bims-meluca 2023-07-16 papers

on Metabolism of non-small cell lung carcinoma

Issue of 2023‒07‒16
twelve papers selected by
the Muñoz-Pinedo/Nadal (PReTT) lab
L’Institut d’Investigació Biomèdica de Bellvitge

Evaluation of Efficacy of ALK Inhibitors According to Body Mass Index in ALK Rearranged NSCLC Patients-A Retrospective Observational Study.
Identification of Plasma Metabolites Associated with Lung Cancer Survival.
Glutamine antagonist DRP-104 suppresses tumor growth and enhances response to checkpoint blockade in KEAP1 mutant lung cancer.
Assessing the role of colonic and other anatomical sites uptake by [18 F]FDG-PET/CT and immune-inflammatory peripheral blood indexes in patients with advanced non-small cell lung cancer treated with first-line immune checkpoint inhibitors.
Machine learning for prediction of immunotherapeutic outcome in non-small-cell lung cancer based on circulating cytokine signatures.
Mevalonate improves anti-PD-1/PD-L1 efficacy by stabilizing CD274 mRNA.
Associations between detectable circulating tumor DNA and tumor glucose uptake measured by 18F-FDG PET/CT in early-stage non-small cell lung cancer.
Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer.
A comparison of the microbiome composition in lower respiratory tract at different sites in early lung cancer patients.
The Effect of GLUT1 and HIF-1α Expressions on Glucose Uptake and Patient Survival in Non-Small-Cell Lung Carcinoma.
Metabolic Dysregulation Explains the Diverse Impacts of Obesity in Males and Females with Gastrointestinal Cancers.
Regulation of PD-L1 expression in non-small cell lung cancer by interleukin-1β.

Cancers (Basel). 2023 Jun 30. pii: 3422. [Epub ahead of print]15(13):

Evaluation of Efficacy of ALK Inhibitors According to Body Mass Index in ALK Rearranged NSCLC Patients-A Retrospective Observational Study.

Marco Siringo, Gabriella Gentile, Salvatore Caponnetto, Isabella Sperduti, Daniele Santini, Enrico Cortesi, Alain Jonathan Gelibter.

  No evidence exists as to whether body mass index (BMI) impairs clinical outcomes from ALK inhibitors (ALKi) in patients with ALK-rearranged non-small cell lung cancer (NSCLC). Retrospective data of patients affected by metastatic ALK-rearranged NSCLC treated with ALKi were collected. We divided patients into "low- BMI" (≤25 kg/m2) and "high- BMI" (>25 kg/m2) categories and correlated them with overall survival (OS) and progression-free survival (PFS). We included 40 patients treated with ALKi. We observed a 3-year OS of 81.5% in high-BMI vs. 49.6% in low-BMI categories (p = 0.049); the 3-year first-line PFS was superior in high-BMI vs. low-BMI patients (47% vs. 19%, p = 0.019). As expected, patients treated with Alectinib had a 55.6% 3-year PFS vs. 7.1% for others treated with ALKi (p = 0.025). High-BMI was associated with a 100% 3-year PFS rate vs. 25.4% in low-BMI Alectinib patients (p = 0.03). BMI was independently correlated with first-line PFS and OS at multivariate analysis with PS (HR 0.39, CI 95% 0.16-0.96, p = 0.042; HR 0.18, CI 95% 0.05-0.61, p = 0.006). High-BMI was associated with higher efficacy in ALK-rearranged patients. These results are particularly exciting for Alectinib and could be correlated to mechanisms that should be investigated in subsequent prospective studies.

Keywords:  ALK; Alectinib; BMI; NSCLC; predictive biomarker

DOI:  https://doi.org/10.3390/cancers15133422
Methods Mol Biol. 2023 ;2695 181-193

Identification of Plasma Metabolites Associated with Lung Cancer Survival.

Peiyu Wang, Yuyao Yuan, Mantang Qiu.

