Prognosis Of Non-small Cell Lung Cancer Patients Research Articles

Deep learning analysis of histopathological images predicts immunotherapy prognosis and reveals tumour microenvironment features in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer mortality worldwide. Immune checkpoint inhibitors (ICIs) have emerged as a crucial treatment option for patients with advanced NSCLC. However, only a subset of patients experience clinical benefit from ICIs. Therefore, identifying biomarkers that can predict response to ICIs is imperative for optimising patient selection. Hematoxylin and eosin (H&E) images of NSCLC patients were obtained from the local cohort (n = 106) and The Cancer Genome Atlas (TCGA) (n = 899). We developed an ICI-related pathological prognostic signature (ir-PPS) based on H&E stained histopathology images to predict prognosis in NSCLC patients treated with ICIs using deep learning. To accomplish this, we employed a modified ResNet model (ResNet18-PG), a widely-used deep learning architecture well-known for its effectiveness in handling complex image recognition tasks. Our modifications include a progressive growing strategy to improve the stability of model training and the use of the AdamW optimiser, which enhances the optimisation process by adjusting the learning rate based on training dynamics. The deep learning model, ResNet18-PG, achieved an area under the receiver operating characteristic curve (AUC) of 0.918 and a recall of 0.995 on the local cohort. The ir-PPS effectively risk-stratified NSCLC patients. Patients in the low-risk group (n = 40) had significantly improved progression-free survival (PFS) after ICI treatment compared to those in the high-risk group (n = 66, log-rank P = 0.004, hazard ratio (HR) = 3.65, 95%CI: 1.75-7.60). The ir-PPS demonstrated good discriminatory power for predicting 6-month PFS (AUC = 0.750), 12-month PFS (AUC = 0.677), and 18-month PFS (AUC = 0.662). The low-risk group exhibited increased expression of immune checkpoint molecules, cytotoxicity-related genes, an elevated abundance of tumour-infiltrating lymphocytes, and enhanced activity in immune stimulatory pathways. The ir-PPS signature derived from H&E images using deep learning could predict ICIs prognosis in NSCLC patients. The ir-PPS provides a novel imaging biomarker that may help select optimal candidates for ICIs therapy in NSCLC.

Serum Exosomal MiR-874 as a Potential Biomarker for Nonsmall Cell Lung Cancer Diagnosis and Prognosis

AbstractLung cancer, primarily nonsmall cell lung cancer (NSCLC), is a leading cause of cancer-related fatalities globally. Due to late detection, the 5-year survival rate for NSCLC remains low. Therefore, the current research aimed to assess the diagnostic and prognostic value of serum exosomal miR-874 levels in NSCLC patients. This study involved 161 NSCLC patients and 80 control subjects. Blood samples were collected from all participants, and serum exosomal MiR-874 levels were quantified using quantitative reverse transcription-polymerase chain reaction. The study revealed a significant decrease in MiR-874 levels among NSCLC patients compared to controls. The receiver operating characteristic analysis demonstrated the diagnostic value of serum exosomal MiR-874 in effectively distinguishing NSCLC patients from controls.Furthermore, associations were observed between serum exosomal MiR-874 expression and adverse clinical factors such as young age, male sex, smoking, high tumor grade, squamous cell carcinoma histopathology, advanced tumor stage, and lymphatic involvement. Patients with high levels of MiR-874 had significantly longer overall and disease-free survival compared to those with lower levels. The study demonstrates that levels of serum exosomal miR-874 are considerably lower in NSCLC patients, indicating its potential as a diagnostic biomarker. The study's findings suggest that the expression of MiR-874 may predict the prognosis of NSCLC patients based on clinical features.

ABCG2 Gene Expression in Non-Small Cell Lung Cancer.

