Prognosis Of Non-small Cell Lung Cancer Research Articles

The detection of circulating tumor cells indicates poor therapeutic efficacy and prognosis in patients with nonsmall cell lung cancer: A systematic review and meta-analysis.

The efficacy and prognostic value of circulating tumor cells (CTCs) in nonsmall cell lung cancer (NSCLC) are controversial based on the existing research. This systematic review and meta-analysis evaluated the significance of CTCs in NSCLC therapy monitoring and prognosis prediction, supporting their potential as clinical biomarkers. We conducted a comprehensive search of PubMed, Embase, Web of Science, The Cochrane Library, WanFang Data, CNKI, and VIP through September 20, 2023. Inclusion criteria were cohort studies involving NSCLC patients, focusing on peripheral blood CTCs, and assessing outcomes such as pre- and posttreatment CTC rates or levels, progression-free survival (PFS), and overall survival (OS). Two reviewers independently extracted the data and assessed risk of bias using the Newcastle-Ottawa Scale. We utilized Review Manager 5.4.1 for meta-analysis, calculating pooled odds ratios (ORs) for dichotomous outcomes, mean differences for continuous variables and hazard ratios (HRs) for survival data, applying fixed- or random-effects models based on heterogeneity assessed by the I2 statistic. This study was registered in PROSPERO (No. CRD42023450035). Twenty-two eligible studies with a total of 1674 NSCLC patients were included. Meta-analysis results showed that the CTCs-positive rate (OR=0.59, 95% CI 0.45 to 0.77, p=0.0001) and CTCs count (mean difference=-3.10, 95% CI -5.52 to -0.69, p=0.01) were significantly decreased after antitumor treatment. Compared with the CTCs nonreduced group, the CTC-reduced group showed better PFS (HR=1.71, 95% CI 1.35 to 2.17, p<0.00001) and OS (HR=1.50, 95% CI 1.21 to 1.86, p=0.0003) after treatment. PFS and OS in CTC-positive groups were lower than those in the CTCs-negative group pretreatment (HR=2.49, 95% CI 1.78 to 3.47, p<0.00001; HR=1.80, 95% CI 1.29 to 2.52, p=0.0006) and posttreatment (HR=3.36, 95% CI 2.12 to 5.33, p<0.00001; HR=3.31, 95% CI 1.75 to 6.27, p=0.0002). CTCs can be used as a biomarker to monitor NSCLC efficacy, predict prognosis and guide follow-up treatment.

The prognostic value and model construction of inflammatory markers for patients with non-small cell lung cancer

The aim of this study was to investigate and analyse the predictive value of systemic inflammatory markers based on peripheral blood biomarkers for the prognosis of non-small cell lung cancer (NSCLC) patients. Based on a retrospective monitoring cohort of 973 NSCLC patients from an Affiliated Tumor Hospital from 2012 to 2023. The log-rank test and Cox proportional risk regression model were used to identify independent prognostic inflammatory markers. Subsequently, a nomogram prediction model was constructed and evaluated. The results of multivariate Cox regression analysis showed that patients with high NLR group (HR = 1.238, 95% CI 1.015–1.510, P = 0.035), and high CAR group (HR = 1.729, 95% CI 1.408–2.124, P < 0.001) were risk factors affecting the prognosis of NSCLC patients. The nomogram that includes age, tumor stage, smoking history, BMI, NLR, and CAR can effectively predict the prognosis of NSCLC patients.The inflammatory markers NLR and CAR, which combine inflammatory and nutritional status, are effective predictors of the prognosis of NSCLC patients. The combination of clinical information and these easily accessible inflammatory markers has significant research value for prognostic assessment, clinical treatment, and follow-up monitoring of NSCLC patients.

Nanoparticles targeting mutant p53 overcome chemoresistance and tumor recurrence in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) shows high drug resistance and leads to low survival due to the high level of mutated Tumor Protein p53 (TP53). Cisplatin is a first-line treatment option for NSCLC, and the p53 mutation is a major factor in chemoresistance. We demonstrate that cisplatin chemotherapy increases the risk of TP53 mutations, further contributing to cisplatin resistance. Encouragingly, we find that the combination of cisplatin and fluvastatin can alleviate this problem. Therefore, we synthesize Fluplatin, a prodrug consisting of cisplatin and fluvastatin. Then, Fluplatin self-assembles and is further encapsulated with poly-(ethylene glycol)–phosphoethanolamine (PEG–PE), we obtain Fluplatin@PEG–PE nanoparticles (FP NPs). FP NPs can degrade mutant p53 (mutp53) and efficiently trigger endoplasmic reticulum stress (ERS). In this study, we show that FP NPs relieve the inhibition of cisplatin chemotherapy caused by mutp53, exhibiting highly effective tumor suppression and improving the poor NSCLC prognosis.