  Limited knowledge has been reported regarding the performance of plasma metabolomics for predicting lung cancer prognosis. In this chapter, we compared the plasma metabolomics of lung cancer patients with differential disease-free survival (DFS, <3 years vs. >4 years) using liquid chromatography-mass spectrometry. We identified 29 survival-related aqueous metabolites but no lipid metabolites. Amino acids and organic acids constitute the majority of these metabolites. The metabolic pathways of these metabolites were cysteine and methionine metabolism and arginine biosynthesis. The Cox proportional hazards regression models confirmed the predictive values of 18 metabolites for DFS, while the phosphocholine and xanthine showed independent predictive values. Regarding cancer phenotypes, thelephoric acid, phosphocholine, inosine, 3-hydroxyanthranilic acid, hypoxanthine, xanthine, and 4-hydroxybenzoic acid showed good correction with lymph node metastasis. Taken together, plasma metabolomics is a powerful tool for identifying prognostic metabolites of lung cancer.

Keywords:  Lung cancer; Metabolites; Plasma metabolomic; Prognosis

DOI:  https://doi.org/10.1007/978-1-0716-3346-5_12
bioRxiv. 2023 Jun 28. pii: 2023.06.27.546750. [Epub ahead of print]

Glutamine antagonist DRP-104 suppresses tumor growth and enhances response to checkpoint blockade in KEAP1 mutant lung cancer.

Ray Pillai, Sarah E LeBoeuf, Yuan Hao, Connie New, Jenna L E Blum, Ali Rashidfarrokhi, Shih Ming Huang, Christian Bahamon, Warren L Wu, Burcu Karadal-Ferrena, Alberto Herrera, Ellie Ivanova, Michael Cross, Jozef P Bossowski, Hongyu Ding, Makiko Hayashi, Sahith Rajalingam, Triantafyllia Karakousi, Volkan I Sayin, Kamal M Khanna, Kwok-Kin Wong, Robert Wild, Aristotelis Tsirigos, John T Poirier, Charles M Rudin, Shawn M Davidson, Sergei B Koralov, Thales Papagiannakopoulos.

Loss-of-function mutations in KEAP1 frequently occur in lung cancer and are associated with resistance to standard of care treatment, highlighting the need for the development of targeted therapies. We have previously shown that KEAP1 mutant tumors have increased glutamine consumption to support the metabolic rewiring associated with NRF2 activation. Here, using patient-derived xenograft models and antigenic orthotopic lung cancer models, we show that the novel glutamine antagonist DRP-104 impairs the growth of KEAP1 mutant tumors. We find that DRP-104 suppresses KEAP1 mutant tumor growth by inhibiting glutamine-dependent nucleotide synthesis and promoting anti-tumor CD4 and CD8 T cell responses. Using multimodal single-cell sequencing and ex vivo functional assays, we discover that DRP-104 reverses T cell exhaustion and enhances the function of CD4 and CD8 T cells culminating in an improved response to anti-PD1 therapy. Our pre-clinical findings provide compelling evidence that DRP-104, currently in phase 1 clinical trials, offers a promising therapeutic approach for treating patients with KEAP1 mutant lung cancer. Furthermore, we demonstrate that by combining DRP-104 with checkpoint inhibition, we can achieve suppression of tumor intrinsic metabolism and augmentation of anti-tumor T cell responses.

DOI: https://doi.org/10.1101/2023.06.27.546750
Thorac Cancer. 2023 Jul 13.

Assessing the role of colonic and other anatomical sites uptake by [18 F]FDG-PET/CT and immune-inflammatory peripheral blood indexes in patients with advanced non-small cell lung cancer treated with first-line immune checkpoint inhibitors.

Alessio Rizzo, Ornella Cantale, Andrea Mogavero, Lucia Garetto, Manuela Racca, Tiziana Venesio, Shobana Anpalakhan, Silvia Novello, Vanesa Gregorc, Giuseppe Luigi Banna.

