Intratumoral heterogeneity of glutaminase and lactate dehydrogenase A protein expression in colorectal cancer

Insights into metabolic heterogeneity of colorectal cancer gained from fluorescence lifetime imaging

Heterogeneity of tumor metabolism is an important, but still poorly understood aspect of tumor biology. Present work is focused on the visualization and quantification of cellular metabolic heterogeneity of colorectal cancer using fluorescence lifetime imaging (FLIM) of redox cofactor NAD(P)H. FLIM-microscopy of NAD(P)H was performed in vitro in four cancer cell lines (HT29, HCT116, CaCo2 and CT26), in vivo in the four types of colorectal tumors in mice and ex vivo in patients' tumor samples. The dispersion and bimodality of the decay parameters were evaluated to quantify the intercellular metabolic heterogeneity. Our results demonstrate that patients' colorectal tumors have significantly higher heterogeneity of energy metabolism compared with cultured cells and tumor xenografts, which was displayed as a wider and frequently bimodal distribution of a contribution of a free (glycolytic) fraction of NAD(P)H within a sample. Among patients' tumors, the dispersion was larger in the high-grade and early stage ones, without, however, any association with bimodality. These results indicate that cell-level metabolic heterogeneity assessed from NAD(P)H FLIM has a potential to become a clinical prognostic factor.

RFC2 promotes aerobic glycolysis and progression of colorectal cancer

BACKGROUND

Replication factor C subunit 2 (RFC2) participates in the growth and metastasis of various malignancies. Our study investigated the roles of RFC2 in colorectal cancer (CRC).

RESULTS

RFC2 expression was upregulated in CRC tissues and cells. High RFC2 expression was associated with poor prognosis. Knockdown RFC2 inhibited proliferation, induced apoptosis, and suppressed migration and invasion of CRC cells. CREB5 was a transcription factor of RFC2, and CREB5 knockdown suppressed RFC2 expression. Furthermore, RFC2 promoted aerobic glycolysis and MET/PI3K/AKT/mTOR pathway.

CONCLUSION

RFC2 promoted the progression of CRC cells via activating aerobic glycolysis and the MET/PI3K/AKT/mTOR pathway.

Intratumoral metabolic heterogeneity of colorectal cancer

Although the metabolic phenotype within tumors is known to differ significantly from that of the surrounding normal tissue, the importance of this heterogeneity is just becoming widely recognized. Colorectal cancer (CRC) is often classified as the Warburg phenotype, a metabolic type in which the glycolytic system is predominant over oxidative phosphorylation (OXPHOS) in mitochondria for energy production. However, this dichotomy (glycolysis vs. OXPHOS) may be too simplistic and not accurately represent the metabolic characteristics of CRC. Therefore, in this review, we decompose metabolic phenomena into factors based on their source/origin and reclassify them into two categories: extrinsic and intrinsic. In the CRC context, extrinsic factors include those based on the environment, such as hypoxia, nutrient deprivation, and the tumor microenvironment, whereas intrinsic factors include those based on subpopulations, such as pathological subtypes and cancer stem cells. These factors form multiple layers inside and outside the tumor, affecting them additively, dominantly, or mutually exclusively. Consequently, the metabolic phenotype is a heterogeneous and fluid phenomenon reflecting the spatial distribution and temporal continuity of these factors. This allowed us to redefine the characteristics of specific metabolism-related factors in CRC and summarize and update our accumulated knowledge of their heterogeneity. Furthermore, we positioned tumor budding in CRC as an intrinsic factor and a novel form of metabolic heterogeneity, and predicted its metabolic dynamics, noting its similarity to circulating tumor cells and epithelial-mesenchymal transition. Finally, the possibilities and limitations of using human tumor tissue as research material to investigate and assess metabolic heterogeneity are discussed.

Insulin-Like Growth Factor 1 (IGF-1) Signaling in Glucose Metabolism in Colorectal Cancer

Colorectal cancer (CRC) is one of the most common aggressive carcinoma types worldwide, characterized by unfavorable curative effect and poor prognosis. Epidemiological data re-vealed that CRC risk is increased in patients with metabolic syndrome (MetS) and its serum components (e.g., hyperglycemia). High glycemic index diets, which chronically raise post-prandial blood glucose, may at least in part increase colon cancer risk via the insulin/insulin-like growth factor 1 (IGF-1) signaling pathway. However, the underlying mechanisms linking IGF-1 and MetS are still poorly understood. Hyperactivated glucose uptake and aerobic glycolysis (the Warburg effect) are considered as a one of six hallmarks of cancer, including CRC. However, the role of insulin/IGF-1 signaling during the acquisition of the Warburg metabolic phenotypes by CRC cells is still poorly understood. It most likely results from the interaction of multiple processes, directly or indirectly regulated by IGF-1, such as activation of PI3K/Akt/mTORC, and Raf/MAPK signaling pathways, activation of glucose transporters (e.g., GLUT1), activation of key glycolytic enzymes (e.g., LDHA, LDH5, HK II, and PFKFB3), aberrant expression of the oncogenes (e.g., MYC, and KRAS) and/or overexpression of signaling proteins (e.g., HIF-1, TGF-β1, PI3K, ERK, Akt, and mTOR). This review describes the role of IGF-1 in glucose metabolism in physiology and colorectal carcinogenesis, including the role of the insulin/IGF system in the Warburg effect. Furthermore, current therapeutic strategies aimed at repairing impaired glucose metabolism in CRC are indicated.

Identification of a six-gene metabolic signature predicting overall survival for patients with lung adenocarcinoma

Background

Lung cancer is the leading cause of cancer-related deaths worldwide. Lung adenocarcinoma (LUAD) is one of the main subtypes of lung cancer. Hundreds of metabolic genes are altered consistently in LUAD; however, their prognostic role remains to be explored. This study aimed to establish a molecular signature that can predict the prognosis in patients with LUAD based on metabolic gene expression.

Methods

The transcriptome expression profiles and corresponding clinical information of LUAD were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The differentially expressed genes (DEGs) between LUAD and paired non-tumor samples were identified by the Wilcoxon rank sum test. Univariate Cox regression analysis and the lasso Cox regression model were used to construct the best-prognosis molecular signature. A nomogram was established comprising the prognostic model for predicting overall survival. To validate the prognostic ability of the molecular signature and the nomogram, the Kaplan-Meier survival analysis, Cox proportional hazards model, and receiver operating characteristic analysis were used.

Results

The six-gene molecular signature (PFKP, PKM, TPI1, LDHA, PTGES, and TYMS) from the DEGs was constructed to predict the prognosis. The molecular signature demonstrated a robust independent prognostic ability in the training and validation sets. The nomogram including the prognostic model had a greater predictive accuracy than previous systems. Furthermore, a gene set enrichment analysis revealed several significantly enriched metabolic pathways, which suggests a correlation of the molecular signature with metabolic systems and may help explain the underlying mechanisms.

Conclusions

Our study identified a novel six-gene metabolic signature for LUAD prognosis prediction. The molecular signature could reflect the dysregulated metabolic microenvironment, provide potential biomarkers for predicting prognosis, and indicate potential novel metabolic molecular-targeted therapies.