bims-meluca 2022-10-09 papers

on Metabolism of non-small cell lung carcinoma

Issue of 2022–10–09
eight papers selected by
the Muñoz-Pinedo/Nadal (PReTT) lab, L’Institut d’Investigació Biomèdica de Bellvitge

Correlation of Tryptophan Metabolic Pathway with Immune Activation and Chemosensitivity in Patients with Lung Adenocarcinoma.
Platelet Count as a Prognostic Factor in Stage IV Non-Small Cell Lung Cancer.
The clinical significance of preoperative serum triglyceride, high-density lipoprotein, and low-density lipoprotein levels in lung squamous cell carcinoma.
Identidication of novel biomarkers in non-small cell lung cancer using machine learning.
Metformin Synergizes with PD-L1 Monoclonal Antibody Enhancing Tumor Immune Response in Treating Non-Small Cell Lung Cancer and Its Molecular Mechanism Investigation.
LP07 and LLC pre-clinical models of lung cancer induce divergent anabolic deficits and expression of pro-inflammatory effectors of muscle wasting.
Circulating CD81-expressing extracellular vesicles as biomarkers of response for immune-checkpoint inhibitors in advanced NSCLC.
Prognostic Index for Nonsmall Cell Lung Cancer Based on Immune-Related Genes Expression.

J Oncol. 2022 ;2022 2158525

Correlation of Tryptophan Metabolic Pathway with Immune Activation and Chemosensitivity in Patients with Lung Adenocarcinoma.

Zheng Wang, Danni Liu, Rongjie Yang.

Lung adenocarcinoma (LUAD) is the most common type of lung cancer with high malignancy and easy metastasis in the early stage. In this study, we aimed to figure out the role of tryptophan metabolic pathway in LUAD prognosis and treatment. Different molecular subtypes were constructed based on tryptophan metabolism-related genes. Significant prognostic genes and clinical prognostic characteristics, immune infiltration level, and pathway activity in different subtypes were determined by algorithms, such as the least absolute shrinkage and selection operator (Lasso), CIBERSORT, Tumor Immune Dysfunction and Exclusion (TIDE), and gene set enrichment analysis (GSEA). The effect of different gene mutation types on the prognosis of patients with LUAD was explored. The clinical prognosis model was constructed and its reliability was verified. Of the 40 genes in the tryptophan metabolism pathway, 13 had significant prognostic significance. Based on these 13 genes, three molecular subtypes (C1, C2, and C3) were established. Among them, C1 had the worst prognosis and the lowest enrichment score of tryptophan metabolism. At the same time, C1 had the most genetic variation, the highest level of immune infiltration, and significantly activated pathways related to tumor development. The high-risk and low-risk groups had significant differences in prognosis, immune infiltration and pathway enrichment, which was consistent with the results of subtype analysis. Mutation in tryptophan metabolism-related genes leads to abnormal tryptophan metabolism, immune deficiency, and activation of cancer-promoting pathways. This results in high malignancy, poor prognosis, and failure of traditional clinical treatments. Through the establishment of risk score (RS) clinical prognosis model, we determined that RS could reliably predict the prognosis of patients with LUAD.

DOI: https://doi.org/10.1155/2022/2158525
Mymensingh Med J. 2022 Oct;31(4): 937-946

Platelet Count as a Prognostic Factor in Stage IV Non-Small Cell Lung Cancer.

B Saha, N Khatun, N Azim, S A Islam, M F Proteek, M R Islam, F A Begum, M A Biddut, M K Khan, M R Islam.

