Hepatoid adenocarcinoma of the lung:A case report

BACKGROUND Hepatoid adenocarcinoma of the lung(HAL)is a rare type of non-small cell lung cancer(NSCLC),histologically similar to hepatocellular carcinoma.HAL has high malignancy and poor prognosis,and a better treatment plan needs further study.CASE SUMMARY In order to deeply understand the occurrence and development of HAL,here we report a case of HAL with extensive metastasis of alpha fetoprotein negative KRAS A146T mutation.The patient refused chemotherapy and received one course of treatment(immune checkpoint inhibitors),and died three months later due to progressive disease.CONCLUSION HAL is a special type of NSCLC.The surgical treatment of HAL in the limited stage can achieve long-term survival,but most of them were in the advanced stage when they were found,and the prognosis was poor,which requires multidisciplinary comprehensive treatment.

Research progress on lung cancer stem cells in epidermal growth factor receptor–tyrosine kinase inhibitor targeted therapy resistance in lung adenocarcinoma

Lung cancer is the leading cause of cancer-related deaths globally.In recent years,with the widespread use of genetic testing,epidermal growth factor receptor–tyrosine kinase inhibitor(EGFR-TKI)–targeted drugs have been efficacious to patients with lung adenocarcinoma exhibiting EGFR mutations.However,resistance to treatment is inevitable and eventually leads to tumor progression,recurrence,and reduction in the overall treatment efficacy.Lung cancer stem cells play a crucial role in the development of resistance toward EGFR-TKI–targeted therapy for lung adenocarcinoma.Lung cancer stem cells possess self-renewal,multilineage differentiation,and unlimited proliferation capabilities,which efficiently contribute to tumor formation and ultimately lead to tumor recurrence andmetastasis.In this study,we evaluated the origin,markers,stemness index,relevant classic studies,resistance mechanisms,related signaling pathways,and strategies for reversing lung cancer stem cell resistance to EGFR-TKIs to provide new insights on delaying or reducing resistance and to improve the treatment efficacy of patients with EGFR-mutated lung adenocarcinoma in the future.

Advanced Lung Adenocarcinoma with EGFR 19-del Mutation Transformed into SCC after EGFR-tyrosine Kinase inhibitors Treatment:A Case report

BACKGROUND Epidermal growth factor receptor tyrosine kinase inhibitors(EGFR-TKIs)significantly improve the survival of patients with Epidermal growth factor receptor(EGFR)sensitive mutations in non-small cell lung cancer(NSCLC).CASE SUMMARY A 67-year-old female patient in advanced lung adenocarcinoma suffered from drug resistance after EGFR-TKIs treatment.Secondary pathological tissue biopsy confirmed squamous cell carcinoma(SCC)transformation.Patients inevitably encountered drug resistance issues after receiving EGFR-TKIs treatment for a certain period of time,while EGFR-TKIs can significantly improve the survival of patients with EGFR-sensitive mutations in NSCLC.Notably,EGFR-TKIs resistance includes primary and acquired.Pathological transformation is one of the mechanisms of acquired resistance in EGFR-TKIs,with SCC transformation being relatively rare.Our results provide more detailed results of the patient’s diagnosis and treatment process on SCC transformation after EGFR-TKIs treatment for lung adenocarcinoma.CONCLUSION Squamous cell carcinoma transformation is one of the acquired resistance mechanisms of EGFR-TKIs in advanced lung adenocarcinoma with EGFR mutations.

miR-125b reverses cisplatin resistance by regulating autophagy via targeting RORA/BNIP3L axis in lung adenocarcinoma

