bims-meluca 2022-05-08 papers

on Metabolism of non-small cell lung carcinoma

Issue of 2022–05–08
nine papers selected by
the Muñoz-Pinedo/Nadal (PReTT) lab, L’Institut d’Investigació Biomèdica de Bellvitge and Cristina Muñoz Pinedo, L’Institut d’Investigació Biomèdica de Bellvitge

Glutaminase inhibition impairs CD8 T cell activation in STK11-/Lkb1-deficient lung cancer.
Lactate Transporter SLC16A3 (MCT4) as an Onco-Immunological Biomarker Associating Tumor Microenvironment and Immune Responses in Lung Cancer.
Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma.
Glycosylated Cathepsin V Serves as a Prognostic Marker in Lung Cancer.
miRNA-199a-5p/SLC2A1 axis regulates glucose metabolism in non-small cell lung cancer.
A Review of the Correlation Between Epidermal Growth Factor Receptor Mutation Status and 18F-FDG Metabolic Activity in Non-Small Cell Lung Cancer.
Identifying Molecular Subtypes and 6-Gene Prognostic Signature Based on Hypoxia for Optimizing Targeted Therapies in Non-Small Cell Lung Cancer.
De novo Creation and Assessment of a Prognostic Fat-Age-Inflammation Index "FAIN" in Patients With Cancer: A Multicenter Cohort Study.
A Comprehensive Prognostic and Immune Analysis of Ferroptosis-Related Genes Identifies SLC7A11 as a Novel Prognostic Biomarker in Lung Adenocarcinoma.

Cell Metab. 2022 Apr 23. pii: S1550-4131(22)00130-9. [Epub ahead of print]

Glutaminase inhibition impairs CD8 T cell activation in STK11-/Lkb1-deficient lung cancer.

Sarah A Best, Patrick M Gubser, Shalini Sethumadhavan, Ariena Kersbergen, Yashira L Negrón Abril, Joshua Goldford, Katherine Sellers, Waruni Abeysekera, Alexandra L Garnham, Jackson A McDonald, Clare E Weeden, Dovile Anderson, David Pirman, Thomas P Roddy, Darren J Creek, Axel Kallies, Gillian Kingsbury, Kate D Sutherland.

  The tumor microenvironment (TME) contains a rich source of nutrients that sustains cell growth and facilitate tumor development. Glucose and glutamine in the TME are essential for the development and activation of effector T cells that exert antitumor function. Immunotherapy unleashes T cell antitumor function, and although many solid tumors respond well, a significant proportion of patients do not benefit. In patients with KRAS-mutant lung adenocarcinoma, KEAP1 and STK11/Lkb1 co-mutations are associated with impaired response to immunotherapy. To investigate the metabolic and immune microenvironment of KRAS-mutant lung adenocarcinoma, we generated murine models that reflect the KEAP1 and STK11/Lkb1 mutational landscape in these patients. Here, we show increased glutamate abundance in the Lkb1-deficient TME associated with CD8 T cell activation in response to anti-PD1. Combination treatment with the glutaminase inhibitor CB-839 inhibited clonal expansion and activation of CD8 T cells. Thus, glutaminase inhibition negatively impacts CD8 T cells activated by anti-PD1 immunotherapy.

Keywords:  KEAP1; KRAS; STK11/Lkb1; glutaminase; glutamine; immune microenvironment; immunotherapy; lung adenocarcinoma; metabolism

DOI:  https://doi.org/10.1016/j.cmet.2022.04.003
Int J Gen Med. 2022 ;15 4465-4474

Lactate Transporter SLC16A3 (MCT4) as an Onco-Immunological Biomarker Associating Tumor Microenvironment and Immune Responses in Lung Cancer.

Qingsong Tao, Xin Li, Ting Zhu, Xiaoqin Ge, Shengping Gong, Jianxin Guo, Ruishuang Ma.