Increase platelet count can accompany various cancers including lung cancer. This finding has recently been suggested to indicate poor prognosis. In patients with malignancies, thrombocytosis has previously been related disease stage, histological type and survival. In this study, the prevalence of thrombocytosis and the prognostic information provided by platelet count were analyzed in patients with stage IV Non-Small Cell Lung Cancer (NSCLC) with an aim to assess elevated platelet count as a prognostic factor in patients with stage IV NSCLC and to investigate whether there is relationship between thrombocytosis, other clinico-pathologic factors and median survival. This prospective observational study was conducted in National Institute of Cancer Research and Hospital (NICRH), Dhaka, Bangladesh from September 2019 to August 2020. A total of 108 patients were enrolled purposively. Detail history taking, thorough physical examination was done along with relevant investigations. Data were collected by semi structured questionnaire and analysis was done with the help of Statistical Package for Social Science (SPSS), version 21.0. The mean age of the patients was found 56.4±12.2 years with range from 35 to 75 years. Majority (79.6%) patients were male, 52.8% patients came from low income and 36.1% were farmer. Majority (40.7%) were symptomatic; in bed >50.0% of day. Almost two third (59.3%) had <5.0% weight loss. Almost three fourth (69.4%) had squamous cell carcinoma. At the time of first assessment 75(69.4%) patients had normal and 33(30.6%) had elevated platelet count level. Age, sex and histological type were statistically not significant between normal and elevated platelet count level groups. But performance status, weight loss were statistically significant (p<0.05) between two groups. According to univariate analysis, age, performance status at presentation, weight loss more than 10.0% for 3 months and platelet count prior the start of treatment were all significant predictors for the overall survival. In multivariate analysis age, performance status at presentation and initial thrombocytosis were independent prognostic determinants for overall survival. Median survival time was significantly higher for the normal platelet count group and elevated platelet count group (7.5 months versus 5.5 months) respectively (95% CI, 5.5-7.5), p<0.001. The frequency of thrombocytosis in patients with stage-IV NSCLC at first presentation was 30.6% and median survival time in these patients was significantly shorter compared in patients without thrombocytosis. These results concluded that an elevated platelet count could be a useful prognostic factor for survival in patients with stage-IV NSCLC.
Sci Rep. 2022 Oct 07. 12(1): 16828

The clinical significance of preoperative serum triglyceride, high-density lipoprotein, and low-density lipoprotein levels in lung squamous cell carcinoma.

Zhupeng Li, Jianfeng Xu, Weizhong Feng, Zhifeng Ma, Yuanling Wu, Ting Zhu, Peng Xu, Lingjun Dong, JianYi Ding, Junqing Zhou, Guangmao Yu.

To evaluate the prognostic role of the preoperative plasma lipid profile, including triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) in patients with lung squamous cell carcinoma (LUSC) who underwent complete resection. Clinical data, including preoperative plasma profile levels, were retrospectively collected and reviewed in 300 patients with LUSC who underwent radical lung resection between 2016 and 2017. The overall survival (OS) and disease-free survival (DFS) were assessed by the Kaplan-Meier method and the Cox proportional hazards regression model. TG ≤ 1.35, HDL-C ≤ 1.17, and LDL-C ≤ 2.32 were deemed as independent preoperative risk factors for OS, and HDL-C ≤ 1.17 was an independent preoperative risk factor for DFS. In the multivariate analyses involving OS and DFS, a decreased HDL-C level was significantly associated with worse OS (HR, 0.546; 95% CI, 0.380-0.784, P = 0.001) and DFS (HR, 0.644; 95% CI, 0.422-0.981, P = 0.041). Additionally, an increased TG (HR, 0.546; 95% CI, 0.366-0.814, P = 0.003) or LDL-C (HR, 0.652; 95% CI, 0.456-0.933, P = 0.019) level was significantly associated with better OS. In patients with LUSC, decreased levels of HDL-C may predict worse outcomes for both DFS and OS, while increased TG or LDL-C levels may predict better OS.

DOI: https://doi.org/10.1038/s41598-022-18589-8
Sci Rep. 2022 Oct 06. 12(1): 16693

Identidication of novel biomarkers in non-small cell lung cancer using machine learning.

Fangwei Wang, Qisheng Su, Chaoqian Li.

Lung cancer is one of the leading causes of cancer-related deaths worldwide, and non-small cell lung cancer (NSCLC) accounts for a large proportion of lung cancer cases, with few diagnostic and therapeutic targets currently available for NSCLC. This study aimed to identify specific biomarkers for NSCLC. We obtained three gene-expression profiles from the Gene Expression Omnibus database (GSE18842, GSE21933, and GSE32863) and screened for differentially expressed genes (DEGs) between NSCLC and normal lung tissue. Enrichment analyses were performed using Gene Ontology, Disease Ontology, and the Kyoto Encyclopedia of Genes and Genomes. Machine learning methods were used to identify the optimal diagnostic biomarkers for NSCLC using least absolute shrinkage and selection operator logistic regression, and support vector machine recursive feature elimination. CIBERSORT was used to assess immune cell infiltration in NSCLC and the correlation between biomarkers and immune cells. Finally, using western blot, small interfering RNA, Cholecystokinin-8, and transwell assays, the biological functions of biomarkers with high predictive value were validated. A total of 371 DEGs (165 up-regulated genes and 206 down-regulated genes) were identified, and enrichment analysis revealed that these DEGs might be linked to the development and progression of NSCLC. ABCA8, ADAMTS8, ASPA, CEP55, FHL1, PYCR1, RAMP3, and TPX2 genes were identified as novel diagnostic biomarkers for NSCLC. Monocytes were the most visible activated immune cells in NSCLC. The knockdown of the TPX2 gene, a biomarker with a high predictive value, inhibited A549 cell proliferation and migration. This study identified eight potential diagnostic biomarkers for NSCLC. Further, the TPX2 gene may be a therapeutic target for NSCLC.