  BACKGROUND: Inflammation in non-small cell lung cancer (NSCLC) may impair the response to immune checkpoint inhibitors (ICIs) and can be indicated by peripheral blood inflammatory indexes. 2-deoxy-2-[18 F]fluoro-D-glucose positron emission tomography/computed tomography ([18 F] FDG-PET/CT) may be used as a marker of inflammation by measuring glucose metabolism in different colonic sites.METHODS: This retrospective analysis aimed to investigate the correlation between [18 F] FDGPET/CT SUVratio in six gastrointestinal districts, the spleen, the pharynx and the larynx alongside the most avid tumor lesion with peripheral blood inflammatory indexes, including the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammatory index (SII, i.e., NLR times platelets) and lactate dehydrogenase (LDH), in patients with [18 F] FDG-PET/CT staged IV NSCLC who received first-line immune checkpoint inhibitors (ICIs). The role of SUVratios and peripheral blood inflammatory indexes in predicting overall survival (OS) and progression-free survival (PFS) was then explored.
RESULTS: A total of 43 patients were treated with first-line ICI alone (58%) or in combination with chemotherapy (42%). A significant correlation was only found between the rectosigmoid SUVratio and NLR (p = 0.0465). NLR >5.5 and LDH > 333.5 were associated with a worse OS (p = 0.033 and p = 0.009, respectively). The SII was associated with a worse PFS in patients treated with ICI alone (p = 0.033). None of the SUVratios were significantly associated with OS or PFS, although a high left colon SUVratio showed a trend toward a worse PFS.
CONCLUSION: There was no significant correlation between [18 F]FDG PET/CT uptake in different anatomical sites, and in the tumor, and systemic immune-inflammatory indexes. The prognostic role of high left colon SUVratio deserves further investigation.

Keywords:  NLR; gut microbiome; immune checkpoint inhibitor; immunotherapy; lung cancer

DOI:  https://doi.org/10.1111/1759-7714.15032
J Immunother Cancer. 2023 07;pii: e006788. [Epub ahead of print]11(7):

Machine learning for prediction of immunotherapeutic outcome in non-small-cell lung cancer based on circulating cytokine signatures.

Feifei Wei, Koichi Azuma, Yoshiro Nakahara, Haruhiro Saito, Norikazu Matsuo, Tomoyuki Tagami, Taku Kouro, Yuka Igarashi, Takaaki Tokito, Terufumi Kato, Tetsuro Kondo, Shuji Murakami, Ryo Usui, Hidetomo Himuro, Shun Horaguchi, Kayoko Tsuji, Kenta Murotani, Tatsuma Ban, Tomohiko Tamura, Yohei Miyagi, Tetsuro Sasada.

  BACKGROUND: Immune checkpoint inhibitor (ICI) therapy has substantially improved the overall survival (OS) in patients with non-small-cell lung cancer (NSCLC); however, its response rate is still modest. In this study, we developed a machine learning-based platform, namely the Cytokine-based ICI Response Index (CIRI), to predict the ICI response of patients with NSCLC based on the peripheral blood cytokine profiles.METHODS: We enrolled 123 and 99 patients with NSCLC who received anti-PD-1/PD-L1 monotherapy or combined chemotherapy in the training and validation cohorts, respectively. The plasma concentrations of 93 cytokines were examined in the peripheral blood obtained from patients at baseline (pre) and 6 weeks after treatment (early during treatment: edt). Ensemble learning random survival forest classifiers were developed to select feature cytokines and predict the OS of patients undergoing ICI therapy.
RESULTS: Fourteen and 19 cytokines at baseline and on treatment, respectively, were selected to generate CIRI models (namely preCIRI14 and edtCIRI19), both of which successfully identified patients with worse OS in two completely independent cohorts. At the population level, the prediction accuracies of preCIRI14 and edtCIRI19, as indicated by the concordance indices (C-indices), were 0.700 and 0.751 in the validation cohort, respectively. At the individual level, patients with higher CIRI scores demonstrated worse OS [hazard ratio (HR): 0.274 and 0.163, and p<0.0001 and p=0.0044 in preCIRI14 and edtCIRI19, respectively]. By including other circulating and clinical features, improved prediction efficacy was observed in advanced models (preCIRI21 and edtCIRI27). The C-indices in the validation cohort were 0.764 and 0.757, respectively, whereas the HRs of preCIRI21 and edtCIRI27 were 0.141 (p<0.0001) and 0.158 (p=0.038), respectively.
CONCLUSIONS: The CIRI model is highly accurate and reproducible in determining the patients with NSCLC who would benefit from anti-PD-1/PD-L1 therapy with prolonged OS and may aid in clinical decision-making before and/or at the early stage of treatment.

