bims-meluca Biomed News
on Metabolism of non-small cell lung carcinoma
Issue of 2023–05–07
eight papers selected by
the Muñoz-Pinedo/Nadal (PReTT) lab, L’Institut d’Investigació Biomèdica de Bellvitge



  1. bioRxiv. 2023 Apr 20. pii: 2023.04.18.537350. [Epub ahead of print]
      LKB1/STK11 is a serine/threonine kinase that plays a major role in controlling cell metabolism, resulting in potential therapeutic vulnerabilities in LKB1-mutant cancers. Here, we identify the NAD + degrading ectoenzyme, CD38, as a new target in LKB1-mutant NSCLC. Metabolic profiling of genetically engineered mouse models (GEMMs) revealed that LKB1 mutant lung cancers have a striking increase in ADP-ribose, a breakdown product of the critical redox co-factor, NAD + . Surprisingly, compared with other genetic subsets, murine and human LKB1-mutant NSCLC show marked overexpression of the NAD+-catabolizing ectoenzyme, CD38 on the surface of tumor cells. Loss of LKB1 or inactivation of Salt-Inducible Kinases (SIKs)-key downstream effectors of LKB1- induces CD38 transcription induction via a CREB binding site in the CD38 promoter. Treatment with the FDA-approved anti-CD38 antibody, daratumumab, inhibited growth of LKB1-mutant NSCLC xenografts. Together, these results reveal CD38 as a promising therapeutic target in patients with LKB1 mutant lung cancer.
    SIGNIFICANCE: Loss-of-function mutations in the LKB1 tumor suppressor of lung adenocarcinoma patients and are associated with resistance to current treatments. Our study identified CD38 as a potential therapeutic target that is highly overexpressed in this specific subtype of cancer, associated with a shift in NAD homeostasis.
    DOI:  https://doi.org/10.1101/2023.04.18.537350
  2. Biomed Pharmacother. 2023 May 03. pii: S0753-3322(23)00592-9. [Epub ahead of print]163 114802
      Cancer-associated cachexia (CAC) is a multifactorial disorder characterized by an unrestricted loss of body weight as a result of muscle and adipose tissue atrophy. Cachexia is influenced by several factors, including decreased metabolic activity and food intake, an imbalance between energy uptake and expenditure, excessive catabolism, and inflammation. Cachexia is highly associated with all types of cancers responsible for more than half of cancer-related mortalities worldwide. In healthy individuals, adipose tissue significantly regulates energy balance and glucose homeostasis. However, in metastatic cancer patients, CAC occurs mainly because of an imbalance between muscle protein synthesis and degradation which are organized by certain extracellular ligands and associated signaling pathways. Under hypoxic conditions, hypoxia-inducible factor-1 (HIF-1α) accumulated and translocated to the nucleus and activate numerous genes involved in cell survival, invasion, angiogenesis, metastasis, metabolic reprogramming, and cancer stemness. On the other hand, the ubiquitination proteasome pathway is inhibited during low O2 levels which promote muscle wasting in cancer patients. Therefore, understanding the mechanism of the HIF-1 pathway and its metabolic adaptation to biomolecules is important for developing a novel therapeutic method for cancer and cachexia therapy. Even though many HIF inhibitors are already in a clinical trial, their mechanism of action remains unknown. With this background, this review summarizes the basic concepts of cachexia, the role of inflammatory cytokines, pathways connected with cachexia with special reference to the HIF-1 pathway and its regulation, metabolic changes, and inhibitors of HIFs.
    Keywords:  Adipogenesis; Cancer-associated cachexia; Hypoxia-inducible factor-1; Metabolism; Muscle wasting; Signaling pathways
    DOI:  https://doi.org/10.1016/j.biopha.2023.114802
  3. Ann Oncol. 2023 Apr 28. pii: S0923-7534(23)00656-7. [Epub ahead of print]
       BACKGROUND: Prior studies characterized the association of molecular alterations with treatment-specific outcomes in KRAS-mutant (KRASMUT) lung adenocarcinoma (LUAD). Less is known about the prognostic role of molecular alterations and their associations with metastatic disease.
