Pan-cancer prognosis, immune infiltration, and drug resistance characterization of lung squamous cell carcinoma tumor microenvironment-related genes.

Background: The tumor microenvironment (TME) plays an important role in cancer development; however, its implications in lung squamous cell carcinoma (LUSC) and pan-cancer have been poorly understood. Methods: In this study, The Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissue using Expression Data (ESTIMATE) datasets were applied to identify differentially expressed genes. Additionally, online public databases were utilized for in-depth bioinformatics analysis of pan-cancer datasets to investigate the prognostic implications of TME-related genes further. Results: Our study demonstrated a significant association between stromal scores, immune scores, and specific clinical characteristics in LUSC patients. C3AR1, CSF1R, CCL2, CCR1, and CD14 were identified as prognostic genes related to the TME. All TME-related prognostic genes demonstrated varying degrees of correlation with immune infiltration subtypes and tumor cell stemness. Moreover, our study revealed that TME-related prognostic genes, particularly C3AR1 and CCR1, might contribute to drug resistance in cancer cells. Conclusions: The identified TME-related prognostic genes, particularly C3AR1 and CCR1, have potential implications for understanding and targeting drug resistance mechanisms in cancer cells.

Giant pulmonary sclerosing pneumocytoma with potentially malignant biological behavior: a case report and literature review.

Background: Pulmonary sclerosing pneumocytoma (PSP) is a rare benign lung tumor which generally presents as a solitary pulmonary nodule in middle-aged females. However, the PSP in some patients exhibits potentially malignant biological behavior, with recurrence and lymphatic or distant metastasis being observed. Case Description: We encountered a case of a 46-year-old female with an inordinately massive tumor 9.5 cm in diameter and a relatively high Ki-67 proliferation rate. Fine needle aspiration (FNA) played a significant but limited role in the preoperative diagnosis: the computed tomography (CT)-guided lung puncture biopsy was consistent with the typical pathology of PSP; however, endobronchial ultrasound-guided transbronchial lung biopsy (EBUS-TBLB) could not provide a definitive diagnosis. The patient ultimately underwent thoracoscopic resection and mediastinal lymph node dissection. Here, we provide a review of the literature on patients with PSP with malignant biological behavior to raise awareness of the malignant potential of PSP and describe our experience to inform future management. Conclusions: PSP lacks specificity in its clinical and radiological characteristics and has complex pathological manifestations. FNA is valuable in the diagnosis and differential diagnosis of PSP but involves the risk of misdiagnosis or missed diagnosis. Additionally, we believe that the accepted benign features of PSP need to be updated and that the potential malignant features of PSP should be carefully monitored. Surgical resection is curative but strict follow-up is crucial.

Pan-Cancer Prognostic, Immunity, Stemness, and Anticancer Drug Sensitivity Characterization of N6-Methyladenosine RNA Modification Regulators in Human Cancers.

N6-methyladenosine RNA modification plays a significant role in the progression of multiple tumorigenesis. Our study identified the imperative role of m6A regulators in the tumor immune microenvironment, survival, stemness score, and anticancer drug sensitivity of pan-cancer. The Wilcox test was to identify the differential expression between 17 m6A regulators across 33 TCGA cancer types and their normal tissues from UCSC Xena GDC pan-cancer. Survival analysis of m6A-related regulators in 33 TCGA cancer types was identified using the "survival" and "survminer" package. The Spearman correlation test and Pearson correlation test were used to identify the correlation relationship between m6A regulators expression and tumor microenvironment, tumor stem cell score, and drug sensitivity of anticancer drugs. ConsensusPathDB was used for exploring m6A regulators functional enrichment. The 17 (METTL3, WTAP, METTL14, RBM15, RBM15B, VIRMA, HNRNPC, HNRNPA2B1, YTHDC1, ZC3H13, YTHDF1, YTHDC2, YTHDF2, IGF2BP3, IGF2BP1, FTO, and ALKBH5) m6A regulators were differentially expressed in 18 TCGA cancer types and adjacent normal tissues. Correlation analysis indicated that the relationship between the expression of 17 m6A regulators and tumor microenvironment indicated that the higher expression of m6A regulators, the higher the degree of tumor stem cells. The anticancer drug sensitivity analysis indicated that ZC3H13 expression had a positive relationship with anticancer drugs such as selumetinib, dabrafenib, cobimetinib, trametinib, and hypothemycin (p < 0.001). YTHDF2 expression was significantly negatively correlated with the anticancer drug dasatinib (p < 0.001). The pan-cancer immune subtype analysis showed that the 17 m6A regulators were significantly different in immune subtype C1 (wound healing), C3 (inflammatory), C2 (IFN-gamma dominant), C5 (immunological quiet), C4 (lymphocyte depleted), and C6 (TGF-beta dominant) (p < 0.001). Our study provides a comprehensive insight for revealing the significant role of m6A regulators in the tumor immune microenvironment, stemness score, and anticancer drug sensitivity of human cancers.

