scholarly journals Tumor microenvironmental prognosis analysis and molecular labeling of immune-related genes in Luminal B type breast cancer

2019 ◽  
Author(s):  
Fengjiao Gan ◽  
Kang Hu ◽  
Xiaomei Li ◽  
Ni Jiang ◽  
Qiaoyuan Wu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Molecular Subtype ◽  
Clinical Results ◽  
Genomic Variation ◽  
Immune Gene ◽  
Cox Regression Analysis ◽  
Luminal B ◽  
The Relationship

Abstract Background: Tumor microenvironment (TME) cells is one of the important elements, constitute the tumor tissues and in predicting tumor clinical results and treatment effect has the important significance of clinical pathology. However, a detailed map for prognostic landscape of TME in Luminal B breast cancer is still lacking. Methods: ownloaded the expression profile and clinical follow-up information of luminal B breast cancer from TCGA and GEO, and used CIBERSORT to evaluate the infiltration mode of TME in 209 patients, and constructed the molecular subtype of luminal B breast cancer based on TME, further evaluated the relationship between molecular subtype and prognosis. DESeq2 was used to analyze the differentially expressed genes among molecular subtypes of luminal B breast cancer, and cox multivariate regression analysis was used for feature selection to construct TME signature. Results: ased on the median value of TMEscore, the samples were divided into High TMEscore and Low TMEscroe, and the relationship with prognosis, clinical features, immune gene expression and genomic variation was further evaluated. Different TME cells have significant correlation in luminal B breast cancer. These TME cells stratified different clinical results of luminal B breast cancer, and further TMEscore was established by Cox regression analysis. High TME score is associated with poor prognosis. Meanwhile, this study showed that CXCL10, CXCL9, GZMB and other immune activation genes and PDCD1LG2 and other immune checkpoint genes have higher expression levels in high TME score, and the mutation frequency of TP53 gene was lower in risk-H than that in risk-L. Conclusion: In this study, we systematically evaluated the TME infiltration patterns of 209 TCGA luminal B breast cancer patients and developed the TME score approach. It was found that TME score is a powerful prognostic biomarker and predictor of response to immunocheckpoint inhibitors and provides a new strategy for luminal B breast cancer immunotherapy.

scholarly journals Identification and development of an independent immune-related genes prognostic model for breast cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lin Chen ◽  
Yuxiang Dong ◽  
Yitong Pan ◽  
Yuhan Zhang ◽  
Ping Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Validation Dataset ◽  
Immune Gene ◽  
Cox Regression Analysis ◽  
Immune Genes ◽  
Immune Related Genes

Abstract Background Breast cancer is one of the main malignant tumors that threaten the lives of women, which has received more and more clinical attention worldwide. There are increasing evidences showing that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients and construct an immune-related genes prognostic index. Methods The list of 2498 immune genes was obtained from ImmPort database. In addition, gene expression data and clinical characteristics data of BC patients were also obtained from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P < 0.05 was considered to be statistically significant. Results In total, 556 immune genes were differentially expressed between normal tissues and BC tissues (p < 0. 05). According to the univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P < 0.05). Finally, a 15 immune genes risk scores model was established. All patients were divided into high- and low-groups. KM survival analysis revealed that high immune risk scores represented worse survival (p < 0.001). ROC curve indicated that the immune genes risk scores model had a good reliability in predicting prognosis (5-year OS, AUC = 0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC = 0.685, 5-year OS AUC = 0.717, P = 0.00048). Moreover, the immune risk signature was proved to be an independent prognostic factor for BC patients. Finally, it was found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways. Conclusion In conclusion, our study provides a new perspective for the expression of immune genes in BC. The constructed model has potential value for the prognostic prediction of BC patients and may provide some references for the clinical precision immunotherapy of patients.

scholarly journals Identification of an Independent Immune-Genes Prognostic Index for Breast Cancer

