scholarly journals Deep Inguinal Lymph Node Metastases Can Predict Pelvic Lymph Node Metastases and Prognosis in Penile Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhenyu Yang ◽  
Xingliang Tan ◽  
Yanjun Wang ◽  
Yuantao Zou ◽  
Dong Chen ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Logistic Regression ◽  
Lymph Node ◽  
Regression Models ◽  
Inguinal Lymph Node ◽  
Pelvic Lymph Node ◽  
Logistic Regression Models ◽  
Node Metastasis ◽  
Node Metastases ◽  
Penile Squamous Cell Carcinoma

ObjectivesTo evaluate the relationship between deep inguinal lymph node metastasis (ILNM) and pelvic lymph node metastasis (PLNM) and explore the prognostic value of deep ILNM in penile squamous cell carcinoma (PSCC).Materials and MethodsThe records of 189 patients with ILNM treated for PSCC were analysed retrospectively. Logistic regression models were used to test for predictors of PLNM. Cox regression was performed in univariable and multivariable analyses of cancer-specific survival (CSS). CSS was compared using Kaplan-Meier analyses and log rank tests.ResultsPLNM were observed in 53 cases (28.0%). According to logistic regression models, only deep ILNM (OR 9.72, p<0.001) and number (≥3) of metastatic inguinal lymph nodes (ILNs) (OR 2.36, p=0.03) were independent predictors of PLNM. The incidences of PLNM were 18% and 19% with negative deep ILNM and extranodal extension (ENE); and 76% and 42% with positive deep ILNM and ENE, respectively. The accuracy of deep ILNM, ENE, bilateral involvement and number (≥3) of ILNMs for predicting PLNM were 81.0%, 65.6%, 63.5% and 67.2%, respectively. The CSS was significantly different in patients with positive and negative deep ILNM (median 1.7 years vs not reached, p<0.01). Patients who presented with deep ILNM had worse CSS (median 3.8 years vs not reached, p<0.01) in those with negative PLNs.ConclusionsDeep ILNM is the most accurate factor for predicting PLNM in PSCC according to our data. We recommend that patients with deep ILNM should be referred for pelvic lymph node dissection. Involvement of deep ILNs indicates poor prognosis. We propose that patients with metastases of deep ILNs may be staged as pN3.

Pelvic lymph node status prediction in melanoma patients with inguinal lymph node metastasis

2014 ◽  
Vol 24 (5) ◽  
pp. 462-467 ◽  
Author(s):  
Sandro Pasquali ◽  
Simone Mocellin ◽  
Francesco Bigolin ◽  
Antonella Vecchiato ◽  
Maria C. Montesco ◽  
...  
Keyword(s):  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Inguinal Lymph Node ◽  
Pelvic Lymph Node ◽  
Lymph Node Status ◽  
Inguinal Lymph Node Metastasis ◽  
Node Metastasis ◽  
Node Status ◽  
Melanoma Patients

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 Association of Programmed Death Ligand 1 and C-X-C Chemokine Receptor Type 4 Immunoexpression with Pelvic Lymph Node Metastasis in Cervical Squamous Cell Carcinoma

2020 ◽  
Vol 8 (A) ◽  
pp. 818-823
Author(s):  
Bhayu Chandra Purnomo ◽  
Birgitta M. Dewayani ◽  
Sri Suryanti ◽  
Bethy S. Hernowo
Keyword(s):  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Tumor Cells ◽  
Chemokine Receptor ◽  
Pelvic Lymph Node ◽  
Programmed Death Ligand 1 ◽  
Node Metastasis ◽  
Pelvic Lymph Node Metastasis ◽  
Programmed Death

BACKGROUND: Squamous cell carcinoma (SCC) is the most common type of cervical cancer. Pelvic lymph node metastasis in cervical SCC is common. Programmed death ligand 1 (PD-L1) on tumor cells has been reported to impede anti-tumor immunity, resulting in immune evasion. C-X-C chemokine receptor type 4 (CXCR4) plays an important role in proliferation, survival, and migration (chemotaxis) of tumor cells. AIM: This study aimed to analyze the association of PD-L1 and CXCR4 immunoexpression with pelvic lymph node metastasis in cervical SCC. MATERIALS AND METHODS: Forty cases of cervical SCC in the Department of Anatomical Pathology, Faculty of Medicine, Padjadjaran University, Dr. Hasan Sadikin Hospital, Bandung, during 2013–2018 were collected and divided into two groups; (1) cervical SCC metastasize to pelvic lymph node and (2) cervical SCC non-metastasize to pelvic lymph node, of 20 cases, respectively. The expression of PD-L1 and CXCR4 was detected using immunohistochemistry. RESULTS: High immunoexpression of PD-L1 and CXCR4 in cervical SCC showed significant association with pelvic lymph node metastasis (p < 0.05). The stepwise logistic regression analysis revealed that both PD-L1 and CXCR4 immunoexpression influenced pelvic lymph node metastasis simultaneously. CONCLUSION: It could be concluded that the higher PD-L1 and CXCR4 immunoexpression showed the higher ability of tumor cells to metastasize to the pelvic lymph node.

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