Type Of Lung Cancer Research Articles

Primary squamous cell carcinoma and adenocarcinoma simultaneously occurring in the same lung lobe: a case report and literature review

The co-occurrence of distinct lung cancer types within the same lobe is an exceedingly rare phenomenon. Here, we present a unique case wherein primary invasive squamous cell carcinoma and invasive adenocarcinoma concurrently manifested in the identical lung lobe. Additionally, we provide a comprehensive overview of the diagnosis and treatment approaches for multiple primary lung cancers, along with highlighting existing challenges based on the most recent guidelines. Our case underscores the importance of sampling each lesion individually, conducting separate diagnostic procedures, and determining the histological subtype for effective treatment planning irrespective of their location or size.

Long non-coding RNA MSL3P1 regulates CUL3 mRNA cytoplasmic transport and stability and promotes lung adenocarcinoma metastasis.

Lung adenocarcinoma (LUAD) is the most prevalent histological type of lung cancer. Previous studies have reported that specific long non-coding RNAs (lncRNAs) are involved in cancer development and progression. The phenotype and mechanism of ENST00000440028, named MSL3P1, a lncRNA which we referring to a cancer-testis gene with potential roles in tumorigenesis and progression, have not been reported. We found that MSL3P1 is overexpressed in LUAD tumor tissues, which is significantly associated with clinical characteristics, metastasis, and poor clinical prognosis. MSL3P1 promotes the metastasis of LUAD in vitro and in vivo. The enhancer reprogramming in LUAD tumor tissue is the major driver of the aberrantly expression of MSL3P1. Mechanistically, due to the competitive binding to CUL3 mRNA with ZFC3H1 protein (a protein involved in targeting polyadenylated RNA to exosomes and promoting the degradation of target mRNA), MSL3P1 can prevent the ZFC3H1-mediated RNA degradation of CUL3 mRNA and transport it to the cytoplasm. This activates the downstream epithelial-to-mesenchymal transition signaling pathway, and promote tumor invasion and metastasis. Implications: This study indicates that lncRNA MSL3P1 regulates CUL3 mRNA stability and promotes the metastasis and holds potential as a prognostic biomarker and therapeutic target in LUAD.

Smoking-induced CCNA2 expression promotes lung adenocarcinoma tumorigenesis by boosting AT2/AT2-like cell differentiation

Lung adenocarcinoma (LUAD), a type of non-small cell lung cancer (NSCLC), originates from not only bronchial epithelial cells but also alveolar type 2 (AT2) cells, which could differentiate into AT2-like cells. AT2-like cells function as cancer stem cells (CSCs) of LUAD tumorigenesis to give rise to adenocarcinoma. However, the mechanism underlying AT2 cell differentiation into AT2-like cells in LUAD remains unknown. We analyze genes differentially expressed and genes with significantly different survival curves in LUAD, and the combination of these two analyses yields 147 differential genes, in which 14 differentially expressed genes were enriched in cell cycle pathway. We next analyze the protein levels of these genes in LUAD and find that Cyclin-A2 (CCNA2) is closely associated with LUAD tumorigenesis. Unexpectedly, high CCNA2 expression in LUAD is restrictedly associated with smoking and independent of other driver mutations. Single-cell sequencing analyses reveal that CCNA2 is predominantly involved in AT2-like cell differentiation, while inhibition of CCNA2 significantly reverses smoking-induced AT2-like cell differentiation. Mechanistically, CCNA2 binding to CDK2 phosphorylates the AXIN1 complex, which in turn induces ubiquitination-dependent degradation of β-catenin and inhibits the WNT signaling pathway, thereby failing AT2 cell maintenance. These results uncover smoking-induced CCNA2 overexpression and subsequent WNT/β-catenin signaling inactivation as a hitherto uncharacterized mechanism controlling AT2 cell differentiation and LUAD tumorigenesis.

Detection of Oncogene Hotspot Mutations in Female NSCLC Tumor DNA and Cell-Free DNA.

