scholarly journals Comprehensive analysis of lymph nodes metastasis associated genes in cervical cancer and its significance in treatment and prognosis

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ping Yang ◽  
Youqin Ruan ◽  
Zhiling Yan ◽  
Yang Gao ◽  
Hongying Yang ◽  
...  
Keyword(s):  
Lymph Node ◽  
High Risk ◽  
Lymph Node Metastasis ◽  
Cervical Carcinoma ◽  
Risk Score ◽  
Risk Groups ◽  
Node Metastasis ◽  
Prognostic Gene ◽  
Prognostic Gene Signature ◽  
Score Model

Abstract Background Cervical carcinoma is one of the most common malignant tumors of the female reproductive system. Lymph nodes metastasis, the most common metastasis, which can be detected even in small-size tumor patients, results in worse prognosis. Therefore, it is of great significance to explore novel lymph nodes metastasis associated biomarkers, which can predict the prognosis and provide a good reference for clinical decision making in cervical carcinoma patients. However, systematic and comprehensive studies related to the key molecules in lymph node metastasis in cervical carcinoma patients are still absent. Methods Transcriptome and clinical data of 307 cervical carcinoma patients were obtained from The Cancer Genome Atlas (TCGA). Then, survival of patients with and without lymph node metastasis was analyzed by Kaplan-Meier (K-M) curves. Differential expressed genes (DEGs) were detected between tumor and control samples using limma package and defined as lymph node metastasis related genes. Univariate and multivariate Cox regression analyses were carried out to screen robust prognostic gene signature. The risk score model and nomogram for predicting survival were constructed based on prognostic gene signature. The performance of the risk score model was evaluated by operating characteristic (ROC) curves. Based on risk score, patients were divided into low- and high- risk groups. DEGs, functional enrichment analysis and tumor microenvironment (immune infiltration and expressions of immune checkpoints) were detected in low- and high-risk groups. Results A total of 103 lymph node metastasis-associated genes were identified. Univariate and multivariate Cox regression analyses identified TEKT2, LPIN2, FABP4 and CXCL2 as prognostic gene signature. The risk score model was constructed and validated in cervical carcinoma patients. 345 DEGs identified between high- and low-risk groups were significantly enriched into immune-related biological processes. Furthermore, we found that the immune infiltration and expressions of immune checkpoints were significantly different between low- and high-risk groups. Conclusion Our study revealed that lymph node metastasis played an important role in the prognosis of cervical carcinoma patients. Furthermore, we established a risk score model based on lymph node metastasis related genes, which could accurately predict the survival of cervical carcinoma patients. Besides, our findings in tumor microenvironments of low- and high-risk groups improved our understanding of the relationship between lymph node metastasis related genes and cervical carcinoma.

scholarly journals Comprehensive Analysis of Lymph Nodes Metastasis Associated Genes in Cervical Cancer and its Significance in Treatment and Prognosis

2021 ◽  
Author(s):  
Ping Yang ◽  
Youqing Ruan ◽  
Zhiling Yan ◽  
Yang Gao ◽  
Hongying Yang ◽  
...  
Keyword(s):  
Lymph Node ◽  
High Risk ◽  
Lymph Node Metastasis ◽  
Cervical Carcinoma ◽  
Risk Score ◽  
Risk Groups ◽  
Node Metastasis ◽  
Prognostic Gene ◽  
Prognostic Gene Signature ◽  
Score Model