Background/Objectives: ATP-binding cassette subfamily G member 2 [ABCG2/breast cancer resistance protein (BCRP)] contributes to mechanisms of multidrug resistance (MDR) and is a marker of side population (SP) cells in human cancers. The primary objective of this study was to investigate the impact of ABCG2 gene expression on the non-small cell lung cancer (NSCLC) development, course of cancer disease, and patient prognosis using publicly available data. Obtained results were supplemented with assessment of ABCG2 expression in blood of NSCLC patients. Methods: The dataset of lung cancer was analyzed utilizing the TIMER 2.0, UALCAN, TNMplot, MEXPRESS, cBioPortal, MethSurv, KM Plotter, STRING, and ShinyGO 0.80 databases. Blood samples from 50 patients were assessed using the real-time PCR method. Results: The ABCG2 gene was expressed at a low level in NSCLC, and did not correlate with clinical aggressiveness of lung cancer. Higher ABCG2 expression improved overall survival, but only in LUAD. In addition, CpG sites located on the CpG island affecting the NSCLC patient's prognosis were indicated. In the case of our own laboratory results, the study did not reveal any changes in the ABCG2 expression levels in blood collected from patients at different time points during the diagnostic-therapeutic procedure. In the in silico analysis, most ABCG2 protein interactors were associated with the development of drug resistance. Conclusions: ABCG2 appears to have a particularly significant impact on the survival of patients with lung cancer and on the effect of immunotherapy related to immune cell infiltration. Presented findings may support personalized medicine strategies based on bioinformatics findings.

Multiregional transcriptomic profiling provides improved prognostic insight in localized non-small cell lung cancer

Lung Cancer remains the leading cause of cancer deaths in the USA and worldwide. Non-small cell lung cancer (NSCLC) harbors high transcriptomic intratumor heterogeneity (RNA-ITH) that limits the reproducibility of expression-based prognostic models. In this study, we used multiregional RNA-seq data (880 tumor samples from 350 individuals) from both public (TRACERx) and internal (MDAMPLC) cohorts to investigate the effect of RNA-ITH on prognosis in localized NSCLC at the gene, signature, and tumor microenvironment levels. At the gene level, the maximal expression of hazardous genes (expression negatively associated with survival) but the minimal expression of protective genes (expression positively associated with survival) across different regions within a tumor were more prognostic than the average expression. Following that, we examined whether multiregional expression profiling can improve the performance of prognostic signatures. We investigated 11 gene signatures collected from previous publications and one signature developed in this study. For all of them, the prognostic prediction accuracy can be significantly improved by converting the regional expression of signature genes into sample-specific expression with a simple function—taking the maximal expression of hazardous genes and the minimal expression of protective genes. In the tumor microenvironment, we found a similar rule also seems applicable to immune ITH. We calculated the infiltration levels of major immune cell types in each region of a sample based on expression deconvolution. Prognostic analysis indicated that the region with the lowest infiltration level of protective or highest infiltration level of hazardous immune cells determined the prognosis of NSCLC patients. Our study highlighted the impact of RNA-ITH on the prognostication of NSCLC, which should be taken into consideration to optimize the design and application of expression-based prognostic biomarkers and models. Multiregional assays have the great potential to significantly improve their applications to prognostic stratification.

Exploring the impact of HDL and LMNA gene expression on immunotherapy outcomes in NSCLC: a comprehensive analysis using clinical & gene data.

Analyzing the impact of peripheral lipid levels on the efficacy of immune checkpoint inhibitor therapy in non-small cell lung cancer (NSCLC) patient populations and exploring whether it can serve as a biomarker for broadening precise selection of individuals benefiting from immunotherapy. We retrospectively collected clinical data from 201 cases of NSCLC patients receiving immune checkpoint inhibitor therapy. The clinical information included biochemical indicators like total cholesterol, triglycerides, high-density lipoprotein (HDL), and low-density lipoprotein (LDL). We utilized machine learning algorithms and Cox proportional hazards regression models to investigate independent predictors for both short-term and long-term efficacy of immunotherapy. Additionally, we concurrently developed a survival prediction model. Analyzing the Genes of Patients with Treatment Differences to Uncover Mechanisms. Correlation analysis revealed a significant positive association between HDL and ORR, DCR, and PFS. T-test results indicated that the high-HDL group exhibited higher DCR (81.97% vs. 45.57%) and ORR (61.48% vs. 16.46%). Kruskal-Wallis test showed that the high-HDL group had a longer median PFS (11 months vs. 6 months). Utilizing six machine learning algorithms, we constructed models to predict disease relief and stability. The model built using the random forest algorithm demonstrated superior performance, with AUC values of 0.858 and 0.802. Furthermore, both univariate and multivariate Cox analyses identified HDL and LDL as independent risk factors for predicting PFS. In patients with poor immunotherapy response, there is upregulation of BCL2L11, AKT1, and LMNA expression. HDL and LDL are independent factors influencing the survival prognosis of NSCLC patients undergoing immune checkpoint inhibitor therapy. HDL is expected to become new biomarkers for predicting the immunotherapy efficacy in patients with NSCLC. In patients with poor immunotherapy response, upregulation of the LMNA gene leads to apoptosis resistance and abnormal lipid metabolism.

