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Oral squamous cell carcinoma (OSCC) is the most common type of head and neck (H&N) cancers with an increasing worldwide incidence and a worsening prognosis. The abundance of tumour infiltrating lymphocytes (TILs) has been shown to be a key prognostic indicator in a range of cancers with emerging evidence of its role in OSCC progression and treatment response. However, the current methods of TIL analysis are subjective and open to variability in interpretation. An automated method for quantification of TIL abundance has the potential to facilitate better stratification and prognostication of oral cancer patients. We propose a novel method for objective quantification of TIL abundance in OSCC histology images. The proposed TIL abundance (TILAb) score is calculated by first segmenting the whole slide images (WSIs) into underlying tissue types (tumour, lymphocytes, etc.) and then quantifying the co-localization of lymphocytes and tumour areas in a novel fashion. We investigate the prognostic significance of TILAb score on digitized WSIs of Hematoxylin and Eosin (H&E) stained slides of OSCC patients. Our deep learning based tissue segmentation achieves high accuracy of 96.31%, which paves the way for reliable downstream analysis. We show that the TILAb score is a strong prognostic indicator ( p  = 0.0006) of disease free survival (DFS) on our OSCC test cohort. The automated TILAb score has a significantly higher prognostic value than the manual TIL score ( p  = 0.0024). In summary, the proposed TILAb score is a digital biomarker which is based on more accurate classification of tumour and lymphocytic regions, is motivated by the biological definition of TILs as tumour infiltrating lymphocytes, with the added advantages of objective and reproducible quantification.

Esophageal cancer (EC) is an aggressive malignancy with an increasing incidence and a poor prognosis. EC is histologically divided into two major categories: adenocarcinoma (EAC) and squamous cell carcinoma (ESCC). EAC and ESCC are molecularly different and therefore treatments should reflect the respective histological subtype. Combined modality therapy is needed for localized EC. When EC is advanced (stage 4), systemic therapy is the mainstay treatment for palliation. For localized EC, several strategies are considered standard, and more trials are necessary to determine a unified and more effective approach. The management for advanced EC is slowly evolving as immunotherapy is showing some promise for ESCC, but more data from ongoing studies are anticipated. Treatment advances will be based on high-definition genomic investigation of individual tumors. Herein, we review the contemporary trends in diagnosing and treating EAC and ESCC.

Patients with head and neck squamous cell carcinoma (HNSCC) are at a high risk of developing recurrence and secondary cancers. This study evaluates the prognostic and surveillance utilities of circulating tumour cells (CTCs) in HNSCC. A total of 154 HNSCC patients were recruited and followed up for 4.5 years. Blood samples were collected at baseline and follow-up. CTCs were isolated using a spiral microfluid device. Recurrence and death due to cancer were assessed during the follow-up period. In patients with HNSCC, the presence of CTCs at baseline was a predictor of recurrence (OR = 8.40, p  < 0.0001) and death (OR= ∞, p  < 0.0001). Patients with CTCs at baseline had poor survival outcomes ( p  < 0.0001). Additionally, our study found that patients with CTCs in a follow-up appointment were 2.5 times more likely to experience recurrence or death from HNSCC ( p  < 0.05) prior to their next clinical visit. Our study highlights the prognostic and monitoring utilities of CTCs’ in HNSCC patients. Early identification of CTCs facilitates precise risk assessment, guiding treatment choices and ultimately enhancing patient outcomes.