The platinum-based chemotherapy is one of the most frequently used treatment protocols for lung adenocarcinoma(LUAD),and chemoresistance,however,usually results in treatment failure and limits its application in the clinic.It has been shown that microRNAs(miRNAs)play a significant role in tumor chemoresistance.In this study,miR-125b was identified as a specific cisplatin(DDP)-resistant gene in LUAD,as indicated by the bioinformatics analysis and the real-time quantitative PCR assay.The decreased serum level of miR-125b in LUAD patients was correlated with the poor treatment response rate and short survival time.MiR-125b decreased the A549/DDP proliferation,and the multiple drug resistance-and autophagy-related protein expression levels,which were all reversed by the inhibition of miR-125b.In addition,xenografts of human tumors in nude mice were suppressed by miR-125b,demonstrating that through autophagy regulation,miR-125b could reverse the DDP resistance in LUAD cells,both in vitro and in vivo.Further mechanistic studies indicated that miR-125b directly repressed the expression levels of RORA and its downstream BNIP3L,which in turn inhibited autophagy and reversed chemoresistance.Based on these findings,miR-125b in combination with DDP might be an effective treatment option to overcome DDP resistance in LUAD.

Lung adenocarcinoma with initial binocular symptoms

Dear Editor,Lung adenocarcinoma with choroidal metastasis is a common form of cancer,with breast cancer accounting for 40%-53%and lung cancer accounting for 20%-29%of primary cases with choroidal metastases[1].This type of metastatic cancer typically affects people aged 40-70y,and is more prevalent in women than men[1].Ocular symptoms,including vision loss,can be an early indication of the disease,as many tumors are asymptomatic in their early stages.Studies have shown that 40.3%of cases involve the macular region,which explains why ocular symptoms are often the first manifestation of the disease[2].When choroidal metastasis is suspected in patients without a history of cancer,a combination of diagnostic tools should be used to identify the primary source of the tumor.Choroidal tumors can serve as an indication of future lung cancer diagnosis in some patients with lung cancer[1].In this report,we present a case of bilateral lung adenocarcinoma where ocular symptoms were the first indication of the disease.

Leveraging diverse cell-death patterns to predict the clinical outcome of immune checkpoint therapy in lung adenocarcinoma:Based on muti-omics analysis and vitro assay

Advanced LUAD shows limited response to treatment including immune therapy.With the development of sequencing omics,it is urgent to combine high-throughput multi-omics data to identify new immune checkpoint therapeutic response markers.Using GSE72094(n=386)and GSE31210(n=226)gene expression profile data in the GEO database,we identified genes associated with lung adenocarcinoma(LUAD)death using tools such as“edgeR”and“maftools”and visualized the characteristics of these genes using the“circlize”R package.We constructed a prognostic model based on death-related genes and optimized the model using LASSO-Cox regression methods.By calculating the cell death index(CDI)of each individual,we divided LUAD patients into high and low CDI groups and examined the relationship between CDI and overall survival time by principal component analysis(PCA)and Kaplan-Meier analysis.We also used the“ConsensusClusterPlus”tool for unsupervised clustering of LUAD subtypes based on model genes.In addition,we collected data on the expression of immunomodulatory genes and model genes for each cohort and performed tumor microenvironment analyses.We also used the TIDE algorithm to predict immunotherapy responses in the CDI cohort.Finally,we studied the effect of PRKCD on the proliferation and migration of LUAD cells through cell culture experiments.The study utilized the TCGA-LUAD cohort(n=493)and identified 2,901 genes that are differentially expressed in patients with LUAD.Through KEGG and GO enrichment analysis,these genes were found to be involved in a wide range of biological pathways.The study also used univariate Cox regression models and LASSO regression analyses to identify 17 candidate genes that were best associated with mortality prognostic risk scores.By comparing the overall survival(OS)outcomes of patients with different CDI values,it was found that increased CDI levels were significantly associated with lower OS rates.In addition,the study used unsupervised cluster analysis to divide 115 LUAD patients into two distinct clusters with significant differences in OS timing.Finally,a prognostic indicator called CDI was established and its feasibility as an independent prognostic indicator was evaluated by Cox proportional risk regression analysis.The immunotherapy efficacy was more sensitive in the group with high expression of programmed cell death models.Relationship between programmed cell death(PCD)signature models and drug reactivity.After evaluating the median inhibitory concentration(IC50)of various drugs in LUAD samples,statistically significant differences in IC50 values were found in cohorts with high and low CDI status.Specifically,Gefitinib and Lapatinib had higher IC50 values in the high-CDI cohort,while Olaparib,Oxaliplatin,SB216763,and Axitinib had lower values.These results suggest that individuals with high CDI levels are sensitive to tyrosine kinase inhibitors and may be resistant to conventional chemotherapy.Therefore,this study constructed a gene model that can evaluate patient immunotherapy by using programmed cell death-related genes based on muti-omics.The CDI index composed of these programmed cell death-related genes reveals the heterogeneity of lung adenocarcinoma tumors and serves as a prognostic indicator for patients.