   Purpose: Lactate, a marker of tumor metabolic reprogramming, maintains the acidic microenvironment and also affects the metabolism and function of immune cells. SLC16A3 is responsible for the extracellular transport of lactate, which is a key component of glycolysis. However, the role of SLC16A3 in immune infiltration and immunosuppression of lung cancer is largely unknown. Our study explored the therapeutic and prognostic value of SLC16A3 in predicting immune infiltration and immune checkpoint efficacy of lung cancer.
Methods: SLC16A3 expression was evaluated with TCGA database. Kaplan-Meier analysis was performed for survival rates. GO and KEEG enrichment was conducted to determine predictive signaling pathways. We utilized TIMER and CIBERSORT to analyze the correlation between SLC16A3 and immunocyte infiltration as well as immune checkpoint. Interleukin and HIF-1a expression was measured with ELISA kit and flow cytometry separately.
Results: In comparison with normal tissues, SLC16A3 expression was significantly upregulated in both lung adenocarcinoma (LUAD) and squamous carcinoma (LUSC), which was closely related to poor prognosis. GO analysis indicated that SLC16A3 involved in different signal pathways in LUAD and LUSC and linked to HIF-1 signaling in LUAD. High SLC16A3 was correlated with immunosuppressive cells (Treg, Th2 and iDC), immune checkpoint (PD1, PD-L1, PVR, Tim-3, ITGAM) and immunosuppressive factors (foxp3, TGF-β) in LUAD not LUSC. Furthermore, SLC16A3 was identified to tightly interact with IL-8 which may induce microenvironment immune tolerance. Based on the clinical prediction, we performed experiments with LUAD A549 cells and showed reduced IL-8 and HIF-1a when treated with SLC16A3 knockdown. HIF-1a stimulation by dimethyloxalylglycine (DMOG) could restore IL-8 secretion in SLC16A3 downregulated cells.
Conclusion: Taken together, our results suggest that SLC16A3 contributes to a worse prognosis in lung cancer and may play an important role in immune microenvironment and evasion through HIF-1a-IL8 axis, which could be a novel therapeutic target for immunotherapy in lung cancer.

Keywords:  IL-8; SLC16A3 (MCT4); bioinformatics analysis; immune evasion; lung cancer

DOI:  https://doi.org/10.2147/IJGM.S353592
Front Oncol. 2022 ;12 867470

Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma.

Teng Mu, Haoran Li, Xiangnan Li.

   Background: Lung adenocarcinoma (LUAD) is the major non-small-cell lung cancer pathological subtype with poor prognosis worldwide. Herein, we aimed to build an energy metabolism-associated prognostic gene signature to predict patient survival.
Methods: The gene expression profiles of patients with LUAD were downloaded from the TCGA and GEO databases, and energy metabolism (EM)-related genes were downloaded from the GeneCards database. Univariate Cox and LASSO analyses were performed to identify the prognostic EM-associated gene signatures. Kaplan-Meier and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signatures. A CIBERSORT analysis was used to evaluate the correlation between the risk model and immune cells. A nomogram was used to predict the survival probability of LUAD based on a risk model.
Results: We constructed a prognostic signature comprising 13 EM-related genes (AGER, AHSG, ALDH2, CIDEC, CYP17A1, FBP1, GNB3, GZMB, IGFBP1, SORD, SOX2, TRH and TYMS). The Kaplan-Meier curves validated the good predictive ability of the prognostic signature in TCGA AND two GEO datasets (p<0.0001, p=0.00021, and p=0.0034, respectively). The area under the curve (AUC) of the ROC curves also validated the predictive accuracy of the risk model. We built a nomogram to predict the survival probability of LUAD, and the calibration curves showed good predictive ability. Finally, a functional analysis also unveiled the different immune statuses between the two different risk groups.
Conclusion: Our study constructed and verified a novel EM-related prognostic gene signature that could improve the individualized prediction of survival probability in LUAD.

