bims-meluca 2024-06-16 papers

on Metabolism of non-small cell lung carcinoma

Issue of 2024‒06‒16
eight papers selected by
the Muñoz-Pinedo/Nadal (PReTT) lab, L’Institut d’Investigació Biomèdica de Bellvitge

Concurrent loss of LKB1 and KEAP1 enhances SHMT-mediated antioxidant defence in KRAS-mutant lung cancer.
Lactate-induced activation of tumor-associated fibroblasts and IL-8-mediated macrophage recruitment promote lung cancer progression.
Tumor metabolic activity is associated with subcutaneous adipose tissue radiodensity and survival in non-small cell lung cancer.
Identification of PSMD11 as a novel cuproptosis- and immune-related prognostic biomarker promoting lung adenocarcinoma progression.
Identification of cachexia in lung cancer patients with an ensemble learning approach.
The clinical features and prognostic implications of the co-mutated TP53 gene in advanced non-small cell lung cancer.
C-reactive protein as robust laboratory value associated with prognosis in patients with stage III non-small cell lung cancer (NSCLC) treated with definitive radiochemotherapy.
High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC).

Nat Metab. 2024 Jun 14.

Concurrent loss of LKB1 and KEAP1 enhances SHMT-mediated antioxidant defence in KRAS-mutant lung cancer.

Hyun Min Lee, Nefertiti Muhammad, Elizabeth L Lieu, Feng Cai, Jiawei Mu, Yun-Sok Ha, Guoshen Cao, Chamey Suchors, Kenneth Joves, Constantinos Chronis, Kailong Li, Gregory S Ducker, Kellen Olszewski, Ling Cai, Derek B Allison, Sara E Bachert, William R Ewing, Harvey Wong, Hyosun Seo, Isaac Y Kim, Brandon Faubert, James Kim, Jiyeon Kim.

Non-small-cell lung cancer (NSCLC) with concurrent mutations in KRAS and the tumour suppressor LKB1 (KL NSCLC) is refractory to most therapies and has one of the worst predicted outcomes. Here we describe a KL-induced metabolic vulnerability associated with serine-glycine-one-carbon (SGOC) metabolism. Using RNA-seq and metabolomics data from human NSCLC, we uncovered that LKB1 loss enhanced SGOC metabolism via serine hydroxymethyltransferase (SHMT). LKB1 loss, in collaboration with KEAP1 loss, activated SHMT through inactivation of the salt-induced kinase (SIK)-NRF2 axis and satisfied the increased demand for one-carbon units necessary for antioxidant defence. Chemical and genetic SHMT suppression increased cellular sensitivity to oxidative stress and cell death. Further, the SHMT inhibitor enhanced the in vivo therapeutic efficacy of paclitaxel (first-line NSCLC therapy inducing oxidative stress) in KEAP1-mutant KL tumours. The data reveal how this highly aggressive molecular subtype of NSCLC fulfills their metabolic requirements and provides insight into therapeutic strategies.

DOI: https://doi.org/10.1038/s42255-024-01066-z
Redox Biol. 2024 May 25. pii: S2213-2317(24)00187-3. [Epub ahead of print]74 103209

Lactate-induced activation of tumor-associated fibroblasts and IL-8-mediated macrophage recruitment promote lung cancer progression.

Xuyu Gu, Yifei Zhu, Jincheng Su, Sheng Wang, Xiangyu Su, Xu Ding, Lei Jiang, Xiang Fei, Wentian Zhang.