Non-small-cell lung cancer (NSCLC) is the most prevalent type of lung cancer, with extensively characterized mutational spectra. Several biomarkers (such as EGFR, BRAF, KRAS gene mutations, etc.) have emerged as predictive and prognostic markers for NSCLC. Unfortunately, the quality of the available tumor biopsy and/or cytology material is not always adequate to perform the necessary molecular testing, prompting the search for alternatives. Cell-free DNA (cfDNA) found in plasma is emerging as a highly promising avenue or a supplementary method for assessing the efficacy of cancer treatments. This is especially valuable in instances where conventional biopsy specimens, like formalin-fixed, paraffin-embedded (FFPE), or freshly frozen tumor tissues prove inadequate for conducting molecular pathology analyses subsequent to the initial diagnostic procedures. By leveraging cfDNA from plasma, clinicians gain an additional tool to gauge the effectiveness of cancer therapies, thereby enhancing their ability to optimize tailored treatment strategies. In this study, 51 Lithuanian females with NSCLC were analyzed, with adenocarcinoma being the predominant pathology diagnosis in 40 cases (78%). Target mutations were identified in 38 out of 51 patients (74.5%) in tumor tissue samples, while in plasma samples, they were identified in only 10 patients' samples (19.6%). Even though we did not have enough voluminous plasma samples in our study, gene mutations were detected in plasma from ten women, three of whom were diagnosed with early stages of lung cancer (stages I and II). For these patients, the following mutations were detected: deletion in exon 19 of the EGFR gene and single nucleotide polymorphisms in the TP53 and MET genes. All other women were diagnosed with stages III or IV of lung cancer. This indicates that the later stages of cancer contribute more cfDNA in plasma, making extraction less complicated.

Polyphyllin I ameliorates gefitinib resistance and inhibits the VEGF/VEGFR2/p38 pathway by targeting HIF-1a in lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have been administered as the first-line therapy for patients with EGFR mutations in LUAD, but it is almost inevitable that resistance to EGFR-TKIs therapy eventually arises. Polyphyllin I (PPI), derived from Paris polyphylla rhizomes, has been shown to have potent anti-cancer properties in a range of human cancer types including LUAD. However, the role of PPI in gefitinib resistance and the underlying mechanism remain elusive. PurposeTo evaluate the antitumor impacts of PPI on gefitinib resistance cells and investigate its molecular mechanism. MethodsCCK-8, wound healing, transwell assay, and xenograft model were performed to determine the anti-cancer effects of PPI as well as its ability to overcome gefitinib resistance. Immunoblotting, co-immunoprecipitation, phospho-RTK antibody array, qRT-PCR, and immunofluorescence were utilized to explore the mechanism by which PPI overrides gefitinib resistance. ResultsPPI inhibited cell survival, growth, and migration/invasion in both gefitinib-sensitive (PC9) and -resistant (PC9/GR) LUAD cells (IC50 at 2.0 μM). Significantly, treatment with PPI at 1.0 μM resensitized the resistant cells to gefitinib. Moreover, cell-derived xenograft experiments revealed that the combination of PPI and gefitinib overcame gefitinib resistance. The phospho-RTK array and immunoblotting analyses showed PPI significant inhibition of the VEGFR/p38 pathway. In addition, molecular docking suggested the interaction between PPI and HIF-1α. Mechanistically, PPI reduced the protein expression of HIF-1α in both normoxia and hypoxia conditions by triggering HIF-1α degradation. Moreover, HIF-1α protein but not mRNA level was elevated in gefitinib-resistant LUAD. We further demonstrated that PPI considerably facilitated the binding of HIF-1α to VHL. ConclusionsWe present a novel discovery demonstrating that PPI effectively counteracts gefitinib resistance in LUAD by modulating the VEGF/VEGFR/p38 pathway. Mechanistic investigations unveil that PPI facilitates the formation of the HIF-1α /VHL complex, leading to the degradation of HIF-1α and subsequent inhibition of angiogenesis. These findings uncover a previously unidentified mechanism governing HIF-1α expression in reaction to PPI, providing a promising method for therapeutic interventions targeting EGFR-TKI resistance in LUAD.

MAMILNet: advancing precision oncology with multi-scale attentional multi-instance learning for whole slide image analysis

