Diagnosis Of Lung Adenocarcinoma Research Articles

Comprehensive analysis identifies YKT6 as a potential prognostic and diagnostic biomarker in lung adenocarcinoma

BackgroundLung cancer is the most common cause of cancer-related death worldwide. The most prevalent histological subtype of lung cancer is lung adenocarcinoma (LUAD), with incidence rising each year. Treating LUAD remains a significant issue due to a lack of early diagnosis and poor therapy outcomes. YKT6 is a member of the SNARE protein family, whose clinical value and biological function in LUAD has yet to be established.MethodsTCGA, HPA and UALCAN were used to analyze YKT6 mRNA and protein levels, the correlation between YKT6 expression and clinicopathological features and prognosis. YKT6 mRNA and protein expression were verified by qRT-PCR, immunohistochemistry (IHC) and tissue microarrays (TMA). Additionally, lung cancer cell lines were chosen for YKT6 silencing to explore the effects on cell proliferation and migration. The cBioPortal was used to select YKT6-related genes. Protein-protein interaction (PPI) network was created based on STRING database and hub genes were screened, with their expression levels and prognosis values in LUAD analyzed accordingly. YKT6-related genes were enriched by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses.ResultsIn LUAD, YKT6 was distinctly highly expressed with relation to clinical features of staging, smoking, lymph node metastasis, and TP53 mutation. Elevated YKT6 expression was linked to adverse prognosis, serving as an independent unfavorable prognostic factor. Moreover, YKT6 presented high diagnostic value in LUAD patients (AUC = 0.856). Experimental validation indicated that freshly collected LUAD tissues showed significantly high mRNA expression of YKT6. IHC and TMA verified increased YKT6 protein level in LUAD. Knockdown of YKT6 inhibited cell proliferation and promoted apoptosis, with mitigated capability of migration and invasion. The top ten hub genes screened by PPI network were highly expressed in LUAD, and significantly associated with poor prognosis. GO and KEGG analyses showed that YKT6-related genes were mainly involved in cell cycle.ConclusionElevated YKT6 expression is related to poor prognosis of LUAD patients. YKT6 can serve as a novel biomarker for LUAD diagnosis and prognosis. Cell proliferation, migration and invasion was impaired with increased apoptosis upon YKT6 silencing in lung cancer cells. In summary, this study comprehensively uncovered that YKT6 could be identified as a potential prognostic and diagnostic biomarker in LUAD.

7639 A Rare Cause of Lung Adenocarcinoma with Metastasis to the Thyroid

Abstract Disclosure: E. Echevarria-Torres: None. C.G. Yap: None. K.E. Izuora: None. A rare cause of lung adenocarcinoma with metastasis to the thyroid. Metastasis to the thyroid gland from non-thyroid malignancies is rare. When metastasis occurs, presenting symptoms are typically nonspecific, representing a diagnostic challenge. With the goal of raising awareness, we present a case of lung adenocarcinoma with metastasis to the thyroid. An 85-year-old man with a history of hypertension, hyperlipidemia and 60 years smoking history presented to the endocrine clinic for evaluation of subclinical hyperthyroidism. On the physical exam, there was fullness in the right thyroid area which on ultrasound showing a large right thyroid nodule occupying the entire lobe. There was also a solid 4.5 cm x 3.4 cm x 4.6 cm nodule in the mid-anterior left thyroid lobe. Fine needle aspiration cytology of right nodule revealed malignant cells and cell block material positive for TTF-1 (Thyroid Transcription Factor 1) concerning for malignancy. The left thyroid nodule cytology was consistent with benign follicular nodule. Chest CT ordered for surgical planning showed right upper lobe pleural-based lung opacity measuring 3.7 cm x 2.9 cm with supra clavicular lymphadenopathy. Biopsy of lung mass and supra clavicular lymph nodes revealed primary lung adenocarcinoma involving the lymph nodes consistent with stage Iva (cT3NxM1b). The patient was referred to oncology for further management. Discussion: Metastatic lesions to the thyroid gland account for less than 1 % of all malignant thyroid tumors with most cases found on autopsy. This is hypothesized to be due to the rich blood supply and high iodine content of the thyroid gland. Thyroid metastasis usually presents several years after initial diagnosis and treatment of non- thyroid malignancy. Patients can present with enlarging thyroid nodules, neck swelling, dysphagia and, in rare instances, upper airway obstruction. We present a rare case of lung cancer with metastasis into the thyroid. The thyroid nodule initially palpated upon physical exam led to eventual thyroid ultrasound and subsequently to his diagnosis of lung adenocarcinoma after findings of lung nodule which was biopsied and showed primary lung adenocarcinoma. TTF-1 was also positive which is typically expressed by lung adenocarcinomas. Treatment for thyroid metastasis is surgery, along with treatment of primary malignancy. The earlier the diagnosis and treatment the more favorable the prognosis. Radiotherapy and chemotherapy are other means to reduce the recurrence. Thyroid hormone replacement will be warranted post operatively for hypothyroidism. We present this uncommon case to raise awareness about the presentation of thyroid metastasis to enhance timely diagnosis and intervention. Presentation: 6/1/2024