  Alterations in the tumor microenvironment are closely associated with the metabolic phenotype of tumor cells. Cancer-associated fibroblasts (CAFs) play a pivotal role in tumor growth and metastasis. Existing studies have suggested that lactate produced by tumor cells can activate CAFs, yet the precise underlying mechanisms remain largely unexplored. In this study, we initially identified that lactate derived from lung cancer cells can promote nuclear translocation of NUSAP1, subsequently leading to the recruitment of the transcriptional complex JUNB-FRA1-FRA2 near the DESMIN promoter and facilitating DESMIN transcriptional activation, thereby promoting CAFs' activation. Moreover, DESMIN-positive CAFs, in turn, secrete IL-8, which recruits TAMs or promotes M2 polarization of macrophages, further contributing to the alterations in the tumor microenvironment and facilitating lung cancer progression. Furthermore, we observed that the use of IL-8 receptor antagonists, SB225002, or Navarixin, significantly reduced TAM infiltration and enhanced the therapeutic efficacy of anti-PD-1 or anti-PD-L1 treatment. This finding indicates that inhibiting IL-8R activity can attenuate the impact of CAFs on the tumor microenvironment, thus restraining the progression of lung cancer.

Keywords:  Cancer-associated fibroblasts; Lung cancer; Tumor microenvironment; Tumor progression; Tumor-associated macrophages

DOI:  https://doi.org/10.1016/j.redox.2024.103209
Clin Nutr. 2024 May 28. pii: S0261-5614(24)00186-9. [Epub ahead of print]43(7): 1809-1815

Tumor metabolic activity is associated with subcutaneous adipose tissue radiodensity and survival in non-small cell lung cancer.

Yan Sun, Min Deng, Olivier Gevaert, Merel Aberle, Steven W Olde Damink, David van Dijk, Sander S Rensen.

  BACKGROUND: Cachexia-associated body composition alterations and tumor metabolic activity are both associated with survival of cancer patients. Recently, subcutaneous adipose tissue properties have emerged as particularly prognostic body composition features. We hypothesized that tumors with higher metabolic activity instigate cachexia related peripheral metabolic alterations, and investigated whether tumor metabolic activity is associated with body composition and survival in patients with non-small-cell lung cancer (NSCLC), focusing on subcutaneous adipose tissue.METHODS: A retrospective analysis was performed on a cohort of 173 patients with NSCLC. 18F-fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) scans obtained before treatment were used to analyze tumor metabolic activity (standardized uptake value (SUV) and SUV normalized by lean body mass (SUL)) as well as body composition variables (subcutaneous and visceral adipose tissue radiodensity (SAT/VAT radiodensity) and area; skeletal muscle radiodensity (SM radiodensity) and area). Subjects were divided into groups with high or low SAT radiodensity based on Youden Index of Receiver Operator Characteristics (ROC). Associations between tumor metabolic activity, body composition variables, and survival were analyzed by Mann-Whitney tests, Cox regression, and Kaplan-Meier analysis.
RESULTS: The overall prevalence of high SAT radiodensity was 50.9% (88/173). Patients with high SAT radiodensity had shorter survival compared with patients with low SAT radiodensity (mean: 45.3 vs. 50.5 months, p = 0.026). High SAT radiodensity was independently associated with shorter overall survival (multivariate Cox regression HR = 1.061, 95% CI: 1.022-1.101, p = 0.002). SAT radiodensity also correlated with tumor metabolic activity (SULpeak rs = 0.421, p = 0.029; SUVpeak rs = 0.370, p = 0.048). In contrast, the cross-sectional areas of SM, SAT, and VAT were not associated with tumor metabolic activity or survival.
CONCLUSION: Higher SAT radiodensity is associated with higher tumor metabolic activity and shorter survival in patients with NSCLC. This may suggest that tumors with higher metabolic activity induce subcutaneous adipose tissue alterations such as decreased lipid density, increased fibrosis, or browning.

Keywords:  Body composition measurement; Non-small-cell lung cancer; PET–CT; Subcutaneous adipose tissue radiodensity; Survival; Tumor metabolic activity

DOI:  https://doi.org/10.1016/j.clnu.2024.05.040
Cancer Med. 2024 Jun;13(11): e7379

Identification of PSMD11 as a novel cuproptosis- and immune-related prognostic biomarker promoting lung adenocarcinoma progression.

