bims-meluca 2021-06-20 papers

bims-meluca

Biomed News

on Metabolism of non-small cell lung carcinoma

Issue of 2021‒06‒20
nine papers selected by
Cristina Muñoz Pinedo
L’Institut d’Investigació Biomèdica de Bellvitge

Metabolic Phenotypes, Dependencies, and Adaptation in Lung Cancer.
ENO1 promotes lung cancer metastasis via HGFR and WNT signaling-driven epithelial-mesenchymal transition.
Modelling of SHMT1 riboregulation predicts dynamic changes of serine and glycine levels across cellular compartments.
Visceral Obesity Promotes Lung Cancer Progression-Toward Resolution of the Obesity Paradox in Lung Cancer.
lncRNA GAS6-AS1 inhibits progression and glucose metabolism reprogramming in LUAD via repressing E2F1-mediated transcription of GLUT1.
mTORC2 regulates ribonucleotide reductase to promote DNA replication and gemcitabine resistance in non-small cell lung cancer.
Optimization of a modeling platform to predict oncogenes from genome-scale metabolic networks of non-small-cell lung cancers.
Preclinical evidence of synergism between atovaquone and chemotherapy by AMPK-dependent mitochondrial dysfunction.
Comprehensive Profiling Reveals Distinct Microenvironment and Metabolism Characterization of Lung Adenocarcinoma.

Cold Spring Harb Perspect Med. 2021 Jun 14. pii: a037838. [Epub ahead of print]

Metabolic Phenotypes, Dependencies, and Adaptation in Lung Cancer.

Gina M DeNicola, David B Shackelford.

Lung cancer is a heterogeneous disease that is subdivided into histopathological subtypes with distinct behaviors. Each subtype is characterized by distinct features and molecular alterations that influence tumor metabolism. Alterations in tumor metabolism can be exploited by imaging modalities that use metabolite tracers for the detection and characterization of tumors. Microenvironmental factors, including nutrient and oxygen availability and the presence of stromal cells, are a critical influence on tumor metabolism. Recent technological advances facilitate the direct evaluation of metabolic alterations in patient tumors in this complex microenvironment. In addition, molecular alterations directly influence tumor cell metabolism and metabolic dependencies that influence response to therapy. Current therapeutic approaches to target tumor metabolism are currently being developed and translated into the clinic for patient therapy.

DOI: https://doi.org/10.1101/cshperspect.a037838
Cancer Res. 2021 Jun 18. pii: canres.3543.2020. [Epub ahead of print]

ENO1 promotes lung cancer metastasis via HGFR and WNT signaling-driven epithelial-mesenchymal transition.

Hsin-Jung Li, Feng-Yi Ke, Chia-Ching Lin, Mei-Yi Lu, Yi-Huei Kuo, Yi-Ping Wang, Kang-Hao Liang, Shin-Chang Lin, Ya-Hsuan Chang, Hsuan-Yu Chen, Pan-Chyr Yang, Han-Chung Wu.

ENO1 (α-enolase) expression is significantly correlated with reduced survival and poor prognosis in many cancer types, including lung cancer. However, the function of ENO1 in carcinogenesis remains elusive. In this study, we found that high expression of ENO1 is present in metastatic lung cancer cell lines and malignant tumors and is associated with poor overall survival of lung cancer patients. Knockdown of ENO1 decreased cancer cell proliferation and invasiveness, whereas overexpression of ENO1 enhanced these processes. Moreover, ENO1 expression promoted tumor growth in orthotopic models and enhanced lung tumor metastasis in tail-vein injection models. These effects were mediated by upregulation of mesenchymal markers N-cadherin and vimentin and the epithelial-mesenchymal transition (EMT) regulator SLUG, along with concurrent downregulation of E-cadherin. Mechanistically, ENO1 interacted with hepatocyte growth factor receptor (HGFR) and activated HGFR and Wnt signaling via increased phosphorylation of HGFR and the Wnt co-receptor LRP5/6. Activation of these signaling axes decreased GSK-3β activity via Src-PI3K-AKT signaling and inactivation of the β-catenin destruction complex to ultimately upregulate SLUG and β-catenin. Additionally, we generated a chimeric anti-ENO1 monoclonal antibody (chENO1-22) that can decrease cancer cell proliferation and invasion. chENO1-22 attenuated cancer cell invasion by inhibiting ENO1-mediated GSK3β inactivation to promote SLUG protein ubiquitination and degradation. Moreover, chENO1-22 prevented lung tumor metastasis and prolonged survival in animal models. Taken together, these findings illuminate the molecular mechanisms underlying the function of ENO1 in lung cancer metastasis and supports the therapeutic potential of a novel antibody targeting ENO1 for treating lung cancer.