The Mechanism of Celastrol in the Treatment of Metastatic Lung Adenocarcinoma Revealed by Network Pharmacology and Molecular Docking

Background: Celastrol is an active ingredient extracted from Traditional Chinese Medicine (TCM), which can restrain the progression of lung cancer, whereas its underlying mechanism is unclear. In our study, the underlying mechanism of celastrol in the treatment of lung adenocarcinoma (LUAD) with metastasis was investigated by network pharmacology and molecular docking. Method: Potential targets of celastrol were collected from TCMSP, Batman-TCM and GeneCard database, and its potential targets were predicted using the STP platform and the TargetNet server. Metastasis marker genes (MGs) were obtained from the HCMDB. The genes correlated with LUAD were gathered from the GeneCard and OMIM database. And the common targets among celastrol potential targets, MGs and LUAD were analyzed. The protein-protein interaction (PPI) networks were obtained from the STRING database. SangerBox and the Xiantao bioinformatics tool were applied to visualize GO and KEGG analysis. Molecular docking tested the binding affinity between celastrol and core genes. Result: A total of 107 targets of celastrol against metastasis LUAD were obtained. The core targets were obtained from the PPI network, namely AKT1, JUN, MYC, STAT3, IL6, TNF, NFKB1, BCL2, IL1B, and HIF1A. GO and KEGG enrichment analysis indicated celastrol for the treatment of metastasis LUAD most refers to cellular response to chemical stress, DNA-binding transcription factor binding, transcription regulator complex and pathways in cancer. And some of these targets are associated with differential expressions and survival rates in LUAD. Moreover, Molecular docking shows celastrol can bind with BCL2 well by hydrogen bond and hydrophobic interaction. Conclusion: This finding roundly expounded the core genes and potential mechanisms of celastrol for the treatment of metastasis LUAD, offering the theoretical basis and antitumor mechanism of TCM in the treatment of lung cancer.

MicroRNA (let-7b-5p)-targeted DARS2 regulates lung adenocarcinoma growth by PI3K/AKT signaling pathway

Background:The aberrant intraellular expression of a mitochondrial aspartyl tRNA synthetase 2(DARS2)has been reported in human cancers.Nevertheless its critical role and detailed mechanism in lung adenocarcinoma(LUAD)remain unexplored.Methods:Initially,The Cancer Genome Atlas(TCGA)based Gene Expression Profiling Interactive Analysis(GEPIA)database (http:/gepia.cancer-pku.cn/)was used to analyze the prognostic relevance of DARS2 expression in LUAD.Further,cell counting kit(CCK)8,immunostaining,and transwell invasion assays in LUAD cell lines in vitro,as well as DARS2 silence on LUAD by tumorigenicity experiments in wivo in nude mice,were performed.Besides,we analyzed the expression levels of p-PI3K(phosphorylated Phosphotylinosital3 kinase),PI3K,AKT(Protein Kinase B),p-AKT(phosphorylated Protein Kinase B),PCNA(proliferating cell nudear antigen),cleaved-caspase 3,E cadherin,and N-cadherin proteins using the Westem blot analysis.Results:LUAD tissues showed higher DARS2 expression compared to normal tissues.Upregulation of DARS2 could be related to Tumor-Node-Metastasis(TNM)stage,high lymph node metastasis,and inferior prognosis.DARS2 silence decreased the proliferation,migration,and invasion abilities of LUAD cells.In addition,the DARS2 downregulation decreased the PCNA and N-cadherin expression and increased cleaved:caspase 3 and E cadherin expressions in LUAD cells,coupled with the inactivation of the PI3K/AKT signaling pathway.Moreover,DARS2 silence impaired the tumonigenicity of LUAD in vivo.Interestingly,let:7b-5p could recognize DARS2 through a complementary sequence.Mechanistically,the increased let 7b 5p expression attenuated the promo oncogenic action of DARS2 during LUAD progression,which were inversely correlated to each other in the LUAD tssues Conclusion:In summary,let 7b-5p,downregulated DARS2 expression,regulating the progression of LUAD cells by the PI3K/AKT signaling pathway.