BackgroundWhole Slide Image (WSI) analysis, driven by deep learning algorithms, has the potential to revolutionize tumor detection, classification, and treatment response prediction. However, challenges persist, such as limited model generalizability across various cancer types, the labor-intensive nature of patch-level annotation, and the necessity of integrating multi-magnification information to attain a comprehensive understanding of pathological patterns.MethodsIn response to these challenges, we introduce MAMILNet, an innovative multi-scale attentional multi-instance learning framework for WSI analysis. The incorporation of attention mechanisms into MAMILNet contributes to its exceptional generalizability across diverse cancer types and prediction tasks. This model considers whole slides as “bags” and individual patches as “instances.” By adopting this approach, MAMILNet effectively eliminates the requirement for intricate patch-level labeling, significantly reducing the manual workload for pathologists. To enhance prediction accuracy, the model employs a multi-scale “consultation” strategy, facilitating the aggregation of test outcomes from various magnifications.ResultsOur assessment of MAMILNet encompasses 1171 cases encompassing a wide range of cancer types, showcasing its effectiveness in predicting complex tasks. Remarkably, MAMILNet achieved impressive results in distinct domains: for breast cancer tumor detection, the Area Under the Curve (AUC) was 0.8872, with an Accuracy of 0.8760. In the realm of lung cancer typing diagnosis, it achieved an AUC of 0.9551 and an Accuracy of 0.9095. Furthermore, in predicting drug therapy responses for ovarian cancer, MAMILNet achieved an AUC of 0.7358 and an Accuracy of 0.7341.ConclusionThe outcomes of this study underscore the potential of MAMILNet in driving the advancement of precision medicine and individualized treatment planning within the field of oncology. By effectively addressing challenges related to model generalization, annotation workload, and multi-magnification integration, MAMILNet shows promise in enhancing healthcare outcomes for cancer patients. The framework’s success in accurately detecting breast tumors, diagnosing lung cancer types, and predicting ovarian cancer therapy responses highlights its significant contribution to the field and paves the way for improved patient care.

Inhibition of ALDOA and ENO1‐mediated Glycolysis of Oridonin as a Novel Anti‐tumor Strategy of Non‐small Cell Lung Cancer

AbstractNon‐small cell lung cancer (NSCLC) is the most common type of lung cancer. Oridonin (ORI), the main pharmacodynamic component of the Chinese herb Herba Rabdosiae with anti‐cancer activity has been reported to inhibit various types of cancer including NSCLC. However, its direct target proteins acting on NSCLC still require further investigation. In this study, we analyze the direct protein profile and identify the key targets of ORI by combining activity‐based protein profiling (ABPP) and the cellular thermal shift assay (CETSA). As a result, ORI can significantly promote LLC cell apoptosis, decrease mitochondrial membrane potential (MMP), and increase reactive oxygen species (ROS) accumulation. In addition, both ABPP and CETSA indicate that ORI directly binds to key proteins of the glycolysis pathway, including Aldolase A (ALDOA), Enolase 1 (ENO1), Pyruvate kinase M2 (PKM2) and Lactate dehydrogenase (LDHA). Based on the LLC mouse model, ORI markedly inhibits the growth of lung tumors, increases the serum levels of antioxidant enzymes catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GSH‐Px), and reduces the production of malondialdehyde (MDA). To sum up, ORI can be regarded as a novel anti‐tumor strategy of NSCLC by inhibiting ALDOA and ENO1‐mediated glycolysis.This article is protected by copyright. All rights reserved

A liquid biopsy assay for the noninvasive detection of lymph node metastases in T1 lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a common pathological type of lung cancer. The presence of lymph node metastasis plays a crucial role in determining the overall treatment approach and long-term prognosis for early LUAD, therefore accurate prediction of lymph node metastasis is essential to guide treatment decisions and ultimately improve patient outcomes. We performed transcriptome sequencing on T1 LUAD patients with positive or negative lymph node metastases and combined this data with The Cancer Genome Atlas Program cohort to identify potential risk molecules at the tissue level. Subsequently, by detecting the expression of these risk molecules by real-time quantitative PCR in serum samples, we developed a model to predict the risk of lymph node metastasis from a training cohort of 96 patients and a validation cohort of 158 patients. Through transcriptome sequencing analysis of tissue samples, we identified 11 RNA (miR-412, miR-219, miR-371, FOXC1, ID1, MMP13, COL11A1, PODXL2, CXCL13, SPOCK1 and MECOM) associated with positive lymph node metastases in T1 LUAD. As the expression of FOXC1 and COL11A1 was not detected in serum, we constructed a predictive model that accurately identifies patients with positive lymph node metastases using the remaining nine RNA molecules in the serum of T1 LUAD patients. In the training set, the model achieved an area under the curve (AUC) of 0.89, and in the validation set, the AUC was 0.91. We have established a new risk prediction model using serum samples from T1 LUAD patients, enabling noninvasive identification of those with positive lymph node metastases.

Study on the Mechanism of Competing Endogenous Network of 'Scutellaria barbata D.Don-Houttuynia cordata- Radix Scutellariae' in the Treatment of NSCLC based on Bioinformatics, Molecular Dynamics and Experimental Verification.