DOI: https://doi.org/10.1158/0008-5472.CAN-20-3543
Comput Struct Biotechnol J. 2021 ;19 3034-3041

Modelling of SHMT1 riboregulation predicts dynamic changes of serine and glycine levels across cellular compartments.

Michele Monti, Giulia Guiducci, Alessio Paone, Serena Rinaldo, Giorgio Giardina, Francesca Romana Liberati, Francesca Cutruzzolá, Gian Gaetano Tartaglia.

  Human serine hydroxymethyltransferase (SHMT) regulates the serine-glycine one carbon metabolism and plays a role in cancer metabolic reprogramming. Two SHMT isozymes are acting in the cell: SHMT1 encoding the cytoplasmic isozyme, and SHMT2 encoding the mitochondrial one. Here we present a molecular model built on experimental data reporting the interaction between SHMT1 protein and SHMT2 mRNA, recently discovered in lung cancer cells. Using a stochastic dynamic model, we show that RNA moieties dynamically regulate serine and glycine concentration, shaping the system behaviour. For the first time we observe an active functional role of the RNA in the regulation of the serine-glycine metabolism and availability, which unravels a complex layer of regulation that cancer cells exploit to fine tune amino acids availability according to their metabolic needs. The quantitative model, complemented by an experimental validation in the lung adenocarcinoma cell line H1299, exploits RNA molecules as metabolic switches of the SHMT1 activity. Our results pave the way for the development of RNA-based molecules able to unbalance serine metabolism in cancer cells.

Keywords:  Metabolic networks; RNA-binding protein; RNA-protein interactions; Serine/Glycine metabolism

DOI:  https://doi.org/10.1016/j.csbj.2021.05.019
J Thorac Oncol. 2021 May 25. pii: S1556-0864(21)02171-7. [Epub ahead of print]

Visceral Obesity Promotes Lung Cancer Progression-Toward Resolution of the Obesity Paradox in Lung Cancer.

Joseph Barbi, Santosh K Patnaik, Sarabjot Pabla, Robert Zollo, Randall J Smith, Stephanie N Sass, Aravind Srinivasan, Cara Petrucci, Robert Seager, Jeffrey Conroy, Eric Kannisto, Xialong Wang, Shrunjal Shah, Rohit Gosain, Kris Attwood, Charles Roche, Sai Yendamuri.

  INTRODUCTION: Although obesity is associated with adverse cancer outcomes in general, most retrospective clinical studies suggest a beneficial effect of obesity in NSCLC.METHODS: Hypothesizing that this "obesity paradox" arises partly from the limitations of using body mass index (BMI) to measure obesity, we quantified adiposity using preoperative computed tomography images. This allowed the specific determination of central obesity as abdominal visceral fat area normalized to total fat area (visceral fat index [VFI]). In addition, owing to the previously reported salutary effect of metformin on high-BMI patients with lung cancer, metformin users were excluded. We then explored associations between visceral obesity and outcomes after surgical resection of stage I and II NSCLC. We also explored potential immunologic underpinnings of such association using complimentary analyses of tumor gene expression data from NSCLC tumors and the tumor transcriptome and immune microenvironment in an immunocompetent model of lung cancer with diet-induced obesity.
RESULTS: We found that in 513 patients with stage I and II NSCLC undergoing lobectomy, a high VFI is associated with decreased recurrence-free and overall survival. VFI was also inversely related to an inflammatory transcriptomic signature in NSCLC tumors, consistent with observations made in immunocompetent murine models wherein diet-induced obesity promoted cancer progression while exacerbating elements of immune suppression in the tumor niche.
CONCLUSIONS: In all, this study uses multiple lines of evidence to reveal the adverse effects of visceral obesity in patients with NSCLC, which align with those found in animal models. Thus, the obesity paradox may, at least in part, be secondary to the use of BMI as a measure of obesity and the confounding effects of metformin use.