Keywords:  energy metabolism; lung adenocarcinoma; nomogram; prognosis; risk model

DOI:  https://doi.org/10.3389/fonc.2022.867470
Front Oncol. 2022 ;12 876245

Glycosylated Cathepsin V Serves as a Prognostic Marker in Lung Cancer.

Lewei Yang, Qi Zeng, Yun Deng, Yeqing Qiu, Wei Yao, Yifeng Liao.

  Dysregulation of cysteine cathepsin protease activity is pivotal in tumorigenic transformation. However, the role of cathepsin protease in lung cancer remains unknown. Here, we analyzed GEO database and found that lung cancer presented high expression of cathepsin V (CTSV). We then performed immunohistochemistry assay in 73 paired lung cancer tissues and normal lung tissues and confirmed that CTSV is overexpressed in lung cancer and correlates with poor prognosis. The mass spectrometry experiment showed that the N-glycosylation locus of CTSV are N221 and N292, glycosylated CTSV (band 43 kDa) was particularly expressed in lung cancer samples and correlated with lymph node metastasis. Mechanistic studies showed that only glycosylated CTSV (43-kDa band) are secreted to extracellular matrix (ECM) and promoted the metastasis of lung cancer. Importantly, the Elisa detection in serum of 12 lung cancer patients and 12 healthy donors showed that the level of CTSV in serum distinguished lung cancer patients from healthy donors. Together, our findings reveal the clinical relevance of CTSV glycosylation and CTSV drives the metastasis of lung cancer, suggesting that the glycosylated CTSV in serum is a promising biomarker for lung cancer.

Keywords:  CTSV; glycosylation; lung cancer; metastasis; prognosis

DOI:  https://doi.org/10.3389/fonc.2022.876245
J Cancer. 2022 ;13(7): 2352-2361

miRNA-199a-5p/SLC2A1 axis regulates glucose metabolism in non-small cell lung cancer.

Yikun Xu, Binshu Chai, Xianyi Wang, Zong Wu, Zhitao Gu, Xiaomin Liu, Yiqi Zhao, Tangbing Chen, Zhongliang Ma, Qiangling Sun.

  Lung cancer is acknowledged as a common cancer with high morbidity and mortality. MicroRNAs (miRNAs), kind of non-coding single-stranded RNA molecules, can be used in cancer clinical treatments. In this research, miR-199a-5p was seen lowly expressed in NSCLC sera samples. miR-199a-5p suppressed the cell proliferation, migration and arrested cell cycle in NSCLC cell lines. The results showed that SLC2A1 (glucose transporter 1, GLUT1) was a direct target of miR-199a-5p. Downregulation of SLC2A1 could not only inhibit cell proliferation, migration and cell cycle, but also promote cell apoptosis. The data suggests that miR-199a-5p can inhibit glucose metabolism in NSCLC by targeting SLC2A1.This study proves that miR-199a-5p / SLC2A1 can play an essential role in the development of NSCLC by targeting SLC2A1. It puts forward a new approach for clinical treatments of NSCLC.

Keywords:  GLUTs; NSCLC; SLC2A1/GLUT1; miR-199a-5p; non-coding RNAs

DOI:  https://doi.org/10.7150/jca.67990
Front Oncol. 2022 ;12 780186

A Review of the Correlation Between Epidermal Growth Factor Receptor Mutation Status and 18F-FDG Metabolic Activity in Non-Small Cell Lung Cancer.

Maoqing Jiang, Xiaohui Zhang, Yan Chen, Ping Chen, Xiuyu Guo, Lijuan Ma, Qiaoling Gao, Weiqi Mei, Jingfeng Zhang, Jianjun Zheng.

