scholarly journals Combining Clinicopathological Parameters and Molecular Indicators to Predict Lymph Node Metastasis in Endometrioid Type Endometrial Adenocarcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Peng Jiang ◽  
Yuzhen Huang ◽  
Yuan Tu ◽  
Ning Li ◽  
Wei Kong ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Low Risk ◽  
Good Discrimination ◽  
Training Cohort ◽  
Node Metastasis ◽  
Risk Probability ◽  
Risk Patients ◽  
Molecular Indicators

BackgroundLymph node metastasis (LNM) is a critical unfavorable prognostic factor in endometrial cancer (EC). At present, models involving molecular indicators that accurately predict LNM are still uncommon. We addressed this gap by developing nomograms to individualize the risk of LNM in EC and to identify a low-risk group for LNM.MethodsIn all, 776 patients who underwent comprehensive surgical staging with pelvic lymphadenectomy at the First Affiliated Hospital of Chongqing Medical University were divided into a training cohort (used for building the model) and a validation cohort (used for validating the model) according to a predefined ratio of 7:3. Logistics regression analysis was used in the training cohort to screen out predictors related to LNM, after which a nomogram was developed to predict LNM in patients with EC. A calibration curve and consistency index (C-index) were used to estimate the performance of the model. A receiver operating characteristic (ROC) curve and Youden index were used to determine the optimal threshold of the risk probability of LNM predicted by the model proposed in this study. Then, the prediction performance of different models and their discrimination abilities for identifying low-risk patients were compared.ResultLNM occurred in 87 and 42 patients in the training and validation cohorts, respectively. Multivariate logistic regression analysis showed that histological grade (P=0.022), myometrial invasion (P=0.002), lymphovascular space invasion (LVSI) (P=0.001), serum CA125 (P=0.008), Ki67 (P=0.012), estrogen receptor (ER) (0.009), and P53 (P=0.003) were associated with LNM; a nomogram was then successfully established on this basis. The internal and external calibration curves showed that the model fits well, and the C-index showed that the prediction accuracy of the model proposed in this study was better than that of the other models (the C-index of the training and validation cohorts was 0.90 and 0.91, respectively). The optimal threshold of the risk probability of LNM predicted by the model was 0.18. Based on this threshold, the model showed good discrimination for identifying low-risk patients.ConclusionCombining molecular indicators based on classical clinical parameters can predict LNM of patients with EC more accurately. The nomogram proposed in this study showed good discrimination for identifying low-risk patients with LNM.

scholarly journals Implications of Isolated Para-Aortic Lymph Node Metastasis in Endometrial Cancer: A Large-Scale, Multicenter, and Retrospective Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Wenting Li ◽  
Jie Jiang ◽  
Yu Fu ◽  
Yuanming Shen ◽  
Chuyao Zhang ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Large Scale ◽  
Low Risk ◽  
Surgical Staging ◽  
Node Metastasis ◽  
Aortic Lymph Node ◽  
Risk Patients ◽  
Metastatic Sites

Objective: To systematically evaluate lymph node metastasis (LNM) patterns in patients with endometrial cancer (EC) who underwent complete surgical staging, which included systematic pelvic and para-aortic lymphadenectomy.Methods: Four thousand and one patients who underwent complete surgical staging including systematic pelvic and para-aortic lymphadenectomy for EC were enrolled from 30 centers in China from 2001 to 2019. We systematically displayed the clinical and prognostic characteristics of patients with various LNM patterns, especially the PLN-PAN+ [para-aortic lymph node (PAN) metastasis without pelvic lymph node (PLN) metastasis]. The efficacy of PAN+ (para-aortic lymph node metastasis) prediction with clinical and pathological features was evaluated.Results: Overall, 431 of the 4,001 patients (10.8%) showed definite LNM according to pathological diagnosis. The PAN+ showed the highest frequency (6.6%) among all metastatic sites. One hundred fourteen cases (26.5%) were PLN-PAN+ (PAN metastasis without PLN metastasis), 167 cases (38.7%) showed PLN+PAN-(PLN metastasis without PAN metastasis), and 150 cases (34.8%) showed metastasis to both regions (PLN+PAN+). There was also 1.9% (51/2,660) of low-risk patients who had PLN-PAN+. There are no statistical differences in relapse-free survival (RFS) and disease-specific survival (DSS) among PLN+PAN-, PLN-PAN+, and PLN+PAN+. The sensitivity of gross PLNs, gross PANs, and lymphovascular space involvement (LVSI) to predict PAN+ was 53.8 [95% confidence interval (CI): 47.6–59.9], 74.2 95% CI: 65.6–81.4), and 45.8% (95% CI: 38.7–53.2), respectively.Conclusion: Over one-fourth of EC patients with LMN metastases were PLN-PAN+. PLN-PAN+ shares approximate survival outcomes (RFS and DSS) with other LNM patterns. No effective clinical methods were achieved for predicting PAN+. Thus, PLN-PAN+ is a non-negligible LNM pattern that cannot be underestimated in EC, even in low-risk patients.