2020 ◽  
Author(s):  
Deng Rong ◽  
Yu yun ◽  
Lin chen ◽  
Dong Yuxiang ◽  
Pan Yitong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Prognostic Index ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Validation Dataset ◽  
Immune Gene ◽  
Cox Regression Analysis ◽  
Immune Genes

Abstract Objective: There are increasing evidences that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients.Methods: We obtained the list of 2498 immune genes from ImmPort database. In addition, we obtained gene expression data and clinical characteristics data of BC patients from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P< 0.05 was considered to be statistically significant. Results: In total, 556 immune genes were differentially expressed in normal tissues and BC tissues (p<0. 05). In univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P<0.05). Through lasso regression analysis, a 15 immune genes risk scores model was established. KM survival analysisrevealed that high immune risk scores represented worse survival (p<0.001). ROC curve indicated that the immune genes risk scores model had good a reliability in predicting prognosis (5-year OS, AUC=0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC=0.685, 5-year OS AUC=0.717, P=0.00048). Moreover, immune risk scoreswere proved to be an independent influencing factor for BC patients. Finally, we found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways.Conclusion:In a word, our study provides a new perspective for the expression of immune genes in BC. In addition, the immune risk scores have considerable advantages in predicting the survival of BC, which ares associated with a variety of oncogenic pathways.

scholarly journals Clonal Architectures Predict Clinical Outcome in Gastric Adenocarcinoma Based on Genomic Variation, Tumor Evolution, and Heterogeneity

2021 ◽  
Vol 30 ◽  
pp. 096368972198960
Author(s):  
Chenxia Ren ◽  
Cuiling Wu ◽  
Niuniu Wang ◽  
Changhong Lian ◽  
Changqing Yang
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Genomic Variation ◽  
Systematic Evaluation ◽  
Tumor Evolution ◽  
Cox Regression Analysis ◽  
Cancer Cell Fraction ◽  
Gastric Cancer Patients ◽  
The Relationship

Stomach adenocarcinoma (STAD) is a highly heterogeneous disease. Due to the lack of effective molecular markers and personalized treatment, the prognosis of gastric cancer patients is still very poor. The ABSOLUTE algorithm and cancer cell fraction were used to evaluate the clonal and subclonal status of 349 TCGA (The Cancer Genome Cancer Atlas)-STAD patients. Non-negative matrix factorization was used to identify the mutation characteristics of the samples. Univariate Cox regression analysis was used to determine the relationship between clonal/subclonal events and prognosis, and the Spearman correlation was used to evaluate the relationship of clonal/subclonal events to tumor mutation burden (TMB) and neoantigens. The evolution pattern of STAD demonstrated great tumor heterogeneity. TP53, USH2A, and GLI3 appeared earliest in STAD and may drive STAD. CTNNB1, LRP1B, and ERBB4 appeared the latest in STAD, and may be related to STAD’s progress. Univariate Cox regression analysis identified four early genes, eight intermediate genes, and seven late genes significantly associated with overall survival. The number of subclonal events in the T stage was significantly different. The N stage, gender, and histological type were significantly different for clonal events, and there was a significant correlation between clonal/subclonal events and TMB/neoantigens. Our results highlight the importance of systematic evaluation of evolutionary models in the clinical management of STAD and personalized gastric cancer treatment.

scholarly journals The immune‐related biomarker TEK inhibits the development of clear cell renal cell carcinoma (ccRCC) by regulating AKT phosphorylation

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Siming Chen ◽  
Mengxue Yu ◽  
Lingao Ju ◽  
Gang Wang ◽  
Kaiyu Qian ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Regression Analysis ◽  
Molecular Mechanisms ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Survival Prediction ◽  
Immune Gene ◽  
Cox Regression Analysis ◽  
The Relationship