    PATIENTS AND METHODS: We analyzed clinicogenomic data from 1817 patients with KRASMUT LUAD sequenced at the Dana-Farber Cancer Institute (DFCI) and Memorial Sloan Kettering Cancer Center (MSKCC). Patients with metastatic (M1) and non-metastatic (M0) disease were compared. Transcriptomic data from TCGA was investigated to characterize the biology of differential associations with clinical outcomes. Organ-specific metastasis was associated with overall survival (OS).
    RESULTS: KEAP1 (DFCI: OR=2.3, q=0.04; MSKCC: OR=2.2, q=0.00027) and SMARCA4 mutations (DFCI: OR=2.5 , q=0.06; MSKCC: OR=2.6, q=0.0021) were enriched in M1 vs M0 tumors. On integrative modeling, NRF2 activation was the genomic feature most associated with OS. KEAP1 mutations were enriched in M1 vs M0 tumors independent of STK11 status (KEAP1MUT/STK11WT: DFCI OR=3.0, P=0.0064; MSKCC OR=2.0, P=0.041; KEAP1MUT/STK11MUT: DFCI OR=2.3, P=0.0063; MSKCC OR=2.5, P=3.6e-05); STK11 mutations without KEAP1 loss were not associated with stage (KEAP1WT/STK11MUT: DFCI OR=0.97, P=1.0; MSKCC OR=1.2, P=0.33) or outcome. KEAP1/KRAS-mutated tumors with and without STK11 mutations exhibited high functional STK11 loss. The negative effects of KEAP1 were compounded in the presence of bone (HR=2.3, P=4.4e-14) and negated in the presence of lymph node metastasis (HR=1.0, P=0.91).
    CONCLUSIONS: Mutations in KEAP1 and SMARCA4, but not STK11, were associated with metastatic disease and poor OS. Functional STK11 loss, however, may contribute to poor outcomes in KEAP1MUT tumors. Integrating molecular data with clinical and metastatic-site annotations can more accurately risk stratify patients.
    Keywords:  KEAP1; KRAS; Lung adenocarcinoma; Metastatic; STK11
    DOI:  https://doi.org/10.1016/j.annonc.2023.04.514
  4. Immunobiology. 2023 Apr 18. pii: S0171-2985(23)00057-8. [Epub ahead of print]228(3): 152389
       INTRODUCTION: Despite the clinical success of PD-1/PD-1-ligand immunotherapy in non-small cell lung cancer (NSCLC), the appearance of primary and acquired therapy resistance is a major challenge reflecting that the mechanisms regulating the expression of the PD-1-ligands PD-L1 and PD-L2 are not fully explored. Type I and II interferons (IFNs) induce PD-L1 and PD-L2 expression. Here, we examined if PD-L1 and PD-L2 expression also can be induced by type III IFN, IFN-λ, which is peculiarly important for airway epithelial surfaces.
    METHODS: In silico mRNA expression analysis of PD-L1 (CD274), PD-L2 (PDCD1LG2), and IFN- λ signaling signature genes in NSCLC tumors and cell lines was performed using RNA sequencing expression data from TCGA, OncoSG, and DepMap portals. IFN-λ-mediated induction of PD-L1 and PD-L2 expression in NSCLC cell lines was examined by real-time quantitative polymerase chain reaction and flow cytometry.
    RESULTS: IFNL genes encoding IFN- λ variants are expressed in the majority of NSCLC tumors and cell lines along with the IFNLR1 and IL10R2 genes encoding the IFN-λ receptor subunits. The expression of PD-L1 and PD-L2 mRNA is higher in NSCLC tumors with IFNL mRNA expression compared to tumors without IFNL expression. In the NSCLC cell line HCC827, stimulation with IFN-λ induced both an increase in PD-L1 and PD-L2 mRNA expression and cell surface abundance of the corresponding proteins. In the NSCLC cell line A427, displaying a low basal expression of PD-L1 and PD-L2 mRNA and corresponding proteins, stimulation with IFN-λ resulted in an induction of the former.
