Lung Cancer Tissues Research Articles

EZH2 G553C significantly increases the risk of brain metastasis from lung cancer due to salt bridge instability

BackgroundThe incidence and mortality of lung cancer is the highest in China and the world. Brain is the most common distant metastasis site of lung cancer. Its transfer mechanism and predictive biomarkers are still unclear. EZH2 participates in the catalysis of transcriptional inhibition complex, mediates chromatin compactness, leads to the silencing of its downstream target genes, participates in the silencing of multiple tumor suppressor genes, and is related to cell proliferation, apoptosis and cycle regulation. In physiology, EZH2 has high activity in stem cells or progenitor cells, inhibits genes related to cell cycle arrest and promotes self-renewal. To detect the expression and mutation of EZH2 gene in patients with brain metastasis of lung cancer, and provide further theoretical basis for exploring the pathogenesis of brain metastasis of lung cancer and finding reliable biomarkers to predict brain metastasis of lung cancer.MethodsThis study investigated susceptible genes for brain metastasis of lung cancer. The second-generation sequencing technology was applied to screen the differential genes of paired samples (brain metastasis tissues, lung cancer tissues and adjacent tissues) of lung cancer patients with brain metastasi.ResultsIt revealed that there was a significant difference in the G553C genotype of EZH2 between lung cancer brain metastasis tissues and lung cancer tissues (p = 0.045). The risk of lung cancer brain metastasis in G allele carriers was 2.124 times higher than that in C allele carriers. Immunohistochemistry showed that compared with lung cancer patients and lung cancer patients with brain metastasis, the expression level of EZH2 in lung cancer tissues of lung cancer patients was significantly higher than that in adjacent lung tissues (p < 0.0001), and higher than that in brain metastasis tissues (p = 0.0309). RNA in situ immunohybridization showed that EZH2 mRNA expression was gradually high in lung cancer adjacent tissues, lung cancer tissues and lung cancer brain metastasis tissues.ConclusionsEZH2 G553C polymorphism contributes to the prediction of brain metastasis of lung cancer, in which G allele carriers are more prone to brain metastasis.

Regulatory mechanism and expression level of PRPS2 in lung cancer.

Lung cancer, with high morbidity and mortality, is the commonest respiratory system neoplasm, which seriously endangers the life safety of patients. In this study, the effect of PRPS2 on cell progression was preliminarily investigated. Immunohistochemical staining, western blot and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) were performed to verify the expression level of PRPS2 in lung cancer. Lung cancer cell lines with stable downregulation of PRPS2 were constructed in A549 cells and NCIH460 cells. The function of PRPS2 silencing on the proliferation ability was verified by the EdU and cell colony formation experiment. Scratch and transwell tests were conducted to verify the role of PRPS2 silencing on the migratory and invasive ability of cells. The impact of PRPS2 silencing on cell apoptosis and cell cycle was verified by flow cytometry test. The effects of PRPS2 silencing on apoptosis-associated proteins were assessed by western blot assay. The function of PRPS2 silencing on tumor growth in vivo was studied through xenograft tumor experiment. In comparison with normal tissues, PRPS2 was upregulated in lung cancer tissues. PRPS2 knockdown notably hindered the migratory ability, invasive ability and proliferation, but accelerated cell apoptosis. In vivo experiments confirmed that PRPS2 silencing blocked the growth of transplanted tumors. In lung cancer, PRPS2 silencing suppressed the malignant progression, indicating that PRPS2 might be a novel biomarker for lung cancer treatment and diagnosis.

Acetate reprogrammes tumour metabolism and promotes PD-L1 expression and immune evasion by upregulating c-Myc.

Acetate, a precursor of acetyl-CoA, is instrumental in energy production, lipid synthesis and protein acetylation. However, whether acetate reprogrammes tumour metabolism and plays a role in tumour immune evasion remains unclear. Here, we show that acetate is the most abundant short-chain fatty acid in human non-small cell lung cancer tissues, with increased tumour-enriched acetate uptake. Acetate-derived acetyl-CoA induces c-Myc acetylation, which is mediated by the moonlighting function of the metabolic enzyme dihydrolipoamide S-acetyltransferase. Acetylated c-Myc increases its stability and subsequent transcription of the genes encoding programmed death-ligand 1, glycolytic enzymes, monocarboxylate transporter 1 and cell cycle accelerators. Dietary acetate supplementation promotes tumour growth and inhibits CD8+ T cell infiltration, whereas disruption of acetate uptake inhibits immune evasion, which increases the efficacy of anti-PD-1-based therapy. These findings highlight a critical role of acetate promoting tumour growth beyond its metabolic role as a carbon source by reprogramming tumour metabolism and immune evasion, and underscore the potential of controlling acetate metabolism to curb tumour growth and improve the response to immune checkpoint blockade therapy.