9388 Unusual Case Of Ectopic Adrenocorticotropic Hormone Syndrome Secondary To Non-small Cell Lung Cancer

Abstract Disclosure: A. TakallooBakhtiari: None. G.L. Nunlee-Bland: None. V. Ganta: None. A. Zenebe: None. H. Abdalla: None. A. Elobeid: None. W.A. Odonkor: None. Introduction: Ectopic adrenocorticotropic hormone syndrome (EAS) is a rare condition due to adrenocorticotropic hormone (ACTH) release from non-pituitary tumors. It increases the mortality of affected patients thus finding and removal of the ACTH-producing source allows for curing or reduction of symptoms and serum cortisol levels. The most common cause of EAS is lung cancer. Cushing syndrome (CS) due to EAS is an uncommon paraneoplastic phenomenon in non-small cell lung cancer. Clinical case: The patient is an 80-year-old man with a past medical history of hypertension, dementia, stroke, schizophrenia, and recently diagnosed lung adenocarcinoma. He presented with a few weeks history of dysuria and generalized fatigue. There was no family history for any endocrine disorders. He has a 40 pack-year history of tobacco use. He denied alcohol or illicit drug use. Upon initial evaluation, VS: BP 155/95 mmHg, HR 82 beats/min, Ht 77 inches, Wt 125 lb with a BMI 14.7 Kg/m2. He had no typical symptoms of CS. A physical exam showed a cachectic man with no other remarkable findings. Laboratory tests on admission showed severe hypokalemia of 1.8 mEq/L (3.5-5 mEq/L) with hypochloremic metabolic alkalosis. (bicarbonate 45 mEq/L (22-28 mEq/L) and chloride 79 mEq/L (96-106 mEq/L)). Patient was normoglycemic with HbA1c of 5.0%. Random morning cortisol was 55 μg/dL (13-24 μg/dL). Supine renin and aldosterone levels were 0.45 ng/ml/h (0.25-5.8 ng/ml/h) and 1.0 ng/dL (3-16 ng/dL), respectively, excluding hyperaldosteronism. Beside urinary tract infection, other biochemical workup revealed elevated 24-h urinary free cortisol level 5233 mcg/24h (4.0-50.0 mcg/24h) with creatinine 0.7 g/24h (0.5-2.15 g/24h). Failure to suppress cortisol with low dose dexamethasone suppression test (LDDST) was evident: morning cortisol >60.0 g/dL , with concurrent serum dexamethasone 299 ng/dL (180-550 ng/dL). Plasma ACTH level was elevated 327 pg/ml (6-50 pg/ml), favoring ACTH-dependent CS. A magnetic resonance imaging (MRI) of the sella and computed tomography (CT) of the abdomen did not show pituitary or adrenal masses. Therefore, a diagnosis of ectopic CS due to lung cancer was established. Pathology of the lung mass showed tumor cells were negative for synaptophysin, chromogranin, and CD52. The immunohistochemically findings support primary adenocarcinoma of the lung. Patient refused surgical or medical treatment and was discharged to a hospice facility. Conclusion: The clinical presentation of EAS ranges from the abrupt onset of the signs and symptoms of severe hypercortisolism, including hypertension, hypokalaemia, metabolic alkalosis as in our patient to the gradual and slow onset of the classical signs and symptoms of CS. Though EAS with adenocarcinoma of the lung is rare, it is important to consider it within the differential diagnosis of any adenocarcinoma of the lung presenting with the relevant symptoms. Presentation: 6/3/2024

A Risk Model Developed based on Homologous Recombination Deficiency Genes for Evaluating the Drug Sensitivity and Prognostic Prediction of Lung Adenocarcinoma.

