bims-meluca Biomed News
on Metabolism of non-small cell lung carcinoma
Issue of 2023–07–30
eight papers selected by
the Muñoz-Pinedo/Nadal (PReTT) lab, L’Institut d’Investigació Biomèdica de Bellvitge



  1. Cancers (Basel). 2023 Jul 12. pii: 3592. [Epub ahead of print]15(14):
       BACKGROUND: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of tumors. Natural killer (NK) cells can play an important role in cancer immune surveillance. The aim of this prospective observational study was to analyze peripheral blood mononuclear cells (PBMCs) in patients with advanced non-small-cell lung cancer (NSCLC) receiving ICIs in order to identify predictive factors for better survival outcomes.
    METHODS: Forty-seven stage IV NSCLC patients were enrolled. Patients underwent baseline (T0) and longitudinal (T1) evaluations after ICIs. Peripheral immune blood cell counts were analyzed using flow cytometry.
    RESULTS: Basal levels of CD3-CD56+ NK cells were higher in patients with controlled disease (DC) compared to progression disease (PD) patients (127 cells/µL vs. 27.8 cells/µL, p < 0.001). Lower NK cell values were independent prognostic factors for shorter overall survival (OS) (HR 0.992; 95% CI 0.987-0.997, p < 0.001) and progression-free survival (PFS) (HR 0.988; 95% CI 0.981-0.994, p < 0.001). During the longitudinal evaluation, CD3-CD56+ NK cells (138.1 cells/µL vs. 127 cells/µL, p = 0.025) and CD56bright NK cells (27.4 cells/µL vs. 18.1 cells/µL, p = 0.034) significantly increased in the DC group. Finally, lower values of CD3-CD56+ NK cells (28.3 cells/µL vs. 114.6 cells/µL, p = 0.004) and CD56dim NK cells (13.2 cells/µL vs. 89.4 cells/µL, p < 0.001) were found in sarcopenic patients compared to patients without sarcopenia.
    CONCLUSIONS: Peripheral NK cells could represent a non-invasive and useful tool to predict ICI therapy response in NSCLC patients, and the association of low NK cell levels with sarcopenia deserves even more attention in clinical evaluation.
    Keywords:  immune checkpoint inhibitors (ICIs); lung cancer; natural killer (NK) cells; non-small-cell lung cancer (NSCLC); peripheral blood mononuclear cells (PBMCs); sarcopenia
    DOI:  https://doi.org/10.3390/cancers15143592
  2. bioRxiv. 2023 Jul 17. pii: 2023.07.15.549147. [Epub ahead of print]
      Tumor mutations can influence the surrounding microenvironment leading to suppression of anti-tumor immune responses and thereby contributing to tumor progression and failure of cancer therapies. Here we use genetically engineered lung cancer mouse models and patient samples to dissect how LKB1 mutations accelerate tumor growth by reshaping the immune microenvironment. Comprehensive immune profiling of LKB1 -mutant vs wildtype tumors revealed dramatic changes in myeloid cells, specifically enrichment of Arg1 + interstitial macrophages and SiglecF Hi neutrophils. We discovered a novel mechanism whereby autocrine LIF signaling in Lkb1 -mutant tumors drives tumorigenesis by reprogramming myeloid cells in the immune microenvironment. Inhibiting LIF signaling in Lkb1 -mutant tumors, via gene targeting or with a neutralizing antibody, resulted in a striking reduction in Arg1 + interstitial macrophages and SiglecF Hi neutrophils, expansion of antigen specific T cells, and inhibition of tumor progression. Thus, targeting LIF signaling provides a new therapeutic approach to reverse the immunosuppressive microenvironment of LKB1 -mutant tumors.
    DOI:  https://doi.org/10.1101/2023.07.15.549147
  3. Nucl Med Commun. 2023 Jul 31.
       OBJECTIVE: This study aimed to investigate the relationship between 18 F-fluorodeoxyglucose PET/computed tomography ( 18 F-FDG PET/CT) metabolic parameters and clinical benefit and prognosis in nonsmall cell lung cancer (NSCLC).