SLC12A8 promotes the migration and invasion of non-small cell lung cancer (NSCLC) cells.

This study aims to investigate the impacts of SLC12A8 on the invasion, migration, and epithelial-mesenchymal transition (EMT) of non-small cell lung cancer (NSCLC) cells. GEPIA database was employed to examine SLC12A8 expression pattern in lung cancer cells. Subsequently, qRT-PCR and Western blot analyses were conducted to assess SLC12A8 expression in NSCLC tissues and cell lines. The overall prognosis of NSCLC patients was evaluated using Kaplan-Meier plot and univariate and multivariate COX regression curves. The knockdown of SLC12A8 was established using lentivirus-mediated shRNA in A549 and H1299 cells. Cell proliferation, invasion, migration, and apoptosis were evaluated using CCK-8 assay, transwell, and flow cytometry techniques, respectively. Western blot analysis was performed to measure the expression levels of EMT-related proteins (E-cadherin and vimentin). The expression level of SLC12A8 was found to be significantly higher in both NSCLC cell lines and tissues. High SLC12A8 expression was correlated with a poor prognosis in NSCLC patients. Knocking down SLC12A8 led to a significant decrease in proliferation, migration, and invasion abilities, while promoting apoptosis in NSCLC cells. Additionally, SLC12A8 knockdown resulted in decreased levels of N-cadherin and vimentin, along with increased E-cadherin expression. The results indicate that reducing SLC12A8 expression may suppress the malignant phenotype of NSCLC cells, as well as the EMT. SLC12A8 may serve as a target for the clinical management of NSCLC progression.

Potential Impact of Omega 6/3 Ratio and CD68+ Macrophage Infiltration on Survival in NSCLC Patients Undergoing Pulmonary Resection.

Background: Lung cancer remains the leading cause of cancer-related mortality worldwide with non-small cell lung cancer (NSCLC) accounting for the majority of cases. The stage of detection significantly influences survival rates with early-stage diagnosis offering the best prognosis. This study investigates the prognostic impact of the omega-6/omega-3 ratio and tumor infiltration by CD8+ lymphocytes and CD68+ macrophages on overall survival (OS) and disease-free survival (DFS) in NSCLC patients undergoing pulmonary resection. Methods: We conducted a retrospective analysis of 53 patients with early-stage NSCLC who underwent pulmonary resection between September 2017 and January 2020. The omega-6/omega-3 ratio was quantified using gas chromatography and spectrometry. Tumor infiltration by CD8 and CD68 was assessed through immunohistochemistry. Survival outcomes were evaluated using Kaplan-Meier and Cox regression analyses. Results: An increased omega-6/omega-3 ratio and higher CD68+ macrophage infiltration were associated with a trend towards worse OS and DFS in NSCLC patients, though these results did not reach statistical significance. CD8+ T-cell infiltration was associated with improved survival outcomes, confirming its role as a favorable prognostic marker. Comparative analysis with existing datasets revealed similar demographic and clinical characteristics, reinforcing the generalizability of our findings. Conclusions: The omega-6/omega-3 ratio and CD68+ macrophage infiltration serve as important factors potentially influencing prognosis in NSCLC patients undergoing pulmonary resection. These findings highlight the need for further research to refine the prognostic utility of these biomarkers and to explore therapeutic strategies targeting inflammation and immune cell infiltration.

Two-polarized roles of transcription factor FOSB in lung cancer progression and prognosis: dependent on p53 status