scholarly journals An Immune-related Gene Signature of Predicting Lymph Node Metastasis and Responses to Immune Checkpoint Inhibitor Treatment in Gastric Cancer Patients

2021 ◽  
Author(s):  
Ke-wei Wang ◽  
Mei-dan Wang ◽  
Hua Wang ◽  
Jian-feng Huang ◽  
Xiao-long Wu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
T Cells ◽  
Lymph Node ◽  
High Risk ◽  
Lymph Node Metastasis ◽  
Gene Signature ◽  
Low Risk ◽  
Training Dataset ◽  
Node Metastasis ◽  
Risk Patients

Abstract BackgroundImmune-related genes have been used as prognostic markers in multiple types of tumors. We aimed to develop an immune-related gene signature for predicting individual lymph node metastasis in gastric cancer (GC) patients, characterize the molecular and immune profiles of different risk patients and assess the potential value of this signature identifying patients with response to immune checkpoint inhibitor (ICI) treatment.MethodsA total of 1338 GC patients from a training dataset, three external silico validation datasets and an external clinical dataset were included in this study. The microarray analysis was used to detect differentially expressed immune-related genes (DEIGs) between lymph node metastatic and non-lymph node metastatic gastric cancer tissues. Subsequently, we built a lymph node metastasis gene signature for gastric cancer (LGSGC), and then classified patients into low-risk and high-risk groups according to the LGSGC. Moreover, we implemented association analysis for this signature and the prognosis, molecular characteristics, immune profiles and the response of ICI treatment in different risk GC patients. Resultshe receiver operating characteristics (ROC) curve analysis (an area under curve [AUC] values of 0.85) showed that the LGSGC could distinguish lymph node metastatic patients from non-lymph node metastatic patients in the training dataset. Additionally, compared to low-risk group, high-risk group exhibited worse overall survival (hazard ratio [HR]=2.42) in the training dataset. Robust diagnostic and prognostic clinical ability of the LGSGC were successfully validated in four validation datasets. Next, the high-risk patients were characterized by active cancer and immune response-related pathways, high TP53, CSMD3 and FAT4 mutation rate, high infiltration of Neutrophils, M1 Macrophages, M0 Macrophages, M2 Macrophages, T cells gamma delta and T cells follicular helper, more abundant check point, more aggressive inflammation and Type I IFN response, and more benefit from ICI. On the contrary, low-risk patients were characterized by active cancer and tumor metabolism-related pathways, low TP53 mutation rate, high infiltration of Mast cells resting, NK cells resting, Plasma cells and T cells CD4 memory resting, and less benefit from ICI therapy. Of note, we also validated the LGSGC, which identified patients having response to ICI treatment with an AUC value of 0.71 in an advanced GC dataset and an AUC value of 0.64 in an IMvigor210 dataset. ConclusionsThe LGSGC is a reliable indicator to distinguish LNM in GC and could discriminate the prognosis, molecular characteristics, immune profiles and the response of ICI treatment in different risk groups. This signature may provide a reference for treatment decisions for different risk GC patients.

scholarly journals Real-Time Elastography: A Web-Based Nomogram Improves the Preoperative Prediction of Central Lymph Node Metastasis in cN0 PTC

2022 ◽  
Vol 11 ◽  
Author(s):  
Chunwang Huang ◽  
Wenxiao Yan ◽  
Shumei Zhang ◽  
Yanping Wu ◽  
Hantao Guo ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Lymph Node ◽  
Prediction Model ◽  
Central Lymph Node Metastasis ◽  
Central Lymph Node ◽  
Web Based ◽  
Training Cohort ◽  
Node Metastasis ◽  
Central Lymph ◽  
Risk Predictors

