High TKTL1 expression as a sign of poor prognosis in colorectal cancer with synchronous rather than metachronous liver metastases

Characterization of cancer subtypes associated with clinical outcomes by multi-omics integrative clustering

Cancer patients show heterogeneous phenotypes and very different outcomes and responses even to common treatments, such as standard chemotherapy. This state-of-affairs has motivated the need for the comprehensive characterization of cancer phenotypes and fueled the generation of large omics datasets, comprising multiple omics data reported for the same patients, which might now allow us to start deciphering cancer heterogeneity and implement personalized therapeutic strategies. In this work, we performed the analysis of four cancer types obtained from the latest efforts by The Cancer Genome Atlas, for which seven distinct omics data were available for each patient, in addition to curated clinical outcomes. We performed a uniform pipeline for raw data preprocessing and adopted the Cancer Integration via MultIkernel LeaRning (CIMLR) integrative clustering method to extract cancer subtypes. We then systematically review the discovered clusters for the considered cancer types, highlighting novel associations between the different omics and prognosis.

Identification of a hypoxia-related gene prognostic signature in colorectal cancer based on bulk and single-cell RNA-seq

Colorectal cancer (CRC) is the most common and fatal tumor in the gastrointestinal system. Its incidence and mortality rate have increased in recent years. Hypoxia, a persistent physiological tumor feature, plays a vital role in CRC tumorigenesis, metastasis, and tumor microenvironment (TME). Therefore, we constructed a hypoxia-related gene (HRG) nomogram to predict overall survival (OS) and explored the role of HRGs in the CRC TME. The Cancer Genome Atlas (TCGA) dataset was used as the training set, and two Gene Expression Omnibus datasets (GSE39582 and GSE103479) were used as the testing sets. HRGs were identified using the Gene Set Enrichment Analysis (GSEA) database. An HRG prognostic model was constructed in the training set using the least absolute shrinkage and selection operator regression algorithm and validated in the testing sets. Then, we analyzed tumor-infiltrating cells (TICs) using the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm. Furthermore, single-cell next-generation RNA sequencing (RNA-seq) was used to investigate HRG expression in different TICs in the GSE139555 dataset. Finally, reverse transcription polymerase chain reactions (RT-PCR) were used to validate HRG mRNA expression in ten pairs of CRC normal and cancer tissue samples. A six HRG prognostic signature was constructed, with a superior OS prediction ability in CRC patients (area under the receiver operating characteristic curve (AUC) at one year: 0.693, AUC at three years: 0.712, and AUC at five years: 0.780). GSEA enrichment analysis identified six pathways enriched in the high-risk group. The TIC analysis indicated that the high-risk group had lower T-cell expression and higher neutrophil expression than the low-risk group. Furthermore, immune-related genes had an inseparable relationship with the HRG prognostic signature. Based on single-cell RNA-seq data, we found elevated hexokinase 1 (HK1) and glucose-6-phosphate isomerase (GPI) gene expression in natural killer (NK) and CD8⁺ T cells. RT-PCR in ten CRC normal-tumor tissue pairs showed that expression of the signature's six HRGs varied differently in cancerous and paracancerous tissues. The constructed HRG signature successfully predicted the OS of whole-stage CRC patients. In addition, we showed that the signature's six HRGs were closely associated with the TME in CRC, where hypoxia inhibits the antitumor function of T cells.

Human TKTL1 implies greater neurogenesis in frontal neocortex of modern humans than Neanderthals

Neanderthal brains were similar in size to those of modern humans. We sought to investigate potential differences in neurogenesis during neocortex development. Modern human transketolase-like 1 (TKTL1) differs from Neanderthal TKTL1 by a lysine-to-arginine amino acid substitution. Using overexpression in developing mouse and ferret neocortex, knockout in fetal human neocortical tissue, and genome-edited cerebral organoids, we found that the modern human variant, hTKTL1, but not the Neanderthal variant, increases the abundance of basal radial glia (bRG) but not that of intermediate progenitors (bIPs). bRG generate more neocortical neurons than bIPs. The hTKTL1 effect requires the pentose phosphate pathway and fatty acid synthesis. Inhibition of these metabolic pathways reduces bRG abundance in fetal human neocortical tissue. Our data suggest that neocortical neurogenesis in modern humans differs from that in Neanderthals.