Gastric cardia adenocarcinoma (GCA) and esophageal squamous cell carcinoma (ESCC) present significant health challenges in China, often diagnosed at advanced stages with poor prognoses. However, effective biomarkers for early detection remain elusive. This study aimed to integrate methylome and transcriptome data to identify DNA methylation markers for the early detection of GCA and ESCC. In the discovery stage, we conducted Infinium MethylationEPIC array analysis on 36 paired GCA and non-tumor adjacent tissues (NAT), identifying differentially methylated CpG sites (DMCs) between GCA/ESCC and NAT through combined analyses of in-house and publicly available data. In the validation stage, targeted pyrosequencing and quantitative real-time RT-PCR were performed on paired tumor and NAT samples from 50 GCA and 50 ESCC patients. In the application stage, an independent set of 438 samples, including GCA, ESCC, high- and low-grade dysplasia (HGD/LGD), and normal controls, was tested for selected DMCs using pyrosequencing. Our analysis validated three GCA-specific, two ESCC-specific, and one tumor-shared DMCs, exhibiting significant hypermethylation and decreased expression of target genes in tumor samples compared with NAT. Leveraging these DMCs, we developed a GCA-specific 4-marker panel (cg27284428, cg11798358, cg07880787, and cg00585116) with an area under the receiver operating characteristic curve (AUC) of 0.917, effectively distinguishing between cardia HGD/GCA patients and cardia LGD/normal controls. Similarly, an ESCC-specific 3-marker panel (cg14633892, cg04415798, and cg00585116) achieved an AUC of 0.865 in distinguishing esophageal HGD/ESCC cases. Furthermore, integrating cg00585116, age, and alcohol consumption yielded a tumor-shared logistic model with good discrimination for two cancer/HGD (AUC, 0.767; 95% confidence interval, 0.720–0.813). The mean AUC of the model after 5-fold cross-validation was 0.764. In summary, our study identifies novel DNA methylation markers capable of accurately distinguishing GCA/ESCC and HGD from LGD and normal controls. These findings offer promising prospects for targeted DNA methylation assays in future minimally invasive cancer screening methods.

Imbalance of oral salivary microbiota has been linked to the pathogenesis of a variety of systemic diseases, and oral bacterial species have been shown to be useful biomarkers for systemic diseases.This study aimed to characterize the alterations of oral microbiota in patients with esophageal squamous cell carcinoma (ESCC) and to evaluate the diagnostic performance of oral microbial biomarkers for ESCC. The relative abundance of flora in saliva samples was analyzed by 16S rDNA sequencing, and differences in the species present in samples from ESCC patients and healthy controls (HCs) were identified by analyzing species diversity and performing LEfSe analysis. Receiver operating characteristic (ROC) curve analysis was applied to evaluate the diagnostic performance of the characteristic bacteria individually and in combination. Differences in bacterial diversity indexes were observed for the saliva of ESCC patients versus HCs ( <0.05), but principal coordinate analysis did not detect a significant difference in the composition of oral microbiota between ESCC patients and HCs ( >0.05). LEfSe analysis showed that , , , , and were more abundant in ESCC patient saliva than in HC saliva, whereas ( ), ( ), , and were significantly less abundant in ESCC patient saliva ( <0.05). From ROC curve analysis, could detect ESCC with an area under the ROC curve (AUC) of 0.599, sensitivity of 62.2%, and specificity of 70%, whereas the ratio of had an AUC of 0.791, sensitivity of 93.3%, and specificity of 62.3%. Moreover, the combination of the and ratios showed further improved diagnostic performance for ESCC (AUC=0.826) and even good sensitivity and specificity for the diagnosis of early ESCC (68.2% and 86%, respectively; AUC=0.786). This study shows that in saliva can be used as a characteristic marker of ESCC, and the ratios of and offered significantly improved diagnostic performance, especially for early ESCC.