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. Traditional Chinese medicine, known for its multi-target and multi-pathway characteristics, offers a potential treatment approach for NSCLC. This study aimed to explore the mechanism of the competitive endogenous network of 'Scutellaria barbata D.Don-Houttuynia cordata-Radix Scutellariae' in treating NSCLC through bioinformatics analysis and in vitro experiments. Various databases and ceRNA networks were utilized to collect and screen components and target genes, molecular docking and molecular dynamics simulations to determine the binding ability of ligand-receptor complexes. In vitro experiments were conducted to validate the effects of active ingredients of 'Scutellaria barbata D.Don-Houttuynia cordata- Radix Scutellariae' on non-small cell lung cancer cell line A549. The key target proteins CCL2, EDN1, MMP9, PPARG, and SPP1 were docked well with their corresponding TCM ligands. Among the ligand-receptor complexes, MMP9-Luteolin and MMP9-Quercetin demonstrated the weaking binding force, while the SPP1-Quercetin complex, associated with NSCLC prognosis, exhibited stable structure formation through hydrogen bond interaction during MD simulation. In vitro experiments confirmed the inhibitory effect of Quercetin on SPP1 expression, as well as the proliferation and migration of A549 cells. The findings suggest that 'Scutellaria barbata D.Don-Houttuynia cordata-Radix Scutellariae' may potentially treat lung cancer by suppressing the expression of SPP1. This study provides valuable insights and novel research directions for understanding the mechanism of traditional Chinese medicine in combating lung cancer.

Deciphering the heterogeneity dominated by tumor-associated macrophages for survival prognostication and prediction of immunotherapy response in lung adenocarcinoma

Tumor-associated macrophages (TAMs) are a specific subset of macrophages that reside inside the tumor microenvironment. The dynamic interplay between TAMs and tumor cells plays a crucial role in the treatment response and prognosis of lung adenocarcinoma (LUAD). The study aimed to examine the association between TAMs and LUAD to advance the development of targeted strategies and immunotherapeutic approaches for treating this type of lung cancer. The study employed single-cell mRNA sequencing data to characterize the immune cell composition of LUAD and delineate distinct subpopulations of TAMs. The “BayesPrism” and “Seurat” R packages were employed to examine the association between these subgroups and immunotherapy and clinical features to identify novel immunotherapy biomarkers. Furthermore, a predictive signature was generated to forecast patient prognosis by examining the gene expression profile of immunotherapy-associated TAMs subsets and using 104 machine-learning techniques. A comprehensive investigation has shown the existence of a hitherto unidentified subgroup of TAMs known as RGS1 + TAMs, which has been found to have a strong correlation with the efficacy of immunotherapy and the occurrence of tumor metastasis in LUAD patients. CD83 was identified CD83 as a distinct biomarker for the expression of RGS1 + TAMs, showcasing its potential utility as an indicator for immunotherapeutic interventions. Furthermore, the prognostic capacity of the RTMscore signature, encompassing three specific mRNA (NR4A2, MMP14, and NPC2), demonstrated enhanced robustness when contrasted against the comprehensive collection of 104 features outlined in the published study. CD83 has potential as an immunotherapeutic biomarker. Meanwhile, The RTMscore signature established in the present study might be beneficial for survival prognostication.

Lung Cancer Prediction and Classification Using Decision Tree and VGG16 Convolutional Neural Networks

Introduction A malignant abnormal growth that starts in the tissues of the lungs is called Lung Cancer. It ranks among the most common and lethal cancers globally. Lung Cancer is particularly dangerous because of its aggressive nature and how quickly it can extend to other areas of the body. We propose a two-step verification architecture to check the presence of Lung Cancer. The model proposed by this paper first assesses the patient based on a few questions about the patient's symptoms and medical background. Then, the algorithm determines whether the patient has a low, medium, or high risk of developing lung cancer by diagnosing the response using the “Decision Tree” classification at an accuracy of 99.67%. If the patient has a medium or high risk, we further validate the finding by examining the patient's CT scan image using the “VGG16” CNN model at an accuracy of 92.53%. Background One of the key areas of research on Lung Cancer prediction is to identify patients based on symptoms and medical history. Its subjective nature makes it challenging to apply in real-world scenarios. Another research area in this field involves forecasting the presence of cancer cells using CT scan imagery, providing high accuracy. However, it requires physician intervention and is not appropriate for early-stage prediction. Objective This research aims to forecast the severity of Lung Cancer by analyzing the patient with a few questions regarding the symptoms and past medical conditions. If the patient has a medium or a high risk, we further examine their CT scan, validate the result and also predict the type of Lung Cancer. Methodology This paper uses the “Decision Tree” algorithm and the Customised “VGG16” model of CNN for the implementation. The “Decision Tree” algorithm is used to analyze the answers given by the patient to distinguish the severity of Lung Cancer. We further use Convolution Neural Networks with a Customised “VGG16” model to examine the patient's CT scan image, validate the result and categorize the type of Lung Cancer. Results The “Decision Tree” approach for forecasting the severity of lung cancer yields an accuracy of 99.67%. The accuracy of the customized “VGG16” CNN model to indicate the type of Lung Cancer suffered by the patient is 92.53% Conclusion This research indicates that our technique provides greater accuracy than the prior approaches for this problem and has extensive use in the prognosis of Lung Cancer.

