BACKGROUND:Epidemiological evidence regarding the association between long-term air pollution exposures and esophageal cancer is limited and controversial. This study aims to investigate this association further and assess its impact on different histological subtypes of esophageal cancer. METHODS:Data from the UK Biobank cohort, which included 444,932 participants, was utilized for this study. High-resolution 1 × 1 km data from the UK's Department for Environment, Food and Rural Affairs was used to estimate annual concentrations of air pollutants based on participants' residential addresses. The Time-Dependent Cox proportional hazard model was employed to estimate the hazard ratios (HRs) and 95 % confidence intervals (CIs) for the incidence of esophageal cancer associated with air pollutant exposure. RESULT:Over a follow-up duration of 4,777,149 person-years, 1008 new esophageal cancer cases were observed. No association between PM2.5 and PM10 exposure and esophageal cancer was found. However, long-term exposure to NO2, NOx, SO2 and benzene demonstrated a linear relationship with the risk of esophageal cancer incidence. The HRs were 1.278 (95 % CI: 1.104-1.480) per 10 μg/m3 for NO2, 1.129 (95 % CI: 1.046-1.218) per 10 μg/m3 for NOx, 1.109 (95 % CI: 1.041-1.182) per 1 μg/m3 for SO2 and 1.086 (95 % CI: 1.010-1.167) per 0.1 μg/m3 for benzene, respectively. No statistically significant heterogeneity was detected between the histological subtypes of squamous cell carcinoma and adenocarcinoma. Elderly individuals were more vulnerable to nitrogen oxides, while smokers or former smokers were more susceptible to the effects of sulfur dioxide. CONCLUSION:Long-term exposure to air pollutants may significantly increase the risk of esophageal cancer. Effective and targeted control of ambient air pollutant concentrations could potentially reduce the disease burden of esophageal cancer.

BACKGROUND:Concurrent chemo-radiotherapy (CCRT) is the standard treatment for locally advanced cervical cancer (LACC), but there are still many patients who suffer tumor recurrence. However, valuable predictors of treatment outcomes remain limited. This study aimed to assess the value of the serum immune biomarkers to predict the prognosis. METHODS:We reviewed cervical cancer patients treated with CCRT between January 2014 and May 2018 at Peking Union Medical College Hospital. The systemic immune inflammation index (SII), systemic inflammation response index (SIRI), and lactate dehydrogenase (LDH) were calculated using blood samples. The relationship between immune markers and the treatment outcome was analyzed. The area under the receiver operating characteristic (ROC) curve was used to evaluate the predictive efficiency. The Cox proportional hazards model and log-rank were used to predict overall survival (OS) and disease-free survival (DFS). RESULTS:This study included 667 patients. Among them, 195 (29.2%) patients were defined as treatment failure, including 127 (19.0%) patients with pelvic failure, 94 (14.1%) distant failure, and 25 (3.7%) concurrent pelvic and distant failure. It revealed that the tumor stage, size, metastatic lymph nodes (MLNs), and serum immune biomarkers, such as SII, SIRI, and LDH, were significantly related to treatment outcomes. We demonstrated that the optimal cut-off of the SII, SIRI, and LDH were 970.4 × 10 9 /L, 1.3 × 10 9 /L, and 207.52 U/L, respectively. Importantly, this study presented that LDH level had the highest OR (OR = 4.2; 95% CI [2.3-10.8]). Furthermore, the OS and DFS for patients with pre-SII ≥970.5 × 10 9 /L were significantly worse than those with pre-SII <970.5 × 10 9 /L. Similarly, pre-SIRI ≥1.25 × 10 9 /L and pre-LDH ≥207.5 U/L were related to poor survival outcomes. CONCLUSIONS:This study demonstrated that the baseline SII, SIRI, and LDH levels can be used to accurately and effectively predict the treatment outcomes after CCRT and long-term prognosis. Our results may offer additional prognostic information in clinical, which helps to detect the potential recurrent metastasis in time.

