bims-meluca 2023-02-19 papers

on Metabolism of non-small cell lung carcinoma

Issue of 2023‒02‒19
nine papers selected by
the Muñoz-Pinedo/Nadal (PReTT) lab
L’Institut d’Investigació Biomèdica de Bellvitge

Identification of four metabolic subtypes and key prognostic markers in lung adenocarcinoma based on glycolytic and glutaminolytic pathways.
Xanthine dehydrogenase rewires metabolism and the survival of nutrient deprived lung adenocarcinoma cells by facilitating UPR and autophagic degradation.
SLC3A2 Promotes Tumor Associated Macrophage Polarization via Metabolic Reprogramming in Lung Cancer.
Decreased monocyte-to-lymphocyte ratio was associated with satisfied outcomes of first-line PD-1 inhibitors plus chemotherapy in stage IIIB-IV non-small cell lung cancer.
Glucose deprivation promotes pseudo-hypoxia and de-differentiation in lung adenocarcinoma.
A prognostic baseline blood biomarker and tumor growth kinetics integrated model in paclitaxel/platinum treated advanced non-small cell lung cancer patients.
Low muscle mass in lung cancer is associated with an inflammatory and immunosuppressive tumor microenvironment.
Clinical impact of cachexia biomarkers in advanced cancer.
A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer.

BMC Cancer. 2023 Feb 13. 23(1): 152

Identification of four metabolic subtypes and key prognostic markers in lung adenocarcinoma based on glycolytic and glutaminolytic pathways.

Jinjin Zhang, Xiaopeng Wang, Congkuan Song, Qi Li.

  BACKGROUND: Glucose and glutamine are the main energy sources for tumor cells. Whether glycolysis and glutaminolysis play a critical role in driving the molecular subtypes of lung adenocarcinoma (LUAD) is unknown. This study attempts to identify LUAD metabolic subtypes with different characteristics and key genes based on gene transcription profiling data related to glycolysis and glutaminolysis, and to construct prognostic models to facilitate patient outcome prediction.METHODS: LUAD related data were obtained from the Cancer Genome Atlas and Gene Expression Omnibus, including TCGA-LUAD, GSE42127, GSE68465, GSE72094, GSE29013, GSE31210, GSE30219, GSE37745, GSE50081. Unsupervised consensus clustering was used for the identification of LUAD subtypes. Differential expression analysis, weighted gene co-expression network analysis (WGCNA) and CytoNCA App in Cytoscape 3.9.0 were used for the screening of key genes. The Cox proportional hazards model was used for the construction of the prognostic risk model. Finally, qPCR analysis, immunohistochemistry and immunofluorescence colocalization were used to validate the core genes of the model.
RESULT: This study identified four distinct characterized LUAD metabolic subtypes, glycolytic, glutaminolytic, mixed and quiescent types. The glycolytic type had a worse prognosis than the glutaminolytic type. Nine genes (CXCL8, CNR1, AGER, ALB, S100A7, SLC2A1, TH, SPP1, LEP) were identified as hub genes driving the glycolytic/glutaminolytic LUAD. In addition, the risk assessment model constructed based on three genes (SPP1, SLC2A1 and AGER) had good predictive performance and could be validated in multiple independent external LUAD cohorts. These three genes were differentially expressed in LUAD and lung normal tissues, and might be potential prognostic markers for LUAD.
CONCLUSION: LUAD can be classified into four different characteristic metabolic subtypes based on the glycolysis- and glutaminolysis-related genes. Nine genes (CXCL8, CNR1, AGER, ALB, S100A7, SLC2A1, TH, SPP1, LEP) may play an important role in the subtype-intrinsic drive. This metabolic subtype classification, provides new biological insights into the previously established LUAD subtypes.

Keywords:  Glutaminolysis; Glycolysis; Lung adenocarcinoma (LUAD); Metabolic subtype

DOI:  https://doi.org/10.1186/s12885-023-10622-x
Int J Biol Sci. 2023 ;19(3): 772-788

Xanthine dehydrogenase rewires metabolism and the survival of nutrient deprived lung adenocarcinoma cells by facilitating UPR and autophagic degradation.

