A nomogram for predicting occult lymph node metastasis in early hypopharyngeal cancer with cN0

Single-Cell and Bulk RNA Sequencing Reveal Tumor Cell Characteristics and Communication Features of Primary and Lymphatic Metastatic Hypopharyngeal Squamous Cell Carcinoma

BACKGROUND

Lymph node metastasis (LNM) is strongly associated with poor prognosis in hypopharyngeal squamous carcinoma (HPSCC). Identifying key drivers of LNM and potential therapeutic targets in HPSCC is therefore essential for the early detection of high-risk patients and for informing personalized treatment strategies.

METHODS

Single-cell RNA sequencing data were used to characterize malignant epithelial cells (maECs) in HPSCC primary tumors (PT) and LNM, as well as differences in cell-to-cell communication. Concurrently, combined with bulk RNA sequencing data, a ligand receptor pairs (LRs) model was developed to predict the prognosis of HPSCC patients.

RESULTS

PT and LNM maECs have different gene expression characteristics, with genes involved in interferon signaling and TGF-β response pathways enriched in LNM maECs, suggesting potential immunosuppressive reprogramming. Cell communication analysis revealed distinct interactions and signaling features in PT and LNM microenvironments. Subsequently, a 4-LRs model was constructed to stratify HPSCC patients into low-or high-risk groups, with the high-risk group demonstrating significantly worse overall survival (OS) outcomes compared with the low-risk group in the training (p < 0.0001), testing (p = 0.0021), and entire (p < 0.0001) cohorts. Receiver operating characteristic curves showed that this risk model can effectively predict the 1-, 3-, and 5-year OS of HPSCC patients. Notably, the risk score effectively discriminated LNM status (area under the curve [AUC] = 0.927) among HPSCC patients, highlighting its potential as a HPSCC metastasis prediction tool.

CONCLUSIONS

These results provide biomarkers of LNM maECs as well as potential mechanisms of HPSCC metastasis, which may help with the precision treatment, diagnosis, and prognosis of HPSCC.

Old age decreases the risk of lymph node metastasis in T1-2 hypopharynx squamous cell carcinoma patients

Cervical lymph node metastasis (LNM) is an important prognostic factor for hypopharynx squamous cell carcinoma (SCC) patients, which can be detected in a large fraction of clinically diagnosed early hypopharynx SCC patients; however, the importance of knowing the risk of LNM in the younger/older patients has not been well defined. The objective of this study is to assess the effect of age and LNM in T1-2 hypopharynx SCC patients. Patients with T1-2 hypopharynx SCC were extracted from the Surveillance, Epidemiology and End Results database between 2005 and 2014. Univariate and multivariate logistic regression models were produced to recognize the association between age and risk factors of LNM. A total of 1018 patients were analyzed. Older patients have a lower risk of LNM compared with their younger peers ( P  < 0.01). In multivariate analyses, older age was associated with a significantly lower risk of LNM. Compared with patients aged 80-93 years old, the hazard ratios for patients aged 31-49, 50-59, 60-69, and 70-79 years old were 2.464 [95% confidence interval (CI): 1.338-4.537], 2.668 (95% CI: 1.638-4.346), 3.192 (95% CI: 1.957-5.205), and 1.564 (95% CI: 0.945-2.588), respectively. Subgroup analysis shows that the effect of older age was significantly associated with a higher risk of LNM in Caucasian male who harbored moderately/poorly differentiated tumors. Our study demonstrates that older patients with T1-2 hypopharynx SCC had a lower risk of LNM than their younger peers, especially males with moderately/poorly differentiated tumors. More accurate assessments of LNM and prophylactic neck dissection or prophylactic adjuvant radiation therapy to the neck will be imperative for reducing recurrence in younger T1-2 hypopharynx SCC.