Qiumin Huang, Ran Tian, Jinxi Yu, Wei Du.

  BACKGROUND: Due to the unfavorable prognosis associated with lung adenocarcinoma (LUAD), the development of targeted therapies and immunotherapies is essential. Cuproptosis, an emerging form of regulated cell death, is implicated in mitochondrial metabolism and is induced by copper ions. This study aimed to explore the prognostic value of cuproptosis- and immune-related genes (CIRGs) in LUAD.METHODS: We used The Cancer Genome Atlas database to develop a prognostic prediction model for LUAD patients based on eight CIRGs. Using Cox regression analysis, we determined that the CIRG signature is a reliable, independent prognostic factor. We further identified PSMD11 as a critical CIRG and performed immunohistochemistry to study the protein expression levels of PSMD11 in LUAD tissues. We also investigated the impact of PSMD11 on the biological behavior of lung cancer cell lines.
RESULTS: We found that patients with low PSMD11 expression levels displayed an improved prognosis compared with those with high PSMD11 expression levels. Overexpression of PSMD11 enhanced proliferation, migration, invasion, and tumor growth of lung carcinoma cell line A549, while PSMD11 knockdown diminished proliferation, migration, invasion, and tumor growth of lung carcinoma cell line PC9. Additionally, we discovered that PSMD11 expression was positively correlated with the infiltration of myeloid-derived suppressor cells and the increased expression of immunosuppressive molecules.
CONCLUSION: These findings suggest that PSMD11 may serve as a valuable prognostic biomarker and therapeutic target for LUAD.

Keywords:   PSMD11 ; cuproptosis; immune cells; lung adenocarcinoma; prognosis

DOI:  https://doi.org/10.1002/cam4.7379
Front Nutr. 2024 ;11 1380949

Identification of cachexia in lung cancer patients with an ensemble learning approach.

Pingping Jia, Qianqian Zhao, Xiaoxiao Wu, Fangqi Shen, Kai Sun, Xiaolin Wang.

  Objective: Nutritional intervention prior to the occurrence of cachexia will significantly improve the survival rate of lung cancer patients. This study aimed to establish an ensemble learning model based on anthropometry and blood indicators without information on body weight loss to identify the risk factors of cachexia for early administration of nutritional support and for preventing the occurrence of cachexia in lung cancer patients.Methods: This multicenter study included 4,712 lung cancer patients. The least absolute shrinkage and selection operator (LASSO) method was used to obtain the key indexes. The characteristics excluded weight loss information, and the study data were randomly divided into a training set (70%) and a test set (30%). The training set was used to select the optimal model among 18 models and verify the model performance. A total of 18 machine learning models were evaluated to predict the occurrence of cachexia, and their performance was determined using area under the curve (AUC), accuracy, precision, recall, F1 score, and Matthews correlation coefficient (MCC).
Results: Among 4,712 patients, 1,392 (29.5%) patients were diagnosed with cachexia based on the framework of Fearon et al. A 17-variable gradient boosting classifier (GBC) model including body mass index (BMI), feeding situation, tumor stage, neutrophil-to-lymphocyte ratio (NLR), and some gastrointestinal symptoms was selected among the 18 machine learning models. The GBC model showed good performance in predicting cachexia in the training set (AUC = 0.854, accuracy = 0.819, precision = 0.771, recall = 0.574, F1 score = 0.658, MCC = 0.549, and kappa = 0.538). The abovementioned indicator values were also confirmed in the test set (AUC = 0.859, accuracy = 0.818, precision = 0.801, recall = 0.550, F1 score = 0.652, and MCC = 0.552, and kappa = 0.535). The learning curve, decision boundary, precision recall (PR) curve, the receiver operating curve (ROC), the classification report, and the confusion matrix in the test sets demonstrated good performance. The feature importance diagram showed the contribution of each feature to the model.
Conclusions: The GBC model established in this study could facilitate the identification of cancer cachexia in lung cancer patients without weight loss information, which would guide early implementation of nutritional interventions to decrease the occurrence of cachexia and improve the overall survival (OS).