Keywords:  Biomarkers, Tumor; Biostatistics; Cytokines; Immune Checkpoint Inhibitors; Non-Small Cell Lung Cancer

DOI:  https://doi.org/10.1136/jitc-2023-006788
Acta Pharm Sin B. 2023 Jun;13(6): 2585-2600

Mevalonate improves anti-PD-1/PD-L1 efficacy by stabilizing CD274 mRNA.

Wenxin Zhang, Xiaohui Pan, Yanjun Xu, Hongjie Guo, Mingming Zheng, Xi Chen, Honghai Wu, Fengming Luan, Qiaojun He, Ling Ding, Bo Yang.

  Mevalonate metabolism plays an important role in regulating tumor growth and progression; however, its role in immune evasion and immune checkpoint modulation remains unclear. Here, we found that non-small cell lung cancer (NSCLC) patients with higher plasma mevalonate response better to anti-PD-(L)1 therapy, as indicated by prolonged progression-free survival and overall survival. Plasma mevalonate levels were positively correlated with programmed death ligand-1 (PD-L1) expression in tumor tissues. In NSCLC cell lines and patient-derived cells, supplementation of mevalonate significantly up-regulated the expression of PD-L1, whereas deprivation of mevalonate reduced PD-L1 expression. Mevalonate increased CD274 mRNA level but did not affect CD274 transcription. Further, we confirmed that mevalonate improved CD274 mRNA stability. Mevalonate promoted the affinity of the AU-rich element-binding protein HuR to the 3'-UTR regions of CD274 mRNA and thereby stabilized CD274 mRNA. By in vivo study, we further confirmed that mevalonate addition enhanced the anti-tumor effect of anti-PD-L1, increased the infiltration of CD8+ T cells, and improved cytotoxic function of T cells. Collectively, our findings discovered plasma mevalonate levels positively correlated with the therapeutic efficacy of anti-PD-(L)1 antibody, and provided the evidence that mevalonate supplementation could be an immunosensitizer in NSCLC.

Keywords:  HuR; Immune checkpoint blockade; Metabolites; Mevalonate; NSCLC; PD-L1; mRNA stability

DOI:  https://doi.org/10.1016/j.apsb.2023.04.002
BMC Cancer. 2023 Jul 11. 23(1): 646

Associations between detectable circulating tumor DNA and tumor glucose uptake measured by 18F-FDG PET/CT in early-stage non-small cell lung cancer.

Anine Larsen Ottestad, Håkon Johansen, Tarje Onsøien Halvorsen, Hong Yan Dai, Sissel Gyrid Freim Wahl, Elisabeth Fritzke Emdal, Bjørn Henning Grønberg.

  BACKGROUND: The low level of circulating tumor DNA (ctDNA) in the blood is a well-known challenge for the application of liquid biopsies in early-stage non-small cell lung cancer (NSCLC) management. Studies of metastatic NSCLC indicate that ctDNA levels are associated with tumor metabolic activity as measured by 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET/CT). This study investigated this association in NSCLC patients considered for potentially curative treatment and explored whether the two methods provide independent prognostic information.METHOD: Patients with stage I-III NSCLC who had routinely undergone an 18F-FDG PET/CT scan and exploratory ctDNA analyses were included. Tumor glucose uptake was measured by maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) from the 18F-FDG PET/CT scans. ctDNA detectability and quantity, using variant allele frequency, were estimated by tumor-informed ctDNA analyses.
RESULTS: In total, 63 patients (median age 70 years, 60% women, and 90% adenocarcinoma) were included. The tumor glucose uptake (SUVmax, MTV, and TLG) was significantly higher in patients with detectable ctDNA (n = 19, p < 0.001). The ctDNA quantity correlated with MTV (Spearman's ρ = 0.53, p = 0.021) and TLG (Spearman's ρ = 0.56, p = 0.013) but not with SUVmax (Spearman's ρ = 0.034, p = 0.15). ctDNA detection was associated with shorter OS independent of MTV (HR: 2.70, 95% CI: 1.07-6.82, p = 0.035) and TLG (HR: 2.63, 95% CI: 1.06-6.51, p = 0.036). Patients with high tumor glucose uptake and detectable ctDNA had shorter overall survival and progression-free survival than those without detectable ctDNA, though these associations were not statistically significant (p > 0.05).
CONCLUSION: There was a positive correlation between plasma ctDNA quantity and MTV and TLG in early-stage NSCLC patients. Despite the correlation, the results indicated that ctDNA detection was a negative prognostic factor independent of MTV and TLG.