  PET/CT with 18F-2-fluoro-2-deoxyglucose (18F-FDG) has been proposed as a promising modality for diagnosing and monitoring treatment response and evaluating prognosis for patients with non-small cell lung cancer (NSCLC). The status of epidermal growth factor receptor (EGFR) mutation is a critical signal for the treatment strategies of patients with NSCLC. Higher response rates and prolonged progression-free survival could be obtained in patients with NSCLC harboring EGFR mutations treated with tyrosine kinase inhibitors (TKIs) when compared with traditional cytotoxic chemotherapy. However, patients with EGFR mutation treated with TKIs inevitably develop drug resistance, so predicting the duration of resistance is of great importance for selecting individual treatment strategies. Several semiquantitative metabolic parameters, e.g., maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG), measured by PET/CT to reflect 18F-FDG metabolic activity, have been demonstrated to be powerful in predicting the status of EGFR mutation, monitoring treatment response of TKIs, and assessing the outcome of patients with NSCLC. In this review, we summarize the biological and clinical correlations between EGFR mutation status and 18F-FDG metabolic activity in NSCLC. The metabolic activity of 18F-FDG, as an extrinsic manifestation of NSCLC, could reflect the mutation status of intrinsic factor EGFR. Both of them play a critical role in guiding the implementation of treatment modalities and evaluating therapy efficacy and outcome for patients with NSCLC.

Keywords:  18F-FDG; epidermal growth factor receptor; non-small cell lung cancer; positron emission tomography; tyrosine kinase inhibitors

DOI:  https://doi.org/10.3389/fonc.2022.780186
Int J Gen Med. 2022 ;15 4417-4432

Identifying Molecular Subtypes and 6-Gene Prognostic Signature Based on Hypoxia for Optimizing Targeted Therapies in Non-Small Cell Lung Cancer.

Jingrong Lin, Shujiao Chen, Linling Xiao, Ziyan Wang, Yanqing Lin, Shungui Xu.

   Background: Non-small cell lung cancer (NSCLC) accounts for a great number of all lung cancer cases. Hypoxia, one of the hallmarks in solid cancer, is closely involved in cancer cell progression and migration. This study aimed to develop a molecular subtyping system based on hypoxia-related genes and construct a prognostic model for NSCLC patients.
Methods: Unsupervised consensus clustering was used to classify molecular subtypes. Mutation and immune analyses were conducted to compare differences among the molecular subtypes. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO) analysis, and step Akaike information criterion (stepAIC) were performed to screen prognostic genes.
Results: Two molecular subtypes (C1 and C2) were identified based on hypoxia-related genes and showed significant differences in survival, enriched pathways, tumor microenvironment (TME), and sensitivity to immunotherapy and chemotherapy. Interestingly, C1 subtype had better survival and response to targeted therapies. Oncogenic pathways, such as hypoxia, epithelial mesenchymal transition (EMT), NOTCH signaling, and p53 signaling pathways were more enriched in C2 subtype. A 6-gene prognostic model with robust ability was developed to classify NSCLC patients into high-risk and low-risk groups.
Conclusion: The novel molecular subtypes could assist personalized therapies to select suitable patients. The six prognostic genes may be novel targets for further understanding mechanisms of NSCLC development associated with hypoxia and exploiting novel targeted therapies.

Keywords:  bioinformatics analysis; hypoxia; immunotherapy; molecular subtypes; non-small cell lung cancer; prognostic genes; tumor microenvironment

DOI:  https://doi.org/10.2147/IJGM.S352238
Front Nutr. 2022 ;9 860285

De novo Creation and Assessment of a Prognostic Fat-Age-Inflammation Index "FAIN" in Patients With Cancer: A Multicenter Cohort Study.

Liangyu Yin, Chunhua Song, Jiuwei Cui, Xin Lin, Na Li, Yang Fan, Ling Zhang, Jie Liu, Feifei Chong, Chang Wang, Tingting Liang, Xiangliang Liu, Li Deng, Mei Yang, Jiami Yu, Xiaojie Wang, Xing Liu, Shoumei Yang, Zheng Zuo, Kaitao Yuan, Miao Yu, Minghua Cong, Zengning Li, Min Weng, Qinghua Yao, Pingping Jia, Suyi Li, Zengqing Guo, Wei Li, Hanping Shi, Hongxia Xu.

