bims-meluca Biomed News
on Metabolism of non-small cell lung carcinoma
Issue of 2022‒06‒12
nine papers selected by
Cristina Muñoz Pinedo
L’Institut d’Investigació Biomèdica de Bellvitge
  1. Integrative metabolomics and transcriptomics analysis reveals novel therapeutic vulnerabilities in lung cancer.
  2. Contribution of Metabolic Tumor Volume and Total Lesion Glycolysis to Predict Prognosis in Early-Stage Lung Cancer at Preoperative Staging.
  3. A CRISPR screen identifies redox vulnerabilities for KEAP1/NRF2 mutant non-small cell lung cancer.
  4. High expression of the phosphoinositide 3-kinase p11γ isoform can predict poor prognosis of non-small cell lung cancer.
  5. Associations of genetic risk, BMI trajectories, and the risk of non-small cell lung cancer: a population-based cohort study.
  6. Prognostic values of inflammatory indexes in bevacizumab-treated patients with advanced non-small-cell lung cancer.
  7. Immune complexome analysis of serum samples from non-small-cell lung cancer patients identifies predictive biomarkers for nivolumab therapy.
  8. Th22 Cells/IL-22 Serves as a Protumor Regulator to Drive Poor Prognosis through the JAK-STAT3/MAPK/AKT Signaling Pathway in Non-Small-Cell Lung Cancer.
  9. Angiogenic Factor-Based Signature Predicts Prognosis and Immunotherapy Response in Non-Small-Cell Lung Cancer.
  1. Cancer Med. 2022 Jun 08.
    Integrative metabolomics and transcriptomics analysis reveals novel therapeutic vulnerabilities in lung cancer.
    Jose Thaiparambil, Jianrong Dong, Sandra L Grimm, Dimuthu Perera, Chandra Shekar R Ambati, Vasanta Putluri, Matthew J Robertson, Tajhal D Patel, Brandon Mistretta, Preethi H Gunaratne, Min P Kim, Jason T Yustein, Nagireddy Putluri, Cristian Coarfa, Randa El-Zein.
      BACKGROUND: Non-small cell lung cancer (NSCLC) comprises the majority (~85%) of all lung tumors, with lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) being the most frequently diagnosed histological subtypes. Multi-modal omics profiling has been carried out in NSCLC, but no studies have yet reported a unique metabolite-related gene signature and altered metabolic pathways associated with LUAD and LUSC.METHODS: We integrated transcriptomics and metabolomics to analyze 30 human lung tumors and adjacent noncancerous tissues. Differential co-expression was used to identify modules of metabolites that were altered between normal and tumor.
    RESULTS: We identified unique metabolite-related gene signatures specific for LUAD and LUSC and key pathways aberrantly regulated at both transcriptional and metabolic levels. Differential co-expression analysis revealed that loss of coherence between metabolites in tumors is a major characteristic in both LUAD and LUSC. We identified one metabolic onco-module gained in LUAD, characterized by nine metabolites and 57 metabolic genes. Multi-omics integrative analysis revealed a 28 metabolic gene signature associated with poor survival in LUAD, with six metabolite-related genes as individual prognostic markers.
    CONCLUSIONS: We demonstrated the clinical utility of this integrated metabolic gene signature in LUAD by using it to guide repurposing of AZD-6482, a PI3Kβ inhibitor which significantly inhibited three genes from the 28-gene signature. Overall, we have integrated metabolomics and transcriptomics analyses to show that LUAD and LUSC have distinct profiles, inferred gene signatures with prognostic value for patient survival, and identified therapeutic targets and repurposed drugs for potential use in NSCLC treatment.
    Keywords:  adenocarcinoma of lung; carcinoma, non-small-cell lung; carcinoma, squamous cell; drug repositioning; lung neoplasms; metabolomics; systems biology; transcriptome
    DOI:  https://doi.org/10.1002/cam4.4933
  2. J Coll Physicians Surg Pak. 2022 Jun;32(6): 740-745
    Contribution of Metabolic Tumor Volume and Total Lesion Glycolysis to Predict Prognosis in Early-Stage Lung Cancer at Preoperative Staging.