Keywords:  18F-FDG PET/CT; Circulating tumor DNA; Glucose metabolism; Liquid biopsy; Non-small cell lung cancer

DOI:  https://doi.org/10.1186/s12885-023-11147-z
Sci Rep. 2023 Jul 08. 13(1): 11072

Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer.

Ksenia M Shestakova, Natalia E Moskaleva, Andrey A Boldin, Pavel M Rezvanov, Alexandr V Shestopalov, Sergey A Rumyantsev, Elena Yu Zlatnik, Inna A Novikova, Alexander B Sagakyants, Sofya V Timofeeva, Yuriy Simonov, Sabina N Baskhanova, Elena Tobolkina, Serge Rudaz, Svetlana A Appolonova.

Lung cancer is referred to as the second most common cancer worldwide and is mainly associated with complex diagnostics and the absence of personalized therapy. Metabolomics may provide significant insights into the improvement of lung cancer diagnostics through identification of the specific biomarkers or biomarker panels that characterize the pathological state of the patient. We performed targeted metabolomic profiling of plasma samples from individuals with non-small cell lung cancer (NSLC, n = 100) and individuals without any cancer or chronic pathologies (n = 100) to identify the relationship between plasma endogenous metabolites and NSLC by means of modern comprehensive bioinformatics tools, including univariate analysis, multivariate analysis, partial correlation network analysis and machine learning. Through the comparison of metabolomic profiles of patients with NSCLC and noncancer individuals, we identified significant alterations in the concentration levels of metabolites mainly related to tryptophan metabolism, the TCA cycle, the urea cycle and lipid metabolism. Additionally, partial correlation network analysis revealed new ratios of the metabolites that significantly distinguished the considered groups of participants. Using the identified significantly altered metabolites and their ratios, we developed a machine learning classification model with an ROC AUC value equal to 0.96. The developed machine learning lung cancer model may serve as a prototype of the approach for the in-time diagnostics of lung cancer that in the future may be introduced in routine clinical use. Overall, we have demonstrated that the combination of metabolomics and up-to-date bioinformatics can be used as a potential tool for proper diagnostics of patients with NSCLC.

DOI: https://doi.org/10.1038/s41598-023-38140-7
Transl Lung Cancer Res. 2023 Jun 30. 12(6): 1264-1275

A comparison of the microbiome composition in lower respiratory tract at different sites in early lung cancer patients.

Kai Su, Yibo Gao, Jie He.

  Background: Lung microbiome dysbiosis has been associated with lung carcinogenesis. However, the differences in the microbiome composition at different lung sites of lung cancer patients remain little understood. Studying the whole lung microbiome in cancer patients could provide new insights for interpreting the complex interplay between the microbiome and lung cancer and finding new targets for more effective therapies and preventive measures.Methods: A total of 16 patients with non-small cell lung cancer (NSCLC) were recruited for this study. Samples were obtained from four sites, including lung tumor tissues (TT), para-tumor tissues (PT), distal normal lung tissues (DN), and bronchial tissues (BT). The DNA was isolated from the tissues, and the V3-V4 regions were amplified. Sequencing libraries were generated and sequenced on an Illumina NovaSeq6000 platform.
Results: The richness and evenness of the microbiome were generally consistent among the TT, PT, DN, and BT groups in lung cancer patients. Principal coordinate analysis (PCoA) and nonmetric multidimensional scaling (NMDS) based on Bray-Curtis, weighted and unweighted UniFrac distance showed no distinct separation trend among the four groups. Proteobacteria, Firmicutes, Bacteroidota, and Desulfobacterota were the most common phyla in all four groups, while TT showed the highest abundance of Proteobacteria and the lowest abundance of Firmicutes. At the genus level, Rubellimicrobium and Fictibacillus were higher in the TT group. In the predicted functional analysis by PICRUSt, there were no specifically discrepant pathways among the four groups. In addition, an inverse relationship between body mass index (BMI) and alpha diversity was observed in this study.
Conclusions: A non-significant result was obtained from the microbiome diversity comparison between different tissues. However, we demonstrated that lung tumors were enriched with specific bacterial species, which might contribute to tumorigenesis. Moreover, we found an inverse relationship between BMI and alpha diversity in these tissues, providing a new clue for deciphering the mechanisms of lung carcinogenesis.