25-hydroxycholesterol promotes proliferation and metastasis of lung adenocarcinoma cells by regulating ERβ/TNFRSF17 axis.

Lung adenocarcinoma is the main type of lung cancer in women. Our previous findings have evidenced that 25-hydroxycholesterol (25-HC) promotes migration and invasion of lung adenocarcinoma cells (LAC), during which LXR as a 25-HC receptor plays an important role. Estrogen receptor beta (ERβ) is a receptor of 27-hydroxycholesterol that is structurally analogous to 25-HC, but its role in the functional actions of 25-HC remained largely unknown. In this study, we demonstrated that 25-HC treatment triggered ERβ expression in LAC. Knockdown of ERβ inhibited 25-HC-mediated proliferation, migration and invasion, and reduced 25-HC-induced LAC metastasis in vivo. Further investigation revealed that ERβ knockdown restrained the expression of TNFRSF17 (BCMA). In vivo experiments also confirmed that ERβ knockdown blocked 25-HC-induced TNFRSF17 expression. TNFRSF17 knockdown also restrained 25-HC-induced proliferation, migration and invasion. Bioinformatic analysis showed that the levels of ERβ and TNFRSF17 were elevated in lung adenocarcinoma, and were closely related to tumor stages and nodal metastasis status. These results suggested that 25-HC promoted the proliferation and metastasis of LAC by regulating ERβ/TNFRSF17 axis.

NCI 159456 PERK Inhibitor as a Targeted Therapy for Lung Cancer: An In Vitro Study.

Non-small cell lung cancer (NSCLC) represents the most common histological type of lung cancer, characterized by a five-year survival rate of 15% and poor prognosis. Accumulating evidence indicates a prominent role of endoplasmic reticulum (ER) stress and the protein kinase RNA-like ER kinase (PERK)-dependent pathway of the unfolded protein response (UPR) in the pathogenesis of NSCLC. Increased expression of downstream targets of PERK was observed in various subtypes of NSCLC, and it was associated with a more aggressive phenotype, high risk of recurrence, and poor prognosis. Therefore, the present study aimed to investigate the biological effect of the selective PERK inhibitor NCI 159456 on A549 NSCLC cells and Human Pulmonary Fibroblasts (HPF) in vitro. Treatment of both normal and ER-stressed A549 cells with NCI 159456 resulted in a significant increase in the mRNA expression level of pro-apoptotic genes like activating transcription factor 4 (ATF4), DNA damage inducible transcript 3 (DDIT3), and BCL2 Associated X, Apoptosis Regulator (BAX) as well as a decreased level of the anti-apoptotic gene B-cell lymphoma 2 (Bcl-2). Cytotoxicity and genotoxicity analyses revealed that NCI 159456 significantly decreased viability and increased DNA damage in A549 cells under normal and ER stress conditions. Caspase-3 and reactive oxygen species (ROS) detection assays demonstrated that NCI 159456 significantly induced apoptosis and increased the ROS level in normal and ER-stressed A549 cells. Importantly, treatment with the inhibitor did not affect substantially normal HPF cells at any used concentration. The results indicate that PERK inhibitors could potentially be applied as a targeted therapy for NSCLC.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq reveals immune suppression subtypes and establishes a novel signature for determining the prognosis in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer with lower survival rates. Recent advancements in targeted therapies and immunotherapies targeting immune checkpoints have achieved remarkable success, there is still a large percentage of LUAD that lacks available therapeutic options. Due to tumor heterogeneity, the diagnosis and treatment of LUAD are challenging. Exploring the biology of LUAD and identifying new biomarker and therapeutic targets options are essential. We performed single-cell RNA sequencing (scRNA-seq) of 6 paired primary and adjacent LUAD tissues, and integrative omics analysis of the scRNA-seq, bulk RNA-seq and whole-exome sequencing data revealed molecular subtype characteristics. Our experimental results confirm that CDC25C gene can serve as a potential marker for poor prognosis in LUAD. We investigated aberrant gene expression in diverse cell types in LUAD via the scRNA-seq data. Moreover, multi-omics clustering revealed four subgroups defined by transcriptional profile and molecular subtype 4 (MS4) with poor survival probability, and immune cell infiltration signatures revealed that MS4 tended to be the immunosuppressive subtype. Our study revealed that the CDC25C gene can be a distinct prognostic biomarker that indicates immune infiltration levels and response to immunotherapy in LUAD patients. Our experimental results concluded that CDC25C expression affects lung cancer cell invasion and migration, might play a key role in regulating Epithelial-Mesenchymal Transition (EMT) pathways. Our multi-omics result revealed a comprehensive set of molecular attributes associated with prognosis-related genes in LUAD at the cellular and tissue level. Identification of a subtype of immunosuppressive TME and prognostic signature for LUAD. We identified the cell cycle regulation gene CDC25C affects lung cancer cell invasion and migration, which can be used as a potential biomarker for LUAD.