Keywords:  Immunity; Lung cancer; Obesity; Visceral adiposity

DOI:  https://doi.org/10.1016/j.jtho.2021.04.020
Mol Ther Nucleic Acids. 2021 Sep 03. 25 11-24

lncRNA GAS6-AS1 inhibits progression and glucose metabolism reprogramming in LUAD via repressing E2F1-mediated transcription of GLUT1.

Jing Luo, Huishan Wang, Li Wang, Gaoming Wang, Yu Yao, Kai Xie, Xiaokun Li, Lin Xu, Yi Shen, Binhui Ren.

  Glucose metabolism reprogramming is one of the hallmarks of cancer cells, although functional and regulatory mechanisms of long noncoding RNA (lncRNA) in the contribution of glucose metabolism in lung adenocarcinoma (LUAD) remain incompletely understood. The aim of this study was to uncover the role of GAS6-AS1 in the regulation of progression and glucose metabolism in LUAD. We discovered that overexpression of GAS6-AS1 suppressed tumor progression of LUAD both in vitro and in vivo. Metabolism-related assays revealed that GAS6-AS1 inhibited glucose metabolism reprogramming. Mechanically, GAS6-AS1 was found to repress the expression of glucose transporter GLUT1, a key regulator of glucose metabolism. Ectopic expression of GLUT1 restored the inhibition effect of GAS6-AS1 on cancer progression and glucose metabolism reprogramming. Further investigation identified that GAS6-AS1 directly interacted with transcription factor E2F1 and suppressed E2F1-mediated transcription of GLUT1, and GAS6-AS1 was downregulated in LUAD tissues and correlated with clinicopathological characteristics and survival of patients. Taken together, our results identified GAS6-AS1 as a novel tumor suppressor in LUAD and unraveled its underlying molecular mechanism in reprogramming glucose metabolism. GAS6-AS1 potentially may serve as a prognostic marker and therapeutic target in LUAD.

Keywords:  E2F1; GAS6-AS1; GLUT1; glucose metabolism; lung adenocarcinoma

DOI:  https://doi.org/10.1016/j.omtn.2021.04.022
Neoplasia. 2021 Jun 11. pii: S1476-5586(21)00032-4. [Epub ahead of print]23(7): 643-652

mTORC2 regulates ribonucleotide reductase to promote DNA replication and gemcitabine resistance in non-small cell lung cancer.

Ling Tian, Congcong Chen, Yanguan Guo, Fan Zhang, Jinye Mi, Qi Feng, Shengbin Lin, Naite Xi, Jiaxin Tian, Li Yu, Yan Chen, Mingrong Cao, Caiyong Lai, Jun Fan, Yongchang Zhang, Guo Chen.