BackgroundGiven the difficulty of accurately determining the central lymph node metastasis (CLNM) status of patients with clinically node-negative (cN0) papillary thyroid carcinoma (PTC) before surgery, this study aims to combine real-time elastography (RTE) and conventional ultrasound (US) features with clinical features. The information is combined to construct and verify the nomogram to foresee the risk of CLNM in patients with cN0 PTC and to develop a network-based nomogram.MethodsFrom January 2018 to February 2020, 1,157 consecutive cases of cN0 PTC after thyroidectomy and central compartment neck dissection were retrospectively analyzed. The patients were indiscriminately allocated (2:1) to a training cohort (771 patients) and validation cohort (386 patients). Multivariate logistic regression analysis of US characteristics and clinical information in the training cohort was performed to screen for CLNM risk predictors. RTE data were included to construct prediction model 1 but were excluded when constructing model 2. DeLong’s test was used to select a forecast model with better receiver operator characteristic curve performance to establish a web-based nomogram. The clinical applicability, discrimination, and calibration of the preferable prediction model were assessed.ResultsMultivariate regression analysis showed that age, sex, tumor size, bilateral tumors, the number of tumor contacting surfaces, chronic lymphocytic thyroiditis, and RTE were risk predictors of CLNM in cN0 PTC patients, which constituted prediction model 1. Model 2 included the first six risk predictors. Comparison of the areas under the curves of the two models showed that model 1 had better prediction performance (training set 0.798 vs. 0.733, validation set 0.792 vs. 0.715, p < 0.001) and good discrimination and calibration. RTE contributed significantly to the performance of the prediction model. Decision curve analysis showed that patients could obtain good net benefits with the application of model 1.ConclusionA noninvasive web-based nomogram combining US characteristics and clinical risk factors was developed in the research. RTE could improve the prediction accuracy of the model. The dynamic nomogram has good performance in predicting the probability of CLNM in cN0 PTC patients.

scholarly journals Serum exosomal miR-4787-3p as potential lymph node metastasis and prognostic marker in esophageal squamous cell carcinoma.

2021 ◽  
Author(s):  
Shuang Liu ◽  
Zheng Lin ◽  
Jianwen Wang ◽  
Zerong Zheng ◽  
Wenqing Rao ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Cox Regression ◽  
High Serum ◽  
Migration And Invasion ◽  
Cox Regression Analysis ◽  
Mirna Array ◽  
Node Metastasis

Abstract Background: To explore the miR-4787-3p expression levels in the serum exosome and tissue and its role in lymph node metastasis and prognosis in ESCC. Methods: The miRNA array was conducted to detect the ESCC serum exosomal miRNAs expression. A receiver operating characteristic (ROC) curve was constructed to determine the predictive ESCC with lymph node metastasis efficacy of serum exosomal miR-4784-3p. The Cox regression analysis was preformed to explore prognostic factors for ESCC. Transwell assay and CCK-8 assays were utilized to evaluate cell migration, invasion, and proliferation, respectively. Results: High serum exosomal miR-4787-3p expression was demonstrated in lymph node metastasis group (P =0.011). The serum exosomal miR-4787-3p expression was significantly associated with histologic grade (P = 0.010), and TNM stage (P = 0.033). However, there was no significant relationship between tissue miR-4787-3p expression and clinical characteristics (P >0.05). ROC analyses revealed that the AUCs of serum exosomal miR-4787-3p for lymph node metastasis prediction was 0.787. The Cox regression analysis found that high expression serum exosomal miR-4787-3p were correlated with poor prognoses (for OS, HR=2.68, 95% CI: 1.02~7.04; for DFS, HR = 2.65, 95% CI: 1.05~6.68). Nevertheless, no association between tissue miR-4787-3p expression and ESCC prognosis. In addition, upregulated expression of miR-4787-3p could promote migration and invasion in vitro. Conclusions: Serum exosomal miR-4787-3p can be promising biomarkers for ESCC metastasis and prognosis

scholarly journals A Novel RNA-Seq-Based Model for Preoperative Prediction of Lymph Node Metastasis in Oral Squamous Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Bo Qiao ◽  
Min Zhao ◽  
Jing Wu ◽  
Huan Wu ◽  
Yiming Zhao ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Rna Seq ◽  
Node Metastasis ◽  
Preoperative Prediction

Objective. To develop and validate a novel RNA-seq-based nomogram for preoperative prediction of lymph node metastasis (LNM) for patients with oral squamous cell carcinoma (OSCC). Methods. RNA-seq data for 276 OSCC patients (including 157 samples with LNM and 119 without LNM) were downloaded from TCGA database. Differential expression analysis was performed between LNM and non-LNM of OSCC. These samples were divided into a training set and a test set by a ratio of 9 : 1 while the relative proportion of the non-LNM and LNM groups was kept balanced within each dataset. Based on clinical features and seven candidate RNAs, we established a prediction model of LNM for OSCC using logistic regression analysis. Tenfold crossvalidation was utilized to examine the accuracy of the nomogram. Decision curve analysis was performed to evaluate the clinical utility of the nomogram. Results. A total of 139 differentially expressed RNAs were identified between LNM and non-LNM of OSCC. Seven candidate RNAs were screened based on FPKM values, including NEURL1, AL162581.1 (miscRNA), AP002336.2 (lncRNA), CCBE1, CORO6, RDH12, and AC129492.6 (pseudogene). Logistic regression analysis revealed that the clinical N stage (p<0.001) was an important factor to predict LNM. Moreover, three RNAs including RDH12 (p value < 0.05), CCBE1 (p value < 0.01), and AL162581.1 (p value < 0.05) could be predictive biomarkers for LNM in OSCC patients. The average accuracy rate of the model was 0.7661, indicating a good performance of the model. Conclusion. Our findings constructed an RNA-seq-based nomogram combined with clinicopathology, which could potentially provide clinicians with a useful tool for preoperative prediction of LNM and be tailored for individualized therapy in patients with OSCC.

