bims-meluca 2024-03-10 papers

on Metabolism of non-small cell lung carcinoma

Issue of 2024–03–10
seven papers selected by
the Muñoz-Pinedo/Nadal (PReTT) lab, L’Institut d’Investigació Biomèdica de Bellvitge

Identification of the novel biomarkers involved in the mitochondrial metabolism-related reactive oxygen species and their role in lung cancer T-cell exhaustion and immunotherapy.
Metabolomics analysis reveals novel serum metabolite alterations in cancer cachexia.
PD-L1 on large extracellular vesicles is a predictive biomarker for therapy response in tissue PD-L1-low and -negative patients with non-small cell lung cancer.
Prognostic Significance of the Cachexia Index in Patients with Non-Small-Cell Lung Cancer and Brain Metastases after Stereotactic Radiotherapy.
Prognostic significance of body mass index and serum albumin as the indicators of nutritional status in small cell lung cancer.
Influence of abdominal fat distribution and inflammatory status on post-operative prognosis in non-small cell lung cancer patients: a retrospective cohort study.
Transcriptome profiling and metabolic pathway analysis towards reliable biomarker discovery in early-stage lung cancer.

Heliyon. 2024 Mar 15. 10(5): e27022

Identification of the novel biomarkers involved in the mitochondrial metabolism-related reactive oxygen species and their role in lung cancer T-cell exhaustion and immunotherapy.

Sheng Wang, Bo Liu, Fang Li, Zhe Tang, Xuyu Gu, Xianglin Yuan.

   Purpose: To study the role of mitochondrial metabolism and obtain novel biomarkers in immunotherapy for non-small cell lung cancer (NSCLC).
Methods: We collected the 188 genes involved in mitochondrial metabolism(MMGs) from the MSIGDB project and then quantified the activity of mitochondrial metabolism. All the NSCLC patients were divided into C1 and C2 clusters based on the 26 prognosis-related MMGs. The differences in biology, differential immune microenvironment, chronic hypoxia and prognosis between C1 and C2 patients were also analyzed. In addition, we validated the results of bioinformatics analysis in lung cancer tissues and cell lines.
Results: Patients in the C2 cluster had a higher level of mitochondrial metabolism. Patients in the C2 cluster responded better to immunotherapy and had a lower level of T-cell exclusion. The markers of T-cell failure were upregulated in the C1 patients. Hypoxia can lead to a high percentage of C1 patients. ADH1C might be involved in mitochondrial metabolism and immunotherapy response, which can be affected by hypoxia, making it an underlying biomarker. The expression levels of ADH1C in BEAS-2B, H1299, A549 and H460 cells were detected, revealing that ADH1C is upregulated in lung cancer cells. We observed that patients with low ADH1C expression had a longer survival time. The enzyme activities of HK, PK, LDH and SDH were significantly reduced in H1299 and H460 cells with ADH1C knockdown, along with more ROS. Furthermore, the expression levels of PD-L1 and HHLA2 in tumor tissues were analyzed, which found that ADH1C was significantly positively correlated with the expression of PD-L1 and HHLA2.
Conclusions: In summary, our study comprehensively explored the molecules involved in mitochondrial metabolism and their role in immunotherapy and T lymphocyte failure.

Keywords:  ADH1C; Immunotherapy; Mitochondrial metabolism; Non-small cell lung cancer; T lymphocyte failure

DOI:  https://doi.org/10.1016/j.heliyon.2024.e27022
Front Oncol. 2024 ;14 1286896

Metabolomics analysis reveals novel serum metabolite alterations in cancer cachexia.

Tushar H More, Karsten Hiller, Martin Seifert, Thomas Illig, Rudi Schmidt, Raphael Gronauer, Thomas von Hahn, Hauke Weilert, Axel Stang.