[...]this study summarized indicative genera associated with ESCC progression in paired esophageal biopsy and swab specimens, and developed risk stratification models of high-risk populations based on microbial factors, epidemiological factors, and actual detection requirements. [...]we developed risk stratification models of ESCC and precancerous lesions based on multinomial logistic regression and plotted the receiver operator characteristic (ROC) curve with the area under the curve (AUC). According to the results of the present study, significant differences were observed in age, education level, oral health (gingival bleeding), and dietary habits (drinking water, meat, fried food and scallion, ginger, or garlic) among the normal, esophagitis, LGIN, HGIN, and ESCC groups. [...]the highest accuracy of the risk stratification models for each detection requirement were 68.09% (model_1-adding tooth

PurposeCancer stem cells (CSCs) are held accountable for the progress of head and neck squamous cell carcinoma (HNSCC). In the presented study, the authors evaluated the prognostic value of CSC markers in two particular HNSCC cohorts.MethodsThis two cohort study consisted of 85 patients with advanced stage HNSCC, treated with primary radio(chemo)therapy (pRCT), and 95 patients with HNSCC, treated with surgery and partially adjuvant radio(chemo)therapy. Overall survival (OS), disease-free survival (DFS), and disease-specific survival (DSS) were assessed. Samples were assessed for the expression of different molecular stem cell markers (ALDH1, BCL11B, BMI‑1, and CD44).ResultsIn the pRCT cohort, none of the baseline patient and tumor features exhibited a statistically significant relation with survival in either the cohort or the human papillomavirus (HPV)-stratified subcohorts. High expression of BMI‑1 significantly decreased OS and DFS, while high expression of CD44 decreased all modes of survival. Multivariate analysis showed significant prognostic influence for all tested CSC markers, with high BMI‑1 and CD44 decreasing survival (BMI-1: OS, DFS, DSS; CD44: OS, DFS) and high ALDH1 and BCL11B showing a beneficial effect on survival (ALDH1: OS, DFS; BCL11B: OS, DSS). In the surgical cohort, classical prognosticators such as HPV status, R1 resection, and nodal status in HPV-negative HNSCC played a significant role, but the tested CSC markers showed no significant effect on prognosis.ConclusionAlthough validation in independent cohorts is still needed, testing for CSC markers in patients with advanced or late stage HNSCC might be beneficial, especially if many comorbidities exist or disease is irresectable. The findings might guide the development and earlier use of targeted therapies in the future.

Background Early diagnosis and treatment of esophageal squamous cell dysplasia (ESCdys) and esophageal squamous cell carcinoma (ESCC) could significantly reduce the incidence and mortality of ESCC. This pilot study aimed to investigate whether P16/CDKN2A methylation could serve as a cytologic biomarker for early detection of ESCdys and ESCC. Methods Paired esophageal biopsy and cytology specimens (exfoliated cells) were obtained from subjects at different stages of ESCC development. The methylation status of P16 gene in these two specimen types was determined using a 115‐bp MethyLight assay. Categorical data were compared by the Chi‐square test. Logistic regression was performed to assess adjusted odds ratios of P16 methylation associated with ESCC and ESCdys. Prediction models for identifying individuals at risk of ESCC and high‐grade ESCdys (high‐grade intraepithelial neoplasia, HGIN) were developed by multivariable logistic regression. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis. Internal validation of the prediction models was performed using the 1000‐bootstrap resample. Results A total of 105 subjects with diagnoses ranging from normal mucosa through ESCC were included in this study. An increase in P16 methylation frequency was observed with increasing severity of esophageal lesions (p for trend <0.001). In the adjusted logistic regression models, P16 methylation in cytology specimens was positively associated with ESCC and ESCdys risk, whereas P16 methylation in biopsy specimens was only associated with a higher risk of developing ESCC. The predictive capacity of base model I (AUC, 0.816) for ESCC and HGIN was significantly increased by adding P16 methylation in cytology specimens (model III; AUC, 0.882; p = 0.043), but not P16 methylation in biopsy specimens (model II; AUC, 0.850; p = 0.225). Bootstrap validation showed optimism‐corrected AUC of 0.789 for model I, 0.822 for model II, and 0.854 for model III. Conclusion P16 methylation as a cytologic marker was associated with the ESCC development and has the potential for application in minimally invasive ESCC screening. P16 methylation as a cytologic marker has the potential for application in minimally invasive screening for esophageal squamous cell carcinoma.