scholarly journals DNA ploidy in curettage specimens identifies high-risk patients and lymph node metastasis in endometrial cancer

2015 ◽  
Vol 112 (10) ◽  
pp. 1656-1664 ◽  
Author(s):  
T S Njølstad ◽  
◽  
J Trovik ◽  
T S Hveem ◽  
M L Kjæreng ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Lymph Node ◽  
High Risk ◽  
Lymph Node Metastasis ◽  
Dna Ploidy ◽  
High Risk Patients ◽  
Node Metastasis ◽  
Risk Patients

scholarly journals Long-Term Efficacy of Ultrasound-Guided Percutaneous Laser Ablation for Low-Risk Papillary Thyroid Microcarcinoma: A 5-Year Follow-Up Study

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Kai Peng ◽  
Ping Zhou ◽  
Wengang Liu
Keyword(s):  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Low Risk ◽  
Papillary Thyroid ◽  
Ultrasound Guided ◽  
Node Metastasis ◽  
Thyroid Microcarcinoma ◽  
Percutaneous Laser Ablation

Objective. To evaluate the long-term efficacy and safety of ultrasound-guided percutaneous laser ablation (PLA) for the treatment of low-risk papillary thyroid microcarcinoma (PTMC). Methods. From June 2012 to May 2015, 105 patients with solitary, pathologically confirmed PTMC lesions were treated with ultrasound-guided PLA. Nodule location, nodule volume, thyroid function, and clinical symptoms were evaluated before ablation. Contrast-enhanced ultrasound (CEUS) was performed 1 h after treatment to evaluate whether the ablation was complete. Ultrasound examination was performed at 1, 3, 6, and 12 months after ablation and every 6 months thereafter to determine the size of the ablation area and search for recurrence in the thyroid parenchyma and lymph node metastasis. Thyroid function was examined before and 1 month after ablation. Fine needle aspiration biopsy was performed for any suspicious metastatic lymph nodes and recurrent lesions in the thyroid. Results. All 105 lesions were completely inactivated after one ablation, making the success rate for single ablation 100%. The average ablation time was 2.78 ± 1.05  min, and the average ablation energy was 505 ± 185  J. All patients could tolerate and complete the ablation. No serious complications occurred during the treatment; only minor side effects such as pain and local discomfort were reported. The volume reduction rates were − 781.14 ± 653.29 % at 1 h posttreatment and − 268.65 ± 179.57 % , − 98.39 ± 76.58 % , 36.78 ± 30.32 % , 75.55 ± 21.81 % , 96.79 ± 10.57 % , and 100% at 1, 3, 6, 12, 18, and 24 months after ablation, respectively. This rate remained 100% at the later follow-up times. Overall, 28 (26.67%), 74 (70.48%), 96 (91.43%), and 103 (100%) were completely absorbed by 6, 12, 18, and 24 months after PLA. One patient developed another lesion 12 months after ablation, and two patients had central cervical lymph node metastasis 24 months after ablation. Conclusion. PLA is a safe and effective alternative clinical treatment for low-risk PTMC.

scholarly journals A Clinical-Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Gallbladder Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Xingyu Liu ◽  
Xiaoyuan Liang ◽  
Lingxiang Ruan ◽  
Sheng Yan
Keyword(s):  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Gallbladder Cancer ◽  
Prediction Models ◽  
Validation Cohort ◽  
External Validation ◽  
Training Cohort ◽  
Clinical Variables ◽  
Node Metastasis ◽  
Preoperative Prediction

ObjectivesThe aim of the current study was to develop and validate a nomogram based on CT radiomics features and clinical variables for predicting lymph node metastasis (LNM) in gallbladder cancer (GBC).MethodsA total of 353 GBC patients from two hospitals were enrolled in this study. A Radscore was developed using least absolute shrinkage and selection operator (LASSO) logistic model based on the radiomics features extracted from the portal venous-phase computed tomography (CT). Four prediction models were constructed based on the training cohort and were validated using internal and external validation cohorts. The most effective model was then selected to build a nomogram.ResultsThe clinical-radiomics nomogram, which comprised Radscore and three clinical variables, showed the best diagnostic efficiency in the training cohort (AUC = 0.851), internal validation cohort (AUC = 0.819), and external validation cohort (AUC = 0.824). Calibration curves showed good discrimination ability of the nomogram using the validation cohorts. Decision curve analysis (DCA) showed that the nomogram had a high clinical utility.ConclusionThe findings showed that the clinical-radiomics nomogram based on radiomics features and clinical parameters is a promising tool for preoperative prediction of LN status in patients with GBC.

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