CRTAC1 identified as a promising diagnosis and prognostic biomarker in lung adenocarcinoma.

CRTAC1, one of the pyroptosis-related genes, has been identified as a protective factor in certain kinds of cancer, such as gastric adenocarcinoma and bladder cancer. The study aimed to investigate the role of CRTAC1 in lung adenocarcinoma (LUAD). LUAD datasets were obtained from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA), pyroptosis-related genes from GeneCard. Limma package used to find differentially expressed genes (DEGs), least absolute shrinkage and selection operator (LASSO) regression and weighted genes co-expression network analysis (WGCNA) to identify CRTAC1 as hub gene. CRTAC1 expression was confirmed in a real-world cohort using quantitative polymerase chain reaction (qPCR) and Western Blot (WB) analyses. Cellular experiments were conducted to investigate CRTAC1's potential oncogenic mechanisms. CRTAC1 mRNA expression was significantly lower in LUAD tissues (p < 0.05) and showed high accuracy in diagnosing LUAD. Reduced CRTAC1 expression was associated with a poor prognosis. Higher CRTAC1 expression correlated with increased immune cell infiltration. Individuals with high CRTAC1 expression showed increased drug sensitivity. Additionally, qPCR and WB analyses showed that CRTAC1 expression was lower in tumor tissue compared to adjacent normal tissue at both the RNA and protein levels. Upregulation of CRTAC1 significantly inhibited LUAD cell proliferation, invasion, and migration in cellular experiments. CRTAC1 has the potential to serve as a diagnostic and prognostic biomarker in LUAD.

Detection of fucosylated extracellular vesicles miR-4732-5p related to diagnosis of early lung adenocarcinoma by the electrochemical biosensor.

Our preliminary investigation has identified the potential of serum fucosylated extracellular vesicles (EVs) miR-4732-5p in the early diagnosis of lung adenocarcinoma (LUAD) by a fucose-captured strategy utilizing lentil lectin (LCA)-magnetic beads and subsequent screening of high throughput sequencing and validation of real-time quantitative polymerase chain reaction (RT-qPCR). Considering the relatively complicated procedure, expensive equipment, and stringent laboratory condition, we have constructed an electrochemical biosensor assay for the detection of miR-4732-5p. miR-4732-5p is extremely low in serum, down to the fM level, so it needs to be detected by highly sensitive electrochemical methods based on the Mg2+-dependent DNAzyme splitting nucleic acid lock (NAL) cycle and hybridization chain reaction (HCR) signal amplification. In this study, signal amplification is achieved through the dual amplification reactions using NAL cycle in combination with HCR. In addition, hybridized DNA strands bind to a large number of methylene blue (MB) molecules to enhance signaling. Based on the above strategy, we further enhance our signal amplification strategies to improve detection sensitivity and accuracy. The implementation of this assay proceeded as follows: initially, miR-4732-5p was combined with NAL, and then Mg2+-dependent DNAzyme splitted NAL to release auxiliary DNA (S1) strands, which were subsequently captured by the immobilized capture probe DNA (C1) strands on the electrode surface. Following this, abundant quantities of DNA1 (H1) and DNA2 (H2) tandems were generated by HCR, and S1 strands then hybridized with the H1 and H2 tandems through base complementary pairing. Finally, MB was bonded to the H1 and H2 tandems through π-π stacking interaction, leading to the generation of a signal current upon the detection of a potential capable of inducing a redox change of MB by the electrode. Furthermore, we evaluated the performance of our developed electrochemical biosensor assay. The results demonstrated that our assay is a reliable approach, characterized by its high sensitivity (with a detection limit of 2.6 × 10-17 M), excellent specificity, good accuracy, reproducibility, and stability. Additionally, it is cost-effective, requires simple operation, and is portable, making it suitable for the detection of serum fucosylated extracellular vesicles miR-4732-5p. Ultimately, this development has the potential to enhance the diagnostic efficiency for patients with early-stage LUAD.

Machine-learning developed an iron, copper, and sulfur-metabolism associated signature predicts lung adenocarcinoma prognosis and therapy response.