Human epididymis protein 4, a novel potential biomarker for diagnostic and prognosis monitoring of lung cancer.

This study aimed to explore the application value of human epididymis protein 4 (HE4) in diagnosing and monitoring the prognosis of lung cancer. First, TCGA (The Cancer Genome Atlas) databases were used to analyze whey-acidic-protein 4-disulfide bond core domain 2 (WFDC2) gene expression levels in lung cancer tissues. Then, a total of 160 individuals were enrolled, categorized into three groups: the lung cancer group (n = 80), the benign lesions group (n = 40), and the healthy controls group (n = 40). Serum HE4 levels and other biomarkers were quantified using an electro-chemiluminescent immunoassay. Additionally, the expression of HE4 in tissues was analyzed through immunohistochemistry (IHC). In vitro cultures of human airway epithelial (human bronchial epithelial [HBE]) cells and various lung cancer cell lines (SPC/PC9/A594/H520) were utilized to detect HE4 levels via western blot (WB). Analysis of the TCGA and UALCAN (The University of Alabama at Birmingham Cancer Data Analysis Portal) databases showed that WFDC2 gene expression levels were upregulated in lung cancer tissues (p < 0.01). Compared with the control group and the benign group, HE4 was significantly higher in the serum of patients with lung cancer (p < 0.001). Receiver operating characteristic (ROC) analysis confirmed that HE4 had better diagnostic efficacy than classical markers in the differential diagnosis of lung cancer and benign lesions and had the highest diagnostic value in lung adenocarcinoma (area under the ROC curve [AUC] = 0.826). HE4 increased in early lung cancer and positively correlated with poor prognosis (p < 0.001). Moreover, the results of WB and IHC revealed that the expression of HE4 was increased in lung cancer cells (SPC/A549/H520) and lung cancer tissues but decreased in PC9 cells with a lack of exon EGFR19 (p < 0.05). Serum HE4 emerges as a promising novel biomarker for the diagnosis and prognosis assessment of lung cancer.

Role of pyroptosis-related cytokines in the prediction of lung cancer

ObjectivesLung cancer is the leading cause to induce cancer-related mortality. Effective biomarkers for prediction the occurrence of lung cancer is urgently needed. Our previous studies indicated that pyroptosis-related cytokines TNF-α, IFN-γ, MIP-1α, MIP-1β, MIP-2 and IP-10 is important to influence the efficacy of chemotherapy drug in lung cancer tissues. But the role of pyroptosis-related cytokines in prediction the occurrence of lung cancer is still unknown. MethodsBlood samples were collected from 258 lung cancer patients at different stage and 80 healthy volunteers. Serum levels of pyroptosis-related cytokines including TNF-α, IFN-γ, MIP-1α, MIP-1β, MIP-2 and IP-10 were measured by Cytometric Bead Array (CBA). ROC curve was performed to evaluate the cut-off value and diagnosis value for prediction and diagnosis of lung cancer. ResultsCompared with control group, the levels of IP-10, MIP-1α, MIP-1β, MIP-2 and TNF-α were significantly higher in lung cancer patients (45.5 (37.1–56.7): 57.2 (43.0–76.5), 34.4 (21.8–75.2): 115.4 (96.6–191.2), 49.3 (25.6–78.7): 160.5 (124.9–218.6), 22.6 (17.8–31.2): 77.9 (50.1–186.5), 3.80 (2.3–6.2): 10.3 (5.7–16.6)), but the level of IFN-γ was decreased in the patients (12.38 (9.1–27.8): 5.9 (3.5–9.7)). All the above cytokines were significantly associated with the diagnosis of lung cancer, and the AUC values of IFN-γ, IP-10, MIP-1α, MIP-1β, MIP-2, and TNF-α were 0.800, 0.656, 0.905, 0.921, 0.914, and 0.824. And the AUC can rise to 0.986 after combining the above factors, and the sensitivity and specificity also up to 96.7 % and 93.7 %, respectively. Additionally, TNF-α (r = 0.400, P < 0.01), MIP-2 (r = 0.343, P < 0.01), MIP-1α (r = 0.551, P < 0.01) and MIP-1β (r = 0.403, p < 0.01) were positively associated with occurrence of lung cancer, but IFN-γ (r = −0.483, p < 0.01) was negatively associated with occurrence of lung cancer. As far as the potential of early diagnosis of lung cancer, TNF-α (AUC = 0.577), MIP-1α (AUC = 0.804) and MIP-1β (AUC = 0.791) can predict the early stage of lung cancer, and combination of the above three cytokines has a better predictive efficiency (AUC = 0.854). ConclusionOur study establishes a link between the levels of IP-10, MIP-1α, MIP-1β, MIP-2, TNF-α and IFN-γ and diagnosis of lung cancer. Besides, we observed a synergistic effect of these five pyroptosis-related cytokines in diagnosing lung cancer patient, suggesting their potential as biomarkers for lung cancer diagnosis. Moreover, the combination of TNF-α, MIP-1α and MIP-1β are also potential predictors for the early diagnosis of lung cancer.

