Predictors for distant metastasis in head and neck cancer, with emphasis on age

Considerable interlaboratory variation in PD-L1 positivity for head and neck squamous cell carcinoma in the Netherlands- A nationwide evaluation study

AIMS

Patients with recurrent or metastatic head and neck squamous cell carcinoma (HNSCC) are eligible for first-line immune checkpoint inhibition if their tumour is positive for programmed death ligand 1 (PD-L1) determined by the combined positive score (CPS). This nationwide study, using real-world data, investigated the developing PD-L1 testing landscape in the first 3 years after introduction of the test in HNSCC and examined interlaboratory variation in PD-L1 positivity rates.

METHODS

Pathology reports of HNSCC patients mentioning PD-L1 were extracted from the Dutch Pathology Registry (Palga). Tumour and PD-L1 testing characteristics were analysed per year and interlaboratory variation in PD-L1 positivity rates was assessed using funnel plots with 95% confidence limits around the overall mean.

RESULTS

A total of 817 PD-L1 tests were reported in 702 patients among 19 laboratories; 85.2% of the tests on histological material were stated to be positive. The national PD-L1 positivity rate differed significantly per year during the study period (79.7-89.9%). The use of the recommended 22C3 antibody increased from 59.9 to 74.3%. A total of 673 PD-L1 tests on histological material from 12 laboratories were analysed to investigate interlaboratory variation. Four (33%) deviated significantly from the national mean of PD-L1-positive cases using CPS ≥ 1 cut-off, while two (17%) deviated significantly for CPS ≥ 20 cut-off.

CONCLUSION

In the first 3 years of PD-L1 assessment in HNSCC, the testing landscape became more uniform. However, interlaboratory variation in PD-L1 positivity rates between Dutch laboratories was substantial. This implies that there is a need for further test standardisation to reduce this variation.

Advancing Head and Neck Cancer Survival Prediction via Multi-Label Learning and Deep Model Interpretation

A comprehensive and reliable survival prediction model is of great importance to assist in the personalized management of Head and Neck Cancer (HNC) patient treated with curative Radiation Therapy (RT). In this work, we propose IMLSP, an Interpretable Multi-Label multi-modal deep Survival Prediction framework for predicting multiple HNC survival outcomes simultaneously and provide time-event specific visual explanation of the deep prediction process. We adopt Multi-Task Logistic Regression (MTLR) layers to convert survival prediction from a regression problem to a multi-time point classification task, and to enable predicting of multiple relevant survival outcomes at the same time. We also present Grad-Team, a Gradient-weighted Time-event activation mapping approach specifically developed for deep survival model visual explanation, to generate patient-specific time-to-event activation maps. We evaluate our method with the publicly available RADCURE HNC dataset, where it outperforms the corresponding single-modal models and single-label models on all survival outcomes. The generated activation maps show that the model focuses primarily on the tumor and nodal volumes when making the decision and the volume of interest varies for high- and low-risk patients. We demonstrate that the multi-label learning strategy can improve the learning efficiency and prognostic performance, while the interpretable survival prediction model is promising to help understand the decision-making process of AI and facilitate personalized treatment. The project website can be found at https://github.com/***.

A Matter of Margins in Oral Cancer-How Close Is Enough?

In patients with oral cancer, the risk factors for local, regional, and distant recurrence according to margin status have not been well established. We aimed to determine the risk factors for recurrence by margin status and to identify a margin cut-off point for improved survival in patients with close margins. We retrospectively reviewed adult patients treated at our centre from 2009 to 2021 for primary oral cancer. Margins were classified as positive (<1 mm), close (1 to 4.9 mm), or clear (>5 mm). Univariate and multivariate analyses were performed. A total of 326 patients (210 men) were included. The mean age was 59.1 years. Margin status was close (n = 168, 51.5%), clear (n = 83, 25.4%), or positive (n = 75, 23.0%). In the univariate analysis, positive surgical margins (HR = 7.53) had the greatest impact on distant failure. Positive surgical margins-without nodal involvement-had the greatest impact on the risk of distant failure. In the close margin group, the optimal cut-off for disease-free survival (AUC = 0.58) and overall survival (AUC = 0.63) was a deep margin > 3 mm, with survival outcomes that were comparable to the clear margin group. These finding suggest that margins < 5 mm may be sufficient in certain well-defined cases. Prospective studies are warranted to confirm these findings.