BACKGROUND: Previous studies have largely neglected the role of sulfur metabolism in LUAD, and no study has combine iron, copper, and sulfur-metabolism associated genes together to create prognostic signatures. METHODS: This study encompasses 1564 LUAD patients, 1249 NSCLC patients, and over 10,000 patients with various cancer types from diverse cohorts. We employed the R package ConsensusClusterPlus to separate patients into different ICSM (Iron, Copper, and Sulfur-Metabolism) subtypes. Various machine-learning methods were utilized to develop the ICSMI. Enrichment analyses were conducted using ClusterProfiler and GSVA, while IOBR quantified immune cell infiltration. GISTIC2.0 and maftools were utilized for CNV and SNV data analysis. The Oncopredict package predicted drug information based on GDSC1. TIDE algorithm and cohorts GSE91061 and IMvigor210 evaluated patient response to immunotherapy. Single-cell data was processed using the Seurat package, AUCell package calculated cells geneset activity scores, and the Scissor algorithm identified ICSMI-associated cells. In vitro experiments was conducted to explore the role of ICSMRGs in LUAD. RESULTS: Unsupervised clustering identified two distinct ICSM subtypes of LUAD, each with unique clinical characteristics. The ICSMI, comprising 10 genes, was constructed using integrated machine-learning methods. Its prognostic power was validated in 10 independent datasets, revealing that LUAD patients with higher ICSMI levels had poorer prognoses. Furthermore, ICSMI demonstrated superior predictive abilities compared to 102 previously published signatures. A nomogram incorporating ICSMI and clinical features exhibited high predictive performance. ICSMI positively correlated with patients gene mutations, and integrated analysis of bulk and single-cell transcriptome data revealed its association with TME modulators. Cells representing the high-ICSMI phenotype exhibited more malignant features. LUAD patients with high ICSMI levels exhibited sensitivity to chemotherapy and targeted therapy but displayed resistance to immunotherapy. In a comprehensive analysis across various cancers, ICSMI retained significant prognostic value and emerged as a risk factor for the majority of cancer patients. CONCLUSIONS: ICSMI provides critical prognostic insights for LUAD patients, offering valuable insights into the tumor microenvironment and predicting treatment responsiveness.

A combination of radiomic features, clinic characteristics, and serum tumor biomarkers to predict the possibility of the micropapillary/solid component of lung adenocarcinoma.

BACKGROUND: Invasive lung adenocarcinoma with MPP/SOL components has a poor prognosis and often shows a tendency to recurrence and metastasis. This poor prognosis may require adjustment of treatment strategies. Preoperative identification is essential for decision-making for subsequent treatment. OBJECTIVE: This study aimed to preoperatively predict the probability of MPP/SOL components in lung adenocarcinomas by a comprehensive model that includes radiomics features, clinical characteristics, and serum tumor biomarkers. DESIGN: A retrospective case control, diagnostic accuracy study. METHODS: This study retrospectively recruited 273 patients (males: females, 130: 143; mean age ± standard deviation, 63.29 ± 10.03 years; range 21-83 years) who underwent resection of invasive lung adenocarcinoma. Sixty-one patients (22.3%) were diagnosed with lung adenocarcinoma with MPP/SOL components. Radiomic features were extracted from CT before surgery. Clinical, radiomic, and combined models were developed using the logistic regression algorithm. The clinical and radiomic signatures were integrated into a nomogram. The diagnostic performance of the models was evaluated using the area under the curve (AUC). Studies were scored according to the Radiomics Quality Score and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines. RESULTS: The radiomics model achieved the best AUC values of 0.858 and 0.822 in the training and test cohort, respectively. Tumor size (T_size), solid tumor size (ST_size), consolidation-to-tumor ratio (CTR), years of smoking, CYFRA 21-1, and squamous cell carcinoma antigen were used to construct the clinical model. The clinical model achieved AUC values of 0.741 and 0.705 in the training and test cohort, respectively. The nomogram showed higher AUCs of 0.894 and 0.843 in the training and test cohort, respectively. CONCLUSION: This study has developed and validated a combined nomogram, a visual tool that integrates CT radiomics features with clinical indicators and serum tumor biomarkers. This innovative model facilitates the differentiation of micropapillary or solid components within lung adenocarcinoma and achieves a higher AUC, indicating superior predictive accuracy.

