Project description:Lymphocytes and neutrophils are involved in the immune response against cancer. This study aimed to investigate the relationship between lymphocyte percentage/neutrophil percentage and the clinical characteristics of lung cancer patients, and to explore whether they could act as valuable predictors to ameliorate lung cancer prognosis. A total of 1312 patients were eligible to be recruited. Lymphocyte percentage and neutrophil percentage were classified based on their reference ranges. Survival curves were determined using Kaplan-Meier method, and univariate and multivariate cox regression analyses were performed to identify the significant predictors. Decision curve analysis was used to evaluate the clinical benefit. The results of both training and validation cohorts indicated that lymphocyte percentage exhibited high correlation with clinical characteristics and metastasis of lung cancer patients. Both lymphocyte percentage and neutrophil percentage were closely associated with survival status (all p < 0.0001). Low lymphocyte percentage could act as an indicator of poor prognosis; it offered a higher clinical benefit when combined with the clinical characteristic model. Our findings suggested that pretreatment lymphocyte percentage served as a reliable predictor of lung cancer prognosis, and it was also an accurate response indicator in lung adenocarcinoma and advanced lung cancer. Measurement of lymphocyte percentage improved the clinical utility of patient characteristics in predicting mortality of lung cancer patients.
Project description:The EIF3 gene family is essential in controlling translation initiation during the cell cycle. The significance of the EIF3 subunits as prognostic markers and therapeutic targets in breast cancer is not yet clear. We analyzed the expression of EIF3 subunits in breast cancer on the GEPIA and Oncomine databases and compared their expression in breast cancer and normal tissues using BRCA data downloaded from TCGA. Then we performed clinical survival analysis on the Kaplan-Meier Plotter database and clinicopathologic analysis on the bc-genexMiner v4.1 database. And EIF3B was chosen for mutation analysis via the Cancer SEA online tool. Meanwhile, we performed the immunohistochemical assay, real-time RT-PCR, and Western blotting to analyze EIF3B expression levels in breast cancer. An EIF3B knockdown and a negative control cell line were conducted for MTT assay and cell cycle analysis to assess cell growth. Specifically, the results of TCGA and online databases demonstrated that upregulated EIF3B was associated with poorer overall and advanced tumor progression. We also confirmed that EIF3B was more highly expressed in breast cancer cells and tissues than normal and correlated with a worse outcome. And knockdown of EIF3B expression inhibited the cell cycle and proliferation. Furthermore, EIF3B was highly mutated in breast cancer. Collectively, our results suggested EIF3B as a potential prognostic marker and therapeutic target for breast cancer.
Project description:BackgroundThe migration of lymphocytes shares many similarities in mode and mechanism with the metastasis of lung cancer tumor cells. But changes in the expression of lymphocyte migration regulation related proteins in urine exosomes remain unclear. This study is to investigate the expression changes of lymphocyte migration regulation related proteins in urine exosomes of lung cancer patients, and further verify their correlation with the development and progression of lung cancer.MethodsUrine exosomes were collected from lung cancer patients and healthy people aged 15-79 years. Mass spectrometry was used to screen and explore the expression changes of lymphocyte migration regulation related proteins in healthy people of different ages. Enzyme-linked immunosorbent assay and western blotting were used to detect the expression changes of lymphocyte migration regulation related proteins in lung cancer patients.ResultsAnalyzing the data of urine exosome proteomics, a total of 12 lymphocyte related proteins were identified, 5 of which were lymphocyte migration regulation related proteins. Among these proteins, WASL and STK10 proteins showed a gradual decrease in expression with age, and WNK1 protein showed a gradual increase. Lung cancer patients had reduced expression of WASL and increased expression of STK10 and WNK1 proteins in urine exosomes compared to normal people. Urine exosome WASL, STK10, and WNK1 were diagnosed with lung cancer, with a combined AUC of 0.760.ConclusionsLymphocyte migration regulation related proteins were differentially expressed in the urine exosome of lung cancer patients, and WASL, STK10 and WNK1 may serve as potential biomarkers for lung cancer diagnosis.