This study was designed to construct a risk model based on homologous recombination deficiency (HRD) to evaluate the prognosis and drug sensitivity for patients with lung adenocarcinoma (LUAD). LUAD is a subtype of lung cancer with unfavorable overall survival (OS) and prognosis. HRD has been widely studied in various tumors, but its role in LUAD has not been fully understood. We aimed to construct an HRD-related risk model for predicting the prognosis and drug sensitivity of patients with LUAD. Gene expression data of the LUAD samples were collected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We extracted HRD genes from previous literature and performed univariate COX analysis to select those closely associated with LUAD prognosis. ConsensusClusterPlus was employed to stratify the samples in the TCGA-LUAD cohort into different subtypes. A RiskScore model was established applying random forest method. Furthermore, immunotherapy response and drug sensitivity were predicted using Tumor Immune Dysfunction and Exclusion (TIDE) software and pRRophytic R package, respectively. Finally, the clinical features between High- and Low- RiskScore groups were compared. A total of 16 HRD genes relevant to LUAD prognosis were selected and used to classify 3 LUAD clusters (C1, C2, and C3). Specifically, C1, with a lower TIDE score displayed higher immune infiltration and immunotherapy benefit and the optimal OS, while C2 was closely correlated with tumor-relevant pathways and had the worst OS. Finally, 4 HRD genes (RAD51AP1, BRCA1, H2AFX, and FANCL) were determined to develop a RiskScore signature. It was found that a higher RiskScore was related to more advanced stages, worse OS, and tumor development pathways. Additionally, the High-RiskScore group with a higher TIDE score was sensitive to 44 traditional chemotherapy drugs. A nomogram combined with RiskScore exhibited an accurate survival prediction ability. The HRD-based RiskScore played a crucial role in LUAD development, showing a strong potential to serve as a prognostic indicator for LUAD. Our findings contributed to the diagnosis of LUAD and its treatment.

Development and validation of machine learning models for diagnosis and prognosis of lung adenocarcinoma, and immune infiltration analysis.

The aim of our study was to develop robust diagnostic and prognostic models for lung adenocarcinoma (LUAD) using machine learning (ML) techniques, focusing on early immune infiltration. Feature selection was performed on The Cancer Genome Atlas (TCGA) data using least absolute shrinkage and selection Operator (LASSO), random forest (RF), and support vector machine (SVM) algorithms. Six ML algorithms were employed to construct the diagnostic models, which were evaluated through receiver operating characteristic (ROC) curves, precision-recall curves (PRC), and classification error (CE), and validated on the GSE7670 dataset. Additionally, a lasso cox prognostic model was built on the TCGA-LUAD dataset and externally validated using independent Gene Expression Omnibus datasets (GSE30219, GSE31210, GSE50081, and GSE37745). Single-sample gene set enrichment analysis (ssGSEA) was performed to assess immune cell infiltration in stage I LUAD samples, revealing significant differences in immune cell types. These findings demonstrate a positive correlation between immune infiltration in stage I LUAD and Th2 cells, Tcm cells, and T helper cells, while a negative correlation was observed with Macrophages, Eosinophils, and Tem cells. These insights provide novel perspectives for clinical diagnosis and treatment of LUAD.

SMARCA4 mutations and expression in lung adenocarcinoma: prognostic significance and impact on the immunotherapy response.