Single-cell analyzing of tumor microenvironment and cell adhesion between early and late-stage lung cancer

Lung adenocarcinoma (LUAD) is a highly heterogeneous disease that threaten human life with serious incidence and high mortality. High heterogeneity of tumor microenvironment (TME) was reported in multiple studies. However, the factor of controlling the tumor migration progression between eary and late-stage LUAD is still not fully understood. In this study, we conducted a comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data of LUAD obtained from the GEO database. The identification of cell clusters revealed significant expansion of epithelial cells in late-stage patients. Interpretation of the cell-cell communication results between early-stage and late-stage patient samples indicated that early tumor cells may interact with epithelial cells through the TGF-β pathway to promote tumor progression. The cell cycle analysis demonstrated a significant increase in the number of cells in the G2 and M phases in late-stage lung cancer. Further analysis using Non-negative Matrix Factorization (NMF) revealed early-stage cell-specific gene features involved in cell adhesion-related biological processes. Among these, the Tensin (TNS) gene family, particularly TNS1, showed high expression in epithelial cells and fibroblasts of early-stage samples, specifically associated with cell adhesion. Survival analysis using TCGA database for LUAD demonstrated that patients with high expression of TNS1 exhibited significantly higher overall survival rates compared to those with low expression. Immunofluorescence experiments have demonstrated co-expression of TNS1 with fibroblast and tumor cell markers (α-SMA and EPCAM). Immunohistochemistry experiments further validated the significantly higher expression levels of TNS1 in early-stage LUAD tissues compared to late-stage lung cancer tissues (P<0.05). Pathway experiments have shown that early-stage tumor patients with high expression of TNS1 exhibit stronger phosphorylation levels of Akt and mTOR, indicating a more potent activation of the Akt/mTOR signaling pathway. In conclusion, the results of this study demonstrate that TNS1 is an adhesive molecule in the immune microenvironment of early-stage tumor cells, and it may serve as a novel prognostic marker for lug cancer.

The novel DNA methylation marker FIBIN suppresses non-small cell lung cancer metastasis by negatively regulating ANXA2

ObjectivesThe clinical T1 stage solid lung cancer with metastasis is a serious threat to human life and health. In this study, we performed RNA sequencing on T1 advanced-stage lung cancer and adjacent tissues to identify a novel biomarker and explore its roles in lung cancer. MethodsQuantitative reversed-transcription PCR, reverse transcription PCR and Western blot, MSP and Methtarget were utilized to evaluate FIBIN expression levels at both the transcriptional and protein levels as well as its methylation status. Differential target protein was evaluated for relative and absolute quantitation by isobaric tags. Co-IP was performed to detect the interactions between target protein. Precise location and expression levels of target proteins were revealed by immunofluorescence staining and component protein extraction using specific kits, respectively. ResultsWe reported that FIBIN was frequently silenced due to promoter hypermethylation in lung cancer. Additionally, both in vitro and in vivo experiments confirmed the significant anti-proliferation and anti-metastasis capabilities of FIBIN. Mechanistically, FIBIN decreased the nuclear accumulation of β-catenin by reducing the binding activity of GSK3β with ANXA2 while promoting interaction between GSK3β and β-catenin. ConclusionOur findings firstly identify FIBIN is a tumor suppressor, frequently silenced due to promoter hypermethylation. FIBIN may serve as a predictive biomarker for progression or metastasis among early-stage lung cancer patients.

Mogrol-mediated enhancement of radiotherapy sensitivity in non-small cell lung cancer: a mechanistic study.