The Application of tDCS to Treat Pain and Psychocognitive Symptoms in Cancer Patients: A Scoping Review.

The use of transcranial direct current stimulation (tDCS) to modulate pain, psychological aspects, and cognitive functions has increased in recent years. The present scoping review aims to investigate the use of tDCS in cancer patients and its significant impact on psychocognitive and pain related symptoms. From the earliest available date to June 2023, a comprehensive search was conducted in three electronic scientific databases-PubMed, Scopus, and Embase-and other supplementary sources. Ten relevant studies were identified and included, comprising single case studies, randomized controlled trials, pilot studies, and one retrospective study. PRISMA guidelines for scoping reviews were followed. These studies investigated the use of tDCS to improve pain and psychocognitive aspects in patients with various types of cancer, including breast, oral, bladder, lung, pancreatic, head and neck cancer, hepatocellular carcinoma, and meningioma. Overall, the results suggest that tDCS has shown efficacy in relieving pain, reducing anxiety and depression, and improving cognitive function in cancer patients. Due to the limited number and high heterogeneity of the existing literature in this field, more investigation and the establishment of standardized protocols would be required to obtain more conclusive evidence.

Composition of the sputum bacterial microbiome of patients with different pathomorphological forms of non-small-cell lung cancer.

Recent studies have shown that the bacterial microbiome of the respiratory tract influences the development of lung cancer. Changes in the composition of the microbiome are observed in patients with chronic inflammatory processes. Such microbiome changes may include the occurrence of bacteria that cause oxidative stress and that are capable of causing genome damage in the cells of the host organism directly and indirectly. To date, the composition of the respiratory microbiome in patients with various histological variants of lung cancer has not been studied. In the present study, we determined the taxonomic composition of the sputum microbiome of 52 patients with squamous cell carcinoma of the lung, 52 patients with lung adenocarcinoma and 52 healthy control donors, using next-generation sequencing (NGS) on the V3-V4 region of the bacterial gene encoding 16S rRNA. The sputum microbiomes of patients with different histological types of lung cancer and controls did not show significant differences in terms of the species richness index (Shannon); however, the patients differed from the controls in terms of evenness index (Pielou). The structures of bacterial communities (beta diversity) in the adenocarcinoma and squamous cell carcinoma groups were also similar; however, when analyzed according to the matrix constructed by the Bray-Curtis method, there were differences between patients with squamous cell carcinoma and healthy subjects, but not between those with adenocarcinoma and controls. Using the LEFse method it was possible to identify an increase in the content of Bacillota (Streptococcus and Bacillus) and Actinomycetota (Rothia) in the sputum of patients with squamous cell carcinoma when compared with samples from patients with adenocarcinoma. There were no differences in the content of bacteria between the samples of patients with adenocarcinoma and the control ones. The content of representatives of the genera Streptococcus, Bacillus, Peptostreptococcus (phylum Bacillota), Prevotella, Macellibacteroides (phylum Bacteroidota), Rothia (phylum Actinomycetota) and Actinobacillus (phylum Pseudomonadota) was increased in the microbiome of sputum samples from patients with squamous cell carcinoma, compared with the control. Thus, the sputum bacterial microbiome of patients with different histological types of non-small-cell lung cancer has significant differences. Further research should be devoted to the search for microbiome biomarkers of lung cancer at the level of bacterial species using whole-genome sequencing.

MiR-29b-3p targetedly regulates VEGF to inhibit tumor progression and cisplatin resistance through Nrf2/HO-1 signaling pathway in non-small cell lung cancer.