    CONCLUSION: The type III IFN, IFN- λ, is capable of inducing PD-L1 and PD-L2 expression, at least in some NSCLC cells, and this regulation will need acknowledgment in the development of new diagnostic procedures, such as gene expression signature profiles, to improve PD-1/PD-1-ligand immunotherapy in NSCLC.
    Keywords:  IFN signaling; IFNL; Immunotherapy; Lung cancer
    DOI:  https://doi.org/10.1016/j.imbio.2023.152389
  5. Oncoimmunology. 2023 ;12(1): 2204745
      Better biomarkers for programmed death - (ligand) 1 (PD-(L)1) checkpoint blockade in non-small cell lung cancer (NSCLC) are needed. We explored the predictive value of early response evaluation using Fluor-18-deoxyglucose positron emission tomography and pre- and on-treatment flowcytometric T-cell profiling in peripheral blood and tumor-draining lymph nodes (TDLN). The on-treatment evaluation was performed 7-14 days after the start of PD-1 blockade in NSCLC patients. These data were related to (pathological) tumor response, progression-free survival, and overall survival (OS). We found that increases in total lesion glycolysis (TLG) had a strong reverse correlation with OS (r = -0.93, p = 0.022). Additionally, responders showed decreased progressors and increased Treg frequencies on-treatment. Frequencies of detectable PD-1-expressing CD8+ T cells decreased in responders but remained stable in progressors. This was especially found in the TDLN. Changes in activated Treg rates in TDLN were strongly but, due to low numbers of data points, non-significantly correlated with ΔTLG and reversely correlated with OS.
    Keywords:  NSCLC; PD-1 inhibitor; PET–CT; T-cell profiling; TDLN; biomarker; immunotherapy
    DOI:  https://doi.org/10.1080/2162402X.2023.2204745
  6. Front Nutr. 2023 ;10 1143213
       Background: Sarcopenia, frailty, and malnutrition are associated with undesirable clinical outcomes in cancer patients. Sarcopenia-related measurements may be promising fast biomarkers for frailty. Our objectives were to assess the prevalence of nutritional risk, malnutrition, frailty, and sarcopenia in lung cancer inpatients, and describe the relationship of them.
    Methods: Stage III and IV lung cancer inpatients were recruited before chemotherapy. The skeletal muscle index (SMI) was assessed by multi-frequency bioelectric impedance analysis (m-BIA). Sarcopenia, frailty, nutritional risk, and malnutrition were diagnosed according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019), Fried Frailty Phenotype (FFP), nutritional risk screening-2002 (NRS-2002), and Global Leadership Initiative on Malnutrition criteria (GLIM), and correlation analysis was performed between them with Pearson's r correlation coefficients. A univariate and multivariate logistic regression analysis was conducted for all patients, gender and age-stratified subgroups to obtain odds ratios (ORs) and 95% confidence intervals (95%CIs).
    Results: The cohort included 97 men (77%) and 29 women (23%), with mean age of 64.8 ± 8.7 years. Among the 126 patients, 32 (25.4%) and 41 (32.5%) had sarcopenia and frailty, and the prevalence of nutritional risk and malnutrition was 31.0% (n = 39) and 25.4% (n = 32). Adjusted for age and gender, SMI was correlated with FFP (r = -0.204, p = 0.027), and did not remain significantly when stratified by gender. Stratification according to age revealed in ≥65-years-old population, SMI and FFP were significantly correlated (r = -0.297, p = 0.016), which is not seen in <65-years-old group (r = 0.048, p = 0.748). The multivariate regression analysis showed FFP, BMI, and ECOG were the independent variables associated with sarcopenia (OR 1.536, 95%CI 1.062-2.452, p = 0.042; OR 0.625, 95%CI 0.479-0.815, p = 0.001; OR 7.286, 95%CI 1.779-29.838, p = 0.004).