A new tool to predict aggressive lung cancer types before surgeryWe developed a tool to help doctors determine whether lung cancer is one of the more dangerous types, called micropapillary (MPP) or solid (SOL) patterns, before surgery. These patterns can be more harmful and spread quickly, so knowing they are there can help doctors plan the best treatment. We looked at the cases of 273 lung cancer patients who had surgery and found that 61 of them had these aggressive cancer types. To predict these patterns, we used a computer process known as logistic regression, analyzing CT scan details, health information, and blood tests for cancer markers. Based on CT scans, our tool was very good at predicting whether these patterns were present in two patient groups. However, predictions using only basic health information like the size of the tumor and whether the patient smoked needed to be more accurate. We found a way to make our predictions even better. Combining all information into one chart, known as a nomogram, significantly improved our ability to predict these dangerous cancer patterns. This combined chart could be a big help for doctors. It gives them a clearer picture of the cancer's aggressiveness before surgery, which can guide them to choose the best treatment options. This approach aims to offer a better understanding of the tumor, leading to more tailored and effective treatments for patients facing lung cancer.

Invasion and Grading of Pulmonary Non-Mucinous Adenocarcinoma.

Lung adenocarcinoma staging and grading were recently updated to reflect the link between histologic growth patterns and outcomes. The lepidic growth pattern is regarded as "in-situ," whereas all other patterns are regarded as invasive, though with stratification. Solid, micropapillary, and complex glandular patterns are associated with worse prognosis than papillary and acinar patterns. These recent changes have improved prognostic stratification. However, multiple pitfalls exist in measuring invasive size and in classifying lung adenocarcinoma growth patterns. Awareness of these limitations and recommended practices will help the pathology community achieve consistent prognostic performance and potentially contribute to improved patient management.

GTSE1: A potential prognostic and diagnostic biomarker in various tumors including lung adenocarcinoma.

OBJECTIVE: This research was aimed to comprehensively investigate the expression levels, diagnostic and prognostic implications, and the relationship with immune infiltration of G2 and S phase-expressed-1 (GTSE1) across 33 tumor types, including lung adenocarcinoma (LUAD), through gene expression profiling. METHODS: GTSE1 mRNA expression data together with clinical information were acquired from Xena database of The Cancer Genome Atlas (TCGA), ArrayExpress, and Gene Expression Omnibus (GEO) database for this study. The Wilcoxon rank-sum test was used to detect differences in GTSE1 expression between groups. The ability of GTSE1 to accurately predict cancer status was evaluated by calculating the area under the curve (AUC) value for the receiver operating characteristic curve. Additionally, we investigated the predictive value of GTSE1 in individuals diagnosed with neoplasms using univariate Cox regression analysis as well as Kaplan-Meier curves. Furthermore, the correlation between GTSE1 expression and levels of immune infiltration was assessed by utilizing the Tumor Immune Estimate Resource (TIMER) database to calculate the Spearman rank correlation coefficient. Finally, the pan-cancer analysis findings were validated by examining the association between GTSE1 expression and prognosis among patients with LUAD. RESULTS: GTSE1 exhibited significantly increased expression levels in a wide range of tumor tissues in contrast with normal tissues (p < 0.05). The expression of GTSE1 in various tumors was associated with clinical features, overall survival, and disease-specific survival (p < 0.05). In immune infiltration analyses, a strong correlation of the level of immune infiltration with the expression of GTSE1 was observed. Furthermore, GTSE1 demonstrated good discriminative and diagnostic value for most tumors. Additional experiments confirmed the relationship between elevated GTSE1 expression and unfavorable prognosis in individuals diagnosed with LUAD. These findings indicated the crucial role of GTSE1 expression level in influencing the development and immune infiltration of different types of tumors. CONCLUSIONS: GTSE1 might be a potential biomarker for the prognosis of pan-cancer. Meanwhile, it represented a promising target for immunotherapy.

TIMM17A overexpression in lung adenocarcinoma and its association with prognosis.