    Elanur Karaman, Sibel Goksel, Kerim Tuluce.
      OBJECTIVE: To evaluate the effect of metabolic tumor volume (MTV) and total lesion glycolysis (TLG) values of the primary tumor measured by preoperative positron emission tomography/computed tomography (FDG-PET/CT) on survival in patients with operated non-small cell lung cancer (NSCLC).STUDY DESIGN: Cohort study.
    PLACE AND DURATION OF STUDY: Recep Tayyip Erdogan University, Faculty of Medicine, Department of Medical Oncology from January 2017 to June 2020, Turkey.
    METHODOLOGY: Patients with operated NSCLC were reviewed retrospectively. Metabolic parameters of FDG-PET/CT such as pathological tumor features, type of operation, MTV/TLG values, and whether they received adjuvant therapy were evaluated. Disease-free survival (DFS) and overall survival (OS) times were calculated.
    RESULTS: Most of the 77 patients (96.1%) were male. The mean age is 64±8 years. Lobectomy was performed in 66 (85.7%) patients, and pneumonectomy was performed in 11 (14.3%) patients. The mean tumor diameter was 3.7±2.015cm. Squamous cell carcinoma was detected in 37 patients (48.1%) and adenocarcinoma in 35 patients (45.5%). Thirty-eight patients (49.4%) received adjuvant chemotherapy. SUVmax, MTV, and TLG values of the primary tumor were high in patients under 65 years of age and with a tumor diameter of ≥3cm. DFS was nine months (4.5-18), and OS was 19 months (11-29). The 2-year survival rate was 75.6%. It was observed that patients with adenocarcinoma relapsed more frequently, which negatively affected survival (p=0.023, and p=0.024 respectively). High MTV (p=0.01) and TLG (p=0.015) values were associated with poor prognosis.
    CONCLUSION: NSCLC is a heterogeneous disease, and survival is affected by many factors. Our study showed that the subtype of adenocarcinoma and high MTV and TLG values of the primary tumor are poor prognostic factors in operated early-stage lung cancers.
    KEY WORDS: Early-stage, Non-small cell lung cancer, MTV, TLG, NSCLC, Survival, FDG-PET/CT.
    DOI:  https://doi.org/10.29271/jcpsp.2022.06.740
  3. Redox Biol. 2022 Jun 02. pii: S2213-2317(22)00130-6. [Epub ahead of print]54 102358
    A CRISPR screen identifies redox vulnerabilities for KEAP1/NRF2 mutant non-small cell lung cancer.
    Chang Jiang, Nathan P Ward, Nicolas Prieto-Farigua, Yun Pyo Kang, Anish Thalakola, Mingxiang Teng, Gina M DeNicola.
      The redox regulator NRF2 is hyperactivated in a large percentage of non-small cell lung cancer (NSCLC) cases, which is associated with chemotherapy and radiation resistance. To identify redox vulnerabilities for KEAP1/NRF2 mutant NSCLC, we conducted a CRISPR-Cas9-based negative selection screen for antioxidant enzyme genes whose loss sensitized cells to sub-lethal concentrations of the superoxide (O2•-) -generating drug β-Lapachone. While our screen identified expected hits in the pentose phosphate pathway, the thioredoxin-dependent antioxidant system, and glutathione reductase, we also identified the mitochondrial superoxide dismutase 2 (SOD2) as one of the top hits. Surprisingly, β-Lapachone did not generate mitochondrial O2•- but rather SOD2 loss enhanced the efficacy of β-Lapachone due to loss of iron-sulfur protein function, loss of mitochondrial ATP maintenance and deficient NADPH production. Importantly, inhibition of mitochondrial electron transport activity sensitized cells to β-Lapachone, demonstrating that these effects may be translated to increase ROS sensitivity therapeutically.