BackgroundActivator protein-1 (AP-1) represents a transcription factor family that has garnered growing attention for its extensive involvement in tumor biology. However, the roles of the AP-1 family in the evolution of lung cancer remain poorly characterized. FBJ Murine Osteosarcoma Viral Oncogene Homolog B (FOSB), a classic AP-1 family member, was previously reported to play bewilderingly two-polarized roles in non-small cell lung cancer (NSCLC) as an enigmatic double-edged sword, for which the reasons and significance warrant further elucidation.Methods and ResultsBased on the bioinformatics analysis of a large NSCLC cohort from the TCGA database, our current work found the well-known tumor suppressor gene TP53 served as a key code to decipher the two sides of FOSB – its expression indicated a positive prognosis in NSCLC patients harboring wild-type TP53 while a negative one in those harboring mutant TP53. By constructing a panel of syngeneically derived NSCLC cells expressing p53 in different statuses, the radically opposite prognostic effects of FOSB expression in NSCLC population were validated, with the TP53-R248Q mutation site emerging as particularly meaningful. Transcriptome sequencing showed that FOSB overexpression elicited diversifying transcriptomic landscapes across NSCLC cells with varying genetic backgrounds of TP53 and, combined with the validation by RT-qPCR, PREX1 (TP53-Null), IGFBP5 (TP53-WT), AKR1C3, and ALDH3A1 (TP53-R248Q) were respectively identified as p53-dependent transcriptional targets of FOSB. Subsequently, the heterogenous impacts of FOSB on the tumor biology in NSCLC cells via the above selective transcriptional targets were confirmed in vitro and in vivo. Mechanistic investigations revealed that wild-type or mutant p53 might guide FOSB to recognize and bind to distinct promoter sequences via protein-protein interactions to transcriptionally activate specific target genes, thereby creating disparate influences on the progression and prognosis in NSCLC.ConclusionsFOSB expression holds promise as a novel prognostic biomarker for NSCLC in combination with a given genetic background of TP53, and the unique interactions between FOSB and p53 may serve as underlying intervention targets for NSCLC.

Targeting Nrf2/PHKG2 axis to enhance radiosensitivity in NSCLC

While ferroptosis shows promise in anti-cancer strategy, the molecular mechanisms behind this process remain poorly understood. Our research aims to highlight the regulation of radiotherapy-induced ferroptosis in non-small cell lung cancer (NSCLC) via the NRF2/PHKG2 axis-mediated mechanism. To identify ferroptosis-associated genes associated with radioresistance in NSCLC, this study employed high-throughput transcriptome sequencing and Lasso risk regression analysis. Clinical samples were analyzed to confirm PHKG2 expression changes before and after radiotherapy. The study further examined ferritinophagy-related factors, intracellular iron levels, mitochondrial function, and ferroptosis in NSCLC cells undergoing radiation exposure to explore the effect of PHKG2 on radiosensitivity or radioresistance. The research also demonstrated the transcriptional inhibition of PHKG2 by NRF2 and created in situ transplantation tumor models of NSCLC to examine the role of NRF2/PHKG2 axis in NSCLC radiosensitivity and resistance in vivo. The Lasso risk regression model that incorporated ferroptosis-associated genes effectively predicted the prognosis of patients with NSCLC. Radiotherapy-sensitive tissues exhibited an increased expression of PHKG2. Overexpression of PHKG2 led to elevated intracellular iron levels by promoting ferritinophagy and increased mitochondrial stress-dependent ferroptosis induced by radiotherapy. PHKG2 transcription repression was achieved through NRF2. The FAGs-Lasso risk regression model can accurately predict the prognosis of NSCLC patients. Targeting Nrf2 upregulates the expression of PHKG2 and reverses radiotherapy resistance in NSCLC by promoting iron autophagy and inducing mitochondrial dysfunction, thereby increasing radiotherapy sensitivity.

A comprehensive meta-analysis of tissue resident memory T cell shaping non-small-cell lung cancer immune microenvironment and patient prognosis.

210 Background: Tissue-resident memory T cells (TRM) are a specialized subset of long-lived memory T cells that reside in peripheral tissues. However, the impact of TRM-related immunosurveillance on the tumor-immune microenvironment (TIME) and tumor progression across various non-small-cell lung cancer (NSCLC) patient populations is yet to be elucidated. Methods: Our comprehensive analysis of multiple independent single-cell and bulk RNA-seq datasets of patient NSCLC samples generated reliable, unique TRM signatures, through which we inferred the abundance of TRM in NSCLC. A machine learning model was developed to prognosticate survival, tested in multiple independent NSCLC cohorts. Model performance was corroborated through Kaplan-Meier survival plots, receiver operating characteristic (ROC) curves, principal component analysis, and t-SNE analyses. Results: We discovered that TRM abundance is consistently positively correlated with CD4+ T helper 1 cells, M1 macrophages, and resting dendritic cells in the TIME. In addition, TRM signatures are strongly associated with immune checkpoint genes and the prognosis of NSCLC patients. A TRM-based machine learning model to predict patient survival was validated and an 18-gene risk score was further developed to effectively stratify patients into low-risk and high-risk categories, wherein patients with high-risk scores had significantly lower overall survival than patients with low-risk. The prognostic value of the risk score was independently validated by the TCGA dataset and multiple independent NSCLC patient datasets. Notably, low-risk NSCLC patients with higher TRM infiltration exhibited enhanced T-cell immunity, nature killer cell activation, and other TIME immune responses related pathways, indicating a more active immune profile benefitting from immunotherapy. However, the TRM signature revealed low TRM abundance and a lack of prognostic association among lung squamous cell carcinoma patients in contrast to adenocarcinoma, indicating that the two NSCLC subtypes are driven by distinct TIMEs. Conclusions: Altogether, this study provides valuable insights into the complex interactions between TRM and TIME and their impact on NSCLC patient prognosis. The development of a simplified 18-gene risk score provides a practical prognostic marker for risk stratification. Keywords: Tissue resident memory T cell, non-small-cell lung cancer, prognosis, tumor immune microenvironment, machine learning.