    METHODS: In total, 34 advanced NSCLC patients who received 18 F-FDG PET/CT before immunotherapy were retrospectively included in this study. All patients were divided into two groups, the clinical benefit (CB) group and the no-clinical benefit (no-CB) group, based on the efficacy of evaluation after 6 months of treatment. Also clinical information, characteristics of metastases, survival, PD-L1 expression level and glucose metabolic parameters were evaluated.
    RESULTS: Finally, 24 patients were in the CB group, and 10 patients were in the no-CB group. There was a significant difference between the CB group and the no-CB group in TNM stages ( P  = 0.005), visceral and bone metastasis ( P  = 0.031), metabolic tumor volume of primary lesion (MTV-P; P  = 0.003), the metabolic tumor volume of whole-body (MTVwb; P  = 0.005) and total lesion glycolysis of whole-body (TLGwb, P  = 0.015). However, for patient outcomes, the independent prognostic factors associated with progression free survival were TNM stage (HR = 0.113; 95% CI, 0.029-0.439; P  = 0.002), TLG-P (HR = 0.085; 95% CI, 0.018-0.402; P  = 0.002) and TLG-LN (HR = 0.068; 95% CI, 0.015-0.308; P  = 0.000), and the TLG-LN (HR = 0.242; 95% CI, 0.066-0.879; P  = 0.002) was the independent prognostic factor associated with overall survival.
    CONCLUSIONS: Metastatic lesion burden evaluated by 18 F-FDG PET/ CT can predict response to immunotherapy in advanced NSCLC patients, in which lymph node metastasis lesion metabolic burden is a meaningful predictor, but a large multicenter trial is still needed to validate this conclusion.
    DOI:  https://doi.org/10.1097/MNM.0000000000001737
  4. Int J Mol Sci. 2023 Jul 17. pii: 11547. [Epub ahead of print]24(14):
      In the past decade, targeted therapies for solid tumors, including non-small cell lung cancer (NSCLC), have advanced significantly, offering tailored treatment options for patients. However, individuals without targetable mutations pose a clinical challenge, as they may not respond to standard treatments like immune-checkpoint inhibitors (ICIs) and novel targeted therapies. While the mechanism of action of ICIs seems promising, the lack of a robust response limits their widespread use. Although the expression levels of programmed death ligand 1 (PD-L1) on tumor cells are used to predict ICI response, identifying new biomarkers, particularly those associated with the tumor microenvironment (TME), is crucial to address this unmet need. Recently, inflammatory cytokines such as interleukin-1 beta (IL-1β) have emerged as a key area of focus and hold significant potential implications for future clinical practice. Combinatorial approaches of IL-1β inhibitors and ICIs may provide a potential therapeutic modality for NSCLC patients without targetable mutations. Recent advancements in our understanding of the intricate relationship between inflammation and oncogenesis, particularly involving the IL-1β/PD-1/PD-L1 pathway, have shed light on their application in lung cancer development and clinical outcomes of patients. Targeting these pathways in cancers like NSCLC holds immense potential to revolutionize cancer treatment, particularly for patients lacking targetable genetic mutations. However, despite these promising prospects, there remain certain aspects of this pathway that require further investigation, particularly regarding treatment resistance. Therefore, the objective of this review is to delve into the role of IL-1β in NSCLC, its participation in inflammatory pathways, and its intricate crosstalk with the PD-1/PD-L1 pathway. Additionally, we aim to explore the potential of IL-1β as a therapeutic target for NSCLC treatment.