Man-Man Chen, Wei Guo, Si-Meng Chen, Xiao-Zhen Guo, Lan Xu, Xiao-Yu Ma, Yu-Xiang Wang, Cen Xie, Ling-Hua Meng.

  Xanthine dehydrogenase (XDH) is the rate-limiting enzyme in purine catabolism by converting hypoxanthine to xanthine and xanthine to uric acid. The altered expression and activity of XDH are associated with the development and prognosis of multiple types of cancer, while its role in lung adenocarcinoma (LUAD) remains unknown. Herein, we demonstrated that XDH was highly expressed in LUAD and was significantly correlated with poor prognosis. Though inhibition of XDH displayed moderate effect on the viability of LUAD cells cultured in the complete medium, it significantly attenuated the survival of starved cells. Similar results were obtained in XDH-knockout cells. Nucleosides supplementation rescued the survival of starved LUAD cells upon XDH inhibition, while inhibition of purine nucleoside phosphorylase abrogated the process, indicating that nucleoside degradation is required for the XDH-mediated survival of LUAD cells. Accordingly, metabolic flux revealed that ribose derived from nucleoside fueled key carbon metabolic pathways to sustain the survival of starved LUAD cells. Mechanistically, down-regulation of XDH suppressed unfolded protein response (UPR) and autophagic flux in starved LUAD cells. Inhibition of XDH decreased the level of amino acids produced by autophagic degradation, which was accompanied with down-regulation of mTORC1 signaling. Supplementation of amino acids including glutamine or glutamate rescued the survival of starved LUAD cells upon knockout or inhibition of XDH. Finally, XDH inhibitors potentiated the anti-cancer activity of 2-deoxy-D-glucose that induced UPR and/or autophagy in vitro and in vivo. In summary, XDH plays a crucial role in the survival of starved LUAD cells and targeting XDH may improve the efficacy of drugs that induce UPR and autophagy in the therapy of LUAD.

Keywords:  LUAD; UPR; Xanthine dehydrogenase; autophagy; cell survival; nucleoside degradation

DOI:  https://doi.org/10.7150/ijbs.78948
Cancer Sci. 2023 Feb 15.

SLC3A2 Promotes Tumor Associated Macrophage Polarization via Metabolic Reprogramming in Lung Cancer.

Zhuan Li, Songming Chen, Xiang He, Siyuan Gong, Lunquan Sun, Liang Weng.

  Tumor associated macrophages (TAMs) are one of the most abundant immunosuppressive cells in the tumor microenvironment and possess crucial functions in facilitating tumor progression. Emerging evidences indicate that altered metabolic properties in cancer cell support the tumorigenic functions of TAMs. However, mechanisms and mediators underly crosstalk between cancer cell and TAMs remain largely unknown. In present study, we revealed that high Solute Carrier Family 3 Member 2 (SLC3A2) expression in lung cancer patients were associated with TAMs and poor prognosis. Knockdown of SLC3A2 in lung adenocarcinoma cells impaired M2 polarization of macrophages in co-culture system. By using metabolome analysis, we identified that knockdown SLC3A2 altered metabolism of lung cancer cells and changed multiple metabolites including arachidonic acid in the tumor microenvironment. More importantly, we demonstrated that arachidonic acid was responsible for SLC3A2 mediated macrophage polarization in the tumor microenvironment to differentiate into M2 type both in vitro and in vivo. Our data illustrate previously undescribed mechanisms responsible for TAMs polarization and suggest that SLC3A2 acts as a metabolic switch on lung adenocarcinoma cells to induce macrophage phenotypic reprogramming via arachidonic acid.

Keywords:  Arachidonic acid; Lung adenocarcinoma; Macrophage polarization; SLC3A2; Tumor associated macrophage

DOI:  https://doi.org/10.1111/cas.15760
Front Immunol. 2023 ;14 1094378

Decreased monocyte-to-lymphocyte ratio was associated with satisfied outcomes of first-line PD-1 inhibitors plus chemotherapy in stage IIIB-IV non-small cell lung cancer.