   Background and Aims: Malnutrition is highly prevalent and is related to multiple impaired clinical outcomes in cancer patients. This study aimed to de novo create an objective, nutrition-related index specially for prognostic purposes in oncology populations.
Methods: We performed a multicenter cohort study including 14,134 cancer patients. The prognostic impact for each baseline characteristic was estimated by calculating Harrell's C-index. The optimal parameters reflecting the nutritional and inflammatory impact on patients' overall survival were selected to develop the fat-age-inflammation (FAIN) index. The associations of the FAIN with the nutritional status, physical performance, quality of life, short-term outcomes and mortality of patients were comprehensively evaluated. Independent external validation was performed to further assess the prognostic value of the FAIN.
Results: The study enrolled 7,468 men and 6,666 women with a median age of 57 years and a median follow-up of 42 months. The FAIN index was defined as: (triceps skinfold thickness + albumin) / [age + 5 × (neutrophil count/lymphocyte count)]. There were significant associations of the FAIN with the nutritional status, physical performance, quality of life and short-term outcomes. The FAIN also showed better discrimination performance than the Nutritional Risk Index, the Prognostic Nutritional Index and the Controlling Nutritional Status index (all P < 0.05). In multivariable-adjusted models, the FAIN was independently associated with a reduced death hazard both as a continuous variable (HR = 0.57, 95%CI = 0.47-0.68) and per one standard deviation (HR = 0.83, 95%CI = 0.78-0.88). External validation in a multicenter lung cancer cohort (n = 227) further confirmed the prognostic value of the FAIN.
Conclusions: This study created and assessed the prognostic FAIN index, which might act as a feasible option to monitor the nutritional status and help develop intervention strategies to optimize the survival outcomes of cancer patients.

Keywords:  cancer; fat mass; inflammation; malnutrition; mortality

DOI:  https://doi.org/10.3389/fnut.2022.860285
J Immunol Res. 2022 ;2022 1951620

A Comprehensive Prognostic and Immune Analysis of Ferroptosis-Related Genes Identifies SLC7A11 as a Novel Prognostic Biomarker in Lung Adenocarcinoma.

Li Qian, Fu Wang, Shu-Min Lu, Hua-Jie Miao, Xin He, Jia Feng, Hua Huang, Rong-Feng Shi, Jian-Guo Zhang.

Lung adenocarcinoma (LUAD) is still one of the illnesses with the greatest mortality and morbidity. As a recently identified mode of cellular death, the activation of ferroptosis may promote the effectiveness of antitumor therapies in several types of tumors. However, the expression and clinical significance of Ferroptosis-associated genes in LUAD are still elusive. The RNA sequencing data of LUAD and relevant clinical data were downloaded from The Cancer Genome Atlas (TCGA) datasets. Subsequently, potential prognostic biomarkers were determined by the use of biological information technology. The R software package "ggalluvial" was applied to structure Sanguini diagram. Herein, our team screened 14 dysregulated ferroptosis-associated genes in LUAD. Among them, only four genes were associated with clinical outcome of LUAD patients, including ATP5MC3, FANCD2, GLS2, and SLC7A11. In addition, we found that high SLC7A11 expression predicted an advanced clinical progression in LUAD patients. Additionally, 8 immune checkpoint genes and 7 immune cells for LUAD were recognized to be related to the expression of SLC7A11. KEGG assays indicated that high expression of SLC7A11 might participate in the modulation of intestinal immune network for IgA generation and Staphylococcus aureus infection. Overall, our findings revealed that SLC7A11 might become a potentially diagnostic biomarker and SLC7A11 might serve as an independent prognosis indicator for LUAD.

DOI: https://doi.org/10.1155/2022/1951620