Development and validation of a nomogram to predict cervical lymph node metastasis in head and neck squamous cell carcinoma

Background

Head and neck cancers are a heterogeneous, aggressive, and genetically complex collection of malignancies of the oral cavity, nasopharynx, oropharynx, hypopharynx, larynx, paranasal sinuses and salivary glands, which are difficult to treat. Regional lymph nodes metastasis is a significant poor prognosis factor for head and neck squamous cell carcinoma. Metastasis to the regional lymph nodes reduces the 5-year survival rate by 50% compared with that of patients with early-stage disease. Accurate evaluation of cervical lymph node is a vital component in the overall treatment plan for patients with squamous cell carcinoma of the head and neck. However, current models are struggle to accurately to predict cervical lymph node metastasis. Here, we analyzed the clinical, imaging, and pathological data of 272 patients with HNSCC confirmed by postoperative pathology and sought to develop and validate a nomogram for prediction of lymph node metastasis in patients with head and neck squamous cell carcinoma.

Methods

We retrospectively analyzed the clinical, imaging, and pathological data of 272 patients with head and neck squamous cell carcinoma (HNSCC) confirmed by postoperative pathology at the Affiliated Hospital of Qingdao University from June 2017 to June 2021. Patients were randomly divided into the training and validation cohorts in a 3:1 ratio, and after screening risk factors by logistic regression, nomogram was developed for predicting lymph nodes metastasis, then the prediction model was verified by C-index, area under curve (AUC), and calibration curve.

Results

Of the 272 patients, seven variables were screened to establish the predictive model, including the differentiation degree of the tumor [95% confidence interval(CI):1.224~6.735, P=0.015], long-to-short axis ratio of the lymph nodes (95%CI: 0.019~0.217, P<0.001), uneven/circular enhancement (95%CI: 1.476~16.715, P=0.010), aggregation of lymph nodes (95%CI:1.373~10.849, P=0.010), inhomogeneous echo (95%CI: 1.337~23.389, P=0.018), unclear/absent medulla of lymph nodes (95%CI: 2.514~43.989, P=0.001), and rich blood flow (95%CI: 1.952~85.632, P=0.008). The C-index was 0.910, areas under the curve of training cohort and verification cohort were 0.953 and 0.938 respectively, indicating the discriminative ability of this nomogram. The calibration curve showed a favorable compliance between the prediction of the model and actual observations. The clinical decision curve showed this model is clinically useful and had better discriminative ability between 0.25 and 0.9 for the probability of cervical LNs metastasis.

Conclusions

We established a good prediction model for cervical lymph node metastasis in head and neck squamous cell carcinoma patients which can provide reference value and auxiliary diagnosis for clinicians in making neck management decisions of HNSCC patients.

Risk factors and prognostic models of lymph node metastatic hypopharyngeal squamous cell carcinoma

PURPOSE

To explore the risk factors for lymph node metastasis (LNM) and establish nomograms for predicting survival outcomes and assessing individual risk in patients with LNM and hypopharyngeal squamous carcinoma (HSCC).

METHODS

Clinical data of patients with HSCC were retrospectively reviewed. The study's primary endpoints were overall survival (OS) and disease-specific survival (DSS). Nomograms were established based on Cox regression analyses. The accuracy and calibration ability of the nomograms were evaluated using the C-index, area under the curve, calibration curves, and decision curve analysis.

RESULTS

Overall, 2888 patients were enrolled, and the LNM rate was 74.2%. Age ≤ 60 years, male sex, unmarried status, pyriform sinus location, grade III-IV, tumor larger than 4 cm, and advanced T stage increased the risk of LNM. In addition, LNM was a negative prognostic factor for OS and DSS. Ten variables were identified and incorporated into nomograms to estimate OS and DSS. Our nomograms outperformed the traditional staging system in training and validation cohorts. Patients were stratified into risk subgroups based on the OS- and DSS-nomogram scores. Patients in the high-risk subgroup had a higher risk of death and disease-specific mortality than those in the low- and intermediate-risk subgroups.

