirmed elevated GDP1L expression in tumour tissue compared to adjacent normal tissue. GPD1L exhibited increased expression and promoter demethylation with advancing tumour stage, confirming positive selection during tumorigeneses. GPD1L overexpression was associated with metabolic dysregulation and enrichment of gene sets related to cell cycle control, epithelial-mesenchymal transition, and E2F targets. Moreover, we demonstrated an inverse correlation between GPD1L expression and therapeutic response for three therapeutic agents (PF-562271, Linsitinib, and BMS-754807), highlighting its potential as a predictive biomarker for HCC treatment outcomes. These data provide insights into the prognostic significance, molecular characteristics, and predictive potential of GPD1L in HCC.

Characterizing cancer metabolism from bulk and single-cell RNA-seq data using METAFlux

Cells often alter metabolic strategies under nutrient-deprived conditions to support their survival and growth. Characterizing metabolic reprogramming in the tumor microenvironment (TME) is of emerging importance in cancer research and patient care. However, recent technologies only measure a subset of metabolites and cannot provide in situ measurements. Computational methods such as flux balance analysis (FBA) have been developed to estimate metabolic flux from bulk RNA-seq data and can potentially be extended to single-cell RNA-seq (scRNA-seq) data. However, it is unclear how reliable current methods are, particularly in TME characterization. Here, we present a computational framework METAFlux (METAbolic Flux balance analysis) to infer metabolic fluxes from bulk or single-cell transcriptomic data. Large-scale experiments using cell-lines, the cancer genome atlas (TCGA), and scRNA-seq data obtained from diverse cancer and immunotherapeutic contexts, including CAR-NK cell therapy, have validated METAFlux's capability to characterize metabolic heterogeneity and metabolic interaction amongst cell types.

Alterations of the Gut Microbiota and Metabolomics Associated with the Different Growth Performances of Macrobrachium rosenbergii Families

To investigate the key gut microbiota and metabolites associated with the growth performance of Macrobrachium rosenbergii families, 16S rRNA sequencing and LC-MS metabolomic methods were used. In this study, 90 M. rosenbergii families were bred to evaluate growth performance. After 92 days of culture, high (H), medium (M), and low (L) experimental groups representing three levels of growth performance, respectively, were collected according to the weight gain and specific growth rate of families. The composition of gut microbiota showed that the relative abundance of Firmicutes, Lachnospiraceae, Lactobacillus, and Blautia were much higher in Group H than those in M and L groups. Meanwhile, compared to the M and L groups, Group H had significantly higher levels of spermidine, adenosine, and creatinine, and lower levels of L-citrulline. Correlation analysis showed that the abundances of Lactobacillus and Blautia were positively correlated with the levels of alpha-ketoglutaric acid and L-arginine. The abundance of Blautia was also positively correlated with the levels of adenosine, taurine, and spermidine. Notably, lots of metabolites related to the metabolism and biosynthesis of arginine, taurine, hypotaurine, and fatty acid were upregulated in Group H. This study contributes to figuring out the landscape of the gut microbiota and metabolites associated with prawn growth performance and provides a basis for selective breeding.

Identification and Characterization of Metabolic Subtypes of Endometrial Cancer Using a Systems-Level Approach

Endometrial cancer (EC) is the most common gynecological cancer worldwide. Understanding metabolic adaptation and its heterogeneity in tumor tissues may provide new insights and help in cancer diagnosis, prognosis, and treatment. In this study, we investigated metabolic alterations of EC to understand the variations in metabolism within tumor samples. Integration of transcriptomics data of EC (RNA-Seq) and the human genome-scale metabolic network was performed to identify the metabolic subtypes of EC and uncover the underlying dysregulated metabolic pathways and reporter metabolites in each subtype. The relationship between metabolic subtypes and clinical variables was explored. Further, we correlated the metabolic changes occurring at the transcriptome level with the genomic alterations. Based on metabolic profile, EC patients were stratified into two subtypes (metabolic subtype-1 and subtype-2) that significantly correlated to patient survival, tumor stages, mutation, and copy number variations. We observed the co-activation of the pentose phosphate pathway, one-carbon metabolism, and genes involved in controlling estrogen levels in metabolic subtype-2, which is linked to poor survival. PNMT and ERBB2 are also upregulated in metabolic subtype-2 samples and present on the same chromosome locus 17q12, which is amplified. PTEN and TP53 mutations show mutually exclusive behavior between subtypes and display a difference in survival. This work identifies metabolic subtypes with distinct characteristics at the transcriptome and genome levels, highlighting the metabolic heterogeneity within EC.