Abstract Background High immunogenicity is an important feature of ccRCC, but its underlying immune-related molecular mechanisms remain unclear. This study aimed to investigate the effect of immune-related gene TEK on ccRCC and its prognostic value. Methods The immune-related differentially expressed genes (DEGs) and transcription factors (TFs) in ccRCC were screened based on The Cancer Genome Atlas (TCGA) database, and a regulatory network of TF was constructed. Prognostic-related immune genes were screened by univariate Cox regression analysis and functional annotation was performed. Univariate and multivariate Cox regression analyses were performed to construct the immune gene risk model and identify the hub gene TEK that independently affected the prognosis of ccRCC. The effectiveness of the TEK was verified by external microarray datasets. The relationship between TEK and immune cells in ccRCC was evaluated based on Tumor Immune Estimation Resource (TIMER). The expression of TEK in clinical specimens was verified by qRT-PCR and immunohistochemical (IHC) staining. MTT and cloning formation assay were used to evaluate cell proliferation. Transwell assays were used to assess cell migration. Apoptosis was assessed by flow cytometry, and the expression of related proteins was detected by Western blot and immunofluorescence. Results We constructed a prognostic model consisting of 12 hub genes and performed risk scores to determine the relationship between these scores and prognosis. Through Cox regression analysis and survival analysis, TEK, an immune marker highly related to survival prognosis, was obtained and validated. In vitro experiments showed that knockdown of TEK promoted the proliferation and migration of ccRCC cells, and we found that TEK promoted apoptosis by regulating the phosphorylation of AKT, thereby inhibiting cell proliferation. Conclusions TEK plays an important role in risk assessment and survival prediction for ccRCC patients as a new immune gene and maybe an emerging target for immunotherapy for ccRCC patients.

scholarly journals The Investigation of Associations between TP53 rs1042522, BBC3 rs2032809, CCND1 rs9344, EGFR rs2227983 Polymorphisms and Breast Cancer Phenotype and Prognosis

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1419
Author(s):  
Justina Bekampytė ◽  
Agnė Bartnykaitė ◽  
Aistė Savukaitytė ◽  
Rasa Ugenskienė ◽  
Erika Korobeinikova ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Cancer Prognosis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Cox Regression Analysis ◽  
Pcr Rflp ◽  
Oncological Diseases ◽  
Cancer Phenotype

Breast cancer is one of the most common oncological diseases among women worldwide. Cell cycle and apoptosis—related genes TP53, BBC3, CCND1 and EGFR play an important role in the pathogenesis of breast cancer. However, the roles of single nucleotide polymorphisms (SNPs) in these genes have not been fully defined. Therefore, this study aimed to analyze the association between TP53 rs1042522, BBC3 rs2032809, CCND1 rs9344 and EGFR rs2227983 polymorphisms and breast cancer phenotype and prognosis. For the purpose of the analysis, 171 Lithuanian women were enrolled. Genomic DNA was extracted from peripheral blood; PCR-RFLP was used for SNPs analysis. The results showed that BBC3 rs2032809 was associated with age at the time of diagnosis, disease progression, metastasis and death. CCND1 rs9344 was associated with tumor size, however an association resulted in loss of significance after Bonferroni correction. In survival analysis, significant associations were observed between BBC3 rs2032809 and OS, PFS and MFS. EGFR rs2227983 also showed some associations with OS and PFS (univariate Cox regression analysis). However, the results were in loss of significance (multivariate Cox regression analysis). In conclusion, BBC3 rs2032809 polymorphism was associated with breast cancer phenotype and prognosis. Therefore, it could be applied as potential markers for breast cancer prognosis.