This study investigated mogrol's impact on non-small cell lung cancer (NSCLC) radiosensitivity and underlying mechanisms, using various methods including assays, bioinformatics, and xenograft models. CCK-8, clonogenic, flow cytometry, TUNEL, and Western blot assays evaluated mogrol and radiation effects on NSCLC viability and apoptosis. Ubiquitin-specific protease 22 (USP22) expression in NSCLC patient tissues was determined by RT-qPCR and Western blot. A xenograft model validated mogrol's effects on tumor growth. Bioinformatics identified four ubiquitin-specific proteases, including USP22, in NSCLC. Kaplan-Meier analysis confirmed USP22's value in lung cancer survival. Human Protein Atlas (HPA) database analysis indicated higher USP22 expression in lung cancer tissues. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis implicated ERK1/2 in NSCLC progression, and molecular docking showed stability between mogrol and ERK1/2. Further in vivo and in vitro experiments have demonstrated that mogrol enhances the inhibitory effect of radiation on NSCLC cell viability and clonogenic capacity. Cell viability and clonogenic capacity are reduced by >50%, and an increase in cellular apoptosis is observed, with apoptotic levels reaching 10%. USP22 expression was significantly elevated in NSCLC tissues, particularly in radiotherapy-resistant patients. Mogrol downregulated USP22 expression by inhibiting the ERK/CREB pathway, lowering COX2 expression. Mogrol also enhanced radiation's inhibition of tumor growth in mice. Mogrol enhances NSCLC radiosensitivity by downregulating USP22 via the ERK/CREB pathway, leading to reduced COX2 expression.NEW & NOTEWORTHY Mogrol enhances non-small cell lung cancer (NSCLC) cell sensitivity to radiotherapy by downregulating USP22 through the ERK/CREB pathway, reducing COX2 expression. These findings highlight mogrol's potential as an adjunct to improve NSCLC radiotherapy and open avenues for further research and clinical applications.

Machine Learning-driven Lung Cancer Detection

Machine Learning-driven Lung Cancer Detection

Adrenergic microenvironment driven by cancer-associated Schwann cells contributes to chemoresistance in patients with lung cancer.

Doublecortin (DCX)-positive neural progenitor-like cells are purported components of the cancer microenvironment. The number of DCX-positive cells in tissues reportedly correlates with cancer progression; however, little is known about the mechanism by which these cells affect cancer progression. Here we demonstrated that DCX-positive cells, which are found in all major histological subtypes of lung cancer, are cancer-associated Schwann cells (CAS) and contribute to the chemoresistance of lung cancer cells by establishing an adrenergic microenvironment. Mechanistically, the activation of the Hippo transducer YAP/TAZ was involved in the acquisition of new traits of CAS and DCX positivity. We further revealed that CAS express catecholamine-synthesizing enzymes and synthesize adrenaline, which potentiates the chemoresistance of lung cancer cells through the activation of YAP/TAZ. Our findings shed light on CAS, which drive the formation of an adrenergic microenvironment by the reciprocal regulation of YAP/TAZ in lung cancer tissues.

STUB1 promotes the degradation of HSPB1 and induces ferroptosis in lung cancer cells.

Lung cancer is a common malignancy characterized by ferroptosis, an iron-dependent form of cell death caused by excessive lipid peroxidation. The disruption of the ubiquitination system plays a crucial role in tumor development and spread. In recent years, there has been increasing interest in utilizing ferroptosis for lung cancer treatment; however, the precise mechanism of how ubiquitination modulates ferroptosis remains unclear. We used databases to analyze STUB1 expression patterns in lung cancer tissues compared to normal tissues and performed immunohistochemistry. The functional role of STUB1 was investigated through gain-of-function and loss-of-function experiments both in vitro and in vivo. Malondialdehyde levels, Fe2+ content, and cell viability assays were employed to evaluate ferroptosis status. Downstream targets of STUB1 were identified through screening and validated using immunoprecipitation and ubiquitination assays. Our findings demonstrate that STUB1 is downregulated in lung cancer cells and functions as an inhibitor of their growth and metastasis both in vitro and in vivo while promoting ferroptosis. Mechanistically, STUB1 induces ferroptosis through E3 ligase-dependent degradation of the ferroptosis suppressor HSPB1. Furthermore, our study elucidated the specific types and sites of modification on HSPB1 mediated by STUB1. This research establishes STUB1 as a tumor suppressor influencing proliferation of lung cancer cells as well as the epithelial-mesenchymal transition process associated with it. Importantly, our work highlights the role of STUB1 in ubiquitination-mediated degradation of HSPB1, providing insights for potential treatments for lung cancer.