Immature central tumor tertiary lymphoid structures are associated with better prognosis in non-small cell lung cancer

Background & aimsTertiary lymphoid structures (TLSs) are predictive biomarkers of favorable clinical outcomes and immunotherapy response in several solid malignancies, including non-small cell lung cancer (NSCLC). However, the relationship between TLSs and NSCLC prognosis has not been eludicated from the aspects of location, density, and maturity. This study aimed to investigate the clinicopathological and prognostic significance of TLSs in NSCLC.MethodsA collection of 151 resected pulmonary nodules in patients with NSCLC was retrospectively analyzed. Two experienced pathologists reviewed hematoxylin-eosin (H&E) slides and assessed TLS scores at different anatomic subregions. Then, we analyzed their correlation with clinicopathologic parameters and CD8 staining intensity and assessed multiple clinicopathological factors affecting patient prognosis.ResultsCD8 expression was correlated with total (TLS-CT) (P = 0.000), aggregates (Agg) (TLS-CT) (P = 0.001), follicles (FOL)-I (TLS-CT) (P = 0.025), and TLS(overall) (P = 0.013). TLS scores in the central tumor (CT) and invasion margin (IM) areas were negatively correlated with distant metastasis and Union for International Cancer Control (UICC) stage in NSCLC patients, while TLS score in the CT area was positively correlated with CD8 expression. TLS (overall), Agg (TLS-CT), and FOL-I (TLS-CT) were positively correlated with distant metastasis, UICC stage, and CD8 expression in NSCLC patients. Agg (TLS-IM) was positively correlated with distant metastasis and UICC stage. FOL-I (TLS-IM) was positively correlated with UICC stage. FOL-II (TLS-IM) was positively correlated with distant metastasis (P < 0.05). Multivariate Cox regression analysis showed that unfavorable independent prognostic factors were associated with metastasis status and UICC stage. Independent prognostic factors with protective effects included Agg (TLS-CT), FOL-I (TLS-CT), total (TLS-CT), and overall TLS (P < 0.05).ConclusionHistological score assessment of H&E sections of Agg (TLS-CT), FOL-I (TLS-CT), total (TLS-CT), and overall TLS levels in NSCLC has prognostic value.

DNA variants detected in primary and metastatic lung adenocarcinoma: a case report and review of the literature.

Non-small cell lung cancer (NSCLC) has been found to have recurrent genetic abnormalities, and novel therapies targeting these aberrations have improved patient survival. In this study, specimens from benign tissue, primary tumors, and brain metastases were obtained at autopsy from a 55-year-old White female patient diagnosed with NSCLC and were examined using next-generation sequencing (NGS) and chromosomal microarray assay (CMA). No genetic aberrations were noted in the benign tissue; however, NGS identified a mutation in the KRAS proto-oncogene, GTPase (KRAS): KRAS exon 2 p.G12D in primary and metastatic tumor specimens. We observed 7 DNA copy number aberrations (CNAs) in primary and metastatic tumor specimens; an additional 7 CNAs were exclusively detected in the metastatic tumor specimens. These DNA alterations may be genetic drivers in the pathogenesis of the tumor specimen from our patient and may serve as biomarkers for the classification and prognosis of NSCLC.

Abstract 6189: Deep-learning model trained on multiplex immunofluorescence-stained tissue samples predicts the survival of patients with non-small cell lung cancer better than PD-L1 TPS alone