Identification of a Prognostic Model Based on Immune-Related Genes of Lung Squamous Cell Carcinoma.

Immune-related genes (IRGs) play considerable roles in tumor immune microenvironment (IME). This research aimed to discover the differentially expressed immune-related genes (DEIRGs) based on the Cox predictive model to predict survival for lung squamous cell carcinoma (LUSC) through bioinformatics analysis. First of all, the differentially expressed genes (DEGs) were acquired based on The Cancer Genome Atlas (TCGA) using the limma R package, the DEIRGs were obtained from the ImmPort database, whereas the differentially expressed transcription factors (DETFs) were acquired from the Cistrome database. Thereafter, a TFs-mediated IRGs network was constructed to identify the candidate mechanisms for those DEIRGs in LUSC at molecular level. Moreover, Gene Ontology (GO), together with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, was conducted for exploring those functional enrichments for DEIRGs. Besides, univariate as well as multivariate Cox regression analysis was conducted for establishing a prediction model for DEIRGs biomarkers. In addition, the relationship between the prognostic model and immunocytes was further explored through immunocyte correlation analysis. In total, 3,599 DEGs, 223 DEIRGs, and 46 DETFs were obtained from LUSC tissues and adjacent non-carcinoma tissues. According to multivariate Cox regression analysis, 10 DEIRGs (including CALCB, GCGR, HTR3A, AMH, VGF, SEMA3B, NRTN, ENG, ACVRL1, and NR4A1) were retrieved to establish a prognostic model for LUSC. Immunocyte infiltration analysis showed that dendritic cells and neutrophils were positively correlated with IRGs, which possibly exerted an important part within the IME of LUSC. Our study identifies a prognostic model based on IRGs, which is then used to predict LUSC prognosis and analyze immunocyte infiltration. This may provide a novel insight for exploring the potential IRGs in the IME of LUSC.

Investigating the mechanism of ShuFeng JieDu capsule for the treatment of novel Coronavirus pneumonia (COVID-19) based on network pharmacology.

ShuFeng JieDu capsule (SFJDC), a traditional Chinese medicine, has been recommended for the treatment of COVID-19 infections. However, the pharmacological mechanism of SFJDC still remains vague to date. The active ingredients and their target genes of SFJDC were collected from TCMSP. COVID-19 is a type of Novel Coronavirus Pneumonia (NCP). NCP-related target genes were collected from GeneCards database. The ingredients-targets network of SFJDC and PPI networks were constructed. The candidate genes were screened by Venn diagram package for enrichment analysis. The gene-pathway network was structured to obtain key target genes. In total, 124 active ingredients, 120 target genes of SFJDC and 251 NCP-related target genes were collected. The functional annotations cluster 1 of 23 candidate genes (CGs) were related to lung and Virus infection. RELA, MAPK1, MAPK14, CASP3, CASP8 and IL6 were the key target genes. The results suggested that SFJDC cloud be treated COVID-19 by multi-compounds and multi-pathways, and this study showed that the mechanism of traditional Chinese medicine (TCM) in the treatment of disease from the overall perspective.

Identification and validation of the prognostic value of immune-related genes in non-small cell lung cancer.