Project description:The present study aimed to elucidate the prognostic mutation signature (PMS) associated with long-term survival in a diffuse large B-cell lymphoma (DLBCL) cohort. All data including derivation and validation cohorts were retrospectively retrieved from The Cancer Genome Atlas (TCGA) database and whole-exome sequencing (WES) data. The Lasso Cox regression analysis was used to construct the PMS based on WES data, and the PMS was determined using the area under the receiver operating curve (AUC). The predictive performance of eligible PMS was analyzed by time-dependent receiver operating curve (ROC) analyses. After the initial evaluation, a PMS composed of 94 PFS-related genes was constructed. Notably, this constructed PMS accurately predicted the 12-, 36-, and 60-month PFS, with AUC values of 0.982, 0.983, and 0.987, respectively. A higher level of PMS was closely linked to a significantly worse PFS, regardless of the molecular subtype. Further evaluation by forest plot revealed incorporation of international prognostic index or tumor mutational burden into PMS increased the prediction capability for PFS. The drug-gene interaction and pathway exploration revealed the PFS-related genes were associated with DNA damage, TP53, apoptosis, and immune cell functions. In conclusion, this study utilizing a high throughput genetic approach demonstrated that the PMS could serve as a prognostic predictor in DLBCL patients. Furthermore, the identification of the key signaling pathways for disease progression also provides information for further investigation to gain more insight into novel drug-resistant mechanisms.
Project description:BackgroundNumerous studies have found that infiltrating M2 macrophages play an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of M2 macrophage infiltration and M2 macrophage-related genes in immunotherapy and clinical outcomes remain obscure.MethodsSample information was extracted from TCGA and GEO databases. The TIME landscape was revealed using the CIBERSORT algorithm. Weighted gene co-expression network analysis (WGCNA) was used to find M2 macrophage-related gene modules. Through univariate Cox regression, lasso regression analysis, and multivariate Cox regression, the genes strongly associated with the prognosis of LUAD were screened out. Risk score (RS) was calculated, and all samples were divided into high-risk group (HRG) and low-risk group (LRG) according to the median RS. External validation of RS was performed using GSE68571 data information. Prognostic nomogram based on risk signatures and other clinical information were constructed and validated with calibration curves. Potential associations of tumor mutational burden (TMB) and risk signatures were analyzed. Finally, the potential association of risk signatures with chemotherapy efficacy was investigated using the pRRophetic algorithm.ResultsBased on 504 samples extracted from TCGA database, 183 core genes were identified using WGCNA. Through a series of screening, two M2 macrophage-related genes (GRIA1 and CLEC3B) strongly correlated with LUAD prognosis were finally selected. RS was calculated, and prognostic risk nomogram including gender, age, T, N, M stage, clinical stage, and RS were constructed. The calibration curve shows that our constructed model has good performance. HRG patients were suitable for new ICI immunotherapy, while LRG was more suitable for CTLA4-immunosuppressive therapy alone. The half-maximal inhibitory concentrations (IC50) of the four chemotherapeutic drugs (metformin, cisplatin, paclitaxel, and gemcitabine) showed significant differences in HRG/LRG.ConclusionsIn conclusion, a comprehensive analysis of the role of M2 macrophages in tumor progression will help predict prognosis and facilitate the advancement of therapeutic techniques.
Project description:BackgroundFor selected early stage small cell lung cancer (SCLC), curative intent surgery is often performed. Previous studies, predominantly from East Asia, reported that high neutrophil to lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) correlate with poor prognosis in several types of tumors including SCLC. Our aim was to investigate the prognostic value of NLR and PLR in Caucasian patients with resected SCLC, as potential tool to select patients for multimodal treatment including surgery.MethodsConsecutive patients evaluated at three centers between 2000 and 2013 with histologically confirmed and surgically resected SCLC were retrospectively analyzed. NLR and PLR at diagnosis was used to categorize patients into "high" and "low" groups based on receiver operating curve analysis. Univariate and multivariate analyses were used to evaluate the impact of clinical and pathological characteristics on outcome.ResultsThere were a total of 189 patients with a median age of 58 years, and the majority had stage I or II disease. We found a significant correlation between NLR and tumor stage (p = 0.007) and age (p = 0.038). Low NLR (LNLR) was associated with significantly longer overall survival, while PLR had no prognostic impact. There were significant associations between NLR and PLR but not with gender, vascular involvement, tumor necrosis, peritumoral inflammation, or tumor grade.ConclusionPre-operative LNLR may be a favorable prognostic factor in stage I-II SCLCs. PLR is not prognostic in this population. LNLR is easy to assess and can be integrated into routine clinical practice. Further prospective studies are needed to confirm these observations.
Project description:Gene-expression profiling can be used to classify human tumors into molecular subtypes or risk groups, representing potential future clinical tools for treatment prediction and prognostication. However, it is less well-known how prognostic gene signatures derived in one malignancy perform in a pan-cancer context. In this study, a gene-rule-based single sample predictor (SSP) called classifier for lung adenocarcinoma molecular subtypes (CLAMS) associated with proliferation was tested in almost 15 000 samples from 32 cancer types to classify samples into better or worse prognosis. Of the 14 malignancies that presented both CLAMS classes in sufficient numbers, survival outcomes were significantly different for breast, brain, kidney and liver cancer. Patients with samples classified as better prognosis by CLAMS were generally of lower tumor grade and disease stage, and had improved prognosis according to other type-specific classifications (e.g. PAM50 for breast cancer). In all, 99.1% of non-lung cancer cases classified as better outcome by CLAMS were comprised within the range of proliferation scores of lung adenocarcinoma cases with a predicted better prognosis by CLAMS. This finding demonstrates the potential of tuning SSPs to identify specific levels of for instance tumor proliferation or other transcriptional programs through predictor training. Together, pan-cancer studies such as this may take us one step closer to understanding how gene-expression-based SSPs act, which gene-expression programs might be important in different malignancies, and how to derive tools useful for prognostication that are efficient across organs.