Abstract In non-small cell lung cancer (NSCLC), the composition and structure of the tumor immune microenvironment (TME) critically impact patient outcomes, necessitating improved computational approaches to characterize the TME beyond traditional metrics like the PD-L1 tumor proportion score (TPS). Here, we developed an interpretable deep-learning model that robustly predicts patient overall survival (OS) and identifies unique PD-L1 enriched neighborhoods linked to patient prognosis. We utilized a dataset of 507 NSCLC patient biopsy samples prospectively acquired as part of the DFCI ImmunoPROFILE project. Each sample was stained for Cytokeratin as tumor marker, PD-L1, PD-1, CD8, and FOXP3 using a targeted multiplex immunofluorescence assay. Inner tumor regions of interest were automatically processed for spatially resolved identification and quantification of marker expression at the single-cell level. The dataset was divided into 380 patients for model development and 127 for testing. The deep-learning model, a graph neural network (GNN), was trained to predict OS based on local cell neighborhoods using a weakly supervised training paradigm. The GNN models neighborhoods as a graph, with cells and their corresponding marker expression representing nodes and edges connecting adjacent cells, for an average of 42 cells per neighborhood. Survival predictions were obtained by averaging predictions over all neighborhoods from one sample. The GNN model demonstrated robust performance with a concordance index (c-index) of 0.79 on the test data, surpassing traditional metrics such as TPS and immune marker density-based models (c-index: 0.50 and 0.74, respectively). Beyond assessing performance, we investigated the features learned by the GNN using k-means clustering in the model’s feature space. We identified three clusters that were notably enriched in PD-L1 positive tumor cells. The first cluster shows an especially “high TPS” phenotype, where the GNN predicted such neighborhoods to be generally poor for survival. The other two clusters were additionally enriched with PD-L1 positive immune cells (ICs) and associated with favorable survival predictions. Notably, one cluster was also enriched with other types of ICs (”PD-L1 IC mixed”), which the GNN predicted as especially favorable for survival compared to exclusive enrichment of PD-L1 ICs (”PD-L1 IC dominant”). A score summarizing these three PD-L1 expression patterns was significantly associated with OS (p-value: 0.01; HR: 0.72, 95% CI: 0.16-1.27), validating the features learned by the GNN. In sum, we developed a highly interpretable deep-learning model leveraging cellular neighborhood graphs, which effectively identifies expression patterns correlating with NSCLC prognosis, offering promise for developing personalized treatment strategies. Citation Format: Katharina Viktoria Hoebel, James R. Lindsay, Joao V. Alessi, Jason L. Weirather, Ian D. Dryg, Jennifer Altreuter, Mark M. Awad, Scott J. Rodig, William E. Lotter. Deep-learning model trained on multiplex immunofluorescence-stained tissue samples predicts the survival of patients with non-small cell lung cancer better than PD-L1 TPS alone [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6189.

Abstract 3635: Insulin-like growth factor receptor predicts poor prognosis in early-stage non-small cell lung cancer

Abstract Introduction: Insulin like growth factor receptor (IGF1R) is involved in the proliferation and metastasis of various cancers. However, the clinical significance of IGF1R in non-small cell lung cancer (NSCLC) remains to be unclear. In this study, we retrospectively evaluated the correlation between IGF1R expression and clinicopathological features of NSCLC. Method: A total of 782 specimens of NSCLC patients who underwent surgical resection of primary lung cancer between 2010 and 2019 at Osaka Metropolitan University Hospital was enrolled in this study. Immunohistochemical staining of IGF1R were performed, and the correlation between IGF1R expression and clinicopathological features of NSCLC, especially in recurrence free survival (RFS) and overall survival (OS), was evaluated. We also evaluated an association between IGF1R and programmed death ligand 1 (PD-L1) expression. Results: IGF1R expression was positive in 279 (35.8%) patients. IGF1R-positive group had significantly longer smoking histories (median smoking index, 1,000 vs 600, p &amp;lt;0.01) and a higher proportion of squamous cell carcinomas (35.1% vs 14.1 %, p &amp;lt;0.01). IGF1R-positive group also significantly expressed PD-L1 (24.4% vs 6.4%, p&amp;lt;0.01). IGF1R-positive group had significantly worse RFS (10-year recurrence-free rate; 42.7% vs 53.7%, p &amp;lt;0.01) and OS (10-year survival rate; 54.4% vs 67.3%, p &amp;lt;0.01). RFS and OS were significantly worse in the IGF1R-positive NSCLC patients at stage 0 and stage I (10-year recurrence-free rate; 49.0% vs 62.9%, p &amp;lt;0.01, 10-year survival rate; 57.4% vs 74.2%, p&amp;lt;0.01), but not in stage II (10-year recurrence-free rate; 52.0% vs 43.8%, p=0.68, 10-year survival rate; 63.4% vs 47.5%, p=0.95) and III (10-year recurrence-free rate; 20.7% vs 20.8%, p=0.77, 10-year survival rate; 38.3% vs 54.6%, p=0.18). IGF1R expression was associated with poorer RFS and OS in early-stage NSCLC. Conclusion: IGF1R is a predictor of poor prognosis in resected early-stage NSCLC. Citation Format: Hiroaki nagamine, Masakazu Yashiro, Megumi Mizutani, Akira Sugimoto, Yoshiya Matsumoto, Yoko Tani, Kenji Sawa, Kazuhiro Yamada, Hiroyasu Kaneda, Tetsuya Watanabe, Kazuhisa Asai, Satoshi Suzuki, Tomoya Kawaguchi. Insulin-like growth factor receptor predicts poor prognosis in early-stage non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3635.