Knockdown of HE4 suppresses tumor growth and invasiveness in lung adenocarcinoma through regulation of EGFR signaling

It has been shown that the high expression of human epididymis protein 4(HE4)in most lung cancers is related to the poor prognosis of patients,but the mechanism of pathological transformation of HE4 in lung cancer is still unclear.The current study is expected to clarify the function and mechanism of HE4 in the occurrence and metastasis of lung adenocarcinoma(LUAD).Immunoblotting evaluated HE4 expression in lung cancer cell lines and biopsies,and through analysis of The Cancer Genome Atlas(TCGA)dataset.Frequent HE4 overexpression was demonstrated in LUAD,but not in lung squamous cell carcinoma(LUSC),indicating that HE4 can serve as a biomarker to distinguish between LUAD and LUSC.HE4 knockdown significantly inhibited cell growth,colony formation,wound healing,and invasion,and blocked the G1-phase of the cell cycle in LUAD cell lines through inactivation of the EGFR signaling downstream including PI3K/AKT/mTOR and RAF/MAPK pathways.The first-line EGFR inhibitor gefitinib and HE4 shRNA had no synergistic inhibitory effect on the growth of lung adenocarcinoma cells,while the third-line EGFR inhibitor osimertinib showed additive anti-proliferative effects.Moreover,we provided evidence that HE4 regulated EGFR expression by transcription regulation and protein interaction in LUAD.Our findings suggest that HE4 positively modulates the EGFR signaling pathway to promote growth and invasiveness in LUAD and highlight that targeting HE4 could be a novel strategy for LUAD treatment.

Deep learning model based on PET/CT and combination with Cox proportional hazard model for predicting progression of lung invasive adenocarcinoma after surgery

Objective To observe the efficacy of deep learning(DL)model based on PET/CT and its combination with Cox proportional hazard model for predicting progressive disease(PD)of lung invasive adenocarcinoma within 5 years after surgery.Methods The clinical,PET/CT and 5-year follow-up data of 250 patients with lung invasive adenocarcinoma were retrospectively analyzed.According to PD or not,the patients were divided into the PD group(n=71)and non-PD group(n=179).The basic data and PET/CT findings were compared between groups,among which the quantitative variables being significant different between groups were transformed to categorical variables using receiver operating characteristic(ROC)curve and corresponding cut-off value.Multivariant Cox proportional hazard model was used to select independent predicting factors of PD of lung invasive adenocarcinoma within 5 years after surgery.The patients were divided into training,validation and test sets at the ratio of 6∶2∶2,and PET/CT data in training set and validation set were used to train model and tuning parameters to build the PET/CT DL model,and the combination model was built in serial connection of DL model and the predictive factors.In test set,the efficacy of each model for predicting PD of lung invasive adenocarcinoma within 5 years after surgery was assessed and compared using the area under the curve(AUC).Results Patients'gender and smoking status,as well as the long diameter,SUV max and SUV mean of lesions measured on PET images,the long diameter,short diameter and type of lesions showed on CT were statistically different between groups(all P<0.05).Smoking(HR=1.787[1.053,3.031],P=0.031)and lesion SUV max>4.15(HR=5.249[1.062,25.945],P=0.042)were both predictors of PD of lung invasive adenocarcinoma within 5 years after surgery.In test set,the AUC of PET/CT DL model for predicting PD was 0.847,of the combination model was 0.890,of the latter was higher than of the former(P=0.036).Conclusion DL model based on PET/CT had high efficacy for predicting PD of lung invasive adenocarcinoma within 5 years after surgery.Combining with Cox proportional hazard model could further improve its predicting efficacy.