    Keywords:  immune-checkpoint inhibitors (ICIs); interleukin-1 beta (IL-1β); non-small cell lung cancer (NSCLC); programmed death ligand 1 (PD-L1); therapeutic resistance
    DOI:  https://doi.org/10.3390/ijms241411547
  5. Diagnostics (Basel). 2023 Jul 22. pii: 2448. [Epub ahead of print]13(14):
      We investigated the role of Coefficient of Variation (CoV), a first-order texture parameter derived from 18F-FDG PET/CT, in the prognosis of Non-Small Cell Lung Cancer (NSCLC) patients. Eighty-four patients with advanced NSCLC who underwent 18F-FDG PET/CT before therapy were retrospectively studied. SUVmax, SUVmean, CoV, total Metabolic Tumor Volume (MTVTOT) and whole-body Total Lesion Glycolysis (TLGWB) were determined by an automated contouring program (SUV threshold at 2.5). We analyzed 194 lesions: primary tumors (n = 84), regional (n = 48) and non-regional (n = 17) lymph nodes and metastases in liver (n = 9), bone (n = 23) and other sites (n = 13); average CoVs were 0.36 ± 0.13, 0.36 ± 0.14, 0.42 ± 0.18, 0.30 ± 0.14, 0.37 ± 0.17, 0.34 ± 0.13, respectively. No significant differences were found between the CoV values among the different lesion categories. Survival analysis included age, gender, histology, stage, MTVTOT, TLGWB and imaging parameters derived from primary tumors. At univariate analysis, CoV (p = 0.0184), MTVTOT (p = 0.0050), TLGWB (p = 0.0108) and stage (p = 0.0041) predicted Overall Survival (OS). At multivariate analysis, age, CoV, MTVTOT and stage were retained in the model (p = 0.0001). Patients with CoV > 0.38 had significantly better OS than those with CoV ≤ 0.38 (p = 0.0143). Patients with MTVTOT ≤ 89.5 mL had higher OS than those with MTVTOT > 89.5 mL (p = 0.0063). Combining CoV and MTVTOT, patients with CoV ≤ 0.38 and MTVTOT > 89.5 mL had the worst prognosis. CoV, by reflecting the heterogeneity of glycolytic phenotype, can predict clinical outcomes in NSCLC patients.
    Keywords:  18F-FDG PET/CT; Coefficient of Variation; Metabolic Tumor Volume; Non-Small Cell Lung Cancer; heterogeneity; prognosis
    DOI:  https://doi.org/10.3390/diagnostics13142448
  6. Front Immunol. 2023 ;14 1217590
       Background: Lung adenocarcinoma (LUAD) is a major subtype of non-small cell lung cancer (NSCLC) with a highly heterogeneous tumor microenvironment. Immune checkpoint inhibitors (ICIs) are more effective in tumors with a pre-activated immune status. However, the potential of the immune activation-associated gene (IAG) signature for prognosis prediction and immunotherapy response assessment in LUAD has not been established. Therefore, it is critical to explore such gene signatures.
    Methods: RNA sequencing profiles and corresponding clinical parameters of LUAD were extracted from the TCGA and GEO databases. Unsupervised consistency clustering analysis based on immune activation-related genes was performed on the enrolled samples. Subsequently, prognostic models based on genes associated with prognosis were built using the last absolute shrinkage and selection operator (LASSO) method and univariate Cox regression. The expression levels of four immune activation related gene index (IARGI) related genes were validated in 12 pairs of LUAD tumor and normal tissue samples using qPCR. Using the ESTIMATE, TIMER, and ssGSEA algorithms, immune cell infiltration analysis was carried out for different groups, and the tumor immune dysfunction and rejection (TIDE) score was used to evaluate the effectiveness of immunotherapy.
    Results: Based on the expression patterns of IAGs, the TCGA LUAD cohort was classified into two clusters, with those in the IAG-high pattern demonstrating significantly better survival outcomes and immune cell infiltration compared to those in the IAG-low pattern. Then, we developed an IARGI model that effectively stratified patients into different risk groups, revealing differences in prognosis, mutation profiles, and immune cell infiltration within the tumor microenvironment between the high and low-risk groups. Notably, significant disparities in TIDE score between the two groups suggest that the low-risk group may exhibit better responses to ICIs therapy. The IARGI risk model was validated across multiple datasets and demonstrated exceptional performance in predicting overall survival in LUAD, and an IARGI-integrated nomogram was established as a quantitative tool for clinical practice.
    Conclusion: The IARGI can serve as valuable biomarkers for evaluating the tumor microenvironment and predicting the prognosis of LUAD patients. Furthermore, these genes probably provide valuable guidance for establishing effective immunotherapy regimens for LUAD patients.
    Keywords:  immune activation; immune infiltration; immunotherapy efficacy; lung adenocarcinoma; prognosis
    DOI:  https://doi.org/10.3389/fimmu.2023.1217590
  7. Front Nutr. 2023 ;10 1172610
       Background: Reduced muscle mass (RMM) is a phenotypic criterion for malnutrition; the appendicular skeletal muscle mass index (ASMI) and fat-free mass index (FFMI) are both applicable indicators in the global leadership initiative on malnutrition (GLIM) guideline. However, their sensitivity and prognostic effect remain unclear.