Keywords:  16S rRNA sequencing; Lung microbiome; microbiota dysbiosis; non-small cell lung cancer (NSCLC)

DOI:  https://doi.org/10.21037/tlcr-23-231
Int J Mol Sci. 2023 Jun 24. pii: 10575. [Epub ahead of print]24(13):

The Effect of GLUT1 and HIF-1α Expressions on Glucose Uptake and Patient Survival in Non-Small-Cell Lung Carcinoma.

Josipa Kokeza, Ante Strikic, Marin Ogorevc, Nela Kelam, Martina Vukoja, Ivo Dilber, Sandra Zekic Tomas.

  Lung cancer is the second-most-common cancer while being the leading cause of cancer deaths worldwide. It has been found that glucose transporter 1 (GLUT1) and hypoxia-inducible factor 1α (HIF-1α) are overexpressed in various malignancies and that they correlate with the maximum standard uptake values (SUVmax) on 18F-fluorodeoxyglucose-positron emission tomography/computed tomography (18F-FDG PET/CT) and poor prognosis. In this study, we aim to evaluate the relationship between the SUVmax, GLUT1, and HIF-1α expression with primary tumor size, histological type, lymph node metastases, and patient survival. Of the 48 patients with non-small-cell lung cancer, those with squamous cell carcinomas (SCCs) had significantly higher GLUT1 and HIF-1α immunohistochemical expressions in comparison to adenocarcinomas (ACs), while there was no statistically significant difference in FDG accumulation between them. No significant correlation was noted between either GLUT1 or HIF-1α protein expression and FDG uptake and overall survival. However, an analysis of tumor transcriptomics showed a significant difference in overall survival depending on mRNA expression; patients with SCC and high HIF-1α levels survived longer compared to those with low HIF-1α levels, while patients with AC and low GLUT1 levels had a higher average survival time than those with high GLUT1 levels. Further studies are needed to determine the prognostic value of the expression of these factors depending on the histologic type.

Keywords:  GLUT1; HIF-1α; PET CT; lung adenocarcinoma; lung squamous cell carcinoma

DOI:  https://doi.org/10.3390/ijms241310575
Int J Mol Sci. 2023 Jun 29. pii: 10847. [Epub ahead of print]24(13):

Metabolic Dysregulation Explains the Diverse Impacts of Obesity in Males and Females with Gastrointestinal Cancers.

Spencer R Rosario, Bowen Dong, Yali Zhang, Hua-Hsin Hsiao, Emily Isenhart, Jianmin Wang, Erin M Siegel, Arta M Monjazeb, Dwight H Owen, Prasenjit Dey, Fred K Tabung, Daniel J Spakowicz, William J Murphy, Stephen Edge, Sai Yendamuri, Sami Ibrahimi, Jill M Kolesar, Patsy H McDonald, Deepak Vadehra, Michelle Churchman, Song Liu, Pawel Kalinski, Sarbajit Mukherjee.