Tumor-suppressive miR-4732-3p is sorted into fucosylated exosome by hnRNPK to avoid the inhibition of lung cancer progression

BackgroundAberrant fucosylation observed in cancer cells contributes to an augmented release of fucosylated exosomes into the bloodstream, where miRNAs including miR-4732-3p hold promise as potential tumor biomarkers in our pilot study. However, the mechanisms underlying the sorting of miR-4732-3p into fucosylated exosomes during lung cancer progression remain poorly understood.MethodsA fucose-captured strategy based on lentil lectin-magnetic beads was utilized to isolate fucosylated exosomes and evaluate the efficiency for capturing tumor-derived exosomes using nanoparticle tracking analysis (NTA). Fluorescence in situ hybridization (FISH) and qRT-PCR were performed to determine the levels of miR-4732-3p in non-small cell lung cancer (NSCLC) tissue samples. A co-culture system was established to assess the release of miRNA via exosomes from NSCLC cells. RNA immunoprecipitation (RIP) and miRNA pull-down were applied to validate the interaction between miR-4732-3p and heterogeneous nuclear ribonucleoprotein K (hnRNPK) protein. Cell functional assays, cell derived xenograft, dual-luciferase reporter experiments, and western blot were applied to examine the effects of miR-4732-3p on MFSD12 and its downstream signaling pathways, and the impact of hnRNPK in NSCLC.ResultsWe enriched exosomes derived from NSCLC cells using the fucose-captured strategy and detected a significant upregulation of miR-4732-3p in fucosylated exosomes present in the serum, while its expression declined in NSCLC tissues. miR-4732-3p functioned as a tumor suppressor in NSCLC by targeting 3'UTR of MFSD12, thereby inhibiting AKT/p21 signaling pathway to induce cell cycle arrest in G2/M phase. NSCLC cells preferentially released miR-4732-3p via exosomes instead of retaining them intracellularly, which was facilitated by the interaction of miR-4732-3p with hnRNPK protein for selective sorting into fucosylated exosomes. Moreover, knockdown of hnRNPK suppressed NSCLC cell proliferation, with the elevated levels of miR-4732-3p in NSCLC tissues but the decreased expression in serum fucosylated exosomes.ConclusionsNSCLC cells escape suppressive effects of miR-4732-3p through hnRNPK-mediated sorting of them into fucosylated exosomes, thus supporting cell malignant properties and promoting NSCLC progression. Our study provides a promising biomarker for NSCLC and opens a novel avenue for NSCLC therapy by targeting hnRNPK to prevent the "exosome escape" of tumor-suppressive miR-4732-3p from NSCLC cells.

Enhancing lung cancer diagnosis with data fusion and mobile edge computing using DenseNet and CNN

The recent advancements in automated lung cancer diagnosis through the application of Convolutional Neural Networks (CNN) on Computed Tomography (CT) scans have marked a significant leap in medical imaging and diagnostics. The precision of these CNN-based classifiers in detecting and analyzing lung cancer symptoms has opened new avenues in early detection and treatment planning. However, despite these technological strides, there are critical areas that require further exploration and development. In this landscape, computer-aided diagnostic systems and artificial intelligence, particularly deep learning methods like the region proposal network, the dual path network, and local binary patterns, have become pivotal. However, these methods face challenges such as limited interpretability, data variability handling issues, and insufficient generalization. Addressing these challenges is key to enhancing early detection and accurate diagnosis, fundamental for effective treatment planning and improving patient outcomes. This study introduces an advanced approach that combines a Convolutional Neural Network (CNN) with DenseNet, leveraging data fusion and mobile edge computing for lung cancer identification and classification. The integration of data fusion techniques enables the system to amalgamate information from multiple sources, enhancing the robustness and accuracy of the model. Mobile edge computing facilitates faster processing and analysis of CT scan images by bringing computational resources closer to the data source, crucial for real-time applications. The images undergo preprocessing, including resizing and rescaling, to optimize feature extraction. The DenseNet-CNN model, strengthened by data fusion and edge computing capabilities, excels in extracting and learning features from these CT scans, effectively distinguishing between healthy and cancerous lung tissues. The classification categories include Normal, Benign, and Malignant, with the latter further sub-categorized into adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. In controlled experiments, this approach outperformed existing state-of-the-art methods, achieving an impressive accuracy of 99%. This indicates its potential as a powerful tool in the early detection and classification of lung cancer, a significant advancement in medical imaging and diagnostic technology.