Immune-related genes play a significant role in predicting the overall survival and monitoring the status of the cancer immune microenvironment. The aim of this research study was to identify differentially expressed immune-related genes (DEIRGs) and establish a Cox prediction model for the evaluation of prognosis in patients with non-small cell lung cancer (NSCLC). Transcription expression data, immune gene data, and tumor transcription factor data from The Cancer Genome Atlas (TCGA), the Immunology Database and Analysis Portal, and the Cistrome Cancer database were analyzed to detect differentially expressed genes (DEGs), DEIRGs, and differentially expressed transcription factors (DETFs). Multivariate Cox regression analysis was used to obtain potential DEIRGs as independent prognostic factors. Oncomine, The Human Protein Atlas (HPA), TIMER databases were performed to validate the mRNA and protein expression level of DEIRGs. TIMER database was performed to explore the immunocytes infiltration of DEIRGs. In total, 7448 DEGs, 536 DEIRGs, 87 DETFs were identified from 1,037 NSCLC tissues and 108 normal tissues in TCGA database. Fifteen-DEIRG signatures (THBS1, S100P, S100A16, DLL4, CD70, DKK1, IL33, NRTN, PDGFB, STC2, VGF, GCGR, HTR3A, LGR4, SHC3) could be perceived as independent prognostic factors for predicting the overall survival of patients with NSCLC (P = 4.89e--09). Immune cell correlation analysis showed that neutrophils and b cells were positively and negatively correlated with the riskscore of the prediction model, respectively. Our study identified a Cox prediction model based on DEIRGs to predict the overall survival of patients with NSCLC. The immunocyte infiltration analysis provided a novel horizon for monitoring the status of the NSCLC immune microenvironment.

Serum miR-1228-3p and miR-181a-5p as Noninvasive Biomarkers for Non-Small Cell Lung Cancer Diagnosis and Prognosis.

BACKGROUND: Lung cancer is the leading cause of cancer-related mortality worldwide, and non-small cell lung cancer (NSCLC) accounts for over 80% of all lung cancers. Serum microRNAs (miRNAs), due to their high stability, have the potential to become valuable noninvasive biomarkers. This present study was aimed to identify the serum miRNAs expression signatures for the diagnosis and prognosis of NSCLC using bioinformatics analysis. METHODS: A total of 12 miRNAs profiling studies have been identified in Pubmed, Gene Expression Omnibus (GEO), and ArreyExpress databases. Differentially expressed miRNAs (DEmiRNAs) were analyzed according to GEO2R online tool and RRA method from R. Then, prediction of DEmiRNAs' target genes from TargetScan, PicTar, miRDB, Tarbase, and miRanda database. Furthermore, we using reverse transcription- quantitative polymerase chain reaction (RT-qPCR) to evaluate the expression levels of DEmiRNAs in serum samples obtained from NSCLC patients and healthy controls. Subsequently, the clinical significance of the tested miRNAs was determined using receiver operating characteristic (ROC) analysis and Cox regression analysis. RESULTS: A total of 27 DEmiRNAs were identified and 5 of them (miR-1228-3p, miR-1228-5p, miR-133a-3p, miR-1273f, miR-545-3p) were significantly up-regulated and 4 of them (miR-181a-5p, miR-266-5p, miR-361-5p, miR-130a-3p) were significantly down-regulated in NSCLC patients compared with healthy controls. RT-qPCR validated that miR-1228-3p (P =0.006) and miR-181a-5p (P =0.030) were significantly differentially expressed in the serum of NSCLC patients and healthy controls. ROC analysis on miR-1228-3p and miR-181a-5p revealed the area under the curve (AUC) of 0.685 (95% confidence interval [CI], 0.563-0.806; P =0.006) and 0.647 (95% CI, 0.506-0.758; P =0.049). ROC analysis on miR-1228-3p combined miR-181a-5p revealed the AUC of 0.711 (95% CI, 0.593-0.828; P =0.002). Multivariate Cox regression analysis demonstrated that the high serum miR-1228-3p level was an independent factor for the poor prognosis of NSCLC patients. CONCLUSIONS: Serum miR-1228-3p and miR-181a-5p are potential noninvasive biomarkers for the diagnosis and prognosis of NSCLC patients.

Integrative analysis of DNA methylation-driven genes for the prognosis of lung squamous cell carcinoma using MethylMix.