Lung adenocarcinoma (LUAD), a leading cause of cancer-related mortality worldwide, demands a deeper understanding of its molecular mechanisms and the identification of reliable biomarkers for better diagnosis and targeted therapy. Leveraging data from the Cancer Genome Atlas (TCGA), the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and the Human Protein Atlas (HPA), we investigated the mRNA and protein expression profiles of TIMM17A and assessed its prognostic significance through Kaplan-Meier survival curves and Cox regression analysis. Through Gene Set Enrichment Analysis, we explored the regulatory mechanisms of TIMM17A in LUAD progression and demonstrated its role in modulating the proliferative capacity of A549 cells, a type of LUAD cell, via in vitro experiments. Our results indicate that TIMM17A is significantly upregulated in LUAD tissues, correlating with clinical staging, lymph node metastasis, overall survival, and progression-free survival, thereby establishing it as a critical independent prognostic factor. The construction of a nomogram model further enhances our ability to predict patient outcomes. Knockdown of TIMM17A inhibited the growth of LUAD cells. The potential of TIMM17A as a biomarker and therapeutic target for LUAD presents a promising pathway for improving patient diagnosis and treatment strategies.

Evaluation of the preoperative neutrophil-to-lymphocyte ratio as a predictor of the micropapillary component of stage IA lung adenocarcinoma.

OBJECTIVE: To assess the ability of markers of inflammation to identify the solid or micropapillary components of stage IA lung adenocarcinoma and their effects on prognosis. METHODS: We performed a retrospective study of clinicopathologic data from 654 patients with stage IA lung adenocarcinoma collected between 2013 and 2019. Logistic regression analysis was used to identify independent predictors of these components, and we also evaluated the relationship between markers of inflammation and recurrence. RESULTS: Micropapillary-positive participants had high preoperative neutrophil-to-lymphocyte ratios. There were no significant differences in the levels of markers of systemic inflammation between the participants with or without a solid component. Multivariate analysis showed that preoperative neutrophil-to-lymphocyte ratio (odds ratio [OR] = 2.094; 95% confidence interval [CI], 1.668-2.628), tumor size (OR = 1.386; 95% CI, 1.044-1.842), and carcinoembryonic antigen concentration (OR = 1.067; 95% CI, 1.017-1.119) were independent predictors of a micropapillary component. There were no significant correlations between markers of systemic inflammation and the recurrence of stage IA lung adenocarcinoma. CONCLUSIONS: Preoperative neutrophil-to-lymphocyte ratio independently predicts a micropapillary component of stage IA lung adenocarcinoma. Therefore, the potential use of preoperative neutrophil-to-lymphocyte ratio in the optimization of surgical strategies for the treatment of stage IA lung adenocarcinoma should be further studied.

Proteomic profiling of tumor microenvironment and prognosis risk prediction in stage I lung adenocarcinoma.

OBJECTIVES: With the increasing popularity of CT screening, more cases of early-stage lung cancer are being diagnosed. However, 24.5% of stage I non-small-cell lung cancer (NSCLC) patients still experience treatment failure post-surgery. Biomarkers to predict lung cancer patients at high risk of recurrence are needed. MATERIALS AND METHODS: We collected protein mass spectrometry data from the Taiwan Lung Cancer Moonshot Project and performed bioinformatics analysis on proteins with differential expressions between tumor and adjacent normal tissues in 74 stage I lung adenocarcinoma (LUAD) cases, aiming to explore the tumor microenvironment related prognostic biomarkers. Findings were further validated in 6 external cohorts. RESULTS: The analysis of differentially expressed proteins revealed that the most enriched categories of diseases and biological functions were cellular movement, immune cell trafficking, and cancer. Utilizing proteomic profiling of the tumor microenvironment, we identified five prognostic biomarkers (ADAM10, MIF, TEK, THBS2, MAOA). We then developed a risk score model, which independently predicted recurrence-free survival and overall survival in stage I LUAD. Patients with high risk scores experienced worse recurrence-free survival (adjusted hazard ratio = 8.28, p < 0.001) and overall survival (adjusted hazard ratio = 6.88, p = 0.013). Findings had been also validated in the external cohorts. CONCLUSION: The risk score model derived from proteomic profiling of tumor microenvironment can be used to predict recurrence risk and prognosis of stage I LUAD.

Diagnostic Value of Immunostaining for Thyroid Transcription Factor 1 (TTF1) and Paired Box 8 (PAX8) in Distinguishing Pulmonary Metastases of Mesonephric and Mesonephric-like Adenocarcinomas from Primary Lung Adenocarcinomas.