The switch/sucrose non-fermenting (SWI/SNF) complex family includes important chromatin-remodeling factors that are frequently mutated in lung adenocarcinoma (LUAD). However, the role of one family member, SMARCA4, in LUAD prognosis and immunotherapy sensitivity remains unclear. In the present study, 6745 LUAD samples from the cBioPortal database were used to analyze the relationships between SMARCA4 mutations and patient prognoses and clinical characteristics. Additionally, we examined the correlation between SMARCA4 mutations and prognosis in patients treated with immunotherapy using two immune-related datasets. SMARCA4 mutations and low expression were associated with shorter survival, and mutations were associated with a high tumor mutational burden and high microsatellite instability. SMARCA4 mutations were accompanied by KRAS, KEAP1, TP53 and STK11 mutations. No significant difference was observed in the immunotherapy response between patients with and without SMARCA4 mutations. When KRAS or STK11 mutations were present, immunotherapy effectiveness was poorer; however, when both SMARCA4 and TP53 mutations were present, immunotherapy was more effective. Furthermore, low SMARCA4 expression predicted a higher immunophenoscore, and SMARCA4 expression was correlated with certain immune microenvironment features. Taken together, our results suggest that SMARCA4 mutations and low expression might be associated with poor LUAD prognosis. Additionally, immunotherapy efficacy in patients with SMARCA4 mutations depended on the co-mutant genes. Thus, SMARCA4 could be an important factor to be considered for LUAD diagnosis and treatment.

FP7.3 - Acute Appendicitis and Lung Metastasis – A rare combination

Abstract Background Lung cancer is the third most common cancer in the UK. Although widespread metastasis is common, metastasis to the appendix is rare. Here we present a case of acute appendicitis secondary to lung metastasis. Case Presentation An 84-year-old man was admitted with a two-day history of right iliac fossa and suprapubic pain. He was known to have previous lung cancer treated with radical radiotherapy. Bloods on admission revealed elevated inflammatory markers with WCC 14.73 x 109/L and CRP 71.1mg/L. A Computed tomography was performed which showed acute appendicitis with perforation. An emergency laparoscopic appendicectomy was performed which showed a mid-appendiceal perforation with a localized abscess cavity. His recovery was uneventful, and the patient was discharged on postoperative day 2. Histological analysis revealed an adenocarcinoma in the appendicular lumen and within the muscle wall extending to the serosal surface. Immunochemistry profile was positive for CK, CK-19, TTF1 and Napsin A favoring a diagnosis of lung adenocarcinoma which was rationalized in the lung MDT. The patient remains under the respiratory physicians for close follow up. Discussion Lung metastasis to the appendix causing acute appendicitis is uncommon, with only twelve cases of appendiceal metastasis reported in the literature, ten of which presented with a perforated appendix. It may be considered as a differential for the cause of perforated acute appendicitis especially in patients with background of lung cancer.

Expression of GPR56 reflects a hypoactivated state of circulating B cells and is downregulated in B cell subsets in patients with early-stage lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most prevalent subtype of lung cancer, and the early detection and diagnosis of this disease are crucial in reducing mortality rates. The timely diagnosis of LUAD is essential for controlling tumour development and enabling early surgical treatment. GPR56 is a vital G protein-coupled receptor and its role in T lymphocytes has received considerable attention. However, its function in B cells remains unclear. This study aimed to investigate the significance of GPR56 in LUAD. We found that GPR56 exhibited a significant increase in circulating plasmablasts and a decrease in new memory B cells. GPR56 expression in B cells was significantly reduced after LPS stimulation and the proportion of HLA-DR+ and CD40+ proportions were also decreased in GPR56+ B cells after stimulation. Additionally, GPR56 exhibited significant down-regulation in circulating B cell subsets of early-stage LUAD patients, and there were significant correlations between GPR56+ B cell subsets and tumour markers. In conclusion, GPR56 could reflect the hypoactivation state of B cells and the decreased proportion of GPR56+ B cell subset in LUAD patients can signify the active humoral immunity in vivo. The expression of GPR56 in B cells could potentially hold value in the early diagnosis of LUAD.

LungPath: artificial intelligence-driven histologic pattern recognition for improved diagnosis of early-stage invasive lung adenocarcinoma.