Identification of prognostic molecular subtypes and model based on CD8+ T cells for lung adenocarcinoma

Background:Cytotoxic T lymphocytes(CD8+T)cells function critically in mediating anti-tumor immune response in cancer patients.Characterizing the specific functions of CD8+T cells in lung adenocarcinoma(LUAD)could help better understand local anti-tumor immune responses and estimate the effect of immunotherapy.Methods:Gens related to CD8+T cells were identified by cluster analysis based on the single-cell sequencing data of three LUAD tissues and their paired normal tissues.Weighted gene co-expression network analysis(WGCNA),consensus clustering,differential expression analysis,least absolute shrinkage and selection operator(LASSO)and Cox regression analysis were conducted to classify molecular subtypes for LUAD and to develop a risk model using prognostic genes related to CD8+T cells.Expression of the genes in the prognostic model,their effects on tumor cell invasion,and interactions with CD8+T cells were verified by cell experiments.Results:This study defined two LUAD clusters(CD8+0 and CD8+1)based on CD8+T cells,with cluster CD8+0 being significantly associated with the prognosis of LUAD.Three heterogeneous subtypes(clusters 1,2,and 3)differing in prognosis,genome mutation events,and immune status were categorized using 42 prognostic genes.A prognostic model created based on 11 significant genes(including CD200R1,CLEC17A,ZC3H12D,GNG7,SNX30,CDCP1,NEIL3,IGF2BP1,RHOV,ABCC2,and KRT81)was able to independently estimate the death risk for patients in different LUAD cohorts.Moreover,the model also showed general applicability in external validation cohorts.Low-risk patients could benefit more from taking immunotherapy and were significantly related to the resistance to anticancer drugs.The results from cell experiments demonstrated that the expression of CD200R1,CLEC17A,ZC3H12D,GNG7,and SNX30 was significantly downregulated,while that of CDCP1,NEIL3,IGF2BP1,RHOV,ABCC2 and KRT81 was upregulated in LUAD cells.Inhibition of CD200R1 greatly increased the invasiveness of the LUAD cells,but inhibiting CDCP1 expression weakened the invasion ability of LUAD cells.Conclusion:This study defined two prognostic CD8+T cell clusters and classified three heterogeneous molecular subtypes for LUAD.A prognostic model predictive of the potential effects of immunotherapy on LUAD patients was developed.

Pituitary metastasis from lung adenocarcinoma:A case report

BACKGROUND Pituitary gland metastasis is an unusual event,and pituitary metastasis from lung adenocarcinoma is extremely rare and associated with poor prognosis.To date,approximately 15 cases have been reported.CASE SUMMARY Here,we present the case of a 64-year-old woman with pituitary metastasis derived from lung adenocarcinoma,which was difficult to distinguish from other sellar tumors.The patient presented to the neurosurgery clinic with blurred vision and intermittent headache.During hospitalization,brain computed tomography(CT)and magnetic resonance imaging revealed a pituitary macroadenoma.Chest CT revealed irregular nodules in the basal segment of the lower lobe of the left lung,which were likely lung cancer.Positron emission tomography-CT revealed a carbohydrate metabolism tumor in the lungs and sellar region,which was considered malignant.Postoperative pathological examination of the sellar tumor revealed lung adenocarcinoma.CONCLUSION Excision of pituitary metastases combined with radiotherapy and chemotherapy should be a priority treatment for patients with pituitary metastasis.

PKHD1L1 blocks the malignant behavior of lung adenocarcinoma cells and restricts tumor growth by regulating CBX7