Combination of anlotinib and second-line chemotherapy as surrogate to reduce immunosuppression in patients with advanced non-small cell lung cancer.

To study the clinical effects of anlotinib combined with second-line chemotherapy (SLC) on immunosuppression in patients with advanced non-small cell lung cancer (NSCLC). In this retrospective study, the medical records of 106 patients with advanced NSCLC admitted to the Lianyungang First People's Hospital from November 2020 to March 2022 were retrospectively analyzed. Amongst 106 patients, 53 patients received second-line single-agent chemotherapy regimens (SLC group), and 53 patients received anlotinib combined with SLC (ASLC group). Prognosis, levels of immune cells and inflammatory cytokine, and adverse reactions were analyzed. Clinical efficacy of the ASLC group was significantly higher than the SLC group (p<0.05). After treatment, patients in the ASLC group exhibited significantly higher levels of CD4+/CD8+ and CD4+ compared to those in the SLC group (p<0.05), while the difference in CD8+ level between the two groups was not statistically significant (p>0.05). After treatment, levels of tumor necrosis factor-α (TNF-α), interleukin-10 (IL-10), interleukin-8 (IL-8), interleukin-6 (IL-6) in the ASLC group were lower compared to the SLC group (p<0.05). In patients with advanced NSCLC, anlotinib combined with SLC is associated with higher levels of immune cells and reduced inflammatory factors. This treatment regimen, thus, can reduce immunosuppression and improve the prognosis of NSCLC patients.

USP32 facilitates non-small cell lung cancer progression via deubiquitinating BAG3 and activating RAF-MEK-ERK signaling pathway

The regulatory significance of ubiquitin-specific peptidase 32 (USP32) in tumor is significant, nevertheless, the biological roles and regulatory mechanisms of USP32 in non-small cell lung cancer (NSCLC) remain unclear. According to our research, USP32 was strongly expressed in NSCLC cell lines and tissues and was linked to a bad prognosis for NSCLC patients. Interference with USP32 resulted in a significant inhibition of NSCLC cell proliferation, migration potential, and EMT development; on the other hand, USP32 overexpression had the opposite effect. To further elucidate the mechanism of action of USP32 in NSCLC, we screened H1299 cells for interacting proteins and found that USP32 interacts with BAG3 (Bcl2-associated athanogene 3) and deubiquitinates and stabilizes BAG3 in a deubiquitinating activity-dependent manner. Functionally, restoration of BAG3 expression abrogated the antitumor effects of USP32 silencing. Furthermore, USP32 increased the phosphorylation level of the RAF/MEK/ERK signaling pathway in NSCLC cells by stabilizing BAG3. In summary, these findings imply that USP32 is critical to the development of NSCLC and could offer a theoretical framework for the clinical diagnosis and management of NSCLC patients in the future.

A comprehensive meta-analysis of tissue resident memory T cells and their roles in shaping immune microenvironment and patient prognosis in non-small cell lung cancer.