Factors Predictive of Distant Metastases in Patients With Breast Cancer Who Have a Pathologic Complete Response After Neoadjuvant Chemotherapy

2005 ◽  
Vol 23 (28) ◽  
pp. 7098-7104 ◽  
Author(s):  
Ana M. Gonzalez-Angulo ◽  
Sean E. McGuire ◽  
Thomas A. Buchholz ◽  
Susan L. Tucker ◽  
Henry M. Kuerer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Distant Metastasis ◽  
Cox Regression ◽  
Clinical Stage ◽  
Pathologic Complete Response ◽  
Distant Metastases ◽  
Complete Response ◽  
Cox Regression Analysis

Purpose To identify clinicopathological factors predictive of distant metastasis in patients who had a pathologic complete response (pCR) after neoadjuvant chemotherapy (NC). Methods Retrospective review of 226 patients at our institution identified as having a pCR was performed. Clinical stage at diagnosis was I (2%), II (36%), IIIA (27%), IIIB (23%), and IIIC (12%). Eleven percent of all patients were inflammatory breast cancers (IBC). Ninety-five percent received anthracycline-based chemotherapy; 42% also received taxane-based therapy. The relationship of distant metastasis with clinicopathologic factors was evaluated, and Cox regression analysis was performed to identify independent predictors of development of distant metastasis. Results Median follow-up was 63 months. There were 31 distant metastases. Ten-year distant metastasis-free rate was 82%. Multivariate Cox regression analysis using combined stage revealed that clinical stages IIIB, IIIC, and IBC (hazard ratio [HR], 4.24; 95% CI, 1.96 to 9.18; P < .0001), identification of ≤ 10 lymph nodes (HR, 2.94; 95% CI, 1.40 to 6.15; P = .004), and premenopausal status (HR, 3.08; 95% CI, 1.25 to 7.59; P = .015) predicted for distant metastasis. Freedom from distant metastasis at 10 years was 97% for no factors, 88% for one factor, 77% for two factors, and 31% for three factors (P < .0001). Conclusion A small percentage of breast cancer patients with pCR experience recurrence. We identified factors that independently predicted for distant metastasis development. Our data suggest that premenopausal patients with advanced local disease and suboptimal axillary node evaluation may be candidates for clinical trials to determine whether more aggressive or investigational adjuvant therapy will be of benefit.

scholarly journals Analysis of CK5/6 and EGFR and Its Effect on Prognosis of Triple Negative Breast Cancer

2021 ◽  
Vol 10 ◽  
Author(s):  
Zhen Wang ◽  
Lei Liu ◽  
Ying Li ◽  
Zi’an Song ◽  
Yi Jing ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Multivariate Logistic Regression Analysis ◽  
Pathological Examination ◽  
Cox Regression Analysis ◽  
Tumor Stages

BackgroundTriple-negative breast cancer (TNBC) is considered to be higher grade, more aggressive and have a poorer prognosis than other types of breast cancer. Discover biomarkers in TNBC for risk stratification and treatments that improve prognosis are in dire need.MethodsClinical data of 195 patients with triple negative breast cancer confirmed by pathological examination and received neoadjuvant chemotherapy (NAC) were collected. The expression levels of EGFR and CK5/6 were measured before and after NAC, and the relationship between EGFR and CK5/6 expression and its effect on prognosis of chemotherapy was analyzed.ResultsThe overall response rate (ORR) was 86.2% and the pathological complete remission rate (pCR) was 29.2%. Univariate and multivariate logistic regression analysis showed that cT (clinical Tumor stages) stage was an independent factor affecting chemotherapy outcome. Multivariate Cox regression analysis showed pCR, chemotherapy effect, ypT, ypN, histological grades, and post- NAC expression of CK5/6 significantly affected prognosis. The prognosis of CK5/6-positive patients after NAC was worse than that of CK5/6-negative patients (p=0.036). Changes in CK5/6 and EGFR expression did not significantly affect the effect of chemotherapy, but changes from positive to negative expression of these two markers are associated with a tendency to improve prognosis.ConclusionFor late-stage triple negative breast cancer patients receiving NAC, patients who achieved pCR had a better prognosis than those with non- pCR. Patients with the change in expression of EGFR and CK5/6 from positive to negative after neoadjuvant chemotherapy predicted a better prognosis than the change from negative to positive group.