Liang Zheng, Anning Xiong, Shuyuan Wang, Jianlin Xu, Yinchen Shen, Runbo Zhong, Jun Lu, Tianqing Chu, Wei Zhang, Ying Li, Xiaoxuan Zheng, Baohui Han, Hua Zhong, Wei Nie, Xueyan Zhang.

  Objectives: Immune-checkpoint inhibitors (ICIs) combined with chemotherapy are more widely used than monotherapy and have shown better survival in patients with advanced non-small cell lung cancer (NSCLC) without oncogenic driver alterations. The monocyte-to-lymphocyte ratio (MLR) might predict the treatment outcomes of ICI therapy in advanced NSCLC patients but has not yet been investigated. In addition, the cutoff of MLR is controversial. Therefore, the present study aimed to explore the associations between changes in MLR at the initial stage of treatment and clinical outcomes in stage IIIB-IV NSCLC patients receiving first-line PD-1 inhibitor combined with chemotherapy.Methods: The present study included 139 stage IIIB-IV NSCLC patients treated with first-line PD-1 inhibitor combined with chemotherapy. The blood results were assessed 10 days before initiation of PD-1 inhibitor-based combination therapy (time point 1, baseline) and before the third cycle of combined therapy (time point 2). Compared to altered MLR, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) in baseline and in time point 2, patients were divided into decreased MLR/NLR/PLR and increased MLR/NLR/PLR groups. The objective response rate (ORR), progression-free survival (PFS), and the association with the changes in blood indicators were analyzed.
Results: A total of 48 patients were categorized in the decreased MLR group and 91 in the increased MLR group. Patients with decreased MLR had a significantly higher ORR in the univariate (P<0.001) and multivariate (P<0.001) Cox proportional hazards models. On the other hand, decreased MLR was significantly associated with prolonged PFS in the univariate (P=0.007) and multivariate (P=0.016) analyses. Next, 91 patients comprised the decreased NLR group and 48 as the increased NLR group. Patients with decreased NLR exhibited high ORR (P=0.001) and prolonged PFS in univariate analysis (P=0.033). Then, 64 patients comprised the decreased PLR group and 75 the increased PLR group. Decreased PLR was significantly associated with high ORR in univariate (P<0.001) and multivariate (P=0.017) analyses. The subgroup analyses showed that decreased MLR was significantly associated with satisfactory outcomes in patients with all PD-L1 expressions.
Conclusion: Decreased MLR was associated with high ORR and long PFS and might have a potential predictive value in patients with stage IIIB-IV NSCLC treated with first-line PD-1 inhibitor combined with chemotherapy. In addition, changes in MLR might have predictive value in all PD-L1-expressing populations. Decreased NLR and PLR also showed improved survival, suggesting that changes in NLR and PLR may be complementary to predicting prognosis.

Keywords:  chemotherapy; immune checkpoint inhibitors (ICI); monocyte-to-lymphocyte ratio (MLR); non-small cell lung cancer (NSCLC); prognostic value

DOI:  https://doi.org/10.3389/fimmu.2023.1094378
bioRxiv. 2023 Feb 01. pii: 2023.01.30.526207. [Epub ahead of print]

Glucose deprivation promotes pseudo-hypoxia and de-differentiation in lung adenocarcinoma.

Pasquale Saggese, Aparamita Pandey, Eileen Fung, Abbie Hall, Jane Yanagawa, Erika F Rodriguez, Tristan R Grogan, Giorgio Giurato, Giovanni Nassa, Annamaria Salvati, Alessandro Weisz, Steven M Dubinett, Claudio Scafoglio.