Objective:To explore the role of polycystic kidney and hepatic disease 1-like 1(PKHD1L1)in lung adenocarcinoma(LUAD).Methods:Bioinformatics tools were utilized to examine the clinical profile of PKHD1L1 and chromobox protein homolog 7(CBX7)in LUAD.The Cell Counting Kit-8,colony formation,terminal deoxynucleotidyl transferase dUTP nick end labeling,Transwell,and wound-healing assays were carried out to assess the proliferative,apoptotic,invasive,and migrative capacities of the cells.Furthermore,the interrelation between PKHD1L1 and CBX7 was validated using a co-immunoprecipitation assay.A LUAD mice model was constructed by subcutaneous injection of A549 cells.Finally,immunohistochemical staining was performed to evaluate CBX7 and Ki67 expression.Results:PKHD1L1 was downregulated in LUAD and predicted dismal outcomes in patients with LUAD.PKHD1L1 upregulation repressed the proliferative,invasive,and migrative capabilities of A549 cells and exacerbated the apoptotic rate.Additionally,PKHD1L1 may bind to CBX7 and positively modulate CBX7 expression.CBX7 deletion partly abrogated the effects of PKHD1L1 upregulation on the cellular biological activities in A549 cells.Furthermore,the PKHD1L1/CBX7 axis regulates the Hippo signaling pathway in A549 cells.PKHD1L1 restricted tumor growth in LUAD xenograft mice;this was partly abolished by CBX7 knockdown.Conclusion:PKHD1L1 can hinder LUAD progression by regulating CBX7-mediated Hippo signaling.

Deregulation of interferon-gamma receptor 1 expression and its implications for lung adenocarcinoma progression

Interferon-gamma(IFN-γ)plays a dual role in cancer;it is both a pro-and an antitumorigenic cytokine,depending on the type of cancer.The deregulation of the IFN-γcanonic pathway is associated with several disorders,including vulner-ability to viral infections,inflammation,and cancer progression.In particular,the interplay between lung adenocarcinoma(LUAD)and viral infections appears to exist in association with the deregulation of IFN-γsignaling.In this mini-review,we investigated the status of the IFN-γsignaling pathway and the expression level of its components in LUAD.Interestingly,a reduction in IFNGR1 expression seems to be associated with LUAD progression,affecting defenses against viruses such as severe acute respiratory syndrome coronavirus 2.In addition,alterations in the expression of IFNGR1 may inhibit the antiproliferative action of IFN-γsignaling in LUAD.

Advanced lung adenocarcinoma with EGFR 19-del mutation transforms into squamous cell carcinoma after EGFR tyrosine kinase inhibitor treatment

In this editorial we comment on the article by Ji et al.We focus specifically on the EGFR tyrosine kinase inhibitor(EGFR-TKI)treatment and the development of drug resistance to EGFR-TKIs.

Prognostic and immunological roles of heat shock protein A4 in lung adenocarcinoma

BACKGROUND Heat shock protein A4(HSPA4)belongs to molecular chaperone protein family which plays important roles within variable cellular activities,including cancer initiation and progression.However,the prognostic and immunological significance of HSPA4 in lung adenocarcinoma(LUAD)has not been revealed yet.AIM To explore the prognostic and immunological roles of HSPA4 to identify a novel prognostic biomarker and therapeutic target for LUAD.METHODS We assessed the prognostic and immunological significance of HSPA4 in LUAD using data from The Cancer Genome Atlas database.The association between HSPA4 expression and clinical-pathological features was assessed through Kruskal-Wallis and Wilcoxon signed-rank test.Univariate/multivariate Cox regression analyses and Kaplan-Meier curves were employed to evaluate prognostic factors,including HSPA4,in LUAD.Gene set enrichment analysis(GSEA)was conducted to identify the key signaling pathways associated with HSPA4.The correlation between HSPA4 expression and cancer immune infiltration was evaluated using single-sample gene set enrichment analysis(ssGSEA).RESULTS Overexpressing HSPA4 was significantly related to advanced pathologic TNM stage,advanced pathologic stage,progression disease status of primary therapy outcome and female subgroups with LUAD.In addition,increased HSPA4 expression was found to be related to worse disease-specific survival and overall survival.GSEA analysis indicated a significant correlation between HSPA4 and cell cycle regulation and immune response,particularly through diminishing the function of cytotoxicity cells and CD8 T cells.The ssGSEA algorithm showed a positive correlation between HSPA4 expression and infiltrating levels of Th2 cells,while a negative correlation was observed with cytotoxic cell infiltration levels.CONCLUSION Our findings indicate HSPA4 is related to prognosis and immune cell infiltrates and may act as a novel prognostic biomarker and therapeutic target for LUAD.