Vision Transformer-Based Multilabel Survival Prediction for Oropharynx Cancer After Radiation Therapy

PURPOSE

A reliable and comprehensive cancer prognosis model for oropharyngeal cancer (OPC) could better assist in personalizing treatment. In this work, we developed a vision transformer-based (ViT-based) multilabel model with multimodal input to learn complementary information from available pretreatment data and predict multiple associated endpoints for radiation therapy for patients with OPC.

METHODS AND MATERIALS

A publicly available data set of 512 patients with OPC was used for both model training and evaluation. Planning computed tomography images, primary gross tumor volume masks, and 16 clinical variables representing patient demographics, diagnosis, and treatment were used as inputs. To extract deep image features with global attention, we used a ViT module. Clinical variables were concatenated with the learned image features and fed into fully connected layers to incorporate cross-modality features. To learn the mapping between the features and correlated survival outcomes, including overall survival, local failure-free survival, regional failure-free survival, and distant failure-free survival, we employed 4 multitask logistic regression layers. The proposed model was optimized by combining the multitask logistic regression negative-log likelihood losses of different prediction targets.

RESULTS

We employed the C-index and area under the curve metrics to assess the performance of our model for time-to-event prediction and time-specific binary prediction, respectively. Our proposed model outperformed corresponding single-modality and single-label models on all prediction labels, achieving C-indices of 0.773, 0.765, 0.776, and 0.773 for overall survival, local failure-free survival, regional failure-free survival, and distant failure-free survival, respectively. The area under the curve values ranged between 0.799 and 0.844 for different tasks at different time points. Using the medians of predicted risks as the thresholds to identify high-risk and low-risk patient groups, we performed the log-rank test, the results of which showed significantly larger separations in different event-free survivals.

CONCLUSION

We developed the first model capable of predicting multiple labels for OPC simultaneously. Our model demonstrated better prognostic ability for all the prediction targets compared with corresponding single-modality models and single-label models.

Tumor-Derived RAB21+ABHD12+ sEVs Drive the Premetastatic Microenvironment in the Lung

Tumor metastasis is a spatial and temporal process that starts with remodeling to generate a proper premetastatic niche in a distant tissue. Infiltration of immunosuppressive macrophages is one of the notable characteristics in the premetastatic niche, which is a fundamental requirement for primary tumor metastasis. Here, we demonstrated that small extracellular vesicles (sEV) carrying RAB21 homed to lung macrophages and interacted with integrin-β1 on macrophages. ABHD12 expression was high in lung metastatic tumors and was mostly expressed by macrophages. Head and neck squamous cell carcinoma (HNSCC)-derived sEVs carrying ABHD12-polarized macrophages toward an immunosuppressive phenotype, driving premetastatic niche formation, which facilitated lung metastasis. ABHD12 additionally upregulated S1PR1 by activating the AKT-FoxO1 pathway in macrophages, and significantly enhanced antitumor responses were observed in tumor models treated with agents targeting both S1PR1 and PD-1. Collectively, our study suggests that RAB21+ABHD12+ sEVs derived from HNSCC cells contribute to the formation of the immunosuppressive microenvironment in the premetastatic niche and are a potential therapeutic target for enhancing the antitumor efficacy of anti-PD-1 therapy.

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.