Objective This study aims to assess the effectiveness of the Gradient Boosting (GB) algorithm on glioma prognosis prediction and to explore new predictive models for glioma patient survival after tumor resection. Methods A cohort of 776 glioma cases (WHO grades II–IV) between 2010 and 2017 was obtained. Clinical characteristics and biomarker information were reviewed. Subsequently, we constructed the conventional Cox survival model and three different supervised machine learning models, including support vector machine (SVM), random survival forest (RSF), Tree GB, and Component GB. Then, the model performance was compared with each other. At last, we also assessed the feature importance of models. Results The concordance indexes of the conventional survival model, SVM, RSF, Tree GB, and Component GB were 0.755, 0.787, 0.830, 0.837, and 0.840, respectively. All areas under the cumulative receiver operating characteristic curve of both GB models were above 0.800 at different survival times. Their calibration curves showed good calibration of survival prediction. Meanwhile, the analysis of feature importance revealed Karnofsky performance status, age, tumor subtype, extent of resection, and so on as crucial predictive factors. Conclusion Gradient Boosting models performed better in predicting glioma patient survival after tumor resection than other models.

A model for predicting the recurrence pattern of patients with locally advanced non-small cell lung cancer (LA-NSCLC) treated with chemoradiotherapy is of great importance for precision treatment. The present study analyzed whether the comprehensive quantitative values (CVs) of the fluorine-18(18F)-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) radiomic features and metastasis tumor volume (MTV) combined with clinical characteristics could predict the recurrence pattern of patients with LA-NSCLC treated with chemoradiotherapy. Patients with LA-NSCLC treated with chemoradiotherapy were divided into training and validation sets. The recurrence profile of each patient, including locoregional recurrence (LR), distant metastasis (DM) and both LR/DM were recorded. In the training set of patients, the primary tumor prior radiotherapy with 18F-FDG PET/CT and both primary tumors and lymph node metastasis were considered as the regions of interest (ROIs). The CVs of ROIs were calculated using principal component analysis. Additionally, MTVs were obtained from ROIs. The CVs, MTVs and the clinical characteristics of patients were subjected to aforementioned analysis. Furthermore, for the validation set of patients, the CVs and clinical characteristics of patients with LA-NSCLC were also subjected to logistic regression analysis and the area under the curve (AUC) values calculated. A total of 86 patients with LA-NSCLC were included in the analysis, including 59 and 27 patients in the training and validation sets of patients, respectively. The analysis revealed 22 and 12 cases with LR, 24 and 6 cases with DM and 13 and 9 cases with LR/DM in the training and validation sets of patients, respectively. Histological subtype, CV2-5 and CV3-4 were identified as independent variables in the logistic regression analysis (P<0.05). In addition, the AUC values for diagnosing LR, DM and LR/DM were 0.873, 0.711 and 0.826, and 0.675, 0.772 and 0.708 in the training and validation sets of patients, respectively. Overall, the results demonstrated that the spatial and metabolic heterogeneity quantitative values from the primary tumor combined with the histological subtype could predict the recurrence pattern of patients with LA-NSCLC treated with chemoradiotherapy.

Background The study purpose was to characterize the mycobiome and its associations with the expression of pathogenic genes in esophageal squamous cell carcinoma (ESCC). Methods Patients with primary ESCC were recruited from two central hospitals. We performed internal transcribed spacer 1 (ITS1) ribosomal DNA sequencing analysis. We compared differential fungi and explored the ecology of fungi and the interaction of bacteria and fungi. Results The mycobiota diversity was significantly different between tumors and tumor-adjacent samples. We further analysed the differences between the two groups, at the species level, confirming that Rhodotorula toruloides, Malassezia dermatis, Hanseniaspora lachancei, and Spegazzinia tessarthra were excessively colonized in the tumor samples, whereas Preussia persica, Fusarium solani, Nigrospora oryzae, Acremonium furcatum, Golovinomyces artemisiae, and Tausonia pullulans were significantly more abundant in tumor-adjacent samples. The fungal co-occurrence network in tumor-adjacent samples was larger and denser than that in tumors. Similarly, the more complex bacterial-fungal interactions in tumor-adjacent samples were also detected. The expression of mechanistic target of rapamycin kinase was positively correlated with the abundance of N. oryzae and T. pullulans in tumor-adjacent samples. In tumors, the expression of MET proto-oncogene, receptor tyrosine kinase (MET) had a negative correlation and a positive correlation with the abundance of R. toruloides and S. tessarthra, respectively. Conclusion This study revealed the landscape of the esophageal mycobiome characterized by an altered fungal composition and bacterial and fungal ecology in ESCC.