Early-stage invasive lung adenocarcinoma (ADC) characterized by a predominant micropapillary or solid pattern exhibit an elevated risk of recurrence following sub-lobar resection, thus determining histological subtype of early-stage invasive ADC prior surgery is important for formulating lobectomy or sub-lobar resection. This study aims to develop a deep learning algorithm and assess its clinical capability in distinguishing high-risk or low-risk histologic patterns in early-stage invasive ADC based on preoperative computed tomography (CT) scans. Two retrospective cohorts were included: development cohort 1 and external test cohort 2, comprising patients diagnosed with T1 stage invasive ADC. Electronic medical records and CT scans of all patients were documented. Patients were stratified into two risk groups. High-risk group: comprising cases with a micropapillary component ≥5% or a predominant solid pattern. Low-risk group: encompassing cases with a micropapillary component <5% and an absence of a predominant solid pattern. The overall segmentation model was modified based on Mask Region-based Convolutional Neural Network (Mask-RCNN), and Residual Network 50 (ResNet50)_3D was employed for image classification. A total of 432 patients participated in this study, with 385 cases in cohort 1 and 47 cases in cohort 2. The fine-outline results produced by the auto-segmentation model exhibited a high level of agreement with manual segmentation by human experts, yielding a mean dice coefficient of 0.86 [95% confidence interval (CI): 0.85-0.87] in cohort 1 and 0.84 (95% CI: 0.82-0.85) in cohort 2. Furthermore, the deep learning model effectively differentiated the high-risk group from the low-risk group, achieving an area under the curve (AUC) of 0.89 (95% CI: 0.88-0.90) in cohort 1. In the external validation conducted in cohort 2, the deep learning model displayed an AUC of 0.87 (95% CI: 0.84-0.88) in distinguishing the high-risk group from the low-risk group. The average diagnostic time was 16.00±3.2 seconds, with an accuracy of 0.82 (95% CI: 0.81-0.83). We have developed a deep learning algorithm, LungPath, for the automated segmentation of pulmonary nodules and prediction of high-risk histological patterns in early-stage lung ADC based on CT scans.

Deciphering Dormant Cells of Lung Adenocarcinoma: Prognostic Insights from O-glycosylation-Related Tumor Dormancy Genes Using Machine Learning.

Lung adenocarcinoma (LUAD) poses significant challenges due to its complex biological characteristics and high recurrence rate. The high recurrence rate of LUAD is closely associated with cellular dormancy, which enhances resistance to chemotherapy and evasion of immune cell destruction. Using single-cell RNA sequencing (scRNA-seq) data from LUAD patients, we categorized the cells into two subclusters: dormant and active cells. Utilizing high-density Weighted Gene Co-expression Network Analysis (hdWGCNA) and pseudo-time cell trajectory, aberrant expression of genes involved in protein O-glycosylation was detected in dormant cells, suggesting a crucial role for O-glycosylation in maintaining the dormant state. Intercellular communication analysis highlighted the interaction between fibroblasts and dormant cells, where the Insulin-like Growth Factor (IGF) signaling pathway regulated by O-glycosylation was crucial. By employing Gene Set Variation Analysis (GSVA) and machine learning, a risk score model was developed using hub genes, which showed high accuracy in determining LUAD prognosis. The model also demonstrated robust performance on the training dataset and excellent predictive capability, providing a reliable basis for predicting patient clinical outcomes. The group with a higher risk score exhibited a propensity for adverse outcomes in the tumor microenvironment (TME) and tumor mutational burden (TMB). Additionally, the 50% inhibitory concentration (IC50) values for chemotherapy exhibited significant variations among the different risk groups. In vitro experiments demonstrated that EFNB2, PTTG1IP, and TNFRSF11A were upregulated in dormant tumor cells, which also contributed greatly to the diagnosis of LUAD. In conclusion, this study highlighted the crucial role of O-glycosylation in the dormancy state of LUAD tumors and developed a predictive model for the prognosis of LUAD patients.

Lung adenocarcinoma size as a predictor of distant metastasis: A CT scan-based measurement.