CT-Based Screening for Pulmonary Metastases in Head and Neck Squamous Cell Cancers: Diagnostic Accuracy and Cost Comparison with PET-CECT

This study's objective was to compare detection rates of radiograph, computed tomography (CT), and positron emission tomography-contrast-enhanced computed tomography (PET-CECT) for pulmonary metastasis/synchronous primary lung tumors in head and neck squamous cell cancer (HNSCC) and its association with clinico-radio-pathological factors. Our retrospective study included 837 HNSCC patients from January 2012 to December 2017. Lung nodules were characterized on CT as benign, indeterminate, and metastatic. The true detection rate and statistical significance of associated risk factors were calculated. Risk factors for metastasis were determined using univariate and multivariate logistic regression models. Seventy-five (8.9%) patients had pulmonary metastasis and 3 (0.3%) had second lung primary. Detection rate of pulmonary metastasis by CT was higher (sensitivity-97.3%, specificity-97.2%) as compared to radiograph (sensitivity 49% and specificity 89%). Correlation was found between pulmonary and extra-pulmonary metastasis and N classification (P = 0.01, P = 0.02) and positive low jugular node (P = 0.001, P = 0.001). Using PET-CECT in place of CT costed an extra outlay of 7,033,805 INR (95,551.85 USD) while detecting distant metastasis in only 4 (0.47%) extra cases. Chest CT is a useful pulmonary metastases screening tool in advanced HNSCC patients with reasonable imaging cost as compared to PET-CT.

Lymph nodes: at the intersection of cancer treatment and progression

Metastasis to lymph nodes (LNs) is a common feature of disease progression in most solid organ malignancies. Consequently, LN biopsy and lymphadenectomy are common clinical practices, not only because of their diagnostic utility but also as a means of deterring further metastatic spread. LN metastases have the potential to seed additional tissues and can induce metastatic tolerance, a process by which tumor-specific immune tolerance in LNs promotes further disease progression. Nonetheless, phylogenetic studies have revealed that distant metastases are not necessarily derived from nodal metastases. Furthermore, immunotherapy efficacy is increasingly being attributed to initiation of systemic immune responses within LNs. We argue that lymphadenectomy and nodal irradiation should be approached with caution, particularly in patients receiving immunotherapy.

Risk Factors for Synchronous Lung Metastasis in Squamous Cell Carcinoma of Hypopharynx

Background: The objective of this study is to assess the risk factors for synchronous lung metastases (LM) in patients with hypopharynx squamous cell carcinomas (HPSCC). Methods: HPSCC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2013. We examined the association between risk factors and synchronous LM using chi-squared tests. Predictors of survival rates were assessed using univariate and multivariate analyses. Results: A total of 1683 patients were analyzed, including 70 patients (4.2%) with synchronous LM, and 1613 patients without synchronous LM (95.8%). Multivariate logistic regression analysis showed that Caucasian (P = .038), lower T (P = .026) or N classification (P = .000), and highly differentiated disease (P = .002) were associated with a significantly lower risk of LM. Elderly not married patients with higher T or N classification, multiple sites of metastases, and no surgical therapy to the primary tumors were more likely to reduce life expectancy. Conclusion: By analyzing data from a large cohort, Caucasian, lower T or N classification, and highly differentiated disease were associated with a significantly lower risk of LM. Elderly not married patients with advanced T or N classification, no surgical therapy to the primary tumors, and multiple sites of metastases were more likely to reduce life expectancy. More accurate assessments of LM will be imperative for early diagnosis and treatment in non-Caucasian patients who harbored higher T or N classification and poorly differentiated disease.

The influence of tumor volume on the risk of distant metastases in head and neck squamous cell carcinomas

BACKGROUND AND PURPOSE

Distant metastases (DM) in head and neck squamous cell carcinomas (HNSCC) are in most circumstances non-curable. The TNM staging system is insufficient to predict the risk of DM. This study investigates if the DM risk can be predicted using a multivariate model including pre-treatment total tumor volume for both p16-positive oropharyngeal squamous cell carcinoma (OPSCC) and all other sites (other HNSCC).

MATERIALS AND METHODS

The study includes patients with localized pharyngeal and laryngeal squamous cell carcinomas treated with primary radiotherapy from 2008-2017 from three head and neck cancer centers. Patients were identified in the Danish Head and Neck Cancer (DAHANCA) database. Total (nodal and primary) tumor volume (Gross Tumor Volume, GTV) was extracted from local treatment planning systems. The GTV was grouped by volume (cm3) in four intervals and included in a multivariate Cox proportional hazard regression controlled for pre-selected clinical values incl. stage.

