The immune heterogeneity between pulmonary adenocarcinoma and squamous cell carcinoma: a comprehensive analysis based on lncRNA model
Ontology highlight
ABSTRACT: Adenocarcinoma (AD) and squamous carcinoma (SCC) are major types of lung cancer. Although they both belong to non-small cell lung cancer (NSCLC), the differences in clinical prognosis and molecular mechanism between them are remarkable. Recently, numerous studies proved that immune status of carcinoma patients influence deeply the clinical outcome. Based on the theory of “Immune edit”, many immunotherapies come out and tremendously extended the life of the patients. Thus, research on immune status is significant and essential. Our study aims to select specific lncRNAs which control the key immune-related genes to construct the risk model for AD and SCC respectively and the patients were divided into high- and low-risk groups based on risk score. The prognostic significance of risk score was validated by our own cohorts. Besides, The GSEA analysis suggested that immune response or process of AD patients in high-risk group was weaken while the situation is opposite for SCC cohort. The evaluation of immune infiltration reveled that the infiltrating degree of dendritic cell (DC cell) might be the important change for AD patients. In addition, the prediction of response to immune checkpoint inhibitors (ICIs) treatment, based on T cell immune dysfunction and exclusion (TIDE) and immunophenoscore (IPS), indicated that the reasons for the deterioration of the immune microenvironment were T cell exclusion in AD patients and T cell dysfunction in SCC patients and the high-risk patients with SCC might benefit from ICIs treatment. Furthermore, the prediction of downstream targets via The Cancer Proteome Atlas (TCPA) database and RNA-seq analysis based on transferred lung cancer cell line indicated that lINC00996 was potential to become the therapeutic target for AD patients.
Project description:To systematically characterize anti-PD-1/PD-L1 immunotherapy-related changes in serum glycoproteins and discover novel biomarkers related to treatment response, we analyzed a series of sera samples from patients with metastatic lung squamous cell carcinoma (SCC) and lung adenocarcinoma (ADC), collected before and during ICIs treatment, with mass-spectrometry-based label-free quantification methodology.
Project description:Immunotherapy has improved the prognosis of patients with advanced non-small cell lung
cancer (NSCLC), but only a small subset of patients achieved clinical benefit. The purpose of our study was to integrate multidimensional data using a machine learning method to predict the therapeutic efficacy of immune checkpoint inhibitors (ICIs) monotherapy in patients with advanced NSCLC.The authors retrospectively enrolled 112 patients with stage IIIB-IV NSCLC receiving ICIs monotherapy. The random forest (RF) algorithm was used to establish efficacy prediction models based on five different input datasets, including precontrast computed tomography (CT) radiomic data, postcontrast CT radiomic data, combination of the two CT radiomic data, clinical data, and a combination of radiomic and clinical data. The 5-fold cross-validation was used to train and test the random forest classifier. The performance of the models was assessed according to the area under the curve (AUC) in the receiver operating characteristic (ROC) curve. Among these models(RF MLP LR XGBoost), our reproduced onnx models have better performance, especially for random forest. The response variable with a value (1/0) indicates the (efficacy/inefficacy) of PD-1/PD-L1 monotherapy in patients with advanced NSCLC
Project description:Lung cancer (LC) is one of the major cancers, with survival of patients dictated by the time of diagnosis. Cell-free circulating miRNAs have been proposed as candidate biomarkers for non-small cell lung cancer. The goal of this study was to profile the miRNAs in blood plasma of lung cancer patients diagnosed with squamous cell carcinoma (SCC, n=14) or adenocarcinoma (AD, n=6), and healthy individuals (HD) using miRCURY LNA miRNA qPCR Serum/Plasma Panel (Exiqon). Average Cq of detected assays was used for normalization of miRNA expression.
Project description:Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurate prediction of individual patient responses to ICIs remains a challenge. We performed a genome-wide analysis of 5-hydroxymethylcytosine (5hmC) in plasma cell-free DNA (cfDNA) samples from 83 lung cancer patients. Using machine learning approaches, we developed a 5hmC signature to predict ICI treatment response and calculated a weighted-predictive score (wp-score) based on the 5hmC levels of signature genes in each sample. A low wp-score was significantly correlated with longer progression-free survival across three independent patient sample sets, and demonstrated superior predictive capability to tumor programmed death-ligand 1. Moreover, we identified novel 5hmC-associated genes and signaling pathways integral to ICI treatment response in lung cancer. Our study suggests that cfDNA 5hmC analysis is a minimally invasive, innovative strategy for guiding treatment selection in lung cancer patients.
