bims-meluca Biomed News
on Metabolism of non-small cell lung carcinoma
Issue of 2021‒06‒06
five papers selected by
Cristina Muñoz Pinedo
L’Institut d’Investigació Biomèdica de Bellvitge


  1. Front Pharmacol. 2021 ;12 671328
      The emergence of secondary resistance is the main failure cause of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) as a targeted therapy for non-small cell lung cancer (NSCLC). EGFR mutations of NSCLC cells can markedly increase glutamine transporter (SLC1A5) expression, thereby increasing glutamine metabolism. Glutamine metabolites can activate EGFR downstream signals, including mTOR, ERK1/2, STAT3, etc., which is an important cause for the decreased sensitivity of NSCLC to EGFR-TKIs. CCK8 and Annexin V/PI assays were conducted to detect the effects of Almonertinib and/or V9302 on the proliferation and apoptosis of NSCLC cells. Proteomics was used to determine the effect of Almonertinib on energy metabolism-related proteins in NSCLC. siRNA transfection was performed to study the effect of SLC1A5 down-regulation on cell proliferation. In addition, the effects of drugs on colony formation capacity were determined by colony formation assay. Immunofluorescence and Western blot were utilized to detect the apoptosis- and autophagy-related proteins expression. DAPI staining was utilized to detect the effect of drugs on the nucleus. Transmission electron microscope was used to observe the changes of submicroscopic structure such as autophagosomes and nucleus of cells. mCherry-GFP-LC3B tandem fluorescent protein was to used to detect the level of autophagy flux. Tumor-bearing nude mouse model was utilized to detect the effect of V9302 on the anti-tumor effect of Almonertinib in vivo. As a result, Almonertinib suppressed H1975 and A549 cell proliferation depended on its dosage and treatment duration, and it also induced apoptosis. A549 cells with wild-type EGFR had lower sensitivity to Almonertinib. The expression of SLC1A5 was up-regulated by stimulating with low concentration of Almonertinib in NSCLC cells. SLC1A5 was highly expressed in A549 cells with wild-type EGFR. Glutamine deletion or SLC1A5 inhibition/silencing inhibited the proliferation of NSCLC cells, and decreased cellular glutamine uptake. The combination of SLC1A5 inhibitor V9302 and Almonertinib had a synergistic inhibitory effect on the proliferation of NSCLC. V9302 enhanced the effect of Almonertinib in apoptosis-inducing in NSCLC cells. The combination of V9302 and Almonertinib might induce apoptosis by inhibiting autophagy.
    Keywords:  EGFR-TKI; SLC1A5; almonertinib; apoptosis; autophagy
    DOI:  https://doi.org/10.3389/fphar.2021.671328
  2. Antioxidants (Basel). 2021 May 15. pii: 786. [Epub ahead of print]10(5):
      Nrf2 (nuclear factor erythroid 2 (NF-E2)-related factor 2) transcription factor is recognized for its pro-survival and cell protective role upon exposure to oxidative, chemical, or metabolic stresses. Nrf2 controls a number of cellular processes such as proliferation, differentiation, apoptosis, autophagy, lipid synthesis, and metabolism and glucose metabolism and is a target of activation in chronic diseases like diabetes, neurodegenerative, and inflammatory diseases. The dark side of Nrf2 is revealed when its regulation is imbalanced (e.g., via oncogene activation or mutations) and under such conditions constitutively active Nrf2 promotes cancerogenesis, metastasis, and radio- and chemoresistance. When there is no stress, Nrf2 is instantly degraded via Keap1-Cullin 3 (Cul3) pathway but despite this, cells exhibit a basal activation of Nrf2 target genes. It is yet not clear how Nrf2 maintains the expression of its targets under homeostatic conditions. Here, we found a stable 105 kDa Nrf2 form that is resistant to Keap1-Cul3-mediated degradation and translocates to the nucleus of lung cancer cells. RNA-Seq analysis indicate that it might originate from the exon 2 or exon 3-truncated transcripts. This stable 105 kDa Nrf2 form might help explain the constitutive activity of Nrf2 under normal cellular conditions.