   Background: Cachexia is a body wasting syndrome that significantly affects well-being and prognosis of cancer patients, without effective treatment. Serum metabolites take part in pathophysiological processes of cancer cachexia, but apart from altered levels of select serum metabolites, little is known on the global changes of the overall serum metabolome, which represents a functional readout of the whole-body metabolic state. Here, we aimed to comprehensively characterize serum metabolite alterations and analyze associated pathways in cachectic cancer patients to gain new insights that could help instruct strategies for novel interventions of greater clinical benefit.
Methods: Serum was sampled from 120 metastatic cancer patients (stage UICC IV). Patients were grouped as cachectic or non-cachectic according to the criteria for cancer cachexia agreed upon international consensus (main criterium: weight loss adjusted to body mass index). Samples were pooled by cachexia phenotype and assayed using non-targeted gas chromatography-mass spectrometry (GC-MS). Normalized metabolite levels were compared using t-test (p < 0.05, adjusted for false discovery rate) and partial least squares discriminant analysis (PLS-DA). Machine-learning models were applied to identify metabolite signatures for separating cachexia states. Significant metabolites underwent MetaboAnalyst 5.0 pathway analysis.
Results: Comparative analyses included 78 cachectic and 42 non-cachectic patients. Cachectic patients exhibited 19 annotable, significantly elevated (including glucose and fructose) or decreased (mostly amino acids) metabolites associating with aminoacyl-tRNA, glutathione and amino acid metabolism pathways. PLS-DA showed distinct clusters (accuracy: 85.6%), and machine-learning models identified metabolic signatures for separating cachectic states (accuracy: 83.2%; area under ROC: 88.0%). We newly identified altered blood levels of erythronic acid and glucuronic acid in human cancer cachexia, potentially linked to pentose-phosphate and detoxification pathways.
Conclusion: We found both known and yet unknown serum metabolite and metabolic pathway alterations in cachectic cancer patients that collectively support a whole-body metabolic state with impaired detoxification capability, altered glucose and fructose metabolism, and substrate supply for increased and/or distinct metabolic needs of cachexia-associated tumors. These findings together imply vulnerabilities, dependencies and targets for novel interventions that have potential to make a significant impact on future research in an important field of cancer patient care.

Keywords:  GC-MS metabolomics; body metabolism; cancer cachexia; erythronic acid; glucuronic acid; metabolic pathways; serum metabolites

DOI:  https://doi.org/10.3389/fonc.2024.1286896
J Extracell Vesicles. 2024 Mar;13(3): e12418

PD-L1 on large extracellular vesicles is a predictive biomarker for therapy response in tissue PD-L1-low and -negative patients with non-small cell lung cancer.

Nadja Schöne, Marcel Kemper, Kerstin Menck, Georg Evers, Carolin Krekeler, Arik Bernard Schulze, Georg Lenz, Eva Wardelmann, Claudia Binder, Annalen Bleckmann.

  Immunotherapy has revolutionized the treatment of patients with non-small cell lung cancer (NSCLC). High expression of tissue PD-L1 (tPD-L1) is currently the only approved biomarker for predicting treatment response. However, even tPD-L1 low (1-49%) and absent (<1%) patients might benefit from immunotherapy but, to date, there is no reliable biomarker, that can predict response in this particular patient subgroup. This study aimed to test whether tumour-associated extracellular vesicles (EVs) could fill this gap. Using NSCLC cell lines, we identified a panel of tumour-related antigens that were enriched on large EVs (lEVs) compared to smaller EVs. The levels of lEVs carrying these antigens were significantly elevated in plasma of NSCLC patients (n = 108) and discriminated them from controls (n = 77). Among the tested antigens, we focused on programmed cell death ligand 1 (PD-L1), which is a well-known direct target for immunotherapy. In plasma lEVs, PD-L1 was mainly found on a population of CD45- /CD62P+ lEVs and thus seemed to be associated with platelet-derived vesicles. Patients with high baseline levels of PD-L1+ lEVs in blood showed a significantly better response to immunotherapy and prolonged survival. This was particularly true in the subgroup of NSCLC patients with low or absent tPD-L1 expression, thus identifying PD-L1-positive lEVs in plasma as a novel predictive and prognostic marker for immunotherapy.

Keywords:  PD-L1; biomarker; extracellular vesicles; immunotherapy; lung cancer

DOI:  https://doi.org/10.1002/jev2.12418
Clin Med Insights Oncol. 2024 ;18 11795549231222362

Prognostic Significance of the Cachexia Index in Patients with Non-Small-Cell Lung Cancer and Brain Metastases after Stereotactic Radiotherapy.