Abstract Background: Cervical carcinoma is one of the most common malignant tumors of the female reproductive system. Lymph nodes metastasis, the most common metastasis, which can be detected even in small-size tumor patients, results in worse prognosis. Therefore, it is of great significance to explore novel lymph nodes metastasis associated biomarkers, which can predict the prognosis and provide a good reference for clinical decision making in cervical carcinoma patients. However, systematic and comprehensive studies related to the key molecules in lymph node metastasis in cervical carcinoma patients are still absent. Methods: Transcriptome and clinical data of 307 cervical carcinoma patients were obtained from The Cancer Genome Atlas (TCGA). Then, survival of patients with and without lymph node metastasis was analyzed by Kaplan-Meier (K-M) curves. Differential expressed genes (DEGs) were detected between tumor and control samples using limma package and defined as lymph node metastasis related genes. Univariate and multivariate Cox regression analyses were carried out to screen robust prognostic gene signature. The risk score model and nomogram for predicting survival were constructed based on prognostic gene signature. The performance of the risk score model was evaluated by operating characteristic (ROC) curves. Based on risk score, patients were divided into low- and high- risk groups. DEGs, functional enrichment analysis and tumor microenvironment (immune infiltration and expressions of immune checkpoints) were detected in low- and high-risk groups. Results: A total of 103 lymph node metastasis-associated genes were identified. Univariate and multivariate Cox regression analyses identified TEKT2, LPIN2, FABP4 and CXCL2 as prognostic gene signature. The risk score model was constructed and validated in cervical carcinoma patients. 345 DEGs identified between high- and low-risk groups were significantly enriched into immune-related biological processes. Furthermore, we found that the immune infiltration and expressions of immune checkpoints were significantly different between low- and high-risk groups.Conclusion: Our study revealed that lymph node metastasis played an important role in the prognosis of cervical carcinoma patients. Furthermore, we established a risk score model based on lymph node metastasis related genes, which could accurately predict the survival of cervical carcinoma patients. Besides, our findings in tumor microenvironments of low- and high-risk groups improved our understanding of the relationship between lymph node metastasis related genes and cervical carcinoma.

The prominent value of apparent diffusion coefficient in assessing high-risk factors and prognosis for patients with endometrial carcinoma before treatment

2020 ◽  
pp. 028418512094027
Author(s):  
Quan Quan ◽  
Yunfeng Lu ◽  
Beibei Xuan ◽  
Jingxian Wu ◽  
Wanchun Yin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Diffusion Coefficient ◽  
Lymph Node ◽  
High Risk ◽  
Lymph Node Metastasis ◽  
Apparent Diffusion Coefficient ◽  
Treatment Schedule ◽  
Node Metastasis ◽  
High Risk Factors ◽  
Apparent Diffusion

Background To date, there are no consensus methods to evaluate the high-risk factors and prognosis for managing the personalized treatment schedule of patients with endometrial carcinoma (EC) before treatment. Apparent diffusion coefficient (ADC) is regarded as a kind of technique to assess heterogeneity of malignant tumor. Purpose To explore the role of ADC value in assessing the high-risk factors and prognosis of EC. Material and Methods A retrospective analysis was made on 185 patients with EC who underwent 1.5-T magnetic resonance imaging (MRI). Mean ADC (mADC), minimum ADC (minADC), and maximum ADC (maxADC) were measured and compared in different groups. Results Among the 185 patients with EC, the mADC and maxADC values in those with high-risk factors (type 2, deep myometrial invasion, and lymph node metastasis) were significantly lower than in those without. According to receiver operating characteristic (ROC) curve analysis, the areas under the curve (AUC) were significant for mADC, minADC, and maxADC predicting high-risk factors. Furthermore, the AUCs were significant for mADC and maxADC predicting lymph node metastasis but were not significant for minADC. Patients with lower mADC were associated with worse overall survival and disease-free survival; the opposite was true for patients with higher mADC. Conclusion Our study showed that ADC values could be applied to assess the high-risk factors of EC before treatment and might significantly relate to the prognosis of EC. It might contribute to managing initial individualized treatment schedule and improve outcome in patients with EC.

scholarly journals Development and Verification of the Hypoxia- and Immune-Associated Prognostic Signature for Pancreatic Ductal Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Dongjie Chen ◽  
Hui Huang ◽  
Longjun Zang ◽  
Wenzhe Gao ◽  
Hongwei Zhu ◽  
...  
Keyword(s):  
High Risk ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Risk Score ◽  
Cox Regression ◽  
Pearson Correlation ◽  
Risk Groups ◽  
Low Risk ◽  
Ductal Adenocarcinoma ◽  
Prognostic Signature ◽  
Score Model

We aim to construct a hypoxia- and immune-associated risk score model to predict the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC). By unsupervised consensus clustering algorithms, we generate two different hypoxia clusters. Then, we screened out 682 hypoxia-associated and 528 immune-associated PDAC differentially expressed genes (DEGs) of PDAC using Pearson correlation analysis based on the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression project (GTEx) dataset. Seven hypoxia and immune-associated signature genes (S100A16, PPP3CA, SEMA3C, PLAU, IL18, GDF11, and NR0B1) were identified to construct a risk score model using the Univariate Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, which stratified patients into high- and low-risk groups and were further validated in the GEO and ICGC cohort. Patients in the low-risk group showed superior overall survival (OS) to their high-risk counterparts (p < 0.05). Moreover, it was suggested by multivariate Cox regression that our constructed hypoxia-associated and immune-associated prognosis signature might be used as the independent factor for prognosis prediction (p < 0.001). By CIBERSORT and ESTIMATE algorithms, we discovered that patients in high-risk groups had lower immune score, stromal score, and immune checkpoint expression such as PD-L1, and different immunocyte infiltration states compared with those low-risk patients. The mutation spectrum also differs between high- and low-risk groups. To sum up, our hypoxia- and immune-associated prognostic signature can be used as an approach to stratify the risk of PDAC.