RESULTS

The study includes 2,865 patients, of which 321 (11 %) had DM post-treatment. The risk of DM was assessed in a multivariate model based on 2,751 patients (p16-positive OPSCC: 1,032; and other HNSCC: 1,719). There was a significant association between GTV and the risk of DM, and in tumor volumes ≥ 50 cm3 hazard ratios of 7.6 (2.5-23.4) for p16-positive OPSCC and 4.1 (2.3-7.2) in other HNSCC were observed.

CONCLUSION

Tumor volume is an independent risk factor for DM. The addition of total tumor volume to a predictive model is important to identify subgroups of HNSCC patients at high risk of DM.

IMP3 Expression as a Potential Tumour Marker in High-Risk Localisations of Cutaneous Squamous Cell Carcinoma: IMP3 in Metastatic cSCC

BACKGROUND

High IMP3 expression is correlated with a worse outcome. Until now, there have been no data about IMP3 expression and clinical outcome for high-risk localisation of squamous cell carcinoma of the skin (cSCC).

METHODS

One-hundred twenty-two patients with cSCC of the lip and ear were included, and IMP3 expression in the tumours was immunohistochemically assessed in different evaluation approaches. Subsequently, subgroups were analysed in a matched pair approach and correlated with clinical pathologic parameters. In the following, different IMP3 analysis methods were tested for clinical suitability.

RESULTS

We found a significant correlation between IMP3 expression and risk for lymph node metastasis, local relapse, and progression-free survival.

CONCLUSIONS

On basis of our data, we suggest a prognostic benefit cutoff value for high (>50%) and low (<50%) IMP3 expression. Thus, IMP3 expression has a high scientific potential for further studies and could potentially be used as a prognostic marker in diagnostic and therapeutic decision-making.

A Random Forest Model for Post-Treatment Survival Prediction in Patients with Non-Squamous Cell Carcinoma of the Head and Neck

BACKGROUND

Compared to squamous cell carcinoma, head and neck non-squamous cell carcinoma (HNnSCC) is rarer. Integrated survival prediction tools are lacking.

METHODS

4458 patients of HNnSCC were collected from the SEER database. The endpoints were overall survivals (OSs) and disease-specific survivals (DSSs) of 3 and 5 years. Cases were stratified-randomly divided into the train & validation (70%) and test cohorts (30%). Tenfold cross validation was used in establishment of the model. The performance was evaluated with the test cohort by the receiver operating characteristic, calibration, and decision curves.

RESULTS

The prognostic factors found with multivariate analyses were used to establish the prediction model. The area under the curve (AUC) is 0.866 (95%CI: 0.844-0.888) for 3-year OS, 0.862 (95%CI: 0.842-0.882) for 5-year OS, 0.902 (95%CI: 0.888-0.916) for 3-year DSS, and 0.903 (95%CI: 0.881-0.925) for 5-year DSS. The net benefit of this model is greater than that of the traditional prediction methods. Among predictors, pathology, involved cervical nodes level, and tumor size are found contributing the most variance to the prediction. The model was then deployed online for easy use.

CONCLUSIONS

The present study incorporated the clinical, pathological, and therapeutic features comprehensively and established a clinically effective survival prediction model for post-treatment HNnSCC patients.

A novel nomogram and risk classification system for predicting overall survival in head and neck squamous cell cancer with distant metastasis at initial diagnosis

INTRODUCTION

Head and neck squamous cell carcinoma (HNSCC) is one of the most invasive cancer types globally, and distant metastasis (DM) is associated with a poor prognosis. The objective of this study was designed to construct a novel nomogram and risk classification system to predict overall survival (OS) in HNSCC patients presenting with DM at initial diagnosis.