Non-small cell lung carcinoma (NSCLC) is a common type of lung cancer. Prior investigations have elucidated the pivotal role of miR-29b-3p in restraining tumor growth and metastasis. Nonetheless, it remains to be determined whether miR-29b-3p can effectively suppress NSCLC progression and enhance the sensitivity of NSCLC cells to cisplatin. This investigation sought to determine the mechanism by which miR-29b-3p inhibited the advancement of NSCLC and mitigated resistance to cisplatin. We initially assessed miR-29b-3p and VEGF levels in NSCLC tissues and cell lines. Next, miR-29b-3p expression was elevated in NSCLC cell lines H1975 and A549 by overexpression plasmid transfection. Following this, a sequence of molecular biology experiments was conducted to evaluate the impact of miR-29b-3p on the biological behaviors of NSCLC cells and their resistance to cisplatin. Additionally, we predicted VEGF was a target gene of miR-29b-3p by bioinformatics analysis. We next employed western blot to evaluate the protein expression of Nrf2 and HO-1 in NSCLC cells. Finally, we elucidated the effects of VEGF and Nrf2/HO-1pathway on NSCLC progression and cisplatin resistance by in vitro assays. In comparison to paracancerous tissues and human normal lung epithelial cells, the expression of miR-29b-3p was notably reduced and VEGF expression was clearly elevated in NSCLC tissues and cells. Moreover, miR-29b-3p upregulated obviously suppressed the biological activities of NSCLC cells and increased their sensitivity to cisplatin. Furthermore, in NSCLC cells, miR-29b-3p bound to VEGF and negatively regulate its transcription. Additionally, miR-29b-3p overexpression also inhibited the Nrf2/HO-1 signaling pathway. Finally, the overexpression of VEGF and the activation of the Nrf2/HO-1 pathway reversed miR-29b-3p-mediated inhibitory effect on biological behaviors of NSCLC cells and increased the cisplatin resistance. Our findings indicate that miR-29b-3p impedes NSCLC cells' biological behaviors and augments their sensitivity to cisplatin by targeting VEGF to modulate the Nfr2/HO-1 signaling pathway.

Abstract CT257: Hyperprogressive disease following bintrafusp alfa and DNA damaging chemotherapy in relapsed small cell lung cancer

Abstract Background: Small cell lung cancer (SCLC) is the most aggressive type of lung cancer. Current therapies have limited efficacy in SCLC, and despite a highly mutated genome, SCLC is largely unresponsive to immunotherapy. We sought to leverage the immune surveillance triggered by DNA damage in patients with relapsed SCLC using bintrafusp alfa, a bifunctional fusion protein targeting both PD-L1 and TGF-beta. Hyperprogressive disease (HPD), characterized by the rapid acceleration of tumor growth, has been reported in approximately 13% of patients treated with immune checkpoint inhibitors. However, the mechanistic basis is poorly understood. Methods: This is a safety run-in and phase II clinical trial. Cohort 1 enrolled patients with relapsed SCLC across Arms A (bintrafusp alfa 2400 mg q3 wks), B (bintrafusp alfa 2400 mg on D1 plus topotecan 1 mg/m2/day on D1-5 q3 wks), and C (bintrafusp alfa 1200 mg on D1 q2 wks plus temozolomide 200 mg/m2/day on D1-5 q4 wks). The primary endpoint was objective response rate (ORR). Results: Thirty-seven patients enrolled. Grade 3 treatment-related adverse events (TRAE) included transaminitis (27.0%), anemia (24.4%), lymphopenia (10.8%), and maculopapular rash (5.4%). Grade 4 TRAE included thrombocytopenia (8.1%), lymphopenia (5.4%) and transaminitis (5.4%). One patient experienced grade 5 tumor hemorrhage. By RECIST 1.1, partial responses were observed in 5 (13.5%), stable disease in 11 (29.7%), and progressive disease in 21 (56.8%) patients. Importantly, 13 (35.1%) patients developed HPD (≥ 2x increase in tumor growth rate from pre-trial vs on-trial, time to treatment failure ≤ 2 months, and ≥ 50% increase tumor burden). Changes in circulating cell-free DNA (n=20) tumor fraction using DELFI-TF, a mutation-independent, low-coverage whole genome sequencing approach, correlated with treatment responses. Pre-treatment serum from HPD (n=10 vs. 9 non-HPD) patients showed significantly lower levels of inflammatory cytokines (CXCL10, CCL13, CCL8, CCL19, TRAIL) and Granzyme H, and higher levels of anti-inflammatory cytokine IL10. Consistently, pre-treatment tumor transcriptomes of HPD (n=5 vs. 7 non-HPD) patients revealed suppression of IFN-gamma response, allograft rejection, and inflammatory response pathways. Conclusions: Concomitant TGF-beta and PD-L1 blockade is associated with a high frequency of HPD in SCLC patients. cfDNA could be critical for monitoring HPD. Tumor and blood immune signatures may inform the likelihood of HPD, with immune excluded tumors more likely to develop HPD. NCT Number: NCT03554473 Bintrafusp alfa was provided by EMD Serono (CrossRef Funder ID: 10.13039/100004755) Citation Format: Brett Schroeder, Nobuyuki Takahashi, Howard Yang, Renee Donahue, Zachary Skidmore, Alissa Konicki, Michael Nirula, Max Greenberg, George Chrisafis, Yang Zhang, Yo-Ting Tsai, Linda Sciuto, Samantha Nichols, Melissa Abel, Parth Desai, Rajesh Kumar, Christopher Schultz, Danielle Pinkiert, Chante Graham, Ajit Sharma, Justin Malin, Manan Krishnamurthy, Sophie Zhuang, Maxwell Lee, Lorenzo Rinaldi, Jeffrey Schlom, Lalage Wakefield, Anish Thomas. Hyperprogressive disease following bintrafusp alfa and DNA damaging chemotherapy in relapsed small cell lung cancer [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 CT257.