Previous studies have associated tumor size with metastasis and prognosis in lung carcinoma; however, a precise cut-off for predicting distant metastasis in lung adenocarcinoma remains unclear. The aim of this study was to determine the cut-off point for predicting distant metastasis in lung adenocarcinoma. A cross-sectional study was conducted at Dr. Moewardi Hospital, Surakarta, Indonesia, from January 2022 to September 2023. Total sampling was employed, involving patients over 18 years old with a confirmed diagnosis of lung adenocarcinoma based on lung computed tomography (CT) scan findings, who had not yet received chemotherapy and had confirmed metastasis outside the lung. The study's dependent variable was the incidence of distant metastasis, while the independent variable was lung adenocarcinoma size. Two experienced thoracic radiologists measured lung adenocarcinoma size by assessing the longest axis using chest multi-slice computed tomography (MSCT) in the lung window setting. Receiver operating characteristic (ROC) curve analysis determined the optimal tumor size cut-off for predicting distant metastasis. Of 956 thoracic cancer patients, 108 were diagnosed with lung adenocarcinoma. After applying the inclusion and exclusion criteria, 89 patients were eligible. In the present study, tumor size predicted 68.1% of distant metastasis cases, with a cut-off point of 7.25 cm, yielding a sensitivity of 61.9% and a specificity of 61.5%. Tumors >7.25 cm had a 2.60-fold higher risk of distant metastasis compared to smaller tumors, with larger tumors more likely to spread to various sites. In conclusion, lung adenocarcinomas larger than 7.25 cm have a 2.60-fold increased risk of distant metastasis, making tumor size a crucial predictive factor. The study provides valuable insights for radiologists and can improve diagnosis accuracy and treatment planning by emphasizing tumor size as a key factor in managing lung adenocarcinoma.

Isolated Monoclonal T-Cell Receptor Gene Rearrangement in a Lung Adenocarcinoma Harboring MET Exon 14 Skipping: Diagnostic Pitfall.

In the diagnostic workup of poorly differentiated tumors, T-cell receptor (TCR) clonality has long been considered as evidence of T-cell lymphoma. MET exon 14 skipping (METex14) is a mutation typically seen in lung adenocarcinoma. Herein, we present the first report of METex14 lung adenocarcinoma with isolated monoclonal TCRγ gene rearrangement. A 69-year-old woman presented to an outside hospital with pleural effusions. A pleural decortication demonstrated malignant cells positive for CD30 and CD138 but negative for BerEP4, KRT5, and EMA. An equivocal HHV8 staining was interpreted as positive, leading to the erroneous outside diagnosis of primary effusion lymphoma. Additional workup at our institution revealed a lack of HHV8 and T-cell markers but the presence of TCRγ clonality, pankeratin, and TTF1 expression. Repeat TCRγ testing on the in-house biopsy was negative for clonality. Next-generation sequencing detected METex14, confirming the diagnosis of lung adenocarcinoma. The potential diagnostic pitfall and prognostic/predictive implications are discussed.

SGPP2 is activated by SP1 and promotes lung adenocarcinoma progression

The late diagnosis and easy metastasis of lung adenocarcinoma (LADC) remains a challenge. SGPP2 is reported to modulate cell processes in many cancers. However, the roles and molecular mechanisms of SGPP2 in LADC are unclear. Online bioinformatics tools GEPIA, CPTAC, and K-M plotter were used to analyze the expression of SGPP2 and the prognosis in LADC. JASPAR and PROMO were used to predict the transcription factors of SGPP2. Real-time quantitative reverse transcription PCR and western blot were used to detect the levels of SGPP2 in LADC cell lines and tissues. Cell counting kit-8, colony formation, flow cytometry, and transwell assay were used to detect cell proliferation, apoptosis, and invasion. The anti-cancer effect of SGPP2 silence was evaluated in the LADC xenograft model. It was found that SGPP2 was highly expressed and related to the poor prognosis of LADC patients. Elevated SGPP2 expression was detected in LADC cell lines and tissues. The chi-square test indicated that the expression of SGPP2 was positively related to tumor, node, metastasis grades and lymph node metastasis. Knocking down SGPP2 significantly inhibited LADC cell viability, and invasion, but induced apoptosis. The anti-tumor effects of SGPP2 were verified in vivo. The upstream transcription factor of SGPP2 was predicted to be SP1, which was highly expressed in LADC tissues and cell lines. Overexpression of SP1 partly rescued the inhibition of SGPP2-shRNA in cell growth, colony formation, and invasion capabilities, and decreased apoptotic cell number in LADC cells. This study demonstrated that SGPP2, activated by SP1, promotes LADC cell proliferation and invasion, and suppresses apoptosis in LADC.