Prediction of prognosis,immune escape and drug sensitivity of lung adenocarcinoma based on Cuproptosis-related LncRNA

Background:Lung Adenocarcinoma(LUAD)is the leading cause of death from lung cancer.Cuproptosis is the latest discovered way of programmed cell death,and Cuproptosis-Related Gene(CRG)is associated with the risk of LUAD.At present,there are few research of LUAD and Cuproptosis focuses on Long non-coding RNA(LncRNA).As genomics advances,LncRNA emerges as a potential target for understanding tumor progression and prognosis,offering prospects for biological targeted therapy.Therefore,this study provides new biomarkers and therapeutic targets for LUAD from the perspective of LncRNA.Methods:Gene expression,clinical outcome and gene mutation data of LUAD patients were downloaded from TCGA database.Spearman correlation was used to analyze the correlation between LncRNA and CRG.Univariate Cox,multivariate Cox and LASSO Cox regression analysis were used to construct a prognostic model of Cuproptosis-LncRNAs.GO and KEGG enrichment and immune function analysis were performed on differentially expressed genes between different risk groups.Then,immune escape analysis was performed on LUAD patients with different TIDE score.Finally,drug sensitivity analysis was performed on these differentially expressed genes.Results:A total of 2244 Cuproptosis-LncRNAs were found.Through the application of univariate Cox regression analysis,multivariate Cox regression analysis,and LASSO Cox regression analysis,a prognostic model was developed,integrating 15 Cuproptosis-LncRNAs to assess the risk of mortality.Following that,the model underwent assessment through risk score analysis,Kaplan-Meier survival analysis,risk distribution,and evaluation of survival outcomes.The results revealed an AUC value of 0.755 for the model,surpassing the AUC of other clinical pathological features.The results of KEGG analysis showed that the differentially expressed genes in different model groups were mainly involved in Amoebiasis,Fat digestion and absorption,and other signaling pathways.The results of TMB showed that the prognostic model of TMB combined with risk score could well evaluate the prognosis of patients.The TIDE scores did not exhibit a notable distinction between the two risk models.Analysis of drug sensitivity revealed that individuals in the low-risk category demonstrated greater responsiveness to 5-Fluorouracil,Axitinib,Bexarotene,and other drugs compared to those in the high-risk group.Conclusion:Our research offers a valuable reference for predicting the prognosis of LUAD,contributing to a better understanding of the future elucidation of the process and mechanism of Cuproptosis-LncRNAs in LUAD.

Clinical and pathological characteristics and expression of related molecules in patients with airway disseminated lung adenocarcinoma

Objective:Lung adenocarcinoma exhibits diverse genetic and morphological backgrounds,in addition to considerable differences in clinical pathology and molecular biological characteristics.Among these,the phenomenon of spread through air space(STAS),a distinct mode of lung cancer infiltration,has rarely been reported.Therefore,this study aimed to explore the relationship between STAS tumor cells and the clinical and molecular characteristics of patients with lung adenocarcinoma,as well as their impact on prognosis.Methods:This study included 147 patients who were diagnosed with lung adenocarcinoma at the Inner Mongolia Autonomous Region Cancer Institute between January 2014 and December 2017.Surgical resection specimens were retrospectively analyzed.Using univariate and multivariate Cox analyses,we assessed the association between STAS and the clinicopathological features and molecular characteristics of patients with lung adenocarcinoma.Furthermore,we investigated the effects on patient prognosis.In addition,we developed a column–line plot prediction model and performed internal validation.Results:Patients with positive STAS had a significantly higher proportion of tumors with a diameter≥2 cm,with infiltration around the pleura,blood vessels,and nerves,and a pathological stage>IIB than in STAS-negative patients(P<0.05).Cox multivariate survival analysis revealed that clinical stage,STAS status,tumor size,and visceral pleural invasion were independent prognostic factors influencing the 5-year progression-free survival in patients with lung adenocarcinoma.The predictive values and P values from the Hosmer-Lemeshow test were 0.8 and 0.2,respectively,indicating no statistical difference.Receiver operating characteristic curve analysis demonstrated areas under the curve of 0.884 and 0.872 for the training and validation groups,respectively.The nomogram model exhibited the best fit with a value of 192.09.Conclusions:Clinical stage,pleural invasion,vascular invasion,peripheral nerve invasion,tumor size,and necrosis are independent prognostic factors for patients with STAS-positive lung adenocarcinoma.The nomogrambased on the clinical stage,pleural invasion,vascular invasion,peripheral nerve invasion,tumor size,and necrosis showed good accuracy,differentiation,and clinical practicality.