Structural Perspectives in the Development of Novel EGFR Inhibitors for the Treatment of NSCLC.

Non-small cell Lung cancer (NSCLC) is the most common type of lung cancer, which is caused by high consumption of tobacco and smoking. It is an epithelial lung cancer that affects about 2.2 million people across the globe, according to International Agency for Research on Cancer (IARC). Non-small cell lung cancer is a malignant tumor caused by EGFR mutation that occurs in the in-frame deletion of exon 19 and L858R point mutation in exon 21. Presently, clinically available inhibitors of EGFR (including erlotinib, lapatinib, gefitinib, selumetinib, etc.) are not specific and responsible for undesirable adverse effects. Moreover, to solve this problem search for newer EGFR inhibitors is the utmost need for the treatment and/or management of increasing lung cancer burden. The discovery of therapeutic agents that inhibit the specific target in tumorous cells, such as EGFR, is one of the successful strategies in treating many cancer therapies, including lung cancer. The exhaustive literature survey (2018-2023) has shown the importance of medicinally privileged pyrimidine derivatives together, fused and/or clubbed with other heterocyclic rings to design and develop novel EGFR inhibitors. Pyrimidine derivatives substituted with phenylamine, indole, pyrrole, piperazine, pyrazole, thiophene, pyridine and quinazoline derivatives substituted with phenylamine, pyrimidine, morpholine, pyrrole, dioxane, acrylamide, indole, pyridine, furan, pyrimidine, pyrazole etc. are privileged heterocyclic rings shown promising activity by inhibiting EGFR and TKIs. The present review summarizes the structure-activity relationship (SAR) and enzyme inhibitory activity, including IC50 values, percentage inhibition, and kinetic studies of potential compounds from various literature. The review also includes various aspects of molecular docking studies with compounds under clinical trials and patents filed on pyrimidine-based EGFR inhibitors in treating non-small cell lung cancer. The present review may benefit the medicinal chemist for developing novel compounds such as EGFR inhibitors.

Anoikis-related gene signatures predict prognosis of lung adenocarcinoma patients and reveal immune infiltration.

Lung adenocarcinoma (LUAD), a type of lung cancer, is one of the most aggressive and deadly malignancies worldwide. Malignant tumor cells exhibit strong anti-anoikis properties to achieve distant metastasis through the circulatory system. However, more research is needed to understand how anoikis is involved in the progression, metastasis and especially the prognosis of LUAD. We obtained anoikis-related genes (ARGs) from two websites, Harmonizome and Genecards, and integrated them to select and model the genes associated with LUAD prognosis. In addition, we investigated differences in the immune cell microenvironment and pathways of enrichment analysis between subtypes. We finally constructed a nomogram based on ARGs and used decision curve analysis (DCA) to demonstrate that this model could help clinicians make clinical decisions. Sixty-four differentially expressed genes (DEGs) were found to be associated with survival, and of these, six were chosen to build a prognostic model. The time-dependent receiver operating characteristic (ROC) curves showed that the model had a satisfactory predictive ability. Enrichment analysis and immune microenvironment analysis revealed that the immune status and drug sensitivity of populations at high and low risk were different. We integrated the clinicopathological features of LUAD with the risk score to build the nomogram. The nomogram was shown to be a good predictor of short- and long-term survival in LUAD patients through DCA analysis. This new model based on six ARGs and nomograms in our study could help patients with LUAD develop personalized treatment plans.