Predictive role and molecular biological function of proline-rich small repeat protein SPRR3 in the diagnosis of lung adenocarcinoma

The fascinating role of SPRR3 in various malignant tumors has prompted extensive research to unravel its expression patterns and prognostic significance. To comprehensively investigate SPRR3, we leveraged multiple datasets containing invaluable biomedical information, specifically focusing on the comparative analysis of SPRR3 gene expression levels across different cancer types. Meticulous examination of lung adenocarcinoma allowed us to delve deeper into the correlation between SPRR3 expression and its molecular biological functions. Our comprehensive analysis encompassed 33 malignant tumors, and the results unveiled significant differential expression of SPRR3 across a range of malignancies. Moreover, this aberrant expression of SPRR3 was observed to be closely associated with poorer prognosis in these malignant tumors. Notably, our investigation also unearthed a compelling link between SPRR3 and immune infiltrating cells in lung adenocarcinoma. The utilization of receiver operating characteristic (ROC) curves and survival curves in our study illustrated the immense potential of SPRR3 as a highly accurate predictor of cancer. These findings further emphasize the possibility of SPRR3 serving as a promising diagnostic and prognostic biomarker for a diverse array of cancers.

Prediction of lung adenocarcinoma prognosis and diagnosis with a novel model anchored in circadian clock-related genes

Lung adenocarcinoma is the most common primary lung cancer seen in the world, and identifying genetic markers is essential for predicting the prognosis of lung adenocarcinoma and improving treatment outcomes. It is well known that alterations in circadian rhythms are associated with a higher risk of cancer. Moreover, circadian rhythms play a regulatory role in the human body. Therefore, studying the changes in circadian rhythms in cancer patients is crucial for optimizing treatment. The gene expression data and clinical data were sourced from TCGA database, and we identified the circadian clock-related genes. We used the obtained TCGA-LUAD data set to build the model, and the other 647 lung adenocarcinoma patients’ data were collected from two GEO data sets for external verification. A risk score model for circadian clock-related genes was constructed, based on the identification of 8 genetically significant genes. Based on ROC analyses, the risk model demonstrated a high level of accuracy in predicting the overall survival times of lung adenocarcinoma patients in training folds, as well as external data sets. This study has successfully constructed a risk model for lung adenocarcinoma prognosis, utilizing circadian rhythm as its foundation. This model demonstrates a dependable capacity to forecast the outcome of the disease, which can further guide the relevant mechanism of lung adenocarcinoma and combine behavioral therapy with treatment to optimize treatment decision-making.

SLC4A4 as a novel biomarker involved in immune system response and lung adenocarcinoma progression

BackgroundAltered expression and activity of solute carrier family 4 member 4 (SLC4A4) could affect the growth, survival and metastasis of tumor cells. Currently, the role of SLC4A4 in lung adenocarcinoma (LUAD) immunotherapy and prognosis was not entirely clear. MethodsWe analyzed SLC4A4 expression in LUAD tissues and cell lines using quantitative reverse transcription-polymerase chain reaction, Western blotting, and immunohistochemistry. The effects of SLC4A4 overexpression on angiogenesis, cell migration, invasion, and epithelial-mesenchymal transition were examined. Public databases helped construct a risk model evaluating SLC4A4′s expression on LUAD prognosis and immunotherapy response. Additionally, a xenograft model, flow cytometry, and enzyme-linked immunosorbent assay further explored SLC4A4′s role in tumor immune microenvironment infiltration. ResultsUpregulation of SLC4A4 promoted apoptosis in the LUAD cell line and significantly inhibited the migration and invasive ability of cancer cells (P<0.01). A total of 10 key genes (including SIGLEC6, RHOV, PIR, MOB3B, MIR3135B, LPAR6, KRT8, ITGA2, CPS1, and C6) were screened according to SLC4A4 expression, immune score and stromal score, and a prognostic model with good outcome was constructed (AUC values of which in the training cohort at 1,3, and 5 years reached 0.73, 0.73, and 0.72, respectively). Importantly, we demonstrated that high expression of SLC4A4 was able to increase the proliferation level and cytokine secretion of CD8+ T cells for the purpose of promoting the immune system response to LUAD. ConclusionOur study revealed that SLC4A4 can serve as a prognostic indicator for LUAD, providing new insights into the treatment and diagnosis of LUAD.