Molecular characteristics of non-small cell lung cancer tissue based on quantitative indicators of progesterone receptors expression

Background. Progesterone receptors (PR) are regulators of cell proliferation and therefore can be considered as an aim for targeted medications in the treatment of oncological diseases. At the same time, a quantitative assessment of PR expression in the tissue of non-small cell lung cancer (NSCLC), which has not yet been carried out in other studies, will determine the possibility of using PR modulators for the treatment of this disease and identify the potential category of patients most susceptible to these drugs.Purpose. To characterize NSCLC by quantitative indicators of PR expression and to determine the correlation of clinically significant characteristics of patients and clinical and morphological parameters of a NSCLC tumor with the PR expression to assess the possibility of using PR modulators in the treatment of this disease.Methods. The PR expression in 130 surgical samples of NSCLC was quantified using an immunofluorescence method associated with flow cytometry. Primary antibodies to PR (NBP2-46388) and secondary antibodies conjugated with DyLight650 (ab98729) were used.Results. The expression of progesterone receptors was detected in all the studied tumors; an abnormal distribution of the marker expression level was noted (P=0.01). The mean expression level was 55.3±16.2%, and the median was 57% with a range of 70%, which indicates heterogeneity of PR expression in tumors of different patients. There were no statistically significant differences in the level of PR expression depending on the histotype and stage of NSCLC, as well as on the sex of patients. At the same time, the level of expression and the frequency of overexpression of PR (&gt;67%) in tumors in non-smoking patients are higher than in smokers (P⩽0.02).Conclusion. The high frequency of occurrence and level of PR expression in NSCLC indicate the possible effectiveness of the use of their modulators in the treatment of this disease, especially in non-smoking patients.

Consistency Analysis of Programmed Death Ligand 1 Expression in Non–Small Cell Lung Cancer Between Pleural Effusion and Matched Primary Lung Cancer Tissues by Immunohistochemical Double Staining

In clinical practice, programmed death ligand 1 (PD-L1) detection is prone to nonspecific staining due to the complex cellular composition of pleural effusion smears. In this study, diaminobenzidine (DAB) and 3-amino-9-ethylcarbazole (AEC) immunohistochemistry double staining was performed to investigate PD-L1 expression in tumor cells from malignant pleural effusion (MPE). MPE was considered as a metastasis in non–small cell lung cancer patients; thus, the heterogeneity between metastatic and primary lung cancer was revealed as well. Ninety paired specimens of MPE cell blocks and matched primary lung cancer tissues from non–small cell lung cancer patients were subjected to PD-L1 and thyroid transcription factor-1(TTF-1)/p63 immunohistochemistry double staining. Two experienced pathologists independently evaluated PD-L1 expression using 3 cutoffs (1%, 10%, and 50%). PD-L1 expression in MPE was strongly correlated with that in matched primary lung cancer tissues (R = 0.813; P < .001). Using a 4-tier scale (cutoffs: 1%, 10%, and 50%), the concordance was 71.1% (Cohen’s κ = .534). Using a 2-tier scale, the concordance was 75.6% (1%, Cohen’s κ = 0.53), 78.9% (10%, Cohen’s κ = 0.574), and 95.6% (50%, Cohen’s κ = 0.754). The rates of PD-L1 positivity in MPE (56.7%) were higher than that in lung tissues (32.2%). All 27 discordant cases had higher scores in MPE. The double-staining method provided superior identification of PD-L1-positive tumor cells on a background with nonspecific staining. In conclusion, PD-L1 expression was moderately concordant between metastatic MPE cell blocks and matched primary lung carcinoma tissues, with variability related to tumor heterogeneity. MPE should be considered to detect PD-L1 when histological specimens are unattainable, especially when PD-L1 expression is >50%. PD-L1 positivity rates were higher in MPE. Double staining can improve PD-L1 detection by reducing false-negative/positive results.

PARP1 promotes EGFR-TKI drug-resistance via PI3K/AKT pathway in non-small-cell lung cancer.