BACKGROUND/AIM: Both mesonephric adenocarcinoma (MA) and mesonephric-like adenocarcinoma (MLA) express thyroid transcription factor 1 (TTF1). TTF1 is also considered a highly sensitive and specific diagnostic marker for primary lung adenocarcinoma (PLA). However, distinguishing PLA from pulmonary metastatic MA/MLA (PMM) based on the expression of TTF1 alone can be difficult. This study aimed to investigate the expression of TTF1 and paired box 8 (PAX8) and assess their value in distinguishing PMM from PLA. PATIENTS AND METHODS: We reviewed the electronic medical records and pathology slides of eight PMM cases. We conducted immunostaining for TTF1 and PAX8 in 6, 8, and 21 cases of primary MA/MLA, PMM, and PLA, respectively. RESULTS: Two patients with stage IB uterine MLA developed lung metastases at 5 and 57 months after hysterectomy. Solitary pulmonary nodules were suspected to be primary lung cancer in two patients. Compared to primary tumors, all matched PMMs exhibited reduced TTF1 immunoreactivity. In contrast, the majority of PLAs showed uniform and intense TTF1 expression. All except one PMM exhibited diffuse and strong PAX8 expression, while only one PLA showed focal and weak PAX8 expression. CONCLUSION: Immunostaining for TTF1 and PAX8 can help in distinguishing PMM from PLA in the diagnosis of pulmonary lesions detected in patients with a history of MA/MLA.

Endobronchial Ultrasound Guided Transbronchial Needle Aspiration and PD-L1 Yields.

PURPOSE: Immunotherapy is a leading approach for treating advanced non-small cell lung cancer (NSCLC) by targeting the PD-1/PD-L1 checkpoint signaling pathway, particularly in tumors expressing high levels of PD-L1 (Jug et al. in J Am Soc Cytopathol 9:485-493, 2020; Perrotta et al. in Chest 158: 1230-1239, 2020). Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a minimally invasive method to obtain tissue for molecular studies, including PD-L1 analysis, in unresectable tumors (Genova et al. in Front Immunol 12: 799455, 2021; Wang et al. in Ann Oncol 29: 1417-1422, 2018). This study aimed to assess the adequacy of PD-L1 assessment in EBUS-TBNA cytology specimens. METHODS: Data was collected retrospectively from patients who underwent EBUS-TBNA between 2017 and 2021 for suspected lung cancer biopsy. Samples positive for NSCLC were examined for PD-L1 expression. EBUS was performed by experienced practitioners, following institutional guidelines of a minimum of five aspirations from positively identified lesions. Sample adequacy for molecular testing was determined by the pathology department. RESULTS: The analysis involved 387 NSCLC cases (149 squamous cell, 191 adenocarcinoma, 47 unspecified). Of the 263 EBUS-TBNA specimens tested for PD-L1, 237 (90.1%) were deemed adequate. While 84% adhered to the protocol, adherence did not yield better results. Significantly higher PD-L1 adequacy was observed in squamous cell carcinomas (93.2%) compared to adenocarcinoma (87.6%). The number of aspirations and sedation type did not correlate with PD-L1 adequacy in either cancer type, but lesion size and location had a significant impact in adenocarcinomas. Adenocarcinoma exhibited higher PD-L1 expression (68%) compared to squamous cell carcinoma (48%). CONCLUSION: EBUS-TBNA offers high yields for assessing immunotherapy markers like PD-L1, with satisfactory adequacy regardless of NSCLC subtype, lesion size, or location.

Endobronchial Ultrasound Guided Transbronchial Needle Aspiration and Next Generation Sequencing Yields.