Abstract 5426: SMC2 orchestrates non-small cell lung cancer proliferation, invasion, and metastasis by modulating the ERK/AKT/NF-κB pathways

Abstract Chromatin instability has been associated with the expression of structural maintenance of chromosomes (SMC) family members and is a common feature in many tumors. SMC family members have been associated with poor outcomes in several cancer types. However, little is known about their functions and mechanisms in promoting cancer progression, particularly in non-small cell lung cancer (NSCLC). Here, we evaluated the expression of SMC family members in the tumor microenvironment of NSCLC specimens using single-cell RNA sequencing analyses. After a survival analysis, it was found that the sole factor associated with a poor prognosis for NSCLC was member SMC2 expression. Immunohistochemistry was used with data from the Human Protein Atlas, the Cancer Genome Atlas, and the Gene Expression Omnibus databases to confirm the overexpression of SMC2 in NSCLC. We demonstrated that SMC2 regulates not only the fluctuations in the critical states of tumor cells, which are defined by different transcriptome and metabolic properties but also coordinates the immunological components and cell-to-cell communications of the immune milieu, potentially through the pleiotrophin and the Galectin pathways. In vitro and in vivo evidence support the pro-metastatic role of SMC2 in NSCLC. Subsequent investigations showed that SMC2 increases NSCLC progression and metastasis via modulating the ERK/AKT/NF-κB pathway and the epithelial-mesenchymal transition process. Our research clarifies the role and potential mechanisms of SMC2 in NSCLC, providing new treatment options and valuable insights for the management of NSCLC. Citation Format: Yan He, Zhenyu Luo, Yiyao Wang, Shan Xiong, Rui Wan, Xue Zhang, Hua Bai, Jie Wang. SMC2 orchestrates non-small cell lung cancer proliferation, invasion, and metastasis by modulating the ERK/AKT/NF-κB pathways [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5426.

Abstract 4238: ModelingRET-rearranged non-small cell lung cancer (NSCLC): Generation of lung cell progenitors from patient-derived induced pluripotent stem cells (iPSCs)

Abstract Rearranged during Transfection (RET) oncogenic rearrangements can occur in 1-2% of lung adenocarcinomas. While RET-driven NSCLC models have been developed using various approaches, no model based on patient-derived induced pluripotent stem cells (iPSCs) has been described yet. Patient-derived iPSCs hold great promise for disease modeling. However, generating iPSCs with specific oncogenic drivers, like RET rearrangements, presents challenges due to reprogramming efficiency and genotypic variability within tumors. To address this issue, we aimed to generate lung progenitor cells (LPCs) from patient-derived iPSCs carrying the somatic mutation RETC634Y which is commonly associated with hereditary medullary thyroid carcinoma. Additionally, we have established a RETC634Y knock-in iPSC model to validate the effect of this oncogenic mutation during LPC differentiation. We successfully generated LPCs from RETC634Y iPSCs using a 16-days protocol and showed an overexpression of cancer-associated markers as compared to control iPSCs. Transcriptomic analysis revealed a distinct signature of NSCLC tumor repression, suggesting a lung multilineage lung dedifferentiation, along with an upregulated signature associated with RETC634Ymutation potentially linked to poor NSCLC prognosis. These findings were validated using the RETC634Y knock-in iPSC model, highlighting key cancerous targets such as PROM2 and C1QTNF6, known to be associated with poor prognostic outcomes. Furthermore, the LPCs derived from RETC634Y iPSCs exhibited a positive response to the RET inhibitor Pralsetinib, evidenced by the downregulation of the cancer markers. This study provides a novel off-the-shelf iPSC model of RET-driven NSCLC, paving the way for exploring the molecular mechanisms involved in RET-driven NSCLC to study disease progression and to uncover potential therapeutic targets. Citation Format: Paul Marcoux, Jinwook Hwang, Christophe Desterke, Jusuf Imeri, Annelise Bennaceur Griscelli, Ali Turhan. ModelingRET-rearranged non-small cell lung cancer (NSCLC): Generation of lung cell progenitors from patient-derived induced pluripotent stem cells (iPSCs) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4238.