Background Esophageal microbiota may influence esophageal squamous cell carcinoma (ESCC) pathobiology. Therefore, we investigated the characteristics and interplay of the esophageal microbiota in ESCC. Methods We performed 16S ribosomal RNA sequencing on paired esophageal tumor and tumor-adjacent samples obtained from 120 primarily ESCC patients. Analyses were performed using quantitative insights into microbial 2 (QIIME2) and phylogenetic investigation of communities by reconstruction of unobserved states 2 (PICRUSt2). Species found to be associated with ESCC were validated using quantitative PCR. Results The microbial diversity and composition of ESCC tumor tissues significantly differed from tumor-adjacent tissues; this variation between subjects beta diversity is mainly explained by regions and sampling seasons. A total of 56 taxa were detected with differential abundance between the two groups, such as R. mucilaginosa , P. endodontalis , N. subflava , H. Pylori , A. Parahaemolyticus , and A. Rhizosphaerae . Quantitative PCR confirmed the enrichment of the species P. endodontalis and the reduction of H. Pylori in tumor-adjacent tissues. Compared with tumor tissue, a denser and more complex association network was formed in tumor-adjacent tissue. The above differential taxa, such as H. Pylori , an unclassified species in the genera Sphingomonas , Haemophilus , Phyllobacterium , and Campylobacter , also participated in both co-occurrence networks but played quite different roles. Most of the differentially abundant taxa in tumor-adjacent tissues were negatively associated with the epidermal growth factor receptor (EGFR), erb-b2 receptor tyrosine kinase 2 (ERBB2), erb-b2 receptor tyrosine kinase 4 (ERBB4), and fibroblast growth factor receptor 1 (FGFR1) signaling pathways, and positively associated with the MET proto-oncogene, receptor tyrosine kinase (MET) and phosphatase and tensin homolog (PTEN) signaling pathways in tumors. Conclusion Alterations in the microbial co-occurrence network and functional pathways in ESCC tissues may be involved in carcinogenesis and the maintenance of the local microenvironment for ESCC.

Background: Esophageal squamous cell carcinoma(ESCC) is severe cancer in the world. The role of esophageal microbiota for ESCC is still uncertain. In the current study, 120 paired tissues from ESCC patients were collected, and 16s rRNA sequencing was performed to explore the esophageal microbiota. Results: The present investigation shows that the diversity and composition of the microbiota in ESCC cancerous tissues and para-cancerous tissues is significantly different, this variation between subjects beta diversity mainly explained by regions and sampling seasons. Species R.Mucilaginosa, P.Endodontalis, unclassified species in genus Leptotrichia, genus Phyllobacterium, and genus Sphingomonas were enriched in cancerous tissue. On the other hand, class Bacilli, N.Subflava, H.Pylori, A.Parahaemolyticus, A.Rhizosphaerae, unclassified species in genus Campylobacter and genus Haemophilus were increased in para-cancerous tissue. Compared with the co-occurrence network in cancerous tissue, a denser and more complex association network was formed in para-cancerous tissue. Moreover, the above differential taxa also participated in both co-occurrence network but played quite different roles. Finally, the functional association analyses revealed the altered signaling pathways in ESCCs were correlated to esophageal microbiota. Conclusion: Compared with para-cancerous tissues, microbiota in cancerous tissues showed significant differences in diversity and composition. The alterations in microbial co-occurrence network and functional pathways in ESCC tissues may be involved in carcinogenesis and the maintenance of local microenvironment for ESCC. These discoveries of the esophageal microbiota for ESCC patients may contribute to the etiology for ESCC prevention, diagnosis, early intervention, and treatment.

Objective: To further explore risk factors of esophageal squamous cell cancer specific for different macroscopic types. Methods: A total of 423 patients and 423 age (+/- 3 years) and gender matched controls were recruited. Multinomial logistic regression and multivariable logistic regression analysis were used to evaluate the risk factors of ESCC specific for different macroscopic types. Results: In this study, we found that drinking hot tea (OR = 1.98, 95% CI:1.14-3.43) and higher intake of hard food (OR = 1.64, 95% CI:1.05-2.58) positively associated with ulcerative type of ESCC, but not with medullary type or other types. Although alcohol drinking and lower intake of fresh vegetable appeared to be more harmful to the ulcerative-type ESCC, the discrepant risks were not significantly different in ulcerative type and medullary type. Moreover, tobacco smoking, intake of hot food, spicy food, fresh fruit, scallion and garlic were related to ESCC risk, whereas no significant difference in magnitude of their associations with respect to macroscopic type was observed. Furthermore, significant multiplicative interaction between tobacco smoking and alcohol drinking was found in ulcerative-type and medullary-type ESCC. Conclusion: Drinking hot tea and higher intake of hard food were associated with increased risk of ulcerative type of ESCC. However, the mechanism for this difference needs to be further studied.