Tyrosine kinase inhibitor (TKI) resistance is the main type of drug resistance in lung cancer patients with epidermal growth factor receptor (EGFR) mutations, but its underlying mechanism remains unclear. The purpose of this work was to investigate the mechanism by which PARP1 regulates EGFR-TKI resistance to identify potential targets for combating drug resistance. The GEO databases, TCGA databases, western blot and qPCR studies were used to investigate the expression of PARP1 in lung cancer cells and tissues and its correlation with the prognosis of lung cancer. The expression of PARP1 in lung cancer TKI resistant cell PC9-ER and TKI sensitive cell PC9 was analyzed by qPCR and western blot. After knocking down of PARP1, CCK-8 assays, colony formation, flow cytometry were used to investigate its impact on erlotinib sensitivity, cell survival, cell cycle, and apoptosis. RNA-seq was used to investigate the mechanism by which PARP1 participates in EGFR-TKI resistance, and the results were validated in vitro and in vivo studies. PARP1 was highly expressed in both lung cancer tissues and cells. Subsequently, increased PARP1 expression was observed in PC9-ER compared with its parental cell line. Knockdown of PARP1 increased erlotinib sensitivity, promoted cell apoptosis, and suppressed cell growth. RNA-seq and previous studies have shown that the PI3K/AKT/mTOR/P70S6K pathway is involved in PARP1-mediated TKI resistance, and these results were confirmed by Western blot in vitro and in vivo. PARP1 may serve as a potential therapeutic target for reversing EGFR-TKI resistance in NSCLC via the PI3K/AKT/mTOR/P70S6K pathway.

Delivery of miR-29a improves the permeability of cisplatin by downregulating collagen I expression

In the clinical setting, chemotherapy is the most widely used antitumor treatment, however, chemotherapy resistance significantly limits its efficacy. Reduced drug influx is a key mechanism of chemoresistance, and inhibition of the complexity of the tumor microenvironment (TME) may improve chemotherapy drug influx and therapeutic efficiency. In the current study, we identified that the major extracellular matrix protein collagen I is more highly expressed in lung cancer tissues than adjacent tissues in patients with lung cancer. Furthermore, Kaplan–Meier analysis suggested that COL1A1 expression was negatively correlated with the survival time of patients with lung cancer. Our previous study demonstrated that miR-29a inhibited collagen I expression in lung fibroblasts. Here, we investigated the effect of miR-29a on collagen I expression and the cellular behavior of lung cancer cells. Our results suggest that transfection with miR-29a could prevent Lewis lung carcinoma (LLC) migration by downregulating collagen I expression, but did not affect the proliferation, apoptosis, and cell cycle of LLC cells. In a 3D tumoroid model, we demonstrated that miR-29a transfection significantly increased cisplatin (CDDP) permeation and CDDP-induced cell death. Furthermore, neutral lipid emulsion-based miR-29a delivery improved the therapeutic effect of cisplatin in an LLC spontaneous tumor model in vivo. In summary, this study shows that targeting collagen I expression in the TME contributes to chemotherapy drug influx and improves therapeutic efficacy in lung cancer.

Abstract LB347: PLA2G2D/PGD2-PTGDR signaling deficiency restricts the melanoma progression and lung metastasis

Abstract Normal 0 false false false EN-US KO X-NONE/* Style Definitions */table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0in; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-font-kerning:1.0pt; mso-ligatures:standardcontextual;} Melanoma is a serious form of skin cancer with an approximate incidence more than 160,000 cases and 41,000 melanoma-associated death per annual globally. Malignant Melanoma is more dangerous because of its rapid spread and metastasis if it were not treated at an early stage. The high mortality of malignant melanoma incites an urgent need to refine the current treatments. Phospholipase A2 group IID (PLA2G2D) is an inducible enzyme expressed in myeloid cells, positively associated with immune infiltration through producing anti-inflammatory prostaglandin D2 (PGD2). The aging-related increase of PLA2G2D and PTGDR, a PGD2 receptor, makes them attractive targets for treating aged-related diseases, such as chronic inflammation and cancer diseases. In this study, by using Pla2g2d-/- and Ptgdr-/- mice, we found that PLA2G2D or PTGDR deficiency effectively restricted the in-situ growth and lung metastasis of subcutaneously implanted melanoma B16F10. These benefits are associated with the early enrichment of γδ-T cells in the tumor mass. The activation and accumulation of γδ-T cells can be induced in B16F10-bearing WT mice by the adoptive transfer of Pla2g2d-/- or Ptgdr-/- DCs. Pro-inflammatory characteristics of Pla2g2d-/- or Ptgdr-/- DCs, especially the production of IL-1b, contribute to γδ-T cells recruitment. These tumor-restraining effects were further confirmed in DC-specific PTGDR deficient (zDCcrePtgdrfloxp ) mice. Taken together with the prominent expression of PLA2G2D and PTGDR in human lung cancer tissue, this study demonstrates the potential of PLA2G2D-PGD2/PTGDR signaling-targeted therapy in treating melanoma and lung metastasis. Citation Format: Hima Dhakal, Jian Zheng. PLA2G2D/PGD2-PTGDR signaling deficiency restricts the melanoma progression and lung metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB347.