Identification of cellular senescence-associated genes as new biomarkers for predicting the prognosis and immunotherapy response of non-small cell lung cancer and construction of a prognostic model

BackgroundGlobally, lung carcinoma remains the leading cause of death, with its associated morbidity and mortality rates remaining elevated. Despite the slow advancement of treatment, the outlook remains bleak. Cellular senescence represents a halt in the cell cycle, encompassing a range of physiological and pathological activities, along with diverse phenotypic alterations, including variations in secretory phenotype, macromolecular harm, and metabolic disturbances. Research has revealed its vital function in the formation and growth of tumors. This study aimed to examine cellular senescence-related mRNAs linked to the outlook of non-small cell lung cancer (NSCLC) and to formulate a predictive risk framework for NSCLC. MethodsWe acquired the NSCLC expression data from The Cancer Genome Atlas (TCGA) to examine mRNAs linked to cellular senescence. Both single-variable and multiple-variable cox proportion risk assessments were utilized to determine the traits of cellular senescence-related mRNAs linked to NSCLC prognosis. Subsequently, the prognostic model for cellular senescence-related mRNAs was integrated with clinical-pathological characteristics to create a prognostic nomogram. Furthermore, the study delved into the risk-oriented predictive model, examining immune infiltration and responses to immunotherapy among both high and low-risk categories. ResultsUtilizing both univariate and multivariate Cox proportion risk assessments, a risk model comprising 12 mRNAs associated with cellular aging was ultimately developed: IGFBP1, TLR3, WT1, ID1, PTTG1, ERRFI1, HEPACAM, MAP2K3, RAD21, NANOG, PRKCD, SOX5. Univariate analysis and multivariate analysis illustrated that the risk score served as a standalone indicator for prognosis, and the hazard ratio (HR) of the risk score were 1.182 (1.139–1.226) (p < 0.001) and 1.162 (1.119 − 1.206) (p < 0.001), respectively. Individual prognoses were forecasted using nomogram, c-index, and principal component analysis (PCA). Furthermore, the risk-oriented model revealed notable statistical variances in immune infiltration and response to immunotherapy among the high and low risk categories. ConclusionsThis study shows that mRNAs related to cell senescence associated with prognosis are reliable predictors of NSCLC immunotherapy reaction and prognosis.

Inhibition of PD-L1 expression in non-small cell lung cancer may reduce vasculogenic mimicry formation by inhibiting the epithelial mesenchymal transformation process

Non-small cell lung cancer (NSCLC) is a kind of highly malignant tumor. Studies have shown that Vasculogenic mimicry (VM) may be responsible for dismal prognosis in NSCLC. Immunotherapy with programmed death-1 (PD-1) or programmed death ligand-1 (PD-L1) has significantly altered the treatment of assorted cancers, including NSCLC, but its role and mechanism in the formation of Vasculogenic mimicry (VM) in NSCLC remains unclear. This study aimed to investigate the role of the anti-PD-L1 antibody in the formation of VM in NSCLC and its possible mechanisms. The results showed that anti-PD-L1 antibody therapy could inhibit the growth of NSCLC-transplanted tumors and reduce the formation of VMs. In addition, this study found that anti-PD-L1 antibodies could increase the expression of the epithelial-mesenchymal transition (EMT) related factor E-cadherin. zinc finger E-box binding homeobox 1 (ZEB1) is an important transcription factor regulating EMT. Knocking down ZEB1 could significantly inhibit tumor growth, as well as the expression of VE-cadherin and mmp2, while remarkably increase the expression of E-cadherin. During this process, the formation of VM was inhibited by knowing down ZEB1 in both in vitro and in vivo experiments of the constructed ZEB1 knockdown stable transfected cell strains. Therefore, in this study, we found that anti-PD-L1 antibodies may reduce the formation of VMs by inhibiting the EMT process.

RGS20 promotes non-small cell lung carcinoma proliferation via autophagy activation and inhibition of the PKA-Hippo signaling pathway