scholarly journals Immune‐related Long Noncoding RNA Signature for Patients with Cervical Cancer

2020 ◽  
Author(s):  
Jianfeng Zheng ◽  
Jinyi Tong ◽  
Benben Cao ◽  
Xia Zhang ◽  
Zheng Niu
Keyword(s):  
Cervical Cancer ◽  
High Risk ◽  
Risk Score ◽  
Immune Cell ◽  
Risk Group ◽  
Risk Groups ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Training Set ◽  
Score Model

Abstract Background: Cervical cancer (CC) is a common gynecological malignancy for which prognostic and therapeutic biomarkers are urgently needed. The signature based on immune‐related lncRNAs(IRLs) of CC has never been reported. This study aimed to establish an IRL signature for patients with CC.Methods: The RNA-seq dataset was obtained from the TCGA, GEO, and GTEx database. The immune scores（IS）based on single-sample gene set enrichment analysis (ssGSEA) were calculated to identify the IRLs, which were then analyzed using univariate Cox regression analysis to identify significant prognostic IRLs. A risk score model was established to divide patients into low-risk and high-risk groups based on the median risk score of these IRLs. This was then validated by splitting TCGA dataset(n=304) into a training-set(n=152) and a valid-set(n=152). The fraction of 22 immune cell subpopulations was evaluated in each sample to identify the differences between low-risk and high-risk groups. Additionally, a ceRNA network associated with the IRLs was constructed.Results: A cohort of 326 CC and 21 normal tissue samples with corresponding clinical information was included in this study. Twenty-eight IRLs were collected according to the Pearson’s correlation analysis between immune score and lncRNA expression (P < 0.01). Four IRLs (BZRAP1-AS1, EMX2OS, ZNF667-AS1, and CTC-429P9.1) with the most significant prognostic values (P < 0.05) were identified which demonstrated an ability to stratify patients into low-risk and high-risk groups by developing a risk score model. It was observed that patients in the low‐risk group showed longer overall survival (OS) than those in the high‐risk group in the training-set, valid-set, and total-set. The area under the curve (AUC) of the receiver operating characteristic curve (ROC curve) for the four IRLs signature in predicting the one-, two-, and three-year survival rates were larger than 0.65. In addition, the low-risk and high-risk groups displayed different immune statuses in GSEA. These IRLs were also significantly correlated with immune cell infiltration. Conclusions: Our results showed that the IRL signature had a prognostic value for CC. Meanwhile, the specific mechanisms of the four-IRLs in the development of CC were ascertained preliminarily.

High-grade Papillary Early Gastric Carcinoma With High Risk for Lymph Node Metastasis and Poor Prognosis

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Yuqing Cheng ◽  
Mingzhan Du ◽  
Xiaoli Zhou ◽  
Lingchuan Guo ◽  
Kequn Xu ◽  
...  
Keyword(s):  
Lymph Node ◽  
High Risk ◽  
Lymph Node Metastasis ◽  
Gastric Carcinoma ◽  
Poor Prognosis ◽  
Early Gastric Carcinoma ◽  
High Grade ◽  
Node Metastasis

scholarly journals Upregulation of miR-205 induces CHN1 expression, which is associated with the aggressive behaviour of cervical cancer cells and correlated with lymph node metastasis

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jianbing Liu ◽  
Yunfeng Li ◽  
Xihua Chen ◽  
Xiangbo Xu ◽  
Haoqi Zhao ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Lymph Node ◽  
High Risk ◽  
Cell Growth ◽  
Lymph Node Metastasis ◽  
Cancer Cells ◽  
Migration And Invasion ◽  
Node Metastasis ◽  
Cervical Cancer Cells ◽  
Human Cervical Cancer