Lung cancer is the most common cause of cancer-related deaths worldwide. Pathologically, lung cancer can be non-small cell lung cancer (NSCLC) or small cell lung cancer (SCLC), while NSCLC accounts for approximately 85% of lung cancer patients. Stage III NSCLC represents a heterogeneous group of disease entities that are potentially curable and are usually dealt with multimodality treatments involving radiotherapy, chemotherapy, and surgical resection. Immune checkpoint inhibitors (ICIs) target programmed cell death receptor-1 (PD-1) and programmed death-ligand 1 (PD-L1). Studies have shown that ICIs have excellent and long-lasting anti-cancer effects in many cancers. The PACIFIC study is the first in the systemic treatment of stage III unresectable NSCLC in the past few decades that both progression-free survival (PFS) and overall survival (OS) have obtained positive results, However, the performance of this treatment strategy remains to be studied in a real-world setting. Such as who will benefit from treatment is still worthy of our continuous exp loration. In this paper, a patient with locally advanced unresectable NSCLC who underwent concurrent chemoradiotherapy followed by sequential immunotherapy (durvalumab) was reported. The patient obtained sustained clinical benefits despite low PD-L1 expression. This case report may serve as a reference for clinicians to make diagnostic and treatment decisions in clinical practice.

Abstract Background No previous study has investigated the association between oolong tea consumption and esophageal squamous cell carcinoma (ESCC), we aim to elucidate the association between oolong tea consumption and ESCC and its joint effects with a novel composite index. Methods In a hospital-based case-control study, 646 cases of ESCC patients and 646 sex and age matched controls were recruited. A composite index was calculated to evaluate the role of demographic characteristics and life exposure factors in ESCC. Unconditional logistic regression was used to calculate the point estimates between oolong tea consumption and risk of ESCC. Results No statistically significant association was found between oolong tea consumption and ESCC (OR = 1.39, 95% CI: 0.94–2.05). However, drinking hot oolong tea associated with increased risk of ESCC (OR = 1.60, 95% Cl: 1.06–2.41). Furthermore, drinking hot oolong tea increased ESCC risk in the high-risk group (composite index> 0.55) (OR = 3.14, 95% CI: 1.93–5.11), but not in the low-risk group (composite index≤0.55) (OR = 1.16, 95% CI: 0.74–1.83). Drinking warm oolong tea did not influence the risk of ESCC. Conclusions No association between oolong tea consumption and risk of ESCC were found, however, drinking hot oolong tea significantly increased the risk of ESCC, especially in high-risk populations.

Background Nasopharyngeal carcinoma (NPC) may be cured with radiation therapy. Tumor proximity to critical structures demands accuracy in tumor delineation to avoid toxicities from radiation therapy; however, tumor target contouring for head and neck radiation therapy is labor intensive and highly variable among radiation oncologists. Purpose To construct and validate an artificial intelligence (AI) contouring tool to automate primary gross tumor volume (GTV) contouring in patients with NPC. Materials and Methods In this retrospective study, MRI data sets covering the nasopharynx from 1021 patients (median age, 47 years; 751 male, 270 female) with NPC between September 2016 and September 2017 were collected and divided into training, validation, and testing cohorts of 715, 103, and 203 patients, respectively. GTV contours were delineated for 1021 patients and were defined by consensus of two experts. A three-dimensional convolutional neural network was applied to 818 training and validation MRI data sets to construct the AI tool, which was tested in 203 independent MRI data sets. Next, the AI tool was compared against eight qualified radiation oncologists in a multicenter evaluation by using a random sample of 20 test MRI examinations. The Wilcoxon matched-pairs signed rank test was used to compare the difference of Dice similarity coefficient (DSC) of pre- versus post-AI assistance. Results The AI-generated contours demonstrated a high level of accuracy when compared with ground truth contours at testing in 203 patients (DSC, 0.79; 2.0-mm difference in average surface distance). In multicenter evaluation, AI assistance improved contouring accuracy (five of eight oncologists had a higher median DSC after AI assistance; average median DSC, 0.74 vs 0.78; P < .001), reduced intra- and interobserver variation (by 36.4% and 54.5%, respectively), and reduced contouring time (by 39.4%). Conclusion The AI contouring tool improved primary gross tumor contouring accuracy of nasopharyngeal carcinoma, which could have a positive impact on tumor control and patient survival. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Chang in this issue.