METHODS

HNSCC patients with initially diagnosed DM between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Firstly, all patients were randomly assigned to a training cohort and validation cohort (8:2), respectively. The Cox proportional hazards regression model was used to analyze the prognostic factors associated with OS. Then, the nomogram based on the prognostic factors and the predictive ability of the nomogram were assessed by the calibration curves, receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Finally, a risk classification system was established according to the nomogram scores.

RESULTS

A total of 1240 patients initially diagnosed with HNSCC with DM were included, and the 6-, 12- and 18-month OS of HNSCC with DM were 62.7%, 40.8% and 30%, respectively. The independent prognostic factors for HNSCC patients with DM included age, marital status, primary site, T stage, N stage, bone metastasis, brain metastasis, liver metastasis, lung metastasis, surgery, radiotherapy and chemotherapy. Based on the independent prognostic factors, a nomogram was constructed to predict OS in HNSCC patients with DM. The C-index values of the nomogram were 0.713 in the training cohort and 0.674 in the validation cohort, respectively. The calibration curves and DCA also indicated the good predictability of the nomogram. Finally, a risk classification system was built and it revealed a statistically significant difference among the three groups of patients according to the nomogram scores.

CONCLUSIONS

Factors associated with the overall survival of HNSCC patients with DM were found. According to the identified factors, we generated a nomogram and risk classification system to predict the OS of patients with initially diagnosed HNSCC with DM. The prognostic nomogram and risk classification system can help to assess survival time and provide guidance when making treatment decisions for HNSCC patients with DM.

Quantitative parameters derived from 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging can accurately estimate the histologic grade of hypopharyngeal squamous cell carcinoma preoperatively

PURPOSE

Among head and neck cancers, hypopharyngeal squamous cell carcinoma (HSCC) shows the highest malignancy, which is associated with histologic grading. This study was designed to investigate whether quantitative parameters derived from ¹⁸F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (¹⁸F-FDG PET/MRI) can preoperatively estimate the histologic grade of HSCC.

METHODS

¹⁸F-FDG PET/MRI of neck was successfully performed in 21 patients with histologically proven HSCC including poorly differentiated group (ten patients) and well-moderately differentiated group (eleven patients). Quantitative parameters derived from FDG-PET, diffusion-weighted imaging (DWI), and dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) were calculated based on volume of interest drawn on the tumor and compared between two groups. The efficacy of quantitative parameters for the estimation of histologic grades of HSCC was evaluated.

RESULTS

There were statistically significant differences in mean value of standard uptake value (SUV), apparent diffusion coefficient (ADC), and K^trans derived from ¹⁸F-FDG PET/MRI of HSCC between two groups (p < 0.05). There was no statistically significant difference in other quantitative parameters derived from ¹⁸F-FDG PET/MRI of HSCC between two groups. The area under the curve (AUC) of the combination of SUV_mean, ADC_mean, and K^trans in the estimation of histologic grade of HSCC was 0.936 with sensitivity of 90.0% and specificity of 81.8%.

CONCLUSION

The combination of SUV_mean, ADC_mean, and K^trans derived from ¹⁸F-FDG PET/MRI can accurately predict the histologic grade of HSCC preoperatively.

Inter-assay reliability of programmed cell death-ligand 1 in head and neck squamous cell carcinoma

OBJECTIVES

The programmed cell death-ligand 1 (PD-L1) 22C3 pharmDx assay is used as a companion diagnostic test to select head and neck squamous cell carcinoma (HNSCC) patients that may benefit from treatment with the checkpoint inhibitor pembrolizumab. Because the Dako platform is not universally available, we studied the performance of a 22C3 laboratory developed test (LDT) performed on a Ventana BenchMark Ultra compared to the 22C3 pharmDx assay.

MATERIALS AND METHODS

Serial sections from tissue micro arrays (TMAs) containing tumour tissue from 97 HNSCC patients were stained with the 22C3 pharmDx assay and 22C3 LDT. All TMA cores were scored by three dedicated head and neck pathologists for PD-L1 expression.