PURPOSE: The use of endobronchial ultrasound (EBUS) is standard practice for lung cancer diagnosis and staging. Next generation sequencing (NGS) for detection of genetic alterations is recommended in advanced, non-squamous, non-small-cell lung cancer (NSCLC). Existing protocols for NGS testing are minimal and reported yields vary. This study aimed to determine the yield of EBUS samples obtained for NGS using a sampling protocol at our institution and assess predictive factors to form collection protocols. METHODS: We reviewed EBUS bronchoscopies from 2016 to 2021 with non-squamous NSCLC diagnoses. For target lesions suspected to be malignant, the sampling protocol was: (a) two slides for on-site evaluation, (b) three to five fine needle aspirations rinsed into saline for immunohistochemical staining and in-house molecular markers, and (c) additional three to five rinses for NGS. Sufficiency for NGS processing was determined by the pathology department. RESULTS: Two hundred and seventy-eight non-squamous NSCLC samples were obtained by EBUS (205 adenocarcinoma; 73 not otherwise specified). EBUS was performed under general anesthesia in 75.5% of cases. The overall sample adequacy for NGS testing was 57.5%. Higher adequacy rates were observed when protocol was adhered to 66.0% versus 37.2% (p < 0.001). There was no statistically significant difference based on the size of the lesion or location of the sample. CONCLUSION: When a protocol of three to five dedicated needle rinses for NGS was followed, we nearly doubled our sample adequacy rate for NSG as compared to standard care. Studies are needed to determine the ideal collection and processing modality to preserve tissue samples for genetic sequencing.

Combined detection of serum IL-6 and CEA contributes to the diagnosis of lung adenocarcinoma in situ.

Background: Effective discrimination of lung adenocarcinoma (LUAD) in situ (AIS) from benign pulmonary nodules (BPN) is critical for the early diagnosis of AIS. Our pilot study in a small cohort of 90 serum samples has shown that serum interleukin 6 (IL-6) detection can distinguish AIS from BPN and health controls (HC). In this study, we intend to comprehensively define the diagnostic value of individual and combined detection of serum IL-6 related to the traditional tumor markers carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1) for AIS. Methods: The diagnostic performance of serum IL-6 along with CEA and CYFRA21-1 were evaluated in a large cohort of 300 serum samples by a chemiluminescence immunoassay and an electrochemiluminescence immunoassay. A training set comprised of 65 AIS, 65 BPN, and 65 HC samples was used to develop the predictive model for AIS. Data obtained from an independent validation set was applied to evaluate and validate the predictive model. Results: In the training set, the levels of serum IL-6 and CEA in the AIS group were significantly higher than those in the BPN/HC group (P < 0.05). There was no significant difference in serum CYFRA21-1 levels between the AIS group and the BPN/HC group (P> 0.05). Serum IL-6 and CEA levels for AIS patients showed an area under the curve (AUC) of 0.622 with 23.1% sensitivity at 90.7% specificity, and an AUC of 0.672 with 24.6% sensitivity at 97.6% specificity, respectively. The combination of serum IL-6 and CEA presented an AUC of 0.739, with 60.0% sensitivity at 95.4% specificity. The combination of serum IL-6 and CEA showed an AUC of 0.767 for AIS patients, with 57.1% sensitivity at 91.4% specificity in the validation set. Conclusions: IL-6 shows potential as a prospective serum biomarker for the diagnosis of AIS, and the combination of serum IL-6 with CEA may contribute to increased accuracy in AIS diagnosis. However, it is worth noting that further research is still necessary to validate and optimize the diagnostic efficacy of these biomarkers and to address potential sensitivity limitations.

Tobacco use, self-reported professional dental cleaning habits, and lung adenocarcinoma diagnosis are associated with bronchial and lung microbiome alpha diversity.

RATIONALE: The lung microbiome is an inflammatory stimulus whose role in the development of lung malignancies is incompletely understood. We hypothesized that the lung microbiome associates with multiple clinical factors, including the presence of a lung malignancy. OBJECTIVES: To assess associations between the upper and lower airway microbiome and multiple clinical factors including lung malignancy. METHODS: We conducted a prospective cohort study of upper and lower airway microbiome samples from 44 subjects undergoing lung lobectomy for suspected or confirmed lung cancer. Subjects provided oral (2), induced sputum, nasopharyngeal, bronchial, and lung tissue (3) samples. Pathologic diagnosis, age, tobacco use, dental care history, lung function, and inhaled corticosteroid use were associated with upper and lower airway microbiome findings. MEASUREMENTS AND MAIN RESULTS: Older age was associated with greater Simpson diversity in the oral and nasopharyngeal sites (p = 0.022 and p = 0.019, respectively). Current tobacco use was associated with greater lung and bronchus Simpson diversity (p < 0.0001). Self-reported last profession dental cleaning more than 6 months prior (vs. 6 or fewer months prior) was associated with lower lung and bronchus Simpson diversity (p < 0.0001). Diagnosis of a lung adenocarcinoma (vs. other pathologic findings) was associated with lower bronchus and lung Simpson diversity (p = 0.024). Last professional dental cleaning, dichotomized as ≤ 6 months vs. >6 months prior, was associated with clustering among lung samples (p = 0.027, R2 = 0.016). Current tobacco use was associated with greater abundance of pulmonary pathogens Mycoplasmoides and Haemophilus in lower airway samples. Self-reported professional dental cleaning ≤ 6 months prior (vs. >6 months prior) was associated with greater bronchial Actinomyces and lung Streptococcus abundance. Lung adenocarcinoma (vs. no lung adenocarcinoma) was associated with lower Lawsonella abundance in lung samples. Inhaled corticosteroid use was associated with greater abundance of Haemophilus among oral samples and greater Staphylococcus among lung samples. CONCLUSIONS: Current tobacco use, recent dental cleaning, and a diagnosis of adenocarcinoma are associated with lung and bronchial microbiome α-diversity, composition (ß-diversity), and the abundance of several respiratory pathogens. These findings suggest that modifiable habits (tobacco use and dental care) may influence the lower airway microbiome. Larger controlled studies to investigate these potential associations are warranted.