Previous studies have recommended harvesting a large number of lymph nodes (LNs) to improve the survival of patients with esophageal squamous cell carcinoma (ESCC). These studies or clinical guidelines focus on the total harvested LNs during lymphadenectomy; however, the extent of LN dissection (LND) required in patients with ESCCs remains controversial. The present study proposed a novel individualized adequate LND (ALND) strategy to compliment current guidelines to improve individualized therapeutic efficacy. For N0 cases, ALND was defined as an LN harvest of >55% of the LNs from nodal zones adjacent to the tumor location; and for N+ cases, ALND was defined as 8, 8, 8, 8 or 16 LNs dissected from the involved cervical, upper, middle, lower and celiac zones, respectively. Retrospective analysis of the ESCC cohort revealed that the ALND was associated with improved patient survival [hazard ratio (HR)=0.45 and 95% CI=0.30-0.66)]. Stratified analyses revealed that the protective role of ALND was prominent, with the exception of higher pN(+) staged (pN2-3) cases (HR=0.52, 95% CI=0.23-1.18). Furthermore, ALND was associated with improved survival in local diseases (T1-3/N0-1; HR=0.50, 95% CI=0.30-0.84) and locally advanced diseases (T4/Nany or T1-3/N2-3; HR=0.32, 95% CI=0.15-0.68). These findings suggested that the proposed ALND strategy may effectively improve the survival of patients with ESCC.

BACKGROUND Recent studies have shown that some members of the tripartite motif-containing protein (TRIM) family function as important regulators in several tumors. However, the clinical significance of TRIM15 in gastric adenocarcinoma has not been elucidated. In the present study, we aimed to examine the expression pattern of TRIM15 and explore whether the TRIM15 expression is correlated with clinicopathological characteristics of patients with gastric adenocarcinoma. MATERIAL AND METHODS The expression pattern of TRIM15 was examined in gastric adenocarcinoma tissues and adjacent normal stomach tissues by using immunohistochemistry staining. The prognostic role of TRIM15 in gastric cancer patients was evaluated by univariate and multivariate analyses. Clinical outcomes were assessed by the Kaplan-Meier analysis and log-rank test. The effects of TRIM15 on cancer cell proliferation and invasion were tested through cellular experiments. RESULTS TRIM15 was highly expressed in normal stomach tissues compared to tumor tissues. TCGA database showed that higher TRIM15 RNA transcription indicates poorer overall survival of gastric cancer patients. Besides, low expression of TRIM15 was significantly associated with advanced tumor invasion depth and advanced TNM stage. Moreover, gastric cancer patients with lower KDM5B expression had poorer overall survival, and TRIM15 was identified as an independent prognosis factor according to multivariate analysis. Using the gastric cancer cell lines, we found that overexpression of TRIM15 can inhibits tumor cell invasion. CONCLUSIONS Our study demonstrated that low expression of TRIM15 in gastric adenocarcinoma tissues was significantly associated with poorer prognosis of patients, indicating the potential of TRIM15 as a novel clinical biomarker and therapeutic target.

Lymph node metastasis (LNM) is one of the major prognostic factors for esophageal squamous cell carcinoma (ESCC). However there is no consensus regarding the prognostic significance of the location of LNM. Therefore, a novel classification was proposed to identify the lymph node (LN) stations which may be useful in predicting prognosis. A total of 260 ESCC patients were enrolled in this prospective study. The prognostic values of LNM in different lymph node (LN) stations were evaluated by random survival forests (RSF). Their prognostic significance was examined by Cox regression and receiver operating characteristic curve (ROC). The three most frequently involved LN stations were station 16 (24.49%), station 1 (22.22%) and station 2 (21.05%). Stations 1, 2, 8M, 8L and 16 were grouped as dominant LN stations (DLNS) which showed higher values in predicting overall survival (OS) and disease-free survival (DFS) than the remaining LN stations, which we define as non-dominant LN stations (N-DLNS). LNM features of DLNS (number of positive LN stations, number of positive LNs and LN ratio), but not those from N-DLNS, served as independent prognostic factors (P<0.05) whenever used alone or when combined with factors from N-DLNS. Furthermore, the area under ROC indicated that DLNS is a more accurate prediction than N-DLNS (P<0.05). This study demonstrated the value of LNM in DLNS in predicting prognosis in surgical ESCC patients, which outperformed those from N-DLNS. Therefore, the method of dominant and non-dominant classification may serve as an additional parameter to improve individualized therapeutic strategies.