  Ribonucleotide reductase (RNR) is the key enzyme that catalyzes the production of deoxyribonucleotides (dNTPs) for DNA replication and it is also essential for cancer cell proliferation. As the RNR inhibitor, Gemcitabine is widely used in cancer therapies, however, resistance limits its therapeutic efficacy and curative potential. Here, we identified that mTORC2 is a main driver of gemcitabine resistance in non-small cell lung cancers (NSCLC). Pharmacological or genetic inhibition of mTORC2 greatly enhanced gemcitabine induced cytotoxicity and DNA damage. Mechanistically, mTORC2 directly interacted and phosphorylated RNR large subunit RRM1 at Ser 631. Ser631 phosphorylation of RRM1 enhanced its interaction with small subunit RRM2 to maintain sufficient RNR enzymatic activity for efficient DNA replication. Targeting mTORC2 retarded DNA replication fork progression and improved therapeutic efficacy of gemcitabine in NSCLC xenograft model in vivo. Thus, these results identified a mechanism through mTORC2 regulating RNR activity and DNA replication, conferring gemcitabine resistance to cancer cells.

Keywords:  DNA replication stress; Gemcitabine; Ribonucleotide reductase; mTORC2

DOI:  https://doi.org/10.1016/j.neo.2021.05.007
FEBS Open Bio. 2021 Jun 17.

Optimization of a modeling platform to predict oncogenes from genome-scale metabolic networks of non-small-cell lung cancers.

You-Tyun Wang, Min-Ru Lin, Wei-Chen Chen, Wu-Hsiung Wu, Feng-Sheng Wang.

  Cancer cell dysregulations result in the abnormal regulation of cellular metabolic pathways. By simulating this metabolic reprogramming using constraint-based modeling approaches, oncogenes can be predicted, and this knowledge can be used in prognosis and treatment. We introduced a trilevel optimization problem describing metabolic reprogramming for inferring oncogenes. First, this study used RNA-Seq expression data of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) samples and their healthy counterparts to reconstruct tissue-specific genome-scale metabolic models and subsequently build the flux distribution pattern that provided a measure for the oncogene inference optimization problem for determining tumorigenesis. The platform detected 45 genes for LUAD and 84 genes for LUSC that lead to tumorigenesis. A high level of differentially expressed genes was not an essential factor for determining tumorigenesis. The platform indicated that pyruvate kinase (PKM), a well-known oncogene with a low level of differential gene expression in LUAD and LUSC, had the highest fitness among the predicted oncogenes based on computation. By contrast, pyruvate kinase L/R (PKLR), an isozyme of PKM, had a high level of differential gene expression in both cancers. Phosphatidylserine synthase 1 (PTDSS1), an oncogene in LUAD, was inferred to have a low level of differential gene expression, and overexpression could significantly reduce survival probability. According to the factor analysis, PTDSS1 characteristics were close to those of the template, but they were unobvious in LUSC. Angiotensin converting enzyme 2 (ACE2) has recently garnered widespread interest as the SARS-CoV-2 virus receptor. Moreover, we determined that ACE2 is an oncogene of LUSC but not of LUAD. The platform developed in this study can identify oncogenes with low levels of differential expression and be used to identify potential therapeutic targets for cancer treatment.

Keywords:  Cancer cell metabolism; Constraint-based modeling; Flux balance analysis; Tissue-specific metabolic models; Trilevel optimization

DOI:  https://doi.org/10.1002/2211-5463.13231
Eur J Pharmacol. 2021 Jun 12. pii: S0014-2999(21)00409-X. [Epub ahead of print] 174256

Preclinical evidence of synergism between atovaquone and chemotherapy by AMPK-dependent mitochondrial dysfunction.

Fan Xie, Jianhua Gong, Hongxia Tan, Han Zhang, Jingping Ma.