DNA methylation analysis in plasma for early diagnosis in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) represents the most prevalent type of lung cancer. SHOX2 and RASSF1A methylation have been identified as important biomarkers for diagnosis and prognosis of lung cancer. Bronchoalveolar lavage fluid (BALF) exhibits good specificity and sensitivity in diagnosing pulmonary diseases, but its acquisition is challenging and may cause discomfort to patients. In clinical, plasma samples are more convenient to obtain than BALF; however, there is little research on the concurrent detection of SHOX2 and RASSF1A methylation in plasma. This study aims to assess the diagnostic value of a combined promoter methylation assay for SHOX2 and RASSF1A in early-stage LUAD using plasma samples. BALF and blood samples were obtained from 36 early-stage LUAD patients, with a control group of nineteen non-tumor individuals. The promoter methylation levels of SHOX2 and RASSF1A in all subjects were assessed using the human SHOX2 and RASSF1A gene methylation kit. The methylation detection rate of SHOX2 and RASSF1A in plasma was 61.11%, slightly lower than that in BALF (66.7%). The Chi-square test revealed no significant difference in the methylation rate between BALF and plasma (P > 0.05). The area under the receiver operating characteristic (ROC) curve analysis for blood was 0.806 (95% CI, 0.677 to 0.900), while for BALF it was 0.781 (95% CI, 0.649 to 0.881). Additionally, we conducted an analysis on the correlation between SHOX2 and RASSF1A methylation levels in plasma with gender, age, tumor differentiation, pathologic classification, and other clinicopathological variables; however, no significant correlations were observed. Measurement of SHOX2 and RASSF1A methylation for early diagnosis of LUAD can be achieved with high sensitivity and specificity by using plasma as a substitute for BALF samples.

PP01.66 An unusual presentation and delayed diagnosis of multifocal lung adenocarcinoma

PP01.66 An unusual presentation and delayed diagnosis of multifocal lung adenocarcinoma

Plasma GPI and PGD are associated with vascular normalization and may serve as novel prognostic biomarkers for lung adenocarcinoma: Multi-omics and multi-dimensional analysis

The aim of this study was to explore potential novel plasma protein biomarkers for lung adenocarcinoma (LUAD). A plasma proteomics analysis was carried out and candidate protein biomarkers were validated in 102 LUAD cases and 102 matched healthy controls. The same LUAD tumor tissues were detected to explore the correlation between the expression of candidate proteins in tissues and plasma and vascular normalization. A LUAD active metastasis mice model was constructed to explore the role of candidate proteins for lung metastasis. GPI and PGD were verified to be upregulated in plasma from LUAD patients, and the expression of GPI in tumor tissue was positively correlated with the expression of GPI in plasma and negatively correlated with the normalization of tumor blood vessels. Meanwhile, a negative correlation between the expression of GPI and PGD in plasma and tumor vascular normalization was discovered. In the LUAD active metastasis model, the lowest levels of vascular normalization and the highest expression of GPI and PGD were found in mice with lung metastases. This study found that GPI and PGD may be potential plasma biomarkers for LUAD, and monitoring those may infer the risk of metastasis and malignancy of the tumor. SignificantWe identified GPI and PGD as potential novel diagnostic and prognostic biomarkers for LUAD. PGD and GPI can be used as diagnostic biomarkers in combination with other available strategies to assist in the screening and diagnosis of LUAD, and as prognostic biomarkers aid in predict the risk of tumor metastasis and malignancy in patients with LUAD.

Ultrasensitive PD-L1-Expressing Exosome Immunosensors Based on a Chemiluminescent Nickel–Cobalt Hydroxide Nanoflower for Diagnosis and Classification of Lung Adenocarcinoma

Ultrasensitive PD-L1-Expressing Exosome Immunosensors Based on a Chemiluminescent Nickel–Cobalt Hydroxide Nanoflower for Diagnosis and Classification of Lung Adenocarcinoma