BackgroundNovel therapeutic targets are urgently needed for treating drug-resistant non-small cell lung cancer (NSCLC) and overcoming drug resistance to molecular-targeted therapies. Regulator of G protein signaling 20 (RGS20) is identified as an upregulated factor in many cancers, yet its specific role and the mechanism through which RGS20 functions in NSCLC remain unclear. Our study aimed to identify the role of RGS20 in NSCLC prognosis and delineate associated cellular and molecular pathways.MethodsImmunohistochemistry and lung cancer tissue microarray were used to verify the expression of RGS20 between NSCLC patients. CCK8 and cell cloning were conducted to determine the proliferation ability of H1299 and Anip973 cells in vitro. Furthermore, Transcriptome sequencing was performed to show enrichment genes and pathways. Immunofluorescence was used to detect the translocation changes of YAP to nucleus. Western blotting demonstrated different expressions of autophagy and the Hippo-PKA signal pathway. In vitro and in vivo experiments verified whether overexpression of RGS20 affect the proliferation and autophagy of NSCLC through regulating the Hippo pathway.ResultsThe higher RGS20 expression was found to be significantly correlated with a poorer five-year survival rate. Further, RGS20 accelerated cell proliferation by increasing autophagy. Transcriptomic sequencing suggested the involvement of the Hippo signaling pathway in the action of RGS20 in NSCLC. RGS20 activation reduced YAP phosphorylation and facilitated its nuclear translocation. Remarkably, inhibiting Hippo signaling with GA-017 promoted cell proliferation and activated autophagy in RGS20 knock-down cells. However, forskolin, a GPCR activator, increased YAP phosphorylation and reversed the promoting effect of RGS20 in RGS20-overexpressing cells. Lastly, in vivo experiments further confirmed role of RGS20 in aggravating tumorigenicity, as its overexpression increased NSCLC cell proliferation.ConclusionOur findings indicate that RGS20 drives NSCLC cell proliferation by triggering autophagy via the inhibition of PKA-Hippo signaling. These insights support the role of RGS20 as a promising novel molecular marker and a target for future targeted therapies in lung cancer treatment.

Predictive impact of sarcopenia in advanced non-small cell lung cancer patients treated with immune checkpoint inhibitors: A retrospective study

BackgroundSarcopenia, characterised by an ongoing loss of skeletal muscle mass and reduced strength and function, is frequently observed in patients with non-small cell lung cancer (NSCLC). However, the relationship between sarcopenia and the prognosis of NSCLC treated with immune checkpoint inhibitors (ICIs) remains unclear. This aimed to assess whether sarcopenia is an independent prognostic factor for survival in patients with advanced NSCLC receiving ICIs. MethodsFor this retrospective cohort study, we analysed the medical records of patients attending our hospital aged 18–75 years who were newly diagnosed with stage IIIB to stage IV NSCLC, and who had received ICIs as first- or second-line therapy between May 2019 and April 2022. The skeletal muscle index (SMI) was calculated from computed tomography (CT) images and relevant clinical characteristics within 4 weeks of initiating treatment and used to diagnose sarcopenia status. The Kaplan-Meier method and log-rank test were used to calculate and compare patients' progression-free survival (PFS). Cox proportional hazard regression was used to examine the associations between sarcopenia and survival outcomes. The chi-square test was used to compare treatment response outcomes, such as the objective response rate (ORR), disease control rate (DCR), and immunotherapy-related adverse events (irAEs), between individuals with and without sarcopenia. Additionally, the Student's t-test was utilised to compare SMI values between patients by their objective response (OR) and disease control (DC). Finally, the Mann-Whitney U test was used to compare nutritional and inflammatory indicators between the sarcopenia groups. ResultsThe study enrolled 70 patients, of whom 34 (48.6%) were diagnosed with sarcopenia. The median PFS of patients with and without sarcopenia was 7.5 vs. 13.4 months, respectively (p = 0.006). The proportional hazards regression analysis showed sarcopenia to be an independent prognostic factor for shorter PFS (hazard ratio (HR): 0.504, 95% CI: 0.265–0.962, p = 0.038). Using chi square tests, we found significant differences in the ORR (20.59% vs. 58.33%, p = 0.001) and occurrence of any irAEs (44.1% vs. 22.2%, p = 0.028) between the sarcopenia and the non-sarcopenia groups, respectively. The Student's t-test showed a significant difference in SMI between the ORR group and the non-ORR group (49.99 ± 7.00 vs. 42.98 ± 2.18 cm2/m2, p = 0.0015). While the sarcopenia group were with significantly a lower CD4+/CD8+ ratios and a higher C-reactive protein (CRP) level (p = 0.026, p = 0.011, respectively). Conclusions: This study found that sarcopenia is a significant predictor of a poor prognosis for patients with advanced NSCLC receiving ICIs. Multiple inflammatory and immune functions related to prognosis also differ by sarcopenia status.

Expression patterns and prognostic role of m6A RNA methylation regulators in Non-small Cell Lung Cancer.