High CASC expression predicts poor prognosis of lung cancer: A systematic review with meta-analysis.

The long non-coding RNA cancer susceptibility candidate (CASC) has abnormal expression in lung cancer tissues and may correlate with lung cancer prognosis. This study aimed to comprehensively evaluate the association between CASC expression and the cancer prognosis. PubMed, Embase, Web of Science, Google Scholar, Cochrane Library, and China National Knowledge Infrastructure databases were searched until April 1, 2023, to obtain the relevant literature. Studies that met the predefined eligibility criteria were included, and their quality was independently assessed by 2 investigators according to the Newcastle-Ottawa Scale (NOS) score. Detailed information was obtained, such as first author, year of publication, and number of patients. Hazard ratio (HR) with a 95% confidence interval (CI) was extracted and grouped to assess the relationship between CASC expression and cancer prognosis. The dichotomous data was merged and shown as the odds ratio (OR) with a 95% CI was extracted to assess the relationship between CASC expression and clinicopathological parameters. A total of 12 studies with 746 patients with lung cancer were included in the meta-analysis. The expression levels of lncRNA CASC2 and CASC7 were decreased, while those of CASC9, 11, 15, and 19 were induced in lung cancer tissues compared with paracancerous tissues. In the population with low CASC expression (CASC2 and CASC7), high CASC expression indicated a good lung cancer prognosis (HR = 0.469; 95% CI, 0.271-0.668). Conversely, in the population with high CASC expression (CASC9, 11, 15, and 19), high CASC expression predicted a poor lung cancer outcome (HR = 1.910; 95% CI, 1.628-2.192). High CASC expression also predicted worse disease-free survival (DFS) (HR = 2.803; 95% CI, 1.804-6.319). Combined OR with 95% CI revealed an insignificant positive association between high CASC expression and advanced TNM stage (OR = 1.061; 95% CI, 0.775-1.454), LNM (OR = 0.962; 95% CI, 0.724-1.277), tumor size (OR = 0.942; 95% CI, 0.667-1.330), and histological grade (OR = 1.022; 95% CI, 0.689-1.517). The CASC expression levels negatively correlate with lung cancer prognosis. Therefore, CASC expression may serve as a prognostic marker and a potential therapeutic target for lung cancer.

ITGAL expression in non-small-cell lung cancer tissue and its association with immune infiltrates.

Integrin subunit alpha L (ITGAL) encodes an integrin component of LFA-1 and is a membrane receptor molecule widely expressed on leukocytes. It plays a key role in the interaction between white blood cells and other cells. There was a significant correlation between the expression of ITGAL and the tumor microenvironment in a number of cancers. However, experimental studies targeting ITGAL and immune cell infiltration in non-small-cell lung cancer (NSCLC) and the response to immune checkpoint inhibitor therapy are lacking. Data were obtained from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases to explore the relationship between ITGAL expression and prognosis, as well as the immune cell infiltration in patients with NSCLC. In addition, immunohistochemical staining for ITGAL and multiplex immunofluorescence (mIF) staining for ITGAL, CD20, CD68, CD4, and CD8 from tissue microarrays containing 118 tumor tissues and paired paracancerous tissues from patients with NSCLC were performed. The correlation between ITGAL expression and clinical factors, as well as the immunophenotypes of tumor-infiltrating immune cells, were also analyzed. In NSCLC tumor tissues, ITGAL was downregulated compared with matched paracancerous tissues, and low ITGAL expression was associated with a poor prognosis of NSCLC patients. Subsequently, immunohistochemistry results for tissue microarray showed that ITGAL expression was mainly elevated in tumor stroma and areas with highly infiltrated immune cells. ITGAL expression was higher in paracancerous tissues than tumor tissues. Furthermore, mIF results indicated that the patients with ITGAL-high expression tend had significantly higher CD8+ T cells, CD68+ macrophages, CD4+ T cells, and CD20+ B cells infiltration in their tumor tissues. Immunophenotypes were classified into three categories, that is deserted, excluded, and inflamed types, according to each kind of immune cell distribution in or around the cancer cell nest. MIF results showed that ITGAL expression level was correlated with the immunophenotypes. Furthermore, ITGAL expression was associated with the prognosis of NSCLC in patients with immune checkpoint inhibitor therapy and the patients with high ITGAL expression tends have better outcomes. ITGAL may be used as a biomarker for assessing the immune microenvironment in patients with NSCLC.