Tissue-resident memory T cells (TRM) are a specialized subset of long-lived memory T cells that reside in peripheral tissues. However, the impact of TRM-related immunosurveillance on the tumor-immune microenvironment (TIME) and tumor progression across various non-small-cell lung cancer (NSCLC) patient populations is yet to be elucidated. Our comprehensive analysis of multiple independent single-cell and bulk RNA-seq datasets of patient NSCLC samples generated reliable, unique TRM signatures, through which we inferred the abundance of TRM in NSCLC. We discovered that TRM abundance is consistently positively correlated with CD4+ T helper 1 cells, M1 macrophages, and resting dendritic cells in the TIME. In addition, TRM signatures are strongly associated with immune checkpoint and stimulatory genes and the prognosis of NSCLC patients. A TRM-based machine learning model to predict patient survival was validated and an 18-gene risk score was further developed to effectively stratify patients into low-risk and high-risk categories, wherein patients with high-risk scores had significantly lower overall survival than patients with low-risk. The prognostic value of the risk score was independently validated by the Cancer Genome Atlas Program (TCGA) dataset and multiple independent NSCLC patient datasets. Notably, low-risk NSCLC patients with higher TRM infiltration exhibited enhanced T-cell immunity, nature killer cell activation, and other TIME immune responses related pathways, indicating a more active immune profile benefitting from immunotherapy. However, the TRM signature revealed low TRM abundance and a lack of prognostic association among lung squamous cell carcinoma patients in contrast to adenocarcinoma, indicating that the two NSCLC subtypes are driven by distinct TIMEs. Altogether, this study provides valuable insights into the complex interactions between TRM and TIME and their impact on NSCLC patient prognosis. The development of a simplified 18-gene risk score provides a practical prognostic marker for risk stratification.

UBQLN4 promotes the proliferation and invasion of non-small cell lung cancer cell by regulating PI3K/AKT pathway

BackgroundUbiquilin-4 (UBQLN4), a member of the ubiquilin family, has received limited attention in cancer research to date. Here, we investigated for the first time the functional role and mechanism of UBQLN4 in non-small cell lung cancer (NSCLC).MethodsThe Cancer Genome Atlas (TCGA) database was employed to validate UBQLN4 as a differentially expressed gene. Expression differences of UBQLN4 in NSCLC cells and tissues were assessed using immunohistochemistry (IHC) experiment and western blotting (WB) experiment. Kaplan-Meier analysis was conducted to examine the association between UBQLN4 expression and NSCLC prognosis. Functional analyses of UBQLN4 were performed through cell counting kit-8 (CCK-8), colony formation, and transwell invasion assays. The impact of UBQLN4 on tumor-associated signaling pathways was assessed using the path scan intracellular signaling array. In vivo tumorigenesis experiments were conducted to further investigate the influence of UBQLN4 on tumor formation.ResultsUBQLN4 exhibited up-regulation in both NSCLC tissues and cells. Additionally, over-expression of UBQLN4 was associated with an unfavorable prognosis in NSCLC patients. Functional loss analyses demonstrated that inhibiting UBQLN4 could suppress the proliferation and invasion of NSCLC cells in both in vitro and in vivo settings. Conversely, functional gain experiments yielded opposite results. Path scan intracellular signaling array results suggested that the role of UBQLN4 is associated with the PI3K/AKT pathway, a correlation substantiated by in vitro and in vivo tumorigenesis experiments.ConclusionWe validated that UBQLN4 promotes proliferation and invasion of NSCLC cells by activating the PI3K/AKT pathway, thereby facilitating the progression of NSCLC. These findings underscore the potential of targeting UBQLN4 as a therapeutic strategy for NSCLC.

The COP9 signalosome stabilized MALT1 promotes Non-Small Cell Lung Cancer progression through activation of NF-κB pathway

MALT1 has been implicated as an upstream regulator of NF-κB signaling in immune cells and tumors. This study determined the regulatory mechanisms and biological functions of MALT1 in non-small cell lung cancer (NSCLC). In cell culture and orthotopic xenograft models, MALT1 suppression via gene expression interference or protein activity inhibition significantly impaired malignant phenotypes and enhanced radiation sensitivity of NSCLC cells. CSN5, the core subunit of COP9 signalosome, was firstly verified to stabilize MALT1 via disturbing the interaction with E3 ligase FBXO3. Loss of FBXO3 in NSCLC cells reduced MALT1 ubiquitination and promoted its accumulation, which was reversed by CSN5 interference. An association between CSN5/FBXO3/MALT1 regulatory axis and poor prognosis in NSCLC patients was identified. Our findings revealed the detail mechanism of continuous MALT1 activation in NF-κB signaling, highlighting its significance as predictor and potential therapeutic target in NSCLC.Graphical

Increasing serum complement component 1q is associated with worse prognosis in advanced non-small cell lung cancer treated with immune checkpoint inhibitors: a single-center, retrospective study.