Keywords:  cachexia; cohort study; ensemble learning; lung cancer; weight loss

DOI:  https://doi.org/10.3389/fnut.2024.1380949
Clin Transl Oncol. 2024 Jun 13.

The clinical features and prognostic implications of the co-mutated TP53 gene in advanced non-small cell lung cancer.

Bing Bai, Xia An, Qinghui Qu, Xin Liu, Yuanyuan Liu, Li Wei.

  BACKGROUND: TP53 is a frequently mutated oncogene within non-small cell lung cancer (NSCLC). However, the clinical and prognostic significance of co-mutations in TP53 in patients with advanced NSCLC has not been fully elucidated.METHODS: A total of 174 patients with advanced NSCLC were enrolled in this study. All patients were subjected to sequencing analysis of tumor-related genes and information such as PD-L1 expression, TMB, and co-mutation changes were collected. Patients were categorized into TP53 mutant and TP53 wild-type groups according to their TP53 mutation status and then statistically analyzed.
RESULTS: TP53 mutations were the most common among all patients, accounting for 56.32%, followed by epidermal growth factor receptor mutations at 48.27%. The most common mutation sites in the TP53 mutation group were exons 5-8.TP53 mutations were significantly associated with PD-L1 and TMB levels. Univariate Cox analysis showed that gender and EGFR mutation affected the prognosis of TP53-mutated NSCLC patients, and multivariate Cox regression analysis identified EGFR mutation as an independent risk factor. The OS of NSCLC patients in the TP53 mutation group was significantly shorter than that of the TP53wt group. Survival curves in the TP53/EGFR combined mutation group showed that patients with combined EGFR mutation had a lower survival rate.
DISCUSSION: TP53 mutations are associated with different clinical indicators and have important implications in clinical treatment. TP53 is a poor prognostic factor for NSCLC patients, and TP53/EGFR co-mutation will affect the survival time of patients. TP53/EGFR co-mutation may be a new prognostic marker for NSCLC.

Keywords:  Co-mutations; Non-small cell lung cancer; Prognostic; TP53; Tumor-related genes

DOI:  https://doi.org/10.1007/s12094-024-03533-1
Sci Rep. 2024 Jun 14. 14(1): 13765

C-reactive protein as robust laboratory value associated with prognosis in patients with stage III non-small cell lung cancer (NSCLC) treated with definitive radiochemotherapy.

Cedric Richlitzki, Marcel Wiesweg, Martin Metzenmacher, Nika Guberina, Christoph Pöttgen, Hubertus Hautzel, Wilfried E E Eberhardt, Kaid Darwiche, Dirk Theegarten, Clemens Aigner, Servet Bölükbas, Martin Schuler, Martin Stuschke, Maja Guberina.

  To evaluate the prognostic value of biomarkers from peripheral blood obtained as routine laboratory assessment for overall survival in a cohort of stage III non-small cell lung cancer (NSCLC) patients treated with definitive radiochemotherapy at a high-volume cancer center. Seven blood biomarkers from 160 patients treated with definitive radiochemotherapy for stage III NSCLC were analyzed throughout the course treatment. Parameters were preselected using univariable and multivariable proportional hazards analysis and were assessed for internal validity using leave-one-out cross validation. Cross validated classifiers including biomarkers in addition to important clinical parameters were compared with classifiers containing the clinical parameters alone. An increased C-reactive protein (CRP) value in the final week of radiotherapy was found as a prognostic factor for overall survival, both as a continuous (HR 1.099 (1.038-1.164), p < 0.0012) as well as categorical variable splitting data at the median value of 1.2 mg/dl (HR 2.214 (1.388-3.531), p < 0.0008). In the multivariable analysis, the CRP value-maintained significance with an HR of 1.105 (1.040-1.173) and p-value of 0.0012. The cross validated classifier using CRP at the end of radiotherapy in addition to clinical parameters separated equally sized high and low risk groups more distinctly than a classifier containing the clinical parameters alone (HR = 2.786 (95% CI 1.686-4.605) vs. HR = 2.287 (95% CI 1.407-3.718)). Thus, the CRP value at the end of radiation therapy has successfully passed the crucial cross-validation test. The presented data on CRP levels suggests that inflammatory markers may become increasingly important during definitive radiochemotherapy, particularly with the growing utilization of immunotherapy as a consolidation therapy for stage III NSCLC.