Background: DNA methylation acts as a key component in epigenetic modifications of genomic function and functions as disease-specific prognostic biomarkers for lung squamous cell carcinoma (LUSC). This present study aimed to identify methylation-driven genes as prognostic biomarkers for LUSC using bioinformatics analysis. Materials and Methods: Differentially expressed RNAs were obtained using the edge R package from 502 LUSC tissues and 49 adjacent non-LUSC tissues. Differentially methylated genes were obtained using the limma R package from 504 LUSC tissues and 69 adjacent non-LUSC tissues. The methylation-driven genes were obtained using the MethylMix R package from 500 LUSC tissues with matched DNA methylation data and gene expression data and 69 non-LUSC tissues with DNA methylation data. Gene ontology and ConsensusPathDB pathway analysis were performed to analyze the functional enrichment of methylation-driven genes. Univariate and multivariate Cox regression analyses were performed to identify the independent effect of differentially methylated genes for predicting the prognosis of LUSC. Results: A total of 44 methylation-driven genes were obtained. Univariate and multivariate Cox regression analyses showed that twelve aberrant methylated genes (ATP6V0CP3, AGGF1P3, RP11-264L1.4, HIST1H4K, LINC01158, CH17-140K24.1, CTC-523E23.14, ADCYAP1, COX11P1, TRIM58, FOXD4L6, CBLN1) were entered into a Cox predictive model associated with overall survival in LUSC patients. Methylation and gene expression combined survival analysis showed that the survival rate of hypermethylation and low-expression of DQX1 and WDR61 were low. The expression of DQX1 had a significantly negatively correlated with the methylation site cg02034222. Conclusion: Methylation-driven genes DQX1 and WDR61 might be potential biomarkers for predicting the prognosis of LUSC.

Methylation and transcriptome analysis reveal lung adenocarcinoma-specific diagnostic biomarkers.

BACKGROUND: DNA methylation can regulate the role of long noncoding RNAs (lncRNAs) in the development of lung adenocarcinoma (LUAD). The present study aimed to identify methylation-driven lncRNAs and mRNAs as biomarkers in the prognosis of LUAD using bioinformatics analysis. METHODS: Differentially expressed RNAs were obtained using the edge R package from 535 LUAD tissues and 59 adjacent non-LUAD tissues. Differentially methylated genes were obtained using the limma R package from 475 LUAD tissues and 32 adjacent non-LUAD tissues. Methylation-driven mRNA and lncRNA were obtained using the MethylMix R package from 465 LUAD tissues with matched DNA methylation and RNA expression and 32 non-LUAD tissues with DNA methylation. Gene ontology and ConsensusPathDB pathway analysis were performed to identify functional enrichment of methylation-driven mRNAs. Univariate and multivariate Cox regression analyses were performed to identify the independent effect of each variable for predicting the prognosis of LUAD. Kaplan-Meier curve analysis of DNA methylation and gene expression might provide potential prognostic biomarkers for LUAD patients. RESULTS: A total of 99 methylation-driven mRNAs and 17 methylation-driven lncRNAs were obtained. Univariate and multivariate Cox regression analysis showed that 6 lncRNAs (FOXE1, HOXB13-AS1_2, VMO1, HIST1H3F, AJ003147.8, ASXL3) were retrieved to construct a predictive model associated with overall survival in LUAD patients. Combined DNA methylation and gene expression survival analysis revealed that 4 lncRNAs (AC023824.1, AF186192.1, LINC01354 and WASIR2) and 8 mRNAs (S1PR1, CCDC181, F2RL1, EFS, KLHDC9, MPV17L, GKN2, ITPRIPL1) might act as independent biomarkers for the prognosis of LUAD. CONCLUSIONS: Methylation-driven lncRNA and mRNA contribute to the survival of LUAD, and 4 lncRNAs and 8 mRNAs might be potential biomarkers for the prognosis of LUAD.

Identification of lncRNA biomarkers in lung squamous cell carcinoma using comprehensive analysis of lncRNA mediated ceRNA network.

Long non-coding RNAs (lncRNAs) act as a member of competing endogenous RNAs (ceRNAs) and plays a significant role in tumorigenesis. The aim of this study was to identify potential lncRNA biomarkers for predicting the prognosis of lung squamous cell carcinoma (LUSC) using a comprehensive analysis of lncRNA mediated ceRNA network. Differentially expressed RNAs datasets were obtained using edge R package in 502 LUSC tissues and 49 adjacent non-LUSC tissues from the Cancer Genome Atlas (TCGA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to identify functional enrichment implication of lncRNA related differentially expressed mRNAs. Survival analysis was used Kaplan-Meier curve method. Univariate and multivariate Cox regression analysis were performed to construct a predictive model with lncRNA biomarkers. A total of 2185 lncRNAs, 170 miRNAs and 2053 mRNAs were differentially expressed between LUSC tissues and adjacent non-LUSC tissues. The novel constructed ceRNA network incorporated 184 LUSC-specific lncRNAs, 18 miRNAs, and 49 mRNAs. About 11 of 184 differentially expressed lncRNAs and 1 of 18 differentially expressed miRNAs and 5 of 49 differentially expressed mRNAs were conspicuously related to overall survival (p < .05). Univariate and multivariate cox regression analysis showed that 6 lncRNAs were retrieved to construct a predictive model to predict the overall survival in LUSC patients. In conclusion, CeRNAs contributed to the progression of LUSC and a model with 6 lncRNAs might be potential biomarker for predicting the prognosis of LUSC.