The role of transketolase in human cancer progression and therapy

Transketolase (TKT) is an enzyme that is ubiquitously expressed in all living organisms and has been identified as an important regulator of cancer. Recent studies have shown that the TKT family includes the TKT gene and two TKT-like (TKTL) genes; TKTL1 and TKTL2. TKT and TKTL1 have been reported to be involved in the regulation of multiple cancer-related events, such as cancer cell proliferation, metastasis, invasion, epithelial-mesenchymal transition, chemoradiotherapy resistance, and patient survival and prognosis. Therefore, TKT may be an ideal target for cancer treatment. More importantly, the levels of TKTL1 were detected using EDIM technology for the early detection of some malignancies, and TKTL1 was more sensitive and specific than traditional tumor markers. Detecting TKTL1 levels before and after surgery could be used to evaluate the surgery's effect. While targeted TKT suppresses cancer in multiple ways, in some cases, it has detrimental effects on the organism. In this review, we discuss the role of TKT in different tumors and the detailed mechanisms while evaluating its value and limitations in clinical applications. Therefore, this review provides a basis for the clinical application of targeted therapy for TKT in the future, and a strategy for subsequent cancer-related research.

TKTL1 Knockdown Impairs Hypoxia-Induced Glucose-6-phosphate Dehydrogenase and Glyceraldehyde-3-phosphate Dehydrogenase Overexpression

Increased expression of transketolase (TKT) and its isoform transketolase-like-1 (TKTL1) has been related to the malignant leukemia phenotype through promoting an increase in the non-oxidative branch of the pentose phosphate pathway (PPP). Recently, it has also been described that TKTL1 can have a role in survival under hypoxic conditions and in the acquisition of radio resistance. However, TKTL1’s role in triggering metabolic reprogramming under hypoxia in leukemia cells has never been characterized. Using THP-1 AML cells, and by combining metabolomics and transcriptomics techniques, we characterized the impact of TKTL1 knockdown on the metabolic reprogramming triggered by hypoxia. Results demonstrated that TKTL1 knockdown results in a decrease in TKT, glucose-6-phosphate dehydrogenase (G6PD) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) activities and impairs the hypoxia-induced overexpression of G6PD and GAPDH, all having significant impacts on the redox capacity of NADPH- and NADH-related cells. Moreover, TKTL1 knockdown impedes hypoxia-induced transcription of genes encoding key enzymes and transporters involved in glucose, PPP and amino acid metabolism, rendering cells unable to switch to enhanced glycolysis under hypoxia. Altogether, our results show that TKTL1 plays a key role in the metabolic adaptation to hypoxia in THP-1 AML cells through modulation of G6PD and GAPDH activities, both regulating glucose/glutamine consumption and the transcriptomic overexpression of key players of PPP, glucose and amino acids metabolism.

Are we still on the right path(way)?: the altered expression of the pentose phosphate pathway in solid tumors and the potential of its inhibition in combination therapy

INTRODUCTION

The pentose phosphate pathway (PPP) branches from glycolysis and is crucial for cell growth, since it provides necessary compounds for anabolic reactions, nucleotide synthesis, and detoxification of reactive-oxygen-species (ROS). Overexpression of PPP enzymes has been reported in multiple cancer types and linked to therapy resistance, making their inhibition interesting targets for anti-cancer therapies.

AREAS COVERED

This review summarizes the extent of PPP upregulation across different cancer types, and the non-metabolic functions that PPP-enzymes might contribute to cancer initiation and maintenance. The effects of PPP-inhibition and their combinations with chemotherapeutics are summarized. We searched the databases provided by the University of Amsterdam to characterize the altered expression of the PPP across different cancer types, and to identify the effects of PPP-inhibition.

EXPERT OPINION

It can be concluded that there are synergistic and additive effects of PPP-inhibition and various classes of chemotherapeutics. These effects may be attributed to the increased susceptibility to ROS. However, the toxicity, low efficacy, and off-target effects of PPP-inhibitors make application in clinical practice challenging. Novel inhibitors are currently being developed, which could make PPP-inhibition a potential therapeutic strategy in the future, especially in combination with conventional chemotherapeutics and the inhibition of other metabolic pathways.

The role of glycometabolic plasticity in cancer

Dysregulated glycometabolism represented by the Warburg effect is well recognized as a hallmark of cancer that can be driven by oncogenes (e.g., c-Myc, K-ras, and BRAF) and contribute to cellular malignant transformation. The Warburg effect reveals the different glycometabolic patterns of cancer cells, but this unique glycometabolic pattern has the characteristic of plasticity rather than changeless which can vary with different internal or external stimuli during evolution. Glycometabolic plasticity enables cancer cells to modulate glycometabolism to support progression, metastasis, treatment resistance and recurrence. In this review, we report the characteristics of glycometabolic plasticity during different stages of cancer evolution, providing insight into the molecular mechanisms of glycometabolic plasticity in cancer. In addition, we discussed the challenges and future research directions of glycometabolism research in cancer.