Investigation of the effects of downregulation of jumping translocation breakpoint (JTB) protein expression in MCF7 cells for potential use as a biomarker in breast cancer

MCF7 is a commonly used luminal type A non-invasive/poor-invasive human breast cancer cell line that does not usually migrate or invade compared with MDA-MB-231 highly metastatic cells, which emphasize an invasive and migratory behavior. Under special conditions, MCF7 cells might acquire invasive features. The aberration in expression and biological functions of the jumping translocation breackpoint (JTB) protein is associated with malignant transformation of cells, based on mitochondrial dysfunction, inhibition of tumor suppressive function of TGF-β, and involvement in cancer cell cycle. To investigate new putative functions of JTB by cellular proteomics, we analyzed the biological processes and pathways that are associated with the JTB protein downregulation. The results demonstrated that MCF7 cell line developed a more "aggressive" phenotype and behavior. Most of the proteins that were overexpressed in this experiment promoted the actin cytoskeleton reorganization that is involved in growth and metastatic dissemination of cancer cells. Some of these proteins are involved in the epithelial-mesenchymal transition (EMT) process (ACTBL2, TUBA4A, MYH14, CSPG5, PKM, UGDH, HSP90AA2, and MIF), in correlation with the energy metabolism reprogramming (PKM, UGDH), stress-response (HSP10, HSP70A1A, HSP90AA2), and immune and inflammatory response (MIF and ERp57-TAPBP). Almost all upregulated proteins in JTB downregulated condition promote viability, motility, proliferation, invasion, survival into a hostile microenvironment, metabolic reprogramming, and escaping of tumor cells from host immune control, leading to a more invasive phenotype for MCF7 cell line. Due to their downregulated condition, four proteins, such as CREBZF, KMT2B, SELENOS and CACNA1I are also involved in maintenance of the invasive phenotype of cancer cells, promoting cell proliferation, migration, invasion and tumorigenesis. Other downregulated proteins, such as MAZ, PLEKHG2, ENO1, TPI2, TOR2A, and CNNM1, may promote suppression of cancer cell growth, invasion, EMT, tumorigenic abilities, interacting with glucose and lipid metabolism, disrupting nuclear envelope stability, or suppressing apoptosis and developing anti-angiogenetic activities. Therefore, the main biological processes and pathways that may increase the tumorigenic potential of the MCF7 cells in JTB downregulated condition are related to the actin cytoskeleton organization, EMT, mitotic cell cycle, glycolysis and fatty acid metabolism, inflammatory response and macrophage activation, chemotaxis and migration, cellular response to stress condition (oxidative stress and hypoxia), transcription control, histone modification and ion transport.

Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity

The clinical outcome and disease severity in coronavirus disease 2019 (COVID-19) are heterogeneous, and the progression or fatality of the disease cannot be explained by a single factor like age or comorbidities. In this study, we used system-wide network-based system biology analysis using whole blood RNA sequencing, immunophenotyping by flow cytometry, plasma metabolomics, and single-cell-type metabolomics of monocytes to identify the potential determinants of COVID-19 severity at personalized and group levels. Digital cell quantification and immunophenotyping of the mononuclear phagocytes indicated a substantial role in coordinating the immune cells that mediate COVID-19 severity. Stratum-specific and personalized genome-scale metabolic modeling indicated monocarboxylate transporter family genes (e.g., SLC16A6), nucleoside transporter genes (e.g., SLC29A1), and metabolites such as α-ketoglutarate, succinate, malate, and butyrate could play a crucial role in COVID-19 severity. Metabolic perturbations targeting the central metabolic pathway (TCA cycle) can be an alternate treatment strategy in severe COVID-19.