CONCLUSIONS

LNM worsens the prognosis of HSCC. This study identified the independent prognostic factors for HSCC with LNM and developed satisfactory OS- and DSS-monogram to provide individual prediction and risk classification for patients with this diagnosis.

Optimal treatment strategy and prognostic analysis for hypopharyngeal squamous-cell carcinoma patients with T3-T4 or node-positive: A population-based study

PURPOSE

To explore the optimal treatment strategy and relevant prognostic analysis for hypopharyngeal squamous-cell carcinoma patients (HSCC) with T3-T4 or node-positive.

METHODS AND MATERIALS

From 2004 to 2018, data for 2574 patients from the Surveillance, Epidemiology, and End Results database (SEER) and 66 patients treated at our center from 2013 to 2022 with T3-T4 or N + HSCC were collected. Patients in the SEER cohort were randomly assigned to the training set or validation set at a 7:3 ratio. Variables with statistically significant (P < 0.05) in univariate COX regression analysis or clinical significance were included in the multivariate COX regression model and subsequently used to construct the nomogram.

RESULTS

The 3-year OS (52.9%vs44.4%, P < 0.01) and 3-year CSS rate (58.7%vs51.5%, P < 0.01) rates in the surgery combined with postoperative adjuvant therapy (S + ADT) group were superior to the radiotherapy combined with chemotherapy (CRT) group. The multivariate Cox regression analysis of the training group showed that age, race, marital status, primary site, T stage, N stage, and treatment modalities were correlated with OS and CSS. Based on those variables, we constructed nomograms for OS and CSS. Both the internal and external validation showed high prediction accuracy of the nomogram.

CONCLUSION

Among patients with T3-T4 or node-positive, S + ADT was associated with superior OS and CSS compared to those treated with primary CRT, while the survival rate in the CRT group was comparable to S + ADT group in T2-T3 disease. The internal and external verification shows that the prognostic model has good discrimination ability and accuracy.

A preoperative nomogram model for the prediction of lymph node metastasis in buccal mucosa cancer

OBJECTIVES

We sought to construct a nomogram model predicting lymph node metastasis (LNM) in patients with squamous cell carcinoma of the buccal mucosa based on preoperative clinical characteristics.

METHODS

Patients who underwent radical resection of a primary tumor in the buccal mucosa with neck dissection were enrolled. Clinical characteristics independently associated with LNM in multivariate analyses were adopted to build the model. Patients at low risk of LNM were defined by a predicted probability of LNM of less than 5%.

RESULTS

Patients who underwent surgery in an earlier period (January 2015-November 2019) were defined as the model development cohort (n = 325), and those who underwent surgery later (November 2019-March 2021) were defined as the validation cohort (n = 140). Age, tumor differentiation, tumor thickness, and clinical N stage assessed by computed tomography/magnetic resonance imaging (cN) were independent predictors of LNM. The nomogram model based on these four predictors showed good discrimination accuracy in both the model development and validation cohorts, with areas under the receiver-operating characteristic curve (AUC) of 0.814 and 0.828, respectively. LNM prediction by the nomogram model was superior to cN in AUC comparisons (0.815 vs. 0.753) and decision curve analysis of the whole cohort. Seventy-one patients were defined as having a low risk of LNM, among whom the actual metastasis rate was only 1.4%.

CONCLUSIONS

A robust nomogram model for preoperative LNM prediction is built.

Development and validation of a nomogram for the prediction of lymph node metastasis within 2-year postoperatively in cT1-T2N0 oral squamous cell carcinoma

BACKGROUND

The current neck management for early oral squamous cell carcinoma (OSCC) has always been a controversial issue. A comprehensive model is necessary for predicting an individual's metastasis risk and appropriate patient counseling.

METHODS

A nomogram for predicting 2-year LNM in patients with cT1-2N0 OSCC was developed and validated using clinicopathological data from 642 patients from 2000 to 2018 in four hospitals, China.