To investigate the expression pattern and prognostic role of m6A RNA methylation regulators in non-small cell lung cancer (NSCLC), we downloaded data from 422 patients from The Cancer Genome Atlas (TCGA) database. The relationship between the expression levels of m6A RNA methylation regulators and clinicopathological variables of NSCLC was analysed using R language. By analysing glioma data in TCGA, we found that a prognostic risk score model could be constructed based on 18 genes with m6A methylation modification. m6A gene alterations were significantly associated with tumour grade and tumour stage. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression models were used to identify 2 m6A RNA methylation modifiers: IFG2BP2, and METTL14 to construct risk profiles. Based on the risk profile, patients were divided into high-risk and low-risk groups. The overall survival rate of the low-risk group was significantly higher than that of the high-risk group. The results suggest that the prognostic risk score model constructed by m6A methylation regulators can predict the prognosis of glioma patients. IFG2BP2 and METTL14 may be the key m6A methylation regulators involved in the development of NSCLC and can be used as the molecular markers for the prognosis of NSCLC.

KEAP1 promotes anti-tumor immunity by inhibiting PD-L1 expression in NSCLC

Immunotherapy has become a prominent first-line cancer treatment strategy. In non-small cell lung cancer (NSCLC), the expression of PD-L1 induces an immuno-suppressive effect to protect cancer cells from immune elimination, which designates PD-L1 as an important target for immunotherapy. However, little is known about the regulation mechanism and the function of PD-L1 in lung cancer. In this study, we have discovered that KEAP1 serves as an E3 ligase to promote PD-L1 ubiquitination and degradation. We found that overexpression of KEAP1 suppressed tumor growth and promoted cytotoxic T-cell activation in vivo. These results indicate the important role of KEAP1 in anti-cancer immunity. Moreover, the combination of elevated KEAP1 expression with anti-PD-L1 immunotherapy resulted in a synergistic effect on both tumor growth and cytotoxic T-cell activation. Additionally, we found that the expressions of KEAP1 and PD-L1 were associated with NSCLC prognosis. In summary, our findings shed light on the mechanism of PD-L1 degradation and how NSCLC immune escape through KEAP1-PD-L1 signaling. Our results also suggest that KEAP1 agonist might be a potential clinical drug to boost anti-tumor immunity and improve immunotherapies in NSCLC.

Factors affecting accuracy of clinical staging in resectable non-small cell lung cancer in a real-world study.

The clinical staging of non-small cell lung cancer (NSCLC) is well known to be related to their prognosis. However, there is usually a discrepancy between clinical staging and pathological staging. There are few analyses of clinical staging accuracy in patients with NSCLC. We compared the concordance rate between clinical and pathological staging of NSCLC and evaluated factors affecting the accuracy in real-world data. Altogether, 811 patients with primary NSCLC who had undergone curative lung resection surgery in Severance Hospital from January 2019 to December 2020 were retrospectively reviewed. We used the eighth edition of the American Joint Committee on Cancer TNM staging. Among 811 patients, endobronchial ultrasound (EBUS) and positron emission tomography (PET-CT) were performed in 31.6% and 96.7%, respectively. The concordance rates between clinical and pathological TNM staging, T factor, and N factor, were 68.7%, 77.7%, and 85.8%, respectively. With multivariable logistic regression analysis, current smokers (OR 0.49; 95% CI: 0.32-0.76, p = 0.001) and a higher clinical stage (p < 0.001) contributed to the clinical staging inaccuracy. Additionally, the presence of a bronchoscopy specialist was significantly associated with clinical staging accuracy (OR 1.53; 95% CI: 1.10-2.13, p = 0.011). Clinical staging accuracy in NSCLC improved compared to before the widespread use of PET-CT and EBUS in clinical staging work-up. Smoking history and absence of expert bronchoscopy specialists showed a meaningful correlation with the inaccuracy of clinical staging. Thus, training more bronchoscopy experts would improve the staging accuracy of NSCLC, which could positively affect the prognosis of NSCLC.

Single-cell and bulk RNA sequencing data jointly reveals VDAC2's impacts on prognosis and immune landscape of NSCLC.

Non-small cell lung cancer (NSCLC) is characterized by stronger metastatic ability and worse prognosis. In NSCLC, hypoxia is a major cause of invasion and metastasis through promoting angiogenesis. In present study, NSCLC cell clusters were extracted from single cell-sequencing dataset GSE131907, which were combined with hypoxia-related genes to group clusters. qRT-PCR and western blot were used to validate the expression of target gene. Nine NSCLC clusters were extracted, which were divided into two hypoxia-related subgroups, C1 and C2. Totally 101 differentially expressed prognostic genes were identified between subgroups. Of which, VDAC2 showed excellent prognostic value for NSCLC and was selected for further analysis. VDAC2 was upregulated in tumor samples in TCGA and was correlated with advanced stages. In vitro experiments validated this trend. Five crucial immune cells showed differential infiltration proportions between high and low VDAC2 expression groups. VDAC2 knockdown significantly inhibited the proliferation and invasion ability of NSCLC cells. Integrating single cell and bulk sequencing data as well as wet lab experiments, hypoxia-related VDAC2 exhibited important prognostic value and showed the promise of becoming immune-therapy target in NSCLC.