RESULTS

Substantial interobserver agreement was reported for both the standardized 22C3 pharmDx assay and the 22C3 LDT (respectively Fleiss' κ 0.62, 95% CI 0.57-0.67 and 0.63, 95% CI 0.58-0.68). Concordance between the assays was almost perfect on core and patient level (respectively Weighted κ 0.84, 95% CI 0.79-0.89 and 0.84, 95% CI 0.75-0.92). Intratumor heterogeneity between the cores per patient case was similar in both assays.

CONCLUSION

After validation a 22C3 LDT is non-inferior to the standardized 22C3 pharmDx assay and can be safely used to select HNSCC patients for pembrolizumab treatment.

Patients with Pulmonary Metastases from Head and Neck Cancer Benefit from Pulmonary Metastasectomy, A Systematic Review

Background and Objectives: The incidence of distant metastases in patients with head and neck cancer (HNC) is approximately 10%. Pulmonary metastases are the most frequent distant location, with an incidence of 70-85%. The standard treatment options are chemo-, immuno- and radiotherapy. Despite a benefit for long-term survival for patients with isolated pulmonary metastases, pulmonary metastasectomy (PM) is not the treatment of choice. Furthermore, many otorhinolaryngologists are not sufficiently familiar with the concept of PM. This work reviews the recent studies of pulmonary metastatic HNC and the results after pulmonary metastasectomy. Materials and Methods: PubMed, Medline, Embase, and the Cochrane library were checked for the case series' of patients undergoing metastasectomy with pulmonary metastases published since 1 January 2000. Results: We included the data of 15 studies of patients undergoing PM. The 5-year survival rates varied from 21% to 59%, with median survival from 10 to 77 months after PM. We could not identify one specific prognostic factor for long-term survival after surgery. However, at least most studies stated that PM should be planned if a complete (R0) resection is possible. Conclusions: PM showed reliable results and is supposedly the treatment of choice for patients with isolated pulmonary metastases. Patients not suitable for surgery may benefit from other non-surgical therapy. Every HNC patient with pulmonary metastases should be discussed in the multidisciplinary tumor board to optimize the therapy and the outcome.

Development of a Machine Learning-Based Predictive Model for Lung Metastasis in Patients With Ewing Sarcoma

Background

This study aimed to develop and validate machine learning (ML)-based prediction models for lung metastasis (LM) in patients with Ewing sarcoma (ES), and to deploy the best model as an open access web tool.

Methods

We retrospectively analyzed data from the Surveillance Epidemiology and End Results (SEER) Database from 2010 to 2016 and from four medical institutions to develop and validate predictive models for LM in patients with ES. Patient data from the SEER database was used as the training group (n = 929). Using demographic and clinicopathologic variables six ML-based models for predicting LM were developed, and internally validated using 10-fold cross validation. All ML-based models were subsequently externally validated using multiple data from four medical institutions (the validation group, n = 51). The predictive power of the models was evaluated by the area under receiver operating characteristic curve (AUC). The best-performing model was used to produce an online tool for use by clinicians to identify ES patients at risk from lung metastasis, to improve decision making and optimize individual treatment.

Results

The study cohort consisted of 929 patients from the SEER database and 51 patients from multiple medical centers, a total of 980 ES patients. Of these, 175 (18.8%) had lung metastasis. Multivariate logistic regression analysis was performed with survival time, T-stage, N-stage, surgery, and bone metastasis providing the independent predictive factors of LM. The AUC value of six predictive models ranged from 0.585 to 0.705. The Random Forest (RF) model (AUC = 0.705) using 4 variables was identified as the best predictive model of LM in ES patients and was employed to construct an online tool to assist clinicians in optimizing patient treatment. (https://share.streamlit.io/liuwencai123/es_lm/main/es_lm.py).

Conclusions

Machine learning were found to have utility for predicting LM in patients with Ewing sarcoma, and the RF model gave the best performance. The accessibility of the predictive model as a web-based tool offers clear opportunities for improving the personalized treatment of patients with ES.