Increased utilization of glucose is a hallmark of cancer. Several studies are investigating the efficacy of glucose restriction by glucose transporter blockade or glycolysis inhibition. However, the adaptations of cancer cells to glucose restriction are unknown. Here, we report the discovery that glucose restriction in lung adenocarcinoma (LUAD) induces cancer cell de-differentiation, leading to a more aggressive phenotype. Glucose deprivation causes a reduction in alpha-ketoglutarate (αKG), leading to attenuated activity of αKG-dependent histone demethylases and histone hypermethylation. We further show that this de-differentiated phenotype depends on unbalanced EZH2 activity, causing inhibition of prolyl-hydroxylase PHD3 and increased expression of hypoxia inducible factor 1α (HIF1α), triggering epithelial to mesenchymal transition. Finally, we identified an HIF1α-dependent transcriptional signature with prognostic significance in human LUAD. Our studies further current knowledge of the relationship between glucose metabolism and cell differentiation in cancer, characterizing the epigenetic adaptation of cancer cells to glucose deprivation and identifying novel targets to prevent the development of resistance to therapies targeting glucose metabolism.

DOI: https://doi.org/10.1101/2023.01.30.526207
CPT Pharmacometrics Syst Pharmacol. 2023 Feb 13.

A prognostic baseline blood biomarker and tumor growth kinetics integrated model in paclitaxel/platinum treated advanced non-small cell lung cancer patients.

Francis Williams Ojara, Andrea Henrich, Nicolas Frances, Yomna M Nassar, Wilhelm Huisinga, Niklas Hartung, Kimberly Geiger, Stefan Holdenrieder, Markus Joerger, Charlotte Kloft.

Paclitaxel/platinum chemotherapy, the backbone of standard first-line treatment of advanced non-small cell lung cancer (NSCLC), exhibits high interpatient variability in treatment response and high toxicity burden. Baseline blood biomarker concentrations and tumor size (sum of diameters) at week 8 relative to baseline (RS8) are widely investigated prognostic factors. However, joint analysis of data on demographic/clinical characteristics, blood biomarker levels, and chemotherapy exposure-driven early tumor response for improved prediction of overall survival (OS) is clinically not established. We developed a Weibull time-to-event model to predict OS, leveraging data from 365 patients receiving 3-weekly paclitaxel/platinum combination chemotherapy for ≤6 cycles. A developed tumor growth inhibition model, combining linear tumor growth and first-order paclitaxel area under the concentration-time curve-induced tumor decay, was used to derive individual RS8. The median model-derived RS8 in all patients was a 20.0% tumor size reduction (range: -78%, +15%). While baseline carcinoembryonic antigen, cytokeratin fragments and thyroid stimulating hormone levels were not significantly associated with OS in a subset of 221 patients, and lactate dehydrogenase, interleukin-6 and neutrophil-to-lymphocyte ratio levels were significant only in univariate analyses (p-value<0.05), C-reactive protein in combination with RS8 most significantly affected OS (p-value<0.01). Compared to the median population OS of 11.3 months, OS was 128% longer at the 5th percentile levels of both covariates and 60% shorter at their 95th percentiles levels. The combined paclitaxel exposure-driven RS8 and baseline blood CRP concentrations enables early individual prognostic predictions for different paclitaxel dosing regimens, forming the basis for treatment decision and optimizing paclitaxel/platinum-based advanced NSCLC chemotherapy.

DOI: https://doi.org/10.1002/psp4.12937
J Transl Med. 2023 02 11. 21(1): 116

Low muscle mass in lung cancer is associated with an inflammatory and immunosuppressive tumor microenvironment.

Sarah Santiloni Cury, Diogo de Moraes, Jakeline Santos Oliveira, Paula Paccielli Freire, Patricia Pintor Dos Reis, Miguel Luiz Batista, Érica Nishida Hasimoto, Robson Francisco Carvalho.