Exploratory pilot study to characterize the immune landscapes of malignant pleural effusions and their corresponding primary tumors from patients with breast carcinoma and lung adenocarcinoma.

INTRODUCTION: Malignant pleural effusion (MPE) is a frequent complication of advanced malignancies. In this pilot study, we characterized the immune landscapes of MPEs, compared them to their primary tumor (PT) samples from breast carcinoma (BC) and lung adenocarcinoma (LADC), and tested the utility of multiplexed image technology in cytological samples. MATERIALS AND METHODS: We evaluated the immune contexture of 6 BC and 5 LADC MPEs and their PTs using 3 multiplex immunofluorescence panels. We explored the associations between sample characteristics and pleural effusion-free survival. RESULTS: No MPE samples had positive programmed death-ligand 1 expression in malignant cells, although 3 of 11 PTs has positive programmed death-ligand 1 expression (more than 1% expression in malignant cells). Overall, in LADC samples, cluster of differentiation 3 (CD3)+ T cells and CD3+CD8+ cytotoxic T cells predominated (median percentages for MPEs versus PTs: 45.6% versus 40.7% and 4.7% versus 6.6%, respectively) compared with BC. CD68+ macrophages predominated in the BC samples (medians for MPEs 61.2% versus PTs for 57.1%) but not in the LADC samples. Generally in PTs, CD3+CD8+ forkhead box P3+ T cells and the median distances from the malignant cells to CD3+CD8+Ki67+ and CD3+ programmed cell death protein 1 + T cells correlated to earlier MPE after PT diagnosis. CONCLUSIONS: The immune cell phenotypes in the MPEs and PTs were similar within each cancer type but different between BC versus LADC. An MPE analysis can potentially be used as a substitute for a PT analysis, but an expanded study of this topic is essential.

Lipidomics reveals new lipid-based lung adenocarcinoma early diagnosis model.

Lung adenocarcinoma (LUAD) continues to pose a significant mortality risk with a lack of dependable biomarkers for early noninvasive cancer detection. Here, we find that aberrant lipid metabolism is significantly enriched in lung cancer cells. Further, we identified four signature lipids highly associated with LUAD and developed a lipid signature-based scoring model (LSRscore). Evaluation of LSRscore in a discovery cohort reveals a robust predictive capability for LUAD (AUC: 0.972), a result further validated in an independent cohort (AUC: 0.92). We highlight one lipid signature biomarker, PE(18:0/18:1), consistently exhibiting altered levels both in cancer tissue and in plasma of LUAD patients, demonstrating significant predictive power for early-stage LUAD. Transcriptome analysis reveals an association between increased PE(18:0/18:1) levels and dysregulated glycerophospholipid metabolism, which consistently displays strong prognostic value across two LUAD cohorts. The combined utility of LSRscore and PE(18:0/18:1) holds promise for early-stage diagnosis and prognosis of LUAD.

[High-grade Fetal Adenocarcinoma of the Lung with Scalp Metastasis: A Case Report].