Leptomeningeal carcinomatosis in a patient with recurrent unresectable squamous cell carcinoma of the retromolar trigone—a brief report

Background

The reported incidence of leptomeningeal carcinomatosis is 3–8% in patients with solid tumours. More commonly, it has been described in the setting of advanced cancers of the lung, breast and malignant melanoma.

Case presentation

A 50-year-old diabetic patient with recurrent unresectable squamous cell carcinoma (SCC) of the right retromolar trigone (rT4bN0M0) presented with severe low backache and weakness in bilateral lower limbs 20 days after the completion of concurrent chemoradiotherapy. Contrast-enhanced MRI of the spine showed multiple nodular enhancing leptomeningeal lesions at the lumbar level and an intramedullary T2/FLAIR-hyperintense longitudinal lesion involving the central cord from C2 to C7 vertebral levels, suggestive of leptomeningeal metastases. Cerebrospinal fluid (CSF) analysis revealed pleocytosis, elevated protein and markedly decreased glucose. The CSF cytology revealed scattered large atypical cells, suspicious for metastasis. Non-contrast MRI of the brain showed a T2/FLAIR-hyperintense lesion involving the right caudate nucleus suggestive of either an acute infarct with haemorrhagic transformation or a haemorrhagic brain metastasis. During assessment, he had high-grade fever and was started on empirical intravenous antibiotics (ceftriaxone, vancomycin and subsequently meropenem) in line with the management for acute bacterial meningitis. Gram staining of CSF did not demonstrate the presence of any bacteria and the specimen was sterile on culture. He did not respond to empirical antibiotics, had a progressive downhill course and eventually died due to aspiration pneumonia.

Conclusion

This brief report highlights the importance of awareness of leptomeningeal carcinomatosis as a possible cause of backache with sensorimotor deficit and autonomic dysfunction in a previously treated case of head and neck SCC.

Effects of Red Blood Cell Transfusions on Distant Metastases of Oral Squamous Cell Carcinomas

Simple Summary

Patients with distant metastasis of oral squamous cell carcinoma should be identified at an early stage of disease. In this study, we investigated if patients who received red blood cell transfusions are at risk for the development of distant metastasis. A positive correlation was found between RBC transfusion (HR = 2.42) and the occurrence of M+ in a multivariate regression model. Therefore, the administration of RBC can be considered as an independent prognostic factor and special attention should be paid to its detrimental effects in the perioperative management of OSCC patients.

Abstract

There is no consensus on the effect of red blood cell (RBC) transfusions on patients with oral squamous cell carcinoma (OSCC). The aim of this study was to investigate the association between RBC administration and the occurrence of distant metastases (M+) after surgical treatment of OSCC. All medical records of patients who underwent primary surgery for OSCC in our department (2003–2019) were analyzed retrospectively (n = 609). Chi and Cox regression models were used to analyze the influence of transfusion on the development of M+, and survival rates. Kaplan–Meier curves were used for graphical presentation. A multitude of patient-specific factors showed a statistical impact in univariate analysis (transfusion, age, gender, diabetes, pT, pN, L, V, Pn, G, UICC, adjuvant therapy, free microvascular transplant, preoperative hemoglobin level). Transfusion status and pN stage were the only variables that showed a significant correlation to M+ in the multivariate Cox model. The hazard ratios for the occurrence of M+ were 2.42 for RBC transfusions and 2.99 for pN+. Administration of RBC transfusions was identified as a significant prognostic parameter for the occurrence of distant metastases after surgical treatment of OSCC. Hence, the administration of RBC transfusions should be considered carefully in the perioperative management.