DOI: https://doi.org/10.1038/s41598-022-21050-5
Evid Based Complement Alternat Med. 2022 ;2022 5983959

Metformin Synergizes with PD-L1 Monoclonal Antibody Enhancing Tumor Immune Response in Treating Non-Small Cell Lung Cancer and Its Molecular Mechanism Investigation.

Yifan Wang, Jingguo Hu, Yu Sun, Bo Song, Yan Zhang, Yusong Lu, Haitao Ma.

Despite non-small cell lung cancer (NSCLC) treatment is proved to be effective using PD-L1 monoclonal antibody (PD-L1 MAb), it is commonly seen in immune-related adverse events reported. We aimed to explore metformin synergized with PD-L1 MAb in treating NSCLC and its potential molecular mechanism. In mice, the transplantable lung cancer models were established and a co-culture system of CD8+T cells and LLC cells was constructed. The anti-tumor effect was assessed by xenograft tumor growth, proliferation signal Ki67 expression, and MTT assays. Immunohistochemistry and western blot assays were also conducted to determine tumor immune response as well as mechanism investigation. The results indicated that tumor volume and cell proliferation were markedly inhibited following metformin synergized with PD-L1 MAb which was more effective than either single metformin or PD-L1 MAb. The cytokines TNF-α, IL-2, and IFN-γ secretion in CD8+ T cells was significantly increased, and the immune response was enhanced by metformin synergized with PD-L1 MAb. Further, the WB results implied that metformin synergized with PD-L1 MAb could activate the AMPK pathway and inhibit mTOR. AMPK inhibitor (Compound C) was added, and the results showed that the anti-tumor effect was reduced in metformin + PD-L1 MAb + CC than in metformin + PD-L1 MAb which indicates the metformin synergized with PD-L1 MAb efficacy was AMPK pathway dependent. In conclusion, metformin synergized with PD-L1 MAb has better efficacy against NSCLC than metformin or PD-L1 MAb alone in an AMPK-dependent way and facilitates increasing CD8+ T cell infiltration and enhancing tumor immune response.

DOI: https://doi.org/10.1155/2022/5983959
J Appl Physiol (1985). 2022 Oct 06.

LP07 and LLC pre-clinical models of lung cancer induce divergent anabolic deficits and expression of pro-inflammatory effectors of muscle wasting.

Daniel J Belcher, Maria Guitart, Brian Hain, Hyo-Gun Kim, David Waning, Esther Barreiro, Gustavo A Nader.

  Pre-clinical models have been instrumental to elucidate the mechanisms underlying muscle wasting in lung cancer (LC). We investigated anabolic deficits and the expression of pro-inflammatory effectors of muscle wasting in the LP07 and Lewis lung carcinoma (LLC) tumor models. Tumor growth resulted in significant weakness in LP07 but not in LLC mice despite similar reductions in gastrocnemius muscle mass in both models. The LP07 tumors caused a reduction in ribosomal (r)RNA and a decrease in rRNA gene (rDNA) transcription elongation, while no changes in ribosomal capacity were evident in LLC tumor bearing mice. Expression of RNA Polymerase I (Pol I) elongation-associated subunits Polr2f, PAF53, and Znrd1 mRNAs was significantly elevated in the LP07 model, while Pol I elongation-related factors FACT and Spt4/5 mRNAs were elevated in the LLC mice. Reductions in RPS6 and 4E-BP1 phosphorylation were similar in both models but was independent of mTOR phosphorylation in LP07 mice. Muscle inflammation was also tumor-specific, IL-6 and TNF-α mRNA increased with LLC tumors, but upregulation of NLRP3 mRNA was independent of tumor type. In summary, while both models caused muscle wasting, only the LP07 model displayed muscle weakness with reductions in ribosomal capacity. Intracellular signaling diverged at the mTOR level with similar reductions in RPS6 and 4E-BP1 phosphorylation regardless of tumor type. The increase in pro-inflammatory factors was more pronounced in the LLC model. Our results demonstrate novel divergent anabolic deficits and expression of pro-inflammatory effectors of muscle wasting in the LP07 and LLC pre-clinical models of lung cancer.