Project description:There is large variability among lung squamous cell carcinoma (SCC) patients in response to treatment with cisplatin based chemotherapy. LncRNAs is potentional a new type of predictive marker that can identify subgroups of patients who benefit from chemotherapy and it will have great value for treatment guidance. Differentially expressed LncRNAs were identified using microarray profiling of tumors with partial response (PR) vs. with progressive disease (PD) from advanced lung SCC patients treated with cisplatin based chemotherapy and validated by quantitative real-time PCR (qPCR). Results: Compared with the PD samples, 953 lncRNAs were consistently overregulated and 749 lncRNAs
Project description:Primary tumor recurrence occurs commonly after surgical resection of lung squamous cell carcinoma (SCC). The aim of this study was to identify genes involved in recurrence in lung squamous cell carcinoma patients. Array comparative genomic hybridization (aCGH) was performed on DNA extracted from tumour tissue from 62 patients with primary lung squamous cell carcinomas. aCGH data was analysed to identify genes affected by copy number alterations that may be involved in SCC recurrence. Candidate genes were then selected for technical validation based on differential copy number between recurrence and non-recurrence SCC tumour samples. Genes technically validated advanced to tests of biological replication by qPCR using an independent test set of 72 primary lung SCC tumour samples. 18q22.3 loss was identified by aCGH as significantly associated with recurrence (p=0.038). Although aCGH copy number loss associated with recurrence was found for seven genes within 18q22.3, only SOCS6 copy number loss was both technically replicated by qPCR and biologically validated in the test set. DNA copy number profiling using 44K element array comparative genomic hybridization microarrays of 62 primary lung squamous cell carcinomas.
Project description:Bronchoalveolar lavage is commonly performed to examine inflammation and responsible pathogens in lung diseases, and its findings may be used to assess the immune profile of the lung tumor microenvironment (TME). To investigate whether analyses of bronchoalveolar lavage fluid (BALF) can help identify non-small cell lung cancer (NSCLC) patients who respond to immune checkpoint inhibitors (ICIs), BALF and blood were prospectively collected before initiating nivolumab. The secreted molecules, microbiome, and cellular profiles based on BALF and blood analysis were compared regarding therapeutic effect in 12 patients. Compared to non-responders, responders showed significantly higher CXCL9 levels and greater diversity in the lung microbiome profile in BALF, and greater frequency of CD56+ subset in blood T cells, whereas no significant difference was found in PD-L1 expression of tumor cells. Antibiotic treatment in a preclinical lung cancer model significantly decreased CXCL9 in the lung TME, resulting in reduced sensitivity to nivolumab, which was reversed by CXCL9 induction in tumor cells. Thus, CXCL9 and the microbiome in the lung TME might be associated with each other, and their balance could contribute to nivolumab sensitivity in NSCLC patients. BALF analysis can help predict the efficacy of ICIs when performed along with currently approved examinations.
Project description:Lung cancer is the second most commonly diagnosed cancer and the leading cause of cancer death worldwide, of which approximately 85% are non-small cell lung cancer (NSCLC). The overall survival (OS) of patients with advanced NSCLC was significantly prolonged with immune checkpoint inhibitors (ICIs) targeting the programmed cell death-1 (PD-1) and programmed death-ligand 1 (PD-L1) axis. For early-stage lung cancer, the 5-year survival rate for patients ranges from 80% in stage IA to 41% in stage IIIA, and many cases relapse after surgical resection. Currently, multiple clinical trials have manifested the encouraging efficacy of neoadjuvant immunotherapy in stage I-IIIA resectable NSCLC. However, the effect of immunotherapy in ultra early-stage NSCLC patients with micro-invasive or even pre-invasive lesions remains unclear. In this study, we aimed to evaluate the activity and safety of sintilimab on high-risk ground glass opacity lesions in multiple primary lung cancer patients.
Project description:Cervical mucus was collected from 86 patients with a normal cervix, cervical intraepithelial neoplasia (CIN), squamous cell carcinoma (SCC), or adenocarcinoma (AD). 76 candidates of miRNAs were selected according to criteria such as absolute value of the signal intensity included more than 20 and the ratio of the SCC/normal or AD/normal included more than four.
Project description:Primary tumor recurrence occurs commonly after surgical resection of lung squamous cell carcinoma (SCC). The aim of this study was to identify genes involved in recurrence in lung squamous cell carcinoma patients. Array comparative genomic hybridization (aCGH) was performed on DNA extracted from tumour tissue from 62 patients with primary lung squamous cell carcinomas. aCGH data was analysed to identify genes affected by copy number alterations that may be involved in SCC recurrence. Candidate genes were then selected for technical validation based on differential copy number between recurrence and non-recurrence SCC tumour samples. Genes technically validated advanced to tests of biological replication by qPCR using an independent test set of 72 primary lung SCC tumour samples. 18q22.3 loss was identified by aCGH as significantly associated with recurrence (p=0.038). Although aCGH copy number loss associated with recurrence was found for seven genes within 18q22.3, only SOCS6 copy number loss was both technically replicated by qPCR and biologically validated in the test set.