Kinase Inhibitors of DNA-PK, ATM and ATR in Combination with Ionizing Radiation Can Increase Tumor Cell Death in HNSCC Cells While Sparing Normal Tissue Cells

(1) Kinase inhibitors (KI) targeting components of the DNA damage repair pathway are a promising new type of drug. Combining them with ionizing radiation therapy (IR), which is commonly used for treatment of head and neck tumors, could improve tumor control, but could also increase negative side effects on surrounding normal tissue. (2) The effect of KI of the DDR (ATMi: AZD0156; ATRi: VE-822, dual DNA-PKi/mTORi: CC-115) in combination with IR on HPV-positive and HPV-negative HNSCC and healthy skin cells was analyzed. Cell death and cell cycle arrest were determined using flow cytometry. Additionally, clonogenic survival and migration were analyzed. (3) Studied HNSCC cell lines reacted differently to DDRi. An increase in cell death for all of the malignant cells could be observed when combining IR and KI. Healthy fibroblasts were not affected by simultaneous treatment. Migration was partially impaired. Influence on the cell cycle varied between the cell lines and inhibitors; (4) In conclusion, a combination of DDRi with IR could be feasible for patients with HNSCC. Side effects on healthy cells are expected to be limited to normal radiation-induced response. Formation of metastases could be decreased because cell migration is impaired partially. The treatment outcome for HPV-negative tumors tends to be improved by combined treatment.

ECM Remodeling in Squamous Cell Carcinoma of the Aerodigestive Tract: Pathways for Cancer Dissemination and Emerging Biomarkers

Squamous cell carcinomas (SCC) include a number of different types of tumors developing in the skin, in hollow organs, as well as the upper aerodigestive tract (UADT) including the head and neck region and the esophagus which will be dealt with in this review. These tumors are often refractory to current therapeutic approaches with poor patient outcome. The most important prognostic determinant of SCC tumors is the presence of distant metastasis, significantly correlating with low patient survival rates. Rapidly emerging evidence indicate that the extracellular matrix (ECM) composition and remodeling profoundly affect SSC metastatic dissemination. In this review, we will summarize the current knowledge on the role of ECM and its remodeling enzymes in affecting the growth and dissemination of UADT SCC. Taken together, these published evidence suggest that a thorough analysis of the ECM composition in the UADT SCC microenvironment may help disclosing the mechanism of resistance to the treatments and help defining possible targets for clinical intervention.

ECM Remodeling in Squamous Cell Carcinoma of the Aerodigestive Tract: Pathways for Cancer Dissemination and Emerging Biomarkers

Simple Summary

Local and distant metastasis of patients affected by squamous cell carcinoma of the upper aerodigestive tract predicts poor prognosis. In the latest years, the introduction of new therapeutic approaches, including targeted and immune therapies, has improved the overall survival. However, a large number of these patients do not benefit from these treatments. Thus, the identification of suitable prognostic and predictive biomarkers, as well as the discovery of new therapeutic targets have emerged as a crucial clinical need. In this context, the extracellular matrix represents a suitable target for the development of such therapeutic tools. In fact, the extracellular matrix is composed by complex molecules able to interact with a plethora of receptors and growth factors, thus modulating the dynamic crosstalk between cancer cells and the tumor microenvironment. In this review, we summarize the current knowledge of the role of the extracellular matrix in affecting squamous cell carcinoma growth and dissemination. Despite extracellular matrix is known to affect the development of many cancer types, only a restricted number of these molecules have been recognized to impact on squamous cell carcinoma progression. Thus, we consider that a thorough analysis of these molecules may be key to develop new potential therapeutic targets/biomarkers.

Abstract

Squamous cell carcinomas (SCC) include a number of different types of tumors developing in the skin, in hollow organs, as well as the upper aerodigestive tract (UADT) including the head and neck region and the esophagus which will be dealt with in this review. These tumors are often refractory to current therapeutic approaches with poor patient outcome. The most important prognostic determinant of SCC tumors is the presence of distant metastasis, significantly correlating with low patient survival rates. Rapidly emerging evidence indicate that the extracellular matrix (ECM) composition and remodeling profoundly affect SSC metastatic dissemination. In this review, we will summarize the current knowledge on the role of ECM and its remodeling enzymes in affecting the growth and dissemination of UADT SCC. Taken together, these published evidence suggest that a thorough analysis of the ECM composition in the UADT SCC microenvironment may help disclosing the mechanism of resistance to the treatments and help defining possible targets for clinical intervention.

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

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.