  The prevalence of obesity, defined as the body mass index (BMI) ≥ 30 kg/m2, has reached epidemic levels. Obesity is associated with an increased risk of various cancers, including gastrointestinal ones. Recent evidence has suggested that obesity disproportionately impacts males and females with cancer, resulting in varied transcriptional and metabolic dysregulation. This study aimed to elucidate the differences in the metabolic milieu of adenocarcinomas of the gastrointestinal (GI) tract both related and unrelated to sex in obesity. To demonstrate these obesity and sex-related effects, we utilized three primary data sources: serum metabolomics from obese and non-obese patients assessed via the Biocrates MxP Quant 500 mass spectrometry-based kit, the ORIEN tumor RNA-sequencing data for all adenocarcinoma cases to assess the impacts of obesity, and publicly available TCGA transcriptional analysis to assess GI cancers and sex-related differences in GI cancers specifically. We applied and integrated our unique transcriptional metabolic pipeline in combination with our metabolomics data to reveal how obesity and sex can dictate differential metabolism in patients. Differentially expressed genes (DEG) analysis of ORIEN obese adenocarcinoma as compared to normal-weight adenocarcinoma patients resulted in large-scale transcriptional reprogramming (4029 DEGs, adj. p < 0.05 and |logFC| > 0.58). Gene Set Enrichment and metabolic pipeline analysis showed genes enriched for pathways relating to immunity (inflammation, and CD40 signaling, among others) and metabolism. Specifically, we found alterations to steroid metabolism and tryptophan/kynurenine metabolism in obese patients, both of which are highly associated with disease severity and immune cell dysfunction. These findings were further confirmed using the TCGA colorectal adenocarcinoma (CRC) and esophageal adenocarcinoma (ESCA) data, which showed similar patterns of increased tryptophan catabolism for kynurenine production in obese patients. These patients further showed disparate alterations between males and females when comparing obese to non-obese patient populations. Alterations to immune and metabolic pathways were validated in six patients (two obese and four normal weight) via CD8+/CD4+ peripheral blood mononuclear cell RNA-sequencing and paired serum metabolomics, which showed differential kynurenine and lipid metabolism, which corresponded with altered T-cell transcriptome in obese populations. Overall, obesity is associated with differential transcriptional and metabolic programs in various disease sites. Further, these alterations, such as kynurenine and tryptophan metabolism, which impact both metabolism and immune phenotype, vary with sex and obesity together. This study warrants further in-depth investigation into obesity and sex-related alterations in cancers that may better define biomarkers of response to immunotherapy.

Keywords:  cancer; gender disparity; immunity; metabolism; obesity; omics

DOI:  https://doi.org/10.3390/ijms241310847
Front Immunol. 2023 ;14 1192861

Regulation of PD-L1 expression in non-small cell lung cancer by interleukin-1β.

Aiko Hirayama, Kentaro Tanaka, Hirono Tsutsumi, Takayuki Nakanishi, Sho Yamashita, Shun Mizusaki, Yumiko Ishii, Keiichi Ota, Yasuto Yoneshima, Eiji Iwama, Isamu Okamoto.

  Introduction: Programmed cell death-ligand 1 (PD-L1) is a biomarker for prediction of the clinical efficacy of immune checkpoint inhibitors in various cancer types. The role of cytokines in regulation of PD-L1 expression in tumor cells has not been fully characterized, however. Here we show that interleukin-1β (IL-1β) plays a key role in regulation of PD-L1 expression in non-small cell lung cancer (NSCLC).Methods: We performed comprehensive screening of cytokine gene expression in NSCLC tissue using available single-cell RNA-Sequence data. Then we examined the role of IL-1β in vitro to elucidate its induction of PD-L1 on NSCLC cells.
Results: The IL-1β gene is highly expressed in the tumor microenvironment, particularly in macrophages. The combination of IL-1β and interferon-γ (IFN-γ) induced a synergistic increase in PD-L1 expression in NSCLC cell lines. IL-1β and IFN-γ also cooperatively activated mitogen-activated protein kinase (MAPK) signaling and promoted the binding of downstream transcription factors to the PD-L1 gene promoter. Furthermore, inhibitors of MAPK signaling blocked upregulation of PD-L1 by IL-1β and IFN-γ.
Discussion: Our study reports high levels of IL-1β in the tumor microenvironment may cooperate with IFN-γ to induce maximal PD-L1 expression in tumor cells via activation of MAPK signaling, with the IL-1β-MAPK axis being a promising therapeutic target for attenuation of PD-L1-mediated suppression of antitumor immunity.

Keywords:  interferon-gamma (IFN-γ) ; interleukin-1β (IL-1β); mitogen-activated protein kinase (MAPK) pathway; non-small cell lung cancer; programmed cell death-ligand 1 (PD-L1); tumor immunology

DOI:  https://doi.org/10.3389/fimmu.2023.1192861