    Keywords:  KEAP1; NADPH; NFE2L2; NSCLC; ROS; SOD2; β-Lapachone
    DOI:  https://doi.org/10.1016/j.redox.2022.102358
  4. Histol Histopathol. 2022 Jun 08. 18480
    High expression of the phosphoinositide 3-kinase p11γ isoform can predict poor prognosis of non-small cell lung cancer.
    Ina Jung, Hyoun Wook Lee, Mee Sook Roh, Jae Seok Lee, Kisu Kim, Kyungeun Kim, Tae Gyu Kim, Hyun-Yeol Nam.
      The protein p110γ is an isoform of the catalytic subunit of class I phosphoinositide 3-kinases (PI3Ks). PI3Ks are involved in the regulation of cell survival, growth, proliferation, and migration and have been implicated in the oncogenesis of various cancers. In this study, p110γ expression in non-small cell lung cancer (NSCLC) and its association with clinicopathological factors and patient survival were evaluated. A total of 230 NSCLC tumors were immunohistochemically stained for p110γ. Of these, 174 (75.7%) and 56 (24.3%) were placed in the low and high expression groups, respectively. The positive rate of p110γ was significantly higher in adenocarcinoma than in squamous cell carcinoma (p⟨0.001). Advanced stage NSCLCs showed higher p110γ expression than those at an early stage (p=0.002). Irrespective of the histological tumor type, the patients with high p110γ expression had significantly worse overall survival than those with low p110γ expression (p=0.004). p110γ expression was an independent poor prognostic factor in the multivariate analysis. Our results suggest that p110γ may be involved in the development and progression of NSCLC, and that p110γ has promising potential as a prognostic factor or novel therapeutic target for NSCLC.
    DOI:  https://doi.org/10.14670/HH-18-480
  5. BMC Med. 2022 Jun 06. 20(1): 203
    Associations of genetic risk, BMI trajectories, and the risk of non-small cell lung cancer: a population-based cohort study.
    Dongfang You, Danhua Wang, Yaqian Wu, Xin Chen, Fang Shao, Yongyue Wei, Ruyang Zhang, Theis Lange, Hongxia Ma, Hongyang Xu, Zhibin Hu, David C Christiani, Hongbing Shen, Feng Chen, Yang Zhao.
      BACKGROUND: Body mass index (BMI) has been found to be associated with a decreased risk of non-small cell lung cancer (NSCLC); however, the effect of BMI trajectories and potential interactions with genetic variants on NSCLC risk remain unknown.METHODS: Cox proportional hazards regression model was applied to assess the association between BMI trajectory and NSCLC risk in a cohort of 138,110 participants from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. One-sample Mendelian randomization (MR) analysis was further used to access the causality between BMI trajectories and NSCLC risk. Additionally, polygenic risk score (PRS) and genome-wide interaction analysis (GWIA) were used to evaluate the multiplicative interaction between BMI trajectories and genetic variants in NSCLC risk.
    RESULTS: Compared with individuals maintaining a stable normal BMI (n = 47,982, 34.74%), BMI trajectories from normal to overweight (n = 64,498, 46.70%), from normal to obese (n = 21,259, 15.39%), and from overweight to obese (n = 4,371, 3.16%) were associated with a decreased risk of NSCLC (hazard ratio [HR] for trend = 0.78, P < 2×10-16). An MR study using BMI trajectory associated with genetic variants revealed no significant association between BMI trajectories and NSCLC risk. Further analysis of PRS showed that a higher GWAS-identified PRS (PRSGWAS) was associated with an increased risk of NSCLC, while the interaction between BMI trajectories and PRSGWAS with the NSCLC risk was not significant (PsPRS= 0.863 and PwPRS= 0.704). In GWIA analysis, four independent susceptibility loci (P < 1×10-6) were found to be associated with BMI trajectories on NSCLC risk, including rs79297227 (12q14.1, located in SLC16A7, Pinteraction = 1.01×10-7), rs2336652 (3p22.3, near CLASP2, Pinteraction = 3.92×10-7), rs16018 (19p13.2, in CACNA1A, Pinteraction = 3.92×10-7), and rs4726760 (7q34, near BRAF, Pinteraction = 9.19×10-7). Functional annotation demonstrated that these loci may be involved in the development of NSCLC by regulating cell growth, differentiation, and inflammation.