Hui Xu, Bin Zhang, Yongqian Zhang, Chunchun Yang, Changwen Bo, Yuanyuan Guo, Yuan Cheng, Li He.

   Background: The cachexia index (CXI) has been proposed as a novel biomarker of cancer cachexia. We aimed to investigate the association between CXI and survival outcomes after stereotactic radiotherapy (SRT) in patients with non-small cell lung cancer (NSCLC) and brain metastases.
Methods: Data from 145 patients with NSCLC, who underwent SRT for brain metastases between April 2016 and August 2020, were retrospectively analyzed. Cachexia index was calculated as skeletal muscle index (SMI) × serum albumin level/neutrophil-to-lymphocyte ratio, whereas SMI was calculated from computed tomography images captured at the L1 level. Kaplan-Meier curves and Cox proportional hazards models were used to assess progression-free survival (PFS) and overall survival (OS). The prognostic values of CXI and other cachexia biomarkers were assessed using receiver operating characteristic (ROC) curve analysis.
Results: Lower pretreatment CXI (<30.8) was significantly associated with older age (P = .039), lower Karnofsky performance score (P = .009), and a high likelihood of extracranial metastases (P = .001). Patients with a lower pretreatment CXI had a significantly shorter PFS and OS than those with a higher CXI (P < .001). Multivariate analysis revealed that pretreatment CXI was an independent risk factor for both PFS, hazard ratio (HR) = 2.375; 95% confidence interval (CI) = 1.610-3.504; P < .001, and OS, HR = 2.340; 95% CI = 1.562-3.505; P < .001. Compared with other biomarkers, pretreatment CXI had the highest area under the ROC curve value for prognostic assessment, reaching 0.734. Moreover, the loss of CXI was a strong risk factor for survival independent of pretreatment CXI (P = .011).
Conclusions: Cachexia index may serve as a clinically useful tool for predicting survival outcomes of patients with NSCLC and brain metastases who undergo SRT.

Keywords:  Non-small cell lung cancer; brain metastases; cancer cachexia; stereotactic radiotherapy; survival

DOI:  https://doi.org/10.1177/11795549231222362
Postgrad Med. 2024 Mar 08.

Prognostic significance of body mass index and serum albumin as the indicators of nutritional status in small cell lung cancer.

Faruk Tas, Akın Ozturk, Kayhan Erturk.

   BACKGROUND: Body mass index (BMI) and serum albumin (ALB) level are long-established markers that reflect the nutritional status and eventually the prognosis of cancer patients. The objective of the study was to determine the clinical significance of these factors and specify their roles in outcomes compared with performance status (PS) and weight loss (WL), which are considered the most significant patient-related prognostic factors in small cell lung cancer (SCLC) treated with platinum-etoposide-based chemotherapy.
METHODS: A total of 378 patients with SCLC were enrolled in the study and analyzed retrospectively.
RESULTS: BMI values were similar by clinical stage, whereas the percentages of the patients with WL, low serum ALB, and particularly poor (≥2) PS were significantly higher in patients with extended disease SCLC (ED-SCLC) compared to those with limited disease SCLC (LD-SCLC). In LD-SCLC, patients with poor PS lived for a significantly shorter time than patients with good PS (HR: 7.791, p = 0.0001); however, BMI (HR: 1.035, p = 0.8), WL (HR: 0.857, p = 0.5), and ALB (HR: 0.743, p = 0.3) had no significant effect on the outcome. In ED-SCLC, PS (HR: 4.257, p = 0.0001), WL (HR: 1.677, p = 0.001), and ALB (HR: 0.680, p = 0.007) had an impact on survival, but BMI did not (HR: 0.791, p = 0.08). In LD-SCLC, the univariate analysis showed that only poor PS was correlated with increased mortality (HR: 7.791, p = 0.0001); yet it lost significance in multivariate analysis. In ED-SCLC, poor PS (HR: 4.257, p = 0.0001), WL (HR: 1.667, p = 0.001), and a low ALB level (HR: 0.680, p = 0.007) were shown to be factors for poor prognosis in the univariate analysis; yet only PS remained significant in multivariate analysis (HR: 2.286, p = 0.001).
CONCLUSION: Even though BMI and serum albumin showed no prognostic value in SCLC patients treated with chemotherapy, PS was found to be the most significant prognostic factor in both LD- and ED-SCLC stages.