  BACKGROUND: Computed tomographies (CT) are useful for identifying muscle loss in non-small lung cancer (NSCLC) cachectic patients. However, we lack consensus on the best cutoff point for pectoralis muscle loss. We aimed to characterize NSCLC patients based on muscularity, clinical data, and the transcriptional profile from the tumor microenvironment to build a cachexia classification model.METHODS: We used machine learning to generate a muscle loss prediction model, and the tumor's cellular and transcriptional profile was characterized in patients with low muscularity. First, we measured the pectoralis muscle area (PMA) of 211 treatment-naive NSCLC patients using CT available in The Cancer Imaging Archive. The cutoffs were established using machine learning algorithms (CART and Cutoff Finder) on PMA, clinical, and survival data. We evaluated the prediction model in a validation set (36 NSCLC). Tumor RNA-Seq (GSE103584) was used to profile the transcriptome and cellular composition based on digital cytometry.
RESULTS: CART demonstrated that a lower PMA was associated with a high risk of death (HR = 1.99). Cutoff Finder selected PMA cutoffs separating low-muscularity (LM) patients based on the risk of death (P-value = 0.003; discovery set). The cutoff presented 84% of success in classifying low muscle mass. The high risk of LM patients was also found in the validation set. Tumor RNA-Seq revealed 90 upregulated secretory genes in LM that potentially interact with muscle cell receptors. The LM upregulated genes enriched inflammatory biological processes. Digital cytometry revealed that LM patients presented high proportions of cytotoxic and exhausted CD8+ T cells.
CONCLUSIONS: Our prediction model identified cutoffs that distinguished patients with lower PMA and survival with an inflammatory and immunosuppressive TME enriched with inflammatory factors and CD8+ T cells.

Keywords:  CD8+ T cells; Computed tomography; Machine learning; Non-small cell lung cancer; Transcriptomics

DOI:  https://doi.org/10.1186/s12967-023-03901-5
Ann Palliat Med. 2023 Feb 01. pii: apm-22-1416. [Epub ahead of print]

Clinical impact of cachexia biomarkers in advanced cancer.

Iain Phillips, Mark Stares.



Keywords:  Cachexia; biomarker; inflammation

DOI:  https://doi.org/10.21037/apm-22-1416
Front Oncol. 2023 ;13 1095313

A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer.

Shuai Han, Dongjie Jiang, Feng Zhang, Kun Li, Kun Jiao, Jingyun Hu, Haihan Song, Qin-Yun Ma, Jian Wang.

  Background: Immune checkpoint blockade (ICB) therapy has brought remarkable clinical benefits to patients with advanced non-small cell lung carcinoma (NSCLC). However, the prognosis remains largely variable.Methods: The profiles of immune-related genes for patients with NSCLC were extracted from TCGA database, ImmPort dataset, and IMGT/GENE-DB database. Coexpression modules were constructed using WGCNA and 4 modules were identified. The hub genes of the module with the highest correlations with tumor samples were identified. Then integrative bioinformatics analyses were performed to unveil the hub genes participating in tumor progression and cancer-associated immunology of NSCLC. Cox regression and Lasso regression analyses were conducted to screen prognostic signature and to develop a risk model.
Results: Functional analysis showed that immune-related hub genes were involved in the migration, activation, response, and cytokine-cytokine receptor interaction of immune cells. Most of the hub genes had a high frequency of gene amplifications. MASP1 and SEMA5A presented the highest mutation rate. The ratio of M2 macrophages and naïve B cells revealed a strong negative association while the ratio of CD8 T cells and activated CD4 memory T cells showed a strong positive association. Resting mast cells predicted superior overall survival. Interactions including protein-protein, lncRNA and transcription factor interactions were analyzed and 9 genes were selected by LASSO regression analysis to construct and verify a prognostic signature. Unsupervised hub genes clustering resulted in 2 distinct NSCLC subgroups. The TIDE score and the drug sensitivity of gemcitabine, cisplatin, docetaxel, erlotinib and paclitaxel were significantly different between the 2 immune-related hub gene subgroups.
Conclusions: These findings suggested that our immune-related genes can provide clinical guidance for the diagnosis and prognosis of different immunophenotypes and facilitate the management of immunotherapy in NSCLC.

Keywords:  immune checkpoint molecules; non-small cell lung cancer; prediction; prognosis; signature

DOI:  https://doi.org/10.3389/fonc.2023.1095313