Immune-related gene based prognostic signature for the risk stratification analysis of breast cancer

2021 ◽  
Vol 16 ◽  
Author(s):  
Dongqing Su ◽  
Qianzi Lu ◽  
Yi Pan ◽  
Yao Yu ◽  
Shiyuan Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Risk Score ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Breast Cancer Patients ◽  
Cox Regression Analysis ◽  
Score Model

Background: Breast cancer has plagued women for many years and caused many deaths around the world. Method: In this study, based on the weighted correlation network analysis, univariate Cox regression analysis and least absolute shrinkage and selection operator, 12 immune-related genes were selected to construct the risk score for breast cancer patients. The multivariable Cox regression analysis, gene set enrichment analysis and nomogram were also conducted in this study. Results: Good results were obtained in the survival analysis, enrichment analysis, multivariable Cox regression analysis and immune-related feature analysis. When the risk score model was applied in 22 breast cancer cohorts, the univariate Cox regression analysis demonstrated that the risk score model was significantly associated with overall survival in most of the breast cancer cohorts. Conclusion: Based on these results, we could conclude that the proposed risk score model may be a promising method, and may improve the treatment stratification of breast cancer patients in the future work.

Abstract P254: Daytime Napping is Associated With Incident Stroke in Community

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Xuting Jin ◽  
Bin Yan ◽  
Ruohan Li ◽  
Ya Gao ◽  
Jingjing Zhang ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Cox Regression ◽  
Life Quality ◽  
Health Study ◽  
Sleep Habits ◽  
Community Based ◽  
Cox Regression Analysis ◽  
Increased Risk ◽  
Registration Number ◽  
The Relationship

Introduction: There are conflicting reports regarding whether daytime napping is a risk factor for cardiovascular events. The purpose of this study was to investigate the relationship between daytime napping and incident stroke within a community-based cohort study. Hypothesis: We assessed the hypothesis that the duration and the frequency of daytime napping may be associated with incident stroke. Methods: Participants without previous stroke were enrolled in the present prospective study from the Sleep Heart Health Study (registration number, NCT00005275). Daytime napping were assessed with a self-reported Sleep Habits Questionnaire. Duration of daytime napping was divided into the following categories: no naps, 0-30 min, 31-60 min, or >60 min. Frequency of naps were categorised as: no naps, 1-2 times/week, 3-4 times/week, 5-6 times/week, or daily. After combining nap duration and frequency, participants were further divided into groups with regular long naps (≥5 times per week and >30 min), regular short naps (≥5 times per week and ≤30 min), irregular naps or no naps. Subsequently, participants were followed up until the first stroke occurred between the date of the completed questionnaire and the final censoring date. Cox regression analysis was used to estimate the relationship between daytime napping and incident stroke. Results: The present study enrolled 4757 participants, of which 220 participants (4.6%) experienced incident stroke during an average follow-up of 10.6 years. There was a higher rate of stroke among participants taking longer and more frequent naps than others. Multivariate Cox regression analysis indicated that, when compared with participants with no naps, those with a nap duration of ≥60 min or of 31-60 min had a higher risk of stroke (HR, 2.182; 95% CI, 1.443-3.301; HR, 1.594; 95% CI, 1.003-2.531, respectively). Moreover, there was an increased risk of stroke among participants taking daily daytime naps (HR, 1.563; 95% CI, 1.059-2.307) or napping 5-6 times per week (HR, 1.548; 95% CI, 1.026-2.335) than those with no naps. And after combining nap duration and frequency, regular long naps and regular short naps were also associated with higher risk of incident stroke (HR, 1.903; 95% CI, 1.182-3.065; HR, 1.451; 95% CI, 1.010-2.084, respectively). Conclusions: In conclusion, daytime napping of long duration and high frequency may increase the risk of incident stroke in community. Modification of sleep habits may improve the life quality among those elderly community-based population.

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