Keywords:  BMI; PS; SCLC; albumin; prognostic factor

DOI:  https://doi.org/10.1080/00325481.2024.2328512
J Cancer Res Clin Oncol. 2024 Mar 03. 150(3): 111

Influence of abdominal fat distribution and inflammatory status on post-operative prognosis in non-small cell lung cancer patients: a retrospective cohort study.

Mengtian Ma, Muqing Luo, Qianyun Liu, Dong Zhong, Yinqi Liu, Kun Zhang.

   PURPOSE: To evaluate the influence of visceral fat area (VFA), subcutaneous fat area (SFA), the systemic immune-inflammation index (SII) and total inflammation-based systemic index (AISI) on the postoperative prognosis of non-small cell lung cancers (NSCLC) patients.
METHODS: 266 NSCLC patients received surgery from two academic medical centers were included. To assess the effect of abdominal fat measured by computed tomography (CT) imaging and inflammatory indicators on patients' overall survival (OS) and progression-free survival (PFS), Kaplan-Meier survival analysis and Cox proportional hazards models were used.
RESULTS: Kaplan-Meier analysis showed the OS and PFS of patients in high-VFA group was better than low-VFA group (p < 0.05). AISI and SII were shown to be risk factors for OS and PFS (p < 0.05) after additional adjustment for BMI (Cox regression model II). After further adjustment for VFA (Cox regression model III), low-SFA group had longer OS (p < 0.05). Among the four subgroups based on VFA (high/low) and SFA (high/low) (p < 0.05), the high-VFA & low-SFA group had the longest median OS (108 months; 95% CI 74-117 months) and PFS (85 months; 95% CI 65-117 months), as well as the lowest SII and AISI (p < 0.05). Low-SFA was a protective factor for OS with different VFA stratification (p < 0.05).
CONCLUSION: VFA, SFA, SII and AISI may be employed as significant prognostic markers of postoperative survival in NSCLC patients. Moreover, excessive SFA levels may encourage systemic inflammation decreasing the protective impact of VFA, which may help to provide targeted nutritional support and interventions for postoperative NSCLC patients with poor prognosis.

Keywords:  Non-small cell lung cancer; Subcutaneous fat; Systemic inflammation; Visceral fat

DOI:  https://doi.org/10.1007/s00432-024-05633-5
J Appl Genet. 2024 Mar 05.

Transcriptome profiling and metabolic pathway analysis towards reliable biomarker discovery in early-stage lung cancer.

Muthu Kumar Thirunavukkarasu, Priyanka Ramesh, Ramanathan Karuppasamy, Shanthi Veerappapillai.

  Earlier diagnosis of lung cancer is crucial for reducing mortality and morbidity in high-risk patients. Liquid biopsy is a critical technique for detecting the cancer earlier and tracking the treatment outcomes. However, noninvasive biomarkers are desperately needed due to the lack of therapeutic sensitivity and early-stage diagnosis. Therefore, we have utilized transcriptomic profiling of early-stage lung cancer patients to discover promising biomarkers and their associated metabolic functions. Initially, PCA highlights the diversity level of gene expression in three stages of lung cancer samples. We have identified two major clusters consisting of highly variant genes among the three stages. Further, a total of 7742, 6611, and 643 genes were identified as DGE for stages I-III respectively. Topological analysis of the protein-protein interaction network resulted in seven candidate biomarkers such as JUN, LYN, PTK2, UBC, HSP90AA1, TP53, and UBB cumulatively for the three stages of lung cancers. Gene enrichment and KEGG pathway analyses aid in the comprehension of pathway mechanisms and regulation of identified hub genes in lung cancer. Importantly, the medial survival rates up to ~ 70 months were identified for hub genes during the Kaplan-Meier survival analysis. Moreover, the hub genes displayed the significance of risk factors during gene expression analysis using TIMER2.0 analysis. Therefore, we have reason that these biomarkers may serve as a prospective targeting candidate with higher treatment efficacy in early-stage lung cancer patients.

Keywords:  CytoHubba; Differential gene expression; Kaplan–Meier analysis; RNA-sequencing; Subio64

DOI:  https://doi.org/10.1007/s13353-024-00847-2