RESULTS

Three variables (pathology grade, depth of invasion, tumor-infiltrating lymphocytes) were included in nomogram. C-indices were 0.826 (95% CI: 0.786-0.866) and 0.726 (95% CI: 0.653-0.780) in the internal and external validation. Kaplan-Meier method found the 2-year LNM rate of high-risk group (35.8%) was much higher than that of the low-risk group (14.5%). The nomogram model has an advantage over the 8th AJCC TNM stage in predicting the individual 2-year LNM probability for early OSCC.

CONCLUSION

Patients with low-risk nomogram score may receive neck observation; those with high-risk score should receive END.

Validation of the risk factors for primary control of early T-stage laryngeal, oropharyngeal, and hypopharyngeal squamous cell carcinoma by transoral surgery: a prospective observational study

BACKGROUND

We had previously identified the following risk factors for insufficient control of early T-stage head and neck cancer by transoral surgery (TOS): (1) tumor thickness > 7 mm on enhanced computed tomography (CT), and (2) poor differentiation in pathological examination. We subsequently used a different patient cohort to validate the usefulness of these factors in determining the need for adaptation of TOS.

STUDY SETTING

A prospective observational study METHODS: Patients who received TOS as a definitive treatment between April 1, 2016 and September 30, 2020 were included. Primary control rates (by single TOS and TOS alone) in relation to the above-mentioned risk factors were calculated. Overall (O), recurrence-free (RF), and disease-free (DF) survival (S) outcomes were evaluated. A combination analysis based on the number of risk factors was also performed.

RESULTS

Patients with tumor thickness > 7 mm had a 2.88-fold [95% confidence interval (CI) 1.01-8.51] higher risk of incomplete primary resection by single TOS, while patients who showed poor differentiation on pathological assessments had a 13.14-fold (95% CI 3.66-47.14) higher risk of insufficient primary control by TOS alone. The 3 year OS, RFS, and DFS rates were 99%, 83%, and 63%, respectively. Patients with both risk factors had a 93.00-fold (95% CI 4.99-1732.00) higher risk of incomplete primary control by TOS alone.

CONCLUSIONS

Among patients with early-stage laryngeal, oropharyngeal, and hypopharyngeal squamous cell carcinoma, primary control by TOS alone may not be achieved in patients with both risk factors, that is, tumor thickness > 7 mm as measured by enhanced CT and poor differentiation on pathological examination.

A Combined Prediction Model for Lymph Node Metastasis Based on a Molecular Panel and Clinicopathological Factors in Oral Squamous Cell Carcinoma

OBJECTIVE

Lymph node metastasis is the most important factor influencing the prognosis of oral squamous cell carcinoma (OSCC) patients. However, there is no proper method for predicting lymph node metastasis. This study aimed to construct and validate a preoperative prediction model for lymph node metastasis and guide personalized neck management based on the gene expression profile and clinicopathological parameters of OSCC.

METHODS

Based on a previous study of related genes in OSCC, the mRNA expression of candidate genes was evaluated by real-time PCR in OSCC specimens. In this retrospective study, the gene expression profile and clinicopathological parameters of 112 OSCC patients were combined to construct the best prediction model for lymph node metastasis of OSCC. The model was validated with 95 OSCC samples in this study. Logistic regression analysis was used. The area under the curve (AUC) ultimately determined the diagnostic value of the prediction model.

RESULTS

The two genes CDKN2A + PLAU were closely related to lymph node metastasis of oral squamous cell carcinoma. The model with the combination of CDKN2A, PLAU, T stage and pathological grade was the best in predicting lymph node metastasis (AUC = 0.807, 95% CI: 0.713-0.881, P=0.0001). The prediction model had a specificity of 96% and sensitivity of 72.73% for stage T1 and T2 OSCC (AUC = 0.855, 95% CI: 0.697-0.949, P=0.0001).

CONCLUSIONS

High expression of CDKN2A and PLAU was associated with lymph node metastasis in OSCC. The prediction model including CDKN2A, PLAU, T stage and pathological grade can be used as the best diagnostic model for lymph node metastasis in OSCC.