Project description:Lung cancer is the leading cause of cancer mortality worldwide and tumor metastasis is the major cause of cancer-related death. Our previous study suggested that Homeobox A5 (HOXA5) could inhibit lung cancer cell invasion via regulating cytoskeletal remodeling and involved in tumor metastasis. Recently, consensus HOX binding sites was found in the p53 gene promoter region. However, whether the HOXA5 could cooperate with p53 and contribute the inhibition of lung cancer cell invasion is still unclear. The aim of the current study is to elucidate the correlation of HOXA5 and p53 in tumor invasion and its prognostic influence in lung cancer patient specimens. Totally 71 cases of primary non-small cell lung cancer (NSCLC) were collected. The median follow-up period is 6.8 years. Immunohistochemical stain for p53 and HOXA5 were performed. Kaplan-Meier plot was done for overall survival analysis. In addition, lung cancer cell lines transfected with wild-type or mutated p53 constructs were overexpressed with HOXA5 for invasion assay. In human specimens, HOXA5 expressed mainly in the cytoplasm (54.1%) rather than nuclei (14.6%) of the NSCLC tumor part. The HOXA5 expression is higher in adenocarcinoma than in squamous cell carcinoma (P < 0.001). In addition, poor prognosis is seen in group with both non-immunoreactive for p53 and HOXA5. HOXA5 and p53 could cooperate to inhibit tumor cell invasion significantly partly by decreasing MMP2 activity in a concentration-dependent manner. Our studies provide new insights into how HOXA5 and p53 cooperate to contribute to the suppression of lung cancer cell invasion and play good prognostic roles in NSCLC.
Project description:The aim of this study was to investigate the usefulness of a novel inflammation-based prognostic system, called COP-LMR (combination of platelet count and lymphocyte to monocyte ratio), for predicting postoperative survival of patients with non-small cell lung cancer (NSCLC). COP-LMR was calculated on the basis of the obtained data. Patients with both an elevated platelet count (PLT) (>30 × 104mm-3) and a low LMR (<3.6) were assigned a score of 2, and patients with one or none of the parameters were assigned a score of 1 or 0, respectively. A total of 1120 patients who underwent complete resection were enrolled in this study. Multivariate analysis revealed that COP-LMR is an independent prognostic factor for disease-free survival (DFS) (P<0.001) and overall survival (OS) (P<0.001). Kaplan-Meier analysis and the log-rank test revealed that COP-LMR stratified the patients into 3 independent groups (P<0.001). In conclusion, COP-LMR is a potential prognostic biomarker in patients undergoing surgery for NSCLC.
Project description:As an indispensable part for cancer precision medicine, biomarkers and signatures for predicting cancer prognosis and therapeutic benefits were urgently required. The purpose of this study was to investigate the prognostic roles of NOP2 in renal clear cell carcinoma (ccRCC) for overall survival (OS) and its relationships with immunity. NOP2-related gene expression matrix associated with clinical information was obtained from the Cancer Genome Atlas (TCGA) ccRCC dataset and NOP2-related pathways were identified by gene set enrichment analysis (GSEA). Associations among the NOP2 expression and MSI, TMB, TNB, and immunity were also explored. Both the NOP2 mRNA and protein/phosphoprotein had a higher expression in ccRCC tumor tissues than in normal kidney tissues (both P < 0.001) and elevated NOP2 expression was associated with poor OS (P < 0.001). Logistic regression analysis revealed the NOP2 expression was significantly linked to stage, age, grade, N stage, T stage, and M stage (all P < 0.05). Univariate/multivariate Cox hazard regression analysis results indicated that NOP2 was an independent prognostic factor for OS in ccRCC and GSEA revealed five NOP2-related signaling pathways. Nomogram based on NOP2 and eight clinical characteristic parameters (grade, age, stage, gender, T stage, race, M stage, N stage) was constructed and carefully evaluated. Furthermore, NOP2 gene expression was also found to be significantly related to MSI, TMB, and immunity. Our findings revealed that NOP2 might be a potential prognostic factor for OS in ccRCC and it was significantly associated with immunity, MSI, and TMB.