The Role and Therapeutic Potential of Non-coding RNAs in Resistance to EGFR-TKIs targeted therapy for Non-small Cell Lung Cancer.

Lung cancer is the leading cause of cancer-related deaths worldwide, of which non-small cell lung cancer (NSCLC) is the most common type, and epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are widely used for the treatment of NSCLC. EGFR-TKIs are known to develop a drug-resistant response after a certain number of cycles of dosing, and how to alleviate or even reverse EGFR-TKI resistance is an urgent problem at present. This review focuses on the role of ncRNAs in the resistance of NSCLC to EGFR-TKIs and the potential mechanisms underlying the development of NSCLC resistance to EGFR-TKIs. NcRNAs are involved in NSCLC resistance to EGFR-TKIs by mediating cellular drug efflux, epithelial-mesenchymal transition, apoptosis, autophagy, and EGFR mutation. ncRNAs play a crucial role in NSCLC resistance to EGFR-TKIs. Hopefully, the results will provide some guidance and help for the treatment and prognosis of NSCLC.

A cuproptosis score model and prognostic score model can evaluate clinical characteristics and immune microenvironment in NSCLC

BackgroundCuproptosis-related genes (CRGs) are associated with lung adenocarcinoma. However, the links between CRGs and non-small-cell lung cancer (NSCLC) are not clear. In this study, we aimed to develop two cuproptosis models and investigate their correlation with NSCLC in terms of clinical features and tumor microenvironment.MethodsCRG expression profiles and clinical data from NSCLC and normal tissues was obtained from GEO (GSE42127) and TCGA datasets. Molecular clusters were classified into three patterns based on CRGs and cuproptosis cluster-related specific differentially expressed genes (CRDEGs). Then, two clinical models were established. First, a prognostic score model based on CRDEGs was established using univariate/multivariate Cox analysis. Then, through principal component analysis, a cuproptosis score model was established based on prognosis-related genes acquired via univariate analysis of CRDEGs. NSCLC patients were divided into high/low risk groups.ResultsEighteen CRGs were acquired, all upregulated in tumor tissues, 15 of which significantly (P < 0.05). Among the three CRG clusters, cluster B had the best prognosis. In the CRDEG clusters, cluster C had the best survival. In the prognostic score model, the high-risk group had worse prognosis, higher tumor mutation load, and lower immune infiltration while in the cuproptosis score model, a high score represented better survival, lower tumor mutation load, and high-level immune infiltration.ConclusionsThe cuproptosis score model and prognostic score model may be associated with NSCLC prognosis and immune microenvironment. These novel findings on the progression and immune landscape of NSCLC may facilitate the provision of more personalized immunotherapy interventions for NSCLC patients.

Converging survival trends in non-small cell lung cancer patients with and without brain metastasis receiving state-of-the-art treatment

IntroductionHistorically, patients with brain metastasis (BM) have been excluded from clinical trials investigating treatments for non-small cell lung cancer (NSCLC) due to their unfavorable prognosis. Advanced treatments have increased survival prospects for NSCLC patients with BM. This study evaluated the life expectancy of NSCLC patients with and without BM in the context of contemporary treatments.MethodsOutcome data were collected for patients with advanced NSCLC attending a tertiary medical center between 2015 and 2020. Patients were stratified according to BM status and compared for overall survival (OS) using log-rank and Cox regression analyses.ResultsThe cohort included 360 patients with NSCLC of whom 134 (37.2%) had BM. Most (95%) of cases of BM developed within the first two years: 63% at diagnosis, 18% during the first year, 14% during the second year. There was no significant difference in OS between patients without BM and those with BM (median 23.7 vs. 22.3 months, HR = 0.97, p = 0.82); patients with BM and a targetable or non-targetable mutation (40.2 vs. 31.4 months, HR = 0.93, p = 0.84, and 20.7 vs. 19.87 months, HR = 0.95, p = 0.75, respectively); and patients with symptomatic BM (23.7 vs. 19.8 months, HR = 0.95, p = 0.78). Treatment for BM (95% of patients) consisted of stereotactic radiosurgery or tyrosine kinase inhibitors, with corresponding intracranial control rates of 90% and 86%.ConclusionThe results imply that the presence of BM has no impact on the prognosis of NSCLC. The practice of excluding NSCLC patients with BM from clinical trials warrants reconsideration.