There is a lack of readily available clinical markers of non-small cell lung cancer (NSCLC) immunotherapy efficacy. Previous studies have found that overexpressed complement component 1q (C1q) promotes macrophage M2 polarization and an immunosuppressive tumor microenvironment. This study aimed to evaluate the association between serum C1q and the efficacy of immune checkpoint inhibitors (ICIs) in patients with advanced NSCLC. A total of 168 patients with advanced NSCLC who received ICIs in the Renmin Hospital of Wuhan University were included in this study. Serum C1q levels were collected before and 3 weeks after immunotherapy treatment, together with other data on clinical and demographic characteristics. The primary outcome was overall survival (OS) (months from first dose of ICIs to death, censored at date of last follow-up). Secondary outcome was progression-free survival (PFS) [defined as months from first dose of ICIs to clinical or radiographic progression by Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) or death, censored at date of last follow-up] and objective response rate (ORR) which was defined as rate of complete response (CR) or partial response (PR) at best response by RECIST 1.1. A total of 168 patients were included in this study, including 127 males (75.60%) and 41 females (24.40%). Thirty-nine patients achieved objective response (2 CR, 37 PR), and 111 patients (66.07%) had stable disease (SD) as best response. The ORR was 23.21% and the disease control rate was 89.28%. The upward trends of serum C1q levels between baseline and post-treatment were strongly associated with the shorter PFS [hazard ratio (HR) =1.554, 95% confidence interval (CI): 1.07-2.10, P=0.01] and OS (HR =1.444, 95% CI: 1.01-1.98, P=0.03). Moreover, taking the median OS 18.9 months as the cut-off of prognosis, receiver operating characteristic (ROC) analysis showed that serum baseline C1q yielded an area under the ROC curve of 0.785 (95% CI: 0.711-0.869). The optimal serum baseline C1q cut-off point to predict immunotherapy prognosis was 216.2 mg/L. These findings suggested that elevated serum C1q after ICIs treatment was related to a worse prognosis in NSCLC. Monitoring the baseline and dynamic data of C1q during hospitalization showed the potential to predict the prognosis of NSCLC patients.

Use of selpercatinib in a patient with &lt;i&gt;RET&lt;/i&gt;-mutated non-small cell lung cancer: case report

Background. The use of the modern targeted drugs in patients with non-small-cell lung cancer (NSCLC) with certain somatic alterations (genetic alterations in EGFR, ALK, ROS1, BRAF, RET genes, etc.) provides a significant increase in overall and disease-free survival with an acceptable toxicity profile. The use of RET inhibitors, such as selpercatinib, has significantly improved prognosis in NSCLC patients with RET gene translocation, since chemotherapy and immunotherapy in this cohort of patients are ineffective options. The RET gene translocation occurs rarely (2–3 % of cases among lung adenocarcinoma), but detection of this genetic alteration with subsequent administration of targeted therapy significantly improves the prognosis of the disease. Case report. We present a clinical case of the efficacy of targeted therapy with selpercatinib in a 60-year-old patient with RET-positive NSCLC. Methods to eliminate toxicity after selpercatinib therapy and therapy response are described. Results. Second-line selpercatinib therapy resulted in partial response in our patient with lung adenocarcinoma and the presence of translocation in RET gene. Adverse effects from targeted therapy were minimized or eliminated by the use of concomitant therapy, temporary cancellation of targeted therapy with subsequent dose reduction and gradual return to full therapeutic doses. Conclusion. This case demonstrates the high significance and importance of genetic testing in patients with lung adenocarcinoma not only for the most common mutations, but also for rarer somatic alterations, such as translocation in the RET gene. Detection of this translocation and subsequent administration of appropriate targeted therapy significantly improves the prognosis of patients.

Cuproptosis-related gene LIPT1 as a prognostic indicator in non-small cell lung cancer: Functional involvement and regulation of ATOX1 expression.

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related deaths, necessitating a deeper understanding of novel cell death pathways like cuproptosis. This study explored the relevance of cuproptosis-related genes in NSCLC and their potential prognostic significance. We analyzed the expression of 16 cuproptosis-related genes in 1017 NSCLC tumors and 578 Genotype-Tissue Expression (GTEx) normal samples from The Cancer Genome Atlas (TCGA) to identify significant genes. A risk model and prognostic nomogram were employed to identify the pivotal prognostic gene. Further in vitro experiments were conducted to investigate the functions of the identified genes in NSCLC cell lines. LIPT1, a gene for lipoate-protein ligase 1 enzyme, emerged as the central prognostic gene with decreased expression in NSCLC. Importantly, elevated LIPT1 levels were associated with a favorable prognosis for NSCLC patients. Overexpression of LIPT1 inhibited cell growth and enhanced apoptosis in NSCLC. We confirmed that LIPT1 downregulates the copper chaperone gene antioxidant 1 (ATOX1), thereby impeding NSCLC progression. Our study identified LIPT1 as a valuable prognostic biomarker in NSCLC as it elucidates its tumor-inhibitory role through the modulation of ATOX1. These findings offered insights into the potential therapeutic targeting of LIPT1 in NSCLC, contributing to a deeper understanding of this deadly disease.