    Methods: Clinical data of 2,477 patients with malignant tumors were collected. Multi-frequency bioelectrical impedance analysis was used to obtain ASMI and FFMI. RMM was confirmed by ASMI (< 7.0 kg/m2 for men and < 5.7 kg/m2 for women) or FFMI (< 17 kg/m2 for men and < 15 kg/m2 for women). Propensity score match analysis and logistic regression analysis were used to evaluate the efficacy of FFMI and ASMI in diagnosing severe malnutrition and multivariate Cox regression analysis to determine the efficacy of RMM in predicting survival.
    Results: In total, 546 (22.0%) and 659 (26.6%) participants were diagnosed with RMM by ASMI (RMM.ASMI group) and FFMI (RMM.FFMI group); 375 cases overlapped. Body mass index (BMI), midarm circumference, triceps skinfold thickness, and maximum calf circumference were all significantly larger in the RMM.FFMI group for both sexes (P < 0.05). A 1:1 matched dataset constructed by propensity score match contained 810 cases. RMM.FFMI was an influential factor of severe malnutrition with HR = 3.033 (95% CI 2.068-4.449, P < 0.001), and RMM.ASMI was a predictive factor of overall survival (HR = 1.318, 95% CI 1.060-1.639, P = 0.013 in the RMM.ASMI subgroup, HR = 1.315, 95% CI 1.077-1.607, P = 0.007 in the RMM.FFMI subgroup).
    Conclusion: In general, RMM indicates negative clinical outcomes; when defined by FFMI, it predicts nutritional status, and when defined by ASMI, it is related to poor survival in cancer patients.
    Keywords:  cancer; malnutrition; nutrition; prognosis; skeletal muscle
    DOI:  https://doi.org/10.3389/fnut.2023.1172610
  8. J Immunother Cancer. 2023 07;pii: e006994. [Epub ahead of print]11(7):
       BACKGROUND: Single-agent PD-(L)1 blockade (IO) alone or in combination with chemotherapy (Chemotherapy-IO) is approved first-line therapies in patients with advanced lung adenocarcinomas (LUADs) with PD-L1 expression ≥1%. These regimens have not been compared prospectively. The primary objective was to compare first-line efficacies of single-agent IO to Chemotherapy-IO in patients with advanced LUADs. Secondary objectives were to explore if clinical, pathological, and genomic features were associated with differential response to Chemotherapy-IO versus IO.
    METHODS: This was a multicenter retrospective cohort study. Inclusion criteria were patients with advanced LUADs with tumor PD-L1 ≥1% treated with first-line Chemotherapy-IO or IO. To compare the first-line efficacies of single-agent IO to Chemotherapy-IO, we conducted inverse probability weighted Cox proportional hazards models using estimated propensity scores.
    RESULTS: The cohort analyzed included 866 patients. Relative to IO, Chemotherapy-IO was associated with improved objective response rate (ORR) (44% vs 35%, p=0.007) and progression-free survival (PFS) in patients with tumor PD-L1≥1% (HR 0.84, 95% CI 0.72 to 0.97, p=0.021) or PD-L1≥50% (ORR 55% vs 38%, p<0.001; PFS HR 0.68, 95% CI 0.53 to 0.87, p=0.002). Using propensity-adjusted analyses, only never-smokers in the PD-L1≥50% subgroup derived a differential survival benefit from Chemotherapy-IO vs IO (p=0.013). Among patients with very high tumor PD-L1 expression (≥90%), there were no differences in outcome between treatment groups. No genomic factors conferred differential survival benefit to Chemotherapy-IO versus IO.
    CONCLUSIONS: While the addition of chemotherapy to PD-(L)1 blockade increases the probability of initial response, never-smokers with tumor PD-L1≥50% comprise the only population identified that derived an apparent survival benefit with treatment intensification.
    Keywords:  Combined Modality Therapy; Genetic Markers; Immune Checkpoint Inhibitors; Non-Small Cell Lung Cancer
    DOI:  https://doi.org/10.1136/jitc-2023-006994