    Keywords:  Nrf2 antibodies; Nrf2 detection; Nrf2 migration in SDS-PAGE
    DOI:  https://doi.org/10.3390/antiox10050786
  3. Front Med. 2021 Jun 04.
      Aberrant de novo lipid synthesis is involved in the progression and treatment resistance of many types of cancers, including lung cancer; however, targeting the lipogenetic pathways for cancer therapy remains an unmet clinical need. In this study, we tested the anticancer activity of orlistat, an FDA-approved anti-obesity drug, in human and mouse cancer cells in vitro and in vivo, and we found that orlistat, as a single agent, inhibited the proliferation and viabilities of lung cancer cells and induced ferroptosis-like cell death in vitro. Mechanistically, we found that orlistat reduced the expression of GPX4, a central ferroptosis regulator, and induced lipid peroxidation. In addition, we systemically analyzed the genome-wide gene expression changes affected by orlistat treatment using RNA-seq and identified FAF2, a molecule regulating the lipid droplet homeostasis, as a novel target of orlistat. Moreover, in a mouse xenograft model, orlistat significantly inhibited tumor growth and reduced the tumor volumes compared with vehicle control (P < 0.05). Our study showed a novel mechanism of the anticancer activity of orlistat and provided the rationale for repurposing this drug for the treatment of lung cancer and other types of cancer.
    Keywords:  FAF2; ferroptosis; lung cancer; orlistat
    DOI:  https://doi.org/10.1007/s11684-020-0804-7
  4. Cancers (Basel). 2021 May 31. pii: 2714. [Epub ahead of print]13(11):
      Serum metabolome is a promising source of molecular biomarkers that could support early detection of lung cancer in screening programs based on low-dose computed tomography. Several panels of metabolites that differentiate lung cancer patients and healthy individuals were reported, yet none of them were validated in the population at high-risk of developing cancer. Here we analyzed serum metabolome profiles in participants of two lung cancer screening studies: MOLTEST-BIS (Poland, n = 369) and SMAC-1 (Italy, n = 93). Three groups of screening participants were included: lung cancer patients, individuals with benign pulmonary nodules, and those without any lung alterations. Concentrations of about 400 metabolites (lipids, amino acids, and biogenic amines) were measured by a mass spectrometry-based approach. We observed a reduced level of lipids, in particular cholesteryl esters, in sera of cancer patients from both studies. Despite several specific compounds showing significant differences between cancer patients and healthy controls within each study, only a few cancer-related features were common when both cohorts were compared, which included a reduced concentration of lysophosphatidylcholine LPC (18:0). Moreover, serum metabolome profiles in both noncancer groups were similar, and differences between cancer patients and both groups of healthy participants were comparable. Large heterogeneity in levels of specific metabolites was observed, both within and between cohorts, which markedly impaired the accuracy of classification models: The overall AUC values of three-state classifiers were 0.60 and 0.51 for the test (MOLTEST) and validation (SMAC) cohorts, respectively. Therefore, a hypothetical metabolite-based biomarker for early detection of lung cancer would require adjustment to lifestyle-related confounding factors that putatively affect the composition of serum metabolome.
    Keywords:  biomarkers; early detection; lung cancer; metabolomics; screening study
    DOI:  https://doi.org/10.3390/cancers13112714
  5. Sci Rep. 2021 Jun 03. 11(1): 11805
      Lung cancer is the leading cause of human cancer mortality due to the lack of early diagnosis technology. The low-dose computed tomography scan (LDCT) is one of the main techniques to screen cancers. However, LDCT still has a risk of radiation exposure and it is not suitable for the general public. In this study, plasma metabolic profiles of lung cancer were performed using a comprehensive metabolomic method with different liquid chromatography methods coupled with a Q-Exactive high-resolution mass spectrometer. Metabolites with different polarities (amino acids, fatty acids, and acylcarnitines) can be detected and identified as differential metabolites of lung cancer in small volumes of plasma. Logistic regression models were further developed to identify cancer stages and types using those significant biomarkers. Using the Variable Importance in Projection (VIP) and the area under the curve (AUC) scores, we have successfully identified the top 5, 10, and 20 metabolites that can be used to differentiate lung cancer stages and types. The discrimination accuracy and AUC score can be as high as 0.829 and 0.869 using the five most significant metabolites. This study demonstrated that using 5 + metabolites (Palmitic acid, Heptadecanoic acid, 4-Oxoproline, Tridecanoic acid, Ornithine, and etc.) has the potential for early lung cancer screening. This finding is useful for transferring the diagnostic technology onto a point-of-care device for lung cancer diagnosis and prognosis.
    DOI:  https://doi.org/10.1038/s41598-021-91276-2