Fetal adenocarcinoma of the lung (FLAC) is a rare tumor. Due to its different clinicopathological features, biological behavior and clinical outcome, FLAC is classified into low-grade FLAC (L-FLAC) and high-grade FLAC (H-FLAC). Most patients with H-FLAC are middle-aged heavy smokers. Here, we describe an extremely rare case of a young male patient who denies smoking and initially presents with a mass on the top of the head and is eventually diagnosed with H-FLAC. The aim of this article is to improve the understanding and awareness of FLAC, and increase the attention to the disease, so as to prevent the underdiagnosis and misdiagnosis of the disease, strengthen early identification and accurate diagnosis, and promote subsequent effective treatment and improve prognosis.
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MECOM: a bioinformatics and experimentally identified marker for the diagnosis and prognosis of lung adenocarcinoma.

Objective: We aimed to explore the clinical value of MDS1 and EVI1 complex locus (MECOM) in lung adenocarcinoma (LUAD). Methods: Bioinformatics and experimental validation confirmed MECOM expression levels in LUAD. The value of MECOM was analyzed by receiver operating characteristic (ROC) curve and Cox regression analysis. Results: Serum MECOM levels were lower in LUAD and correlated with gender, TNM stage, tumor size, lymph node metastasis and distant metastasis. The ROC curve showed that the area under the curve of MECOM was 0.804 for LUAD and, of note, could reach 0.889 for advanced LUAD; specificity was up to 90%. Conclusion: MECOM may contribute to independently identifying LUAD patients, particularly in advanced stages.

Lung adenocarcinoma is a common type of lung cancer with a high incidence and death rate. However, clinical indicators that effectively identify lung adenocarcinoma patients are still lacking. The protein encoded by the MECOM gene is a DNA-binding protein regulating gene expression, which has been found to play a cancer-promoting role in many cancers, but we found that it may play a cancer-suppressing role in lung adenocarcinoma. This study aimed to confirm whether MECOM can be a predictor for lung adenocarcinoma. Our results showed that lung adenocarcinoma patients had lower serum MECOM levels than healthy people, and patients with lower MECOM levels had a shorter survival rate. That is, patients with lower serum MECOM levels may indicate a high risk of developing lung adenocarcinoma and death. Thus, the MECOM gene is expected to be a predictor associated with the risk of developing lung adenocarcinoma and death.

Diagnostic value of cerebrospinal fluid human epididymis protein 4 for leptomeningeal metastasis in lung adenocarcinoma.

Background: The diagnosis of lung adenocarcinoma (LUAD) leptomeningeal metastasis (LM) remains a clinical challenge. Human epididymis protein 4 (HE4) functions as a novel tumor biomarker for cancers. This study aimed to assess the diagnostic value of cerebrospinal fluid (CSF) HE4, and combined with CEACAM6, for LUAD LM. Methods: The CSF HE4 protein level was measured in two independent cohorts by electrochemiluminescence. Test cohort included 58 LUAD LM patients, 22 LUAD patients without LM (Wiot-LM), and 68 normal controls. Validation cohort enrolled 50 LUAD LM patients and 40 normal controls, in parallel with Wiot-LM patients without brain metastases (19 Wiot-LM/BrM patients) or with BrM (26 BrM patients). The CSF level of CEA, CA125, CA153, CA199, CA724, NSE and ProGRP of these samples was measured by electrochemiluminescence, whereas the CSF CEACAM6 level was detected by enzyme-linked immunosorbent assay (ELISA). In addition, the serum level of these biomarkers was detected by same method as CSF. Results: The level of HE4 or CEACAM6 in CSF samples from LUAD LM patients was significantly higher than those from normal controls and Wiot-LM patients. The HE4 or CEACAM6 level in CSF was higher than that in serum of LM patient. The CSF HE4 or CEACAM6 level for distinguished LM from Wiot-LM showed good performance by receiver-operating characteristic analysis. The better discriminative power for LM was achieved when HE4 was combined with CEACAM6. In addition, the CSF HE4 and CEACAM6 level showed little or no difference between Wiot-LM/BrM and BrM patients, the BrM would not significantly influence the HE4 or CEACAM6 level in CSF. The diagnostic power of CSF CA125, CA153, CA199, CA724, NSE and ProGRP for LUAD LM were not ideal. Conclusion: The combination with HE4 and CEACAM6 has the promising application for the diagnosis of LUAD LM.