The value of lung function assessment and Testin expression detection in clinicopathological features and prognosis of NSCLC patients.

The aim of this study is to investigate the clinical value and potential prognostic significance of lung function assessment and Testin expression in non-small cell lung cancer (NSCLC) patients. The NSCLC patients were classified into three groups according to lung function: group of normal lung function, group of PRISm (preserved ratio impaired spirometry) (FEV1, forced expiratory volume during the first second < 80% predicted and FEV1/FVC (forced vital capacity) ≥ 70%) and group of COPD (chronic obstructive pulmonary disease) (FEV1/FVC < 70%). The pre-operational clinicopathological characteristics of these patients were recorded and the markers of systemic inflammatory response, including neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), platelet to lymphocyte ratio (PLR) and eosinophils (EOS), were compared between three groups. The expression of Testin in NSCLC samples was detected by IHC and we further explored the correlation between Testin expression and clinicopathological characteristics and prognosis of NSCLC patients. Finally, Cox regression analysis was conducted to study the prognostic factors of NSCLC patients. Of the 158 NSCLC patients, percentages of normal lung function, PRISm and COPD were 41.4%, 22.8% and 36.1%, respectively. Patients with tumor in the left lung were more likely to have pulmonary dysfunction (PRISm and COPD) than the right lung. The markers of systemic inflammatory response showed differences to various degree in the three groups and NSCLC patients with PRISm or COPD presented more unfavorable prognosis than patients with normal function. The expression of Testin correlated with lymph node metastasis, TNM stage and tumor invasion of NSCLC patients. Moreover, patients with low Testin expression exhibited poorer disease-free survival and overall survival than those with high Testin expression. In Cox regression analysis, we found that PRISm, COPD and Testin expression served as prognostic factors in NSCLC patients. The presence of COPD or PRISm influenced systemic inflammatory response and prognosis of NSCLC patients. Testin expression correlated with clinicopathological features and could be potentially used as a prognostic marker in NSCLC.

HERC5 downregulation in non-small cell lung cancer is associated with altered energy metabolism and metastasis

BackgroundMetastasis is the leading cause of cancer-related death in non-small cell lung cancer (NSCLC) patients. We previously showed that low HERC5 expression predicts early tumor dissemination and a dismal prognosis in NSCLC patients. Here, we performed functional studies to unravel the mechanism underlying the “metastasis-suppressor” effect of HERC5, with a focus on mitochondrial metabolism pathways.MethodsWe assessed cell proliferation, colony formation potential, anchorage-independent growth, migration, and wound healing in NSCLC cell line models with HERC5 overexpression (OE) or knockout (KO). To study early tumor cell dissemination, we used these cell line models in zebrafish experiments and performed intracardial injections in nude mice. Mass spectrometry (MS) was used to analyze protein changes in whole-cell extracts. Furthermore, electron microscopy (EM) imaging, cellular respiration, glycolytic activity, and lactate production were used to investigate the relationships with mitochondrial energy metabolism pathways.ResultsUsing different in vitro NSCLC cell line models, we showed that NSCLC cells with low HERC5 expression had increased malignant and invasive properties. Furthermore, two different in vivo models in zebrafish and a xenograft mouse model showed increased dissemination and metastasis formation (in particular in the brain). Functional enrichment clustering of MS data revealed an increase in mitochondrial proteins in vitro when HERC5 levels were high. Loss of HERC5 leads to an increased Warburg effect, leading to improved adaptation and survival under prolonged inhibition of oxidative phosphorylation.ConclusionsTaken together, these results indicate that low HERC5 expression increases the metastatic potential of NSCLC in vitro and in vivo. Furthermore, HERC5-induced proteomic changes influence mitochondrial pathways, ultimately leading to alterations in energy metabolism and demonstrating its role as a new potential metastasis suppressor gene.