    CONCLUSIONS: Our study has shown an association between BMI trajectories, genetic factors, and NSCLC risk. Interestingly, four novel genetic loci were identified to interact with BMI trajectories on NSCLC risk, providing more support for the aetiology research of NSCLC.
    TRIAL REGISTRATION: http://www.
    CLINICALTRIALS: gov , NCT01696968 .
    Keywords:  Body mass index; Genome-wide interaction study; Non-small cell lung cancer; Trajectory
    DOI:  https://doi.org/10.1186/s12916-022-02400-6
  6. Future Sci OA. 2022 Mar;8(5): FSO798
    Prognostic values of inflammatory indexes in bevacizumab-treated patients with advanced non-small-cell lung cancer.
    Jingru Yang, Mingliang Deng, Minghong Bi, Yaping Wang, Xuxu Qiao, Shanshan Zhang.
      Purpose: Inflammatory indexes, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII) and lymphocyte-to-monocyte ratio (LMR), have been confirmed as prognostic factors in multiple manigances. However, the prognostic value of these parameters in bevacizumab-treated non-small-cell lung cancer (NSCLC) is still not clear.Methods: We retrospectively studied 119 patients with advanced NSCLC who received bevacizumab treatment. The associations of pretreatment NLR, PLR, SII and LMR with progression-free survival (PFS) and overall survival (OS) were analyzed.
    Results & Conclusion: The median PFS and OS of patients with high baseline NLR, PLR and SII and low LMR were significantly decreased than those of patients with low baseline NLR, PLR and SII and high LMR. Multivariable analysis indicated that high baseline SII was independently related with inferior prognosis, and baseline LMR was an independent predictor for OS.
    Keywords:  bevacizumab; lymphocyte-to-monocyte ratio; neutrophil-to-lymphocyte ratio; non-small-cell lung cancer; platelet-to-lymphocyte ratio; systemic immune-inflammation index
    DOI:  https://doi.org/10.2144/fsoa-2021-0162
  7. Clin Chim Acta. 2022 Jun 03. pii: S0009-8981(22)01173-1. [Epub ahead of print]532 84-88
    Immune complexome analysis of serum samples from non-small-cell lung cancer patients identifies predictive biomarkers for nivolumab therapy.
    Rika Aizawa, Yoichi Nakamura, Takaya Ikeda, Nozomi Aibara, Yuki J Kutsuna, Tomoaki Kurosaki, Keisei Aki, Hashizume Junya, Hiroo Nakagawa, Kayoko Sato, Yukinobu Kodama, Mihoko N Nakashima, Mikiro Nakashima, Hiroshi Mukae, Kaname Ohyama.
      BACKGROUND: Immune checkpoint inhibitors (ICIs) have achieved important outcomes in cancer treatment. However, current clinical biomarker tests are not suitable for some patients because they require tumor tissues and have poor predictive value for treatment responses. Therefore, the identification of biomarkers that enable screening tests in all patients is necessary.METHODS: We performed an immune complexome analysis of non-small cell lung cancer patients treated with nivolumab to comprehensively identify and compare antigens incorporated into immune complexes (IC-antigens) in serum samples from the responders (n = 15) and non-responders (n = 20). Additionally, combinations of IC-antigens characteristic to the responder group were evaluated by logistic regression analysis and receiver operating characteristics curves to examine their predictiveness for ICI treatment responses.