A two-circular RNA signature as a noninvasive diagnostic biomarker for lung adenocarcinoma.

BACKGROUND: Recently, circular RNAs (circRNAs) have been reported to be microRNA sponges and play essential roles in cancer development. This study aimed to evaluate whether circulating circRNAs could be used as diagnostic biomarkers for lung adenocarcinoma (LUAD). METHODS: The Gene Expression Omnibus (GEO) dataset was used to investigate differentially expressed circRNAs (DEcircRNAs) in paired LUAD tissues and adjacent nontumor tissues. The expression levels of the host genes were analyzed in The Cancer Genome Atlas (TCGA)-LUAD dataset, and the prognostic value was assessed using the Kaplan-Meier plotter. Quantitative real-time PCR (qRT-PCR) was performed to validate the expression of candidate circRNAs in the LUAD plasma and cells. The CCK8 assay was used to measure the function of circRNAs in cell proliferation. Competing endogenous RNA (ceRNA) network, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to predict the possible mechanisms and functions of circRNAs in LUAD. RESULTS: Two upregulated and two downregulated circRNAs were identified as candidate circRNAs using bioinformatics analysis. qRT-PCR demonstrated that hsa_circ_0005962 was upregulated in LUAD plasma and cells, whereas hsa_circ_0086414 was downregulated. Receiver operating characteristic (ROC) curve analysis confirmed that a signature comprising the two circRNAs had good diagnostic potential, with an area under the ROC curve (AUC) of 0.81 (P < 0.0001). In addition, we observed that overexpression of plasma hsa_circ_0086414 was related to EGFR mutations (P = 0.001). Plasma hsa_circ_0005962 displayed significantly different expression before and after surgery in patients with LUAD (P < 0.0001). In vitro experiments suggested that hsa_circ_0005962 promoted LUAD cell proliferation. For future studies, we predicted the circRNA-miRNA-mRNA network for hsa_circ_0005962. Bioinformatics analysis revealed that hsa_circ_0005962 might be involved in LUAD development. CONCLUSION: A circRNA signature was identified as a potential noninvasive biomarker for LUAD diagnosis.

Bronchobiliary fistula following radiofrequency ablation for liver metastases from breast cancer: A case report and literature review.

RATIONALE: Bronchobiliary fistula (BBF) is a rare clinical condition which is characterized by a channel between biliary tract and bronchial tree. BBF can present with fever, dyspnea, and cough. However, it can be easily misdiagnosed as biliary vomiting, dyspnea, or even severe pneumonia. PATIENT CONCERNS: A 53-year-old woman was diagnosed with breast cancer in April 2011 and underwent radical mastectomy and lymph node dissection, chemotherapy, and radiotherapy. Unfortunately, the patient suffered from bone metastasis during the 1st year and liver metastasis during the 2nd year after radical mastectomy. In 2013, the patient underwent transcatheter arterial chemoembolization therapy twice for liver metastasis. The patient was then treated with radiofrequency ablation (RFA) in 2016. Unfortunately, the patient developed a cough with bitter-tasting yellow sputum and chest tightness 2 weeks after the RFA treatment. Approximately 6 months later, the patient still complained of a cough with yellow sputum and persistent chest tightness. The patient was then admitted to our department. DIAGNOSES: The presence of bile in the sputum supported a diagnosis of BBF. Bronchoscopy was performed, and the presence of bile in the lavage fluid confirmed the diagnosis of BBF. INTERVENTIONS: The patient was treated with antibiotics including sulbactam, cefoperazone, levofloxacin and meropenem, was well as hepatoprotectants, nutritional support and other supportive treatments in our department. OUTCOMES: The patient died because of liver failure. LESSONS: This case demonstrates that we should consider the possibility of BBF when patients experience a recurrent cough with discolored sputum after RFA. In particular, a diagnosis of BBF should be considered in patients who do not respond to antibiotic treatment.