    Conclusion: Comprehensively assessed sarcopenia is independently associated with frailty based on FFP questionnaire, BMI, and ECOG. Therefore, sarcopenia assessment including m-BIA based SMI, and muscle strength and function could be used to indicate frailty to help select the targeting patients for care. Moreover, in addition to muscle mass, muscle quality should not be ignored in clinical practice.
    Keywords:  frailty; lung cancer; malnutrition; nutritional risk; sarcopenia
    DOI:  https://doi.org/10.3389/fnut.2023.1143213
  7. Oncoimmunology. 2023 ;12(1): 2206725
      The immune microenvironment of non-small cell lung cancer (NSCLC) is heterogeneous, which impedes the prediction of response to immune checkpoint inhibitors. We have mapped the expression of 49 proteins to spatial immune niches in 33 NSCLC tumors and report key differences in phenotype and function associated with the spatial context of immune infiltration. Tumor-infiltrating leukocytes (TIL), identified in 42% of tumors, had a similar proportion of lymphocyte antigens compared to stromal leukocytes (SL) but displayed significantly higher levels of functional, mainly immune suppressive, markers including PD-L1, PD-L2, CTLA-4, B7-H3, OX40L, and IDO1. In contrast, SL expressed higher levels of the targetable T-cell activation marker CD27, which increased with a longer distance to the tumor. Correlation analysis confirmed that metabolic-driven immune regulatory mechanisms, including ARG1 and IDO1, are present in the TIL. Tertiary lymphoid structures (TLS) were identified in 30% of patients. They displayed less variation in the expression profile and with significantly higher levels of pan lymphocyte and activation markers, dendritic cells, and antigen presentation compared to other immune niches. TLS also had higher CTLA-4 expression than non-structured SL, which may indicate immune dysfunction. Neither the presence of TIL nor TLS was associated with improved clinical outcomes. The apparent discrimination in functional profiles of distinct immune niches, independent of the overall level of leukocytes, illustrates the importance of spatial profiling to deconvolute how the immune microenvironment can dictate a therapeutic response and to identify biomarkers in the context of immunomodulatory treatment.
    Keywords:  NSCLC; immune infiltration; spatial omics; tertiary lymphoid structures; tumor-infiltrating leukocytes
    DOI:  https://doi.org/10.1080/2162402X.2023.2206725
  8. Front Genet. 2023 ;14 1156322
      Background: Brain metastasis, with an incidence of more than 30%, is a common complication of non-small cell lung cancer (NSCLC). Therefore, there is an urgent need for an assessment method that can effectively predict brain metastases in NSCLC and help understand its mechanism. Materials and methods: GSE30219, GSE31210, GSE37745, and GSE50081 datasets were downloaded from the GEO database and integrated into a dataset (GSE). The integrated dataset was divided into the training and test datasets. TCGA-NSCLC dataset was regarded as an independent verification dataset. Here, the limma R package was used to identify the differentially expression genes (DEGs). Importantly, the RiskScore model was constructed using univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis. Moreover, we explored in detail the tumor mutational signature, immune signature, and sensitivity to treatment of brain metastases in NSCLC. Finally, a nomogram was built using the rms package. Results: First, 472 DEGs associated with brain metastases in NSCLC were obtained, which were closely associated with cancer-associated pathways. Interestingly, a RiskScore model was constructed using 11 genes from 472 DEGs, and the robustness was confirmed in GSE test, entire GSE, and TCGA datasets. Samples in the low RiskScore group had a higher gene mutation score and lower immunoinfiltration status. Moreover, we found that the patients in the low RiskScore group were more sensitive to the four chemotherapy drugs. In addition, the predictive nomogram model was able to effectively predict the outcome of patients through appropriate RiskScore stratification. Conclusion: The prognostic RiskScore model we established has high prediction accuracy and survival prediction ability for brain metastases in NSCLC.
    Keywords:  NSCLC; RiskScore model; brain metastases; chemotherapy drugs; lung cancer; prognosis
    DOI:  https://doi.org/10.3389/fgene.2023.1156322