    RESULTS: The combination of predictive biomarkers detected before treatment was profilin-1, purine nucleoside phosphorylase, alpha-enolase, and nucleoside diphosphate kinase A [p = 0.0043, odds ratio = 2.26, 95% confidence interval (CI) = 1.19-4.28, area under the curve = 0.76]. The combination of predictive biomarkers detected after treatment was peptidyl-prolyl cis-trans isomerase A, ubiquitin-like modifier-activating enzyme 1, complement component C8 beta chain, and apolipoprotein L1 (p = 0.0039, odds ratio = 2.56, 95% CI = 1.25-5.23, area under the curve = 0.77).
    CONCLUSION: Combinations of serum IC-antigens may predict the therapeutic effect of nivolumab in non-small cell lung cancer patients.
    Keywords:  Immune complex antigen; Immune complexome analysis; Nivolumab; Non-small-cell lung cancer; Therapeutic predictive biomarker
    DOI:  https://doi.org/10.1016/j.cca.2022.05.021
  8. J Immunol Res. 2022 ;2022 8071234
    Th22 Cells/IL-22 Serves as a Protumor Regulator to Drive Poor Prognosis through the JAK-STAT3/MAPK/AKT Signaling Pathway in Non-Small-Cell Lung Cancer.
    Yinan Yao, Guangdie Yang, Guohua Lu, Jiani Ye, Luyun Cui, Zhu Zeng, Junjun Chen, Jianying Zhou.
      The interaction of immune cells and cytokines in the tumor microenvironment affects the development and prognosis of tumors with an unclear potential regulatory mechanism. Recent studies have elucidated the protumor role of Th22 cells and its lineage-specific cytokine IL-22 in different human cancers. The present study is aimed at investigating the biological effect of Th22 cells/IL-22 and its molecular mechanism in the pathogenesis process of non-small-cell lung cancer (NSCLC). It was initially found that Th22 cells were enriched in the peripheral blood of NSCLC patients. The level of Th22 cells in peripheral blood mononuclear cells (PBMCs) was positively correlated with the TNM stage, lymph node metastasis, and clinical tumor biomarkers. Furthermore, IL-22 not only antagonized the apoptosis inducing and cell cycle arresting effect by chemotherapy and molecular targeted drugs on NSCLC cell lines but also promoted tumor cell proliferation and tumor tissue growth. Moreover, IL-22 activated the JAK-STAT3/MAPK/AKT signaling pathway, both in vitro and in vivo. Conclusively, the present results confirm that Th22 cells/IL-22 may serve as a negative immune regulator in lung cancer.
    DOI:  https://doi.org/10.1155/2022/8071234
  9. Front Genet. 2022 ;13 894024
    Angiogenic Factor-Based Signature Predicts Prognosis and Immunotherapy Response in Non-Small-Cell Lung Cancer.
    Xinpei Gu, Liuxi Chu, Yanlan Kang.
      Non-small-cell lung cancer (NSCLC) is one of the most common malignancies, and specific molecular targets are still lacking. Angiogenesis plays a central regulatory role in the growth and metastasis of malignant tumors and angiogenic factors (AFs) are involved. Although there are many studies comparing AFs and cancer, a prognostic risk model for AFs and cancer in humans has not been reported in the literature. This study aimed to identify the key AFs closely related to the process of NSCLC development, and four genes have been found, C1QTNF6, SLC2A1, PTX3, and FSTL3. Then, we constructed a novel prognostic risk model based on these four genes in non-small-cell lung cancer (NSCLC) and fully analyzed the relationship with clinical features, immune infiltration, genomes, and predictors. This model had good discrimination and calibration and will perform well in predicting the prognosis of treatment in clinical practice.
    Keywords:  NSCLC; angiogenic factors; biomarkers; immunotherapy response; model validation
    DOI:  https://doi.org/10.3389/fgene.2022.894024
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