Keywords:  cachexia; inflammation; lung cancer; muscle wasting; ribosomal RNA

DOI:  https://doi.org/10.1152/japplphysiol.00246.2022
Front Immunol. 2022 ;13 987639

Circulating CD81-expressing extracellular vesicles as biomarkers of response for immune-checkpoint inhibitors in advanced NSCLC.

Diego Signorelli, Patrizia Ghidotti, Claudia Proto, Marta Brambilla, Alessandro De Toma, Roberto Ferrara, Giulia Galli, Monica Ganzinelli, Giuseppe Lorusso, Arsela Prelaj, Mario Occhipinti, Giuseppe Viscardi, Valentina Capizzuto, Francesca Pontis, Ilaria Petraroia, Anna Maria Ferretti, Mario Paolo Colombo, Valter Torri, Gabriella Sozzi, Marina Chiara Garassino, Elena Jachetti, Orazio Fortunato.

  PD-L1 in tumor cells is the only used biomarker for anti PD1/PD-L1 immune-checkpoints inhibitors (ICI) in Non Small Cell Lung Cancer (NSCLC) patients. However, this parameter is inaccurate to predict response, especially in patients with low tumor PD-L1. Here, we evaluated circulating EVs as possible biomarkers for ICI in advanced NSCLC patients with low tumoral PD-L1. EVs were isolated from plasma of 64 PD-L1 low, ICI-treated NSCLC patients, classified either as responders (R; complete or partial response by RECIST 1.1) or non-responders (NR). EVs were characterized following MISEV guidelines and by flow cytometry. T cells from healthy donors were triggered in vitro using patients' EVs. Unsupervised statistical approach was applied to correlate EVs' and patients' features to clinical response. R-EVs showed higher levels of tetraspanins (CD9, CD81, CD63) than NR-EVs, significantly associated to better overall response rate (ORR). In multivariable analysis CD81-EVs correlated with ORR. Unsupervised analysis revealed a cluster of variables on EVs, including tetraspanins, significantly associated with ORR and improved survival. R-EVs expressed more costimulatory molecules than NR-EVs although both increased T cell proliferation and partially, activation. Tetraspanins levels on EVs could represent promising biomarkers for ICI response in NSCLC.

Keywords:  CD81 (tetraspanin); PD-L1; extracellular vesicles (EV); immunotherapy; lung cancer

DOI:  https://doi.org/10.3389/fimmu.2022.987639
Biomed Res Int. 2022 ;2022 4779811

Prognostic Index for Nonsmall Cell Lung Cancer Based on Immune-Related Genes Expression.

Ying Cao, Hongyu Zhu, Hailin Shen, Desen Liu, Zhenkai Li, Hailong Shang, Hongdi Du, Ying Wang, Juan Ye.

Immune system dysregulation is associated with tumor incidence and growth. Here, we established an RNA-based individualized immune signature associated with prognosis for nonsmall cell lung cancer (NSCLC) to guide adjuvant therapy. We downloaded publicly accessible data on RNA expression and clinical characteristics of NSCLC from the Cancer Genome Atlas (TCGA). From immune-related genes (IRGs) retrieved from the immunology database and analysis portal (ImmPort) database, we then screened differentially expressed immune-related genes (DEIRGs). Using overall survival (OS) as a clinical endpoint, we identified 26 prognostic DEIRGs via univariate and multivariate Cox regression analysis, and then developed a risk model based on these 26 IRGs with an area under the curve (AUC) of 0.701, and its predictive ability independent from other clinical factors. We also downloaded tumor immune infiltrate data and analyzed the correlations between lymphocytic infiltration with our risk scores, but found no significant association. Furthermore, we retrieved 86 differentially expressed transcription factors (TFs) to assess their regulatory relationships with the 26 prognostic DEIRGs. In summary, we developed a robust risk model to predict survival in patients with NSCLC, based on the expression of 26 IRGs. It provides novel predictive and therapeutic molecular targets.

DOI: https://doi.org/10.1155/2022/4779811