Exploring the Need and Strategy for Intraoperative Freezing to Identify Metastatic Adenocarcinoma of the Lungs

Objective: To explore the necessity and strategy of intraoperative freezing to identify primary and metastatic adenocarcinoma of the lung. Methods: This study retrospectively analyzes the impact of failing to make a definitive diagnosis of metastatic adenocarcinoma of the lung on the clinical surgical approach in four cases of intraoperative freezing. It also examines the reasons for this failure and reviews the relevant literature. Results: All 4 cases of intraoperative freezing were diagnosed as invasive adenocarcinoma, and none of them made a definitive diagnosis of metastatic adenocarcinoma. Conclusion: It is difficult to confirm the diagnosis of metastatic adenocarcinoma of the lung by intraoperative frozen section, and the combination of patient history, rapid immunohistochemistry, and histological morphology of intraoperative frozen section for its identification can guide the surgeon to adjust the surgical approach in time and provide evidence for the establishment of surgical protocols for reference.

Deep learning model based on primary tumor to predict lymph node status in clinical stage IA lung adenocarcinoma:a multicenter study

Objective:To develop a deep learning model to predict lymph node(LN)status in clinical stage IA lung adeno-carcinoma patients.Methods:This diagnostic study included 1,009 patients with pathologically confirmed clinical stage T1N0M0 lung adenocarcinoma from two independent datasets(699 from Cancer Hospital of Chinese Academy of Medical Sciences and 310 from PLA General Hospital)between January 2005 and December 2019.The Cancer Hospital dataset was randomly split into a training cohort(559 patients)and a validation cohort(140 patients)to train and tune a deep learning model based on a deep residual network(ResNet).The PLA Hospital dataset was used as a testing cohort to evaluate the generalization ability of the model.Thoracic radiologists manually segmented tumors and interpreted high-resolution computed tomography(HRCT)features for the model.The predictive performance was assessed by area under the curves(AUCs),accuracy,precision,recall,and F1 score.Subgroup analysis was performed to evaluate the potential bias of the study population.Results:A total of 1,009 patients were included in this study;409(40.5%)were male and 600(59.5%)were female.The median age was 57.0 years(inter-quartile range,IQR:50.0-64.0).The deep learning model achieved AUCs of 0.906(95%CI:0.873-0.938)and 0.893(95%CI:0.857-0.930)for predicting pN0 disease in the testing cohort and a non-pure ground glass nodule(non-pGGN)testing cohort,respectively.No significant difference was detected between the testing cohort and the non-pGGN testing cohort(P=0.622).The precisions of this model for predicting pN0 disease were 0.979(95%CI:0.963-0.995)and 0.983(95%CI:0.967-0.998)in the testing cohort and the non-pGGN testing cohort,respectively.The deep learning model achieved AUCs of 0.848(95%CI:0.798-0.898)and 0.831(95%CI:0.776-0.887)for predicting pN2 disease in the testing cohort and the non-pGGN testing cohort,respectively.No significant difference was detected between the testing cohort and the non-pGGN testing cohort(P=0.657).The recalls of this model for predicting pN2 disease were 0.903(95%CI:0.870-0.936)and 0.931(95%CI:0.901-0.961)in the testing cohort and the non-pGGN testing cohort,respectively.Conclusions:The superior performance of the deep learning model will help to target the extension of lymph node dissection and reduce the ineffective lymph node dissection in early-stage lung adenocarcinoma patients.