  Chemoresistance has been associated with increased reliance on mitochondrial functions in many cancers, including lung cancer. Atovaquone is an anti-malaria drug and mitochondrial inhibitor. In this work, we attempted to explore whether atovaquone can be repurposed for lung cancer treatment to overcome chemoresistance. We showed that atovaquone inhibited proliferation, colony formation and survival in non-small cell lung cancer cell (NSCLC) cells. Of note, the effective dose of atovaquone was clinically achievable. Combination index value indicated that atovaquone and carboplatin were synergistic in inhibiting NSCLC. The potent efficacy of atovaquone and its synergism with chemotherapeutic drug were also demonstrated in NSCLC xenograft mice model. Mechanism studies showed that the synergism between atovaquone and carboplatin was due to atovaquone's ability in disrupting mitochondrial functions via specifically inhibiting complex III induced oxygen consumption. Subsequently, atovaquone activated AMP-activated protein kinase (AMPK) and inhibited mammalian target of rapamycin (mTOR) signaling. AMPK inhibition reversed the anti-NSCLC activity of atovaquone, suggesting that the action of atovaquone is also dependent on AMPK. Our work suggests that atovaquone is an attractive candidate for NSCLC treatment. Our findings emphasize that inhibition of mitochondrial function is a promising therapeutic strategy to enhance NSCLC chemosensitivity.

Keywords:  AMPK/mTOR; NSCLC; atovaquone; mitochondrial function; synergism

DOI:  https://doi.org/10.1016/j.ejphar.2021.174256
Front Genet. 2021 ;12 619821

Comprehensive Profiling Reveals Distinct Microenvironment and Metabolism Characterization of Lung Adenocarcinoma.

Chang Li, Chen Tian, Yangyang Liu, Jinyan Liang, Yulan Zeng, Qifan Yang, Yuting Liu, Di Wu, Jingjing Wu, Juanjuan Wang, Kai Zhang, Feifei Gu, Yue Hu, Li Liu.

  Lung adenocarcinoma has entered into an era of immunotherapy with the development of immune checkpoint inhibitors (ICIs). The identification of immune subtype is crucial to prolonging survival in patients. The tumor microenvironment (TME) and metabolism have a profound impact on prognosis and therapy. The majority of previous studies focused on only one aspect, while both of them are essential to the understanding of tumorigenesis and development. We hypothesized that lung adenocarcinoma can be stratified into immune subgroups with alterations in the TME infiltration. We aimed to explore the "TME-Metabolism-Risk" patterns in each subtypes and the mechanism behind. Glycolysis and cholesterol were selected for the analysis of metabolic states based on the first half of the study. Bioinformatic analysis was performed to investigate the transcriptomic and clinical data integrated by three lung adenocarcinoma cohorts (GSE30219, GSE31210, GSE37745, N = 415). The results were validated in an independent cohort (GSE50081, N = 127). In total, 415 lung adenocarcinoma samples were integrated and analyzed. Four major immune subtypes were indentified using bioinformatic analysis. Subtype NC1, characterized by a high level of glycolysis, with extremely low microenvironment cell infiltration. Subtype NC2, characterized by the "Silence" and "Cholesterol biosynthesis Predominant" metabolic states, with a middle degree infiltration of microenvironment cell. Subtype NC3, characterized by the lack of "Cholesterol biosynthesis Predominant" metabolic state, with abundant microenvironment cell infiltration. Subtype NC4, characterized by "Mixed" metabolic state, with a relatively low microenvironment cell infiltration. Least absolute shrinkage and selection operator (LASSO) regression and multivariate analyses were performed to calculate the risk of each sample, and we attempted to find out the potential immune escape mechanism in different subtypes. The result revealed that the lack of immune cells infiltration might contribute to the immune escape in subtypes NC1 and NC4. NC3 was characterized by the high expression of immune checkpoint molecules and fibroblasts. NC2 had defects in activation of innate immune cells. There existed an obviously survival advantage in subtype NC2. Gene set enrichment analysis (GSEA) and Gene Ontology analysis indicated that the PI3K-AKT-mTOR, TGF-β, MYC-related pathways might be correlated with this phenomenon. In addition, some differentially expressed genes (DEGs) were indentified in subtype NC3, which might be potential targets for survival phenotype transformation.

Keywords:  bioinformactics analysis; immune escape; lung adenocarcinoma; metabolism; molecular subtype; prognosis; tumor microenvironment

DOI:  https://doi.org/10.3389/fgene.2021.619821