Keywords:  C-reactive protein (CRP); Definitive radiochemotherapy; ESPATUE trial; Laboratory values; Overall survival; Stage III non-small cell lung cancer (NSCLC)

DOI:  https://doi.org/10.1038/s41598-024-64302-2
J Immunother Cancer. 2024 Jun 10. pii: e009039. [Epub ahead of print]12(6):

High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC).

Myrto K Moutafi, Katherine M Bates, Thazin Nwe Aung, Rolando Garcia Milian, Vasiliki Xirou, Ioannis A Vathiotis, Niki Gavrielatou, Athanasios Angelakis, Kurt A Schalper, Leonidas Salichos, David L Rimm.

  BACKGROUND: Despite the impressive outcomes with immune checkpoint inhibitor (ICI) in non-small cell lung cancer (NSCLC), only a minority of the patients show long-term benefits from ICI. In this study, we used retrospective cohorts of ICI treated patients with NSCLC to discover and validate spatially resolved protein markers associated with resistance to programmed cell death protein-1 (PD-1) axis inhibition.METHODS: Pretreatment samples from 56 patients with NSCLC treated with ICI were collected and analyzed in a tissue microarray (TMA) format in including four different tumor regions per patient using the GeoMx platform for spatially informed transcriptomics. 34 patients had assessable tissue with tumor compartment in all 4 TMA spots, 22 with leukocyte compartment and 12 with CD68 compartment. The patients' tissue that was not assessable in fourfold redundancy in each compartment was designated as the validation cohort; cytokeratin (CK) (N=22), leukocytes CD45 (N=31), macrophages, CD68 (N=43). The human whole transcriptome, represented by~18,000 individual genes assessed by oligonucleotide-tagged in situ hybridization, was sequenced on the NovaSeq platform to quantify the RNAs present in each region of interest.
RESULTS: 54,000 gene variables were generated per case, from them 25,740 were analyzed after removing targets with expression lower than a prespecified frequency. Cox proportional-hazards model analysis was performed for overall and progression-free survival (OS, PFS, respectively). After identifying genes significantly associated with limited survival benefit (HR>1)/progression per spot per patient, we used the intersection of them across the four TMA spots per patient. This resulted in a list of 12 genes in the tumor-cell compartment (RPL13A, GNL3, FAM83A, CYBA, ACSL4, SLC25A6, EPAS1, RPL5, APOL1, HSPD1, RPS4Y1, ADI1). RPL13A, GNL3 in tumor-cell compartment were also significantly associated with OS and PFS, respectively, in the validation cohort (CK: HR, 2.48; p=0.02 and HR, 5.33; p=0.04). In CD45 compartment, secreted frizzled-related protein 2, was associated with OS in the discovery cohort but not in the validation cohort. Similarly, in the CD68 compartment ARHGAP and PNN interacting serine and arginine rich protein were significantly associated with PFS and OS, respectively, in the majority but not all four spots per patient.
CONCLUSION: This work highlights RPL13A and GNL3 as potential indicative biomarkers of resistance to PD-1 axis blockade that might help to improve precision immunotherapy strategies for lung cancer.

Keywords:  biomarker; immune checkpoint inhibitor; lung cancer

DOI:  https://doi.org/10.1136/jitc-2024-009039