Abstract Background Cervical cancer is the leading cause of cancer-related death in women worldwide. However, the mechanisms mediating the development and progression of cervical cancer are unclear. In this study, we aimed to elucidate the roles of microRNAs and a1-chimaerin (CHN1) protein in cervical cancer progression. Methods The expression of miR-205 and CHN1 protein was investigated by in situ hybridisation and immunohistochemistry. We predicted the target genes of miR-205 using software prediction and dual luciferase assays. The expression of mRNAs and proteins was tested by qRT-PCR and western blotting respectively. The ability of cell growth, migration and invasion was evaluated by CCK-8 and transwell. Cell apoptosis was analysed by flow cytometry analysis. Results We found that miR-205 and CHN1 were highly expressed in human cervical cancer tissue compared with paired normal cervical tissues. The CHN1 gene was shown to be targeted by miR-205 in HeLa cells. Interestingly, transfection with miR-205 mimic upregulated CHN1 mRNA and protein, while miR-205 inhibitor downregulated CHN1 in high-risk and human papilloma virus (HPV)-negative human cervical cancer cells in vitro,. These data suggested that miR-205 positively regulated the expression of CHN1. Furthermore, the miR-205 mimic promoted cell growth, apoptosis, migration, and invasion in high-risk and HPV-negative cervical cancer cells, while the miR-205 inhibitor blocked these biological processes. Knockdown of CHN1 obviously reduced the aggressive cellular behaviours induced by upregulation of miR-205, suggesting that miR-205 positively regulated CHN1 to mediate these cell behaviours during the development of cervical cancer. Furthermore, CHN1 was correlated with lymph node metastasis in clinical specimens. Conclusions Our findings showed that miR-205 positively regulated CHN1 to mediate cell growth, apoptosis, migration, and invasion during cervical cancer development, particularly for high-risk HPV-type cervical cancer. These findings suggested that dysregulation of miR-205 and subsequent abnormalities in CHN1 expression promoted the oncogenic potential of human cervical cancer.

scholarly journals Predictors of Survival in Women with High-Risk Endometrial Cancer and Comparisons of Sandwich versus Concurrent Adjuvant Chemotherapy and Radiotherapy

2020 ◽  
Vol 17 (16) ◽  
pp. 5941
Author(s):  
Hui-Hua Chen ◽  
Wan-Hua Ting ◽  
Hsu-Dong Sun ◽  
Ming-Chow Wei ◽  
Ho-Hsiung Lin ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Endometrial Cancer ◽  
Lymph Node ◽  
High Risk ◽  
Lymph Node Metastasis ◽  
Cancer Patients ◽  
Body Mass ◽  
Paraaortic Lymph Node ◽  
Node Metastasis ◽  
Paraaortic Lymph Node Metastasis

Background: to elucidate the predictors of progression-free survival (PFS) and overall survival (OS) in high-risk endometrial cancer patients. Methods: the medical records of all consecutivewomen with high-risk endometrial cancer were reviewed. Results: among 92 high-risk endometrial cancer patients, 30 women experienced recurrence, and 21 women died. The 5-year PFS and OS probabilities were 65.3% and 75.9%, respectively. Multivariable Cox regression revealed that body mass index (hazard ratio (HR) = 1.11), paraaortic lymph node metastasis (HR = 11.11), lymphovascular space invasion (HR = 5.61), and sandwich chemoradiotherapy (HR = 0.15) were independently predictors of PFS. Body mass index (HR = 1.31), paraaortic lymph node metastasis (HR = 32.74), non-endometrioid cell type (HR = 11.31), and sandwich chemoradiotherapy (HR = 0.07) were independently predictors of OS. Among 51 women who underwent sandwich (n = 35) or concurrent (n = 16) chemoradiotherapy, the use of sandwich chemoradiotherapy were associated with better PFS (adjusted HR = 0.26, 95% CI = 0.08–0.87, p = 0.03) and OS (adjusted HR = 0.11, 95% CI = 0.02–0.71, p = 0.02) compared with concurrent chemoradiotherapy. Conclusion: compared with concurrent chemoradiotherapy, sandwich chemoradiotherapy was associated with better PFS and OS in high-risk endometrial cancer patients. In addition, high body mass index, paraaortic lymph node metastasis, and non-endometrioid cell type were also predictors of poor OS in high-risk endometrial cancer patients.

Sign in / Sign up

Export Citation Format

Share Document